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Predicting Student Academic Performance using Machine Learning: Analyzing Socio-Economic and Personal Factors from Secondary Education in Portugal 4

Predicting Student Academic Performance using Machine Learni...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Sahu, Santosh Kumar, Ashok Kumar, Rahul Shukla, Anshita Chole, Vikrant Moolchandani, Jhankar Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Madhya Pradesh Gwalior India

ISBN: (纸本)9798350387490

This paper aims to predict student academic performance using machine learning algorithms by analyzing socioeconomic and personal factors from secondary education in Portugal. The study utilizes a dataset containing demographics, family background, educational support, extra-curricular activities, and academic records to evaluate their impact on students' success in Mathematics and Portuguese courses. Machine learning models such as Logistic Regression, Decision Trees, and Random Forests were employed to analyze the data. The Random Forest model outperformed others with an accuracy of 85 %, indicating significant potential in predicting student performance using the selected features. © 2024 IEEE.

关键词： Adversarial machine learning

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Recent Advances in Analysis and Detection of Tuberculosis System in Chest X-Ray Using Artificial Intelligence (AI) Techniques: A Review

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Current Materials science 2023年第1期16卷 43-51页

作者： Suchitra, Shanmugam Ibrahim, S. Jafar Ali Sathya, Mariappan Sahini, Varsha Chakravarthy, N. Surya Kalyan Kumar, Vaneet Saruchi Department of Computer Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai India Department of IOT SCOPE Vellore Institute of Technology Tamilnadu Vellore India AMC Engineering College Karnataka Bengaluru India Department of Computer Science Engineering CT Institute of Engineering Management and Technology Punjab Jalandhar India Data Science QIS College of Engineering and Technology Andhra Pradhesh Ongole India Department of Applied Sciences CT Institute of Engineering Management and Technology Shahpur Campus Punjab Jalandhar India Department of Biotechnology CT Institute of Pharmaceutical Sciences Shahpur Campus Punjab Jalandhar India

Mycobacterium tuberculosis causes tuberculosis (TB), a bacterial illness. Although germs are most typically found in the lungs, they can affect other sections of the body as well. Tuberculosis is one of the primary causes of mortality in both developed and developing nations, necessitating worldwide attention. Even though TB may be prevented in the majority of instances if discovered and treated early, the number of deaths caused by the disease is quite high. There has been a significant increase in interest and research activity in TB detection in recent years. The new advancement in the field of AI technology may be able to assist them in overcoming these development gaps. computer-Aided Detection and Diagnosis (CADD) aids in the diagnosis of diseases by analysing symptoms and X-ray images of patients. Many solutions are currently be-ing developed to improve the effectiveness of TB diagnosis classification using AI and DL ap-proaches. Although a variety of TB detection techniques have been developed, there is no common-ly acknowledged method. The purpose of this study is to give a survey on Tuberculosis Detection. It also emphasises the difficulty and complexity of the Tuberculosis Detection System's design. © 2023 Bentham science Publishers.

关键词： computer vision

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An Analyzation Of Data Privacy In Sharing And Storing Data In Cloud Environment 10

An Analyzation Of Data Privacy In Sharing And Storing Data I...

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10th International Conference on Electrical Energy Systems, ICEES 2024

作者： Subhasreevignani, R.S. Babu, N. Raji, D. Sowmya, K.N. Afreen Zaiba, S. Reddy Abhishek, G. Siddharth Institute of Engineering & Technology Department of Computer Science and Engineering Andhra Pradesh India Andhra Pradesh India

ISBN: (纸本)9798350353778

The Wide spread use of cloud storage services and their demonstrated power provide the foundational underpinning for the cloud computing industry rapid development. Nevertheless, a lot of security incidents still occur at the cloud storage layer due to deliberate attacks and management negligence, resulting in significant leaks of critical data. To address the issue, we inculate AES and Cryptographic Pseudo Random Number Generator Algorithms. The proposed standard illustrates the process of dividing the data into segments which is encrypted with aes individually to ensure the strong security for data. By distributing the scattered data segments among several cloud sites, security is improved and the possibility of a single point of failure is decreased. Securing access control mechanisms makes it easy for authorized individuals to access and decode data. © 2024 IEEE.

关键词： Cloud security

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Patient Monitoring for Personalized Mobile Health (PMH) Based on Medical Virtual Instruments

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第16期17卷 82-94页

作者： Sweetline, B. Christina Vijayakumaran, C. Samydurai, A. Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu KattankulathurChennai India Department of Computer Science and Engineering SRM Valliammai Engineering College Tamil Nadu KattankulathurChennai India

One of the newest technologies, mobile health, has the potential to support the provision of care for older adults and offer them individualised treatment. This study’s goal is to evaluate the benefits and challenges of personalised mobile health (PMH) for elderly residential care. Virtual worlds are quickly integrating into the landscape of instructional technologies. One of the most well-known of these settings is Second Life (SL). Despite the potential of SL for health professions education, there aren’t many official SL applications for this purpose, and the effectiveness of these applications hasn’t been evaluated to the fullest extent possible. Similarly, it appears that nothing is known about the use of virtual worlds for continuing medical education. In order to better grasp the fundamentals of the aid of MVIs for personal health monitoring (PHM), we were able to pinpoint the key disease regions, sensors, channels, calculations and communication protocols. The main obstacles limiting MVIs’ degree of integration into the international health care system were also identified. The analysis demonstrates that MVIs offer an excellent possibility for the creation of affordable, personalised health systems that meet the unique equipment requirements of a certain field of medicine. © 2023 by the authors of this article. Published under CC-BY.

