Archive

Abstract:

Retinal image analysis has gained a significant research interest due to its widespread applicability in the diagnosis of different eye related diseases. This paper focused in the analysis of Diabetic Retinopathy through different features (Optic Disk, Retinal Vessels, and Exudates etc.,) of retinal image. Towards this objective, a new Retinal Vessel Segmentation mechanism is introduced in this paper. The proposed mechanism accomplished the Gabor Filter for Feature Extraction and Support Vector Machine Algorithm for classification. Here the Gabor Filter ensures a more resilience to the scaling and orientation issues in the retinal image. Afterwards, a feature set consists of thirteen features is extracted from retinal image to provide a proper differentiation between the image pixels and background pixels. Based on these features, the SVM classifier classifies the vessel pixels and background pixels more effectively which improves the classification accuracy and reduces false positive rate. An extensive simulation carried out over the proposed approach through two standard datasets, DRIVE and STARE reveals the outstanding performance with respect to the performance metrics sensitivity, specificity and accuracy.

Keywords:

retinal vessel segmentation,Gabor filter,Support vector machine,Gradient features,Correlation Accuracy,

Refference:

I. A. Bhuiyan, B. Nath, J. Chua, and R. Kotagiri, “Blood vessel
segmentation from color retinal images using unsupervised texture
classification,” in 2007 IEEE International Conference on Image
Processing, vol. 5, pp. 521–524, 2007.
II. A. Budai, G. Michelson, and J. Hornegger, “Multiscale blood vessel
segmentation in retinal fundus
images,” Proc. Bildverarbeitungfr die Med., pp. 261–265, March 2010.
III. A. Budai, R. Bock, A. Maier, J. Hornegger, and G. Michelson, “Robust
vessel segmentation in fundus images,” International Journal of
Biomedical Imaging, no. 154860, 2013.
IV. A.Fathi, A.R.N Naghsh-Nilchi, Automatic wavelet-based retinal blood
vessels segmentation and vessel diameter estimation ,Biomed. Signal
Process. Control 8(1)(2013) 71-80
V. A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever,
“Multiscale vessel enhancement filtering,” in International Conference on
Medical Image Computing and Computer- Assisted Intervention, pp.
130–137, Springer, Berlin Heidelberg, 1998.
VI. A. Hoover, “Locating blood vessels in retinal images by piecewise
threshold probing of a matched filter response,” IEEE Transactions on
Medical Imaging, vol. 19, no. 3, pp. 203–210, 2000.
VII. A.Hoover, Structured Analysis of the Retina
STARE,http://www.ces.clemson.edu/~ahoover/stare/, 2015.
VIII. B D Barkana, “Performance analysis of descriptive statistical features in
retinal vessel segmentation via fuzzy logic, ANN, SVM, and classifier
fusion”, Knowledge-Based Systems, Volume 118, 15February 2017,
Pages 165-176
IX. B.R. Mcclintic, J.I. Mcclintic, B.S. Ba, J.D. Bisognano, R.C. Block, A
relationship between microvascular abnormalities and coronary disease –
a review, Am. J. Med. 123 (4) (2011) 1–12.

