Journal Vol – 15 No -8, August 2020

Abstract:

This paper presents the influence of cycling impact loading and temperature on dynamic crack propagation in thin plates for two types of aluminum plates (7075, 6061) with aspect ratio (1.5,2) and plate boundary conditions (CSCS& SFSF). Using analytical solution and numerical analysis, crack lengths have (3, 5) mm and crack angle (45^o). Analytical solution using program (MATLAB-16), the purpose of analytical solution to get the mechanical and thermal stress with time at crack tip in thin aluminum plate, then calculate the dynamic crack propagation under the effect of these stresses. Numerical analysis using program (ANSYS-18 APDL) based on finite element method, the purpose of numerical analysis to obtain mechanical and thermal stress respect with time at the tip of the crack in thin aluminum plate, then calculate the dynamic crack propagation under the mechanical and thermal stresses effect. The results showed that the dynamic crack propagation increased as the crack length increased, and also found that the dynamic crack propagation decreased as the aspect ratio of the plate increased.

Keywords:

Stress,dynamic crack propagation,crack tip,analysis,plate,

Refference:

I E.E. Gdoutos, “Fracture Mechanics an Introduction”, 2005.
II James M. Gere, “Mechanics of Materials”, 2004.
III Hoai Nam Le, and Catherine Gardin, “Analytical calculation of the stress intensity factor in a surface cracked plate submitted to thermal fatigue loading”, Engineering Fracture Mechanics 77, PP.2354–2369, 2010.
IV Mahmut Uslu, Og˘uzhan Demir, and Ali O. Ayhan, “Surface Cracks in Finite Thickness Plates under Thermal and Displacement-Controlled loads – Part 1: Stress Intensity Factors”, Engineering Fracture Mechanics, Vol. 115, PP. 284–295, 2014.
V Katarina Maksimović, Dragi Stamenković, Mirko Maksimović, and Ivana Vasović, “Determination of Fracture Mechanics Parameters Structural Components with Surface Crack under Thermo mechanical Loads”,Scientific Technical Review, Vol.66, PP.27-33, No.3, 2016.
VI Shiwei Ge, Yafei Xu, Xiao Zhou, and Shangyu Peng, “Thermal Stress Analysis of a Continuous Rigid Frame Bridge”, Annals of Civil and Environmental Engineering, 2017.
VII T. K. Varadan and K. Bhaskar, “Analysis of Plates Theory and Problems”, Department of Aerospace Engineering, India Institution of Technology, Madras, India, 1999.
VIII F. Arace, “Simplified Models for the Analysis of Wave-Controlled Impacts”, 2005.
IX Loke Sworappa and R. Dharni, “Laminated Architectural Glass Subjected to Blast, Impact Loading”, 2005.
X L.S. Srinath, “Advanced Mechanics of Solid”,3rd Edition, McGraw-Hill, 2009.
XI M. Gosz, and B. Moram, “Stress Intensity Factors along Three Dimensional Elliptical Crack Fronts”, U. S. Department of Transportation, 1998.
XII L.L. Faulkner, “Practical Fracture Mechanics in Design”, Marcel Dekker, 2005.
XIII [59] M. Mir Zaei, “Fracture Mechanical Engineering”, TMU, 2000.
XIV Madenci, Erdogan, and Ibrahim Guven, “The finite element method and applications in engineering using ANSYS”. Springer, 2015.
XV Stolarski, Tadeusz, Yuji Nakasone, and Shigeka Yoshimoto, “Engineering analysis with ANSYS software”. Butterworth Heinemann, 2006.
XVI ANSYS Release 18.0 Documentation.
XVII ASM International Handbook, “Properties and Selection”, Vol.2, 1992.

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Abstract:

There has been challenging the pattern recognition that more attention needs to be paid to this area Offline Signature Verification (OSV), particularly when it is relied upon to popularize fully on the skillful frauds that are not accessible during the preparation. Its difficulties additionally incorporate little training tests and great intra-class divergence. At times the crude signature can incorporate additional pixel known as noises or may not be in the legitimate structure where preprocessing is obligatory. Insomuch as a signature is preprocessed accurately, it leads to a superior outcome for both signature matching and fraud disclosure.For example; an  appropriate estimation of gamma value improves the contrast of the signature image, on another hand, Pre-preparing likewise comprises binarization, noise elimination, so forth...The proposed method is for extraction features (such as ;Energy, Contrast, Entropy,and Correlation) from Offline Signature Verification System. In this paper, the data processing deals with twain parallel styles viz signature training and signature testing analysis. Insomuch as that the extracted features from a signature picture doesn't powerful, this will cause higher verification error rates particularly for skillful fabrications in hacking the system.The results show that’s the (UTSig) and the combination of (NISDCC, CEDAR, SigComp2012).Comparing with the other researches, the results in this Paper is the best and the system is more efficientwith (UTSig) signature which were 97%.

Keywords:

Offline Signature Verification,Insomuch,estimation of gamma value,twain parallel styles,UTSig,NISDCC,CEDAR,SigComp2012,

Refference:

I Ahmed, Z. J. (2018). Fingerprints Matching Using the Energy and Low Order Moment of Haar Wavelet Subbands. Journal of Theoretical and Applied Information Technology, 96(18), 6191–6202.

II AL-OBIADIE, S. N. M. (2016). Emotion Detection Using Facial Image Based on Geometric Attributes. University of Baghdad.

III Aldhaher, E., & George, L. (2014). Detection of Diabetic Maculopathy Using Image Analysis Techniques -Introduction and Implementation.

IV Eds, A. D. H. (2018). New Trends in Information and Communications Technology Applications (Vol. 938). https://doi.org/10.1007/978-3-030-01653-1

V Ellen, D., Day, S., & Davies, C. (2018). Scientific examination of documents: methods and techniques. CRC Press.

VI Fadhil, R., & George, L. E. (2017). Finger Vein Identification and Authentication System. LAP Lambert Academic Publishing.

VII Ferrer, M. A., Alonso, J. B., & Travieso, C. M. (2005). Offline geometric parameters for automatic signature verification using fixed-point arithmetic. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(6), 993–997.

VIII George, L. E., Al-Daamy, N., Al-Daamy, S. A., & Ahmed, R. K. (2016). The using of graylevel co-occurrence matrix for features extruction of the breast cancer biopcy image (glcm). Int. J. Engg. Res. and Sci. & Tech, 5(1).

IX Gunjal, S. N., Dange, B. J., & Brahmane, A. V. (2016). Offline Signature Verification using Feature Point Extraction. International Journal of Computer Applications, 975, 8887.

X Hafemann, L. G. (2019). Learning features for Offline Handwritten Signature Verification by MANUSCRIPT-BASED THESIS PRESENTED TO ÉCOLE DE IN PARTIAL FULFILLMENT FOR THE DEGREE OF.

XI Hamza, R. M., & Al-Assadi, T. A. (2012). Genetic algorithm to find optimalGLCM features. Department of Computer Science College of Information Technology.

XII HASSAN, E. K. H., GEORGE, L. E., & MOHAMMED, F. G. (2018). Color image compression based on DCT, differential pulse coding modulation, and adaptive shift coding. Journal of Theoretical and Applied Information Technology, 96(11), 3160–3171.

XIII Inamdar, V. S., Rege, P. P., & Arya, M. S. (2010). Offline Handwritten Signature based Blind Biometric Watermarking and Authetication Technique using Biorthogonal Wavelet Transform. International Journal of Computer Applications, 11(1), 19–27. https://doi.org/10.5120/1547-1970

XIV Jabur, Z. F., & Ali, S. K. (2014). Off line Handwritten Signature Recognition based on Fusion of Global and GLCM Features Using Fuzzy Logic. JOURNAL OF THI-QAR SCIENCE, 4(3), 151–158.

XV Karouni, A., Daya, B., & Bahlak, S. (2011). Offline signature recognition using neural networks approach. Procedia Computer Science, 3, 155–161.

XVI Kaur, H., & Kaur, S. (2014). Offline Hindi Signature Recognition Using Surf Feature Extraction and Neural Networks Approach. Ijsr. Net, 3(8), 1141–1146.

XVII Mahanta, L. B., & Deka, A. (2013). A study on handwritten signature. International Journal of Computer Applications, 79(2).

XVIII Mohammed, S. N., & George, L. E. (2016). Illumination-Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods. Current Journal of Applied Science and Technology, 1–13.

XIX Narwade, P. N., Sawant, R. R., & Bonde, S. V. (2018). Offline handwritten signature verification using cylindrical shape context. 3D Research, 9(4), 48.

XX Pirlo, G., Impedovo, D., Fairhurst, M., Pirlo, G., Impedovo, D., & Fairhurst, M. (2014). Advances in digital handwritten signature processing: a human artefact for e-society. World Scientific Publishing Co., Inc.

XXI Pratt, W. K. (1994). Digital Image Processing. In European Journal of Engineering Education (Vol. 19). https://doi.org/10.1080/03043799408928319

XXII Radhika, K. S., & Gopika, S. (2015). Online and offline signature verification: A combined approach. Procedia Computer Science, 46, 1593–1600. https://doi.org/10.1016/j.procs.2015.02.089

XXIII Rashidi, S., Fallah, A., & Towhidkhah, F. (2012). Feature extraction based DCT on dynamic signature verification. Scientia Iranica, 19(6), 1810–1819. https://doi.org/10.1016/j.scient.2012.05.007

XXIV Shakour, A. A. (2018). Biometric Authentication and Recognition System Using Hand Palm Images. Baghdad University.

XXV Sigari, M. H., Pourshahabi, M. R., & Pourreza, H. R. (2012). An ensemble classifier approach for static signature verification based on multi-resolution extracted features. International Journal of Signal Processing, Image Processing and Pattern Recognition, 5(1), 21–36.

XXVI Sindhu, B., & Jeeva, J. B. (2013). Automated Retinal Vessel Segmentation Using Morphological Operation And Threshold. International Journal of Scientific & Engineering Research, 4(5), 1614–1617. Retrieved from http://www.ijser.org

XXVII Soleimani, A., Araabi, B. N., & Fouladi, K. (2016). Deep Multitask Metric Learning for Offline Signature Verification. Pattern Recognition Letters, 80, 84–90. https://doi.org/10.1016/j.patrec.2016.05.023

XXVIII Soleimani, A., Fouladi, K., & Araabi, B. N. (2016a). Persian offline signature verification based on curvature and gradient histograms. 2016 6th International Conference on Computer and Knowledge Engineering (ICCKE), 147–152. IEEE.

XXIX Soleimani, A., Fouladi, K., & Araabi, B. N. (2016b). UTSig: A Persian offline signature dataset. IET Biometrics, 6(1), 1–8.

XXX Soleimani, A., Fouladi, K., & Araabi, B. N. (2017). UTSig: A Persian offline signature dataset. IET Biometrics, 6(1), 1–8. https://doi.org/10.1049/iet-bmt.2015.0058

XXXI Taylor, J. K., & Cihon, C. (2004). Statistical Techniques for Data Analysis. Retrieved from https://books.google.iq/books?id=yw6JwuAclCUC

XXXII Tuama, S. A., George, L. E., Okelola, M. O., Olabode, E. O., Mbah, E. N., Attah, A. J., … Sudharmaidevi, C. R. (2019). Current Research in Science and Technology Vol. 1. Current Research in Science and Technology Vol. 1, 1–17. https://doi.org/10.9734/bpi/crst/v1

XXXIII Tuama, S., & George, L. (2016). Retina Recognition Based on Texture Analysis: Building a system for individual recognition based on vasicular retina pattern.

XXXIV V.G., Y., & Patil, A. (2014). Offline and Online Signature Verification Systems: a Survey. International Journal of Research in Engineering and Technology, 3(3), 328–332.

XXXV Widiarti, A. R. (2011). Comparing Hilditch, Rosenfeld, Zhang-Suen, and Nagendraprasad-Wang-Gupta Thinning. International Journal of Computer and Information Engineering, 5(6), 563–567.

XXXVI Younesian, T., Masoudnia, S., Hosseini, R., & Araabi, B. N. (2019). Active Transfer Learning for Persian Offline Signature Verification. (February), 234–239. https://doi.org/10.1109/pria.2019.8786013

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Abstract:

Automatic License Recognition (ALPR) has been considered significant in many applications in intelligent transport and monitoring systems. As in other tasks of the computer vision, deep learning methods (DL) were implemented recently in the ALPR context, with a focus on country-specific Iraqi councils, like German or Old and Northern.  In this work, we proposed the DL-ALPR system from the beginning in the license plate detection phase of Iraqi plates according to the latest (YOLO) convolutional layers to detect single class. Utilizing a data set of Iraqi paintings collected by the researcher, and in the second stage, the detection plates are Recognition by extracting a set of license plate features using the SIFT and SURF algorithm, then using KNN to match the plates stored in the database to match them, the data is divided into two parts, part photos: 1300 pictures, And the second part, videos of the Iraqi vehicles in different environmental conditions, and the number is 35 videos. 1300 photos were divided 70% in the training phase and 30% in the testing phase and the results obtained in the testing phase were 99.2% for LP detection and 97.14% for recognition and the total accuracy of the system was 98.17%.

