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15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Nisha, A.G. Shivaprasad, N. Nischitha, C.B. Shashikala, B.M. Sujithra, M. Chaba, Yogesh Electronics & Communications Engineering JSS Science & Technology University Mysuru India Dept.of Electronics & Communications Engineering Sri Jayachamarajendra College of Engineering JSS Science & Technology University Mysuru India Dept.of Computer Science St.Joseph's First Grade College Mysore India Dept.of Computer Applications Sri Jayachamarajendra College of Engineering JSS Science & Technology University Mysuru India Department of Computing-Data Science Coimbatore Institute of Technology Coimbatore India Department of Computer Science and Engineering Guru Jambeshwar University of Science and Technology Haryana Hisar India

ISBN: (纸本)9798331300579

Social media has become a trend nowadays people are spending more time in social media platform like Facebook, Twitter, Instagram to share their opinions, creating new interests, ideas and generate *** provide a major platform for collecting information which helps us to analyze them for our *** such microblogging social network is twitter which allows information collaboration and quick information sharing that provides relief from rising *** has several millions of people tweeting and expressing their perspectives on a due to its distinctively brief and straightforward expressing *** enormous volume of raw data from tweets can be utilised for analysis and processing based on industrial or business *** this technical paper, the application of tweet sentiment analysis by extracting a vast number of tweets using continuous tweet stream provided by Spark and Kafka has been *** system fetches live tweets from Twitter based on the search criteria, process the tweets, by using text mining techniques and classify them based on different labels. © Grenze Scientific Society, 2024.

关键词： Tweets

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Software Bug Prediction using Machine Learning 15

Software Bug Prediction using Machine Learning

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15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sathiyaraj, A. Angel, T.G. Ruby Turukmane, Anil V. Ramkumar, D. Guravaiah, Y. Department of Information Technology School of Computing Sathyabama Institute of Science and Technology Tamil Nadu Chennai600 119 India School of Computer Science and Engineering VIT-AP University Inavolu Andhra Pradesh Amaravati522237 India Department of Computer Science and Engineering MJR College of Engineering and Technology Diguvapokulavaripalli Pulicherla Andra Pradesh Chittoor District517214 India

ISBN: (纸本)9798331300579

The entire success of software is impacted by software bug prediction (SBP), a crucial part of the software development and maintenance life cycles. It is necessary to anticipate issues in order to increase the software's dependability, efficiency, and cost. In spite of the fact that a number of methods have been put out in the literature, it is difficult to create a reliable bug prediction model. In this paper, a machine learning (ML) based prediction method for software issues is introduced. Algorithms for guided machine learning that are based on historical data have been used to predict software errors. Two of the classifiers are Support Vector Machine and Naive Bayes (NB). How accurate and useful ML methods can be employed was demonstrated through the evaluation process. Included is the utilization of a comparative measure. © Grenze Scientific Society, 2024.

关键词： Prediction models

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Enhancing Image Segmentation in the Marine Atmosphere for Time-Sensitive Contextualisation using Convolutional Long Short-Term Memory 2

Enhancing Image Segmentation in the Marine Atmosphere for Ti...

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2nd international conference on advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Reethika, A. Rajeshwari, R. Vijayalakshmi, S. Malathy, S. Gnanasaravanan, S. Suresh Kumar, M. Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering CMR Institute of Technology Bengaluru India Department of Information Technolog KPR Institute of Engineering and Technology Coimbatore India Department of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Information Technology Sri Ranganathar Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798331541217

The work investigates autonomous surface vehicle obstacle avoidance and detection using computer vision techniques. It recognizes boundaries in marine environments by using the temporal context from video feeds from unmanned surface vehicles. The study shows how successful LSTM cells are in the CNN topologies that are currently in use, emphasizing how they might perform better. Nevertheless, datasets and network training techniques are not perfect. The work also uses a benchmarking approach to compare new network configurations. © 2024 IEEE.

关键词： Image segmentation

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Comprehensive Review: Advancing Cognitive Computingthrough Theory of Mind Integration and Deep Learning in Artificial Intelligence 24

Comprehensive Review: Advancing Cognitive Computingthrough T...

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8th international conference on computer science and Application engineering, CSAE 2024

作者： Liu, Shuyan Wang, Kangsheng School of Information Science and Engineering Yunnan University Yunnan Kunming China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798400718090

In this article, we will review our advances in intelligence modeling the mind and explore various efforts to mimic the processes that would allow humans to perform cognition files and line widgets of processing. It presents ideas and stresses how understanding cognitive functions is vital for AI progress. Three principal modeling strategies are examined: cognitive mind modeling, assignation mind modeling, and intelligent body mind modeling. In the article, he explores a few theories, such as symbol systems and the ACT-R framework. It further argues that learning seems limited in encoding models of the mind, citing its successes in language-oriented tasks and its limitations in translating basic mechanisms like reward to model-level language and data from neuroscience. Additionally, it investigates ways of assessing and enhancing learning theory of mind abilities based on tasks that utilize end-to-end function. The review reiterates the need for an improved understanding of human-level thought processing to develop intelligent systems that can better discern intentions and feelings. It provides some ideas on evaluating this based on deep learning approaches. The review argues that viewing learning through the lens of systems yields new insights into human thought and social behavior that could enable the development of novel and more adaptive AI technologies. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

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Fraud Detection and Prevention in E-Commerce: Machine Learning Approaches to Secure Transactions 1

Fraud Detection and Prevention in E-Commerce: Machine Learni...