X. D. Marin, A. Aquino, M. Gegundez-Arias, and J. Bravo, “A new
supervised method for blood vessel segmentation in retinal images by
using gray-level and moment invariants-based features,” IEEE
Transactions on Medical Imaging, vol. 30, no. 1, pp. 146–158, 2011.
XI. F. Zana and J. C. Klein, “Segmentation of vessel-like pattern using
mathematical morphology and curvature evaluation,” IEEE Transactions
on Image Processing, vol. 10, no. 7, pp. 1010–1019, 2001.
XII. G. Azzopardi, N. Strisciuglio, M. Vento, and N. Petkov, “Trainable
COSFIRE filters for vessel delineation with application to retinal
images,” Med. Image Anal., vol. 19, no. 1, pp. 46–57, 2015.
XIII. G. B. Kande, P. V. Subbaiah, and T. S. Savithri, “Unsupervised fuzzy
based vessel segmentation in pathological digital fundus images,” Journal
of Medical Systems, vol. 34, no. 5, pp. 849–858, 2010.
XIV. Liskowski P, Krawiec K. Segmenting Retinal Blood Vessels with Deep
Neural Networks. IEEE Transactions on Medical Imaging. 2016.
XV. Mohan V, Shah SN, Joshi SR, Seshiah V, Sahay BK, Banerjee S, Current
status of management, control, complications and psychosocial aspects of
patients with diabetes in India: Results from the DiabCare India 2011
Study. Indian J EndocrinolMetab 2014; 18:370-8.
XVI. N. Memari, A R Ramil, M I B saripan, S. Mashohor, M Moghbel,
Supervised retinal vessel segmentation from color fundus images based
on matched filtering and AdaBoost classifier, PLoS ONE 12(12):
e0188939, 2017.
XVII. Orlando J, Prokofyeva E, Blaschko M. A Discriminatively Trained Fully
Connected Conditional Random Field Model for Blood Vessel
Segmentation in Fundus Images. IEEE Transactions on Biomedical
Engineering. 2016.
XVIII. Peter Sekulic, M Bajceta, S Dukanovic, “Retinal blood vessels
segmentation using support vector machine and modified line detector”,
22nd International Scientific-Professional Conference
Information Technology, 2017.
XIX. P. Rani, N. Priyadarshini, E. R. Rajkumar, and K. Rajamani, “Retinal
vessel segmentation under
pathological conditions using supervised machine learning,” in 2016
International Conference on, Systems in Medicine and Biology (ICSMB),
pp. 62–66, 2016.
XX. Roychowdhury S, Koozekanani DD, Parhi KK. Blood vessel
segmentation of fundus images by major vessel extraction and subimage
classification. IEEE journal of biomedical and health informatics. 2015
May; 19(3):1118–28. pmid:25014980
XXI. S. A. A. Shah, T. B. Tang, I. Faye, and A. Laude, “Blood vessel
segmentation in color fundus images based on regional and Hessian
features,” Graefe’s Archive for Clinical and Experimental
Ophthalmology, pp. 1– 9, 2017.

XXII. S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum,
“Detection of blood vessels in retinal images using two-dimensional
matched filters,” IEEE Transactions on Medical Imaging, vol. 8, no. 3,
pp. 263–269, 1989.
XXIII. SoumiaBelhadi and NadjiaBenblidia, “Automated Retinal Vessel
Segmentation using Entropic Thresholding Based Spatial Correlation
Histogram of Gray Level Images”, The International Arab Journal of
Information Technology, Vol. 12, No. 5, September 2015.
XXIV. SumathiThangaraj, VivekanandamPeriyasamy, RavikanthBalaji,
“Retinal vessel segmentation using neural network”, IET Image
Processing, Volume: 12, Issue: 5, pp.669-678. 2018
XXV. T. Chakraborti, D. K. Jha, A. S. Chowdhury, and X. Jiang, “A selfadaptive
matched filter for retinal blood vessel detection,” Machine
Vision and Applications, pp. 1–14, 2014.
XXVI. T. Jintasuttisak, and S. Intajag, “Color Retinal Image Enhancement by
Rayleigh Contrast-Limited Adaptive Histogram Equalization”, In: Proc.
of International Conf. on Control, Automation and Systems, Korea, pp.
22-25 2014.
XXVII. T. Mapayi, S. Viriri, and J. R. Tapamo, “Adaptive thresholding technique
for retinal vessel segmentation based on glcm-energy information,”
Computational and Mathematical Methods in Medicine, vol. 2015,
Article ID 597475, 11 pages, 2015.
XXVIII. T. Walter and J.-C. Klein, “Segmentation of color fundus images of
the human retina: detection of the optic disc and the vascular tree using
morphological techniques,” Medical Data Analysis, pp. 282–287, 2001.
XXIX. W. S. Oliveira, J. V. Teixeira, T. I. Ren, G. D. C. Cavalcanti, and J.
Sijbers, “Unsupervised retinal vessel segmentation using combined
filters,” PLoS One, vol. 11, no. 2, article e0149943, 2016.
XXX. X. Jiang and D. Mojon, “Adaptive local thresholding by verificationbased
multi-threshold probing with application to vessel detection in
retinal images,” IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 25, no. 1, pp. 131–137, 2003.
XXXI. Y. MadhuSudhana Reddy, R. S. Ernest Ravindran, Kakarla. Hari
Kishore, “Spatial Mutual Relationship Based Retinal Image Contrast
Enhancement for Efficient Diagnosis of Diabetic Retinopathy”,
International journal of Intelligent Engineering systems, Vol.11, issue.4,
2018.
XXXII. Y. Qian Zhao, X. Hong Wang, X. Fang Wang, F.Y. Shih, Retinal vessels
segmentation based on level set and region growing, Pattern Recognit. 47
(7) (2014) 2437–2446.
XXXIII. Y. Wang, G. Ji, P. Lin, E. Trucco, Retinal vessel segmentation using
multiwavelet kernels and multiscale hierarchical decomposition,
PatternRecognit. 46 (8) (2013) 2117–2133.