Keywords:

Automatic License Recognition,deep learning methods,Iraqi plates,SIFT and SURF algorithm,training phase,testing phase,

Refference:

I. A. Khazri, “Automatic License Plate Detection & Recognition using deep learning”, towards data science, 2019. web: https://towardsdatascience.com/automatic-license-plate-detection-recognition-using-deep-learning-624def07eaaf?gi=fc80f0526b7.

II. Saharkiz, “Nearest Neighbor Algorithm Implementation and Overview ” , Code project, 2009. Web: https://www.codeproject.com/Articles/32970/K-Nearest-Neighbor-Algorithm-Implementation-and-Ov.
III. D. Hoiem, Y. Chodpathumwan, Q. Dai, “Diagnosing Error in Object Detectors”, Computer Vision – ECCV, Springer Berlin Heidelberg, Berlin, Heidelberg, Vol. 1, No. 1, Pp. 340-353, 2012.
IV. H. Bay, T. Tuytelaars, L. Van Gool, “SURF: Speeded Up Robust Features”, Computer Vision – ECCV, Springer Berlin Heidelberg, Berlin, Heidelberg, Vol. 5, No. 1, Pp. 404-417, 2006.
V. H. A.-H. Kahdum, “Leukocytes Image Segmentation and Classification Based on Geometrical Features and Naïve Bayes Classifier,” Master Degree, College of Science, University of Baghdad, Baghdad – Iraq, 2019.
VI. Kusumadewi, C.A. Sari, E.H. Rachmawanto, “License Number Plate Recognition using Template Matching and Bounding Box Method”, Journal of Physics: Conference Series, IOP Publishing, Vol. 1, No. 1, Pp. 012067,2019.
VII. J. Kim, “Automatic Vehicle License Plate Extraction Using Region-Based Convolutional Neural Networks and Morphological Operations”, Symmetry, Vol. 11, No. 7, Pp. 882,2019.

VIII. J. Redmon, A. Farhadi, “YOLO9000: better, faster, stronger”, Proceedings of the IEEE conference on computer vision and pattern recognition, Vol. 1, No. 1, Pp. 7263-7271, 2017.

IX. J.T. Pedersen, “Study group SURF: Feature detection & description”, Department of Computer Science, Aarhus University, Pp. 1-12,2011

X. Mathew, Sheena S, “A Comparison of Sift And Surf Algorithm For The Recognition of An Efficient Iris Biometric System”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5, No. 1, Pp. 37–42, 2016.

XI. P. Marzuki, F. Radzi, Y.C. Wong, N. Abdul Hamid, N. Ali, M. Mat ibrahim, “A design of license plate recognition system using convolutional neural network”, International Journal of Electrical and Computer Engineering (IJECE), Vol. 9, No. 2196, Pp.2, 2019.

XII. R. Girshick, “Fast r-cnn”, Proceedings of the IEEE international conference on computer vision, Vol. 1, No. 1, Pp. 1440-1448, 2015.
XIII. S. Geethapriya, N. Duraimurugan, S. Chokkalingam, “Real-Time Object Detection with Yolo”, International Journal of Engineering and Advanced Technology (IJEAT), Vol. 8, No. 1, Pp. 1440-1448, 2019.

XIV. S. Geethapriya, N. Duraimurugan, S. Chokkalingam, “Real-Time Object Detection with Yolo”, International Journal of Engineering and Advanced Technology (IJEAT), Vol. 8, No. 1, Pp. 1440-1448, 2019.

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Abstract:

Intelligent access control is one of the challenging tasksin the human identification, image analysis, and diagnoses disease and computer vision. The focus towards the intelligent access control has been increased in the last years due to its various, applications in different   domains. For this reason, it was used intelligent access control to facilitate the task of identifying the human.The objective of this paper is to analyse and evaluate the seven techniques for the intelligent access control and advantage and disadvantage of each type. In addition, represents biometrics characteristics in general. The Biometric feature is used to determine human identity including the brain signals. Through this study, brain signals are the best among the techniques. In this study, we first presented a survey of the Computational intelligence techniques in biometrics. All previous studies used brain EEG signals. Where different algorithms were used to extract, the features. These feature applied for human identification. The Accuracy achieved was up to 97% according to the studies found in this research

Keywords:

Computational intelligence,human identification,Biometrics,Finger print,EEG signals,

Refference:

I. Acharya U Rajendra, Hagiwara Yuki, Deshpande Sunny Nitin, Suren S, Koh Joel En Wei, Oh Shu Lih, Arunkumar N Ciaccio Edward J, Lim Choo Min,” Characterization of focal EEG signals: a review”, Future Generation Computer Systems, vol 91, pp 290-299, 2019.
II. Ain Anil K, Nandakumar Karthik, Ross Arun, “50 years of biometric research: Accomplishments, challenges, and opportunities”, Pattern Recognition Letters, vol 79, pp 80-105, 2016.
III. Abhilash Kumar Sharma, Ashish Raghuwanshi, Vijay Kumar Sharma “Biometric System- A Review “, International Journal of Computer Science and Information Technologies, vol 6, no 5,pp 4616-4619, 2015.
IV. Arti B. Waghode, C A Manjare “Biometric Authentication of Person using finger knuckle” , International Conference on Computing, Communication, Control and Automation (ICCUBEA), pp 1-7, 2017.
V. Akshay Bapat and Vivek Kanhangad “Segmentation of hand from cluttered backgrounds for hand geometry biometrics, IEEE Region 10 Symposium (TENSYMP),pp 1- 4, 2017.
VI. Ajay Kumar, David CM Wong, Helen C Shen, and Anil K Jain “Personal verification using palm print and hand geometry biometric”, International Conference on Audio-and Video-Based Biometric Person Authentication, pp 668-678, 2003.
VII. Andrew Boles, Paul Rad,” Voice Biometrics: Deep Learning-based Voiceprint Authentication System ” 12th System of Systems Engineering Conference (SoSE), 2017.
VIII. Angadi, Shanmukhappa and Hatture, Sanjeevakumar “Hand geometry based user identification using minimal edge connected hand image graph”, IET Computer Vision, vol 12, no 5, pp 744-752, 2018.
IX. Angadi, S.A., Hatture, S.M.” Biometric person identification system: a multimodal approach employing spectral graph characteristics of hand geometry and palm print “, International Journal of Intelligent Systems and Applications, vol 8, no 3, 2016.
X. Abdulkareem, K.H., Mohammed, M.A., Gunasekaran, S.S., Al-Mhiqani, M.N., Mutlag, A.A., Mostafa, S.A., Ali, N.S. and Ibrahim, D.A “A Review of Fog Computing and Machine Learning” Concepts, Applications, Challenges, and Open Issues. IEEE Access, 7, pp.153123-153140, 2019.
XI. Abd Ghani, M.K., Mohammed, M.A., Arunkumar, N. et al. Decision-level fusion scheme for nasopharyngeal carcinoma identification using machine learning techniques. Neural Comput & Applic 32, 625–638 (2020). https://doi.org/10.1007/s00521-018-3882-6.
XII. Carmen Camara, Pedro Peris-Lopez, and Juan E. Tapiador “Human Identification Using Compressed ECG Signals” Avda. de la Universidad, 2015.

XIII. Connor, Patrick and Ross, Arun “Biometric recognition by gait: A survey of modalities and features, Computer Vision and Image Understanding”,vol 167, pp 1-27, 2018
XIV. Wang, Lei “Discovering phase transitions with unsupervised learning “, vol 94,pp 195-105, 2016.
XV. Champod Christophe, Lennard Chris J, Margot Pierre, Stoilovic Milutin, “Fingerprints and other ridge skin impressions”, 2017.
XVI. Dhillon, Parwinder Kaur and Kalra, Sheetal “A lightweight biometrics based remote user authentication scheme for IoT services “, Journal of Information Security and Applications,vol 34,pp 255-270,2017.
XVII. Emanuele Maiorana, Senior Member “Longitudinal Evaluation of EEG-based Biometric Recognition”, IEEE Transactions on Information Forensics and Security, vol. 13, no. 5, , pp 1123 – 1138, May 2018.
XVIII. Feng Lin, Kun Woo Cho, Chen Song, Wenyao Xu, Zhanpeng Jin : Brain Password: A Secure and Truly Cancelable Brain Biometrics for Smart Headwear, In Proc. Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services, pp 296-309, 2018.
XIX. Grm Klemen, truc, Vitomir, Artiges Anais, Caron Matthieu, Ekenel,: Strengths and weaknesses of deep learning models for face recognition against image degradations, Iet Biometrics, vol 7, no 1, , pp 81- 89, 2017.

XX. Guodong Guo,and Na Zhang” What is the Challenge for Deep Learning in Unconstrained Face Recognition? “, 13th IEEE International Conference on Automatic Face & Gesture Recognition, 2018.
XXI. Gupta Puneet, Gupta Phalguni “Multibiometric authentication system using slap fingerprints, palm dorsal vein, and hand geometry”, vol 65, no 12, pp 9777-9784, 2018
XXII. Geetika, Manavjeet Kaur “Fuzzy Vault with Iris and Retina: A Review” International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 4, April 2013.
XXIII. Hafemann Luiz G, Sabourin Robert, Oliveira Luiz S, “Offline handwritten signature verification—literature review ” , Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA),pp 1- 8 , 2017.
XXIV. Harakannanavar Sunil S, Puranikmath Veena I “Comparative survey of iris recognition”, International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), pp 280-283, 2017.
XXV. Israa M. Alsaadi, “Physiological Biometric Authentication Systems, Advantages, Disadvantages and Future Development: A Review: In proc, international journal of scientific and technology research, vol 4 issue 12, December 2015.
XXVI. Koike-Akino, T.; Mahajan, R.; Marks, T.K.; Tuzel, C.O.; Wang, Y.; Watanabe, S.; Orlik, P.V ” High-Accuracy User Identification Using EEG Biometrics”, pp 854-858, 2016.
XXVII. Khalaf, B.A., Mostafa, S.A., Mustapha, A., Mohammed, M.A. and Abduallah, W.M.. “Comprehensive review of artificial intelligence and statistical approaches in distributed denial of service attack and defence methods”. IEEE Access, 7, pp.51691-51713, 2019.
XXVIII. Lumini Alessandra, Nanni Loris “Overview of the combination of biometric matchers”, Information Fusion,vol 33,pp 71-85, 2017.
XXIX. M. Abo-Zahhad, Sabah M. Ahmed, Sherif N. Abbas ” A New EEG Acquisition Protocol for Biometric Identification Using Eye Blinking Signals “, International Journal of Intelligent Systems and Applications vol 7,no 6, 2015.
XXX. Madane Manisha, Thepade Sudeep, “Score level fusion based bimodal biometric identification using thepade’s sorted n-ary block truncation coding with varied proportions of iris and palmprint traits”, Procedia Computer Science vol 79, pp 466-473, 2016
XXXI. Ma, Lan and Minett, James W and Blu, Thierry and Wang, William SY “Resting state EEG-based biometrics for individual identification using convolutional neural networks”, pp 2848-2851, 2015.
XXXII. Mostafa, S.A., Mustapha, A., Hazeem, A.A., Khaleefah, S.H. and Mohammed, M.A.”. An agent-based inference engine for efficient and reliable automated car failure diagnosis assistance”. IEEE Access, 6, pp.8322-8331, 2018.
XXXIII. Mostafa, S.A., Mustapha, A., Mohammed, M.A., Hamed, R.I., Arunkumar, N., Ghani, M.K.A., Jaber, M.M. and Khaleefah, S.H.. “Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson’s disease”. Cognitive Systems Research, 54, pp.90-99, 2019.
XXXIV. M. Del Pozo-Banos, J. B. Alonso, J. R. Ticay-Rivas, and C. M. Travieso, “Electroencephalogram subject identification A review” Expert Systems With Applications, vol. 41, no. 15 Nov , pp 6537–6554, 2014.
XXXV. Mohammed, M.A., Ghani, M.K.A., Hamed, R.I. and Ibrahim, D.A”. Analysis of electronic methods for nasopharyngeal carcinoma: Prevalence, diagnosis,challenges and technologies. Journal of Computational Science, 21, pp.241-254, 2017.
XXXVI. Mehwish Leghari, Shahzad Memon, Asghar Ali Chandio,”Feature-Level Fusion of Fingerprint and Online Signature for Multimodal Biometrics”, International Conference on Computing, Mathematics and Engineering Technologies, 2018.
XXXVII. Mohammed, M.A., Al-Khateeb, B. and Ibrahim, D.A., 2016. Case based reasoning shell frameworkas decision support tool. Indian Journal of Science and Technology, 9(42), pp.1-8.
XXXVIII. Nguyen Kien, Fookes Clinton , Jillela Raghavender , Sridharan Sridha, Ross Arun,” Long range iris recognition A survey” , Pattern Recognition, vol 72 ,pp 123-143 , 2017.
XXXIX. Nanni, Loris Lumini Alessandra , Ferrara Matteo , Cappelli Raffaele ” Combining biometric matchers by means of machine learning and statistical approaches ” , Neurocomputing ,vol 149 , pp 526-535 , 2015.
XL. Nitin Kaushal and Purnima Kaushal “Human Identification and Fingerprints: A Review ” Journal of Biometrics & Biostatistics, vol 2,. ISSN:2155-6180 JBMBS, an open access journal,2011.
XLI. Ram K. Nawasalkar1, Harshal R. Lawange2, Surajkumar D. Gupta3, Pradeep K. Butey4 “Study of comparison of human bio-signals for emotion detection using HCI “, international journal of Emerging trends and technology in computer science (IJETTCS) April 2013.
XLII. Rajan Prasad Tripathi, Rhythem Goyal ” Finger Print recognition using biometric analysis and munutia features , In proc , Fourth International Conference on Image Information Processing (ICIIP), 2017.

