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检索条件"任意字段=International Conference on Advances in Computer Science and Engineering"

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Using Machine Learning to Analyze Employee Psychological Contract Fulfillment: A Data-Driven Approach to Predict Job Satisfaction 1

Using Machine Learning to Analyze Employee Psychological Con...

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

作者： Darshith, S.A. Rakesh, D. Rami Reddy, K Tharaka Rami Sahana, A. Nischith, S. Sumalatha JSS - Centre for Management Studies JSS Science and Technology University Mysuru India The Oxford College of Engineering Bengaluru India BIMS University of Mysore Mysuru India Woodland Aeroclub Pvt Ltd Bengaluru India

ISBN: (纸本)9798331518578

Workplace commitment, productivity, and job happiness are all significantly impacted by employee psychological contract fulfilment (PCF). Self-reports and surveys are used in traditional PCF assessment procedures, which can be laborious and subjective. Using a data-driven methodology, this study analyses PCF and predicts work satisfaction using machine learning (ML). Different machine learning methods are trained to identify trends in contract fulfilment and satisfaction levels by utilising sentiment analysis, workplace behavioural indicators, and employee feedback. While model evaluation guarantees accuracy and generalisability, feature selection strategies pinpoint important predictors. The findings show that when it comes to forecasting work happiness, ML models-in particular, ensemble learning techniques-perform better than traditional statistical methods. This study demonstrates the potential of AI-driven insights in HRM, which can help firms better engage employees, meet their expectations, and strengthen retention tactics. The study emphasises how ML may revolutionise workplace dynamics by helping to understand and optimise them. © 2025 IEEE.

关键词： Adversarial machine learning

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Development of a Model to Identify Fake News using Artificial Intelligence 1

Development of a Model to Identify Fake News using Artificia...

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

作者： Santhosh, B. Raj, Preetham N Khanwalkar, Preeti Raj, Ansuman Ravi Kaushik, Lakshay Suhail, Aamir Dayananda Sagar College of Engineering Department of Electronics and Telecommunication Engineering Bangalore560078 India Dayananda Sagar College of Engineering Department of Mathematics Bangalore560078 India City Engineering College Visvesvaraya Technological University Department of Electronics and Telecommunication Engineering Bangalore India

ISBN: (纸本)9798331518578

Various attempts have been made to identify different types of misinformation because news-related misinformation proves to be a major societal concern. Particularly in social networks, blogs, and online publications. People primarily choose web-based resources for daily news content alongside general knowledge acquisition during the time of pervasive internet access. News spreads fast across diverse user groups within a short span of time across an extensive geographical area because social media platforms (SMP) including Instagram, YouTube, Twitter, Facebook, and internet browsers have become increasingly popular. Fake news creates biased or partial opinion which leads to extensive negative outcomes during its propagation and distribution. Contest results often become subject to these deceptive social media tactics which support particular candidates' political objectives. Spammers exploit attractive news headlines as a way to create income-producing clickbait advertisements. Data verification becomes necessary from time to time. News producers create content with a single goal which includes making readers fall for untrue or fraudulent information. The supporting content for news remains difficult to find because its transparency level is low. The process of identifying genuine news requires supplementary information aligned with social media usage or social engagement functions to be provided. I dedicate this paper to establish two distinct categories for online news articles with the aid of artificial intelligence research combined with linguistic analysis and machine learning techniques. This process enables users to verify the authenticity of presented news content by sharing validation responsibilities which results in either valid or invalid classification. © 2025 IEEE.

关键词： Tweets

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advances in Multimodal Fusion of EHR and Medical Imaging Data Using deep learning techniques for advanced treatment of brain cancer 24

Advances in Multimodal Fusion of EHR and Medical Imaging Dat...

