Journal Vol – 14 No -2, April 2019

Detection and Classification of Kidney Disorders using Deep Learning Method

Authors:

Vasanthselvakumar R, Balasubramanian M, Palanivel S

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00021

Abstract:

The main objective of this work is to detect and classify the chronic kidney diseases (CKDs) particularly kidney stone, cystic kidney and suspected renal carcinoma. CKDs make a ground for developing several numbers of diseases other than urinal system. It will cause the pervasiveness of Coronary heart diseases, stroke, cardiomyopathy, pulmonary hypertension, and heart valves diseases, Early prediction of chronic kidney disease will save life from worse diseases, Ultrasound imaging is widely used diagnostic method for abdominal studies. In this proposed system chronic kidney diseases have detected using a framework containing Histogram of oriented gradient feature and Adaboost Algorithm. Convolution Neural Network (CNN) multi layered architecture has trained for kidney diseases classification, Batch prediction method is evaluated for prediction of chronic kidney diseases. The performance accuracy for detection of kidney disease is given as 96.67% The accuracy for the classification of CKD ultrasound using CNN is given by 85.2 %..

Keywords:

Adaboost,Chronic Kidney Diseases, HOG,Convolutional Neural Network,Ultrasound image,

Refference:

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II.Chensi Cao, Feng Liu, Hai Tan, Deshou Song, Wenjie Shu, WeizhongLi, Yiming Zhou, Xiaochen Bo, ZhiXie “Deep Learning and Its Applications in Biomedicine”, Elsevier Transaction on Genomics Proteomics Bioinformatics, vol. 16, pp. 17-32, Mar 2018.

III.Fangwang, KevinHe, JinweiWang, MingHuiZhao, YiLiLuxiaZhang, RajivSaran, Jennifer L.Bragg Gresham, “Prevalence and Risk Factors for CKD: A Comparison Between the Adult Populations in China and the United States” Elsevier transaction on Kidney International Reports, vol. 3, No. 5, pp. 1135-1143 Sep 2018.

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VI.Kemal Adem, SerhatKiliçarslan, OnurCömert, “Classification and diagnosis of cervical cancer with softmax classification with stacked autoencoder” Elsevier transaction on Expert Systems With Applications Vol 115, pp 557-564, Jan 2019.

VII.Ling Zhang , Le Lu, Isabella Nogues, Ronald M. Summers, Shaoxiong Liu, and Jianhua Yao.” DeepPap: Deep Convolutional Networks for Cervical Cell Classification”, IEEE transaction on Journal of Biomedical and Health Informatics, vol. 21, no. 6, Nov 2017.

VIII.M. Balasubramanian, S. Palanivel, V. Ramalingam, “Video-based person recognition using fovea intensity comparison code”, Behaviour & Information Technology, November Vol.30, No. 6, pp. 747-760. 2011.,

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X.Mr.B.Perumal, 2 Dr.M.PallikondaRajasekaran, “A Hybrid Discrete Wavelet Transform with Neural Network Back Propagation Approach for Efficient medical Image Compression”, In Proc International Conference on Emerging Trends in Engineering, Technology and Science(ICETETS), pp 1-5, Feb 2016.

XI.Pietro Perona, Jitendra Malik, “Scale-Space and Edge Detection Using Anisotropic Diffusion”, IEEE Transactions ON Pattern Analysis and Machine Intelligence, vol. 12. no. 7, Pp 629-639, July 1990

XII.R. Vasanthselvakumar, M. Balasubramanian, S.Palanivel, “Pattern Analysis of Kidney Diseases For Detection And Classification Using Ultrasound B -Mode Images”, International Journal of Pure and Applied Mathematics, Volume 117 No. 15, pp. 635-653, 2017.

XIII.Yanwei Pang, Manli Sun, XiaohengJiang, and Xuelong Li, “Convolution in Convolution for Network in Network” IEEE Transaction on Neural Networks and Learning Systems, Vol. 29, no. 5, pp. 1587-1597, May 2018.

XIV.Yongjin Zhou, Jingxu Xu, Qiegen Liu, Cheng Li, Zaiyi Liu, Meiyun Wang, Hairong Zheng, and Shanshan Wang, “A Radiomics Approach With CNN forShear-Wave Elastography Breast Tumor Classification”, IEEE Transactions on Biomedical Engineering, vol. 65, no. 9, pp. 1935-1942, Sep 2018.