XLIII. Shaymaa adnan Abdulrahman, Mohamed Roushdy, Abdel-Badeeh M. Salem,: “Support vector machine approach for human identification based on EEG signals, journal of mechanics of continua and mathematical sciences ,vol 15 , number 2, 2020.
XLIV. Sun Lichao, Wang, Yuqi, Cao Bokai, Philip S Yu, Srisa-An Witawas, Leow Alex D, ” Sequential keystroke behavioural biometrics for mobile user identification via multi-view deep learning” , Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pp 228-240,2017.
XLV. Shaymaa adnan Abdulrahman, Mohamed Roushdy, Abdel-Badeeh M. Salem, A “Survey of biometrics using electroencephalogram EEG” International Journal “Information Content and Processing”, Volume 6, Number 1, pp 18-32, 2019.
XLVI. Snyder David , Ghahremani Pegah , Povey Daniel , Garcia-Romero Daniel, Carmiel, Yishay, Khudanpur Sanjeev “Deep neural network-based speaker embeddings for end-to-end speaker verification” Spoken Language Technology Workshop (SLT) , pp 165-170 , 2016
XLVII. Tazwar Muttaqi, S. Hossein Mousavinezhad “User Identification System Using Biometrics Speaker Recognition by MFCC and DTW along with signal processing package” International Conference on Electro/Information Technology (EIT), 2018 .
XLVIII. Teddy Mantoro, Media A. Ayu, Suhendi.”Multi-Faces Recognition Process Using Haar Cascades and Eigenface Methods”, 6th International Conference on Multimedia Computing and Systems (ICMCS), 2018.
XLIX. Urmila Kalshetti, Akshay Goel, Prakhar Srivastava, Mayuri Ingole, Devika Bhide “Human Authentication from Brain EEG Signals using Machine Learning” International Journal of Pure and Applied Mathematics Vol 118, No. 24 , 2018.
L. Vikramaditya Agarwal, Akshay Sahai, Akshay Gupta, Nidhi Jain,: Human Identification and Verification based on Signature, Fingerprint and Iris Integration , In In Proc , 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO) , pp 46-461 , 2017.
LI. Wael Khalifa Kenneth Revett and Abdel Badeeh Salem “AIS Inspired Approach for User Identification Based on EEG Signals”, ISBN: 978-960-474-344-5, 2014.
LII. Wu, Changsheng and Ding, Wenbo and Liu, Ruiyuan and Wang, Jiyu and Wang, Aurelia C and Wang, Jie and Li, Shengming and Zi, Yunlong and Wang, Zhong Lin” Keystroke dynamics enabled authentication and identification using triboelectric nanogenerator array”, Materials Today, vol 21, no 3, pp 216-222, 2018.
LIII. Xiaoxiang Xu, Li Zhang, Fanzhang Li MSSVT “Multi-scale feature extraction for single face recognition”, 24th International Conference on Pattern Recognition (ICPR), August 2018 20-24.
LIV. Yasemin Bay, Meryem Erbilek, Ama Fosuah, Erbug Celebi “The Impact of Visual and Blind Signing on Signature Biometrics”, 9th International Conference on Computational Intelligence and Communication Networks, pp 161-164 , 2017
LV. Yap Hui-Yen, Choo Yun-Huoy, Khoh Wee-How, “Overview of acquisition protocol in EEG based recognition system”, International Conference on Brain Informatics, pp 129-138 , 2017.
LVI. Zhendong Mu: EEG Feature Extraction Based on Rough Set,3rd International Conference on Management, Education, Information and Control (MEICI), 2015.

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Abstract:

Life on the Earth exists because of atmosphere that surrounds it. As with the passage of time population increases and with this increases anthropogenic activities increases which is adversely affecting our atmosphere. That is why temperature of cities is soaring up. As our atmosphere is occupied by different gases, whose increase or decrease can substantially affects our environment. The major air pollutants, due to human activities, are carbon monoxide ), carbon dioxide ( ), nitrogen dioxide ( ), ozone ( ), sulfur dioxide ( ) and particulate matter ( ).Among these pollutants,  plays a big role as it can be produced due to road traffic and combustion of fossil fuels. In this paper, we investigated  in Pakistan troposphere through Sentinel-5 Precursor (S5-P) satellite. Data from the S5-P, with TROPO phosphoric Monitoring Instrument (TROPOMI) as payload, became available in July 2018, having spatial resolution nine times higher than that of OMI. S5-P launched by European Space Agency(ESA) with one-day revisit cycle, has the capability to sense all atmospheric gases. Our area of study is Pakistan. We processed S5-P datasets in Google Earth Engine(GEE) and produced results of four seasons, during 2018-2019, of . Different regions of Pakistan, which have excess in its troposphere, are also shown. This increase is supported by the fact that with time the increase in urban population causes dramatic negative effects on the atmosphere. Compared to traditional methods, this study will substantially increase the capability of the government and policy makers to take timely action on anthropogenic activities in mentioned cities, in order to mitigate emission of . Our findings illustrate the decrease of in summer, and surges in autumn and vice versa. In autumn Karachi, Sheikhupura, Raiwind, Lahore, Jamber, Faisalabad and Rawalpindi have highest concentration of  . In winter excess  spots over Karachi, Sheikhupura, Lahore, Raiwind, Jamber and Rawalpindi are detected. After winter, spring season shows further decrease in  concentration in which Karachi, Dera Ghazi Khan Sheikhupura, Rawalpindi and Lahore have highest  concentration and in summer in Pakistan troposphere is further reduced to Sheikhupura, Raiwind and Jamber cities.

Keywords:

Earth,Atmosphere,Urban Pollution,NO4,Google Earth Engine,Sentinel 5P,Omi,

Refference:

I. Abbasi, A., & Sardroodi, J. J. (2019). TiO2/graphene oxide heterostructures for gas-sensing: Interaction of nitrogen dioxide with the pristine and nitrogen modified nanostructures investigated by DFT. Surface Review and Letters, 26(04), 1850170.
II. Ahmad, K., Riegler, M., Pogorelov, K., Conci, N., Halvorsen, P., & De Natale, F. (2017). Jord: a system for collecting information and monitoring natural disasters by linking social media with satellite imagery. Paper presented at the Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing.
III. Ashraf, N., Mushtaq, M., Sultana, B., Iqbal, M., Ullah, I., & Shahid, S. A. (2013). Preliminary monitoring of tropospheric air quality of Lahore City in Pakistan. Sustainable Development, 3(1), 19-28.
IV. Beirle, S., Platt, U., Wenig, M., & Wagner, T. (2003). Weekly cycle of NO 2 by GOME measurements: A signature of anthropogenic sources. Atmospheric Chemistry and Physics, 3(6), 2225-2232.
V. Biresselioglu, M. E., Demir, M. H., Rashid, A., Solak, B., & Ozyorulmaz, E. (2019). What are the Preferences of Household Energy Use in Pakistan?: Findings from a National Survey. Energy and Buildings, 109538.
VI. Boersma, K. F., Jacob, D. J., Eskes, H. J., Pinder, R. W., Wang, J., & Van Der A, R. J. (2008). Intercomparison of SCIAMACHY and OMI tropospheric NO2 columns: Observing the diurnal evolution of chemistry and emissions from space. Journal of Geophysical Research: Atmospheres, 113(D16).
VII. DDT, I., & DDE, D. USA: US Environmental Protection Agency; 1998. US EPA Integrated Risk Information System. Silverplatter, 3.
VIII. Dong, Y., & Xu, L. (2019). Aggregate risk of reactive nitrogen under anthropogenic disturbance in the Pearl River Delta urban agglomeration. Journal of cleaner production, 211, 490-502.
IX. Ghude, S. D., Beig, G., Fadnavis, S., & Polade, S. (2009). Satellite derived trends in NO2 over the major global hotspot regions during the past decade and their inter-comparison. Environmental Pollution, 157(6), 1873-1878.
X. Ghude, S. D., Fadnavis, S., Beig, G., Polade, S., & Van Der A, R. (2008). Detection of surface emission hot spots, trends, and seasonal cycle from satellite‐retrieved NO2 over India. Journal of Geophysical Research: Atmospheres, 113(D20).
XI. Goldberg, D. L., Lu, Z., Streets, D. G., de Foy, B., Griffin, D., McLinden, C. A., . . . Eskes, H. (2019). Enhanced capabilities of TROPOMI NO2: Estimating NOx from North American cities and power plants. Environmental science & technology.
XII. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18-27.
XIII. Hvidtfeldt, U. A., Sørensen, M., Geels, C., Ketzel, M., Khan, J., Tjønneland, A., . . . Raaschou-Nielsen, O. (2019). Long-term residential exposure to PM2. 5, PM10, black carbon, NO2, and ozone and mortality in a Danish cohort. Environment international, 123, 265-272.
XIV. Ingmann, P., Veihelmann, B., Langen, J., Lamarre, D., Stark, H., & Courrèges-Lacoste, G. B. (2012). Requirements for the GMES Atmosphere Service and ESA’s implementation concept: Sentinels-4/-5 and-5p. Remote Sensing of Environment, 120, 58-69.
XV. Irizar, J., Melf, M., Bartsch, P., Koehler, J., Weiss, S., Greinacher, R., . . . Martin, D. (2019). Sentinel-5/UVNS. Paper presented at the International Conference on Space Optics—ICSO 2018.
XVI. Kaltenbaugh, A. D. (2019). Comparison of Satellite and Ground-Based NO2 Measurements in the Mid-Atlantic Region during the 2018 OWLETS-2 Campaign. Department of Atmospheric and Oceanic Science, University of Maryland
XVII. Kaplan, G., Avdan, Z. Y., & Avdan, U. (2019). Spaceborne Nitrogen Dioxide Observations from the Sentinel-5P TROPOMI over Turkey. Paper presented at the Multidisciplinary Digital Publishing Institute Proceedings.
XVIII. Lamsal, L., Martin, R., Van Donkelaar, A., Steinbacher, M., Celarier, E., Bucsela, E., . . . Pinto, J. (2008). Ground‐level nitrogen dioxide concentrations inferred from the satellite‐borne Ozone Monitoring Instrument. Journal of Geophysical Research: Atmospheres, 113(D16).
XIX. Liu, L., Zhang, X., Xu, W., Liu, X., Li, Y., Lu, X., . . . Zhang, W. (2017). Temporal characteristics of atmospheric ammonia and nitrogen dioxide over China based on emission data, satellite observations and atmospheric transport modeling since 1980. Atmospheric Chemistry and Physics, 17(15), 9365-9378.
XX. Mapes, B. E. (2001). Water’s two height scales: The moist adiabat and the radiative troposphere. Quarterly Journal of the Royal Meteorological Society, 127(577), 2353-2366.
XXI. Niaz, Y., Zhou, J., Iqbal, M., Nasir, A., & Dong, B. (2015). Ambient Air Quality Evaluation: A Comparative Study in China and Pakistan. Polish Journal of Environmental Studies, 24(4).
XXII. Richter, A., & Burrows, J. (2002). Tropospheric NO2 from GOME measurements. Advances in Space Research, 29(11), 1673-1683.
XXIII. Richter, A., Wittrock, F., Ladstätter-Weißenmayer, A., & Burrows, J. (2002). GOME measurements of stratospheric and tropospheric BrO. Advances in Space Research, 29(11), 1667-1672.
XXIV. Sharp, T. (2017). Earth’s Atmosphere: Composition, Climate & Weather. Space. com. Recuperado de> https://www. space. com/17683-earth-atmosphere. html.
XXV. Shen, L., Jacob, D. J., Liu, X., Huang, G., Li, K., Liao, H., & Wang, T. (2019). An evaluation of the ability of the Ozone Monitoring Instrument (OMI) to observe boundary layer ozone pollution across China: application to 2005–2017 ozone trends. Atmospheric Chemistry and Physics, 19(9), 6551-6560.
XXVI. Shon, Z.-H., Kim, K.-H., & Song, S.-K. (2011). Long-term trend in NO2 and NOx levels and their emission ratio in relation to road traffic activities in East Asia. Atmospheric environment, 45(18), 3120-3131.
XXVII. Tariq, S., & Ali, M. (2015). Tropospheric NO2 trends over South Asia during the last decade (2004–2014) using OMI data. Advances in Meteorology, 2015.
XXVIII. Tariq, S., Ali, M., Mahmood, K., Batool, S. A., & Rana, A. D. (2014). A study of tropospheric NO2 variability over Pakistan using OMI data. Atmospheric Pollution Research, 5(4), 709-720.
XXIX. Theys, N., Hedelt, P., De Smedt, I., Lerot, C., Yu, H., Vlietinck, J., . . . Fernandez, D. (2019). Global monitoring of volcanic SO 2 degassing with unprecedented resolution from TROPOMI onboard Sentinel-5 Precursor. Scientific reports, 9(1), 2643.
XXX. ul-Haq, Z., Tariq, S., Ali, M., Daud Rana, A., & Mahmood, K. (2017). Satellite-sensed tropospheric NO2 patterns and anomalies over Indus, Ganges, Brahmaputra, and Meghna river basins. International journal of remote sensing, 38(5), 1423-1450.
XXXI. Zheng, Z., Yang, Z., Wu, Z., & Marinello, F. (2019). Spatial Variation of NO2 and Its Impact Factors in China: An Application of Sentinel-5P Products. Remote Sensing, 11(16), 1939.

