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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
55

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Forensic Analysis Model for Investigating Cybercrime Over the Network

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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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A Study and Analysis of Software Metrics Components

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A Study and Analysis of Software Metrics Components
Authors:-Research Scholar Sandhya, Professor Mukesh Kumar

Abstract-In software programming, Component-based programming is one of the most well-organized and dependable factor to improve software development capabilities. This kind of programming uses the existing components or program blocks to generate new programs. The reusable components not only speed up the development process but also increase the software’s reliability. But this reliability and efficiency depend on the number of components used along with interfacing with new components. There is the requirement to study the complexity of the inclusion of these new components in the software system so that the complete software analysis will be performed. In this present paper, module component analysis and the integration analysis approach is done to analyze the software system. In this paper, a weighted approach is defined to perform the analysis and to identify the effectiveness of software reusability.

DOI: 10.61137/ijsret.vol.10.issue5.265

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How to submit an article for publication in a journal

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PhD scholars and many masters or postgraduate school scholars who want to grab an academic or researcher post as per the studies need to publish articles in their respective fields. As a newcomer in the field they don’t have much idea about how to publish a research paper or how to write an article and publish it in a journal. They seek help from online portals and seniors or mentors from time to time to know about how to submit an article for publication in a journal. This blog will detail everything one needs to know about the submission of an article in an international journal.

Submit Your Paper  / Check Publication Charges

Before going further let’s understand what one should check on the journal website prior to submission of their manuscript.

  • First of all, go to the journal website and explore it to know the scope, medium of publication, issues, charges and other requirements requested by journal pre-submission of manuscript. As some journals asked for the submission in their prescribed formats so it will be wise to check it before submitting the article.

  • Some journals ask authors/scholars to submit articles directly via mail while others accept from the submission form. One should check the type of submission asked by the journal before submitting their research articles into it.

  • Check the peer review process and overall time for the publication before submitting the article. It will help one understand the expected time of publication in case of acceptance/resubmission/rejection.

Irrespective of Fields one can follow the points below to know how to submit an article for publication in a journal.

How to submit an article for publication in a journal

  • Visit the manuscript submission page of the selected journal.

  • If journals accept paper via form then fill the details asked in the form.

  • A standard article submission form includes title, abstract, author information, address, and contact details. Fill the information as asked and move to the next segment.

  • Upload research articles or manuscripts in the format asked by the journal.

  • Check email and other details before clicking on the submission button.

Wait for the journal’s response after the submission. Journal will contact you via mail so keep in check regularly.

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Exploring the Evolution, Impact and Growth of Investment and Trading Applications

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Exploring the Evolution, Impact and Growth of Investment and Trading Applications/strong>
Authors:-Shivang Gurjar, Umesh Bashyal, Khushi Vishwakarma, Priyanshi Shah, (Dr.) Monika Bhatnagar

Abstract-This paper explores the evolution, impact, and growth of investment and trading applications in the financial ecosystem, emphasizing how these platforms have revolutionized access to the market for retail and institutional investors alike. With the rise of fintech innovations, applications such as robo-advisors, micro-investing apps, and algorithmic trading platforms have democratized investing, lowering barriers to entry and automating portfolio management. These apps leverage advanced technologies like artificial intelligence (AI), machine learning (ML), and big data analytics to offer personalized investment strategies, real-time trading, and portfolio optimization. The paper examines the technological underpinnings of these applications, highlighting the role of AI and algorithmic systems in transforming traditional trading approaches. Case studies of platforms like Groww, Zerodha, and Upstox illustrates how investment apps have expanded market participation, particularly among younger, tech-savvy investors in India. However, the widespread adoption of these platforms has also raised concerns about overtrading, market manipulation, and speculative behaviour. Through a comprehensive review of the benefits, risks, and regulatory challenges, this research also addresses ethical concerns surrounding the gamification of trading and the protection of inexperienced investors. As investment apps continue to evolve, the paper explores future trends, including the integration of blockchain in decentralized finance (DeFi), increased regulatory scrutiny, and the growing focus on sustainability and environmental, social, and governance (ESG) investments. This study provides valuable insights into the ongoing transformation of the financial landscape through technology-driven investment solutions.

DOI: 10.61137/ijsret.vol.10.issue5.264

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how to get published in an academic journal

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Research scholars often find it difficult to submit their research article for publication as they are new to the research field and have no peer experience about the articles or other things needed for successful publication. As a newbie they search for how to get published in an academic journal on different digital platforms or social networking sites. They asked their seniors or mentors for guidance on how to write the article to get published in an academic journal. This blog will help those researchers or academicians in finding a good platform where I can showcase or share the research work with like-minded people.

Submit Your Paper  / Check Publication Charges

Why is research publication important?

Research has been part of our society from ancient times. It plays an important role in transmitting knowledge and experience from one generation to another. The records of previous inventions, discoveries helped us to improve and inspire us to build new things.

How to write a research article?

