The Solution of a Transportation Problem is obtained in two phases. The first phase is finding the initial basic feasible solution by using various methods. The optimal solution is obtained either by using stepping stone method or by MODI method in the second phase. Here we proposed the MODI method with modifications to solve the degenerate transportation problem. This is also illustrated with numerical example.

Keywords: Transportation problem, degeneracy, difference cost,optimum solution.

[1]. Taha.H.A., Operations Research-Introduction, Prentice Hall of India, New Delhi, 2004.
[2]. Sharma J.K., Operations Research- Theory and Applications, Mac-Millian India, New Delhi, 2005.
[3]. An Algorithm for Solving the Transportation Problem, A.Gleyzal.
[4]. F.L. Hitchcock, 1941, the distribution of a product from several sources to numerous localities, Journal of Mathematical Physics, vol.20, pp. 224-230.
[5]. Koopmans T. C., 1949, Optimum Utilization of Transportation System, Econometrica, Supplement vol.17.
[6]. G.B. Dantzig, 1951, Linear Programming and Extensions, Princeton University Press, Princeton.

It investigates the strategic importance of using the best practices in the operational planning process, to achieve quality improvement and the expectation of time in the urban bus service. It is a case study of a pilot project implemented in São Paulo, with demonstration of qualitative and quantitative data. The model presented is based on the implementation of a Quality Program in a public organization, manager of services in public and urban transportation by bus. The theoretical foundations show different conceptions, in qualitative and quantitative research, and make a brief discussion about the underlying context of the service. The systemic approach used in the elaboration of the model masters a basic structure, presented, and can be used in the implementation processes of Quality Programs and Resource Optimization, in urban bus transportation................

Keywords: Operation; Control; Mobility; Traffic; Connectivity.

[1]. ANTP. Documentos Setoriais ANTP – O Transporte Clandestino no Brasil. São Paulo: Ed. ANTP, 2000. n. 1, julho
[2]. BICALHO, M.P. Modos de Transporte Urbano de Passageiros. Mobilidade Urbana no Brasil. São Paulo: Fundação Perseu Abramo, 2016. p. 117-173.
[3]. CHASE, R.B. et al. Administração da produção e operações para vantagens competitivas. 11. ed. São Paulo: Mcgraw-Hill, 2006.
[4]. CHIAVENATO, I. Introdução à Teoria Geral da Administração. 6. ed. Rio de Janeiro: Campus, 2000.
[5]. CRUZ, J.A. et al. Qualidade e produtividade nos Transportes – Transporte Urbano de Passageiros. São Paulo: ed. Cengage Learning, 2008

The concept of Ride-Sharing (RS) is very important valuables of environment because it saving energy and destroy the traffic pressure or traffic congestion. Riding sharing helps to improve resource utilization by sharing the resource for multiple users. Generally maximizing route ride sharing is more difficult and crucial process, because ride sharing includes shared route's distance, total travel distance, route percentage, and waiting time and peak-time traffic. The previous studies have used several features to maximizing route ride sharing, which has been collected from shared route percentage (SRP). The main drawbacks of the previous studies are that need accurate and more number of SRP. Data mining is an effective way to solve such problems in the road network. This paper surveys about the recent data mining various techniques and methods used to ride-sharing (RS) problem.

Keywords: Ride-sharing, Dynamic ride-sharing, shared route percentage, bigraph matching, join-based sharing, and search-based sharing.

[1]. Samina Arshad, Hamid Turab Mirza, Ibrar Hussain."A new method for optimization of dynamic ride sharing system". Journal of Applied Environmental and Biological Scienecs. J.Appl.Environ. Biol. Sci., 5(5) 73-89, 2015.
[2]. Mohammad Asghari, dingxiong Deng, Cyrus Shahabi, Ugur demiryurek, Yaguang Li. "Price-aware Real-time Ride-sharing at Scale An Auction-based Approach".
[3]. Qiulin Lin, Lei Deng, Jingzhou Sun, Minghua Chen. "Optimal Demand-Aware Ride-Sharing Routing".
[4]. Xiaohui Bei, Shengyu Zhang. "Algorithms for Trip-Vehicle Assignment in Ride-Sharing".
[5]. Masayo Ota, Huy Vo, Claudio Silva, Juliana Freire. "STaRS: Simulating Taxi Ride Sharing at Scale".