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Abstract:

The modern digital systems especially those dealing with enormous data consumption application are facing a very complicated problem of high latency in these memory access application. Latency seems to be a major hurdle in the performance of modern memory dependent systems as it experiences delay in the processing. This high latency depends upon too many factors especially applications involving memory access operation. Out of these major factors one is of the binding and allocation application. Number of different approaches in the recent past has adopted to optimize the high latency in memory access application. Yet the modern embedded system faces high latency still due to enormous data transfer. In our approach we focus to optimize the latency of modern digital system by dividing the memory into groups. Following by activating, the fourth coming commands in advance in idle slots of different memory modules. The approach is called slag time management. In our algorithm effective distribution of memory into modules activating the later command in advance is followed by the advance dynamic buffers for saving the most frequently access arrays in it.The proposed technique of dividing the memory into modules utilizing the memory management idle slot management in use of advance of dynamic buffers has significantly approved the overall of latency of

Keywords:

Array binding and allocation,Dynmic random-access memory (DRAM),effective sheduling,empty slots management,memory latency,multi-core processors on chip (MPSoC).,

Refference:

I. David Tawei Wang, “Modern DRAM Memory Systems: Performance Analysis and Scheduling Algorithm”, University of Maryland libraries,2005.
II. Fraboulet, G. Huard, A. Mignotte, “Loop Alignment for Memory Access Optimization”, 12th International Symposium on System Synthesis, 1999.
III. H. Shin, C. Kim, “A Simple Yet Effective Technique for Partitioning”, IEEE Transaction on Very Large Integration (VLSI) System, pp. 380- 386, 1993.
IV. J. I. Gomez, P. Marchal, S. Verdoorlaege, L. Pinuel, F. Catthoor, “Optimizing the Memory Bandwidth with Loop Morphing”, 15th IEEE International Conference on Application-Specific Systems, Architectures and Processors (ASAP’04), 2004.
V. N. Kim, R. Peng, “A memory Allocation and Assignment Method Using Multi-Way Partitioning”, IEEE International SoC Conference, 2004.
VI. Prince, Betty, “High Performance Memories: New Architecture DRAMs and SRAMs — Evolution and Function”, 1st edition, 1996.
VII. P. R. Panda, N. D. Dutt and A. Nicolau, “Incorporating DRAM Access Modes into High-Level Synthesis”, IEEE Transaction on Computer-Aided Design, Vol. 17, pp. 96-106,1998.
VIII. P. R. Panda, N. D. Dutt, A. Nicolau, “Exploiting Off-Chip Memory Access Modes in High-Level Synthesis”, International Conference on Computer-Aided Design (ICCAD ’97), 1997.
IX. P. R. Panda, F. Catthoor, N. D. Dutt, K. Danckaert, E. Brockmeyer, C. Kulkarni, A. Vandercappelle, and P. G. Kjeldsberg, “Data and Memory Optimization Techniques for Embedded Systems”, ACM Transaction Design Automation Electron System, Vol. 6, no. 2, pp. 149-206, 2001.
X. P. R. Panda, “Memory Bank Customization and Assignment in Behavioral Synthesis”, ICCAD, 1999.
XI. P. Marchal, J. I. Gomez, F. Catthoor, “Optimizing the Memory Bandwidth with Loop Fusion”, IEEE International Conference on Hardware/Software Codesign and System Synthesis (CODES + ISSS’04), 2004.
XII. S. Daud, H. shin, “Cycle Accurate Memory Delay Modeling for Off-Chip DRAMs”, System on Chip Conference, 2009.
XIII. S. J. E. Wilton and N. P. Jouppi, “CACTI: An Enhanced Cache Access and Cycle Time Model,” IEEE Journal of Solid state circuits, Vol. 31, pp. 667-688, 1996.
XIV. T. Kim, J. Kim, “Integration of Code Scheduling, Memory Allocation, and Array Binding for Memory Access Optimization”, IEEE Transaction on Computer Aided Design of Integrated circuits and systems, vol. 26, no. 1, pp. 142-151, 2007.
XV. T. Wada, S. Rajan, and S. A. Przbylski, “An Analytical Access Time Model for On-Chip Cache Memories”, IEEE Journal of Solid State circuits, Vol. 27, pp. 1147-1156, 1992.

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Abstract:

The Median Filter (MF) is one of the problems that need massive computational resources to perform its operation in a moderate time.  The MF can be implemented on traditional CPUs and GPUs.  Investigating the performance in terms of processing time of the MF on different architectures can provide the researchers with wider vision to optimally select the computational resources that best fit the required time needed to remove salt and pepper noise.  This paper shows the impact of different parameters affecting the MF processing time.  Resolution of the frame, frame rate per second, and the MF r value are investigated in order to decide both the preferred architecture and algorithm.  OpenMP has been deployed on CPUs and CUDA has been deployed on Nvidia GPGPU K20.  Experimental results show that histogram approach and K20 using CUDA are the best choice for processing 4K resolution with r > 2 and HD resolution with r > 4. For VGA resolution and r > 6, histogram approach and CPU using OpenMP are the best choice.  The paper provides a way to select the architecture-algorithm pair suitable for implementing the MF

Keywords:

CUDA,GPU,Histogram Approach,Median Filter,OpenMP ,

Refference:

I. C. M. Wu and Y. C. Chiang, “Insertion Sort Circuit Design Applied on the Median Filter,” in 2018 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2018, 2018.

II. D. S. Richards, “VLSI Median Filters,” IEEE Trans. Acoust., 1990.

III. G. Gupta, “Algorithm for Image Processing Using Improved Median Filter and Comparison of Mean, Median and Improved Median Filter,” Int. J. Soft Comput., 2011.

IV. H. M.Faheem and B. König-Ries, “A New Scheduling Strategy for Solving the Motif Finding Problem on Heterogeneous Architectures,” Int. J. Comput. Appl., 2014.

V. K. Verma, B. Kumar Singh, and A. S. Thokec, “An enhancement in adaptive median filter for edge preservation,” in Procedia Computer Science, 2015.

VI. L. Hayat, M. Fleury, and A. F. Clark, “Two-dimensional median filter algorithm for parallel reconfigurable computers,” IEE Proc. Vision, Image Signal Process., 1995.

VII. M. Fayez, H. M. Faheem, I. Katib, and N. R. Aljohani, “Real-time image scanning framework using GPGPU – Face detection case study,” in Proceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016, 2016.

VIII. M. Vega-Rodríguez and J. Sánchez-Pérez, “An FPGA-based implementation for median filter meeting the real-time requirements of automated visual inspection systems,” Proc. 10th IEEE Mediterr. Conf. Control Autom. (MED ’02), 2002.

IX. N. A. Sabour, H. M. Faheem, and M. E. Khalifa, “Multi-agent based framework for target tracking using a real time vision system,” in 2008 International Conference on Computer Engineering and Systems, ICCES 2008, 2008.

X. O. Green, “Efficient scalable median filtering using histogram-based operations,” IEEE Trans. Image Process., 2018.

XI. R. Medhat, H. M. Faheem, and M. E. Khaleefa, “Efficient parallel architecture of median filter,” in Proceedings of the 9th IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2010, 2010.

XII. S. Perreault and P. Hébert, “Median filtering in constant time,” IEEE Trans. Image Process., 2007.

XIII. Y. He, P. Liu, Z. Wang, Z. Hu, and Y. Yang, “Filter pruning via geometric median for deep convolutional neural networks acceleration,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2019.

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Abstract:

In the research article an energy optimization method for electrical hardware's utilizing IoTs and wireless sensor is introduced as the Vitality utilization has become one the serious issue in the advanced electrical gear's because of this framework execution is influenced and happens shifts misfortunes. The proposed design improves energy optimization, and decreases the energy utilization. The significant target is to gauge the temperature and lessen vitality utilization utilizing remotely organized IoT and Simulink ideal. The proposed algorithm find the primary destinations of the machine taskand to improve its execution time, and also figure out the temperature of gadget and balance out the temperature, by observing progressively, decreasing vitality utilization and make a vitality productive framework. The equipment is designed with MCU (controlling), single-channel transfer (for exchanging), DHT 11(humidity and temperature sensor),Ac to Dc conversion(adaptor). For the reproduction of the task, Arduino IDE programming is utilized forevery electricalequipment. We can control and schedule the energy utilization capacity through the cayenne web interface using wireless module (undefended source web space for interfacing of the microcontroller), we can switch the states if electrical gear concluded this mesh and fire acquire its outcome and work as indicated by the booking of the hardware. For air temperature sensor Matlab Simulink is used for displaying for gear's energy enhancement the technique decreases the energy consumption of individual equipment’s by 4% as compared to the previously used techniques.

Keywords:

Dynamic Power Management,Real-time systems,Multicore Architecture,IOTs,Wireless sensor network,

Refference:

I. C.-h. Hsu and W.-c. Feng, “A power-aware run-time system for high-performance computing,” in Proceedings of the 2005 ACM/IEEE conference e on Supercomputing. IEEE Computer Society,2005.

II. D. Silver, A. Huang, C.J. Maddison, A. Guez, L. Sifre, G. Van Den Driessche,J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, et al., Masteringthe game of Go with deep neural networks and tree search, Nature 529 (7587)(2016) 484–489.

III. D. Konar, K. Sharma, V. Sarogi and S. Bhattacharyya, “A Multi- Objective Quantum-Inspired Genetic Algorithm (Mo-QIGA) for Real-Time Tasks Scheduling in Multiprocessor Environment”, Procedia Computer Science, vol. 131, pp. 591-599, 2018.

IV. H. Khan, M. U. Hashmi, Z. Khan, R. Ahmad, and A. Saleem, Performance Evaluation for Secure DES-Algorithm Based Authentication & Counter Measures for Internet Mobile Host Protocol,” IJCSNS Int. J. Comput. Sci. Netw. Secur. VOL.18 No.12, December 2018, vol. 18, no. 12, pp. 181–185, 2018.

V. H. Khan, Q. Bashir, and M. U. Hashmi, “Scheduling based Energy Optimization Technique in multiprocessor Embedded Systems,” in 2018 International Conference on Engineering and Emerging Technologies (ICEET).doi:10.1109/iceet1.2018.8338643, 2018.

VI. H. Khan, S. Ahmad, N. Saleem, M. U. Hashmi, and Q. Bashir, “Scheduling Based Dynamic Power Management Technique for offline Optimization of Energy in Multi Core Processors,” Int. J. Sci. Eng. Res. Vol. 9, Issue 12, December-2018, vol. 9, no. 12, pp. 6–10, 2018.

VII. H. Khan, M. U. Hashmi, Z. Khan, and R. Ahmad, “Offline Earliest Deadline first Scheduling based Technique for Optimization of Energy using STORM in Homogeneous Multi- core Systems,” IJCSNS Int. J. Comput. Sci. Netw. Secur. VOL.18 No.12, December 2018, vol. 18, no. 12, pp. 125–130, 2018.

VIII. M. Bohr, R. Chau, T. Ghani, and K. Mistry, “The High- k Solution,” IEEE Spectrum, vol. 44, no. 10, pp. 29-35, Oct. 2007.

IX. N. Fathima, “Website: www.ijirset.com Energy Aware Dynam Slack Allocation for Multiprocessor System,” pp. 7476–7483, 2017.

