International Journal of Innovations in Science & Technology
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Optimal Selection of Reactive Power For Single Tuned Passive Filter Based on Curve Fitting Technique
Get PDFThis research presents the Optimal Reactive Power (Qc) selection for a single-tuned passive filter. DC drives are very popular in the industrial zone due to their high performance, flexibility, easy control, and low cost. DC drives operate by giving supply from an AC utility and AC to DC can be converted using the AC-DC converter. But this conversion introduces harmonics in the input supply current that affect the performance of the DC drive and also cause serious problems for the overall power quality of the system. Many researchers are searching for the appropriate solutions to mitigate this cause. A passive filter is one solution to minimize or avoid harmonics from entering the electrical system. The key aspect of the passive filter design has been a difficult task. The parameters of the passive filter largely depends upon selecting the suitable value of reactive power (Qc). In this paper, the Simulink model of an AC-DC converter based on a separately excited dc motor is used as an industrial load, and a curve fitting technique has been used to select the optimal value of reactive power (Qc) for the passive filter. The simulation results and analysis show that optimal selection of reactive power for single tuned passive filter using the proposed technique is very effective by taking international standards limits for harmonic distortion
What have you read? based Multi-Document Summarization
Get PDFDue to the tremendous amount of data available today, extracting essential information from such a large volume of data is quite tough. Particularly in the case of text documents, which need a significant amount of time from the user to read the material and extract useful information. The major problem is identifying the user\u27s relevant documents, removing the most significant pieces of information, determining document relevancy, excluding extraneous information, reducing details, and generating a compact, consistent report. For all these issues, we proposed a novel technique that solves the problem of extracting important information from a huge amount of text data and using previously read documents to generate summaries of new documents. Our technique is more focused on extracting topics (also known as topic signatures) from the previously read documents and then selecting the sentences that are more relevant to these topics based on update summary generation. Besides this, the concept of overlapping value is used that digs out the meaningful words and word similarities. Another thing that makes our work better is the Dice Coefficient which measures the intersection of words between document sets and helps to eliminate redundancy. The summary generated is based on more diverse and highly representative sentences with an average length. Empirically, we have observed that our proposed novel technique performed better with baseline competitors on the real-world TAC2008 dataset
Computer Malware Classification, Factors, and Detection Techniques: A Systematic Literature Review (SLR)
Get PDFA Systematic Literature Review (SLR) was conducted using tailored searches based on our study topic. We completed all SLR processes, including periodic reviews as SLR. Researchers may find out about the justification, the review procedure, and the research question by using search keywords. This paper describes the trial approach to elaborate the search keywords, resources, restrictions, and validations that were, and explores search strategies made. The reviews are carried out by assessing the publication\u27s quality, devising a data extraction approach, and synthesizing the results. All four research questions were used to analyze the papers concerning the findings. Finally, reports on the categorization of computer malware were analyzed for their detection methods, factors, and how they infiltrate computer systems have been published. SLR identifies the element, characteristics, and detection techniques that are explained in this research paper. Computer malware infects the computer system. This comprehensive literature review\u27s is mainly based on recommendations by earlier studies
Monitoring of Cortisol Levels in Hog Deer with Varying Environment Exposure
