Modeling and analysis: power injection model approach for high performance of electrical distribution networks

The generation of electrical energy varies depending on the needs of the user, initial requirements, capacity, intended use, waste generation, and economic efficiency. In order to meet the challenges of the proposed overvoltage of the presented system, it is possible to use the solar collectors and profit from them economically through smart grid smart control systems. The mathematical model with four main parts was created: simulation, correlation, and evaluation according to the solar program set of photovoltaic solar modules, maximum power point tracking (MPPT), an adaptive neuro-fuzzy inference system (ANFIS) controller, and 600-volt electric network. Then in this phase, the investigation of the effects on the network on the basis of the output power with the coincidence of radiation and the effect of temperature in the network is carried out. An analysis was carried out to evaluate the impact of these fundamental limitations in practical application. In this section, the simulation of the proposed system is discussed. The block diagram of the developed system is presented in the last part. The proposed system was assessed from the Matlab simulation tapes and graphs for each part of the system, and the results of the overall system simulation were taken into account.

K-nearest neighbor and naïve Bayes based diagnostic analytic of harmonic source identification

This paper proposes a comparison of machine learning (ML) algorithm known as the k-nearest neighbor (KNN) and naïve Bayes (NB) in identifying and diagnosing the harmonic sources in the power system. A single-point measurement is applied in this proposed method, and using the S-transform the measurement signals are analyzed and extracted into voltage and current parameters. The voltage and current features that estimated from time-frequency representation (TFR) of S-transform analysis are used as the input for MLs. Four significant cases of harmonic source location are considered, whereas harmonic voltage (HV) and harmonic current (HC) source type-load are used in the diagnosing process. To identify the best ML, the performance measurement of the proposed method including the accuracy, precision, specificity, sensitivity, and F-measure are calculated. The sufficiency of the proposed methodology is tested and verified on IEEE 4-bust test feeder and each ML algorithm is executed for 10 times due to prevent any overfitting result.

Quality of service performances of video and voice transmission in universal mobile telecommunications system network based on OPNET

The universal mobile telecommunications system (UMTS) has distinct benefits in that it supports a wide range of quality of service (QoS) criteria that users require in order to fulfill their requirements. The transmission of video and audio in real-time applications places a high demand on the cellular network, therefore QoS is a major problem in these applications. The ability to provide QoS in the UMTS backbone network necessitates an active QoS mechanism in order to maintain the necessary level of convenience on UMTS networks. For UMTS networks, investigation models for end-to-end QoS, total transmitted and received data, packet loss, and throughput providing techniques are run and assessed and the simulation results are examined. According to the results, appropriate QoS adaption allows for specific voice and video transmission. Finally, by analyzing existing QoS parameters, the QoS performance of 4G/UMTS networks may be improved.

Frequency based edge-texture feature using Otsu’s based enhanced local ternary pattern technique for digital image splicing detection

Sharing information through images is a trend nowadays. Advancements in the technology and user-friendly image editing tool make easy to edit the image and spread fake news through different social networking platforms. Forged image has been generated through an advanced image editing tool, so it is very challenging for image forensics to detect the micro discrepancy which distorted the micro pattern. This paper proposes an image forensic detection technique, which implies multi-level discrete wavelet transform to implement digital image filtering. Canny edge detection technique is implemented to detect the edge of the image to implement Otsu’s based enhanced local ternary pattern (OELTP), which can detect forgery-related artifact. DWT is implemented over Cb and Cr components of the image and using edge texture to improve the Otsu global threshold, which is used to extract features using ELTP technique. Support vector machine (SVM) is used for classification to find the image is forged or not. The performance of the work evaluated on three different open available data sets CASIA v1, CASIA v2, and Columbia. Our proposed work gives better results with some of the previous states of the work in terms of detection accuracy.

Supervised machine learning based liver disease prediction approach with LASSO feature selection

In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of this deadly disease. By diagnosing the disease in a primary stage, early treatment can be helpful to cure the patient. In this research paper, a method is proposed to diagnose the LD using supervised machine learning classification algorithms, namely logistic regression, decision tree, random forest, AdaBoost, KNN, linear discriminant analysis, gradient boosting and support vector machine (SVM). We also deployed a least absolute shrinkage and selection operator (LASSO) feature selection technique on our taken dataset to suggest the most highly correlated attributes of LD. The predictions with 10 fold cross-validation (CV) made by the algorithms are tested in terms of accuracy, sensitivity, precision and f1-score values to forecast the disease. It is observed that the decision tree algorithm has the best performance score where accuracy, precision, sensitivity and f1-score values are 94.295%, 92%, 99% and 96% respectively with the inclusion of LASSO. Furthermore, a comparison with recent studies is shown to prove the significance of the proposed system.