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8th international conference on Algorithms, Computing and Systems, ICACS 2024

作者： Siva Raja, P.M. Vidhya, S. Sumithra, R.P. Anjana, S. Rejini, K. Ramanan, K. Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Nagercoil Tamil Nadu Nagercoil India Department of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu Chennai India

ISBN: (纸本)9798400718304

In this research, the performance of different deep learning models, including CNN + RNN, VGG16 + RNN, VGG19 + RNN, ResNet50 + RNN, and InceptionV3 + RNN in predicting brain tumour grades by employing Electronic Health Record (EHR) and imaging data are evaluated. Confusion matrices show the models' abilities to predict, showing the results of the prediction capability of each model over tumour grades. From the result and analysis, InceptionV3+RNN is performing better than all other ML models. With the multimodal fusion techniques, an informed decision can be made about the grades of the cancer cells, and the clinicians can give the proper treatment to the patients. The proposed approach can be implemented in real-time to predict the cancer grades with the highest level of accuracy for better treatment. © 2024 Copyright held by the owner/author(s).

关键词： Electronic health record

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Exploring Interactive Architecture in a Multidisciplinary Approach 2nd

Exploring Interactive Architecture in a Multidisciplinary Ap...

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2nd international conference on Trends in Architecture and Construction

作者： Chaturvedi, Divyanshi Satpal Nirmala Deenbandhu Chhotu Ram Univ Sci & Technol Dept Architecture Murthal Haryana India

ISBN: (纸本)9789819749904;9789819749881;9789819749874

Architecture has evolved continuously, aligning itself with the evolving needs and desires of society. The idea of interactive architecture emerged with the development of technologies and increment in environmental, functional, and human problems. Interactive architecture refers to the architecture which can change, adapt, and reconfigure to the needs of users and the environment in real time. A Space's Interaction, flexibility, and integration both with the environment and individuals can be done with the help of IoT, artificial intelligence, sensors, actuators, etc. This research paper aims to explore diverse ways and potential in interactive architecture in responding to user needs and environmental dynamics. In the Indian context, the application of interactive architecture is limited, and embracing it will ensure innovation, efficiency, and enhanced user experience. We shouldn't lag in the global evolution of design, adopting these advancements aligns with progress and enriches our built environment. To understand the user-centric perspective, a questionnaire survey (primary) was conducted involving 204 participants along with interviews (secondary). The study encompasses respondents of multiple disciplines, ranging from architects, architecture students, data science students, educators, and others to provide comprehensive insights. The finding of the paper presents that interactive architecture has the potential to revolutionize the way we live and work. Also, there are challenges like high cost, complex technology, and lack of understanding and awareness among the public. In conclusion, this research advances the existing theoretical discourse on interactive architecture and offers more practical insights for architects and other stakeholders in shaping the built environment.

关键词： Smart building Technological advancement User experience Human-building-computer interaction Sustainability

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Deep Learning-Driven Cloud Intrusion Detection: Internet of Things and Cloud Networks 1

Deep Learning-Driven Cloud Intrusion Detection: Internet of ...

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

作者： Moon, Iffath Tanjim Islam Mondal, Md. Nazrul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798331518578

In this paper, we have utilized deep learning approaches to detect cloud intrusion for the Internet of Things (IoT). The emerging growth of IoT and cloud environments has revolutionized many industries by allowing real-time data sharing and storage. Cloud platforms offer the essential infrastructure for managing the massive volumes of data produced by IoT devices. However, due to several flaws, including insufficient encryption, insecure APIs, and weak authentication, intruders can exploit the vulnerabilities to interrupt services and obtain unauthorized access. Therefore, deep learning can be an effective solution to detect cloud intrusion in IoT. In this research, we have developed individual convolutional neural network (CNN) and long short-term memory (LSTM) models, along with a hybrid CNN-LSTM model for multiclass classification and binary classification to detect cloud intrusion. In addition, we have examined which models perform the best for cloud intrusion detection for IoT among the individual and hybrid models. The proposed models are effective in detecting cloud intrusion, as CNN can extract spatial features, and LSTM can capture temporal dependencies from network traffic data. Furthermore, we have utilized one of the most recent and comprehensive datasets for IoT, the ToN-IoT dataset, containing real-world data. In multiclass classification, the hybrid CNN-LSTM has given the best performance, achieving an accuracy of 97.65%, precision of 97.72%, recall of 97.65%, f1 score of 97.67%, and AUC of 99.93%. In binary classification, all CNN, LSTM, and hybrid CNN-LSTM have demonstrated high performance, where LSTM has achieved the highest accuracy of 99.97%. Moreover, we have evaluated the performance of multiclass classification for detecting nine distinct kinds of attacks. In this instance, CNN has shown better performance in detecting backdoor attacks. Thus, this research can make the IoT platform more secure by efficiently detecting cloud intrusion. © 2025

关键词： Network intrusion

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Exploration of Software Field Engineer Training Based on AI+Capability Model 24

Exploration of Software Field Engineer Training Based on AI+...

