Archive

Fostering Conditions for Innovative Reforms in Public Sector Organizations and Their Response to Artificial Intelligence

Authors:

Sayyed Khawar Abbas, Muhammad Aftab

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00040

Abstract:

The paper is intended to investigate the foster effects of political instability, leadership influence, experimentation and budget constraints responsible for poor performance and feedback from public sector organizations. Keeping in view the purpose of the study, the research framework for the study is descriptive. Firstly, Primary data is collected through questionnaires from individuals engaged with public sector organizations. Secondly, unstructured interviews conducted to explore the effect of Artificial intelligence. Through research analysis, the empirical evidence suggest that the innovation activity is intrigued with important conditions responsible for the performance of public sector organization. Political instability suggested negative significance while others have demonstrated positive significance concerning innovation reforms. Artificial Intelligence also demonstrates a strong scope for future public sector organizations. In the following research framework, the data is based on the judgments of employees engaged with public sector organizations. The responses are individual self-reported and not objective, so there is a fair possibility that response would be biased. Furthermore, the responses are from Pakistan’s main cities which cannot be generalized to various countries. This study focuses on the performance of the public sector organization. A large amount of literature has emerged on the likelihood of innovation reforms for private sector firms over the course of time. This paper is widening the horizon to study the likelihood of innovation reforms for public sector organizations by adhering the innovation culture and identifying important factors which may influence. The paper also provides a base for finding more dimensions to implement innovation reforms and also guide policymakers to execute efficient policies. Furthermore, the study is based on questions covering “what” and “how” dimensions. This type of quantitative study lacks for “why” dimension. Therefore, semi-structured interviews and case analysis could explain more regarding innovation reforms. The research framework is the first attempt to examine the impact of different conditions on the implementation of innovation and Artificial intelligence influence in public sector organizations in Pakistan.

Keywords:

Public sector organizations, Innovation reforms, political instability,leadership influence, experimentation, budget constraints, OECD (Organization for Economic Cooperation and Development, ICT (Information and communication technology),Artificial Intelligence,

Refference:

I.Albury, D. (2005). Fostering innovation in public services.Public money and management, 25(1), 51-56.
II.Anthony, A., & Dorothea, H. (2013). From too little to too much innovation?Issues in measuring innovation in the public sector. Structural Change and Economic Dynamics, 27, 27(C), 146-159.
III.Arfeen , M. I., & Khan , P. N. (2009). Public Sector Innovation: Case study of e-government projects in Pakistan.The Pakistan Development Review,439-457.
IV.Arundel , A., Casali, L., & Hollanders, H. (2015). How European public sector agencies innovate: The use of bottom-up,policy-dependent and knowledge-scanning innovation methods.Research Policy, 44(7), 1271-1282.
V.Audretsch, D., & Demircioglu, M. (2017). Conditions for innovation in public sector organizations.Research Policy, 46(9), 1681-1691.
VI.Bommert, B. (2010). “Collaborative innovation in the public sector”.International Public Management Review
, 11(1),15-33.
VII.Bugge, M. M., & Bloch, C. (2016). Between bricolage and breakthroughs—framing the many faces of public sector innovation.Public Money & Management, 36(4), 281-288.
VIII.Butt, F. S., Rafique, T., Nawab, S., Khan, N. A., & Raza, A. (2013). Organizational Transformation in Public Sector Organizations of Pakistan in the Quest of Change Management.Research Journal of Applied Sciences,
Engineering and Technology, 6(16): 3086-3093.
IX.Chesbrough, H. (2003). “The logic of open innovation: managing intellectual property”. California Management Review, 45(3), 33-58.
X.Demircioglu, M. A. (2017). Conditions for innovation in public sector organizations. Research Policy
, 46(9), 1681-1691.
XI.Gallup Organization. (2011).Analytical Report – Innovation in Public Administration: Report.Gallup Organization.
XII.Gassmann, O. (2006). “Opening up the innovation process: towards an agenda”.R&D Management
, 36(3), 223-8.
XIII.Goodman, J. (2016). Robots in Law: How Artificial Intelligence is Transforming Legal Services.
Ark Group. ISBN 978-1-78358-264-8.
XIV.Iqbal, M. Z., Rehan, M., Fatima, A., & Nawab, S. (2017). The Impact of Organizational Justice on Employee Performance in Public Sector Organization of Pakistan.International Journal of Economics &
Management Sciences, (6)3, 1-6.
XV.Koch, P., & Hauknes, J. (2005). On innovation in the public sector – today and beyond. Oslo: Publin.
XVI.Lee, S. M., Hwang, T., & Choi, D. (2012). Lee, S. M., Hwang, T., & Choi, D. (2012). Open innovation in the public sector of leading countries.Management decision,. Management Decision, 50(1), 147-162.
XVII.Lopez, V., & Whitehead, D. (2013). Sampling data and data collection inqualitative research.Nursing and Midwifery Research: Methods and Critical Appraisal for Evidence-based Practice, 124-140.
XVIII.Luc, B., & Hafsi, T. (2007). The changing nature of public entrepreneurship. 67(3), 488-503.: Public Administration Review,.
XIX.Maranville, S. (1992). “Entrepreneurship in the Business Curriculum”. Journal of Education for Business.
, 68(1), 27–31.
XX.Ng, A. (2017, September 22). IBM’s Watson gives proper diagnosis after doctors were stumped. Newyork: NY Daily News.
XXI.OECD. (2014). Innovating the Public Sector: from Ideas to Impact. OECD Conference Centre, Paris
(pp. 1-40). Paris: OECD Conference Centre, Paris.
XXII.Palmer , C., & Kaderdina , F. (2017). Public sector innovation: From ideas to actions. UK: Ernst & Young Global Limited.
XXIII.Russell, S. J., & Norvig, P. (2009). Artificial Intelligence: A Modern Approach. Upper Saddle River, New Jersey: Prentice Hall. ISBN 0-13-604259-7.
XXIV.Sahni, N. R., Wessel, M., & Chr, C. M. (2013). Unleashing breakthrough innovation in government.
Stanford Soc. Innovation Rev, 11(3), 27-31.
XXV.Schweitzer, J. (. (2014). Leadership and innovation capability development in strategic alliances.
Leadership & Organization Development Journal, 35(5),442-469.
XXVI.Smith, S. (2013). Fundamentals of marketing research.Thousand Oaks, CA:SAGE Publications.
XXVII.Torugsa, N., & Arundel, A. (2017). Rethinking the effect of risk aversion on the benefits of service innovations in public administration agencies.Research Policy, (5), 900-910.
XXVIII.UNDP Pakistan. (2018, February). Governance Reforms and Innovation. Retrieved from SUSTAINABLE DEVELOPMENT GOALS: United Nations Development Programme:http://www.pk.undp.org/content/pakistan/en/home/operations/projects/democ ratic_governance/governance-reforms-and-innovation-.html
XXIX.Wynen Jan, Verhoest, K., Ongaro, E., & Thie, S. V. (2014). Innovation-oriented culture in the public sector: Do managerial autonomy and result control lead to innovation?Public Management Review
, 16(1), 45-66
View Download