The Brahmaputra is one of the major and mightiest rivers of India. It passes about 700 km through the middle of the state Assam and finally enters at Bay of Bengal (India). The river Brahmaputra is very much potential in producing the seasonal flood and river bank erosion in its entire course in Assam. Every year the river migrates laterally here and there by cutting its both alluvial banks and thus huge amount of sediments are produced by destroying acres of fertile land causing tremendous loss of thepoor state. It is observed that the rate of erosion is very high in certain locations, the channels are changed completely within a short interval of time with frequent change of depth of channels. After observing the entire course of river in lower Assam region, it has come to notice that the river is eroding its both banks in many locations, but the extent of erosion is not same in all locations and hence it has been attempted to apply the modified Rosgen's method to identify the nature and erosion vulnerability of the locations under consideration.

Keywords: Assam, Brahmaputra, braided, bank angle, clay content, erosion, hazard, migration, Rosgen, vulnerability.

[1]. David L. Rosgen P.H. 2008, A practical method of computing stream bank erosion rate. Wildland hydrology.
[2]. ShreyaBandopadhyay, SusmitaSaha, Kapil Ghosh, Sunil Kr De. Validation of BEHI model through field generation data for assessing bank erosion along the river Haora, Earth Science India, eISSN:0974-8350.
[3]. Purusottam Nayak, Bhagirath Panda 2016. Brahmaputra and socio economic life of people of Assam, A technical report.
[4]. Rosgen, David L. 1973. The use of Color Infrared Photography for the Determination of Sediment Production. In: Fluvial Process and Sedimentation, Canadian National Research Council. Edmonton, Alberta, Canada. 381- 402.
[5]. Rosgen, David L. 1993. Stream classification, streambank erosion and fluvial interpretations for the Lamar River and main tributaries. Technical Report for USDI Park Service, Yellowstone National Park. 82pp.

this study examined the influence of the Co doping concentration on the structural and optical properties of Cd1-xCoxS nanoparticles synthesized using simple Co-precipitation route at room temperature. The samples were characterized by X-ray diffraction and FTIR spectroscopy. From XRD patterns, Co doped CdS nanoparticles have cubic crystal structure with single in phase. The lattice constant and volume of unit cell were increased with increasing Co doping. The crystallite size of prepared nanoparticles increased with increasing Co content from 2.07 to 2.57 nm. The surface morphology of prepared samples was characterized by using scanning electron microscopy (TEM). The pure and Co doped CdS samples have spherical like structured. The dislocation density and strain was decreased with increasing Co doping. The functional groups of the nanoparticles have been identified by FTIR studies. The results showed that Co doping strongly affects the structural and optical properties CdS nanoparticles.

Keywords: Nanocrystals; CdS; dislocation density; strain; FTIR study.

[1]. S. Erra, C. Shivkumar, H. Zhao, K. Barri, D.L. Morel, C.S. Frekides, Thin films solids, 515 (2007) 5833.
[2]. J.R. Lakowicz, I. Gryczynski, G. Piszczek, C.J. Murphy, J. Phys. Chem. B, 106(21) (2002) 5365.
[3]. N.M. Ushakow, GYu Yiurkov, Karanov, N.A. Kataeva, I.D. Kosobudskii, S.P. Gubin, Opt. Spectrosc. 100 (2006) 414.
[4]. N. Venkatram, D.N. Rao, M.A. Akundi, Opt. Express 13 (2005) 867.
[5]. Z. Han, Q. Yang, J. Shi, GQ. Lu, SW, Lewis, Solid State Sci., 10 (2008) 563

This paper Discuss Medium term wind power prediction based wind speed, wind direction, air temperature and power utilizing wind turbine information collected at 72‟s intervals. A time-series model display way to deal wind behavior is studied. Both exponential smoothing and data-driven models are created for wind prediction. An overview of the ongoing improvements in machine learning techniques focused on prediction using Ensemble Learning. The machine learning techniques rapidly developed and Ensemble Learning techniques have been used for prediction. In this paper, to deal with the training samples dynamics and improve the forecasting accuracy, K-means clustering is utilized to classify the samples into several categories, which contain the data of meteorological conditions and historical power data.............