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2nd international conference on advances in Artificial Intelligence and Applications, AAIA 2024

作者： Zhou, Junjie Wu, Qian School of Information Wuhan Software Engineering Vocational College Wuhan Open University Hubei Wuhan China School of Computer Science Wuhan University Hubei Wuhan China Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts Wuhan China

ISBN: (纸本)9798400712883

With the rapid development of artificial intelligence technology, its application in the field of education and teaching is becoming increasingly widespread, bringing revolutionary changes to traditional education models. To cultivate high-quality software vocational skills talents, a digital management platform based on AI+capability model is constructed to explore the innovative application of artificial intelligence in education and teaching, realizing intelligent auxiliary learning functions such as personalized resource recommendation, student growth monitoring, and achievement label portrait. At the same time, a series of intelligent teaching tools such as"AI+Code Generation, AI+Inspection Assistant, AI+Process Map" will be developed to explore and promote the vertical application of big models in talent cultivation. Through innovative models such as"introducing enterprises into education, cultivating students through real-life situations, AI+empowerment, teaching according to students’ aptitude, trinity, innovative training, strengthening processes, and diverse evaluations", it has been fully applied to the talent training scene of software technology field engineers, and its teaching effectiveness is significant. © 2024 Copyright held by the owner/author(s).

关键词： Students

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NMT Framework for Verse Translation from Hindi to English with CDEC 1

NMT Framework for Verse Translation from Hindi to English wi...

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

作者： Chakrawarti, Rajesh Kumar Pathik, Nikhlesh Chauhan, P.S. Jaiswal, Lucky Sushila Devi Bansal College of Engineering Principal Investigator Department of CSE Indore India MANIT Department of CSE Bhopal India Sushila Devi Bansal College of Technology Department of ME Indore India Sushila Devi Bansal College of Engineering Department of CSE Indore India

ISBN: (纸本)9798331518578

In the modern era, AI and ML are highly demanding Technologies. AI and ML are used to train machines and computers to do types of human work or exactly like human beings. With the help of AI and ML people solve real-life problems. 'Chat-GPT' is one of the major examples. 'Chat-GPT' is an 'AI' tool to generate speech and text and it can be manipulated according to them Language translation is one of the important tasks. Because in this world there are uncountable languages is here. And people need to communicate with each other. So, there are many translators present in the market like Google translator, Microsoft Bing Translator, Yandex and many more translators. However, this type of translator translates only the normal text from the source language to the target language. So our research is based on verse(poetic) translation like poems, mythological text etc this type of verse translation is the most challenging task. So our researcher reached the NLP tool named CDEC. Which has already translated the Chinese poem into English and was developed by Cries Dyler this research motive is to run the CDEC and train the verse model from Hindi to the English language. After Completing this task people can translate verse text. All the translated text was analyzed by BLEU Bilingual Evaluation Understudy. This review aims to analyze how to translate verse text from Hindi to English Language with CDEC. © 2025 IEEE.

关键词： computer aided language translation

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AI Applications in Cybersecurity for Proactive Threat Management 1

AI Applications in Cybersecurity for Proactive Threat Manage...