XV.YujiIwahoria, AkiraHattoria, YoshinoriAdachia, M.K.Bhuyanb, Robert J. Woodhamc, KunioKasugaid, “Automatic Detection of Polyp Using Hessian Filter and HOG Features”, Elsevier transaction on Procedia of Computer Science, Volume 60, pp. 730-739, 2015

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Comparison on Performance of Grid Connected DFIG-WT System using B2BC and NSC

Authors:

Subir Datta, Subhasish Deb, Ksh. Robert Singh

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00022

Abstract:

This paper presents a comparative study of the performances of a doubly fed induction generator (DFIG) based grid connected wind turbine (WT) system using back-to-back converter (B2BC) and nine-switch converter (NSC). The time domain simulink results of the system variables, under varying wind velocity, are presented and analyzed all the results in details. Results show that the B2BC- used with DFIG-WT system can be replaced by NSC under any wind speed.

Keywords:

WECS,DFIG,B2BCand NSC,

Refference:

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VIII.G. Li, M. Yin, M. Zhou and C. Zhao, “Decoupling control for multi terminal VSC HVDC based wind farm interconnection,” IEEE Power Engineering Society General Meeting, pp.1-6, 2007.

IX.Gui-Jia Su Hsu, J.S., “A five-leg inverter for driving a traction motor and a compressor motor,” IEEE Transactions on Power Electronics, vol. 21, pp. 687 -692, 2006.

X.H. Nikkhajoei, R. H. Lasseter, “Power quality enhancement of a wind-turbine generator under variable wind speeds usingmatrix converter,” Power Electronic Specialists Conference, pp. 1755-1761, 2008.

XI.Lie Xu, “Coordinated Control of DFIG’s Rotor and Grid Side Converters during Network Unbalance,” IEEE Trans. on Power Electronics, Vol. 23, pp.1041-1049, 2008.

XII.L. Holdsworth, X. G. Wu, J. B. Ekanayake and N. Jenkins, “Comparison of fixed speed and doubly-fed induction wind turbines during power system disturbances,” IEE Proc. Gener. Transm. Distrib., Vol. 150, pp. 343-352, 2003.

XIII.M.V.A. Nunes, H.H. Zurn, U.H. Bezerra, J.A. Pecas Lopes, R.G. Almeida, “Influence of the variable Speed wind Generators in Transient Stability Margin of the Conventional Generators Integrated in Electrical Grids,” IEEE Transactions on Energy Conversion, Vol. 21, pp257-264, 2006.

XIV.M. Jones, S. N. Vukosavic, D. Dujic, E. Levi, and P. Wright, “Five-leg inverter PWM technique for reduced switch count two-motor constant power applications,” IET Proc. Electric Power Application, vol. 2, pp. 275–287, 2008.

XV.O. Ojo, “The generalized discontinuous PWM scheme for three phase voltage source inverters,” IEEE Trans. Ind. Electron., vol.51, pp.1280-1289, 2004.

XVI.P. C. Loh, F. Blaabjerg, F. Gao, A. Baby, and D. A. C. Tan, “Pulse width modulation of neutral-point-clamped indirect matrix converter,” IEEE Trans. Ind. Application, vol. 44, pp. 1805–1814, 2008.

XVII.R.G. Almeida, E.D. Castronuovo, J.A. Pacas Lopes, “Optimum Control in Wind Parks when Carrying out system Operator Requests,” IEEE Transactions Power System. Vol.19, pp 1942-1950, 2006.

XVIII.R. Cardenas, R. Pena, G. Tobar, J. Clare, P. Wheeler, G. Asher, “Stability Analysis of a Wind Energy Conversion System Based Doubly Fed Induction Generator Fed By a Matrix Converter,” IEEE Trans. on Industrial Electronics, Vol. 56, pp.4194-4206, 2009.

XIX.S. Datta, J. P. Mishra and A. K. Roy, “Modified Speed Sensor-less Grid Connected DFIG based WECS”, Indian Journal of Science of Technology, Vol. 8, Issue No. 16, pp.1-12, 2015.

