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Transforming Libyan Organizations through AI: Assessing Readiness and Strategic Pathways

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Transforming Libyan Organizations through AI: Assessing Readiness and Strategic Pathways/strong>
Authors:-Ali Bakeer

Abstract-In the context of Libya’s ongoing digital transformation efforts, many sectors are still grappling with the early stages of deploying advanced technologies, particularly artificial intelligence (AI) tools. This study aims to addresses the pressing issue of AI readiness among Libyan organizations, focusing on the critical success factors that facilitate or hinder the Deployment of AI technologies. The study employs a case study methodology, collecting qualitative data through structured surveys from eighteen participants across various sectors, including education, healthcare, and finance. The findings reveal critical barriers to AI deployment, such as inadequate digital infrastructure, limited internet access, insufficient government support, and a shortage of skilled professionals. In response, a structured framework is developed, outlining essential steps for organizations to successfully integrate AI applications. This framework emphasizes the need for assessing organizational readiness, setting strategic objectives, selecting appropriate AI solutions, conducting pilot projects, implementing training programs, and fostering a culture of continuous improvement. Ultimately, this research aims to bridge the gap between the theoretical benefits of AI and the practical realities faced by Libyan organizations, providing a pathway toward a future where AI drives productivity, innovation, and informed decision-making. The insights derived from this study underscore the importance of collaboration between public and private sectors to ensure sustainable and effective AI Deployment in Libya.

DOI: 10.61137/ijsret.vol.10.issue5.274

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Agri Shield: Identify Plant Disease Using Machine Learning

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Agri Shield: Identify Plant Disease Using Machine Learning/strong>
Authors:-Aditya Bathre, Aajinkya Ingalkar, Awanish Srivastava, Anurag Patel

Abstract-This paper introduces Agri Shield, an innovative approach using machine learning, particularly convolutional neural networks, for predicting plant diseases and recommending sustainable individualized remedies. Agri Shield embodies early-stage disease detection with ecologically friendly solutions, making it easier for farmers and plant enthusiasts to care for plants, as such information would be sourced from a multiplicity of sources. The proposed system is able to detect 20 different diseases of 5 common plants with 93% accuracy.

DOI: 10.61137/ijsret.vol.10.issue5.273

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Magic Hexagon of Order-4 with Star Configuration: A Study on Symmetry and Combinatorial Patterns

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Magic Hexagon of Order-4 with Star Configuration: A Study on Symmetry and Combinatorial Patterns/strong>
Authors:-Himadri Maity

Abstract-This paper presents a new magic hexagon of Order-4 with 24 cells, which exhibits a unique star configuration inside the hexagon. The hexagon follows distinct combinatorial patterns where all combinations of selected numbers result in equal sums. A total of 52 combinations are identified with a constant sum of 190, making this work significant in the study of mathematical patterns and symmetry.

DOI: 10.61137/ijsret.vol.10.issue5.272

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Assessing HRIS Effectiveness in Compliance Management among IT Employees within Trichy District

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Assessing HRIS Effectiveness in Compliance Management among IT Employees within Trichy District/strong>
Authors:-Mrs. A.Keerthana Devi

Abstract-The Information Technology (IT) sector necessitates strict compliance measures to maintain operational integrity and data security because of the quickly changing regulatory environment. This research aims to assess how well Trichy’s IT organizations manage compliance using Human Resource Information System (HRIS) solutions. The research, which involved 2347 individuals in a variety of jobs across several IT businesses, used a thorough questionnaire to explore how employees perceive HRIS performance in negotiating intricate compliance concerns unique to the IT industry. Employee familiarity with compliance rules, data security, privacy features, audit trail maintenance, efficiency of documentation, and adequate user support are among the factors that are being examined. Regression modelling, multivariate analysis, and statistical validation approaches are used in this work to find connections and underlying patterns that affect compliance efficiency. The results of research highlight how important it is for users to be conversant with regulations, since they show a favourable link with improved compliance procedures. Data security plays a critical role in IT firms and is identified as a fundamental factor effecting compliance efficiency. In Trichy’s IT industry, accessibility and the efficacy of HRIS characteristics emerge as critical factors in maximizing compliance procedures. The study’s conclusions provide specific advice on how to improve HRIS capabilities so that they smoothly mesh with the complex compliance requirements that are common in Trichy’s IT environment. Consequences and significance, this study adds to a better knowledge of how HRIS systems can be tailored to successfully navigate and manage compliance in the always changing regulatory landscape of the IT sector. The consequences encompass methods for technology adoption within organizations, guaranteeing strong compliance management procedures that are essential for maintaining the security and integrity of IT operations within Trichy’s IT industry.

