Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2201

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1). S. I. Sarsam, Sarsam and Associates Consult Bureau (SACB), Baghdad, Baghdad, IRAQ

Abstract :

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Asphalt concrete pavement usually practices load repetitions and environment impacts. The quality of the pavement declines through the service life. However, the asphalt pavement can heal the micro cracks by itself. In the present investigation, slab samples of asphalt concrete were prepared at optimum asphalt cement binder requirement with the aid of roller compaction. Asphalt concrete prism specimens were extracted from the slab samples and subjected to four points flexural fatigue test at 20° C. The test was stopped when the stiffness of asphalt concrete declines to 50 % of its value at the start of the test. The beam specimens were subjected to external heating at 60° C for 120 minutes to enhance the viscoelastic properties through micro cracks healing through heating-induced healing method. Beams were tested under repeated flexural bending after the healing process. The variation in the stiffness, fatigue life, phase angle, dissipated energy and deformation after healing was monitored. It was concluded that the flexural stiffness, the phase angle, and dissipated energy were increased after healing while the deformation declines. The crack healing is recommended as a sustainable process to enhance the pavement quality. Keywords: Asphalt concrete, Healing, Micro cracks, Stiffness, Flexure, Dissipated energy, Phase angle.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2202

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1). Dr. S. Vijayarani, Bharathiar University, Coimbatore, Tamil Nadu, India
2). Dr. S. Sharmila, Bharathiar University, Coimbatore, Tamil Nadu, India
3). M. Lavanya, Bharathiar University, Coimbatore, Tamil Nadu, India

Abstract :

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Privacy-Preserving Data Mining (PPDM) develops algorithms for altering sensitive data. The private knowledge of a person, industry, or business organization remains private after the usage of data from the database. Data modification is one of the prominent privacy-preserving techniques used to alter confidential information available in the database and guarantees high privacy protection. In this paper, a new masking technique is proposed for hiding sensitive numerical attributes that are later analyzed using clustering algorithms, namely k-means, filtered clusters, and density-based clusters. The proposed technique is used to hide confidential numerical attributes. After modification, the proposed algorithm compares the original and the modified data and ensures that all the data items are altered or not. Experimental evaluation is illustrated using the employee dataset. The accuracy is calculated based on the comparison of the original and the modified data set in terms of data items found in the number of clusters. For every clustering technique, both the original and modified at a set are divided into two, three, four, and five, clusters. Based on the performance metrics, the k-means algorithm gives the best result compared to other algorithms. The results obtained from the proposed technique are compared with the existing approach. The experimental result indicates that the newly developed method is more efficient than the existing approaches. Keywords: Data masking, Data swapping, Sensitive data, Privacy-Preserving Data Mining, Clustering, Data hiding.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2203

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1). Arun Kumar Datta, Central Power Research Institute, Bhopal, MP, India

Abstract :

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Static drives are being used invariably in all rotating machines nowadays, in spite of its several ill effects. Other than harmonics generation shaft voltages are also prime concern for bearings in the machines connected with static drives. This paper has done research on a 1500 MVA alternator being used for testing of electrical equipment. Model of this alternator and its drives are simulated with real time parameters. Built model is validated and further analysis is carried out by drawing waveforms and frequency spectrums. High levels of harmonics in power circuits and shaft voltages have been observed in the present system. A multilevel inverter (MLI) has been proposed in the drive of this machine replacing conventional current source inverter to control the harmonics and shaft voltages. Keywords: Alternator, current source inverter, common mode voltage, THD, static frequency converter, multilevel inverter.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2204

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1). F.O Aranuwa, Adekunle Ajasin University, Akungba Akoko, Ondo State, NIGERIA
2). Fawehinmi, O.B, Adekunle Ajasin University, Akungba Akoko, Ondo State, NIGERIA

Abstract :

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Iris image has been adjudicated one of the most reliable biometric traits for authentication as a result of its unique patterns, stringency to spoof attack and reliability. However, studies have revealed that inefficient classification sorts and techniques leading to classification errors and inaccurate matching has characterized its processes in many authentication and identification applications. Additionally, most of the existing works in the domain are based on single image classification, and major drawbacks of these methodologies remains insufficient learning input and classification errors. The current work uses Deep learning neural networks (DLNN), a subset of artificial intelligence that are effective in learning complex features from data, such as images. Majorly, the work is focused at classifying both left and right human iris images. Data for the work was acquired from the CASIA-Iris-lamp dataset (http://biometrics.idealtest.org). The dataset contains 16,163 iris datasets, and 20 iterations were passed on the data during modeling to determine the accuracy of the model. Performance metrics such as sensitivity, specificity and accuracy were used to evaluate the performance of the model. Experimental results show that the model performed well with classification accuracy of 99.57% which is relatively an improvement over the existing model that was used as a benchmark with 93.35%. The model correctly classified and predicted all images belonging to the right category as right irises, while it wrongly predicted 14 images belonging to the left category. Connotionally, the right iris recorded higher accuracy compared to that of the left iris. Keywords: Iris, Classification, Deep Learning, CNN, Accuracy