XX.S. Datta, J. P. Mishra and A. K. Roy, “Operation and control of a DFIG-based grid-connected WECS using NSC during grid fault and with unbalanced non-linear load”, International Journal of Ambient Energy, Vol.39, No.7, pp.732-742, 2018.

XXI.T. Kominami and Y. Fujimoto, “A novel nine-switch inverter for independent control of two three-phase loads,” IEEE Industry Applications Society Annual Conference (IAS), pp. 2346-2350, 2007.

XXII.Y. Lei, A. Mullane, G. Lightbody, R. Yacamini, “ Modeling of the wind turbine with a Doubly fed Induction Generator for Grid Integration Studies,” IEEE Transactions on Energy Conversion, Vol. 21, pp.257-264, 2006.

XXIII.Z. Lei, P. C. Loh and F. Gao, “An integrated nine-switch power conditioner for power quality enhancement and voltage sag mitigation,” IEEE Transaction on Power Electronics, vol. 27, pp. 1177-1190, 2012.

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Exponentially backlogged shortage inventory model for deteriorating item with linear selling price of the product

Authors:

M. Mijanur Rahman

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00023

Abstract:

This paper deals with an inventory model for deteriorating items with linear price and frequency of advertisement dependent demand and exponentially backlogged shortages. The deterioration rate follows three-parameter Weibull distribution. The corresponding non-linear problem have been formulated and solved. Numerical example has been considered to illustrate the model and the significant features of the result are discussed. Finally, we have performed the sensitivity analysis taking one or more parameters at a time.

Keywords:

Inventory,Weibul distributiondeterioration,linear price dependent demand,Partially backlogged shortage,

Refference:

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Parameter Estimations of Stochastic Volatility Model by Modified Adaptive Kalman Filter with QML

Authors:

Atanu Das

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00024

Abstract:

To determine the parameters of Stochastic Volatility Model (SVM), a modification to the Quasi Maximum Likelihood (QML) scheme has been proposed by employing (modified) Adaptive Kalman Filter (AKF). AKF allows optimization over lesser number of parameters as the variance ( 2 v  ) of the noise in the volatility state equation is determined by the AKF. The adaptive method, instead of a constant 2 v  , allows it to be time varying. Before applying the methodology on market data, the proposed method is characterized here by synthetic data through simulation investigations. Numerical experiments show that the performance of SVM based QMLKF and novel QML-AKF are comparable to that of more popular GARCH family based techniques

Keywords:

Adaptive Estimation, Noise Covariance Adaptation, Modified AKF,Stochastic Volatility Model,Quasi-Maximum Likelihood,

Refference:

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Impact of Counterfeiting On Quality In Construction Industry In Peshawar

Authors:

Aimal Khan, Muhammad Zeeshan Ahad, Imtiaz Khan, Fawad Ahmad

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00025

Abstract:

During the studying and job author noticed that in construction industry, the counterfeit items, are many and becoming a high reason of concern for the population. Further digging out the subject, exploring the other parallel industries of neighboring economies shows that the counterfeit items are produce in such manner that it become an industry itself. And it has penetrated the other national and international trades of all sorts, where civil work industry is also not speared keeping that its growing day by day and profit margin is higher for the opportunist of the counterfeit material manufactures and distributors. China, Turkey, Taiwan are the main lands of these manufacturer to produce the counterfeit items where Honking, Malaysia, UAE are the main distributing hubs for these counterfeit products due to weak law enforcement or flexible business rules. The impact and presence of counterfeit material in civil industry Peshawar region, 150 participants were selected in three subgroups such as Contractors, client and consultants to collect data through open and closed ended questionnaires, interviews, discussion, physical inspection visits of manufacture, warehouses and deliveries regarding the availability, use and volume of the counterfeit products in the Peshawar market. This data was further analyzed and evaluated with SPSS. The outcome of the data evaluation on the subject exposes the enormous increase of counterfeit material in the industry special in wood work, water sanitation, electric items and civil works as these items were the target of this research. Most factors are the unawareness, low price, scarcity of original product in market that these items exist in substitute product.

Keywords:

Refference:

I.Box Po. Counterfeit Construction Products From Low-Cost Sourcing Countries. 2011;(June):1–12.

II.Buxbaum P. Aafa ’ S Top Counterfeiting Countries. 2018;2017–9.

