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OBSERVED ISSUES IN CLOUD-BASED WEB COMMERCE ADOPTION FOR THE FINANCIAL TRANSACTIONS IN HYDERABAD

Authors:

Srinivasa Rao Gundu, Panem Charan Arur, Thimmapuram Anuradha

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00001

Abstract:

In the present day scenario, maximum financial transactions are being carried out with the help of Cloud-Based Web Trade (CBWT). These Cloud Oriented Web-Based Financial Transactions provide numerous advantages to the end-users. The Commodities are available at a much cheaper rate and numerous choices are left over to the customers and they are also reducing the shopping time. Particularly the time like Pandemic Situation would provide a better way to purchase multiple goods at their fingertips. There are many numbers of reasons are leftover behind the success and the downfall of such Cloud Oriented Web-Based Financial Transactions. Some of these include financial conditions, technical feasibility, and geographical location, etc. However, nowadays there it is facing many Ethical, Service-oriented, and financial challenges in this area. There is needed to make a SWOT Analysis since it is going to be the major financial gateway for numerous people.

Keywords:

Cloud-Based Web Trade (CBWT),SWOT Analysis,Online Banking,Hacking,Security,Business,

Refference:

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COMPARATIVE ANALYSIS OF PREDICTION TECHNIQUES ON THE BASIS OF TELECOM CUSTOMER CHURN

Authors:

Yasser Khan, Zeeshan Rasheed, Naeem Ahmed, Minhaj Ullah, Malik Taimur Ali, Farrukh Hassan, Sheeraz Ahmed

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00002

Abstract:

Telecommunication customer churn is considered as major cause for dropped revenue and customer baseline of voice, multimedia and broadband service provider. There is strong need on focusing to understand the contributory factors of churn. Now considering factors from data sets obtained from Pakistan major telecom operators are applied for modeling. On the basis of results obtained from the optimal techniques, comparative technical evaluation is carried out. This research study is comprised mainly of proposition of conceptual frame work for telecom customer churn that lead to creation of predictive model. This is trained tested and evaluated on given data set taken from Pakistan Telecom industry that has provided accurate & reliable outcomes. Out of four prevailing statistical and machine learning algorithm, artificial neural network is declared the most reliable model, followed by decision tree. The logistic regression is placed at last position by considering the performance metrics like accuracy, recall, precision and ROC curve.  The results from research has revealed main parameters found responsible for customer churn were data rate, call failure rate, mean time to repair and monthly billing amount. On the basis of these parameter artificial neural network has achieved 79% more efficiency as compare to low performing statistical techniques.

Keywords:

Artificial Neural Network,Prediction,Churn management,Telecom Churn,

Refference:

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V. Gordini, Niccolò, and Valerio Veglio. “Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry.” Industrial Marketing Management 62 (2017): 100-107.
VI. Idris, Adnan, Aksam Iftikhar, and Zia ur Rehman. “Intelligent churn prediction for telecom using GP-AdaBoost learning and PSO under sampling.” Cluster Computing 22, no. 3 (2019): 7241-7255.
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IX. Lee, Hyunsong, Hyunhong Choi, and Yoonmo Koo. “Lowering customer’s switching cost using B2B services for telecommunication companies.” Telematics and Informatics 35, no. 7 (2018): 2054-2066.
X. Mashchak, Nataliia, and Oksana Dovhun. “Modern Marketing and Logistics Approaches in the Implementation of E-Commerce.” In Integration of Information Flow for Greening Supply Chain Management, pp. 375-391. Springer, Cham, 2020.
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XIV. Rachid, Ait Daoud, Amine Abdellah, Bouikhalene Belaid, and Lbibb Rachid. “Clustering Prediction Techniques in Defining and Predicting Customers Defection: The Case of E-Commerce Context.” International Journal of Electrical and Computer Engineering 8, no. 4 (2018): 2367.
XV. Stiassny, Alfred, Agnes Somosi, and Krisztina Kolos. “Enhancing customer retention in case of service elimination? An empirical investigation in telecommunications.” (2019).
XVI. Taniguchi, Tadanari. “Self-organizing map analysis and classification of consumption trends of foreigners visiting Japan using a questionnaire survey.” Journal of Global Tourism Research 3, no. 2 (2018).
XVII. Thuethongchai, Nopsaran, Tatri Taiphapoon, Achara Chandrachai, and Sipat Triukose. “Adopt big-data analytics to explore and exploit the new value for service innovation.” Social Sciences 9, no. 3 (2020): 29.
XVIII. Van den Poel, Dirk, and Bart Lariviere. “Customer attrition analysis for financial services using proportional hazard models.” European journal of operational research 157, no. 1 (2004): 196-217.
XIX Wang, Li, Chaochao Chen, Jun Zhou, and Xiaolong Li. “Time-sensitive Customer Churn Prediction based on PU Learning.” arXiv preprint arXiv:1802.09788 (2018).
XX. Yasser Khan, Shahryar Shafiq, Sheeraz Ahmed, Nadeem Safwan, Mehr-e-Munir, Alamgir Khan. : ‘Factors affecting Service Quality, Customer Satisfaction and Customer Churn in Pakistan Telecommunication Services Market’. J. Mech. Cont.& Math. Sci., Vol.-14, No.-4, July-August (2019) pp 576-594. DOI : 10.26782/jmcms.2019.08.00048

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A NEW EVOLUTIONARY METHOD TO PARAMETERS AND ORDERS IDENTIFICATION AND SYNCHRONIZATION OF CHAOTIC FRACTIONAL-ORDER SYSTEMS

Authors:

Ali Soleimanizadeh, Mohammad Ali Nekui

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00004

Abstract:

System identification is an important task in the control theory. Classical control theory is usually known for integer-order processes. Nowadays real processes are fractional order usually. According to a large number of fractional-order systems, identification of these systems is so important. This paper aims to evaluate an improved Biogeography-based Optimization (BBO) approach to estimate the parameters and orders of fractional-order systems. After that, a method based on this algorithm has been introduced to synchronization of chaotic systems. Results show that the proposed scheme has high accuracy.

Keywords:

Fractional-order system,System identification,Biogeography-based Optimization,

Refference:

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V. Bouzeriba A. Fuzzy Adaptive Controller for Synchronization of Uncertain Fractional-Order Chaotic Systems. In Advanced Synchronization Control and Bifurcation of Chaotic Fractional-Order Systems 2018 (pp. 190-217). IGI Global.
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VII. Doye IN, Salama KN, Laleg-Kirati TM. Robust fractional-order proportional-integral observer for synchronization of chaotic fractional-order systems. IEEE/CAA Journal of Automatica Sinica. 2019 Jan;6(1):268-77.
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A NEW CONSTRUCTION OF OS OF SUBALGEBRAS AND INVARIANT SOLUTION OF THE BLACK-SCHOLES EQUATION

Authors:

Zahid Hussain, Sadaqat Hussain, Suhail Abbas, Shams-ur-Rehman, Shahid Hussain

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00005

Abstract:

In this manuscript, the Lie group technique is applied to construct a new OS and invariant solutions of a one-dimensional LA, which describes the symmetries properties of a nonlinear Black-Scholes model. The structure of LA depends on one parameter. We have shown a novel way to construct the so-called OS of subalgebras of the Black-Scholes equation by utilizing the given symmetries. We transform the symmetries of the Black-Scholes equation into a simple ordinary differential equation called the Lie equation, which provides us a way through which to construct a new optimal scheme of subalgebras of the Black-Scholes through applying the concept of LE. The OS which consists of minimal representatives is utilized to develop the invariant solution for the Black-Scholes equation. The fundamental use of the Lie group analysis to the differential equation is the categorization of group invariant solutions of differential equations via OS. Finally, we have utilized the OS to construct the invariant solution of the Black-Scholes equation.