A standard research article has a title, keywords, abstract of the paper, introduction, research data set, references, outcomes and conclusion. One can read previously published articles or papers to get an idea about how to initiate their research article and get published in an academic journal.

how to get published in an academic journal

how to get published in an academic journal

How to get published in an academic journal?

Go to the journal’s website and find the journal manuscript submission page.

  • Some journals accept papers through email while others are asked to fill a submission form to receive research articles on their portals. Complete the submission process as asked by the journal.

  • After submitting the manuscript, wait for the review process to be done. The journal may ask for some changes in the manuscript before final acceptance. So keep in touch with the journal for any corrections or suggestions to improve research work.

  • If the paper gets accepted then complete the publication fees or other formalities asked by the journal to process publication.

  • If all conditions met as per journal’s standard then the paper gets published and the link will be shared with the author.

  • I Hope this article helped you in finding the process of publication in an academic journal. To find more information please visit the official website and submit manuscript for review and publication in an international journal.

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Credit Shield Solutions: Credit Card Fraud Detection System Using Machine Learning Approach

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Credit Shield Solutions: Credit Card Fraud Detection System Using Machine Learning Approach/strong>
Authors:-Assistant Professor Mr. Rakesh Jaiswal, Aditya Krishna, Lucky Singh Rajput, Divyansh Rathore, Kishore Bole

Abstract-In recent times, the exponential growth in the usage of credit cards has increased fraudulent activities, which impacts financial institutions significantly. A large number of machine learning (ML) techniques are used to detect fraudulent transactions in order to thwart such threats. This paper represents a review of state-of-the-art ML algorithms used for credit card fraud detection and further analyzes their performance with regard to accuracy and privacy. Besides, a hybrid approach combining ANN with federated learning is proposed. This approach has the potential to not only increase the detection accuracy but also mitigate data privacy issues. The given model has had promising results for real-time application in credit card fraud detection while keeping users’ data private. Keywords— Artificial Neural Networks, Credit Card Fraud Detection, Federated Learning, Machine Learning, Privacy-Preserving, Blockchain. Credit card fraud has been an exploding problem with the large-scale growth of digital transactions, posing significant risk exposure to financial institutions. In this paper, we conducted a comprehensive review of various ML techniques applied to credit card fraud detection, touching on both aspects of accuracy and concerns over data privacy. We herein present a novel hybrid model based on the paradigm combination of ANN and FL for overcoming challenges arising from accuracy and privacy protection in detection. The advantages of the model are the usage of pattern recognition ability on ANN and its preservation of data privacy through decentralized learning. It has promising uses and outcomes since high detection accuracy and user privacy persistence were noted in achieving this characteristic. This makes this type of model suit fraud detection applications applied real-time. Keywords: Credit card fraud detection Machine learning Artificial neural networks Federated learning Privacy.

DOI: 10.61137/ijsret.vol.10.issue5.263

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A Review of Renewable Energy Based Distributed Generation in Electrical Power System

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A Review of Renewable Energy Based Distributed Generation in Electrical Power System
Authors:- Ravindra Sharma, Dr.Chandrakant Sharma

Abstract-It is possible to describe distributed generation as power generation by small scale generating units installed in distribution systems. There is a steady growth in the penetration of distributed generation (DG) units into electric distribution systems. DG allocation is the process of finding the optimal type, location and size of DG units. The allocation of DGs is a hot research field and poses a difficult problem in electrical power engineering. This paper discusses the recent research work on the issue of DG allocation from the point of view of their optimization algorithms, targets, and decision variables, type of DG, implemented limitations and type of modeling of uncertainty used. In this research an overview of DG types and various DG technologies are highlighted. Some DGs challenges ahead with current drive towards smart grid networks is also discussed. The research gaps are defined on the basis of their views on current research work and some helpful suggestions will be made for future research on DG allocation. The author strongly believes that this paper could be beneficial in the related field for researchers and engineers.

DOI: 10.61137/ijsret.vol.10.issue5.262

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Self Balancing Robot with Autonomous Navigation and Obstacle Detection

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Self Balancing Robot with Autonomous Navigation and Obstacle Detection/strong>
Authors:-Disha Nagpure, Bhakti.B.Bagal, Vaishnavi.B.Kute, Aakanksha.D.Pednekar, Akanksha.S.Shinde

Abstract-This paper details the design and implementation of a two-wheeled self-balancing robot capable of following a predefined path while detecting and avoiding obstacles. The robot utilizes an Infrared (IR) sensor array to track the path and an ultrasonic sensor to identify and measure the distance to obstacles in real-time. The self- balancing mechanism is achieved through a feedback control system that stabilizes the robot on its two wheels using a combination of gyroscopic and accelerometer data. A proportional-integral-derivative (PID) controller is employed to maintain stability and ensure smooth navigation along the path. The system’s effectiveness was evaluated through a series of experiments, demonstrating the robot’s ability to maintain stability, follow complex paths, and avoid collisions with obstacles.

DOI: 10.61137/ijsret.vol.10.issue5.261

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