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2205

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1). Dr. Snehal Mistry, Vidyabharti Trust College of Business, Computer science and Research, Umrakh, Bardoli, Gujarat, India
2). Nikita Agarwal, Gujarat Technological University, Ahmedabad, Gujarat, India

Abstract :

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Aim/Purpose: - This paper identifies the antecedents and factors influencing the adoption of self-service technologies in the banking industry. Background: - Rapid technological advancement has changed the banking environment dramatically. These advancements, particularly the Internet, have transformed the way banks operate. Over the last decade, the banking industry has become highly complex and competitive and operates in a highly volatile and unpredictable global economy. With the increasing demand for electronic services, banks are utilizing SSTs to improve their products and services. Contribution: - The study provides insights into the antecedents and factors which influences the adoptions of SSTs for banking transactions. Impact on Society:- This study provides a reference to banks about the antecedents and factors which influences the customers in adoptions of SSTs for banking transactions, provide a clear insight to banks and so that banks can take positive decisions to increase the performance and productivity. Keywords: SSTs, Antecedents, Factors, Influence, Technology, Acceptance, Adoption.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2206

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1). J. A. Oladunjoye , Federal University, Wukari, Taraba State, NIGERIA
2). T. Moses, Federal University of Lafia, Lafia, Nasarawa, NIGERIA

Abstract :

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It is impossible to overstate how much the advancement of technology has impacted our culture and day-to-day activities. Technology is essential for completing tasks quickly, effectively, and efficiently. Its expansion has resulted in widespread dissemination across several disciplines. The development of biometric technology has improved record authenticity, hence enhancing the integrity and uniqueness of individual records. Every organization places a high value on key management. An efficient key management system offers key records on demand, making it simple to maintain track of the university keys and the people who signed them. The Dalhatu Araf Specialist Hospital in Lafia uses a manual approach for key collection with staff members signing up on handwritten forms. The goal of this project is to automate the manual process and include biometric thumb printing as a means to accurately monitor the whereabouts of signed keys. The study uses the structured system analysis and design methodology as a tool to structurally guide the goal of this study in order to construct the targeted system efficiently. The system being targeted is a mobile application that utilized Java with SQLite database technology. Keywords: Key Collection Management, Device Biometric, Mobile Key Collection, Signed Key Records.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2207

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1). G. F. Ntekim, Department of Civil Engineering, Enugu State University of Science and Technology, Enugu, Enugu State, NIGERIA
2). Charles Chinwuba Ike, Enugu State University of Science and Technology, Enugu State, Nigeria, Enugu State, NIGERIA

Abstract :

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This work aims at studying the compressibility properties of soil in Calabar Municipal, Cross River State, Nigeria. Also, these properties are correlated with the Atterberg Limits of the soil. The magnitude of the overall compressibility prediction of regression model depends on several variable such as the compressive index (Cc), coefficient of consolidation (Cv), coefficient of compressibility (Av), and coefficient of volume compressibility (Mv), which are determined by a consolidation test in the laboratory, by carrying out oedometer test. However, the test itself is time consuming and involves lots of calculation hence, the non-linear regression model of this research focuses on determining the relationship between the compressibility characteristics of the soil and its Atterberg Limits. The regression models developed for the ten samples using the Wolfram Application would enable for prediction of the different Compressibility Properties of the soil in Calabar Metropolis relative to its Atterberg Limits thereby reducing rigorous time-consuming activities. The regression models developed where observed to have a Coefficient of Determination (R2) value above 90% which indicated the adequacy of the model to be employed for prediction. R2 for LL, PL and PI are of values 0.955692, 0.951884 and 0.944464 respectively on Mv, the R2 for LL, PL and PI are 0.97744, 0.976234 and 0.971964 on the Cv. Also, models for Cc gave an R2 with values 0.990806, 0.99053 and 0.990396 respectively. Finally, Av on the LL, PL and PI have R2 as 0.969628, 0.965995 and 0.963419 respectively.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2208

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1). Esther Chinwe Ukeje, Nnamdi Azikiwe University, Awka, Anambra State, NIGERIA
2). Charles Chinwuba Ike, Enugu State University of Science and Technology, Enugu State, Nigeria, Enugu State, NIGERIA

Abstract :

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A consolidation (Oedometer) test can be used to measure the soil's compressibility characteristics, which indicate how much settlement will occur. The Atterberg limit test is very simple and quick in comparison to the Oedometer test, which is more expensive and time-consuming. Soil samples from various areas in Awka, Anambra State, and the surrounding area were gathered for this research. Laboratory investigations were carried out on the soil samples in order to determine the Index properties and compressibility parameters namely liquid limit (LL), plastic limit (PL), plasticity index (PI) and compression index (Cc). Based on the outcome of the experiments, non-linear empirical models were subsequently developed using simple regression analysis. This makes it possible to define the compression index as a function of the soil index (Atterberg limit) characteristics viz; LL, PL, and PI in the study area. A good agreement was found between the model’s predictions and the actual values of the compression index. The regression models were validated with a 95 percent confidence level based on the coefficient of determination (R2) values, which show a strong link between the variables.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2209