Keywords:

Black-Scholes Equation,Generators,LE,OS,Invariant solution,

Refference:

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XIII. N. H. Ibragimov. “CRC Handbook of Lie group analysis of differential equations. Volume1,2,3 CRC Press”, Boca Raton, Ann Arbor, London, Tokyo, (1994,1995,1996).
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XXIII. Sivaram. B. : ‘COMPARATIVE STUDY OF SOLUTION METHODS OF NON-HOMOGENEOUS LINEAR ORDINARY DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS’. J. Mech. Cont.& Math. Sci., Vol.-16, No.-1, January (2021) pp 1-18. DOI : 10.26782/jmcms.2021.01.00001.

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REAL-TIME MONITORING SYSTEM OF POWER TRANSFORMER USING IoT AND GSM

Authors:

Jehan Parvez, Salman Khan, Imran Khan

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00006

Abstract:

The power transformer is the most important and expensive element in the power system. It is used to change the voltage levels at different stages in a power system. The foremost responsibility of the utility grid is to ensure smooth and reliable availability of power through the transformer. But there are different abnormal conditions that can occur in the transformer such as overheating, overexcitation, abnormal frequency, overload, abnormal voltage, open circuit, and breaker failure. These abnormal conditions reduce the life, efficiency, and performance of the transformer, as a result, the overall reliability of the power system gets decreased. Moreover, in case of any failure of the power transformer, the consumers will suffer a severe power outage and consequently, a massive economic loss will occur. During abnormal conditions, the health of a transformer is deteriorating, and it is very important, that the operator should act quickly and accurately in terms of any abnormality occurred. For this purpose, need a proper health monitoring system that should properly monitor the health of the transformer and take proper action to prevent it from greater damages. The proposed system is user-friendly, flexible, reliable, and presenting more functionalities with almost 10 times lower cost than the existing system. This research work has developed a low-cost GSM and internet of things (IoT) based indigenous prototype for transformer monitoring that will be able to early inform the relevant staff through SMS and web data for the different abnormal conditions.

Keywords:

Transformer,Health,Monitoring,GSM,IoT,

Refference:

I. A. Küchler, High Voltage Engineering: Fundamentals-Technology-Applications. Springer, 2017.
II. A. M. Elmashtoly and C.-K. Chang, “Prognostics Health Management System for Power Transformer with IEC61850 and Internet of Things,” Journal of Electrical Engineering & Technology, vol. 15, no. 2, pp. 673-683, 2020.
III. G. Arun, R. Arunkumar, K. K. Kumar, P. Muthupattan, and G. Kannayeram, “GSM BASED SINGLE PHASE DISTRIBUTION TRANSFORMER MONITORING AND CONTROL,” Journal of Critical Reviews, vol. 7, no. 12, pp. 637-640, 2020.
IV. I. Aniebiet and I. S. Fidelis, “Design and Implementation of Gsm Enabled Remote Sensor for Monitoring Power Transformer Operation,” American Journal of Electrical and Computer Engineering, vol. 4, no. 2, pp. 62-71, 2020.
V. J. Jiang, R. Chen, M. Chen, W. Wang, and C. Zhang, “Dynamic fault prediction of power transformers based on hidden Markov model of dissolved gases analysis,” IEEE Transactions on Power Delivery, vol. 34, no. 4, pp. 1393-1400, 2019.
VI. M. Ghiasi, N. Ghadimi, and E. Ahmadinia, “An analytical methodology for reliability assessment and failure analysis in distributed power system,” SN Applied Sciences, vol. 1, no. 1, pp. 1-9, 2019.
VII. M. Subba Rao, SakilaGopal Reddy, K. Sai Janardhan, Sangu Harish Reddy. : ‘DESIGN OF SINGLE LINE TO THREE LINE POWER CONVERTER’. J. Mech. Cont. & Math. Sci., Vol.-15, No.-8, August (2020) pp 822-835. DOI : 10.26782/jmcms.2020.08.00067.
VIII. Maheswari Muthusamy, A.K. Parvathy. : ‘ARTIFICIAL INTELLIGENCE TECHNIQUES-BASED LOW VOLTAGE RIDE THROUGH ENHANCEMENT OF DOUBLY FED INDUCTION WIND GENERATOR’. J. Mech. Cont.& Math. Sci., Vol.-15, No.-3, March (2020) pp 125-139. DOI : 10.26782/jmcms.2020.03.00010
IX. P. Mercy, N. U. Maheswari, S. D. Devi, and V. Dhamodharan, “Wireless protection and monitoring of power transformer using PIC,” IJCSMC, vol. 4, no. 3, pp. 0634-640, 2015.
X. R. V. Jadhav, S. S. Lokhande, and V. N. Gohokar, “Monitoring of transformer parameters using Internet of Things in Smart Grid,” in 2016 International Conference on Computing Communication Control and automation (ICCUBEA), 2016: IEEE, pp. 1-4.
XI. Y. Sun et al., “A temperature-based fault pre-warning method for the dry-type transformer in the offshore oil platform,” International Journal of Electrical Power & Energy Systems, vol. 123, p. 106218, 2020.