Keywords: wind power forecast, k-means clustering, ensemble learning, bagging neural network, WEKA Tool

[1]. J. Jung and R. P. Broadwater, "Current status and future advances for wind speed and power forecasting," Renew. Sust. Energ. Rev., vol. 31, no. 2, pp. 762-777, Jan. 2014.
[2]. D. Carvalho, A. Rocha, M. Gomez-Gesteira, and C. Santos, "A sensitivity study of the WRF model in wind simulation for an area of high wind energy," Environ. Model. Softw., vol. 33, no. 7, pp. 23-34, Mar. 2012.

Location prediction is broadly used to figure out user‟s next place to visit in light of his/her versatility logs. A stunning accessibility of smart carrying and constantly online capacities, these days‟ lots of clients is getting used to 'check-in' their portability exercises on numerous prevalent services and applications. , i.e., report their location and audits from their PDAs or other computerized accessories. Delegate check-in applications like Foursquare. In these a basic issue in location information processing, invaluable for reconnaissance, business, and individual applications. It is extremely challenging because of the sparsity issues of check-in information and Heterogeneousness i.e., the location, content and transient information. A regularly overlooked issue in ongoing investigations is the assortment crosswise over various check-in situations..............

Keywords: Location Prediction, Geographical Closeness, Trajectory Data, Check-in Behavior Analysis, machine learning.

[1]. J. Sang, T. Mei, J.-T. Sun, C. Xu, and S. Li, "Probabilistic sequential pois recommendation via check-in data," in Proceedings of the 20th International Conference on Advances in Geographic Information Systems, 2012, pp. 402–405.
[2]. X. Liu, Y. Liu, K. Aberer, and C. Miao, "Personalized point-of interest recommendation by mining users‟ preference transition," in Proc. of CIKM, 2013, pp. 733–738.
[3]. J.-D. Zhang, C.-Y. Chow, and Y. Li, "Lore: exploiting sequential influence for location recommendations," in Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2014, pp. 103–112.
[4]. W. Wang, H. Yin, S. Sadiq, L. Chen, M. Xie, and X. Zhou, "SPORE: A sequential personalized spatial item recommender system," in Proc. of ICDE, 2016, pp. 954–965.
[5]. D. Lian, X. Xie, V. W. Zheng, N. J. Yuan, F. Zhang, and E. Chen, "CEPR: A collaborative exploration and periodically returning model for location prediction," TIST, vol. 6, p. 8, 2015.

The integration of cloud and Internet of Things (IoT), named CloudIoT, has been considered as an enabler for many different applications.However the security issue is one main concern that some organizations hesitate to adopt such technologies while some just ignore the security issue while integrating the CloudIoT into their business. Therefore, given the cloud-resource providers and IoT devices, how to evaluate their security level becomes an important issue to promote the adoption of CloudIoT as well as reduce the business security risks. To solve this problem, considering the importance of the business data in CloudIoT, we develop an end-to-end security assessment framework based on software defined network (SDN) to evaluate the security level for the given CloudIoT offering. Specially, in order to simplify the network controls and focus on the analysis about the data flow through CloudIoT...............

Keywords: Storage management system; Dataflow management system; Secured Storage.

[1]. J. Baek, R. Safavi-Naini, and W. Susilo. Public key encryption with keyword search revisited. In International conference on Computational Science and Its Applications, pages 1249-1259. Springer-Verlag, 2008.
[2]. Belkin, N.J. and Croft, W.B. Information filtering andinformation retrieval: two sides of the same coin? Commun.ACM 35, 12 (1992), 29-38.
[3]. Liu, H. and Jacobsen, H.-A. A-TOPSS: a publish/subscribe system supporting approximate matching. Proceedings of the 28th international conference on Very Large Data Bases, VLDB Endowment (2002), 1107-1110.
[4]. Erhard Rahm, Philip A. Bernstein: A survey of approaches to automatic schema matching. VLDB Journal 10(4) (2001).
[5]. Jayant Madhavan, Philip A. Bernstein, Erhard Rahm:Generic Schema Matching with Cupid. VLDB 2001: 49-58.