VSM Based Models and Integration of Exact and Fuzzy Similarity For Improving Detection of External Textual Plagiarism

Authors:

Nasreen J. Kadhim, Mohannad T. Mohammed

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00041

Abstract:

A rapid growing has occurred for the act of plagiarism with the aid of Internet explosive growth wherein a massive volume of information offered with effortless use and access makes plagiarism − the process of taking someone else’s work (represented by ideas, or even words) and representing it as his own work − easy to be performed. For ensuring originality, detecting plagiarism has been massively necessitated in various areas so that the people who aim to plagiarize ought to offer considerable effort for introducing works centered on their research. In this paper, a work has been proposed for detecting textual plagiarism focused on proposing models for both candidate retrieval and detailed comparison phases. Firstly, for the candidate retrieval, two models have been proposed established on adopting the vector space method VSM as a retrieval model wherein these models base on offering different representations for text documents. The first model centers on representing documents as vectors consisting of average term 𝑡𝑓 − 𝑖𝑠𝑓 weights instead of representing them as vectors of term 𝑡𝑓 − 𝑖𝑑𝑓 weight. Whereas, the second retrieval model assigns for each term constituting the document a weight resulted from a weighted sum equation that sums this term 𝑡𝑓 − 𝑖𝑑𝑓 weight with its average 𝑡𝑓 − 𝑖𝑠𝑓 weights and considers it as a query for retrieval. The detailed comparison task comes as the second phase wherein a method has been proposed that cores at the integration of two diverse similarity measures and the introduction of one similarity measure involving them; Exact similarity and Fuzzy similarity. Experiments have been conducted using PAN-PC-10 as an evaluation dataset for evaluating the proposed system. As the problem statement in this paper is restricted to detect extrinsic plagiarism and works on English documents, experiments have been performed on the portion dedicated for extrinsic detection and on documents in English language only. These documents have been randomly separated into training and testing dataset. The training data has been used for parameters tuning whereas evaluating the performance of the proposed system and comparing it against the existing methods have been performed using testing dataset. For evaluating performance of the models proposed for the candidate retrieval problem, Precision, Recall, and F-measure have been used as an evaluation metrics. The overall performance of the proposed system has been assessed through the use of the five PAN standard measures Precision, Recall, F-measure, Granularity and 𝑃𝑙𝑎𝑔𝑑𝑒𝑡 . The experimental results has clarified that the proposed system either comparable or outperforms the other state-of-the-art methods.

Keywords:

VSM,TF-IDF, TF-ISF, exact similarit, Jaccard similarity, fuzzy similarity,

Refference:

I.A.Abdi, et al., A linguistic treatment for automatic external plagiarism detection. 2017. 135: p. 135-146.
II.A.Sarkar, U. Marjit, and U. Biswas. A conceptual model to develop an advanced plagiarism checking tool based on semantic matching. in 2014 2nd International Conference on Business and Information Management
(ICBIM). 2014. IEEE.
III.A.Abdi, et al., PDLK: Plagiarism detection using linguistic knowledge.2015. 42(22): p. 8936-8946.
IV.B.Gipp, Citation-based plagiarism detection, in Citation-based plagiarism detection. 2014, Springer. p. 57-88.
V.D.E.J.A.C.Appelt, Introduction to information extraction. 1999. 12(3): p.161-172.
VI.G.Oberreuter and J.D.J.E.S.w.A. VeláSquez, Text mining applied to plagiarism detection: The use of words for detecting deviations in the writing style. 2013. 40(9): p. 3756-3763.
VII.K.Vani and D. Gupta. Investigating the impact of combined similarity metrics and POS tagging in extrinsic text plagiarism detection system. in 2015 International Conference on Advances in Computing,
Communications and Informatics (ICACCI). 2015. IEEE.
VIII.L.Prechelt, G. Malpohl, and M.J.J.U. Philippsen, Finding plagiarisms among a set of programs with JPlag. 2002. 8(11): p. 1016-.
IX.M .Alzahrani, S, et al., Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model. 2015. 27(3): p. 248-268.
X.M.Roig, Avoiding plagiarism, self-plagiarism, and other questionable writing practices: A guide to ethical writing. 2006.
XI.M.Potthast, et al., Cross-language plagiarism detection. 2011. 45(1): p. 45-62.
XII.R.Lukashenko, V. Graudina, and J. Grundspenkis. Computer-based plagiarism detection methods and tools: an overview. in Proceedings of the 2007 international conference on Computer systems and
technologies. 2007. ACM.J. Mech. Cont.& Math. Sci., Vol.-14, No.-3, May-June (2019) pp 555-578
Copyright reserved © J. Mech. Cont.& Math. Sci.Nasreen J. Kadhim et al.578
XIII.S.Wang, et al. Combination of VSM and Jaccard coefficient for external plagiarism detection. in 2013 International Conference on Machine Learning and Cybernetics. 2013. IEEE.
XIV.S.Rao, et al., External & Intrinsic Plagiarism Detection: VSM &Discourse Markers based Approach Notebook for PAN at CLEF 2011.2011.
XV.S. Alzahrani and N. Salim, Fuzzy Semantic-Based String Similarity for Extrinsic Plagiarism Detection Lab Report for PAN at CLEF 2010.2010.
XVI.S.M.Alzahrani, et al., Understanding plagiarism linguistic patterns,textual features, and detection methods. 2012. 42(2): p. 133-149.
View Download