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1st international conference on advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Srinivas, Madhira Kilaru, Mrudula Jain, Divya Sidhu, Kawerinder Singh Department of Computer Science & Engineering - Data Scienc Cheeryala Hyderabad501301 India Siddhartha Academy of Higher Education Velagapudi Ramakrishna Siddhartha School of Engineering India Jaypee University of Engineering and Technology Department of Mathematics Madhya Pradesh Guna473226 India Uttaranchal Institute of Management Uttaranchal University Uttarakhand Dehradun India

ISBN: (纸本)9798331518578

E-commerce has grown as a leading marketplace for world trade, but this market has been contaminated by new risks like fraud. Some of the past techniques of detecting fraud do not do well in handling new methods of fraud in the market. The purpose of this research is to understand the offers of the ML approaches for increasing the efficiency of the fraud detection and prevention in e-Commerce processer. This study shows the utility of using different types of the ML solution alone and in comparison, to one another for real-time cyber fraud identification by demonstrating how and why their false positives and overall effectiveness are lower than other methods, as well as how the models adapt to new tactics. Issues like quality of data used, bias in either selection or process of the algorithm are also covered. © 2025 IEEE.

关键词： Marketplaces

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Cracking the Cultural Code: Understanding the Cultural Barriers for international CS Students in the US 2024

Cracking the Cultural Code: Understanding the Cultural Barri...

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conference on Research on Equitable and Sustained Participation in engineering, Computing, and Technology (RESPECT)

作者： Sthapit, Sandeep Thomas, Madison Brock, Janet Barnes, Tiffany North Carolina State Univ Raleigh NC 27695 USA

ISBN: (纸本)9798400706264

In computer science, cultural assumptions are embedded in programming languages and problem prompts. This paper investigates the impact of cultural assumptions on international computer science students in the US. By performing thematic analysis on semistructured interviews with 12 international graduate students at North Carolina State University, the authors found six main themes. Analyzing these themes provided insight into what barriers international students face and how they can be alleviated. By shedding light on this topic, the authors hope to inform computer science educators and researchers on the importance of creating inclusive and culturally relevant learning environments that accommodate the needs of diverse students.

关键词： cultural identity culturally relevant computing international students inclusive computing curricula and pedagogy

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Network Security and Cryptography: Threats, Obstacles and Solutions-A Bibliometric Analysis

Recent Advances in Computer Science and Communications

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Recent advances in computer science and Communications 2025年第2期18卷 83-101页

作者： Singh, Purushottam Dutta, Sandip Pranav, Prashant Department of Computer Science and Engineering Birla Institute of Technology Mesra Ranchi835215 India

Background: In the wake of escalating cyber threats and the indispensability of ro-bust network security mechanisms, it becomes crucial to understand the evolving landscape of cryptographic research. Recognizing the significant contributions and discerning emerging trends can guide future strategies and technological advancements. Our study endeavors to shed light on this through a bibliometric analysis of publications in the realms of Network Security and Cryptography. Method: To chronicle and synthesize the progression of research methodologies from their in-ception to the present day, we undertook a comprehensive Bibliometric Analysis of Network Security and Cryptography. Our data set was culled from the Clarivate Analytics Web of science Database, encompassing 3,897 papers, 603 sources, and 7,886 authors from across the globe. Results: Our analysis revealed a marked upsurge in cryptographic research since 1992, with China standing out as a dominant contributor in terms of publications. Notably, while 'security' and 'cryptography' emerged as recurrent research themes, there's an observable downtrend in international collaborations. Our study also highlights pivotal topics shaping the network security domain, offering insights into the trajectories of research source growth, structural variabil-ities in research relevance, and prospective intellectual and collaborative avenues as guided by authorship patterns. Conclusion: Cryptographic research is on an upward trajectory, both in volume and signifi-cance. However, the tapering of international collaborations and an evident need to concentrate on emergent challenges, such as data privacy and innovative network attacks, emerge as nota-ble insights. This bibliometric review serves as a compass, directing researchers and academi-cians towards areas warranting heightened attention, thereby informing the roadmap for future investigative pursuits. © 2025 Bentham science Publishers.