Get PDFHog deer (Axis porcinus) is one of the least studied animal species in Pakistan. It belongs to Order Artiodactyla and the family Cervidae. IUCN classified Axis porcinus as an endangered species in 2008. The present study was conducted to investigate the effects of varying environmental exposure, genders, and seasonal changes on captive hog deer (A. porcinus) at Lahore Zoo, Safari Zoo, and Jallo Park in Lahore, Pakistan. Non-invasive techniques were used to monitor stress levels in hog deer. For sample collection, four definite months belonging to two seasons’ winter and summer were considered. A total of 48 urine and faecal samples were collected from both male and female hog deer. Seasonal fluctuations have been found to have a significant impact on faecal and urinary cortisol levels. Higher cortisol levels were found in both male and female hog deer in the summer season at all three visited sites. Fluctuations in environmental exposure at three research sites had a significant impact on faecal and urinary cortisol levels. Higher levels of cortisol were found in both male and female hog deer at Jallo park and Lahore Zoo, as compared to Safari Zoo. It was concluded that lower cortisol levels at Safari Zoo might be due to better environmental conditions and more flexible enclosure size and interaction of various species of deer. Temperature affected hog deer cortisol levels in summer, as higher levels were measured in summer compared to winter. In addition, sex did not predict any stress levels in hog deer. It has been suggested that a large enclosure size can control levels of cortisol in hog deer
Emotional Intelligence, Motivation and Dysfunctional Attitude among Patients with Substance Use: Cognitive Behavior Therapy
Get PDFThe study explores the significant predictive relationship between emotional intelligence, motivation, and dysfunctional attitude among substance use patients with the role of cognitive behavior therapy. The sample was comprised of 150 addictive patients. Among 150 patients, 40 were selected for intervention. The sample was divided into two groups of 20 each in the experimental and controlled groups. Participants were selected using a purposive sampling technique from Poly Clinic Jhelum, Punjab, Pakistan. To estimate the constructs following scales were used Trait Emotional Intelligence Questionnaire-Short Form Scale, Situational Motivation Scale, Dysfunctional Attitude Scale Short Form and Drug Abuse Screening Test all in Urdu. Patients with a high level of dysfunctional attitude were selected for intervention. For each participant, 12 sessions were planned. The statistical calculations were done using Statistical Package for Social Sciences(V-26). Regression analysis confirmed that emotional intelligence and motivation is a significant predictors of dysfunctional attitudes in substance used patients [R²=.066; F (2, 147) = 5.198, p<.01] with 6.6% explained variation in the dysfunctional attitude due to emotional intelligence and motivation. The effectiveness of cognitive behavior therapy was also evident with the experimental groups mean score of emotional intelligence (M=78.6, M = 169.00), motivation (M=58.1, M = 92.10) and dysfunctional attitude (M=61.1, M = 26.00) pre and posttest scores. It indicates that Cognitive Behavior Therapy was effective in the treatment of drug addicts to deal with lower levels of motivation and emotional intelligence as well as higher dysfunctional attitudes.
For emotional intelligence, results showed that there is change in mean score of experimental groups (M=78.6, M = 169.00) For motivation, results showed that there is change in mean score of experimental groups (M=58.1, M = 92.10). For dysfunctional attitude, results showed that there is change in mean score of experimental groups (M=61.1, M = 26.00) which indicate that Cognitive Behavior Therapy was effective in treatment of drug addicts to deal with lower levels of motivation and emotional intelligence as well as higher dysfunctional attitude
Analysis of Code Vulnerabilities in Repositories of GitHub and Rosettacode: A comparative Study
Get PDFOpen-source code hosted online at programming portals is present in 99% of commercial software and is common practice among developers for rapid prototyping and cost-effective development. However, research reports the presence of vulnerabilities, which result in catastrophic security compromise, and the individual, organization, and even national secrecy are all victims of this circumstance. One of the frustrating aspects of vulnerabilities is that vulnerabilities manifest themselves in hidden ways that software developers are unaware of. One of the most critical tasks in ensuring software security is vulnerability detection, which jeopardizes core security concepts like integrity, authenticity, and availability. This study aims to explore security-related vulnerabilities in programming languages such as C, C++, and Java and present the disparities between them hosted at popular code repositories. To attain this purpose, 708 programs were examined by severity-based guidelines. A total of 1371 vulnerable codes were identified, of which 327 in C, 51 in C++, and 993 in Java. Statistical analysis also indicated a substantial difference between them, as there is ample evidence that the Kruskal-Wallis H-test p-value (.000) is below the 0.05 significance level. The Mann-Whitney Test mean rank for GitHub (Mean-rank=676.05) and Rosettacode (Mean-rank=608.64) are also different. The novelty of this article is to identify security vulnerabilities and grasp the nature severity of vulnerability in popular code repositories. This study eventually manifests a guideline for choosing a secure programming language as a successful testing technique that targets vulnerabilities more liable to breaching security.