A Robust and Efficient Finger Print Combination form Privacy Protection

Authors:

Abdullah S. Alotaibi

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00042

Abstract:

Now a day’s fingerprint techniques are widely used in authentication systems, therefore its privacy protection becomes an important issue. Securing a stored fingerprint template is very important because once fingerprints are compromised, it cannot be easily revoked. So, we review here a new system for preserving fingerprint confidentiality. In this system, the fingerprint privacy is maintained by combining two special fingerprints keen on a original identity. In the enlistment phase, two fingerprints need aid taken from two different fingers. We acquire the minutiae positions about one fingerprint, the introduction from claiming another fingerprint, and the reference focuses starting with both fingerprints. In view of those gotten information, a joined minutiae format may be created Also saved previously, a database. In the Confirmation phase, we utilize the fingerprints of the same fingers that need aid at that point utilized within enlistment stage. For same 2 finger prints against a mutual minutiae template, a two-stage fingerprint matching process is used. By storing the combined minutiae template in the database, the complete minutiae characteristic of a single fingerprint will not be compromised when the database is stolen by the attackers. The joined minutiae format will be changed over under a real-look indistinguishable joined together finger impression by utilizing existing finger impression reproduction approach. These effects under another virtual character to those two different fingerprints.

Keywords:

Fingerprint,Combination,Protection,Minutiae,Privacy ,

Refference:

I.A. Kong, K.-H. Cheung, D. Zhang, M. Kamel, and J. You, “An analysis of biohashing and its variants,” Pattern Recognit., vol. 39, no. 7, pp. 1359–1368,2006.
II.A. Nagar, K. Nandakumar, and A. K. Jain, “Biometric template transforma- tion: A security analysis,” in Proc. SPIE, Electron. Imaging, Media Forensics and Security, San Jose, Jan. 2010.
III.A. Othman and A. Ross, “Mixing fingerprints for generating virtual identi- ties,” in Proc. IEEE Int. Workshop on Inform. Forensics and Security (WIFS),Foz do Iguacu, Brazil, Nov. 29–Dec. 2, 2011.
IV.A. Ross and A. Othman, “Mixing fingerprints for template security and priva-cy,” in Proc. 19th Eur. Signal Proc. Conf. (EUSIPCO), Barcelona, Spain, Aug.29–Sep. 2, 2011.
V.B. Yanikoglu and A. Kholmatov, “Combining multiple biometrics to protect privacy,” in Proc. ICPR- BCTP Workshop, Cambridge, U.K., Aug. 2004.
VI.B. J. A. Teoh, C. L. D. Ngo, and A. Goh, “Biohashing: Two factor authentica-tion featuring fingerprint data and tokenised random number,” Pattern Recog-nit., vol. 37, no. 11, pp. 2245–2255, 2004.
VII.E. Camlikaya, A. Kholmatov, and B. Yanikoglu, “Multi-biometric templates using fingerprint and voice,” Proc. SPIE, vol. 69440I, pp. 69440I-1–69440I-9,2008.
VIII.K. G. Larkin and P. A. Fletcher, “A coherent framework for fingerprint analy-sis: Are fingerprints holograms?,” Opt. Express, vol. 15, pp. 8667–8677, 2007.
IX.K. Nandakumar, A. K. Jain, and S. Pankanti, “Fingerprint-based fuzzy vault:Implementation and performance,” IEEE Trans. Inf. Forensics Security, vol. 2,no. 4, pp. 744–57, Dec. 2007.
X.N. K. Ratha, S. Chikkerur, J. H. Connell, and R. M. Bolle, “Generating can-celable fingerprint templates,” IEEE Trans. Pattern Anal. Mach. Intell., vol.29, no. 4, pp. 561–72, Apr. 2007
XI.S. Li and A. C. Kot, “A novel system for fingerprint privacy protection,” in Proc. 7th Int. Conf. Inform. Assurance and Security (IAS), Dec. 5–8, 2011, pp.262–266.
XII.S. Li and A. C. Kot, “Privacy protection of fingerprint database,” IEEE Signal Process. Lett., vol. 18, no. 2, pp. 115–118, Feb. 2011. [9] A. Ross and A.Othman, “Visual cryptography for biometric privacy,” IEEE Trans. Inf. Fo-rensics Security, vol. 6, no. 1, pp. 70–81,Mar. 2011.
XIII.S. Li and A. C. Kot, “Attack using reconstructed fingerprint,” in Proc. IEEE Int. Workshop on Inform. Forensics and Security (WIFS), Foz do Iguacu, Bra-zil, Nov. 29–Dec. 2, 2011.
XIV.W. J. Scheirer and T. E. Boult, “Cracking fuzzy vaults and biometric encryp-tion,” in Proc. Biometrics Symp., Sep. 2007, pp. 34–39.
View Download

Protein sequence comparison under a new complex representation of amino acids based on their physio-chemical properties

Authors:

Jayanta Pal, Soumen Ghosh, Bansibadan Maji , Dilip Kumar Bhattacharya

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00043

Abstract:

The paper first considers a new complex representation of amino acids of which the real parts and imaginary parts are taken respectively from hydrophilic properties and residue volumes of amino acids. Then it applies complex Fourier transform on the represented sequence of complex numbers to obtain the spectrum in the frequency domain. By using the method of ‘Inter coefficient distances’ on the spectrum obtained, it constructs phylogenetic trees of different Protein sequences. Finally on the basis of such phylogenetic trees pair wise comparison is made for such Protein sequences. The paper also obtains pair wise comparison of the same protein sequences following the same method but based on a known complex representation of amino acids, where the real and imaginary parts refer to hydrophobicity properties and residue volumes of the amino acids respectively. The results of the two methods are now compared with those of the same sequences obtained earlier by other methods. It is found that both the methods are workable, further the new complex representation is better compared to the earlier one. This shows that the hydrophilic property (polarity) is a better choice than hydrophobic property of amino acids especially in protein sequence comparison.

Keywords:

omplex Representatio, DFT, Hydrophobicity Proper,Hydrophilicity (Polarity) Property,ICD; Phylogenetic Tree,Voss Representation,

Refference:

I.K. Brodzik, and 0. Peters, “Symbol-balanced quaternionic periodicity transform for latent pattern detection in DNA sequences,”in Proc. IEEE ICASSP, vol. 5, pp. 373-376, 2005.
II.B. D. Silverman, and R. Linsker, “A measure of DNA periodicity,” J. Theor. Biol., vol. 118, pp. 295-300, 1986.
III.Changchuan Yin and Stephen S. –T. Yau, Numerical representation of DNA sequences Based on Genetic Code Context and its applications in Periodicity Analysis Genomes- 978-1—1779-7/08/$25.00@2008 IEEE
IV.D. Anastassiou, Frequency-domain analysis of bimolecular sequences, Bioinformatics, vol.16, no.4, pp. 1073-1081, 2000.
V.D. Anastassiou, “Genomic signal processing,” IEEE Signal Proc.Mag., vol. 18, no. 4, pp. 8-20, July 2001.
VI.D. E. Godsack and R. C. Chalifoux, Contribution of the free energy of mixing hydrophobic side chains to the stability of the tertiary structure, Journal of Theoretical Biology vol. 39, pp. 645-651, 1973.
VII.Ghosh, S., Pal, J. S. Das and Bhattacharya, D.K (2015)-Biological and Theoretical Classifications of Amino Acids in Six Groups. International Journal of Computer Science and Software Engineering, 5, 695-698.
VIII.Ghosh, S., Pal, J. and Bhattacharya, D.K. (2014) Classification of Amino Acids of a Protein on the Basis of Fuzzy Set Theory. International Journal of Modern Sciences and Engineering Technology, 1, 30-35.
IX.G. L. Rosen, “Signal processing for biologically-inspired gradient source localization and DNA sequence analysis,” PhD thesis, Georgia Institute of Technology, Aug. 2006.
X.J. Ning, C. N. Moore, and J. C. Nelson, “Preliminary wavelet analysis of genomic sequences,” in Proc. IEEE Bioinformatics Conf (CSB), pp. 509-510, August 2003.
XI.King, B.R., Aburdene, M., Thompson, A. and Warres, Z. (2014) Application of Discrete Fourier Inter-Coefficient Difference for Assessing Genetic Sequence Similarity.EURASIP Journal on Bioinformatics and
Systems Biology, 2014, 8.
XII.M. Elloumi et al. (Eds.) “Complex Representation of DNA Sequences by Carlo Cattani”, BIRD 2008, CCIS 13, pp. 528–537, 2008._c Springer- Verlag Berlin Heidelberg 2008.
XIII.N. Chakravarthy, A. Spanias, L. D. lasemidis, and K. Tsakalis,”Autoregressive modeling and feature analysis of DNA sequences,”EURASIP JASP, vol. 1, pp. 13-28, 2004.

XIV.Pal, J., Ghosh, S., Maji, B. and Bhattacharya, D.K. (2016) Use of FFT in Protein Sequence Comparison under Their Binary Representations.Computational Molecular Bioscience, 6, 33-40.http://dx.doi.org/10.4236/cmb.2016.62003
IV.P. Argos, J.K.M.Rao and P.A.Hargrave, structural prediction of membrane bound proteins, Eur.J.Biochevol.128, pp. 565-575,1982.
XVI.P. D. Cristea, “Genetic signal representation and analysis,” in Proc. SPIE Conference, International Biomedical Optics Symposium (BIOS’02), vol.4623, pp. 77-84, 2002.
XVII.R. F. Voss, “Evolution of long-range fractal correlations and 1/f noise in DNA base sequences,” Phy. Rev. Lett., vol. 68, no. 25, pp. 3805-3808,June 1992
XVIII.R. Zhang, and C. T. Zhang, “Z curves, an intuitive tool for visualizing and analyzing the DNA sequences,” J. Biomol. Struct. Dyn.,vol. 11, no. 4, pp. 767-782, February 1994.
XIX.Tung Hoang, Changchuan Yin, Hui Zheng, Chenglong YU, Rong Lucy He, Stephen S, T. Tay – A new method to cluster DNA sequences using Fourier power spectrum- Journal of Theoretical Biology- 372 (2015), 135-145.
View Download

Effect of Thin Layer on Bearing Capacity in Layered Profile Soil

Authors:

Abdul Farhan, Farman Ullah, Fawad Ahmad, Mehr E Munir

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00044

Abstract:

Bearing capacity is the main criteria for designing the foundation of a structure. Several theories and experimental methods have been propounded by many researchers for computing the bearing capacity parameters separately. Traditional bearing capacity theories for determining the ultimate bearing capacity of shallow foundations assume that the bearing stratum is homogenous and infinite. However this is not true in all cases. Layered soils are mostly encountered in practice. It is possible to encounter a rigid layer at shallow depth or the soil may be layered and have different shear strength parameters. In such cases shear pattern gets distorted and bearing capacity becomes dependent on the extent of the rupture surface in weaker or stronger material. The best estimation of bearing capacity on layered soil are possible only, if the pressure-settlement characteristics of the foundation-soil are known for the size of the footing. From the review of literature, it may be noted that the bearing capacity equations proposed for the homogenous soils by Terzaghi (1943) and Meyerhof (1951) are not applicable to layered soils. Hence it is necessary to develop an equation for predicting the bearing capacity of granular layered soils. In present investigation, plate load test have been conducted in a large tank to observe the load settlement behavior of plates of different sizes resting on layered granular soils. Tests were conducted on two layers of soils. Fine gravel layer overlain sand layer were tested using mild steel plates of square shapes. The effect of the placement of layers on the bearing capacity characteristics of footing, has been studied and an equation for predicting the bearing capacity of two layered granular soils is developed based on the plate load test data.

Keywords:

Bearing capacity,plate load test,

Refference:

I.Hanna A. M. Bearing Capacity of Foundations on a Weak Sand Layer Overlaying a Strong Deposit, Canadian Geotechnical Journal, 1982: 392-396.
II.Hanna, A.M., and Meyerhof G.G. (1980), “Design charts for ultimate bearing capacity of foundations on sand overlying soft clay”. Can. Geotech.J, 17(2). 300-303.
III.Meyerhof, G. G. Hanna A. M. Design Charts for Ultimate Bearing Capacity of Foundations on Sand Overlaying Soft Clay. Canadian Geotechnical Journal, 1980, 17: 300-303.
IV.Michalowski, R.L. (1997). An estimate of the influence of soil weight on bearing Capacity using limit analysis. Soils and Foundations, Vol. 37, No.4, pp. 57-64.
V.Meyerhof, G. G. & Hanna, A. M. (1978), ultimate bearing capacity of foundations on layered soils under inclined load. Canadian Geotechnical Journal, vol. 15, n. 4, pp. 565-572.
VI.Srivastava, A.K. (1982), Relevance of small scale model tests for estimating load settlement behavior of footings on sand.” M.Tech dissertation.
VII.Terzaghi, k. and Peck, R. B. (1967) Soil Mechanics in Engineering Practice, 2nd edition John Wiley and Sons Inc, New York, USA.
VIII.Valsangkar A. J, Meyerhof, G. G. Experimental Study of Punching Coefficients and Shape Factor for Two Layered Soils. Canadian Geotechnical Journal, 1979, 16: 802-805.
IX.Varghese P.C., A text Book of Foundation Engineering, Prentice Hall of India Pvt. Ltd., New Delhi, Edition 2005
View Download

Bin the Case Bifurcation and Chaos of Logistic Maps with Three Parameters and its Applications

Authors:

Asia Ali Mohammed, Assistant Prof. Radhi A. Zaboon

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00045

Abstract:

In this paper, the generalization of logistic discrete dynamic systems with three parameters have been analyzed with the necessary mathematical requirements and proofs. The dynamics and the qualitative properties of the fixed points and their stability, the bin the case bifurcation diagram and chaos have proposed with application.

Keywords:

fixed point ,stability,bin the case bifurcation diagram,periodic point,

Refference:

I.A. Ferrettia, N. K. Rahman , “A study of Coupled Logistic Map and Its Applications in Chemical Pysics” , Chemical Pysics,vol.119 , no.2-3, pp: 275-288,1988.
II.C.Robiason, “Dynamical System. Stability , Symbolic Dynamics and Chaos “, second edition ,CRC Press Boca Ration.Florida,1999.
III.C. Pellicer –Lostao , R. Lpez – Ruiz,”A Chaotic gas- like Model for Trading Markets “,Journal of Computational Science,vol.1, no.1, pp: 24- 32,2010.
IV.D.Gulick, ” Encounters with Chaos “, McGraw Hill, 1990.
V.F .G. Alvarez, Monotoya, G. Pastor, and M. Romera,” Chaotic cryptosystems”, In Proceedings of IEEE International Carnahan Conference on Security Technology, pp: 332-338, 1999.
VI.G.Geoffrey . ,”Chaotic Dynamics; Fractals, Tilings and Substitutions”,Towson University Mathematics Department, 2015.
VII.G. Jakimoski, and L. Kocarev, “Chaos and cryptography: Block encryption ciphers based on chaotic maps “, IEEE Transactionson Circuits and Systems-I: Fundamental Theory and Applications, vol. 48, no.2,
pp:163-169, 2001.
VIII.G. R.Ahmed ,”On Some Generalized Discrete Logistic Maps” , Journal of Advance Research , vol.4, no.2, pp:163-171,2013.
IX.H. R.Biswas, “One Dimensional Chaotic Dynamical Systems “, Journal of Pure and Applied Mathematics :Advance andApplications , Vol. 10, no.0, pp: 69-101, 2013.
X.I.Sajid ,R.Muhammad ,I.Shahaid ,O.Muhammad , A. S.Hadeed,”Study of Nonlinear Dynamics Using Logistic Map”, LUMS 2nd International Conference on Mathematics and its Applications in Information Technology (LICM08), 2008.
XI.K. Pareeka .N.VinodPatidara ,K . K. Sud ,” Image Encryption Using Chaotic Logistic Map ” ,Image and Vision Computing , vol. 24, no.9, pp: 926-934,2006.
XII.M. SBaptista, ” Cryptography with chaos”, Physics Letters A. Vol. 240, no.1-2, pp: 50-54, 1998.
XIII.R.Klages ,” Applied Dynamical System”, Lectures 5-10 From Deterministic Chaos to Deterministic Din the case offusion, Rainer Klages, QMUL,2010
XIV.R.A.J.Matthews ” On the Derivation of a Chaotic Encryption Algorithm”. Cryptologia, vol.13, no.1, pp: 29-42, 1989.
XV.R. L. Devaney, L. Keen ,”Chaos and Fractals :The Mathematics Behind The Computer Graphics “, American Mathematical Society ,Providence, 1989.
XVI.R. Rak, E. Rak ,” Route to Chaos in Generalized Logistic Map” , Faculty of Mathematics and Natural Science ,University of Rezesow , PL-35-45, Rezesow ,Poland ,2015.
XVII.S. Sternberg. “The Perron-Frobenius Theorem”, Dynamical Systems, pp: 175-195, 2011.
XVIII.T. Habutsu, Y. Nishio, I. Sasase, and S. Mori, “A secret key cryptosystem by iterating a chaotic map”, Advances in Cryptology:Proceedings of EUROCRYPT 91, LNCS 547, Berlin:Springer-Verlag, pp: 127-140, 1991.
XIX.T. –Y. Li and J .York ” Period Three Implies Chaos ” , American Mathematical Monthly, vol.82, no.10, pp: 985-992,1975.
XX.W .Xiangjun ,Haibin K. , Jürgen K. , ” A New Color Image Encryption Scheme Based on DNA Sequences and Multiple Improved 1D Chaotic Maps ” , Contents lists available at Science Direct Applied Soft
Computing journal homepage : www.elsevier.com/locate/asoc,2015.
XXI.Z. Kotulski, and J. Szczepanski, ” Discrete chaotic cryptography”, Annalen der Physik, vol. 509, no.5, pp: 381-394, 1997.
XXII.Z. L. Zhou ,” Symbolic Dynamics (chinsi)” , Shanghai Scientin the case ofic and Technology Education Publish House Shanghai, 1997.
View Download