XXXIV. Y. Wang, G. Ji, P. Lin, and E. Trucco, “Retinal vessel segmentation
using multiwavelet kernels and multiscale hierarchical
decomposition,” Pattern Recognition, vol. 46, no. 8, pp. 2117–2133,
2013
XXXV. Y. Yin, M. Adel, and S. Bourennane, “Automatic segmentation and
measurement of vasculature in retinal fundus images using probabilistic
formulation,” Computational and Mathematical Methods in Medicine,
vol. 2013, Article ID 260410, 16 pages, 2013.
XXXVI. Z. Xiao, M. Adel, and S. Bourennane, “Bayesian method with spatial
constraint for retinal vessel segmentation,” Computational and
Mathematical Methods in Medicine, vol. 2013, Article ID 401413, 9
pages, 2013.

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Abstract:

In this paper, we studied the failure of the pipe during the transient flow. The pipe is made of ductile cast iron. To simulate the flow, a model includes an upstream tank connected to pipe with a valve at the end is presented; the transient flow is caused by fast time closure of the valve. The governing equations of water hammer are given from the mass and movement continuity conservation laws for fluid and mechanical behaviors laws for pipe structure. This mathematical model is a system of nonlinear hyperbolic partial differential equations where have solved by the method of characteristic along finite difference schema. To understand the behavior of material against surge pressure, we introduce the strain energy density theory (SEDT) S. The available mechanical propriety of ductile cast iron is used from previous study to get the critical value of strain energy density Sc. At the variance of stress intensity factor KIC criterion, the benefit of strain energy density S; that it can predict the crack growth initiation and direction when the applied stress does not coincide with the crack plane.

Keywords:

Water hammer,transient flow,method of characteristics,finite differences,strain energy density,

Refference:

I. Abott MB, An introduction to the method of the characteristics. New
York: American Elsevier, 1966.
II. A. Ductile iron pipes productions. EN 545:2002 standards, Greater cairo
foundries.
III. B Chaitanya K Desai, Dilip C Patel, Kalpesh D Maniya, “Experimental
analysis of mixed mode fracture: the strain energy density concept”.
Proceedings of the International Conference on Mechanical Engineering
Dhaka, Bangladesh, 28- 30 December, 2005.

IV. Bouaziz MA, Guidara MA, Schmitt C, Hadj-Taïeb E, Azari Z, “Water
hammer effects on a gray cast iron water network after adding pumps”.
Engineering Failure Analysis, Vo. 44, 2014, 1–16.
V. BRAHMIA, N. et DJEMILI, A, “Etude de l’influence de l’ancrage de la
conduite sur la variation de la pression et des contrainte lors de
l’écoulement transitoire”. Université de Badji Mokhtar ANNABA,
Algerie, 2013.M
VI. Daniela Ristić, Marko Bojanić, “Application of the Effective Strain
Energy Density Factor in the Estimation of the Fatigue Life of Notched
Specimens”. Scientific Technical Review,Vol. LVIII, 2008, No.1.
VII. Fröberg CE, Introduction to numerical analysis. 2nd ed. Addison-Wesley
Publishing Company; 1979.
VIII. J. M. Makar et al, “Failure Modes and Mechanisms in Gray Cast Iron
Pipes”. Institute for Research in Construction, National Research Council
Canada, Ottawa, Ontario, Canada, Infrastructure Research, Waterloo,
Ontario, June 10-13, 2001.
IX. M.H. Afshar, and M. Rohani, “Water hammer simulation by implicit
method of characteristic”. International Journal of Pressure Vessels and
Piping, Vo. 85, 2008, 851-859.
X. M. Dallali et al, “Accuracy and security analysis of transient flows in
relatively long pipelines”. Engineering Failure Analysis, Vo. 51, 2015,
69–82.
XI. Pluvinage G, Fracture and fatigue emanating from stress concentrators.
Kluwer Editor; 2001.
XII. R. Lacalle et al, “Analysis of the failure of a cast iron pipe during its
pressure test”. Engineering Failure Analysis, Vo. 31, 2013, 168–178.
XIII. Schmitt C, et al, “Pipeline failure due to water hammer effects”. Fatigue
Fracture Eng Mater Struct; 29, 2006, 1075–82.
XIV. SIH,G.C. and BARTHELEMY,O.C, “Mixed mode fatigue crack growth
predictions”. Engineering. Fracture Mechanics, Vo. 13, 1980, 439-451.
Wylie EB, Streeter VL, Suo L. Fluid transients in system. New Jersey,
Prentice Hall, 1993.
XV. SIH, G.C. and MACDONALD.B, “Fracture Mechanics Applied to
Engineering Problems- Strain Energy Density Fracture Criterion”.
Engineering. Fracture Mechanics, Vo. 6, 1974, 361-386.
.XVI. Streeter VL, Wylie EB. Hydraulic transients. New York: McGraw-Hill
Book Compagny; 1967. V.
XVII Tijsseling, AS, “Water hammer with fluid-structure interaction in thickwalled
pipes”. Computers and Structures, Vo. 85, 2007, 844-851.
XVIII. Wylie EB, Streeter VL. Fluid transients. New York: Mac Graw-Hill
Company; 1978.

