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Daily Archives: October 15, 2024

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

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

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

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

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

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

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
55

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Forensic Analysis Model for Investigating Cybercrime Over the Network

Forensic Analysis Model for Investigating Cybercrime Over the Network/strong>
Authors:-Midhunya.P.S, Adhulya. D, Merlin Jenifer. L, D. Suganthi, J. Mythili, Dr. N. Prabhu

Abstract-Despite significant investments in security protocols, the frequency of cybersecurity incidents continues to rise, with traditional methods proving ineffective against complex cyber-attacks. This research aims to address this issue by using a publicly accessible dataset on Advanced Persistent Threats (APTs) to develop a data-driven approach for identifying APT phases within the Cyber Kill Chain framework. APTs are sophisticated and targeted attack strategies that can bypass conventional intrusion detection systems, posing a major challenge for security professionals. The study incorporates several machine learning classifiers, including Naïve Bayes, Bayes Net, KNN, Random Forest, and Support Vector Machine (SVM), to analyze the dataset and identify APT phases, offering a promising method for improving cybersecurity detection and response.

DOI: 10.61137/ijsret.vol.10.issue5.499
55

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