Archive

Abstract:

Water is not only necessary for life but it plays vital role in the social accompanied with economic growth of that specific country especially developing countries. Increasing population and rapid urbanization accompanied with climate change may reduce the supply of fresh water globally in twenty-first century. This study aims to understand current household water use and water use pattern in different five houses of different five places of KPK Pakistan for five months, to improve the efficiency of house hold water use, to encourage sustainable use and conservation of water resources. For the provision of new fresh water facilities. It’s necessary for water supply system planners to comprehend current water consumption behaviors of inhabitant, and how they use water of the new facility in future. The water consumption pattern is differs for the nations and societies and dependent on factors which may vary consumption on daily, weekly, monthly and yearly basis. These factors are availability of water source, economic, cultural, seasonal, climatic, and approachability to these water sources.

Daily water consumption pattern for five different houses in different areas of KPK for five months were found by carefully examining the time taken by pump to fill the Household overhead tanks. But in order to increase reliability of the acquired data the pumps were allowed to fill the tank till water flow for one minute at overflow pipe of the water tank was not recorded. During the period of research (March 2018 to July 2018) it was concluded that the average consumption in Charsadda (urban), Charsadda (rural), Mardan (urban), Mardan (rural) and Kohat (urban) was 102.84, 61.81, 105.99, 66.44 and 100 litres per captia per day (LPCD) respectively. Interestingly it was also observed that the trends of water consumption were almost the same in urban and rural areas of different districts of KPK

Keywords:

Daily water Consumption Pattern,Peak factors,LPCD,Overflow pipe,Flow rate,

Refference:

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V. Howard, G., Bartram, J., Water, S., & World Health Organization. (2003). Domestic water quantity, service level and health.

VI. Kumpel, E., Woelfle‐Erskine, C., Ray, I., & Nelson, K. L. (2017). Measuring household consumption and waste in unmetered, intermittent piped water systems. Water Resources Research, 53(1), 302-315.

VII. Mead, N. (2008). Investigation of domestic water end use.

VIII. Sadr, S. M., Memon, F. A., Jain, A., Gulati, S., Duncan, A. P., Hussein, W. E., & Butler, D. (2016). An Analysis of Domestic Water Consumption in Jaipur, India.

IX. Shankhwar, A. K., Ramola, S., Mishra, T., & Srivastava, R. K. (2015). Grey water pollutant loads in residential colony and its economic management. Renewables: Wind, Water, and Solar, 2(1), 5.

X. Singh, O., &Turkiya, S. (2013). A survey of household domestic water consumption patterns in rural semi-arid village, India. GeoJournal, 78(5), 777-790.

XI. Tabassum, R., Arsalan, M. H., & Imam, N. (2016) Estimation of Water Demand For Commercial Units in Karachi City

DISCRETIZATIONS OF A FRACTIONAL ORDER LOGISTIC EQUATION ARISING FROM A SIMPLE SI-TERRORIST MODEL

Authors:

Asep K. Supriatna, Asep Sholahuddin, Hennie Husniah

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00006

Abstract:

The simplest model of terrorist growth model consists of two subpopulations, namely the susceptible subpopulation (S) and the militant or infected and infectious subpopulation (I). The model is governed by a coupled of differential equation reflecting the growth of the susceptible and infected subpopulations. Assuming a constant human population, the system can be reduced to a logistic differential equation. In this paper a fractional order delayed logistic equation is discussed and the discretization in the form of piecewise constant argument is used to find the solution. We use the first and the second order discretization method in the numerical scheme and investigate the effect of the fractional order in the growth of the underlying population modelled by the equation. We found that in general the discretization method can mimic the behavior of the original logistic equation for some parameters. However, destabilizing effect may occur depending on the combination of the values of related parameters, such as the fractional order, the intrinsic growth rate, and the piecewise constant argument parameter.

Keywords:

SI-terrorist model,logistic differential equation,fractional order,piecewise constant argument,

Refference:

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SHORT TERM RAIN FORECASTING FROM RADIOMETRIC BRIGHTNESS TEMPERATURE DATA

Authors:

Kausik Bhattacharyya, Manabendra Maiti , Salil Kumar Biswas, Md Anoarul Islam, Ayan Kanti Pradhan, Pradip Kumar Ghosh, Judhajit Sanyal

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00007

Abstract:

Prediction of rainfall is important in terms of the impact of a rain event on various systems such as communication systems. Traditional approaches used to predict rain events are often sensitive to fluctuations in the datasets on which the predictions are made. The present paper therefore develops a robust machine learning based technique for accurate short term rain forecasting, based on experimentally collected data. Ground based microwave radiometer allows continuous monitoring of ambient temperature, water vapour and liquid water, and other hydrometeors through measurement of radiometric brightness temperature at different frequencies in clear and cloudy weather conditions. The radiometric brightness temperature outputs at 23.834 and 30 GHz are used to establish a relation where data trends which are precursors to rain events can be identified using this parameter. Spline equations are modeled by partitioning the dataset. The predictability of the occurrence of precipitation and the rainfall intensity has been studied based on the rise of brightness temperature from clear to cloudy weather conditions. The rise of brightness temperature at 23.834 and 30 GHz show that the precursory variations of this parameter preceding rain events are observable from 29 to 47 minutes prior to precipitation depending upon the nature of rainfall patterns. The data collected empirically displays trends that are used in this paper to provide a clear forecast of short term precipitation. Spline regression based machine learning models incorporating monthly trends, proposed in this paper improve the accuracy of prediction of short term rain events.