 

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Abstract:

India has been a rapidly urbanizing country despite being known as a country of villages for centuries. Since Independence, India has witnessed the emergence of more than 2500 New Towns across the country, mostly developed through conversion of rural lands. New Town Kolkata in West Bengal being no exception, involved acquisition and conversion of 3075 hectare of rural land of which 68.36% was agricultural land. While such land acquisition led to economic displacement of the local people, it also led to a huge amount of investment in the form of project costs (INR203, 17, 19,887 in 2014-2015) for the development of New Town. This paper aims to determine the direct benefit accrued to the state from the said investment which is achieved in cost of displacement and livelihood changes of local people. For this purpose, the past (before land acquisition) and present economic conditions of these people have been compared. Taking into consideration of almost all sources of income of past as well as present, a cost benefit analysis in present value terms has been done for the period of 1999 (beginning year of land acquisition) to 2014. A quantitative evaluation of cost incurred by the land losers and a comparison with the compensation paid has been made. Also, a qualitative assessment of uncompensated intangible costs incurred by the land losers have been presented. Hence the ethics of the new town planning as practiced in our country is questioned.

Keywords:

Land Conversion,New Town,Opportunity Cost,Cost Benefit Analysis,Gross Profit Ratio,

Refference:

I. Council for Social Development, Indian Social Development Report.
“Development and Displacement”, Oxford University Press. (New Delhi)
(2008),
II. Dey, I. Samaddar, R. and Sen, S. K. “Beyond Kolkata: Rajarhat and the
Dystopia of the Urban Imagination” Routledge (New Delhi) (2013)
III. Kundu, R. “Making Sense of Place in Rajarhat New Town the Village in the
Urban and the Urban in the Village”. Economic & Political Weekly, LI (17).
93-101(2016).
IV. Mallik, C. “Land Dispossession and Rural Transformation: The Case of
Fringe Villages of Kolkata”. Journal of Rural Development. 33 (1). 51-
71(2014).
V. Roy, A. “Development, Land Acquisition and Changing Facets Of Rural
Livelihood: A Case Study From West Bengal”. Journal of Rural
Development. 33(1), 15-32. (2014).
VI. Roy, U. K. “Development of New Townships: A Catalyst in the Growth of
Rural Fringes of Kolkata Metropolitan Area (KMA)”. Annual Conference of
HUDCO. (2005).
VII. Sarkar, A.“Development and Displacement Land Acquisition in West
Bengal”, Economic &Political Weekly, 42 (16): 1435-42. (2007).
VIII. Sengupta, P. & Chattopadhyay, S. “Appraising Compensational Benefit
under “The Right to Fair Compensation and Transparency in Land
Acquisition, Rehabilitation and Resettlement Act, 2013”. Indian Journal of
Regional Science, XLVIII (1), 114 – 119. (2016)
IX. West Bengal Housing and Infrastructure Development Corporation. New
Town Calcutta, Project Report. Kolkata, India. (1999).

