VFAST - Virtual Foundation for Advancement of Science and Technology (Pakistan)
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An Efficient approach for Firearms Detection using Machine Learning
Get PDFEach year, there is a significant number of people impacted by gun-related violence globally. To address this issue, we have created a computer-based system that can automatically identify firearms, specifically pistol. Recent advancements in machine learning has shown success in the fields of recognition and object detection. Our system utilizes the You Only Look Once (YOLO V3) object detection model, which was trained on a personalized dataset. Our training results indicate that YOLO V3 outperforms both traditional convolutional neural network (CNN) models and YOLO V2. Notably, our approach did not require high computation resources or intensive GPUs to train our model. By incorporating this YOLO V3 model into our security system, we hope to rescue lives and decrease the occurrence of manslaughter or mass killings. Moreover, detecting weapons or other dangerous materials and preventing harm or risk to human life could be accomplished by integrating this system into sophisticated surveillance and security robots
Deep Emotions Recognition from Facial Expressions using Deep Learning
Get PDFDeep emotion recognition has a wide range of applications, including human-robot communication, business, movies, services hotels, and even politics. Despite the use of various supervised and unsupervised methods in many different fields, there is still a lack of accurate analysis. Therefore, we have taken on this challenge as our research problem. We have proposed a mechanism for efficient and fine-grained classification of human deep emotions that can be applied to many other problems in daily life. This study aims to explore the best-suited algorithm along with optimal parameters to provide a solution for an efficient emotion detection machine learning system. In this study, we aimed to recognize emotions from facial expressions using deep learning techniques and the JAFFE dataset. The performance of three different models, a CNN (Convolutional Neural Network), an ANN (Artificial Neural Network), and an SVM (Support Vector Machine) were evaluated using precision, recall, F1-score, and accuracy as the evaluation metrics. The results of the experiments show that all three models performed well in recognizing emotions from facial expressions. The CNN model achieved a precision of 0.653, recall of 0.561, F1-score of 0.567, and accuracy of 0.62. The ANN model achieved a precision of 0.623, recall of 0.542, F1-score of 0.542, and accuracy of 0.59. The SVM model achieved a precision of 0.643, recall of 0.559, F1-score of 0.545, and accuracy of 0.6. Overall, the results of the study indicate that deep learning techniques can be effectively used for recognizing emotions from facial expressions using the JAFFE dataset
An empirical study of performance of block cipher algorithms in cloud computing environment
Get PDFThe security of private and sensitive data stored in the public domain is a major problem. It is critical for the user that data be safe both in transit and even after it has been stored on the server. The data owner must be guaranteed that the data held on the service provider site is safeguarded against data theft from outsiders, and the data must be protected even from the service providers. The secret key generation is one of the most important factors for the security of any cryptographic system because the length of the key directly affects the performance and prevents various cryptographic attacks such as brute force attacks. At the application level, our developed system efficiently secures sensitive, private, and personally identifiable information by ensuring privacy and confidentiality of data at rest in the public domain. This study also compares the performance of block cipher algorithms DES, 3DES, Blowfish, and AES. It was deduced from the result that AES consumes less time when compared to other symmetric algorithms with small consistent behavior for various cryptographic operations with small, medium and big datasets.
LeafNet: Using Convolutional Neural Network for Plant Leaf Detection
Get PDFPakistan is home to thousands of plant species. As a result of pollution, natural disasters, and climate change, many of these species are at risk of extinction. Plant categorization and detection systems are designed to assist non-experts in automatically identifying plants based on their leaves to ensure their safety. The current study proposes a plant leaf detection system utilizing a Convolutional Neural Network architecture. Making use of the PlantVillage dataset, the proposed system can identify seven species of plants namely apple, cherry, tomato, potato, soybean, strawberry, and corn. Data augmentation strategies have been used to provide more training examples to get around the problem of bias and imbalanced data. The accuracy achieved on the training set was 98.87% which improved to 99.5% when using data augmentation. Apart from the monitoring of endangered species, the adoption of the proposed model can also aid the evaluation of weed management efforts and analysis of species distribution under climate change
A Novel Method for Ranking a Website Rating via Search Engine Optimization
Get PDFEveryone uses the internet and a search engine (SE) to find what they need, making SE indispensable. Search engines are used to find any sort of information, which is why most companies want to rank well in SE result pages in order to reach their ideal clients. Without a website, companies nowadays have little chance of competing in the industry. As a consequence, the companies have prioritized and funded efforts to improve their website SE rankings. There are a plethora of methods that may be used to optimize a website for search engines. These methods come under a heading, namely, search engine optimization (SEO) by webmasters. In this research, we propose a methodology that combines on-page and off-page SEO strategies to improve user search and website ranking over SE. The proposed method outperforms in terms of website ranking, whereby a website ranking is improved from fifth to second position on Google SE. This significant shift illustrates that on and off page SEO can work together to boost a website visibility over SE result page
Enhancing Energy Efficiency and Coverage in HetNets through Antenna Optimization