Keywords:

Radiometer,brightness temperature,microwave,propagation,rain,weather forecasting,

Refference:

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V. Chan, P.W., & Tam, C.M., “Performance and application of a multi-wavelength, ground-based microwave radiometer in rain now-casting”, 9th IOAS-AOLS of AMS., 2005.
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A NEW STRATEGY FOR PHASE SWAPPING LOAD BALANCING RELYING ON A META-HEURISTIC MOGWO ALGORITHM

Authors:

Ibrahim H. Al-Kharsan, Ali. F. Marhoon, Jawad Radhi Mahmood

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00008

Abstract:

The significant spread of the single-phase loads in the consumer homes make the distribution network suffering from many dangerous problems like the load unbalancing. This problem comes because the single-phase devices continuously plugged in and out to different phases each time. This paper cared about this problem and solved it efficiently by the new meta-heuristic algorithm called GWO that applied for the first time to solve the load balancing issue. The algorithm has the ability based on the smart meter included swapping mechanism to disconnects the appropriate home phases from their initial connection to specific feeders and reconnected again to other feeders for satisfying the balancing in the secondary distribution network. The algorithm adapted to reaching the balancing with a minimal number of swaps and take care of the online PVs if the consumer likes to buy energy to the national utility. It distributed all the PVs in a manner that not cause a balancing problem or lead to a stability issue. The proposed method has been applied to some unbalanced areas with random data generated in MATLAB to confirm the efficacy of the proposed algorithm.

Keywords:

Load balancing,Gray Wolf algorithm,phase swapping, solar energy,swapping factor,unbalanced feeders,

Refference:

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IX. M. M. A. Salama, “Multi-Objective Optimization for the Operation of an Electric Distribution System With a Large Number of Single Phase Solar Generators,” vol. 4, no. 2, pp. 1038–1047, 2013.
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XI. P. V. Prasad, S. Sivanagaraju, and N. Sreenivasulu, “Network reconfiguration for load balancing in radial distribution systems using genetic algorithm,” Electr. Power Components Syst., vol. 36, no. 1, pp. 63–72, 2008.
XII. R. A. Hooshmand and S. Soltani, “Fuzzy optimal phase balancing of radial and meshed distribution networks using BF-PSO algorithm,” IEEE Trans. Power Syst., vol. 27, no. 1, pp. 47–57, 2012.
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A NOVEL 3D-CNN BASED FEATURE EXTRACTION BASED CLASSIFICATION FOR DIABETIC RETINOPATHY (DR) DETECTION

Authors:

Shaik Akbar, Divya Midhunchakkaravarthy

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00009

Abstract:

Diabetic retinopathy (DR) is one of the eye diseases that results in vision loss if not diagnosed earlier. The automated computer aided models on the DR images help in accurate treatment disease prevention. Microaneurysms (MA) and red spots are the indicators of DR for disease diagnosis. Many DR classification approaches have been proposed in the literature with deep learning framework and non-linear functionality. Also, these models are not applicable to large feature space due to high true negative rate. To optimize these problems, a hybrid feature selection based deep learning classifier is used to detect the MA and red spots disease severity on the large image dataset. In this paper, a new feature extraction approach is implemented to find the essential positive bag features to the deep learning framework. A hybrid SVM classification model is used to classify the disease patterns with high true positive rate. Experimental results are simulated on different DR image class labels; results show that the hybrid deep learning classification model is better than the traditional models under various statistical metrics on large dataset.

Keywords:

Diabetic Retinopathy,Deep learning,Feature Extraction,Classification,

Refference:

I. B. Dashtbozorg, J. Zhang, F. Huang, and B. M. ter Haar Romeny, “Retinal Microaneurysms Detection Using Local Convergence Index Features,” IEEE Transactions on Image Processing, vol. 27, no. 7, pp. 3300–3315, Jul. 2018.
II. J. Xu et al., “Automatic Analysis of Microaneurysms Turnover to Diagnose the Progression of Diabetic Retinopathy,” IEEE Access, vol. 6, pp. 9632–9642, 2018.
III. K. M. Adal, P. G. van Etten, J. P. Martinez, K. W. Rouwen, K. A. Vermeer, and L. J. van Vliet, “An Automated System for the Detection and Classification of Retinal Changes Due to Red Lesions in Longitudinal Fundus Images,” IEEE Transactions on Biomedical Engineering, vol. 65, no. 6, pp. 1382–1390, Jun. 2018.
IV. L. Zhou, Y. Zhao, J. Yang, Q. Yu, and X. Xu, “Deep multiple instance learning for automatic detection of diabetic retinopathy in retinal images,” IET Image Processing, vol. 12, no. 4, pp. 563–571, 2018.
V. M. Leeza and H. Farooq, “Detection of severity level of diabetic retinopathy using Bag of features model,” IET Computer Vision, vol. 13, no. 5, pp. 523–530, 2019.
VI. P. Costa, A. Galdran, A. Smailagic, and A. Campilho, “A Weakly-Supervised Framework for Interpretable Diabetic Retinopathy Detection on Retinal Images,” IEEE Access, vol. 6, pp. 18747–18758, 2018.
VII. R. Bhoopalan and S. Sundaramoorthy, “Efficient approach for the automatic detection of haemorrhages in colour retinal images,” IET Image Processing, vol. 12, no. 9, pp. 1540–1544, 2018.
VIII. R. F. Mansour, “Evolutionary Computing Enriched Computer-Aided Diagnosis System for Diabetic Retinopathy: A Survey,” IEEE Reviews in Biomedical Engineering, vol. 10, pp. 334–349, 2017.
IX. R. Pires, S. Avila, H. F. Jelinek, J. Wainer, E. Valle, and A. Rocha, “Beyond Lesion-Based Diabetic Retinopathy: A Direct Approach for Referral,” IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 1, pp. 193–200, Jan. 2017.
X. S. Lahmiri, “High-frequency-based features for low and high retina haemorrhage classification,” Healthcare Technology Letters, vol. 4, no. 1, pp. 20–24, 2017.
XI. S. Manivannan, C. Cobb, S. Burgess, and E. Trucco, “Subcategory Classifiers for Multiple-Instance Learning and Its Application to Retinal Nerve Fiber Layer Visibility Classification,” IEEE Transactions on Medical Imaging, vol. 36, no. 5, pp. 1140–1150, May 2017.
XII. S. Qummar et al., “A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection,” IEEE Access, vol. 7, pp. 150530–150539, 2019.
XIII. S. Sil Kar and S. P. Maity, “Gradation of diabetic retinopathy on reconstructed image using compressed sensing,” IET Image Processing, vol. 12, no. 11, pp. 1956–1963, 2018.
XIV. Seoud, T. Hurtut, J. Chelbi, F. Cheriet, and J. M. P. Langlois, “Red Lesion Detection Using Dynamic Shape Features for Diabetic Retinopathy Screening,” IEEE Transactions on Medical Imaging, vol. 35, no. 4, pp. 1116–1126, Apr. 2016.
XV. W. Cao, N. Czarnek, J. Shan, and L. Li, “Microaneurysm Detection Using Principal Component Analysis and Machine Learning Methods,” IEEE Transactions on NanoBioscience, vol. 17, no. 3, pp. 191–198, Jul. 2018.
XVI. W. Zhou, C. Wu, D. Chen, Y. Yi, and W. Du, “Automatic Microaneurysm Detection Using the Sparse Principal Component Analysis-Based Unsupervised Classification Method,” IEEE Access, vol. 5, pp. 2563–2572, 2017.
XVII. Zeng, H. Chen, Y. Luo, and W. Ye, “Automated Diabetic Retinopathy Detection Based on Binocular Siamese-Like Convolutional Neural Network,” IEEE Access, vol. 7, pp. 30744–30753, 2019.

PREDICTION OF GENDER FROM FACIAL IMAGE USING DEEP LEARNING TECHNIQUES

Authors:

Ramalakshmi K, T. Jemima Jebaseeli, Venkatesan R

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00010

Abstract:

Gender recognition is a process of recognizing a person’s gender from their facial image using deep learning. The posed variation, illumination, and occlusion are some of the factors that affect in recognizing faces. These are reduced by increasing the accuracy of prediction. The network used for training the system is Convolutional Neural Network (CNN). For improving accuracy, the faces are detected and cropped from the image. Face detection is done using Open CV which detects the face by the frontal features of the face. This is done during training the network. The dataset used for training has cropped images. The proposed system predicts the person’s gender without compromising accuracy.

Keywords:

Gender recognition,convolutional neural network,VGGNet,

Refference:

I. Amit Dhomne, Ranjit Kumar and Vijay Bhan. Gender Recognition through Face using Deep Learning. Procedia Computer Science. 2018; 132: 2-10.
II. Biao Shi, HuaijuanZang, RongshengZheng and ShuZhan.An efficient 3D face recognition approach using Frenet feature of iso-geodesic curves. Journal of Visual Communication and Image Representation.2019; 59: 455-460.
III. Dhriti. K-Nearest Neighbor Classification Approach for Face and Fingerprint at Feature Level Fusion.International Journal of Computer Applications. 2012; 60(14): 0975 – 8887.

IV. DongshunCui, GuanghaoZhang, KaiHu, WeiHan and Guang-BinHuan, Face recognition using total loss function on face database with ID photos. Optics & Laser Technology. 2019; 110: 227-233.

V. Gil Levi and Tal Hassner. Age and Gender Classification Using Convolutional Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 2015.

VI. Hui-Cheng Lian, Bao-Liang Lu, ErinaTakikawa, and Satoshi Hosoi. Gender Recognition Using a Min-Max Modular Support Vector Machine. Lecture Notes in Computer Science. 2006; 210-215.
VII. HuiZhi and Sanyang Liu.Face recognition based on genetic algorithm. Journal of Visual Communication and Image Representation.2019; 58: 495-502.

VIII. Kevin Santoso and Gede Putra Kusuma.Face Recognition using Modified OpenFace. Procedia Computer Science.2018; 135: 510-517.

IX. MaafiriAyyad andChougdali Khalid.New fusion of SVD and Relevance Weighted LDA for face recognition, Procedia Computer Science.2019; 148: 380-388.

X. MaafiriAyyad andChougdali Khalid.New fusion of SVD and Relevance Weighted LDA for face recognition, Procedia Computer Science.2019; 148: 380-388.
XI. Rai P and Khanna P. Gender Classification Techniques: A Review. Advances in Computer Science, Engineering & Applications. Advances in Computer Science, Engineering & Applications. 2012; 51-59.