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Design and Implementation of Autonomous Trolley with E Billing
Get PDFShopping became one of the most important tasks that people conduct on a daily basis. A mart is a place where various things can be purchased within a roof. Customers must patiently wait in lengthy lines, especially on weekends, until it is their turn. Due to people\u27s busy schedules, this is a time-consuming process that leaves them exhausted and dissatisfied with the services provided at the checkout counters. We proposed and implemented an autonomous trolley with an electronic billing system. The proposed and developed system is separated into two sections, the first section consists of RFID tags and camera-based product scanning and detection, while the second section consists of bill generation and e-payment. The second output is of a shopping receipt, which was printed using a thermal printer effectively, and smart trolley-based bill detection will be accomplished. This self-billing is a new technology that can present us with numerous advantages. Currently, everyone is familiar with e-payments, and because our system is also based on direct bank transactions. This smart trolley-based bill detection will ultimately be accomplished through the user\u27s bank and Jazz Cash. Automated trolley systems are designed to provide customers with knowledge about their collected items and decision-making abilities based on prior purchase patterns in order to ensure a hassle-free shopping experience.
Knowledge Acquisition System for Sentiment Analysis
Get PDFSentiment analysis is considered an advanced technology to predict and analyze people’s opinions, attitudes, sentiments, and perceptions towards some topics, products, and services. Due to the fast evolution of Internet-based applications, opinion mining becomes a very substantial method nowadays. For this purpose, many systems have been developed so far; some use the statistical method whereas some use parsers to analyze the data. However, this article presents a complete study and uses a hybrid approach toanalyze volumetric data in the form of sentences. The hybrid approach of sentiment analysis uses both deep learning (statistical methods) and knowledge-based methods. Furthermore, this article also uses a sentence structure approach that helps to overcomethe linguistic effects in the knowledge base. In addition, this article also suggests some future directions using the sentence structure of natural language for an expert system
Interpretation of Expressions through Hand Signs Using Deep Learning Techniques
Get PDFIt is a challenging task to interpret sign language automatically, as it comprises high-level vision features to accurately understand and interpret the meaning of the signer or vice versa. In the current study, we automatically distinguish hand signs and classify seven basic gestures representing symbolic emotions or expressions like happy, sad, neutral, disgust, scared, anger, and surprise. Convolutional Neural Network is a famous method for classifications using vision-based deep learning; here in the current study, proposed transfer learning using a well-known architecture of VGG16 to speed up the convergence and improve accuracy by using pre-trained weights. We obtained a high accuracy of 99.98% of the proposed architecture with a minimal and low-quality data set of 455 images collected by 65 individuals for seven hand gesture classes. Further, compared the performance of VGG16 architecture with two different optimizers, SGD, and Adam, along with some more architectures of AlexNet, LeNet05, and ResNet50.
Role of Microbes in Modern Food Industry
Get PDFMicroorganisms are an important part of the food industry as these are helpful in food preservation and production. Usually, microorganisms are used in making dairy products (yogurt and cheese), fermented vegetables (olives, pickles, and sauerkraut), fermented meats (salami), and sourdough bread. These are also utilized for the production of wine and several other beverages. Recently in the food industry, the use of microorganisms has started on a large scale for the production of chocolate, food color, from preserving fruits, vegetables and meat, and as probiotics which are helpful for human health. Different types of the microorganisms produce enzymes of nutritional value such as microbial transglutaminase for fish production. As the human population is increasing, we need to adopt new techniques for producing qualitative and nutritious food. These microorganisms can be used to cope with the shortage of food supply. This review will brief the role of microorganisms in above mentioned products as a leading step towards the modern food industry.
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