The present work attempts to look into the present educational condition of the members of Namasudra community in Karkha and Gerul village of Banshihari block under Dakshin Dinajpur District of the Indian state of West Bengal. The study is basically based on primary data although some books, journals, research articles, research reports have been used as a source of secondary data. The primary data has been collected by interview technique with the help of standard questionnaires and participant observation technique in the year 2018. For this purpose multi-stage stratified random sampling have been applied. The collected data first be tabulated, processed and then presented and interpreted using different cartographic techniques and diagrams. The analysis reveals that there is a significant variation in terms of male female literate...............

Keywords: Educational Scenario, Namasudra Community, Equitable Participation, Critical Synthesis, Development.

[1]. Abdul Kalam, A.P.J. (2005) "For Dignity of Human Life", Yojana , 49 September, 24.
[2]. Anand, Mily Roy and Yadav, Mona (2006): The inclusion of SC girls in education: A long path ahead. Social Change. Vol. 36. No. 4. December 2006. P. 114-130.
[3]. Biswas, N. B.(2004): Emergence of Namasudra as a sub-caste: an Ethnological view. Man In India, 91 (3-4) : 559-566 © Serials Publications.
[4]. Chandrashekar and Akash, S.B (2011): Educational and Occupational Aspirations of Scheduled Caste College Students: An Empirical Study. Southern Economist, Vol. 49. No. 17. 1st January 2011. P. 49-52.
[5]. Chatterjee, S.K., 2000; Educational Development of Scheduled Castes, Gyan Publishing House, New Delhi.

This paper presents the development of an artificial neural network model that predicts wire cut EDM response parameters. Pulse on time, pulse off time, current and servo voltage have been taken as control parameters. Design of experiment has prepared by using taguchi L16 orthogonal array. Dimensional deviation and surface roughness taken as response parameters, these parameters represents the dimensional accuracy and surface quality of EN-47 spring steel part, machined through wire cut EDM process. Process parameters, machining conditions, tool material are the factors that affect product quality. Better understanding of these factors reduces material wastage, machining cost, machining time and improves product quality and productivity.

Keywords: Artificial neural network, dimensional deviation, EN-47, surface roughness, wire cut EDM.

[1]. Priyesh N. Santoki, Prof. Ashwin P. Bhabhor, A review - Status of recent developments & effect of machining parameters on performance parameters in EDM, International Journal of Innovative and Emerging Research in Engineering, 2(1), 2015.
[2]. C. Sommer and S. Sommer, Complete EDM Handbook, 23-31.
[3]. Kumar Sandeep, Current research trends in electrical discharge machining: a review, Research Journal of Engineering Sciences, 2(2), 2013, 56-60.
[4]. Foroogh Hosseinzadeh, P . J. Bouchard, Towards good practice guidelines for the contour method of residual stress measurement, Journal of Engineering, 2014, 1-16.

The theoretical basis of digital modulation and assess the execution of BPSK framework as for Bit error Rate lastly actualize Binary Phase shift Key modulation system in MATLAB .This paper researches the problem of recouping a n-dimensional BPSK signal x0 ∈ {-1, 1}n from m-dimensional estimation vector y = Ax+z, where An and z are thought to be Gaussian with iid passages. We consider two variations of decoders in view of the regularized slightest squares taken after by hard-thresholding: the situation where the curved unwinding is from {-1, 1}n to ℝn and the container obliged situation where the unwinding is to [-1, 1]n. For the two cases, we infer a correct articulation of the bit error likelihood when n and m become at the same time huge at a settled proportion. For the case compelled case.........