XII. Ranjeet Singh and Mohit Kumar Goel. Gender Classification Techniques-From Machine Learning to Deep Learning. International Journal of Computer Technology and Applications. 2016; 9(41): 77-88.
XIII. RupaliSandipKute,VibhaVyas and AlwinAnuse. Component-based face recognition under transfer learning for forensic applications.Information Sciences.2019; 476: 176-191.

XIV. Samik Banerjee and Sukhendu Das.LR-GAN for degraded Face Recognition.Pattern Recognition Letters.2018; 116: 246-253.
XV. SwaroopGuntupalliJandM. Ida Gobbini. Reading Faces: From Features to Recognition.Spotlight. 2017; 21(12): 915-916.

XVI. Vito Santarcangelo, Giovanni Maria Farinella and SebastianoBattiat. Gender Recognition: Methods, Datasets and Results. Conference: International Workshop on Video Analytics for Audience Measurement. 2015.
XVII. YangLi, WenmingZheng and ZhenCuiTong Zhang.Face recognition based on recurrent regression neural network. Neurocomputing. 2018; 297: 50-58.
XVIII. Yan Liang, Yun Zhang andXian-Xian Zeng.Pose-invariant 3D face recognition using half face. Signal Processing: Image Communication. 2017; 57: 84-90.
XIX. Yihua Chen, Ali Rahimi and Luca Cazzanti. Similarity-based Classification: Concepts and Algorithms, Journal of Machine Learning Research. 2009; 747-776.

XX. ZahraddeenSufyanu, FatmaSusilawatiMohamad, Abdulganiyu Abdu Yusuf, AbdulbasitNuhu Musa and RabiuAbdulkadir. Feature Extraction Methods for Face Recognition.International Review of Applied Engineering Research. 2016; 5(3): 5658-5668.

A COMPREHENSIVE STUDY ON MINING COMPETITORS TOWARDS HANDLING UNSTRUCTURED DATASET

Authors:

Safeena Nasreen, R. Vijaya Prakash, Seena Naik Korra

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00011

Abstract:

In the existing very competitive organization situation, there is a demand to evaluate the competitive attributes as well as aspects of a thing that most affect its competition. The evaluation of competition regularly uses the consumer opinions in terms of evaluations, rankings, as well as the mother lode of relevant information, 's coming from the web and also various other sources. Within this paper, a professional meaning of the very competitive mining is explains along with its similar jobs. Lastly, the paper provides the challenges and also usefulness in the competition mining activities with optimum renovations. We feature skillful strategies for examining strength insignificant poll datasets as well as take care of the symbolic problem of finding the greatest k opponents of a provided point. Once and for all, our team determine the nature of our outcomes and the convenience of our method using several datasets coming from different locations.

Keywords:

Mining competitors,structured dataset,unstructured dataset,

Refference:

I. Anusha Medavaka, “Enhanced Classification Framework on Social Networks” in “Journal of Advances in Science and Technology”, Vol. IX, Issue No. XIX, May-2015 [ISSN : 2230-9659]
II. Anusha Medavaka, “Monitoring and Controlling Local Area Network Using Android APP” in “International Journal of Research”, Vol. 7, Issue No. IV, April-2018 [ISSN : 2236-6124]
III. Anusha Medavaka, Dr. P. Niranjan, P. Shireesha, “USER SPECIFIC SEARCH HISTORIES AND ORGANIZING PROBLEMS” in “International Journal of Advanced Computer Technology (IJACT)”, Vol. 3, Issue No. 6 [ISSN : 2319-7900]
IV. Anusha Medavaka, P. Shireesha, “A Survey on TraffiCop Android Application” in “Journal of Advances in Science and Technology”, Vol. 14, Issue No. 2, September-2017 [ISSN : 2230-9659]
V. B. H. Clark as well as D. B. Montgomery, “Managerial Identification of Competitors,” Journal of Marketing, 1999.
VI. G. Pant and O. R. Sheng, “Web footprints of companies: Using on-line isomorphism for competition id,” Information Systems Research, vol. 26, no. 1, pp. 188– 209, 2015.
VII. J. F. Porac as well as H. Thomas, “Taxonomic mental styles in competitor definition,” The Academy of Management Review, 2008.
VIII. K. Xu, S. S. Liao, J. Li, as well as Y. Song, “Mining comparative opin- ions coming from consumer assessments for very competitive intellect,” Decis. Help Syst., 2011.
IX. M. Bergen as well as M. A. Peteraf, “Competitor identity as well as competitor study: a vast- based managing method,” Managerial and Decision Economics, 2002.
X. Q. Wan, R. C.-W. Wong, and Y. Peng, “Finding top-k successful products,” in ICDE, 2011.
XI. W. T. Few, “Managerial competition identification: Integrating the classification, economical and also business identification perspectives, “DoctoralDissertaion, 2007.
XII. X.Q. Wan, R. C.-W. Wong, I. F. Ilyas, M. T. O ¨ zsu, as well as Y. Peng, “Creating affordable items,” PVLDB, vol. 2, no. 1, pp. 898– 909, 2009.