X. P. Nayak and B. Vathasavai, “Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic,” in IEEE Sensors Journal, vol. 17, no. 14, pp. 4492-4499, 15 July15, 2017, doi: 10.1109/JSEN.2017.2711432.

XI. Q. Bashir, H. Khan, M. U. Hashmi, and S. Ali zamin, “A Survey on Scheduling Based Optimization Techniques in Multi-Processor Systems,” in Proceedings of the 3rd International Conference on Engineering & Emerging Technologies (ICEET), Superior University, Lahore, PK, 7-8 April, 2016., 2016.

XII. R. Ayoub, S. Sharifi and T. Rosing, “GentleCool: Cooling Aware -+ pages 295 – 298, 2010.

XIII. R. La Rosa, P. Livreri, C. Trigona, L. Di Donato, and G. Sorbello, “Strategies and techniques for powering wireless sensor nodes through energy harvesting and wireless power transfer,” Sensors (Switzerland), vol. 19, no. 12, 2019.

XIV. S. Shi, Q. Wang, P. Xu, X. Chu, Benchmarking state-of-the-art deep learning software tools, in: Proceedings of the 7th IEEE International Conference on Cloud Computing and Big Data, Macau, China, 2016.

XV. S. Kaxiras, Z. Hu, and M. Martonosi, “Cache Decay: Exploiting Generational Behavior to Reduce Cache Leakage Power,” Proc. Int’l Symp. Computer Architecture (ISCA ’01), pp. 240-251, 2001.

XVI. S. Yang, M. Powell, B. Falsafi, K. Roy, and T. Vijay kumar, “An Integrated Circuit/Architecture Approach to Reducing Leakage in Submicron High-PerformanceI-caches,” Proc. Seventh Int’l Symp. High- Performance Computer Architecture (HPCA’01), pp. 147-157, 2001.

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Abstract:

Artificial intelligence applications, including electronic games, have spread widely in our time among children and young people, and parents have suffered from the disruption of their children from them and the surrounding community due to sitting a lot with these applications and electronic games, especially in light of the pandemic of the Covid-19 virus, and children look at their interests, which leads to their addiction With the aim of developing their mental abilities while parents consider their interests to spend times and at the same time have many implications for achieving the goal of keeping the mind, and therefore the importance of research lies in clarifying how to preserve the mind through applications of artificial intelligence, interests and spoilers from electronic games and how to achieve them for the objective of keeping the mind, and research aims To define the objective of keeping the mind, artificial intelligence and electronic games, and to clarify its interests and spoils and how to bring interests and ward off evil through legitimate controls in order to achieve the objective of keeping the mind, the researcher used the analytical and critical inductive approach by collecting what related to the interests and spoils arising from the applications of artificial intelligence in electronic games on Achieve the intention of keeping the mind and its criticism and how to reduce spoilers by evil controls Consciousness, and the research consisted of preface and two researches, introducing the definition and legitimacy of the goal of mind keeping and artificial intelligence and electronic games, the first topic: the interests and spoils of artificial intelligence applications in electronic games to achieve the goal of keeping the mind, the second topic: legal controls for applications of artificial intelligence in electronic games to achieve a destination Preserving the mind, and a conclusion in it the most important results and recommendations, and the most important results are the importance of knowing the interests and spoils of the applications of artificial intelligence in electronic games and benefiting from these games in a way that achieves the objective of keeping the mind while working to increase its interests and ward off its corruption through the application of legal controls.

Keywords:

Objective for Keeping the Mind,Artificial Intelligence,Electronic Games,Objectives of Shariah,Covid-19,Electronic Education,

Refference:

I. Al-Mabsut Shams Al-Din Abu Bakr Muhammad Ibn Abi Sahl Al-Sarkhasi, Dar Al-Maarefa, Beirut, Dr. I, 1414 AH, 1993 AD

II. Aoun Al-Maabbood and Haasiyah Ibn Al-Qayyim Muhammad Shams Al-Haqq Al-Azim Abadi Abu Al-Tayeb, Dar Al-Kutub Al-Alami – Beirut, Second Edition, 1415

III. Applications of artificial intelligence in education from the viewpoint of a university lecturer, Amal Kazem Meera, edited by JassimKateh, Center for Psychological Research, the first international scientific conference for human studies, intelligence and mental capabilities 12-2019.

IV. Artificial intelligence techniques for developing statistical machine learning, Nada Badr Jarrah, Iraqi Journal of Information Technology, Volume 9 No. 3, 2019

V. Bada’i Al-Sanayi ‘, Aladdin Al-Kasani, Dar Al-Kutub Al-Alami, 2nd Edition, 1406 AH, 1986 AD

VI. Criteria for employing electronic games in developing some values for primary school children from the viewpoint of teachers in the light of some variables, Journal of the College of Education, Al-Azhar University, No. 177, Part Two, January 2018

VII. Electronic games are the reality of their practice among students of Sultan Qaboos University in the Sultanate of Oman and Menoufia University in Egypt, and the availability of them in the two universities’ libraries, Nahid Muhammad Basyouni Salem, Nadia Al-Busaidi

VIII. Julaily Aida Jusoh, M. Hafiz Yusoff, Yousef A.Baker El-Ebiary, SyarillaIryani A. Saany, Ehab HusamAlsheikh Saleh, Muhamad FikhrulEdham. (2020). The Usage of AR in Malaysian School Curriculum. IJFGCN, 13(3), 1053–1067.

IX. Netting in electronic games, jurisprudence study, Yasser bin Ibrahim Al-Khudairi, research paper presented to the Center of Research Excellence in the Jurisprudence of Contemporary Issues, Imam Muhammad bin Saud Islamic University, College of Sharia Riyadh, 1440

X. Sunan Abi Dawood, Abu Dawood Suleiman bin Al-Ash’ath Al-Sijistani, Arab Book House – Beirut

XI. Sunan Ibn Majah, Muhammad bin Yazid Abu Abdullah Al-Qazwini, Dar Al-Fikr, Beirut, investigation: Muhammad Fouad Abdul-Baqi

XII. SyarillaIryani A. Saany, Elsayed M. S. S. Elawadi, Yasser M. Tarshany, M. Hafiz Yusoff, Yousef A.Baker El-Ebiary, Nur Hikmah Binti Ismail. (2020). Utilizing the AR and Mobile Apps to Show the Rhetorical Miracle of the Fetal Growth Stages According Quran. IJFGCN, 13(3), 1068–1081.

XIII. SyarillaIryani A. Saany, Salameh A. Mjlae, Waheeb Abu-Ulbeh, Ahmed Hassan Hassan, Samer Bamansoor, Yousef A.Baker El-Ebiary. (2020). Knowledge Management System Efficiently and Effectively in the Enterprise System. IJFGCN, 13(3), 1092–1101.

XIV. SyarillaIryani A. Saany, Ehab HusamAlsheikh Saleh, Yousef A.Baker El-Ebiary, M. Hafiz Yusoff, Julaily Aida Jusoh, M. WajdiNaim. (2020). Mobile App Using AR Technique to learn kids the future professions. IJFGCN, 13(3), 1042–1052.

XV. The educational implications of children’s use of electronic games as viewed by teachers and parents of primary school students in Medina, Majid bin Muhammad Al-Zyoudi, Thebes University Journal for Educational Sciences, Volume 10 Issue 1, April 2015, p. 15

XVI. The effect of electronic games on children, descriptive and analytical study for children between 7 and 15 years, Wissem Salem Naif, 2015, Directorate of Youth and Sports of Babylon, Algeria.

XVII. The impact of electronic games on remembering, problem-solving and decision-making processes among children of metastatic childhood in Jordan, Maha Al-Shahrouri and Mohamed Odeh Al-Rimawi, Studies of Educational Sciences, Volume 38, Appendix 2, University of Jordan, in 2011

XVIII. The impact of electronic games via smartphones on the academic achievement of the Algerian student, Amira Mashri, MA degree in Media and Communication Sciences, College of Social and Human Sciences, Arab Bin Mahidi University, Algeria, 2017

XIX. The lamp of the bottle in the appendages of Ibn Majah, Ahmad bin Abi Bakr bin Ismail al-Kinani, year of birth 762 / year of death 840, investigation by Muhammad al-Muntaki al-Kashnawi, publishing year 1403, place of publication Beirut

XX. The Pure Sea, Zain Al-Din Ibn Najim Al-Hanafi, Islamic Book House, second edition.

XXI. The Right Mosque, Sunan Al-Tirmidhi, Muhammad bin Isa Abu Issa Al-Tirmidhi Al-Salami, Arab Heritage Revival House, Beirut, investigation: Ahmed Muhammad Shaker and others.
XXII. The role of electronic games in the child’s growth and learning, Andy Mohamed Hegazy, Arab Childhood Magazine, the forty-third issue.

XXIII. Using Artificial Intelligence Techniques in Da`wah to Allah, Ibtisam Bint Abdullah Al-Harbi, Master Thesis in the Department of Da`wah, The Higher Institute for Propagation and Accountability, Muhammad bin Saud University, 1440

XXIV. Video games and their repercussions on the level of academic achievement and some sports activities among adolescent pupils (15 and 18 years old) A survey study conducted at Koueidri High School, Mohamed BakhamisMeliana, Akon Hakim, Bakkah Abdel-Qader, requiring an academic master’s degree, Kassadi University, profitable and few, Algeria 2014

XXV. Yousef A.Baker El-Ebiary, Elsayed M. S. S. Elawadi, .M. Hafiz Yusoff, .SyarillaIryani A. Saany, Yasser M. Tarshany, N. Jannah BintiAbdullah. (2020). Mobile Application Utilizing 2D Animation to Learn Animals Stories in Quran in Multi Languages. IJFGCN, 13(3), 1082–1091.

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Abstract:

Promises developments in information technology, the most affected accounting and communications, and this led to tremendous developments and leaps in accounting that are no longer limited to recording, tabulating, summarizing and presenting data in final accounts on the result of information aimed at providing diverse activity information but rather evolved to be a system for its users from internal parties And external, in order to rationalize decisions, and then it has become a social technology that touches all economic, administrative, social and technical variables in the world of business and finding the accounting treatments necessary for these variables and showing their implications accounting clearly. Insurance is a method or a way for people to make sure the compensation of the loss in life such as illness, damage loss in accident or another specified loss. When people register or use this method, it can cover all damage with a specified condition based on what plan that people register or take. The way of cover by insurance are by return of money or payment support for the damage. For example, a man suffer diabetes in his life, so when he register for an insurance plan, the insurance company will support this man by give the money support for that man to buy medicine or make a checkup at hospital. People that register to insurance agency, they have to pay to that agency by month. The payment cost is based on the plan that they pick. If the plan cover 100% damage the payment for monthly will be more expensive that plan that cover below than 100% damage. However, there are certain problem in insurance agency or company which are pre-existing condition and payment way by monthly or yearly. People are talking about the condition that are changing from the plan that they choose and face problem to make a problem online to certain insurance agency. Therefore, in this study, the paper focus to identify the key criteria of solution to solve this problem. The criteria of solution discussed hoping this solution will become a major guidelines to fix this problemin any insurance agency or company.

Keywords:

E-Payment,E-Commerce,Insurance System,Accounting Issues,

Refference:

I. 15 J.L. & Com. 375 (2009-2010) Insurance and the Pre-Existing Condition Problem(“Going Bare”).

II. Asokan, Nadarajah, et al. “The state of the art in electronic payment systems.” Computer 30.9 (1997): 28-35.

III. Bamansoor, S., Saany, S. I. A., y El-Ebiary, Y. A. B. (2020). The S-Commerce usage and acceptance modelling in Malaysia. 3C TIC. Cuadernos de desarrollo aplicados a las TIC, 9(1), 99-115. http://doi.org/10.17993/3ctic.2020.91.99-115.

IV. El-Ebiary, Y. A. B., & Al-Sammarraie, N. A. (2019). “Mobile Commerce Potentials and challenges – India Case Study”. (IJRTE), 8(IC2), pp. 1154-1157.

V. Harrell, Jeffrey. “Offline to online payment.” U.S. Patent Application No. 14/2018,(2)75.

VI. He, Lin, and Zongxia Liang. “Optimal financing and dividend control of the insurance company with fixed and proportional transaction costs.” Insurance: Mathematics and Economics 44.1 (2019): 88-94.

VII. PulseSolution (Ecommerce Methodology), (2018) 13(2).

VIII. Seita Almandeel, Waheeb Abu-Ulbeh, Ahmed Hassan Hassan, Yosef A.Baker El-Ebiary, Samer Bamansoor, Syarilla Iryani A. Saany. (2020). The Proficiency and Adequacy of Leadership in Operational Administration Level in Association. IJFGCN, 13(3), 1165–1170.