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Abstract:

The main reason for the study is SERVQUAL scale couldn't be validated and adapted inside of a retail setting, given the novel dimensions of service in the connection of retail stores when contrasted with "unadulterated" service environment. The paper means to decide the validity of Retail Service Quality Scale (RSQS) as a distinct option for SERVQUAL in the connection of Indian retail environment. Absolutely 450 clients from hypermarkets in Tamilnadu chose accommodation premise. Retail service quality scale RSQS (28 things) was utilized for validation reason. It consolidates particular validity sorts like construct, convergent, discriminant validity. Confirmatory Factor Analysis has been utilized towards validation and advancement of RSQS measurement model. RSQS model in unique structure is substantial in the Indian retail store environment and legitimate RSQS in the Indian retail environment will be an advantage for considering the composed retail settings. The discoveries and proposals will empower retail stores to assemble knowledge into current levels of service quality and in addition to direct occasional "checks" for surveying extension for service change. RSQS could serve as an analytic apparatus for retailers to recognize service zones that are powerless and needing consideration.

Keywords:

RSQS Validation,SERVQUAL,Hypermarkets,Indian Organized Retail Stores,Service Quality,

Refference:

I. Bentler, P. M, “Comparative fit indexes in structural models”, Psychological
Bulletin, Volume: 107, Issue: 2, pp: 238–246. (1990).
http://dx.doi.org/10.1037/0033-2909.107.2.238
II. Brown, T. A, “Confirmatory factor analysis for applied research”, New
York, NY: Guilford Press., (2006).
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for Retail Stores: Scale Development and Validation”, Journal of the
Academy of Marketing Science, Volume: 24, Winter Issue, pp: 03-16,
(1996).

IV. Gutman J. & Alden S. D., “Adolescents’ Cognitive Structures of Retail Stores
and Fashion Consumption – A Means-End Chain Analysis of Quality”,
Perceived Quality: How Consumers View Stores and Merchandise,
Lexington Books, (1985).
V. B. Yuan; Hair J., Black W., Babin B. & Anderson R.,”Multivariate Data
Analysis “, Prentice Hall Inc., Upper Saddle River, NJ, USA. (7th Edition.)
(2010).
VI. Hu, L.-T., & Bentler, P. M.,”Cutoff criteria for fit indexes in covariance
structure analysis: Conventional criteria versus new alternatives”, Structural
Equation Modeling, Volume: 06, pp: 01–55, (1999).
http://dx.doi.org/10.1080/10705519909540118
VII. Mazursky D. & Jacoby J.,”Forming Impressions of Merchandise and Service
Quality”, Perceived Quality: How Consumers View Stores and Merchandise,
Lexington Books, (1985).
VIII. Mehta, Subhash C., Lalwani A. & Soon Li Han, “Service Quality in Retailing
– Relative Efficiency of Alternative Measurement Scales for Different
Product Service Environments”, International Journal of Retail & Distribution
Management, Volume: 28, Issue: 02, pp: 62-72, (2000).
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Validity”, Journal of Operations Management, Volume: 16, Issue: 04, pp:
387-405, (1998).
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Harvard Business Review, Volume: 68, Issue: 05, pp: 105-111, (1990).
XI. Subhashini Kaul, “Measuring Retail Service Quality: Examining
Applicability of International Research Perspectives in India”, Vikalpa,
Volume: 32, Issue: 01, January – March, pp: 15-26, (2007).
XII. Schneider, Benjamin and Susan White, “Service Quality – Research
Perspectives, Foundations for Organizational Science”, California USA, Sage
Publications Inc, (2004).
XIII. Wisniewski M.,”Using SERVQUAL to Assess Customer Satisfaction with
Public Sector Services”, Managing Service Quality, Volume: 11, Issue: 06,
pp: 380-388, (2001).
XIV. Wong A. and Sohal A., “Service Quality and Customer Loyalty Perspectives
on Two Levels of Retail Relationships”, Journal of Services Marketing,
Volume: 17, Issue: 05, pp:495-513, (2003).