IMPLEMENTATION OF BRT SYSTEM IN PESHAWAR CITY(PAKISTAN) : A METHODOLOGY FOR CASE STUDY ANALYSIS

Authors:

Raza Hussain, Mudasir Hussain, Mushahid Hussain, Ram Chand, Sohail Asghar

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00012

Abstract:

Large cities have increasing mobility problems due to a large number of vehicles on the streets and roads, which results in traffic jams and thus a waste of time and money. An alternative to improve traffic is to prioritize the public transportation system. Many cities across the world have recently launched ambitious programs of BRT system implementation with varying success. And Peshawar is also one of them which has launched a BRT system in 2017. This paper presents the planning management and importance of Bus rapid transit (BRT) for the city like Peshawar as it is more cost-effective mode, and to examine the level of accessibility, perception/acceptability of users on the operations of BRT in Peshawar in terms of distances, safety, affordability, reliability, travel time and waiting time at the BRT bus stops. Creating a safe corridor by combining the existing physical infrastructure and the use of communications systems in all components of the BRT system is to improve passenger safety factors in urban trips. For the study, data for all the cities have been collected from different sources such as local authority websites, organizations involved in the projects, published reports and studies, and the media.

Keywords:

Bus Rapid Transit,passengers,Corridor,Stations,Planning and Management,Peshawar city,

Refference:

I. Ali, Z., Shah, S. A. A., & Hussain, A. (2012). Growing Traffic in Peshawar: An Analysis of Causes and Impacts. South Asian Studies.
II. Asim Farooq, AamirJavaid, Dr. Astrid Karl Peshawar Local Public Transport Strategy and Organization (Pakistan) © 2015 IJEDR | Volume 3, Issue 4 | ISSN: 2321-9939

III. DesMobi, 2016. Preliminary Design Report, Peshawar Bus Rapid Transit Project.

IV. EPA, 1997: Guidelines for Sensitive and Critical Areas. Pakistan Environmental Protection Agency, Government of Pakistan, October

V. GoP, 1997: Sectoral Guidelines for Environmental Reports: – Environmental Protection Agency, Government of Pakistan, October

VI. GoP, 1997: Pakistan Environmental Protection Act 1997: – Government of Pakistan, October

VII. GoP, 1997: Policy Guidelines for Preparation and Review of Environmental Reports: – Environmental Protection Agency, Government of Pakistan, November

VIII. GoP, 1997: Policy and Procedures for filling, review and approval of Environmental Assessment Environmental Protection Agency, Government of Pakistan, November
IX. Government of Khyber Pakhtunkhw. (2015). Khyber Pakhtunkhwa in Figures 2014. Retrieved from http://kpbos.gov.pk/files/1425491934.pdf.
X. L.Da-ming, J. Xiao-jing, “General Introduction of Bus Rapicl Transport Intelligent System of Beijing South-Center Corridor”. In: Conf. Communication and Transportation Systems Engineering and Information, China, 2005
XI. Samina Islam, 2016, Land Acquisition and Resettlement Plan for Peshawar BRT

XII. Survey of Pakistan, 1997. Atlas of Pakistan. Director Map Publication, Survey of Pakistan, Rawalpindi.

XIII. World Bank. 2001. OP 4.12 – Involuntary Resettlement. The World Bank Operational

XIV. World Bank. 2003. Social Analysis Sourcebook, Incorporating Social Dimensions into Bank-Supported Projects. Social Development Department, The World Bank. December 2003.

XV. World Bank. 2005. OP 4.10 – Indigenous People. The World Bank Operational Manual. The World Bank. July 2005

THE BEHAVIOR OF FUME SILICA AND BAGASSE ASH IN CONCRETE

Authors:

Adeed Khan, Waqas Khalid, Mohammad Adil, Muhammad Hasnain, Zeeshan Haider, Mudasir Hussain

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00013

Abstract:

The nanotechnology has added new trends in concrete. By virtue of it has enhanced the concrete properties. The study is associated with the application of nano silica (Fume silica) and Bagasse Ash. The reason for the tests conducted was to discover impacts of fumesilica (FS) & B-A on the quality features of concrete. B-A & fume-Silica were used to examine whether these nano materials are capable to enhance the concrete bonds or they are weak. The tests when conducted, the nano material B-A, replaced cement by10 percent & 20 percent & (1, 2 & 3)percent of fume-Silica was added by weight. The tests when conducted, showed impressive increase in early age compressive strength and steady increase in overall compressive strength. The increased strength was due to the percentage addition nano materials. The FESEM micrographs illustrated that the nano materials have hardened the concrete bonds up to certain addition by weight and a gradual decrease was seen when the amounts of nano materials exceeded than the required ratios.

Keywords:

Concrete,Fume silica,Compressive strength,Bagasse Ash (B-A),

Refference:

I. Bartos, P. J., Sonebi, M., &Tamimi, A. K. (Eds.). (2002). Report 24: workability and rheology of fresh concrete: compendium of tests–report of RILEM Technical Committee TC 145-WSM (Vol. 24). RILEM publications.

II. Feynman, R.P. (1960). There’s plenty of room at the bottom. Engineering and Science 23, pp. 22-36.

III. Garboczi, E.J. (2009). Concrete nanoscience and nanotechnology: Definitions and applications. Nanotechnology in Construction 3, pp. 81-88.

IV. Hammond, G. P., & Jones, C. I. (2008). Embodied energy and carbon in construction materials. Proceedings of the Institution of Civil Engineers-Energy, 161(2), 87-98.