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Abstract:

The means of developing Islamic discourse, from engagement to websites and social media (Facebook, Twitter, etc.), indicate that the direct means of Islamic discourse are many, including: Friday sermon, sermon, lecture, seminar, dialogue and debate. Among the most important innovative features of direct Islamic discourse: integration, balance, order of ideas, participation, compassion, civility, discussion, and attractiveness in presentation. The most important indirect means of Islamic discourse are the electronic means of communication through the Internet.Without doubt, the allocation of properties of the composition for the Quranic discourse helps to understand semantic, and that dosen’t mean the indication here as the first result from the composition, because this result was ascertaining in any level of expression, the composition of it came in a familiar style. What I meant was the second result, as launched by Abdul al-Qahir al-Jurjani (al-ma’ani al-Thawani) that does not happen to the range of mind’s perception except when they recite the composition with expressive capabilities, and composition movements. It was acknowledged that the context represents the foundation of indicators and its non-existence will lead to the scattered vocabularies that is not governed by; any relationship, because it does not connect to any context that can connect it to elements, consequently any analytical process for compositions will not be meaningful; because it is essential to depict the context with the analysis, and with the depiction of the context, the compositions obtains distinguish form in its expression’s vivacity, in which it widen different trends which some if it last long, and some displayed and some which occupy deeper subject, which contribute to its name of subject vivacity. The effect of this vivacity undoubtedly determines the understanding of indications of the Quranic discourse. the research presents characteristics of Quranic discourse commencing the meaning of discourse and its types, then presenting the distinguished style of discourse in the Holy Quran, its features and characteristics. then subject vivacity and this allocates the initial connections between subject vivacity and Quranic discourse and the consolation of this connection. finally conclude the important results followed by some recommendations.

Keywords:

The Internet,Websites,Online Speech,Social Media,Quranic Discourse,Rhetorical,

Refference:

I. ‘Ulum Al-Quran Al-Karim-Dr ‘Abd Al-Man’am Al-Namr-Dar Al-Kitab Al-Misri-1979

II. ‘Ulum Al-Quran- Dr ‘Abdullah Shahatah-Dar Al-I’tisam-3rd Edition-1985

III. Al-Asalib Al-InshaiyyahWaAsraruha Al-Balaghiyyah Fi Al-Quran Al-Karim Asst Prof SobahDarraz-Matba’ah Al-Amanah-Qaherah-1st Edition-1986

IV. Al-AshbahWa Al-Nazhair-Maqatil Ibn Sulaiman Al-Bulkhi-Tahqiq Dr Abdullah Shahatah-Al-Hai’ah Al-Misriyyah Al-‘Ammah Lil Al-Kitab-2nd Edition-1994

V. Al-Bahr Al-Muhit- Abu Hayyan Al-Tauhidi-Footnotes From Tafseer Al-Nahr Al-Mad Min Al-Bahr Li Abi Hayyan, Kitab Al-Dar Al-Laqit Min Al-Bahr Al-Muhit Li Al-Imam Tajuddin Al-Hanafi-Dar Al-Fikr-Beirut-2nd Edition-1983

VI. Al-Balaghah Al-Istilahiyyah-Dr ‘Abdu ‘Abd Al-‘Aziz Qalqaliyyah-Dar Al-Fikr Al-‘Arabiy-Qaherah-1989

VII. Al-Balaghah Al-Quraniyyah Fi Tafseer Al-ZamakhshariWaAtharuha Fi Dirasat Al-Balaghiyyah- Asst Prof Dr Muhammad Muhammad Abu Musa-Maktabah Wahbah-2nd Edition-1988

VIII. Al-Bayan Fi Al-Rawa’i’ Al-Quran- Asst Prof Tamam Hassan-‘Alim Al-Kutub-Qaherah-1st Edition-1993

IX. Al-Burhan Fi ‘Ulum Al-Quran- Badruddin Al-Zarkashi- Dar Al-Kutub Al-‘Ilmiyyah-Beirut-Lebanon- 1st Edition-1999

X. Al-Istifham Fi Al-Quran Al-Karim, DirasahUslubiyyah-Dr Tariq Shilbi-RisalahDukturah-Kulliyyah Al-Adab- Jami’ah ‘Ain Shams-1997

XI. Al-Itqan Fi ‘Ulum Al-Quran – Jalaluddin Al-Suyuthi- Dar Al-Nadwah Al-Jadidah- Beirut-Lebanon.

XII. Al-Jami’ Li Ahkam Al-Quraniy-Al-Qurtubi-Tahqiq Salim Mustafa Al-Badri-Dar Al-Kutub Al-‘Ilmiyyah-Beirut- 1st Edition

XIII. Al-Muharrir Al-Wajiz Fi Tafseer Al-Kutub Al-‘Aziz-Ibn ‘Atiyyah Al-Andalusi-Tahqiq Al-Majlis Al ‘Ilmi Of Taroudan-Maktabah Ibn Taimiyyah-Cairo-1992

XIV. Al-Tafseer Al-Tatbiqi “Manhaj ‘Ilmiy Li Dirasah Al-Nas Al-Quraniy- Dr Hussain Bashir Sadiq- Al-Dar Al-Sudaniyyah Li Al-Kutub- Khourtum-1st Edition-1995

XV. Al-Tahrir Wa Al-Tanwir-Muhammad Al-Tahir Ibn ‘Asyur-Dar Suhunun Li Al-NasyrWa Al-Tauzi’- Tunisia

XVI. Al-Tashil Li ‘Ulum Al-Tanzil-Ibn Jizzi- Al-Dar Al-‘Arabiyyah Li Al-Kitab

XVII. Al-Taswir Al-Fanni Fi Al-Quran Al-Karim-Sayyid Qutb

XVIII. Al-Zaman Fi Al-Quran Al-Karim, DirasahDilaliyyah Li Al-Af’al Al-WaridahFihi- Dr Bakri ‘Abd Al-Karim-Dar Al-Kitab Al-Hadith-2001

XIX. Anwar Al-TanzilWaasrar Al-Ta’wil-Al-Baidhawi- Dar Al-Kutub Al-‘Ilmiyyah-Beirut-Lebanon-1st Edition 2003

XX. Asalib Al-Nida’ Fi Al-Quran DirasahNassiyyah- Dr Muhammad Samir Murad-RisalahMajistir-Kulliyyah Al-Adab-Jami’ah’ainshams

XXI. Asbab Al-Nuzul- Abi Al-Hassan ‘Ali Ibn Ahmad Al-Wahidi-DirasahWaTahqiq Dr Al-Sayyid Al-Jamili- Dar Al-Rayyan Li Al-Turath.

XXII. BasoirDzawi Al-Tamayyuz Fi Lathoif Al-Kitab Al-‘Aziz-Al-Fairuz Abadi-TahqiqAbdulhalim Al-Thohawi- Al-Maktabah Al-‘Ilmiyyah-Beirut

XXIII. Buhjah Al-Arib Fi Bayan Ma Fi Kitabullah Al-‘Aziz Min Al-Gharib-Ibn Al-Turkamani-Tahqiq Marzuq ‘Ali Ibrahim-Al-Haiah Al-Misriyyah Al-‘Ammah Li Al-Kitab-2003

XXIV. Dalai’l Al-I’jaz ‘Abd Al-Qahir Al-Jurjani-Tahqiq Muhammad Khaffaji-Maktabahal-Qaherah-1990

XXV. Dilalat Al-TarakibDirasahBalaghiyyah-Muhammad Muhammad Abu Musa-Maktabah Wahbah-Cairo-3rd Edition-2004

XXVI. DirasatLughawiyyah Fi Al-Quran Al-Karim Wa-Qiraatihi-Dr Ahmadmukhtar Umar-‘Alim Al-Kutub-Cairo-1st Edition-2001

XXVII. Elsayed Mohamed Salem SalemElawadi, Zulazhan Ab. Halim, Najeeb Abbas Al-Sammarraie, Yousef Abubaker El-Ebiary, Bishwajeet Pandey, (2019). “Digitization of the Arabic Language Between Reality and Expectations”, (IJRTE), Volume-8 Issue-2S3, pp. 1151-1158.

XXVIII. Elsayed Mohamed Salem SalemElawadi, Zulazhan Ab. Halim, Najeeb Abbas Al-Sammarraie, Yousef Abubaker El-Ebiary, Bishwajeet Pandey, (2019). “The Impact of E-Learning in Teaching Arabic Language for Non-Native Speakers”, (IJRTE), Volume-8 Issue-2S3, pp. 1159-1162.

XXIX. ElsayedSalemm, Ragab Awad, Abdelsattar Ayoub, Abdelrahman Tahawi, Yousef A.Baker El-Ebiary, Bishwajeet Pandey. “The Importance of Rhetorical and the Technological Learning Solutions for Non-Arabic Speakers” Volume 82, Issue: January-February 2020, P: 16484 – 16492. (TEM).

XXX. Fath Al-Bayan Fi Maqasid Al-Quran- Sadiq Hassan Khan-Dar Al-Fikr Al-‘Arabiy-Cairo

XXXI. Fath Al-Qadir Al-Jami’ Baina Fanni Al-RiwayahWa Al-Dirayah Min ‘Ilm Al-Tafseer- Al-Shaukani-Dar Ibn Hazim-Beirut-1st Edition-2000

XXXII. Fi Zhilal Al-Quran- Sayyid Qutb-Dar Al-Shuruq-Cairo-16th Edition-1990

XXXIII. Hashiyah Al-Saja’i ‘Ala Al-Qitr-Al-Saja’i-Dar Ihya’ Al-Kutub Al-‘Ilmiyyah ‘Isa Al-Halabi-1349

XXXIV. Hashiyah Al-Sawi ‘Ala Al-Jalalain-Ahmad Al-Sawi-Edition Dar Ihya’ Al-Kutub Al-‘Arabiyyah

XXXV. Irshad Al-‘Aql Al-Salim Ila Mazaya Al-Quran Al-Karim-Abu Al-Sa’ud Al-‘Umawi-Dar Al-Kutub Al-‘Ilmiyyah-Beirut-Lebanon- 1st Edition-1999

XXXVI. Jami’ Al-Bayan Fi Tafseer Al-Quran-Al-Tabari- Dar Al-Hadith-Qaherah-1987, Footnotes From Tafseergharaib Al-Quran Li Nazmuddin Al-Nisayuri

XXXVII. Khasais Al-Ta’bir Al-QuraniyWaSimatihi Al-Balaghiyyah- Dr ‘Abd Al-‘Azim Al-Mut’ini-MaktabahWahbah Qaherah-1st Edition-1992

XXXVIII. Khasais Al-TarakibDirasahTahliliyyah Li Masai’l ‘Ilmal-Ma’ani-Asst Prof Dr Muhammad Abu Musa- Maktabah Wahbah-Qaherah-3rd Edition-1980

XXXIX. Mafatih Al-Ghaib- Fakhruddin Al-Razi-Dar Al-Fikr-Beirut-3rd Edition-1985

XL. Qadhaya Fi ‘Ulum Al-Quran Tu’ayyin ‘Ala FahmDilalat Al-Nas- Dr Al-Sayyid Ahmad ‘Abd Al-Ghaffar- Dar Al-Ma’rifah Al-Jami’iyyah

XLI. Ragab Awad, Elsayed Salem, Abdelsattar Ayoub, Abdelrahman Tahawi, Yousef A.Baker El-Ebiary, Bishwajeet Pandey. “The Online Platform Mechanism and Characteristics in Arabic Language Tests for Non-Native Speakers” Volume 82, Issue: January-February 2020, P: 16473 – 16483. (TEM).