III.Cademan A, Henriksson R, Nyqvist V. The Affect Of Counterfeit Products On Luxury Brands. Linnaeus Univ [Internet]. 2012;3.

IV.Favourites Addto. Fake Building Materials Are Endangering Lives 0 05. 2018;1–4.

V.Government Of The United States. Strtegy To Combat Transnational Organized Crime. 2011;28.

VI.Lewis K, Lewis B. The Fake And The Fatal : The Consequences Of Counterfeits. 2007;Xvii:47–58.

VII.Luborsky Fe, Barber Wd. Nondestructive Readout In Plated Wires. Ieee Trans Magn. 1971;7(3):490–3.

VIII.Rutter J, Bryce J. The Consumption Of Counterfeit Goods: “Here Be Pirates” Sociology. 2008.

IX.Tom G, Garibaldi B, Zeng Y, Pilcher J. Consumer Demand For Counterfeit Goods. 15(August 1998):405–21.

X.Understanding Counterfeit Supply. 2006.

XI.Wilcox K, Kim Hm, Sen S. Why Do Consumers Buy Counterfeit Luxury BrandsJ Mark Res [Internet]. 2009;46(2):247–59.

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Automatic Parcel Sorting System based on PLC

Authors:

Zahoor Ahmed, Tayyab Khan Kakar

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00026

Abstract:

The objective of this research paper is to explain the process of PLC based sorting of different parcels in companies. Automatic parcel sorting systems are essential for courier companies with a high distribution capacity and short time-to-deliver and courier companies need to increase the quality and reliability of their services as the Customers demand quicker deliveries of goods. In many courier companies parcel sorting and placing on their particular location is done manually which seems complex and takes time so we have decide to provide ease to courier companies by implementing a system which does all these work without the interference of human being. Our proposed project automatic parcel sorting system based on PLC is one of the useful projects for couriers companies; we used the technique of RFID for the identification of different parcel the solution that we are providing to the courier companies

Keywords:

RFID,PLC,reliability,short time delivery,

Refference:

I.Automatic Sorting Machine Using Delta PLC”, International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163 Volume 1 Issue 7 (August 2014)

II.Automatic letter sorting system for Indian postal address recognition system based on PIN codes”, Georgian Electronic Scientific Journal: Computer science and Telecommunications 2010

III.Automatic Box Sorting Machine Shreeya V. Kulkarni1 Swati R. Bhosale2 Priyanka P. Bandewar3 Prof. G.B.Firame4 IJSRD -International Journal for Scientific Research & Development| Vol. 4, Issue 04, 2016 | ISSN (online): 2321-0613.

IV.Adeoye, A. O. M., A. A. Aderoba, and B. I. Oladapo. “Simulated designof a flow control valve for stroke speed adjustment of hydraulic power of robotic lifting device.” Procedia engineering 173 (2017): 1499-1506.

V.Berger I, Chevion D, Heilper A, Navon Y, Tzadok A, Tross M, Wallach E, inventors; International Business Machines Corp, assignee. Automatic location of address information on parcels sent by mass mailers. United States patent US 6,360,001. 2002 Mar 19.

VI.Bargal, Nilima, et al. “PLC based object sorting automation.” International Research Journal of Engineering and Technology (IRJET) 3.7.

VII.Oladapo, Bankole I., et al. “Experimental analytical design of CNC machine tool SCFC based on -pneumatic system simulation.” Engineering Science and Technology, an International Journal 19.4 (2016): 1958-1965.

VIII.Sowmiya D (2013). Monitoring and control of a PLC based VFD fed three phase induction motor for powder compacting press machine. Intelligent Systems and Control (ISCO), 7th International Conference on Digital Object Identifier: 10.1109/ISCO.2013.6481128. 90 –92.