V. Kline, J., &Barcelo, L. (2012, May). Cement and CO 2, a victim of success!. In Cement Industry Technical Conference, 2012 IEEE-IAS/PCA 53rd (pp. 1-14). IEEE.

VI. Nelson, E.B. and Guillot, D. (2007). Well Cementing. Second edition, Schlumberger Ltd., Sugar Land, Texas, U.S.A., pp. 1-773.

VII. Olivier, J. G., Peters, J. A., &Janssens-Maenhout, G. (2012). Trends in global CO2 emissions 2012 report. The Hague, pp. 1-64.

VIII. Proske, T., Hainer, S., Rezvani, M., &Graubner, C. A. (2013). Eco-friendly concretes with reduced water and cement contents—Mix design principles and laboratory tests. Cement and Concrete Research, 51, 38-46.

IX. Sobolev, K., Flores, I., Hermosillo, R. (2006). Nanomaterials and nanotechnology for high-performance cement composites. In Proceedings of ACI Session on “Nanotechnology of Concrete: Recent Developments and Future Perspectives”. American Concrete Institute, 7 November, Denver, U.S.A., pp. 91-118.

X. Taniguchi, N. (1974). On the basic concept of nano-technology. In Proceedings of International Conference on Production Engineering Tokyo, Part II, Vol. 2, Japan, Society of Precision Engineering, pp. 18-23.

XI. Van den Heede, P., & De Belie, N. (2012). Environmental impact and life cycle assessment (LCA) of traditional and ‘green ‘concretes: literature review and theoretical calculations. Cement and Concrete Composites, 34(4), 431-442

DETECTION OF EXHALE ANALYSIS THROUGH ARDUINO AND INTEGRATED SENSORS

Authors:

S.Venkatesulu, SeenaNaik Korra, E.Sudarshan, A. Rajeshwar Rao

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00014

Abstract:

Nowadays population growth increasing exponentially and also health diseases increase parallel due to environment and manmade things. A common person live healthy to required things are air, food, water environmental conditions and our body functioning. Due to these above parameters health issues are affecting and medical Diagnosis is too costly. The proposed analysis is helping out to every common people with their exhale; through their exhale they can analyze present environmental and body circumstances. The basic analysis is exhale air quality index comparing some gases like carbon oxide, nitrogen, argon and oxygen. The detection of exhale and analysis forms a major application in therapeutic field. It helps in detecting the deviation real time by using Arduino and integrated sensors. The developed system systematically monitors the gases Parameters to get down various consequences so that early detection of dieses symptoms is possible. Detection of abnormality may lead to avoidance of chronic respiratory diseases

Keywords:

Exhale,Arduino,Integrated Sensors,Gases ,Detection of Abnormality,

Refference:

I. H.Donal Brooke Jenkins, Ideal and Real Gases. Dalton’s Law of Partial Pressures.

II. http://www.e-how.com

III. IvacBozic, DjordjeKlisic, Andrej Savic, Detection of Breath Phases, Serbian Journal of Electrical Engineering, Vol. 6, No.3, 389-398, December2009.

IV. K. SeenaNaik and E. Sudarshan ,” Smart Healthcare Monitoring System using Raspberry Pi on IoT Platform” ARPN Journal of Engineering and Applied Sciences ©2006-2019 Asian Research Publishing Network (ARPN). All rights reserved. Vol. 14, No. 4, February 2019. ISSN 1819-6608.

V. Laura Boccanfuso and Jason M. O’Kane, Remote Measurement of Breath Analysis in Real-time Using a High Precision, Single point, Infrared Temperature Sensor, Biomedical Robotics and Biomechatronics (BioRob), 4th IEEE RAS & EMBS Internation Conference, 2012.

VI. MittapelliNikitha, RajeshwarRaoArabelli, Smart Monitoring and Controlling of home Appliances using Internet of Things, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-4, November 2019.

VII. Paul S.Monks and Kerry A.Wills, Breath Analysis, Education in Chemistry, July 2010.

VIII. Phil Corbishley and Esther Rodriguez-Villegas, Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System, IEEE Transactions on Biomedical Engineering, Vol .55, No.1, January 2008.

IX. RajeshwarRaoArabelli , D. Rajababu, Transformer Optimal Protection using Internet of Things, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-11, September 2019.

DESIGN AND SIMULATION OF ALL-OPTICAL NOT GATES BASED ON NANO-RING INSULATOR-METAL –INSULATOR PLASMONIC WAVEGUIDES

Authors:

Hassan Falah Fakhruldeen, Tahreer Safa’a Mansour

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00015

Abstract:

Abstract In this work, the all-optical plasmonic NOT logic gate was proposed using Insulator-Metal-Insulator (IMI) plasmonic waveguides Technology. The proposed all-optical NOT gate is simulated and realized using COMSOL Multiphysics 5.3a software. Recently, plasmonic technology has attracted high attention due to its wide applications in all-optical signal processing. Due to its high localization to metallic surfaces, surface plasmon (SP) may have huge applications in sub-wavelength to guide the optical signal in the waveguides which result in overcoming the diffraction limit problem in conventional optics. The proposed IMI structure is consists of dielectric waveguides plus metallic claddings, which guide the incident light strongly in the insulator region. Our design consists of symmetric nano-rings structures with two straight waveguides which based on IMI structure. The operation of all-optical NOT gate is realized by employing the constructive and destructive interface between the straight waveguides and the nano-rings structured waveguides. There are three ports in the proposed design, input, control and output ports. The activation of the control port is always ON. By changing the structure dimensions, the materials, the phase of the applied optical signal to the input and control ports, the optical transmission at the output port is changed. In our proposed structure, the insulator dielectric material is glass and the metal material is silver. The calculated contrast ratio between (ON and OFF) output states is 3.16 (dB).