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GASOLINE CONSUMPTION PREDICTION VIA DATA MINING TECHNIQUE

Authors:

Soma Gholamveisy

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00007

Abstract:

Due to the increasing dependence of human life on energy, it plays a crucial role in the functioning of the various economic sectors of the countries, potentially and actually. Fuel products, especially gasoline, given their importance in the transportation sector, play major roles in the economic growth and development of countries. Hence, the authorities in each country have to control the fuel supply and demand parameters accurately with a more accurate prediction of fuel consumption and proper planning in the direction of consumption. The purpose of this study is to find appropriate methods and approaches for forecasting gasoline consumption in Tehran using data mining methods. For this purpose, daily consumption data of gasoline stations were collected in 5 different regions of Tehran during the period of 2008-2013. Then, these numbers were predicted on a daily, weekly, monthly, and seasonal basis for analyzing the consumption at different time intervals. The standardization method was also used to match the scales. After data pre-processing, gasoline consumption was predicted using the multi-layer perceptron (MLP) neural network method. The gasoline consumption forecast was evaluated based on the mean squared error (MSE), mean, and mean absolute error (MAE) criteria. The results indicate that the artificial neural network (ANN) can accurately predict gasoline consumption in five different regions of Tehran.

Keywords:

data mining,gasoline consumption,ANN-MLP,prediction,

Refference:

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EFFECTS OF TRAFFIC LOAD, TEMPERATURE AND MATERIAL PROPERTIES ON RUTTING IN FLEXIBLE PAVEMENTS

Authors:

Muhammad Asim, Haseeb Ullah, Haider Khan, Muhammad Yahya

DOI NO:

https://doi.org/10.26782/jmcms.2021.09.00008

Abstract:

Rutting (permanent deformation) is one of the most common and serious kinds of damage to flexible pavement, particularly in countries with high summer temperatures. Rutting also occurs when there is a lot of traffic and the use of poor materials. Pavement engineering is greatly influenced by the use of materials such as asphalt and cement in modern times. To study the effect of load, high temperature, and materials properties on rutting damage of flexible pavement this paper is the best approach to all these concerned issues related to rutting. Abaqus ver.6.12.1 has been used to simulate flexible pavement under different loading and thermal conditions. Three models have been developed in this paper, the first model simulated against traffic loading only, the second model shows combined traffic and thermal loading while the third model related with the change of materials property in terms of Young’s modulus (E).

Keywords:

Flexible Pavements,FEM,Rutting,Traffic loads,Temperature,

Refference:

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