IX.Thirumurugan, P., et al. “Automatic sorting in process industries using PLC.” Global Research and Development Journal for Engineering 3.3 (2018

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Identity-Based Directed Signature Scheme without Bilinear Pairings

Authors:

R. R. V. Krishna Rao, N. B. Gayathri, P. Vasudeva Reddy

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00027

Abstract:

P. Vasudeva ReddyThe most important contribution of modern cryptography is the invention of digital signatures. Digital signature schemes have been extended to meet the specific requirements for real world applications. A directed signature scheme is a kind of signature scheme intended to protect the privacy of the signature verifier. In directed signature schemes, a signer signs the document/message for a designated verifier so that only the designated verifier can verify the validity of the signature and others cannot do. Thus the restriction of verification is controlled by the signer. Such directed signature schemes are applicable in many situations where the signed message is sensitive to the receiver such as signature on medical records, tax information etc. However all the existing directed signature schemes in ID based setting uses bilinear pairings over elliptic curves. Due to the heavy computational cost of pairing operations, these existing ID based directed signature schemes are not much efficient in practice. In order to improve the efficiency, in this paper, we present an efficient Identity-based directed signature scheme without pairings. The proposed scheme is proven secure under the assumption of elliptic curve discrete logarithm problem is hard. In addition, this scheme improves the efficiency than the existing directed signature schemes in terms of computational cost.

Keywords:

Digital signature,Directed Signature,Elliptic Curve Discrete Logarithm Problem,Identity-based Framework,Random Oracle Model,

Refference:

I.A. Shamir; “Identity-based Cryptosystems and Signature Schemes”, Advances in Cryptology, Crypto-84, Lecture Notes in Computer Science, Springer, vol. 196, pp.47-53, 1984

II.B. Uma Prasada Rao; P. Vasudeva Reddy; T. Gowri; “An efficient ID-Based Directed Signature Scheme from Bilinear Pairings”, Available at https://eprint.iacr.org/2009/617.pdf.

III.C. H. Lim; P. J. Lee; “Directed Signatures and Applications to Threshold Cryptosystem”, Workshop on Security Protocol, Cambridge, pp. 131-138, 1996

IV.C. P. Schnorr; “Efficient Identification and Signatures for Smart Cards”,Advances in Cryptology-Crypto’89, Lecture Notes in Computer Science, Springer, vol. 435, pp. 239-252, 1989

V.D. Pointcheval; J. Stern; “Security Arguments for Digital Signatures and Blind Signatures”, Journal of Cryptology, vol. 13, No.3, pp.361-369, 2000

VI.E. S. Ismail; Y. Abu-Hassan; “A Directed Signature Scheme Based on Discrete Logarithm Problems”, Jurnal Teknologi, vol. 47(C), pp. 37-44, 2007

VII.F. Laguillaumie; P. Paillier; D. Vergnaud; “Universally Convertible Directed Signatures”, Advances in Cryptology -ASIACRYPT’05, Lecture Notes in Computer Science, Springer, vol. 3788, pp. 682–701, 2005

VIII.J. Ku; D. Yun; B. Zheng; S. Wei; “An Efficient ID-Based Directed Signature Scheme from Optimal Eta Pairing”, Computational Intelligence and Intelligent Systems, vol. 316, pp. 440-448, 2012

IX.J. Zhang; Y. Yang; X. Niu; “Efficient Provable Secure ID-Based Directed Signature Scheme without Random Oracle”, 6th International Symposium on Neural Networks: Advances in Neural Networks-ISNN 2009, Lecture Notes in Computer Science, Springer, vol. 5553, pp.318-327, 2009

X.L. C. Guillou; J. J. Quisquater; “A “Paradoxical” Indentity-BasedSignature Scheme Resulting from Zero-Knowledge”, Advances in Cryptology-Crypto’88, Lecture Notes in Computer Science, Springer, vol. 403, pp. 216-231, 1988

XI.N. B. Gayathri; T. Gowri; R. R. V. Krishna Rao; P. Vasudeva Reddy; “Efficient and Secure Pairing-free Certificateless Directed Signature Scheme”, Journal of King Saud University-Computer and Information Sciences, Article in press, 2018

XII.N. Koblitz; “Elliptic Curve Cryptosystems”, Mathematics of Computation, vol. 48, no. 177, pp. 203-209, 1987

XIII.N. N. Ramlee; E. S. Ismail; “A New Directed Signature Scheme with Hybrid Problems”, Applied Mathematical Sciences, vol. 7, No. 125, pp. 6217-6225, 2013

XIV.N. Tiwari; S. Padhye; “Provable Secure Multi-proxy Signature Scheme without Bilinear Maps”, International Journal of Network Security,vol.17, no.6, pp.736-742, 2015XV.P.S.L.M. Barreto; B. Libert; N. McCullagh; J.J. Quisquater; “Efficient and Provably Secure Identity-based Signatures and Signcryption from Bilinear Maps”, Advances in Cryptology-ASIACRYPT’05, Lecture Notes in Computer Science, Springer, vol. 3788, pp. 515-532, 2005