Keywords:

Surface plasmon (SP),Insulator-Metal-Insulator (IMI),all-optical NOT gates,all-optical signal processing,

Refference:

I. B. Wang and G. P. Wang, “Surface plasmon polariton propagation in nanoscale metal gap waveguides,” Optics Letters, vol. 29, pp. 1992-1994, 2004.
II. C. Min, P. Wang, X. Jiao, Y. Deng, and H. Ming, “Beam focusing by metallic nano-slit array containing nonlinear material,” Applied Physics B, vol. 90, pp. 97-99, 2008.
III. Dolatabady and N. Granpayeh, “All-optical logic gates in plasmonic metal-insulator-metal nanowaveguide with slot cavity resonator,” Journal of Nanophotonics, vol. 11, p. 026001, 2017.
IV. H. J. Lezec, A. Degiron, E. Devaux, R. Linke, L. Martin-Moreno, F. Garcia-Vidal, et al., “Beaming light from a subwavelength aperture,” Science, vol. 297, pp. 820-822, 2002.
V. H. Raether, “Surface plasmons on smooth surfaces,” in Surface plasmons on smooth and rough surfaces and on gratings, ed: Springer, 1988, pp. 4-39.
VI. M. Ota, A. Sumimura, M. Fukuhara, Y. Ishii, and M. Fukuda, “Plasmonic-multimode-interference-based logic circuit with simple phase adjustment,” Scientific reports, vol. 6, p. 24546, 2016.
VII. N. Nozhat, H. Alikomak, and M. Khodadadi, “All-optical XOR and NAND logic gates based on plasmonic nanoparticles,” Optics Communications, vol. 392, pp. 208-213, 2017.
VIII. T. Birr, U. Zywietz, P. Chhantyal, B. N. Chichkov, and C. Reinhardt, “Ultrafast surface plasmon-polariton logic gates and half-adder,” Optics Express, vol. 23, pp. 31755-31765, 2015.
IX. T. Nikolajsen, K. Leosson, and S. I. Bozhevolnyi, “Surface plasmon polariton based modulators and switches operating at telecom wavelengths,” Applied Physics Letters, vol. 85, pp. 5833-5835, 2004.
X. T. S. M. Hassan Falah Fakhruldeen, “All-optical NoT Gate Based on Nanoring Silver-Air Plasmonic Waveguide ” International Journal of Engineering & Technology, vol. vol. 7, pp. pp. 2818-2821, 2018.
XI. T. S. M. Hassan Falah Fakhruldeen, Yousif I. Hammadi, “All-Optical Logic Gates Based on Graphene Interferometric Waveguide,” JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, vol. Vol.-14, pp. 98-110, 2019.
XII. X.-S. Lin and X.-G. Huang, “Tooth-shaped plasmonic waveguide filters with nanometric sizes,” Optics Letters, vol. 33, pp. 2874-2876, 2008.
XIII. Y.-D. Wu, Y.-T. Hsueh, and T.-T. Shih, “Novel All-optical Logic Gates Based on Microring Metal-insulator-metal Plasmonic Waveguides,” in PIERS Proceedings, 2013.

LOAD BALANCED ENERGY EFFICIENT CROSS LAYER BASED ROUTING PROTOCOL FOR ACCUMULATIVE NETWORKS

Authors:

N Rashmitha, M Susmitha

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00016

Abstract:

It can be easily understood that every relay node in traditional multi-hop (TM) communication networks only attends the previous node that is near to it, which is the difficulty in routing. Using directed graphs, the modeling of these networks is performed well in order to achieve the routing. In the networks of accumulative multi-hop (AM) communication, the routing problem is far-off from understanding and yet rather interested in it. The received data energy from earlier relay transmissions can be acquired by numerous relay nodes that assist communication between a single source and a single destination in the accumulative multi-hop network which is a simple one. At this point, in single-source single-destination accumulative multi-hop networks, the difficulty in finding the optimum paths is studied. A method of Load Balanced Energy efficient cross layer based Routing protocol for accumulative networks are implemented in this paper. The end-to-end network connectivity is enhanced as well as the faults at link or/and node level is reduced in this method. Using an energy efficient neighbor node choosing method, the establishment of a set of various paths is done from the source to the destination. Efficient load balancing is offered at the node and a constant route is discovered between the source and destination that meets the delay requirement. With respect to end to end delay, throughput, and energy consumption, the proposed system is outperformed which is demonstrated in the results of simulation.

Keywords:

Accumulative,Multi-hop,Multi-path routing,Cross layer approach,Load balancing,Energy efficiency,

Refference:

I. A. Molisch, N. Mehta, J. Yedidia, and J. Zhang, “Cooperative relay networks using fountain codes,” in Proc. IEEE Global Commun. Conf. (GLOBECOM), Nov. 2006, pp. 1.