Peer Tutoring Activities To Support Active Learning In Mathematics: Review of The Effects on Student’s Thinking and Metacognitive Skills

Authors:

Mohamad Ariffin Abu Bakar, Norulhuda Ismail

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00046

Abstract:

Mastery of mathematics is an overview of the accuracy of mathematics competency. It is a tremendous impact on well development and complete trained metacognition skills and thinking skills. Therefore, to ensure that students can understand mathematics well is through learning that can enhance and develop metacognitive skills and thinking skills. In order to reduce the weakness of mathematical mastery, one of the interventions is through active and meaningful learning. Active learning focuses on student engagement, interactive, retention and motivation to explore the learning. Through this review, peer tutoring is subject matter to discuss the ability to support active learning and evaluate the effectiveness of peer tutoring activities among students in developing metacognitive skills and thinking skills. A review of previous research through search in database likes Google Scholar, Science Direct, ERIC, Springer Link, Elsevier and several other databases, based on keywords has been implemented. A number of articles and journals have been systematically reviewed to answer questions in this literature study. However, just 13 articles and journals published in 2012 until the current year are selected for this review. Briefly, the constructs and themes in peer tutoring contribute to forming active learning that can lead to increased student thinking and metacognitive skills.

Keywords:

Peer Tutoring,Metacognitive Skil,Thinking Skil,Active Learning,Mathematics Mastery,

Refference:

I.A.B. Festus, “Activity-Based Learning Strategies in the Mathematics Classrooms”. Journal of Education and Practice.Vol.4, No.13,2013
II.A. Ansuategui, F. Jose, M. Miravet, &Lidon “Emotional and Cognitive Effects of Peer Tutoring among Secondary School Mathematics Students”.International Journal of Mathematical Education in Science and
Technology.Vol 48,n8,pp 1185-1205,2017
III.Adnan &ArsadBahri. “Beyond Effective Teaching: Enhancing Students’ Metacognitive Skill Through Guided Inquiry”. IOP Publishing .Journal of Physics: Conf. Series 954 (2018) 012022 doi :10.1088/1742-
6596/954/1/012022,2018.
IV.A. Elliot, “Metacognitive Teaching Strategies And Young Children’s Mathematical Learning”. Proceeding Of Australian Association for Research in Education Conference, AARE.Fremantle,1993
V.B. BozYaman, “A Multiple Case Study: What Happens In Peer Tutoring Of Calculus Studies?”.International Journal of Education in Mathematics,Science and Technology (IJEMST).7(1), 53-72.
Doi:10.18404/ijemst.328336,2019
VI.B. Hott, & J. Walker, “Peer Tutoring. Council for Learning Disabilities”.Retrived from : https://council-for-learning-disabilities.org/peer- tutoring-flexible-peer-mediated-strategy-that-involves-students-serving-as-
academic-tutors, 2012
VII.D. Al Kharusi, “What Positive Impacts Does Peer Tutoring Have Upon The Peer Tutors at SQU?”.Journal of Education and Practice.Vol.7, No.27, 2016.
VIII.D.S. Benders, “The Effect of Flexible Small Groups on Math Achievement in First Grade”. An On-line Journal forTeacherResearch.Vol. 18, Issue 1.Issn 2470-6353.Spring,2016
IX.F. Acar, & E. Ader.”Metacognition Used By Tutors During Peer Tutoring Sessions In Mathematics”.Elementary Education Online.2017; 16(3),pp 1185-1200,2017
X.F.U. Rahman, N.B. Jumani, M.A. Chaudry, S.U.H. Chisti, & F. Abbasi, “Impact Of Metacognitive Awareness On Performance Of Students In Chemistry”. Contemporary Issues In Education Research.Vol 3, No10,2010
XI.G. Pilten, “The Evaluation of Effectiveness of Reciprocal Teaching Strategieson Comprehension of Expository Texts”. Journal of Education and Training Studies.Vol. 4, No. 10; October 2016. Doi:10.11114/jets.v4i10.1791,2016
XII.G. Schraw, & D. Moshman, (1995) . Metacognitive Theories. Educational Psychology Papers and Publications. 40. Retrieved From : http://digitalcommons.unl.edu/edpsychpapers/40 1995
XIII.H.C. Celik, “The Effects of Activity Based Learning on Sixth Grade Students’ Achievement and Attitudes towards Mathematics Activities”.EURASIA Journal of Mathematics, Science and Technology Education,
2018, 14(5), 1963-1977,2018
XIV.H.C. Chu, J.M. Chen, & C.L. Tsai, “Effects of an Online Formative Peer-Tutoring Approach on Students’ Learning Behaviours, Performance and Cognitive Load in Mathematics”.Interactive Learning Environments.Vol
25,n2, pp 203-219,2017
XV.I. Amin, & Y.L. Sukestiyarno, “Analysis Metacognitive Skills On Learning Mathematics In High School”. International Journal of Education and Research.Vol. 3 No. 3 March 2015.
XVI.I. Coskun, & C. Eker, “The Effect Of Teaching Activities Done By Using Activity Based Posters On The Students’ Academic Achievements, Retention Levels In Their Learning”. Universal Journal of Educational Research 6(4): 585-597, 2018. Doi: 10.13189/ujer.2018.060402,2018
XVII.I. Ullah, R. Tabassum, & M. Kaleem, “Effects of Peer Tutoring on the Academic Achievement of Students in the Subject of Biology at Secondary Level”.Educ. Sci. 2018, 8, 112; Doi:10.3390/educsci8030112,2018
XVIII.J.M. Smith, & R. Mancy, “Exploring The Relationship Between Metacognitive And Collaborative Talk During Group Mathematical Problem- Solving – What Do We Mean By Collaborative Metacognition?”, Research in Mathematics Education, 20:1, pp 14-36, Doi:10.1080/ 4794802.2017.1410215,2018
XIX.K. Arrand, “Peer Tutoring”.Journal Pedagogic Development.Volume 4 Issue 1,2014
XX.K. Findley, I. Whitacre, & K. Hensberry, “Integrating Interactive Simulations Into The Mathematics Classroom: Supplementing, Enhancing, Or Driving?” In Galindo, E., & Newton, J., (Eds.). (2017). Proceedings of the 39th Annua
View Download