XVI.Q. Wei; J. He; H. Shao; “Directed Signature Scheme and its Application to Group Key Initial Distribution”, 2ndInternational Conference on Interaction Sciences: Information Technology, Culture and Human (ICIS-2009), ACM, 2009, pp. 24-26, 2009

XVII.R. Lu; Z. Cao; “A Directed Signature Scheme Based on RSA Assumption”, International Journal of Network Security, vol. 2, No. 3, pp.182–421, 2006

XVIII.S. Lal; M. Kumar; “A Directed Signature Scheme and its Applications”, 2004. Available at http://arxiv.org/abs/cs/0409035.

XIX.S. Y. Tan; S. H. Heng; B. M. Goi; “Java Implementation for Pairing-Based Cryptosystems”, Computational Science and Its Applications (ICCSA’10), Lecture Notes in Computer Science, Springer, vol. 6019, pp. 188-198, 2010

XX.Shamus Software Ltd. Miracl Library. Available: http://certivox.org/display /EXT/MIRACL.

XXI.V. Miller; “Uses of Elliptic Curves in Cryptography”, Advances in Cryptology-Crypto 85, pp. 417-426, 1985

XXII.W. Diffie; M.E. Hellman; “New Directions in Cryptography”, IEEE Transactions in Information Theory, vol. 22, pp.644-654, 1976

XXIII.X. Cao; W. Kou; X. Du; “A Pairing-free Identity-based Authenticated Key Agreement Protocol with MinimalMessage Exchanges”, Information Sciences, vol. 180, No. 15, pp. 2895-2903, 2010

XXIV.X. Sun; J. Li; G. Chen; S. Yung; “Identity-Based Directed Signature Scheme from Bilinear Pairings”, Available at https:// eprint.iacr.org/2008/305.pdf.

XXV.Y. Wang; “Directed Signature Based on Identity”, Journal of Yulin College, vol. 15, No. 5, pp. 1–3, 2005

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Codes of Polynomial Type

Authors:

Mohammed Sabiri

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00028

Abstract:

In this work we try to introduce the concept of codes of polynomial type and polynomial codes that are built over the ring A[X]/A[X]f(X).It should be noted that for particular cases of f we will find some classic codes for example cyclic codes, constacyclic codes, So the study of these codes is a generalization of linear codes.

Keywords:

Cyclic codes,dual code,Polynomial code, principal polynomial code,codes of polynomial type,

Refference:

I.Adamek, J. (1991). Foundations of coding. Interscience, Prague.

II.Greferath, M. (1997). Cyclic codes over finite rings. Discrete Mathematics 177, University of Duisburg.

III.Klein, P. N. (2013). Coding the Matrix: Linear Algebra through Computer Science Applications. Newtonian Press, Brown, first edition.

IV.Neubauer, A., Freudenberger, J., and Kuhn,

V. (2007). Coding Theory -Algorithms, Architectures, and Applications.Wiley-Interscience, Germany.

V.Springer, Eindhoven University, third edition.

VI.van Lint, J. (1973). Coding Theory. Springer-Verlag Berlin Heidelberg, London, 2nd edition.

VII.van Lint, J. (1999). Introduction to Coding Theory.VIII.Williams, F. M. and Sloane, N. J. A. (1981). The theory of error-corecting codes. Mathematical Library, North-Holland, third edition

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Optimal Image Compression based on Hybrid Bat Algorithm and Pattern Search

Authors:

V. Manohar, G.Laxminarayana

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00029

Abstract:

In this paper, multilevel image thresholding for image compression is proposed for the first time using Shannon entropy and Fuzzy entropy, which are maximized by the nature-inspired hybrid Bat algorithm and Pattern Search (hBA-PS).The ordinary thresholding method gives high computational complexity, but while extending for multilevel image thresholding, the optimization techniques are needed in order to reduce the computational time. Particle Swarm Optimization (PSO) and FA (Firefly Algorithm) undergo instability when the particle velocity is maximum. It is evident that Bat Algorithm (BA) is good in exploitation whereas Pattern Search (PS) is good in exploration. We hybridized the BA and PS based on their strengths and weaknesses. The proposed technique (hBA-PS) is compared with Differential Evolution (DE), PSO and BA for which the experimental results are compared in terms of Standard deviation, Computational time, Peak Signal to Noise Ratio (PSNR), Weighted PSNR and Reconstructed image quality. The performance of the proposed algorithm is found to be better with Fuzzy entropy compared to Shannon.