Keywords: Digital Modulation, Fading, BER (Bit Error Ratio), SNR (Signal to Noise Ratio)

[1]. Peter JG Teunissen, ―The least-squares ambiguity decorrelation adjustment: a method for fast gps integer ambiguity estimation,‖ Journal of geodesy, vol. 70, no. 1-2, pp. 65–82, 1995.
[2]. Jeffrey C Lagarias and Andrew M Odlyzko, ―Solving low-density subset sum problems,‖ Journal of the ACM (JACM), vol. 32, no. 1, pp. 229–246, 1985.
[3]. PengHui Tan, Lars K Rasmussen, and Teng J Lim, ―Constrained maximum-likelihood detection in cdma,‖ IEEE Transactions on Communications, vol. 49, no. 1, pp. 142– 153, 2001.
[4]. Aylin Yener, Roy D Yates, and SennurUlukus, ―Cdma multiuser detection: A nonlinear programming approach,‖ IEEE Transactions on Communications, vol. 50, no. 6, pp. 1016–1024, 2002.
[5]. Charles Jeon, Arian Maleki, and ChristophStuder, ―On the performance of mismatched data detection in large MIMO systems,‖ CoRR, vol. abs/1605.02324, 2016.

In this paper, unified framework for voice activity detection (VAD) and speech enhancement is proposed. In the proposed framework, there is common import of data amongst VAD and speech enhancement blocks. Another and robust VAD algorithm is actualized for the VAD block of the brought together framework. The recently proposed VAD algorithm utilizes a periodicity measure and a vitality measure got from phantom vitality circulation and otherworldly vitality distinction of the info speech information. For the speech enhancement block, the changed Kalman filtering (MWF) approach is used. It has been demonstrated that the usage of data trade between the VAD and MWF algorithms in the brought together framework builds the execution of the two algorithms and the proposed bound together framework enhances the robustness of a speech acknowledgment framework essentially. Both of the improved algorithms are no iterative. Consequently, the proposed brought together framework is computationally appealing for continuous applications.

Keywords: Speech enhancement, voice activity detection, noise suppression, Kalman filter

[1]. Dongwen Ying, Yonghong Yan, Jianwu Dang, and F.K. Soong. Voice activity detection based on an unsupervised learning framework. Audio, Speech, and Language Processing, IEEE Transactions on, 19(8):2624 –2633, November 2011. ISSN 1558-7916.doi: 10.1109/TASL.2011.2125953.URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5728850&tag=1.
[2]. A. Benyassine, E. Shlomot, H.-Y. Su, D. Massaloux, C. Lamblin, and J.-

Solar energy is radiant and heat energy from the sun which is harnessed using variety of technologies including thermal and photovoltaic. It is most reliable and important form of renewable energy which is present in abundance in earth. The high average solar radiation in India and continuous depletion of conventional resources has lead on the urge of utilizing the solar energy as an alternating energy resource to meet up the required demands. therefore, to meet the load demands solar and other renewable energies are tied up with grid. The objective of this work is to estimate the cost for 500kW on-grid solar photovoltaic power plant with the LCOE simulation. The specifications of the data and equipment are provided based on the availability of information in India. The profit is calculated on LCOE and payback period.

Keywords: Solar photovoltaic (SPV), LCOE (levelized cost of electricity), DC (direct current),kW (kilo watt), PPA (power purchase agreement), PV (photovoltaic).

[1]. Zoheb Hasan khan, Savita Maurya, Ramayna, Swati Agariya.
[2]. Vinay Janarsan Shetty and Keerti Kulkarni "Cost analysis estimation of 500kw grid connected solar photovoltaic plant: a case study" India 2014.
[3]. Normaz Lina Mat Isa, Chee Wei Tan, AHM Yatim "A technoeconomic assessment of grid connected photovoltaic system for hospital building" 2016.
[4]. K. Azizian, M. Yoghoubi, R. Hesami, P. Kanan "Design analysis for Shizan Solar power plant to 500kW power generation capacity" 2011.
[5]. Tarjanne Risto, Kivisto Aija "Comparison of electricity generation costs".2008.
[6]. Seth B. Arling, Fengiqui You, Thomas Veselka and Alfonso Velosa "Assumptions of photovoltaic system and the levelized cost of energy".