Get PDFThe advent of 5G technology has opened up new opportunities across various fields, including healthcare. In the context of wireless communication, the deployment of a two-tier heterogeneous network (HetNet) plays a crucial role in ensuring robust connections among devices, users, and healthcare infrastructure. This study focuses on optimizing coverage and energy efficiency (EE) in HetNets, tailored for specific application domains. We begin by examining how antenna height impacts coverage within macro and pico cells. Precise antenna placement is critical, as it significantly alters coverage patterns, particularly in healthcare settings, which can range from large hospital complexes to remote telemedicine locations. Additionally, we investigate the strategic adjustment of antenna gain in macro and pico cells, showing how this optimization enhances coverage and minimizes interference. Achieving this balance is essential for the reliable transmission of data. Our research also considers the interplay of antenna height, EE, and the maximum number of users (). Surprisingly, we find that has a limited impact on coverage and EE compared to antenna configuration. This emphasizes the crucial role of antenna design and placement in crafting efficient wireless networks.Our study provides insights into improving coverage and EE in HetNets, with implications for various applications. It underscores the importance of strategic antenna optimization in shaping efficient and resilient communication systems. Furthermore, we explore the impact of on EE and leverage idle mode capabilities for further EE enhancements
An Applied Study Regarding the Rules, Precautions and Remedies of Corona Pandemic in the Context of sayings of the Prophet (PBUH) about Plague
Get PDFThe Corona virus (Covid-19) pandemic began in December 2019 in Wuhan, China, and has spread rapidly throughout the world. So far millions of people have died all over the world while millions of people have been suffering from this disease. It is also an infectious disease like plague. In the world many Outbreaks have taken place that have taken many lives. There are many hadiths about the plague, and Covid-19 is also a kind of plague. The cure for Corona virus has not yet been discovered, but some of the protective measures suggested by “WHO”. These were devised by Islam about fourteen hundred years ago, because all of Islam\u27s teachings guarantee the survival of human beings. Infectious disease is believed to be effective, but its effect is not definitive. According to the Prophetﷺ , honey and clone are the remedies for every disease. Each of the world\u27s troubles is the result of certain actions of the past, so it is possible to get rid of this type of trouble by appealing to our Lord through repentance and prayers. The aim of this research paper is to present an applied study regarding the Rules, Precautions and Remedies of Corona Pandemic in the Context of Hadiths about Plague
Dynamic Relationship between Environmental Degradation and Institutions in Pakistan
Get PDFThe paper’s attempt is to fill up the gap in the energy literature with a complete nation revise for Pakistan. We examine the affiliation between CO2, institution quality (IQ), GDP, energy expenditure (EU) and trade openness (TO) for Pakistan over the period of 1984-2014. ARDL model is used for co-integration, CUSUM test for analysis. The consequence shows that there is a long run affiliation with the variables. In addition, we find in one direction fundamental affiliation successively from GDP to CO2 emissions.
Solid Waste Management and Willingness to Pay: An Analysis of Integrated Approach of Garbage Disposal in Multan Pakistan
Get PDFIntroduction: Rapid population growth in developing countries has accelerated urbanization, resulting in a slew of environmental issues. One such problem is the rapid rise in the quantities of solid waste. Pakistan\u27s way of life, like the way of life in many other countries around the world, has changed. As a result of the utilisation arranged populace and ongoing utilisation driven development, squander age has increased dramatically in Pakistan. Removals are being used in an increasing number of food and non-food items. In Pakistan, solid waste management generally consists of flexible, elastic, metals, discarded food, discarded animals, glass, building material, and channel-removed material. Families, businesses, and projects all generate a lot of waste. Heavy waste is frequently generated by medical care facilities and hospitals. Objectives: The investigation of the sources and nature of solid waste generated in urban areas, analysis of current SWM practices, and examination of the socioeconomic, environmental, and health effects of solid waste management were the main goals of the study. Methodology: In this study, a quantitative research design has been chosen. The study\u27s target population consisted of the households in a few Multan city colonies. From 385 respondent information was gathered from 4 colonies. Fitz Gibbon Table for determining the sample size was used. The study employs a stratified random sampling methodology. to evaluate the connection between paying and solid waste management. Questionnaires were used as the data collection tool. SPSS was used to analyze the data. Conclusion: The study\u27s findings indicated that knowledge and home ownership have an impact on willingness to pay. Factors such as income, home ownership, and knowledge of solid waste management have a greater impact on willingness to pay. It was determined that there are some factors that influence a man\u27s willingness to pay for garbage disposal
Quality Standards of Qualitative Research in Applied Linguistics: A Conceptual Review
Get PDFThis study inspects different dimensions of ensuring standards in qualitative research within the field of applied linguistics. It presents a conceptual review of already established key quality standards of qualitative research, their application, their significance followed by the recommendations to ensure quality standards in applied linguistics qualitative research. For this purpose, the researchers have considered journal articles, book chapters and books published between 2002 and 2023 on digital databases to examine the key standards of ensuring trustworthiness and their application in the field of applied linguistics qualitative research. The study presents recommendations for novice researchers who are attempting to conduct qualitative studies ensuring the maximum level of trustworthiness and credibility and making their studies sound in terms of quality standards