Keywords:

Bat algorithm,Pattern Search,Image compression,Thresholding,Shannon entropy,Fuzzy entropy,

Refference:

I.Chandra Sekhar. G.T, Sahu. R. K, Baliarsingh. A.K, and Panda.S,“Load frequency control of power system under deregulated environment using optimal firefly algorithm”, Electrical Power and Energy Systems, Vol.74 pp. 195–211, 2016

II.Chen-Kuei.Y and Wen-Hsiang. T, “Color image compression using quantization, thresholding, and edge detection techniques all based on the moment-preserving principle”, Pattern Recognition Letters,Vol. 19, pp. 205-215, 1998

III.Hooke. R and Jeeves. T.A, “Direct search” solution of numerical and statistical problems. Journal of the Association for Computing Machinery (ACM) 8 (2): 212–229, 1960

IV.Kapur. J. N, P.K.Sahoo, A.K.C Wong, “A new method for gray-level picture thresholding using the entropy of the histogram”, Computer Vision Graphics Image Process, Vol. 29, pp. 273-285, 1985

V.Kaur. L, S. Gupta, R.C. Chauhan, S.C. Saxenac, “Medical ultrasound image compression using joint optimization of thresholding quantization and best-basis selection of wavelet packets”, Digital Signal Processing,Vol.17, pp.189–198, 2007

VI.Kaveh Ahmadi, Ahmad Y. Javaid, Ezzatollah Salari, “An efficient compression scheme based on adaptive thresholding in wavelet domain using particle swarm optimization”Signal Processing:Image Communication,Vol. 32, pp. 33–39,2015

VII.Kiruba M, Sumathy V (2018) Register Pre-allocation based Folded Discrete Tchebichef Transform Architecture for Image compression. InternationaltheVLSI Journal, volume 60, pp. 13-24. https://doi.org / 10.1016/j.vlsi.2017.07.003

VIII.Luca. A, S. Termini, “A definition of a non-probabilistic entropy in the setting of fuzzy sets theory”, Information Control,Volume 20, pp. 301-312, 1972

IX.Navas. K. A, Gayathri Devi K. G, Athulya M. S, Anjali Vasudev, “MWPSNR: A new image fidelity metric”, IEEE Recent Advances in Intelligent Computational Systems (RAICS),pp. 627-632, 2011

X.Otsu. N, “A threshold selection from gray level histograms” IEEE Transactions on System, Man and Cybernetics,Vol. 66, 1979

XI.Prashant. S and Ioana. M, “Selective Thresholding in Wavelet Image Compression”, Wavelets and Signal Processing Part of the series Applied and Numerical Harmonic Analysis,Vol. 2, pp. 377-381, 2003

XII.Rabbani. M, P.W. Jones, “Digital Image Compression Techniques”, SPIE Press, Bellingham, Washington, USA, vol. 7, 1991

XIII.Rafael. B, Renato. P, “Lossy volume compression using Tucker truncation and thresholding”, The Visual Computer, Vol. 1, pp. 1-14, 2015

XIV.Rajeswari. R, “Type-2 Fuzzy Thresholded Bandlet Transform for Image Compression”, Procedia Engineering,Vol. 38, pp. 385-390, 2012

XV.Rini. D. P, Shamsuddin.S. M and Yuhaniz. S. S, “Particle Swarm Optimization: Technique, System and Challenges”, International Journal of Computer Applications(0975 -8887) Vol.:14, No.1, 2011

XVI.Sezgin. M, B. Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Electronics and Imaging, Vol. 13, pp. 146-165, 2004

XVII.Siraj. S, “Comparative study of Birge–Massart strategy and unimodal thresholding for image compression using wavelet transform” Optik,Vol. 126, pp. 5952-5955, 2015