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Abstract:

Hollow-core photonic crystal fibers (HC-PCF) are used for high power beam delivery and can deliver ultra-short or compressed pulses at 1550 nm. This paper study the relation between the length of (9 &7) cell HC-PCFsand the full width at half maximum (FWHM) using laser source with centroidwavelength of 1546.7 nm, i.e. almost 1550nm, and FWHM of 286 pm or 10 ns in the time domain.The FWHM in the frequency domain was increased in both (19&7) cell HC-PCFs as the length of Fabry-Perot interferometer increased till it reachesa specific length and then dramatically decreasedto go to the almost same starting point.

Keywords:

Hollow-Core Photonic Crystal Fiber,FWHM,Pulse compression,the compression factor,

Refference:

I. Agrawal, G.P. Application of Nonlinear Fiber Optics, 2nded.; Academic
Press: New York, 2001.
II. D. G. Ouzounov, F. R. Ahmad, D. M¨uller, N. Venkataraman, M. T.
Gallagher, M. G. Thomas, J. Silcox, K. W. Koch, and A. L. Gaeta,
“Generation of megawatt optical solitons in hollow-Core photonic band-gap
fibers,” Science 301, 1702–1704 (2003).
III. D. V. Skryabin, “Coupled core-surface solitons in photonics crystal fibers,”
Opt. Express 12, 4841–4846 (2004).
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Academic Press: 2006.
V. E. V. Ermolaeva and V. G. Bespalov, “Optimum Condi- tions for Stimulated
Raman Scattering, Compression, and Amplification of Supershort Pulses in a
Plasma with Com- pressed Gases,” Journal of Optical Technology, Vol. 74,
No. 11, 2007, pp. 734-739.
VI. F. G´erˆome, K. Cook, A. K. George, W. Wadsworth, and J. C. Knight,
“Delivery of sub-100fs pulses through 8m of hollow-core fiber using soliton
compression,” Opt. Express 15, 7126–7131 (2007).
VII. F. Luan, J. C. Knight, P. S. J. Russell, S. Campbell, D. Xiao, D. T. Reid, B. J.
Mangan, D. P. Williams, and P. J. Roberts, “Femtosecond soliton pulse
delivery at 800 nm wavelength in hollow-core photonic bandgap fibers,”
Opt. Express 12, 835–840 (2004).
VIII. G. H. He and S. H. Liu, “Physics of Nonlinear Optics,” World Scientific
Publishing Co. Pte Ltd., Singapore, 1999.
IX. G. P. Agrawal, Applications of Nonlinear Fiber Optics (Academic, 2001)
X. H. Q. Quy, “Applied Nonlinear Optics,” Hanoi National University
Publishing, Hanoi, 2007, pp. 214-201.

XI. J. C. Knight, F. G´erˆome, and. J. Wadsworth, “Hollow-core photonic crystal
fibers for delivery and compression of ultrashort optical pulses,” IEEE J.
Quantum Electron. 39, 1047–1056 (2007).
XII. L. V. Tarasov, “Laser Physics,” Mir, Moscow, 1988, pp. 214-335.
XIII. S. O. Atuba, K. Nakkeeran, K. W. Chow, P. Ramesh Babu, A. Manimegalai
& K. Senthilnathan (2016) Generation of a train of ultrashort pulses using
periodic waves in tapered photonic crystal fibers, Journal of Modern Optics,
63:21, 2246-2258, DOI: 10.1080/09500340.2016.1193638
XIV. V. L. Kalashnikov, “Pulse Shortening in the Passive Q- Switched Lasers with
Intracavity Stimulated Raman Scat- tering,” Optics Communications, Vol.
218, No. 1-3, 2003, pp. 147-153. doi:10.1016/S0030-4018(03)01191-X [12]
I. P. Prokopovich and A. A. Khrushchinskii, “Highly Efficient Generation of
Attosecond Pulses in Coherent Stimulated Raman Self-Scattering of Intense
Demtosec-and Laser Pulses,” Laser Physics, Vol. 7, No. 2, 1997, pp. 305-
308.
XV. Weiner, A.M. Ultrafast Optics; John Wiley: Hoboken, NJ,2009.
XVI. Y. Ping, I. Geltner and S. Suckewer, “Raman Scattering,” Physical Review
E, Vol. 67, 2003, Article ID: 016401. doi:10.1103/PhysRevE.67.016401

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Abstract:

Agriculture and its supply chain is one of the major domains of research which need attention for its growth in all developing countries. Food safety and its supply are also drawing the world attention towards its importance and people are focusing on it because of health hazards. In this research, we have presented a model for the uplift of traditional agriculture field to smart farming, considering blockchain with IoT technology. This system promises to provide equal opportunity to all stakeholders involved in the agricultural food supply chain; even they are not interconnected. IoT devices are added to the smart model to reduce human interference for data collection, recording and verification. The validation of our novel model is compared with our own scheme utilizing only IoT devices deployed in the monitoring field without block-chain.  