关键词： Cyber attacks

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Classification for Stress Release Management using Machine Learning 1

Classification for Stress Release Management using Machine L...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Hasan, Yazdani Gupta, Anuj Upadhyay, Diwakar Pandey, Mahima Shankar Malik, Suraj Gochhait, Saikat Noida International University Department of Computer Science India Sharda University School of Engineering and Technology Department of Computer Science & Engineering Uttar Pradesh Greater Noida India Graphic Era Hill University School of Computing Department Haldwani India Galgotia College of Engineering and Technology Department of Computer Science & Engineering Uttar Pradesh Greater Noida India IIMT University Department of Computer Science & Engineering Uttar Pradesh Meerut India Constituent of Symbiosis International Deemed University Symbiosis Institute of Digital and Telecom Management Pune India

ISBN: (纸本)9798350356816

Manipulating the words in some useful ways makes the mind refreshed and worth seeking. Instead of the website, the music software is not able to grab the attention of the user in most of the moody cases. Also, the companies which are running this facility are not able to provide the demanded services. As per the opportunity, the providers are also working hard for more user satisfaction. By adding classification to the existing technology, the providers are designing attractive platforms for the users. The common challenge here is to automate the system. There should be automatic identification system instead of manually operated. Machine learning and data mining techniques are best for classification and deployment of any complex category. This is the only advantage of machine learning, as it drives the optimized method as well as the concept of basic probability. To develop the automated system, the mood classification should be identified from the user's point of view according to their own preferences. Hindi and Bollywood songs are taking heavy traffic in the online channel of music. Also, these are the best for calming the mind. When calculating the response through ratio display, it seems like 70% to 75% accuracy with calls. This paper is also showing the percentage and useful features by implementing the system with machine learning method i.e. Random Forest method. © 2024 IEEE.

关键词： Adversarial machine learning

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Evaluation of Supply Chain Design Decisions under Uncertainty - A Case Study Analysis

Evaluation of Supply Chain Design Decisions under Uncertaint...

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2024 international conference on advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Joe Prathap, P.M. Beevi, L. Sherin Dani, W. Vinil Vivek, Panguluri Venkata Jubilson, E. Ajith R.M.D. Engineering College Department Of Computer Science And Engineering Kavaraipettai India St. Peter's College Of Engineering And Technology Department Of Eee Chennai India School Of Computer Science And Engineering VIT-AP University Andhrapradesh India

ISBN: (纸本)9798350371567

This study digs into the strategic supply chain decision-making process of Bridgestone Tires, a global tyre manufacturing leader, demonstrating the effectiveness of decision tree analysis in dealing with complex uncertainty. Bridgestone Tires has a variety of problems, including fluctuating exchange rates and uncertain demand patterns, demanding strategic plant placement across its global network. Using decision tree methodology, this study examines optimal choices under various current and future situations, providing light on the importance of addressing demand unpredictability and economic variables in financial supply chain design decisions. The findings emphasise the importance of thoroughly integrating financial data, identifying risks, calculating cash flows, and considering alternative scenarios. While decision tree tools are cost-effective, simulation models enable nuanced assessments of complex scenarios, but at a greater setup and operating cost. Finally, this study explains how firms can use decision tree analysis and simulation modelling to effectively manage uncertainties, allowing for more informed and optimised supply chain design decisions in dynamic global environments. © 2024 IEEE.

关键词： Decision trees

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Enhancing Enterprise Data Management with Secure and Scalable Cloud Storage Solutions 2

Enhancing Enterprise Data Management with Secure and Scalabl...

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2nd IEEE international conference on advances in Information Technology, ICAIT 2024

作者： Kanna, Rajesh Lakshmi, D. Muneeshwari, P. Valantina, G. Mary Suguna, R. Department of Petroleum Engineering AMET Deemed to be University Chennai India Department of Computer Science and Engineering Panimalar Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Rajalakshmi Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350383867

Today it has become extremely critical for the business to utilize and safeguard the data(Enterprise data) in a proper way in order to achieve the organizational success which is in accordance with the digital environment. The objective of this paper is to analyze the paradigm change in the patterns from relying mainly on secure and scalable cloud storage solutions to handle evolving challenges encountered in data management. The shift from old stands on site in console to a cloud based storage system gives enterprises unlimited capacity not only is that but they also can scale accordingly and get the best security features. No sentiment was spared by the introductory abstract, which discussed the advantages to the end users of cloud storage, from its flexibility and accessibility to being cheaper than preserving data in conventional storage modes. On the other hand, abstract attracts the security in cloud storage, including encryption, access controls, and compliance certificates that help protect the information from a theft and other risks. The other topic that has been touched upon is scalability, which demonstrates how the cloud makes enterprises to be very adaptable to current storage requirements and enabling growth of storage that is astronomical in magnitude. Consequently, the poem abstract illustrates the essential functions of cloud storage as the technology that particularly empowers innovation through data science and use of analytics and artificial intelligence. This article demonstrates the need for organizations to implement a cloud standard purpose made for the storage of data and the harm of business in the digital age as a strategic priority amidst data management activities. © 2024 IEEE.

关键词： Cloud storage

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