XVIII.Skodras.A,C.Christopoulos; T.Ebrahimi,“The JPEG 2000 still image compression standard”, IEEE Signal Processing Magazine, Vol.18, Issue. 5, pp. 36-58, 2002

XIX.Tahere. I. M. and Mohammad. R. K. M, “ECG Compression with Thresholding of 2-D Wavelet Transform Coefficients and Run Length Coding”, European Journal of Scientific Research,Vol. 27, pp. 248-257, 2009

XX.Tao. W, H. Jin, L. Liu, “Object segmentation using ant colony optimization algorithm and fuzzy entropy”, Pattern Recognitation Letters,Vol. 28,pp.788–796, 2007

XXI.YangX.S,“A new metheuristicbat-inspired algorithm, in: NatureInspired Cooperative Strategies for Optimization”, Studies in Computational Intelligence, Springer Berlin,Volume 284, pp.65–74,2010

 

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ASSESSMENT OF STRUCTURAL DESIGN CAPABILITY OF BUILDING INFORMATION MODELING (BIM) TOOLS IN BUILDING INDUSTRY OF PAKISTAN

Authors:

Muhammad Shoaib Khan, Mohammad Adil, Adeed Khan

DOI NO:

https://doi.org/10.26782/jmcms.2019.04.00030

Abstract:

In Pakistan, lack of adoption of modern automated designs tools have kept the drafting, designing and construction industry, unintegrated. Almost all draftsman provide their architecture design in AutoCAD with a lot of limitation. These limitation tends to create hurdles for structural engineer while designing. After design detailing in AutoCAD and preparation of BOQ and cost estimation in a non-interoperable software is a tedious work and require time. The Architecture Engineer and Construction (AEC) trades needs such techniques to drop project rate, delivery time and increase quality, efficiency and productivity. Building Information Modeling technology can be used as a choice to get above mention parameters in which an accurate BIM model is constructed in software which is used for planning, designing and construction of the facility. In this paper BIM tools Revit and Robot structural analysis professional software are used for design and analysis of structure and in ETABs software for cross check. Detailing, BOQ and cost estimation reports are prepared at the end.

Keywords:

Building Information Modeling,,BIM model,Robot structural analysis,cost estimation,

Refference:

I.A BIM illustrates the geometry, 3-D associations, geographical data, magnitudes and possessions of building basics, rate estimations, solid records and project agenda. This model can be used to establish the whole building life cycle.

II.America, A. G. C. (2005). The contractors guide to BIM.URL: http://iweb. agc. org/iweb/Purchase/ProductDetail. aspx.

III.Azhar, S. (2011). Building information modeling (BIM): Trends, benefits, risks, and challenges for the AEC industry.Leadership and management in engineering,11(3), 241-252.

IV.Bynum, P., Issa, R. R., & Olbina, S. (2012). Building information modeling in support of sustainable design and construction.Journal of Construction Engineering and Management,139(1), 24-34.

V.CRC Construction Innovation. (2007). Adopting BIM for Facilities Management: Solutions for Managing the Sydney Opera House, Cooperative Research Center for Construction Innovation, Brisbane, Australia.

VI.Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2011).BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. John Wiley & Sons.

VII.Joannides, M. M., Olbina, S., & Issa, R. R. (2012). Implementation of building information modeling into accredited programs in architecture and construction education.International Journal of Construction Education and Research,8(2), 83-100.

VIII.Khan M. S., Khan A., Adil M., Role of Building Information Modelling (BIM) in building design Industry, INUMDC 2018, NovemberIX.Khemlani, L.; Papamichael, K.; and Harfmann, A. (November 02, 2006).

IX.Khemlani, L.; Papamichael, K.; and Harfmann, A. (November 02, 2006). The Potential of Digital

X. Migilinskas, D., Popov, V., Juocevicius, V., & Ustinovichius, L. (2013). The benefits, obstacles and problems of practical BIM implementation.Procedia Engineering,57, 767-774.

XI.Nawari, N. O. (2012). BIM standard in off-site construction.Journal of Architectural Engineering,18(2), 107-113.

XII.https://apps.autodesk.com/RVT/en/Detail/Index?id=5990906472327823538&appLang=en&os=Win64XIII.https://diroots.com/plugins/revit-plugin-sheetlink-download/

XIII.https://diroots.com/plugins/revit-plugin-sheetlink-download/

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