XLII. Rauh Al-Ma’ani Fi Tafseer Al-Quran Al-‘Azim Wa Al-Sab’ Al-Mathani-Al-Alusi-Tahqiq Abu ‘Abd Al-Rahman Fuad Ibn Siraj ‘Abd Al-Ghaffar-Al-Maktabah Al-Taufiqiyyah-Cairo

XLIII. Safwah Al-Tafaseer- Muhammad ‘Ali Al-Sabbuni-Dar Al-Sabbuni-Cairo-9th Edition

XLIV. Sahih Al-Bukhari-Al-Bukhari-Al-Majlis Al-A’la Li Al-Shuu’n Al-Islamiyyah-LajnajAkhbarKutub Al-Sunnah-Cairo-2nd Edition-1990

XLV. Tafseer Al-Kashaf- Al-Zamakhshari- Mansyurat Muhammad ‘Ali Baidhun- Dar Al-Kutub Al-‘Ilmiyyah-Beirut-Lebanon-1st Edition-1995

XLVI. Tafseer Al-Quran Al-‘Azim-Ibn Kathir-Maktabah Al-Saffa-Qaherah-1st Edition-2002

XLVII. Uslub Al-Muqabalah Fi Al-Quran Al-Karim-DirasahFanniyyahBalaghiyyahMuqaranah, Asst Prof Dr Kamal Abdul Aziz Ibrahim-RisalahMajistir- Kulliyyah Al-Adab- University Of Zakazik -1985

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Abstract:

It is extremely important for the participants to acquire the modern skills in the field of the main offices business, in addition to applying the latest behavioral and administrative skills, which must be available in the history of the VIPs and their writings. And in order to practice the process of knowledge and knowledge. The electronic archiving system is a system for storing important documents within an electronic system that saves time and effort in reviewing or requesting a document by searching for it via the document number or its history or anything that indicates it, whether the date it was preserved or the values that were preserved with it or anything that indicates to it such as The author, therefore the electronic archiving system is considered an advanced and very useful system not only for history but also for companies, institutions or government departments dispensaries or any entity that has documents and wants to convert them into electronic documents and deal with them within a program that archives paper documents and documents and disposal of papers and preservation traditional. by Abu Shamah a study and criticism.” This study aims to explore the method followed by Abu Shamah in his book “Al-Mudzil” ‘ala al-Raudhatain”, and to discuss the following features: History arranged based on yearly basis, scheduling historical events, and timely arrangements on a monthly basis in a year, connecting the past with the future of the historical events, proclamation of the mistakes of other people and corrections of these mistakes, considerations of figures, presentation on peculiar and miraculous events that he recorded, and explain the most important flaws on the recording method used by Abu Shamah. The most important result of this research is the explanation on the features of the method used by Abu Shamah in al-Mudzila’la al-Raudhatain together with evidences, and with that, readers are presented with an important historical article which demonstrate current social, economy, defence in accurate period of time in our Islamic history from 590-665 hijrah / 1194-1267 ce. The researcher recommends the study of Abu Syamah’s writings in history, Fiqh, Tafseer and language which its study and engagement shall give us many benefits and advantages that will contribute to knowledge and scholars and will uncover treasures and heritage of the original Arabs.

Keywords:

Electronic Archiving,Information systems,File Management,Recording Methods,Al-Mudzil,

Refference:

I. Abu Shamah, al-Raudhotain fi Akhbar al-Daulatain, v1, checked by Ibrahim al-Zibaq, 1st edition, 1997, Matba’ah al-Risalah, Beirut

II. Aby Shamah, al-Mudzil ‘Ala al-Raudhotain, v1, v2, checked by Ibrahim al-Zibaq, 2010, Daral-Bashair al-Islamiyyah, Damascus

III. Al-dawudi, thobaqat al-mufassirin,v1,and whatever next,dar al-kutub al-I’lmiyyah, Beirut, without date and publisher

IV. Al-Farahidi, kitab al-‘Ain, v3,Checked by Dr Mahdi al-Makhzumi, Dr Ibrahim al-Samarai’, without date and publisher

V. Al-Kutubi, Fawat al-Wafayat, V2, checked by Ihsan ‘Abbas,Darsodir Beirut, without year.

VI. Al-Marakishi, al-Mu’jib fi TalkhisAkhbar al-mugharrab, 3rd book, checked by al- Ustaz Muhammad Sa’id al-‘Uryan, Cairo, 1963.

VII. Al-Muwarra, Nafh al-Tayyib, V2, Checked by Ihsan ‘Abbas, Dar Sodir Beirut, 1988.

VIII. Al-Nisfi, Tafseer al-Nisfi,V4, Dar al-Fikr li al-Toba’ahwa al-Nasyr.

IX. Al-Qusyairi, Sohih Muslim, checked by al-sheikh Muhammad Fuad ‘Abd al-Baqi, Dar Ihya’ al-Turath al-‘Arabiy, Beirut.

X. Al-Sabaki, Tobaqot al-Shafi’iyyah al-Kubra, v8, ‘Abd al-Fattah al-Hulw-Mahmud al-Thonahi, Dar Ihya’ al-Kutub al-‘Arabiyyah, without date.

XI. Al-Safadi, al-Wafi bi al-Wafayat, v18, Checked by Ahmad al-Arnau’t, 1st edition, 1991, Dar Ihya’ al-Tharra’ al-‘Arabiy.

XII. Al-Suyuthi, bughyah al-Wa’ah fi Thobaqot al-Lughawiyyinwa al-Nuhah, v2, 2nd edition, Dar al-Fikr, 1979.

XIII. Al-Tabari, Tafseer al-Tabari, Mujallad 12, Dar al-Kutub al-‘Ilmiyyah, Beirut, 1st edition, 1992

XIV. Al-Yafi’I, Mira’h al-Junan, V3, V4, 2nd Edition,1992, Cairo, Dar al-Kitab al-Islamiy.

XV. Al-Zahabi Tarikh al-Islam, wafayat al-masyahirwa al-a’lam, checked by Sa’id Abu ‘Aziz and others, volume 49, al-maktabah al-taufiqiyyah

XVI. Al-Zahabiy, al-‘abr, v3, checked by Abu Hajar Muhammad Sa’id, Dar al-Kutub al-‘Ilmiyyah, Beirut, without year

XVII. Al-Zahabiy, Sir A’lam al-nubala’,v6,v21, checked by Bashar ‘Awad, 10th edition, 1994, Muassasah al-Risalah.

XVIII. Al-Zarkali, al-A’lam, v3,v5, Dar al-‘Ilm li al-Malayiin, 10th edition, 1992

XIX. Elsayed Mohamed Salem SalemElawadi, Zulazhan Ab. Halim, Najeeb Abbas Al-Sammarraie, Yousef Abubaker El-Ebiary, Bishwajeet Pandey, (2019). “Digitization of the Arabic Language Between Reality and Expectations”, (IJRTE), Volume-8 Issue-2S3, pp. 1151-1158.

XX. Elsayed Mohamed Salem SalemElawadi, Zulazhan Ab. Halim, Najeeb Abbas Al-Sammarraie, Yousef Abubaker El-Ebiary, Bishwajeet Pandey, (2019). “The Impact of E-Learning in Teaching Arabic Language for Non-Native Speakers”, (IJRTE), Volume-8 Issue-2S3, pp. 1159-1162.

XXI. Hussain Kazim Khuyun, jurnal entitled: Al-Khawrizmiyyah fi Bilad al-Sham wa Al-Jazeerah (618-644h/1220-1246), Majallahdiyali li al-‘Ulum al-Insaniyyah, No 53,2011.

XXII. Ibn al-‘Imad, Shadzarat al-Zahab, v7, Checked by Mahmud al-Arnau’t, and ‘Abd al-Qadir al-Arnau’t, 1st edition, 1991, Dar ibn Kathir Damascus, Beirut

XXIII. Ibn al-athir, al-kamil fi tarikh, v12, darsodir, Beirut, 1982

XXIV. Ibn al-Kathir, al-Bidayahwa al-Nihayah, V17, Checked by Dr ‘Abdullah Ibn ‘Abd al-Muhsin al-Turkiy, Dar Hajr li al-Toba’ahwa al-Nasyri, in collaboration with Markaz al-Buhuth li al-Dirasah al-‘arabiyyahwa al-Islamiyyah, Cairo, 1 edition, 1998.

XXV. Ibn al-Wardi, Tarikh Ibn al-Wardi,V2, 1st edition,1996, Dar al-Kutub al-‘Ilmiyyah, Beirut

XXVI. Ibn khalkan, wafayat al-A’yan, v4, checked by Ihsan ‘Abbas darsodir, Beirut, 1971

XXVII. Ibn Manzur, Lisan al-‘Arab, Dar al-Fikr, without year.

XXVIII. Ibn qadhiShuhbah, thobaqot al-Shafi’iyyah, v2, 1st edition, 1979, Dairah al-Ma’arif al-‘Uthmaniyyah, Haidar Abad, al-Dukn, India

XXIX. Ibn taghribirdi, al-manhal al-sofi,v7, checked by Muhammad Muhammad Amin, 1993, markaztahqiq al-turath.

XXX. Ibn Taghribirdi, al-nujum al-zahirah,v6,published by dar al-kutub al-misriyyah 1999

XXXI. Majma’ al-Lughah al-‘Arabiyyah, al-Mu’jam al-Wasit, 4 edition, Maktabah al-Shuruq al-Duwaliyyah, 2004

XXXII. Ragab Aboumelih M. S., A. Ramadan M. A., A. Fathi Ramadan, Saad GommaZaghloul, M. Mustakim Bin Abd Halim, Yousef A. Baker El-Ebiary. “E-Learning and The Purpose of Maintaining the Mind in Islam and Its Impact On Teaching and Learning”. Volume 83, Issue: May – June 2020, P: 7596 – 7603. (TEM).

XXXIII. Ragab Aboumelih M. S., A. Ramadan M. A., A. Fathi Ramadan, Saad GommaZaghloul, M. Mustakim Bin Abd Halim, Yousef A.Baker El-Ebiary. “The Role of Social Media in The Spread of Information – A Study On the Endeavor Expansion Between the Appearance of Texts and The Sharia Intentions”. Volume 83, Issue: May – June 2020, P: 9913 – 9921. (TEM).

XXXIV. Yaqut al-Hamawiy, Mu’jam al-Buldan, V4, Dar sodir, Beirut

XXXV. Yaqut al-Hamawi, Mu’jam al-Udaba’, V6, 1st edition, 1993, Dar al-Gharb al-Islamiy, Beirut, Checked by Ihsan ‘Abbas

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Abstract:

OSS (Open Source Software) is a leading-edge technology which has a profound impact on Information Technology.  It has been observed via extent research that there are substantial barriers associated with OSS that thwart the wide adoption of OSS especially in the domain of mission critical software. Critical IT infrastructure is the backbone of any country. Any nation's economy, security, and health are totally dependent on the critical infrastructure. Critical IT infrastructure demands mission critical software to run their day to day work properly and efficiently. It has been observed that critical organizations are operating with proprietary software and are willing to adopt Open source software (OSS). Proprietary software comes with many issues like vendor dependencies, license cost and maintenance cost. This paper investigates the current trends of Critical IT infrastructure and identifies the barriers in OSS adoption in Critical IT Infrastructure Industry.

Keywords:

Open Source Software,Closed Source Software,Factors affecting adoption,Information Technology,

Refference:

I. A. Hafeez-Baig, S. Grist, and R. Gururajan, ‘Technology Management, Data management, Improved outcomes, Efficiency and Software limitation influencing the use of wireless technology for healthcare in Pakistan’, in 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), Jul. 2007, pp. 1104–1110, doi: 10.1109/ICIS.2007.177.
II. B. Buffett, ‘Factors influencing open source software adoption in public sector national and international statistical organisations’, presented at the Meeting on the Management of Statistical Information Systems (MSIS), Dublin, Ireland and Manila, Philippines, Apr. 2014.
III. C. M. Gichira, A. M. Kahonge, and E. K. Miriti, ‘Adoption of Open Source Software by Organizations – A Framework for Kenya’, International Journal of Computer Applications, vol. 59, no. 7, pp. 25–32, Dec. 2012.
IV. C. J. Reynolds and J. C. Wyatt, ‘Open Source, Open Standards, and Health Care Information Systems’, J Med Internet Res, vol. 13, no. 1, Feb. 2011, doi: 10.2196/jmir.1521.
V. D. Nagy, A. M. Yassin, and A. Bhattacherjee, ‘Organizational adoption of open source software: barriers and remedies’, Communications of the ACM, vol. 53, no. 3, pp. 148–151, Mar. 2010, doi: 10.1145/1666420.1666457.
VI. D. Di Ruscio and P. Pelliccione, ‘Simulating upgrades of complex systems: The case of Free and Open Source Software’, Information and Software Technology, vol. 56, no. 4, pp. 438–462, Apr. 2014, doi: 10.1016/j.infsof.2014.01.006.
VII. D. Petrov and N. Obwegeser, ‘Adoption Barriers of Open-Source Software: A Systematic Review’, Social Science Research Network, Rochester, NY, SSRN Scholarly Paper ID 3138085, Mar. 2018. Accessed: Jul. 23, 2018. [Online]. Available: https://papers.ssrn.com/abstract=3138085.
VIII. D. Silic, A. Back, and M. Silic, ‘Taxonomy of technological risks of open source software in the enterprise adoption context’, Info and Computer Security, vol. 23, no. 5, pp. 570–583, Nov. 2015.
IX. E. Noroozi and H. Seifzadeh, ‘Proposing Novel Measures to Alleviate the Risks of Migration to Open Source Software’, in Proceedings of the 10th International Conference on Computer Modelling and Simulation, New York, NY, USA, 2018, pp. 134–139, doi: 10.1145/3177457.3177478.
X. H. Safadi, D. Chan, M. Dawes, M. Roper, and S. Faraj, ‘Open-source health information technology: A case study of electronic medical records’, Health Policy and Technology, vol. 4, no. 1, pp. 14–28, Mar. 2015.