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

作者： Mishra, Manas Kumar Grover, Varun Jain, Rahul Changalva, Ramsundernag Dhami, Aatishkumar Goel, Om G.L. Bajaj Insitute of Technology and Management Department of Computer Science and Engineering Greater Noida201306 India Carlson School of Management University of Minnesota MinneapolisMN55455 United States Texas A&M University College StationTX77840 United States Liverpool John Moores University Liverpool United Kingdom California State University Los AngelesCA90032 United States ABES Engineering College U.P. Ghaziabad India

ISBN: (纸本)9798331518578

AI in cybersecurity has been gaining ground for years now, and it is used to help manage threats beyond monolithic cyber-attacks. AI today plays a critical role in proactive threat management. It is being used in attempting to understand and mitigate threats before they can escalate and cause harm, as it acts as the first line of understanding and defense against them. Tools/Techniques Used for AI-powered Security Systems AI-powered security systems use advanced algorithms and machine learning techniques to monitor network activity continuously and detect anomalies and potential threats in real-time. These systems may also learn from past attacks and data breaches to evolve and refine their abilities to detect and prevent similar attacks in the future. Avoiding cyber threats from killing even half of any possible motive is possible. In cybersecurity, AI applications are capable of automating responses to detected threats, mitigating the repercussions of attacks and shortening the time needed to counteract security incidents. This is especially crucial in a time when the threat landscape changes every day, and attacks happen so regularly that traditional security controls and human intervention tend to fall short more often than not. This proactive approach enables organizations to identify potential threats before they escalate, providing a higher level of protection against a growing number of cyber threats that can compromise their data, assets, and reputation. Nevertheless, the way forward is not easy because the future of Cybercrime has arrived in the present which include Cyberattacks that violates AI tools to get an edge. © 2025 IEEE.

关键词： Cyber attacks

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Analysis of Smart City Solutions for Sustainable Urban Growth in India 1

Analysis of Smart City Solutions for Sustainable Urban Growt...

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

作者： Kaur, Gurmanjot Mishra, Anupama Kumar, Pramod Kapoor, Garima Himalayan School of Science and Technology Swami Rama Himalayan University India C-PACE Swami Rama Himalayan University India

ISBN: (纸本)9798331518578

Over the past three decades, India's cities have benefited from increased urban investment in terms of better economic conditions and infrastructure. Nonetheless, the cities are also dealing with issues of uneven and polarized growth benefits distribution. This paper proposes a multidimensional framework for monitoring and evaluation, also it expands the objective of inclusive cities beyond the confines of 'pro-poor development'. The article explores the need of smart city solutions to promote sustainability and efficiency in rapidly growing cities. It focuses on resource management, environmental impact, and quality of life. The paper concludes with recommendations for cities adopting these solutions, emphasizing the importance of combining new technologies with traditional methods and public engagement. © 2025 IEEE.

关键词： Sustainable city

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An extensive critique on advances in digital control techniques for smart grid and micro grid operation

An extensive critique on advances in digital control techniq...

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2025 IEEE international Students' conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Sarathkumar, D. Bashkaran, K. Manivel, Murugesan Jayakumar, T. Sivakumar, R. Anandhakumar, C. Kongu Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638 060 India Kongunadu College of Engineering and Technology Department of Biomedical Engineering Tamil Nadu Thottiam621215 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India V.S.B Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 639111 India Sri Ramakrishna Institute of Technology Department of Electrical and Electronic Engineering Tamil Nadu Coimbatore641010 India

ISBN: (纸本)9798331529833

The integration of digital control techniques within smart grids and microgrids represents a pivotal advancement in the optimization, reliability, and efficiency of modern electrical networks. This paper explores the latest developments in digital control strategies, focusing on their application to the operation of smart grids and microgrids. Key areas of discussion include the implementation of advanced algorithms for real-time monitoring and control, the role of artificial intelligence and machine learning in predictive maintenance and decision-making, and the impact of distributed control systems on grid stability and resilience. Furthermore, the paper examines the challenges and solutions associated with integrating renewable energy sources and energy storage systems into the grid, emphasizing the importance of adaptive and scalable control frameworks. Through a comprehensive review of recent research and case studies, this paper provides insights into the future trends and potential breakthroughs in digital control technologies, highlighting their critical role in the evolution of smart grid and microgrid infrastructures. The findings suggest that continued innovation in this field will significantly enhance the operational capabilities of electrical grids, paving the way for more sustainable and resilient energy systems. © 2025 IEEE.

关键词： Smart power grids

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