Keywords:

Agriculture,Blockchain,Novel,IoT,Smart Model,

Refference:

I. Abate, Gashaw Tadesse, Tanguy Bernard, Alan de Brauw, and Nicholas
Minot. “The impact of the use of new technologies on farmers’ wheat
yield in Ethiopia: evidence from a randomized control trial.” Agricultural
economics 49, no. 4 (2018): 409-421.
II. Atzori, Marcella. “Blockchain technology and decentralized governance:
Is the state still necessary?.” Available at SSRN 2709713 (2015).
III. Abeyratne, Saveen A., and Radmehr P. Monfared. “Blockchain ready
manufacturing supply chain using distributed ledger.” (2016).
IV. Calatayud, Agustina, John Mangan, and Martin Christopher. “The selfthinking
supply chain.” Supply Chain Management: An International
Journal 24, no. 1 (2019): 22-38.
V. Chang, Hung-Fu, and Tzu-Kang Lin. “Real-time Structural Health
Monitoring System Using Internet of Things and Cloud Computing.”
arXiv preprint arXiv:1901.00670 (2019).
VI. Colombo, Patricia Eustachio, Emma Patterson, Liselotte Schäfer Elinder,
Anna Karin Lindroos, Ulf Sonesson, Nicole Darmon, and Alexandr
Parlesak. “Optimizing School Food Supply: integrating Environmental,
Health, Economic, and Cultural Dimensions of Diet Sustainability with
Linear Programming.” (2019).
VII. Casado-Vara, Roberto, Javier Prieto, Fernando De la Prieta, and Juan M.
Corchado. “How blockchain improves the supply chain: Case study
alimentary supply chain.” Procedia computerscience 134 (2018): 393-398.
VIII. Chen, Weijie, Guo Feng, Chao Zhang, Pingzeng Liu, Wanming Ren, Ning
Cao, and Jianrui Ding. “Development and Application of Big Data
Platform for Garlic Industry Chain.” Computers,Materials & Continua 58,
no. 1 (2019): 229-248.
IX. Choe, Young Chan, Joowon Park, Miri Chung, and Junghoon Moon.
“Effect of the food traceability system for building trust: Price
premium and buying behavior.” Information SystemsFrontiers 11, no. 2
(2009): 167-179.
X. Dasaklis, Thomas K., Fran Casino, and Constantinos Patsakis. “Defining
granularity levels for supply chain traceability based on IoT and
blockchain.” In Proceedings of the InternationalConference on Omni-
Layer Intelligent Systems, pp. 184-190. ACM, 2019.
XI. Gu, Baojing, Xiaoling Zhang, Xuemei Bai, Bojie Fu, and Deli Chen.
“Four steps to food security for swelling cities.” (2019): 31.
XII. Glunz, Benjamin F., Wayne R. Pearson, and Alfredo F. Munoz. “Method
and system for creating 3D models from 2D data for building information
modeling (BIM).” U.S. Patent 9,817,922, issued November 14, 2017.

XIII. Han, Sangyeal, and Heetae Yang. “Understanding adoption of intelligent
personal assistants: A parasocial relationship perspective.” Industrial
Management & Data Systems 118, no. 3 (2018): 618-636.
XIV. Ivanov, Dmitry, Alexander Tsipoulanidis, and Jörn Schönberger.
“Operations and Supply Chain Strategy.” In Global Supply Chain and
Operations Management, pp. 81-110. Springer, Cham, 2019.
XV. Kamilaris, Andreas, Agusti Fonts, and Francesc X. Prenafeta-Boldύ. “The
Rise of the Blockchain Technology in Agriculture and Food Supply
Chain.” (2018).
XVI. Kumar, Subramania Ananda, and Paramasivam Ilango. “The impact of
wireless sensor network in the field of precision agriculture: a review.”
Wireless Personal Communications 98, no. 1 (2018): 685-698.
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Abstract:

Over the recent years we have witnessed an increasing number of applications using deep learning techniques such as Convolutional Neural networks (CNNs), Recurrent Neural Networks (RNN) and Deep Neural Networks (DNN) for remote sensing image classification. But, we found that these models suffer for characterizing complex patterns in remote sensing imagery because of small inter class variations and large intra class variations. The intent of this paper is to study the effect of ensemble classifier constructed by combining three Deep Convolutional Neural Networks (DCNN) namely; CNN, VGG-16 and Res Inception models by using average feature fusion techniques. The proposed approach is validated with 7,000 remote sensing images from Northern Western Polytechnical University – Remote Sensing Image Scene Classification (NWPU- RESISC) 45 class dataset and confirmed as an effective technique to improve the robustness over a single deep learning model.

Keywords:

Image classification,Remote sensing,Feature fusion,Convolutional neural network,Deep CNN and Ensemble classifier,

Refference:

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Benchmark and State of the Art”, Proceedings of the IEEE, pp.1-19, 2017.
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Applications and Management Studies, pp.1-10, 2018.
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Networks for Land Cover Classification of High-Resolution Imagery”, IEEE
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remote sensing images using improved correlations,” IEEE Geosci.
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Image Classification Using Small Training Sample Size”, Third IAPR Asian
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Abstract:

Micro-strip patch antenna has penetrated deep in the market due to its advantages. After studying micro patch antennas, there are some draw backs of it. One of the drawbacks includes the narrowband performance. The primary reason for this is its resonant nature. An E-shaped micro strip patch antenna is used for the broadband applications. This E-shaped antenna is used for the purpose of improving antenna shrinking and information measurement to name a few. This paper shows the detail study of Cowl’s research by using 2 different aspects of micro strip patch antenna. The antenna operated at a frequency of 5GHz. Antennas used were single part narrow band rectangular micro strip patch antenna and slot cut E-shaped micro strip patch antenna. Simulation method included high frequency structure machine (HFSS). Different properties such as Cable loss, information measurement and VSWR were studied using both types of antennas. These properties were then compared between each other.

Keywords:

Micro-Strip,Antenna,Frequency,6.5 GHz,Rectangular patch,

Refference:

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Abstract:

The aim of the study was to investigate how office type influences employee performance, and whether this is different for different personalities. Multiple regression was used in order to test the impact of personality and office type on employee performance. The data was collected from 406 employees working in higher educational institutions, with different office types in Bangalore, Karnataka by using convenience sampling technique. Respondents who were emotionally stable, extroverted and conscientious showed higher level of performance. Specially more emotionally stable respondents showed greater performance, specifically those working in flex offices. Extroverts shown greater performance in shared and cell offices than in open plan and flex offices. Conscientious people shown greater performance in shared and open plan offices.

Keywords:

Cell Offices,Open plan Offices,Shared rooms,Flex Offices,Personality,Big five traits,Employee performance,

Refference:

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472.

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in Czech universities: A pilot study. Studia paedagogica, 19(4), 121-144.

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Abstract:

Corporate governance is aunified, systematic, comprehensive and an integrated mechanism which helps the organization to be transparent. Basically, Its erves as a watch dog for an organization through its monitoring process and create values for itself, share holders and for the society at large. This piece of work aims at a chronological study of corporate governance in Information Technology sector and its impact on society for value creation.A range of studies that have applied in 20-year period are examined in a non-exhaustive review of the literature. These studies are selected from authenticated sources mainly from well-known national and international journals. The paper discusses and summarizes numerous theoretical aspects followed by conceptual criticisms of corporate governance structures/ policies/ framework. Despite these criticisms, the paper concludes that corporate governance remains an useful instrument for industry-oriented research. The author has focused her approach purely from corporate perspective based on her diagnostic studies that is clearly reflected on this paper. The nature and scope of corporate governance is vast and ever evolving. The genesis of the corporate governance reveal that Corporate governance matters are complex that combines its matters like web. The term “governance” designated initially as government dealing with economic and social resources than as a process by which corporate decisions are made or implemented. Corporate governance has become a very effective mechanism which has helped the organizations to create value and stand as a pillar for the growth of Indian economy.The paper provides a useful source of information on corporate governance and its applications. In particular, the paper summarizes a trend of corporate governance over a period of time in India and it is beneficial to the academics, practitioners and researchers.

Keywords:

Corporate Governance,India,CSR,value creation,society,shareholders,

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