DOI: 10.61137/ijsret.vol.10.issue5.271

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Fundamental of Tissue Culture and it’s Future Prospects in Crop Improvement

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Fundamental of Tissue Culture and it’s Future Prospects in Crop Improvement/strong>
Authors:-Anjali, Kopal Singh, Dr. Gurshaminder Singh

Abstract-The science of growing plant cells, tissues, or organs separated from the mother plant on artificial media is known as plant tissue culture. It has various useful goals and comprises research methodologies and approaches from numerous botanical disciplines. It is essential to acquire a thorough understanding of the processes involved in growing and working with plant material in “test tubes” before starting to propagate plants using tissue culture techniques.In a relatively short period of time, during the height of the plant tissue culture era in the 1980s, numerous commercial laboratories were set up worldwide to take use of the potential of micropropagation for the large-scale production of clonal plants for the horticultural sector.The most widely used biotechnological techniques are those based on plant tissue culture. These include investigations into the processes involved in plant development, functional gene studies, the creation of transgenic plants with particular industrial and agronomical traits, healthy plant material, the preservation and conservation of the germplasm of vegetative propagated plant crops.Plant tissue culture has to lead to significant contributions in recent times and today they constitute an indispensable tool in the advancement of agricultural sciences and modern agriculture. This review would enable us to have an analysis of plant tissue culture development for agriculture, human health and well being in general.

DOI: 10.61137/ijsret.vol.10.issue5.270

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Analysis of Methods of Fabricating Perovskite Photovoltaic Cells

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Analysis of Methods of Fabricating Perovskite Photovoltaic Cells/strong>
Authors:-Barakur Calvin Azo, Al Moustafa Saad

Abstract-Perovskite solar cells (PSCs) are a promising photovoltaic technology utilizing organometal halides for high-efficiency, low-cost solar energy conversion. They have the potential to revolutionize renewable energy as a result of their outstanding photovoltaic performance and a surge in their efficiency advancements. with unprecedented progress on certified power conversion efficiency (PCE) from 3.8% to over 25% within a decade. However, large-scale, cost-effective fabrication remains a hurdle for commercialization The Objective of the research is to investigate various Perovskite Solar Cells (PSC) fabrication methods with the goal of identifying scalable and efficient fabrication methods for commercially viable PSCs.

DOI: 10.61137/ijsret.vol.10.issue5.269

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Use of Aeroponics Technique for Potato (Solanum Tuberosum) Mini Tubers Production in India: A Review

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Use of Aeroponics Technique for Potato (Solanum Tuberosum) Mini Tubers Production in India: A Review/strong>
Authors:-Tamanna Sharma, Dr.Shilpa Kaushal, Shubham

Abstract-Potato, also known as Solanum tuberosum L., ranks as the third most vital food crop worldwide and is essential for food security, especially in developing countries. Potatoes grow from tubers instead of seeds like cereals, making them susceptible to seed-borne diseases that lower seed quality and decrease yields in the long run. India, a leading potato-producing nation, is facing a major challenge due to a significant lack of high-quality seed tubers, as only 20-25% of the required amount is being met by state and central agencies. Identified as promising solutions to address this problem are advanced methods of multiplication such as micropropagation, hydroponics, and aeroponics. These technologies make the production of disease-free Mini tubers faster and more efficient. Aeroponics, a method of growing plants without soil using mist, has demonstrated significant potential for producing seed potatoes on a large scale. Derived from research conducted in the early 1900s, aeroponics has advanced to increase crop yields, reduce disease risks, and improve production efficiency. Small tubers created using this method, varying from 5 to 25 mm in size, are grown in controlled settings such as greenhouses and growth chambers. Aeroponics provides several benefits, including enhanced water usage, quicker growth, increased harvest, and decreased reliance on pesticides and herbicides. Nevertheless, it also poses difficulties such as expensive initial costs, the requirement for specific expertise, and accurate management of nutrients. By making advances in temperature, nutrition, and light management, aeroponics presents a hopeful remedy for the lack of seed potatoes and a means to enhance worldwide potato yield.