Comparative review on information and communication technology issues in education sector of developed and developing countries: a case study about Pakistan

The use of information and communication technology is very beneficial in the education sector because it can enhance the quality of education. However, the implementation of ICT in the education sector of developed and developing countries is a challenging task. This paper explains the comparative study of ICT issues in the education sector of developed and developing countries. In particular, we compare issues between Pakistan and high-tech countries. Our study reveals the fact that the education sector is facing numerous ICT problems that are based on culture, finance, management, infrastructure, lack of training, lack of equipment, teacher’s refusal, and ethical issues. At the end of this paper, various issues faced by the implementation of ICT in the education sector of Pakistan have been categorized into various types, namely, infrastructure, lack of IT professionals, lack of high-speed internet and equipment. Our research is based on five key research questions related to ICT issues. We used a mixed approach where the results of this study can be used as a set of guidelines to help make the learning environment technology-oriented, fast, planned, and productive. Future directions are also given at the end of this paper.

Successful factors determining the significant relationship between e-governance system and government operational excellence

Every government's major objective is to provide the greatest services in order to establish efficiency and quality of performance. Syria's government has understood how critical it is to go in the direction of information technology. However, there are gaps and poor links across government sectors, which has tainted the image of Syrian e-governance. As a result, one of the main aims of this study is to figure out what factors impact Syrians' acceptance of the e-government system. A total of 600 questionnaires were delivered to Syrian individuals as part of a survey. The data was analysed using the structural equation model (SEM) using AMOS version 21.0. User intention to utilise an e-government system was shown to be influenced by performance expectations, effort expectations, system flexibility, citizens-centricity, and facilitating conditions. Assurance, responsiveness, reliability, tangibles, and empathy are five fundamental factors that have a major impact on government operation excellence. Behavioural Intention is being utilised as a mediator between the government operation excellence (GOE) initiative and the e-government platform.

Using particle swarm optimization to solve test functions problems

In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.

Effect of repeated electrical breakdowns on mineral and natural ester insulating oils

Transformer insulating oils are exposed to repeated electrical discharge or breakdowns inside power transformers. Durability tests are conducted to analyze the ability of oil to resist decomposition due to such high electrical stresses. With the increasing demand for alternative insulating oils for oil-immersed transformers, it is worthy to compare the performance of different types of insulating oils (conventional mineral-based insulating oil and natural ester-based insulating oil) under repeated electrical breakdown. In this paper, the AC breakdown voltage of different mineral-based and natural ester-based insulating oils is reported. Durability tests were conducted based on the AC breakdown voltage behavior of insulating oils after 50 electrical breakdown shots. The AC breakdown voltage of each insulating oil sample was assessed according to the ASTM D1816 standard test method. Based on the results, it can be concluded that the dissimilarity in chemical composition of the insulating oils has a significant effect on the AC breakdown voltage behavior of these oils under repeated electrical breakdowns.

Prototype mobile contactless transaction system in traditional markets to support the covid-19 physical distancing program

One way to prevent and reduce the spread of the covid-19 pandemic is through physical distancing program. This research aims to develop a prototype contactless transaction system using digital payment mechanisms and QR code technology that will be applied in traditional markets. The method used in the development of electronic market systems is a prototype approach. The application of QR code and digital payments are used as a solution to minimize money exchange contacts that are common in traditional markets. The results showed that the system built was able to accelerate and facilitate the buying and selling transaction process in traditional market environment. Alpha testing shows that all functional systems are running well. Meanwhile, beta testing shows that the user can very well accept the system that was built. The results of the study also show acceptance of the usefulness of the system being built, as well as the optimism of its users to be able to take advantage of this system both technologically and functionally, so its can be a part of the digital transformation of the traditional market to the electronic market and has become one of the solutions in reducing the spread of the current covid-19 pandemic.