Using Increased Section Thickness to Gain Inherent Fire Protection in Single Span Portal Frames

Authors:

Nasir Khan, Muhammad Hasnain, Shabbir Ahmad, Fawad Khan, Sharifullah khan

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00047

Abstract:

All over the world, different designs are used for construction of any type of structure. The Structure is design with mutual understanding of structure and architecture engineer to make structure stable and having an attractive look for the people. Beside this one of most essential component which must be installed in any type of structure is fire protection. To enhance the stanchions thickness in single span portal frame structures with fire boundary conditions cost analysis examine in this study. More ever this study also investigates to gain an inherent fire protection for fire resistance design periods. Using this method the cost is compared with common techniques for fire protection such as applying intumescent coating to frame members. In this study for conducting the analysis a portal type frame structure was designed. Different tests are conduct on the design portal frame structure and it is concluded that for fire resistance using the increase thickness of section is economical of fire protection while the design period is up to 30 minutes. Using the inherent protection method against the application intumescent coating for a period of 30 minutes more than 21% energy is saved. Significant cost of saving recorded in a project having large scale construction.

Keywords:

Fire Protection, Fire boundary condition,intumescent coating,Porta frame structure,Stanchions thickness,

Refference:

I.BOLLUM (Undated). (1987).“Technical Data Sheet Bm066 Fireshield Ultra Universal.” Vertical Column Loading Table.
II.BRITISH STANDARDS INSTITUTION. (2003).”Structural use of steelwork in building – Part 8: Code of practice for fire resistant design.”
III.BUILDING REGULATIONS. (2010). “Fire Safety Buildings Other than Dwelling houses.” Approved Document B Volume 2
IV.CORUS. (2006). “Fire resistance of steel-framed buildings 2006 Edition, Section factor and protection thickness assessment.”
V.HSE. (2012a). “Active Fire Protection.” [Online] Available at: http://www.hse.gov.uk/comah/sragtech/techmeasfire.htm [Accessed 16.11.12]
VI.MDM PUBLISHING. (2012).”Intumescent coating.” [Online] Available at: http://www.mdmpublishing.com/mdmmagazines/magazineifp/newsview/436/ how-to-minimise-the-fire-risk-to-structural-steel
[Accessed 18.10.12].
VII.MONGABAY.(2012). [Online] Available at: http://population.mongabay.com/population/united
kingdom/2641170/nottingham [Accessed 08.01.13]
VIII.SPRAYFINE. (2012). “Passive fire protection.” [Online] Available at: http://www.sprayfine.ltd.uk/treatments/fireprotection.php [Accessed 16.10.12]
IX.STEEL CONSTRUCTION INSTITUTE. (2002). “Single Storey Steel Framed Buildings in Fire Boundary Conditions”.
X.STEEL CONSTRUCTION INSTITUTE. (2004). “Design of Single-Span Steel Portal Frames.” BS 5950-1:2000
View Download

Artificial Intelligence – Machine Learning based Mental Health Diagnosis Automation

Authors:

F. Catherine Tamilarasi, J. Shanmugam

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00048

Abstract:

Mental health of human being is more important parameter and any deficit or issue needs faster diagnosis. In this aspect Medical Image Analysis and psychology have become a promising application domain for Machine Learning (ML) which facilitates an intelligent decision support system for diagnosis.