DOI: 10.61137/ijsret.vol.10.issue5.268

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Optimal Energy Management System Control of Permanent Magnet Direct Drive Linear Generator for Grid-Connected FC-Battery-Wave Energy Conversion

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Optimal Energy Management System Control of Permanent Magnet Direct Drive Linear Generator for Grid-Connected FC-Battery-Wave Energy Conversion/strong>
Authors:-Professor Adel Elgammal, Assistant Professor Curtis Boodoo

Abstract-The Wave Energy Conversion System (WECS) control strategy is presented in this study to make sure the system operates at its best under fluctuating wave resource situations. The suggested system consists of a MOPSO based MPC approach, a point absorber WEC oscillating in heave, back-to-back power converter for grid connections, and a linear permanent magnet generator. Despite the benefits of model predictive control, problems including switching frequency variations, steady-state errors, high processing costs, and constrained prediction horizons continue to exist. The article presents a method that incorporates the switching control action into the cost function while maintaining the finite nature of a model predictive control to handle the switching frequency issue. In order to minimise switching frequency variations while also addressing other control goals, such as regulating the direct current linked voltage and controlling the flow of active and reactive power, the switching control weight factors are optimised. In order to increase power quality, a fuel.

DOI: 10.61137/ijsret.vol.10.issue5.267

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Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning

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Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning/strong>
Authors:-Sukhwinder Sharma, P Hrithika kundar, Saksha K Bangera, Sandesh R Bhat, Shrinit R Poojary

Abstract-The rising number of accidents and injuries on the roads has created a pressing need for systems that can provide safety and protection to passengers while ensuring high performance in adverse conditions. Traditional braking systems may not always respond in time to prevent collisions, particularly in adverse conditions or emergencies. These systems rely on the driver to apply the brakes manually, which can result in delayed response times or even complete failure to apply the brakes in time. Additionally, these systems do not take into account factors such as road conditions, vehicle speed, and driver reaction time. To overcome these limitations and meet the needs, the Autonomous Braking System has been introduced in commercial vehicles, providing rapid brake response according to the driver’s need and safety. This system employs an intelligent control strategy that uses image processing technology based on object detection with the help of haarcascading object detection technique. Computer vision, a crucial component of this system, allows for the detection of path which is being followed by vehicle using Canny’s lane detection technique, obstacles and objects in the vehicle’s path. This information is then used to make decisions about when and how to apply the brakes, ensuring quick and safe stops. Reinforcement learning is also a key element of the system, allowing it to learn from its experiences and make better decisions over time. This involves providing feedback on the system’s performance and using it to adjust its behavior and improve its performance over a period of time. The haarcascading technique here recognizes captured objects as potential obstacles, feeding this information into the algorithm to take appropriate decisions. Overall, the Intelligent Braking System promises to significantly improve safety and performance in commercial vehicles.

DOI: 10.61137/ijsret.vol.10.issue5.266

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Comparative Analysis on Social Media Sites Using Sentiment Analysis

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Comparative Analysis on Social Media Sites Using Sentiment Analysis/strong>
Authors:-Indhuja.G, Abinaya.K, Deekshitha.M, D. Suganthi, J Mythili, Dr. J. Viji Gripsy

Abstract-This paper evaluates user views and emotional tone in postings across many social media sites by means of a comparative analysis utilising sentiment analysis. Understanding the mood underlying user-generated material has become vital for companies, marketers, and academics as social media is playing more and more influence on public debate. Focussing on sites like Twitter, Facebook, and Instagram, the paper uses sentiment analysis methods on social media data. The performance of these models in terms of accuracy, precision, recall, and F1 score is compared using machine learning models including Support Vector Machines (SVM), Light GBM (LGBM), and Long Short-Term Memory (LSTM). The results expose how sentiment patterns vary on different platforms, therefore offering understanding of public opinion dynamics, brand perception, and content engagement. Following LGBM in precisely identifying sentiment, the study emphasises SVM and LSTM’s efficiency and analyses the ramifications of these results for content development, market research, and social media monitoring.

DOI: 10.61137/ijsret.vol.10.issue5.500
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