XI. H. Schmuhl, O. Heinze, and B. Bergh, ‘Use of Open Source Software in Health Care Delivery – Results of a Qualitative Field Study. Contribution of the EFMI LIFOSS Working Group’, Yearb Med Inform, vol. 8, pp. 107–113, 2013.
XII. I. Khan et al., ‘Medical Drop Box (MDB); A National health information exchange and management system for medical industry’, THE PROFESSIONAL MEDICAL JOURNAL, vol. 23, no. 04, pp. 489–498, Apr. 2016, doi: 10.17957/TPMJ/16.3279.
XIII. J. Marsan, G. Paré, and A. Beaudry, ‘Adoption of open source software in organizations: A socio-cognitive perspective’, The Journal of Strategic Information Systems, vol. 21, no. 4, pp. 257–273, Dec. 2012.
XIV. J. S. Norris and P.-H. Kamp, ‘Mission-Critical Development with Open Source Software: Lessons Learned’, in IEEE Softw., Jan. 2004, vol. 21, pp. 42–49, doi: 10.1109/MS.2004.1259211.
XV. K. Gurusamy and J. Campbell, ‘A Case Study of Open Source Software Adoption in Australian Public Sector Organizations’, Queensland University of Technology, Brisbane, 2011.
XVI. L. Jin, S. Verma, and W. H. Chuang, ‘Deploying Mission Critical Learning Management System Using Open Source Software’, Seattle, Washington, 2012.
XVII. M. G. Yaseen and my M. Bahari, ‘A Theoretical Research Framework of Open Source Software Adoption in Malaysian University Information and Communications Technology Centers’, Journal of Information System Research and Innovation, vol. 8, pp. 75–82, 2014, doi: 10.1016/j.infsof.2014.01.006adoper.
XVIII. M. S. Qazi and M. Ali, ‘Pakistan’s health management information system: health managers’ perspectives’, J Pak Med Assoc, vol. 59, no. 1, pp. 10–14, Jan. 2009.
XIX. M. Silic and A. Back, ‘Open Source Software Adoption: Lessons from Linux in Munich’, IT Professional, vol. 19, no. 1, pp. 44–47, Feb. 2017.
XX. M. L. M. Kiah, A. Haiqi, B. B. Zaidan, and A. A. Zaidan, ‘Open source EMR software: Profiling, insights and hands-on analysis’, Computer Methods and Programs in Biomedicine, vol. 117, no. 2, pp. 360–382, Nov. 2014.
XXI. M. Silic and A. Back, ‘Identification and Importance of the Technological Risks of Open Source Software in the Enterprise Adoption Context’, in International Conference on Wirtschaftsinformatik, Osnabrück, Mar. 2015, pp. 1163–1176, Accessed: Oct. 22, 2018. [Online].
XXII. N. G. Chaudhry, S. Ilyas, A. Shahzad, A. Saleem, M. Rashid, T. A. Chaudhry, ‘An open source health care management system for Pakistan’, 2006, pp. 1–7.
XXIII. N. Benkeltoum, ‘Open source software adoption for safety-critical information systems design: the Thales case study
[Adoption de l’open source pour la conception de systems d’information critiques : le cas Thales]’, HAL, hal-01481687, 2016. Accessed: Nov. 29, 2018. [Online]. Available: https://ideas.repec.org/p/hal/journl/hal-01481687.html.
XXIV. ‘Open source forms the backbone of the most significant projects’, Opensource.com. https://opensource.com/business/14/8/black-duck-oss-survey-2014 (accessed Oct. 17, 2018).
XXV. Ø. Hauge, D. S. Cruzes, R. Conradi, K. S. Velle, and T. A. Skarpenes, ‘Risks and Risk Mitigation in Open Source Software Adoption: Bridging the Gap between Literature and Practice’, in Open Source Software: New Horizons, 2010, pp. 105–118.
XXVI. P. WHOROftW, Ed., Medical records manual: a guide for developing countries. Geneva: World Health Organization, 2002.
XXVII. P. Poba-nzaou and S. Uwizeyemungu, ‘Barriers to Mission-Critical Open Source Software Adoption by Organizations: A Provider Perspective’, May 2013, [Online]. Available: https://aisel.aisnet.org/amcis2013/AdoptionOfIT/GeneralPresentations/7.
XXVIII. S. Al Zeheimi and A. Zeki, ‘Perceptions of library and information science community towards open source software adoption in libraries of Oman’, in The 5th International Conference on Information and Communication Technology for The Muslim World (ICT4M), Kuching, 2014, pp. 1–6, Accessed: Oct. 17, 2018. [Online].
XXIX. S. K. Kwan and J. West, a Conceptual Model for Enterprise Adoption of Open Source Software. .
XXX. U. Laila and K. Mehboob, ‘Comparison of open source maturity models’, Procedia Computer Science, vol. 111, pp. 348–354, 2017.
XXXI. U. Laila and S. F. A. Bukhari, ‘Open Source Software (OSS) Adoption Framework for Local Environment and its Comparison’, in Innovations in Computing Sciences and Software Engineering, 2010, pp. 13–16.

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Abstract:

In this research article, we work with varieties of enriched semirings. The proposed study gives the structure of Square Absorption semirings satisfying  for all in S. We study the condition under which  is idempotent and/or   is idempotent. We also study the structure of this class of semirings under which additive reduct and multiplicative reductare positively totally ordered semirings.

Keywords:

Square Absorption Semiring,Idempotent semiring,Periodic,Zeroid,Right (left) regular,

Refference:

I. I. Chajda, H. Langer, (2015) On a variety of commutative multiplicatively idempotents semirings, Semigroup Forum, Springer Science+Businesss Media New York 2016.
II. I. Chajda, H. Langer, (2018) The variety of commutative additively and multiplicatively idempotent semirings, Semigroup Forum, 96:409-415.
III. J.S. Golan, Semirings and their Applications, Kluwer Academic Publishers, Dordercht, 1999.
IV. Mariana Durcheva, A note on idempotent semirings, AIP Conference Proceedings 1789, 060006(2016);
V. M. Ren, X. Zhao (2016), The varieties of semilattice-ordered semigroups satisfying and , Period Math Hung, AkademiaiKiado, Budapest, Hungary 2016.
VI. M. Satyanarayana, “Positively Ordered Semigroups”, Lecture notes in Pure and Applied Mathematics, Marcel Dekker, Inc., Vol. 42(1979).
VII. M. Satyanarayana, “On the additive semigroup structure of semirings” Semigroup Forum Vol. 23(1981)7-4.
VIII. M. Satyanarayana “On the additive semigroup of ordered semirings” Semigroup Forum Vol.31(1985) 193-199.
IX. M. K. Sen, Y. Q. Guo, and K. P. Shum, A Class of Idempotent Semirings, Semigroup Forum, vol. 60(2000) 351-367.
X. M. Amala, T. Vasanthi, Idempotent Property of Semirings, International Journal of Pure Algebra-5(9), 2015, 156-159.
XI. N. Sulochana, T. Vasanthi, Structure of Some Idempotent Semirings, Journal of Computer and Mathematical Sciences, Vol.7(5), 294-301, May 2016.
XII. N. Sulochana, T. Vasanthi, Properties of Completely Regular Semirings, Southeast Asian Bulletin of Mathematics (2016) 40: 923-930.
XIII. T. Vasanthi, Y. Mounikarchana and K. Manjula, Structure of Semirings, Southeast Asian Bulletin of Mathematics (2011) 35: 149-156.
XIV. Y. Sha, M. Ren (2014), On the varieties generated by ai-semirings of order two, Semigroup Forum, Springer Science+Business Media New York 2014.
XV. Y. Guo, K. Shum, M. Sen (2003), The semigroup structure of left Clifford semirings, Acta Math. Sin. (Engl. Ser.), 2003, 19(4): 783-792.

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Abstract:

As the internet is rapidly evolving, communication technologies have become insecure, so several techniques is produced to solve this issue. The digital watermark technique is one of these techniques which provides the protection of property rights. This paper present a technique for image watermarking images that aim to improve the degree of robustness of the watermarking system against noise attacks, also to enhance the quality of the watermark image. In addition, logistic map chaotic is used in this technique to make sure the watermark image where the watermark is available only to a authorize user. This scheme is considered as a blind scheme for both cover image and watermark. Firstly, the watermark logo is encrypted with the logistic map chaotic and then encoded into a string of binary values, the secret image is embedded within another image, i.e. cover image by decomposition of the host image using Haar wavelet transform. The experimental results of the presented work indicate that elevated values of imperceptibility have been indicated via MSE and PSNR parameters. The robustness of image watermark have been evaluated via NC, also it has been indicated for having high robustness against attacks

Keywords:

Haar wavelet transform,Image watermarking,Logistic map chaotic,

Refference:

I. Cox, I., Miller, M., Bloom, J., Fridrich, J., and Kalker, T. Digital watermarking and steganography. Morgan kaufmann, 2007.‏
II. De, S., Bhaumik, J., Dhar, P., and Roy, K. “DCT-Based Gray Image Watermarking Scheme.” Communication, Devices, and Computing. Springer, Singapore, pp: 181-189, 2017.‏
III. D.M. Jose, R. Karuppathal, and A.V. Kumar, “Copyright Protection using Digital Watermarking.” Copyright Protection using Digital Watermarking, 2012, online: https://pdfs.semanticscholar.org/ d536/5a1f9d8ae04f3932eec 02b898a91cd7aa0e1.pdf?_ga =2.23629 5046.623200384.1588546901-125568524.1547477851. Accessed 15-5-2020.
IV. Fiscella, M. Combining CMOS-based microelectrode arrays with genetic labeling to study visual processing in the retina. Diss. ETH Zurich, 2014.‏
V. Hamidi, M., El Haziti, M., Cherifi, H., and El Hassouni, M. “Hybrid blind robust image watermarking technique based on DFT-DCT and Arnold transform.” Multimedia Tools and Applications, Vol. 77, No.20, pp: 27181-27214, 2018.‏
VI. Hsieh, M. S., Tseng, D. C., and Huang, Y. H. “Hiding digital watermarks using multiresolution wavelet transform.” IEEE Transactions on industrial electronics, Vol. 48, No.5, pp: 875-882, 2001.

VII. ‏Kang, X. B., Zhao, F., Lin, G. F., & Chen, Y. J. “A novel hybrid of DCT and SVD in DWT domain for robust and invisible blind image watermarking with optimal embedding strength.” Multimedia Tools and Applications, Vol. 77, No.11, pp: 13197-13224, 2018.
VIII. Mousavi, S. M., Naghsh, A., and Abu-Bakar, S. A. R.”Watermarking techniques used in medical images: a survey.” Journal of digital imaging, Vol. 27 No.6, pp: 714-729, 2014.
IX. Pandey, M. K., Parmar, G., Gupta, R., and Sikander, A. “Non-blind Arnold scrambled hybrid image watermarking in YCbCrcolor space.” Microsystem Technologies, Vol. 25, No. 8, pp: 3071-3081, 2019.‏
X. Pugar, F. H., and Arymurthy, A. M. “Blind Color Image Watermarking Based on 2-level Discrete Wavelet Transform, M-ary Modulation, and Logistic Map.” 2019 12th International Conference on Information & Communication Technology and System (ICTS), pp: 235-240, 2019.‏
XI. Parah, S. A., Loan, N. A., Shah, A. A., Sheikh, J. A., and Bhat, G.M. “A new secure and robust watermarking technique based on logistic map and modification of DC coefficient.” Nonlinear Dynamics, Vol.93, No.4, pp: 1933-1951, 2018.
XII. Patvardhan, C., Kumar, P., and Lakshmi, C. V. “Effective color image watermarking scheme using YCbCrcolor space and QR code.” Multimedia Tools and Applications, Vol. 77, No.10, pp: 12655-12677, 2018.‏
XIII. Sabbane, F., and Tairi, H. “Medical image watermarking technique based on polynomial decomposition.” Multimedia Tools and Applications, Vol. 78, No.23, pp: 34129-34155, 2019‏.
XIV. Singh, A. K., Dave, M., and Mohan, A. “Hybrid technique for robust and imperceptible multiple watermarking using medical images.” Multimedia Tools and Applications, Vol.75, No.14, pp: 8381-8401, 2016.‏
XV. Soualmi, A., Alti, A., and Laouamer, L. “A new blind medical image watermarking based on weber descriptors and Arnold chaotic map.” Arabian Journal for Science and Engineering, Vol. 43, No.12, pp: 7893-7905, 2018.
XVI. Sudibyo, U., Eranisa, F., Rachmawanto, E. H., and Sari, C. A. “A secure image watermarking using Chinese remainder theorem based on haar wavelet transform.” 2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE). IEEE, pp: 208-212, 2017.‏
XVII. Trivedy, S., and Pal, A. K. “A logistic map-based fragile watermarking scheme of digital images with tamper detection.” Iranian Journal of Science and Technology, Transactions of Electrical Engineering, Vol. 41, No.2, pp: 103-113, 2017.
XVIII. Yu, G., and Zhao, X. J. “Study Based on Chaotic Encryption and Digital Watermarking Algorithm.” Recent Advances in Computer Science and Information Engineering. Springer, Berlin, Heidelberg, pp: 619-625, 2012.‏

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