Keywords:

Artificial Intelligence, Deep Learnin, Neural Network, Machin learning,Working Memory,

Refference:

I. Bhaskar Sen, Neil C. Borle, Russell Greiner, Matthew R. G. Brown,” A general prediction model for the detection of ADHD and Autism using structural and functional MRI “, PLoS ONE 13(4): e0194856.
II.D van der Meer, PJ Hoekstra, M van Donkelaar, J Bralten, J Oosterlaan, D Heslenfeld, SV Faraone, B Franke, JK Buitelaar and CA Hartman, “Predicting attention-deficit/hyperactivity disorder severity from
psychosocial stress and stress-response genes: a random forest regression approach”, Translational Psychiatry (2017) 7, e1145; doi:10.1038/tp.2017.114; published online 6 June 2017
III.Daniel S. Margulies and Simon B. Eickhoff ,” Functional Segregation of the Right Inferior Frontal Gyrus: Evidence From Coactivation-Based Parcellation”, Cerebral Cortex, bhy049, https://doi.org/10.1093/cercor/bhy049
IV. doi: 10.1016/j.ijpsycho.2013.01.008. Epub 2013
V. DP Wall, J Kosmicki, TF DeLuca, E Harstad and VA Fusaro1,” Use of machine learning to shorten observation-based screening and diagnosis of autism”, Translational Psychiatry (2012) 2, e100;
doi:10.1038/tp.2012.10; published online 10 April 2012
VI. Gesa Hartwigsen , Nicole E. Neef, Julia A. Camilleri,
VII. https://doi.org/10.1371/journal.pone.0194856
VIII. https://doi.org/10.1371/journal.pone.0194856 , April 17, 2018
IX. JA Kosmicki , V Sochat , M Duda and DP Wall,” Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning”, Translational Psychiatry (2015) 5, e514;
doi:10.1038/tp.2015.7; published online 24 February 2015
X. JA Kosmicki, V Sochat, M Duda and DP Wall, “Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning”, Transl Psychiatry (2015) 5, e514;
doi:10.1038/tp.2015.7
XI. Jan 27. PMID:23361114
XII. Kartick Subramanian, Sundaram Suresh, “Importance of phenotypic information in ADHD diagnosis”, March 2015
https://www.researchgate.net/publication/276848476 Conference Paper ·
DOI: 10.1109/CCIP.2015.7100722
XIII.
M Duda, R Ma, N Haber and DP Wall, “Use of machine learning for
behavioral distinction of autism and ADHD”, Translational Psychiatry
(2016) 6, e732; doi:10.1038/tp.2015.221; published online 9 February
2016
XIV.
Published: 18 April 2018
XV.
Pulkit Agrawal, Dustin Stansbury, Jitendra Malik, Jack L. Gallant,”
Pixels to Voxels: Modeling Visual Representation in the Human Brain”,
View Download

AN OVERVIEW TOWARDS THE TIP-RUBBING EVENT AND USAGE OF ABRADABLE MATERIALS TO MINIMIZE THE OCCURRENCE OF TIP-RUBBING

Authors:

Ch. Vinay Kumar Reddy, I. Rajasri

DOI NO:

https://doi.org/10.26782/jmcms.2019.06.00049

Abstract:

There has actually been a considerable rise in air traffic quantity, especially over the previous twenty years. In order to handle this boost popular, it has actually been needed to raise the effectiveness of airplane engines. For many years, this has actually been accomplished by minimizing the clearance in between blade tips and also the engine casing. Consequently, of the minimized clearance, tip-rubbing often takes place in the engine throughout the procedure. In this paper, a short intro to the tip-rubbing occasion as well as associated prices to the sector, and also just how abradable products are utilized to decrease the incident of tip-rubbing are pointed out. The Rolls-Royce Trent 900 engine and also the 2nd phase compressor area are explained briefly.

Keywords:

tip-rubbing,Rolls-Royce Trent 900 engine,Blade-Casing,

Refference:

I.AircraftAccidentReport–NationalAirlines,Inc.DC-10-10,N60NA,Near
Albuquerque,NewMexico,November3,1973,(1975),NTSB-AAR-75-2,
NationalTransportationSafetyBoard,Washington,D.C.20591.
II.AircraftAccidentReport–In-FlightEngineSeparationJapanAirlines,Inc,
Flight 46e Boeing 747-121, (1993), NTSB/AAR-93/06, National
TransportationSafetyBoard,Washington,D.C.20594.
III.Aidanpää,J.andLindkvist,G.(2010),”DynamicsofaRubbingJeffcottRotor
withThreeBlades”,ProceedingsoftheThirdChaoticModelingandSimulation
InternationalConference,1-4June2010,Chania,Crete,Greece.
IV.AustralianTransportSafetyBureau(2008),In-flightenginefailure,Sydney,
BoeingCompany747-438,VH-OJM,03February2007,200700356.
V.Chu,F.andLu,W.(2007),”Stiffeningeffectoftherotorduringtherotor-to-
statorrubinarotatingmachine”,JournalofSoundandVibration,vol.308,no.
3-5,pp.758-766.
VI.ContactModellinginLS-DYNA-ContactParameters(2001),availableat:http://www.dynasupport.com/tutorial/contact-modeling-in-ls-dyna/contact-parameters (accessed20/09/2011).
VII.Dai,X.,Jin,Z.andZhang,X.(2002),”Dynamicbehaviourofthefullrotor/stoprubbing”,JournalofSoundandVibration,vol.251,no.5,pp.807-822.
VIII.DeRyck,H.(2008),TurbofanDesignfortheCommercialAircraft,Warsaw
University of Technology, Warsaw,Poland.
IX.Dinardo, J. E. (2009), Signal Processing Techniques for Nonlinearity IdentificationofStructuresUsingTransientResponse(MasterofScience thesis),UniversityofMissouri,Missouri,USA.
X.LS-DYNATheoryManual(2006),LivermoreSoftwareTechnology Corporation, Livermore, California94551.
XI. LS-DYNAKeywordUser’sManual(2007),Version971ed.,LivermoreSoftware
Technology Corporation, Livermore, California94551.
XII.Virgin Driver (2010), available at: http://virginflightdeck.blogspot.com/
(accessed11/11/2011).
View Download