II. Agbaria, A.; Gershinsky, G.; Naaman N. &Shagin, K. Extrapolation-based and QoS-aware real-time communication in wireless mobile ad hoc networks. In the 8th IFIP Annual Mediterranean Adhoc Networking Workshop, Med-Hoc-Net 2009. pp.21-26. doi: 10.1109/MEDHOCNET.2009.5205201.

III. Ahmed, M.; Elmoniem, Abd; Ibrahim, Hosny M.; Mohamed, Marghny H. &Hedar, Abdel Rahman. Ant colony and load balancing optimizations for AODV routing protocol. Int. J. Sensor Networks Data Commun., 2012, 1. doi: doi:10.4303/ijsndc/X110203.

IV. Cai, X., Duan, Y., He, Y., Yang, J., Li, C.: Bee-Sensor-C: an energy-efficient and scalable multipath routing protocol for wireless sensor net-works. Int. J. Distrib. Sensor Netw. 26 (2015).

V. I. Maric and R. D. Yates, “Cooperative multihop broadcast for wireless networks,” IEEE J. Sel. Areas Commun., vol. 22, no. 6, pp. 1080–1088, Aug. 2004.

VI. J. Castura and Y. Mao, “Rateless coding over fading channels,” IEEE Commun. Lett., vol. 10, no. 1, pp. 46–48, Jan. 2006.

VII. J. Chen, L. Jia, X. Liu, G. Noubir, and R. Sundaram, “Minimum energy accumulative routing in wireless networks,” in Proc. IEEE INFOCOM, vol. 3. Mar. 2005, pp. 1875–1886.

VIII. J. Gómez-Vilardebó, “Routing in Accumulative Multi-Hop Networks,” in IEEE/ACM Transactions on Networking, vol. 25, no. 5, pp. 2815-2828,Oct. 2017. doi: 10.1109/TNET.2017.2703909.
IX. J. Gomez-Vilardebo, “Heuristic routing algorithms for minimum energy cooperative multi-hop wireless networks,” in Proc. 20th Eur. Wireless Conf., May 2014, pp. 1–5.-12

X. J. Gomez-Vilardebo, “Routing in accumulative multi-hop networks,” in Proc. IEEE Conf. Comput. Commun. (INFOCOM), Apr. 2015, pp. 1814–1821.

XI. L. Sobrinho, “An algebraic theory of dynamic network routing,” IEEE/ACM Trans. Netw., vol. 13, no. 5, pp. 1160–1173, Oct. 2005.

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PREDICTIVE ANALYTICS FOR E-LEARNING SYSTEM USING MACHINE LEARNING APPROACH

Authors:

S.V.N. Sreenivasu, M. Aparna

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00017

admin February 27, 2020

Abstract:

Soft-learning courses are sought-after as well as late. The need to examine understudy's presentation and anticipating their exhibition is expanding alongside it. With the developing notoriety of instructive innovation, different information digging calculations appropriate for anticipating understudy execution have been surveyed. The best calculation is based on the idea of the forecast that the staff needs to make. As the measurement of understudy information broadens the need to address and manage the complexities of the information connection, it is a test for the discovery of the understudy at risk of being short-lived. In this paper covers the ID3 and C4.5 algorithms used for Predictive Analytics on understudy's presentation and Big Data with cloud.

Keywords:

Soft-Learning Techniques,Machine Learning Approach,Basics of Predictive Analytics,Decision Tree Techniques (C4.5 and ID3),Big Data,

Refference:

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IMPROVED VIRTUAL MACHINE LOAD BALANCE USING RTEAH ALGORITHM

Authors:

Srinivasa Rao Gundu, T. Anuradha

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00018

admin February 27, 2020

Abstract:

Since forty years of computing history, cloud computing has made revolutionary changes. The daily life of human beings is completely depended on this advancement. Data centres are the backbone for the cloud computing. During the time of peak hours, load will be heavy on data center. Load balancing is needed. It provides better services to the end-user. Existing load balancing algorithms have their drawbacks. Hybrid algorithm approach is also a way to balance the load in cloud computing. Many efforts are made by several researchers in this direction. Combination of Round robin, Throttled, Equally Spread Current Execution, and Artificial Bee Colony Optimization algorithms as a hybrid algorithm (RTEAH) has shown improved results, hence it can be considered.

Keywords:

Cloud computing,Distributed Computing,Virtual Machine,Data Center,Downtime,

Refference:

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SUGGESTING MULTIPHASE REGRESSION MODEL ESTIMATION WITH SOME THRESHOLD POINT

Authors:

Omar Abdulmohsin Ali

DOI NO:

https://doi.org/10.26782/jmcms.2020.02.00019

admin February 27, 2020

Abstract:

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of this paper is to suggest a new hybrid estimator obtained by an ad-hoc algorithm which relies on data driven strategy that overcomes outliers. While the minor goal is to introduce a new employment of an unweighted estimation method named "winsorization" which is a good method to get robustness in regression estimation via special technique to reduce the effect of the outliers. Another specific contribution in this paper is to suggest employing "Kernel" function as a new weight (in the scope of the researcher's knowledge).Moreover, two weighted estimations are based on robust weight functions named "Cauchy" and "Talworth". Simulations have been constructed with contamination levels (0%, 5%, and 10%) which associated with sample sizes (n=40,100). Real data application showed the superior performance of the suggested method compared with other methods using RMSE and R² criteria.

Keywords:

Data-driven strategy,kernel,multiphase regression,robustness,threshold point,winsorization,

Refference:

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