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1). Rachana Y. Patil, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India
2). Yogesh H. Patil, D. Y. Patil Institute of Technology, Pune, Maharashtra, India

Abstract :

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Cybercrime is on the rise as the digital world continues to expand. Gathering legitimate evidence is what digital forensics is all about. In a legal context, such proof is essential since it demonstrates the victim's crime beyond a reasonable doubt. It is crucial to keep evidence using a good evidence management system to ensure its admissibility in court during trials. We suggest a proxy re-encryption system that only works in one way for delegating power. The suggested approach will provide the safe delegation of access to electronic evidence. Proxy re-encryption as a means of incorporating access control into a secure evidence management solution is validated by the re-encryption scheme's enhanced sense of security. Within this study, we compare and contrast the many different systems that have been presented over the years. Future proposals for improved evidence handling could benefit from this investigation.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2210

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1). Abhishek Jain, Modern Institute of technology & Research centre (MITRC), Alwar, Rajasthan, India
2). S K Sharma, Modern Institute of technology & Research Centre (MITRC), Alwar, Rajasthan, India
3). Rajesh Bhargava, Modern Institute of technology & Research Centre (MITRC), Alwar, Rajasthan, India

Abstract :

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The word quality in the manufacturing field has been included all aspects that affect quality as a product, quality as customer satisfy, and quality as an organizational structure and performance. Hence, all activities of engineering, manufacturing and marketing are included in the term quality. In addition, quality and reliability of the product itself as well as the impact on the environment and society is part of the broad meaning of quality. Moreover, the organization structure & performance is an essential component of quality as well. Finally, Quality as an output must be continuously satisfying to the customer. The purpose of this paper is to find the importance of total quality management (TQM) Pillars implementation in Indian SMEs to improve organizational performance. The outcome of this research is to find the benefits of TQM Pillars implementations in Indian SMEs through questionnaire survey from various organizations. The authors have analyzed the collected questionnaires and identify importance of TQM Pillars in productivity improvement, organizational performance improvement, product quality improvement etc.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2211

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1). Vidhi Rajeshkumar Patel, Chandubhai S. Patel Institute of Technology, CHARUSAT- Charotar University of Science & Technology, Changa, Gujarat, India
2). Mihir Sanjaykumar Patel, Chandubhai S. Patel Institute of Technology, CHARUSAT- Charotar University of Science & Technology, Changa, Gujarat, India
3). Manish Upendrakumar Patel, Chandubhai S. Patel Institute of Technology, CHARUSAT- Charotar University of Science & Technology, Changa, Gujarat, India
4). Tejas Chandramauli Patel, Chandubhai S. Patel Institute of Technology, CHARUSAT- Charotar University of Science & Technology, Changa, Gujarat, India
5). Mihir R. Patel, Chandubhai S. Patel Institute of Technology, CHARUSAT- Charotar University of Science & Technology, Changa, Gujarat, India

Abstract :

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In the recent few years, the conscious approach towards green energy has gained significant momentum. These green sources, a noteworthy amount of power is generated through them and integrated into the grid. Hence, the need of forecasting these energy sources; especially solar energy, for the most efficient utilization is very crucial. Hence, measuring the accurate solar radiance, precise load management and efficient solar energy usage can be ensured. This research utilizes the use of ML algorithms; through which hourly, daily and monthly prediction of solar generation is possible. Concurrently, shift towards smart grid concept and solar energy by Indian power system will be benefited by use ML algorithms, that will fulfill an important aspect; load forecasting. This in turn will assure an economic operation as well as planning of the power system. In addition, sort term planning along with future expansion of generation can be pre-determined with high accuracy.

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Author (s) : DOI : 10.32692/IJDI-ERET/11.2.2022.2212

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1). M. J. Gundalia, Chhotubhai Gopalbhai Patel Institute of Technology, Uka Tarsadia University, Bardoli, Gujarat, India

Abstract :

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The Rainfall is a crucial hydro meteorological variable in arid and semi-arid region due to its yawning impact on agriculture, drinking water and energy sectors. Junagadh (Gujarat-India) region reels under rainfall uncertainties and thereby water resources and crop production suffer a lot. Rainfall is highly complex, nonlinear, and dynamic in nature and affected by many interrelated meteorological parameters. Further the temporal and spatial variability causes more uncertainty in its occurrence. Despite significant contribution of advance computing techniques, the rainfall prediction yet remains a tough challenge. Holt-Winters model is a time series model and it relies on three aspects of the time series: a typical value (average), a slope (trend) over time, and a cyclical repeating pattern (seasonality).Annual rainfall data often exhibits trend and seasonality and hence, the Holt-Winters models could be the best choice for its prediction. This study examined ability of three different types of time series models (Holt-Winters model (HW), Multiplicative Holt-Winters (MHW) and Additive Holt-Winters (AHW)) in predicting annual rainfall for Junagadh (Gujarat-India) region. Performances of the models were evaluated by using refined Willmott’s index (dr) and mean absolute error (MAE) evaluation measures. All the three models performed better and are recommended for forecasting annual rainfall of the selected region and the similar hydro-meteorological regions.

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