关键词： mHealth

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The Politics of Fear and the Experience of Bangladeshi Religious Minority Communities Using Social Media Platforms

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Proceedings of the ACM on Human-computer Interaction 2024年第CSCW2期8卷 1-32页

作者： Rifat, Mohammad Rashidujjaman Das, Dipto Podder, Arpon Jannat, Mahiratul Soden, Robert Semaan, Bryan Ahmed, Syed Ishtiaque Department of Computer Science University of Toronto TorontoON Canada Khulna University of Engineering & Technology Khulna Bangladesh Department of Women and Gender Studies University of Dhaka Dhaka Bangladesh Computer Science and School of the Environment University of Toronto TorontoON Canada Department of Information Science University of Colorado Boulder BoulderCO United States

Despite significant research on online harm, polarization, public deliberation, and justice, CSCW still lacks a comprehensive understanding of the experiences of religious minorities, particularly in relation to fear, as prominently evident in our study. Gaining faith-sensitive insights into the expression, participation, and inter-religious interactions on social media can contribute to CSCW’s literature on online safety and interfaith communication. In pursuit of this goal, we conducted a six-month-long, interview-based study with the Hindu, Buddhist, and Indigenous communities in Bangladesh. Our study draws on an extensive body of research encompassing the spiral of silence, the cultural politics of fear, and communication accommodation to examine how social media use by religious minorities is influenced by fear, which is associated with social conformity, misinformation, stigma, stereotypes, and South Asian postcolonial memory. Moreover, we engage with scholarly perspectives from religious studies, justice, and South Asian violence and offer important critical insights and design lessons for the CSCW literature on public deliberation, justice, and interfaith communication. © 2024 Copyright held by the owner/author(s).

关键词： Social psychology

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Congestion Control Routing Scheme for WSN using AI Technologies 3

Congestion Control Routing Scheme for WSN using AI Technolog...

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3rd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Basha, S.K. Mahaboob Gurumoorthi, E. Beulah, E. Mercy Kesavan, R. Kalaiselvan, S.A. Kumar, Lenin Tkr College of Engineering and Technology Department of Computer Science and Engineering Telangana India Cmr College of Engineering & Technology Department of Computer Science and Engineering Telangana India Vel Tech Multi Tech Dr. Rangarajan Dr.Sakunthala Engineering College Department of Computer Science and Engineering Chennai Avadi India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Vignan Institute of Technology and Sciences Department of Electronics Communication and Engineering Telangana India

ISBN: (纸本)9798350369083

An essential part of wireless sensor networks (WSN) is managing congestion, which occurs when the amount of traffic exceeds the combined or individual capacities of the underlying channel. As a result, developing more advanced methods to prevent, detect, and alleviate congestion requires particular considerations. In order to obtain the highest throughput, these strategies must take into account the limited resources of the WSN. Dedicated congestion control strategies and routing protocols that help in congestion detection as well as management are two of the many methods that have been created in recent years. As a means of avoiding congestion, the sink node in the previous designs would reset the topology and reduce bulk traffic. In this article, we lay the groundwork for WSNs and AI, the latter of which will try to prevent congestion in WSNs from the get-go and the former of which will try to minimize the spread of impending congestion by rerouting traffic. An integral part of modern life, Artificial Intelligence (AI) allows us to create self-governing systems. It is possible to enhance performance and reliability by making use of several sophisticated AI approaches. Better network management and routing in WSN may be the outcome of studying the AI algorithm used by WSN, leading to a more dependable network. Here we'll take a look at several AI algorithms that have found their way into WSNs, and we'll talk about how these algorithms might help WSNs overcome their challenges and become more reliable and efficient. Additionally, artificial intelligence has often been disregarded in these networks because of limitations on data processing as well as power consumptions. Thanks to AI, WSN is now lightning fast, error-free, as well as effective in almost every way. Using AI methods in nodes of wireless sensors for congestion aware routes is the goal of this work. © 2024 IEEE.

关键词： Traffic congestion

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Modeling a Hybrid Stemmer for Kokborok

Modeling a Hybrid Stemmer for Kokborok

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2023 International Conference on Intelligent Systems, Advanced Computing and Communication, ISACC 2023

作者： Debbarma, Pankaj Hrangkhawl, Pusparwng Debbarma, Swapan Tripura Institute of Technology Department of Computer Science and Engineering Narsingarh India Ambedkar College Department of Information Technology Fatikroy India National Institute of Technology Department of Computer Science and Engineering Agartala India

ISBN: (纸本)9798350399387

Kokborok is a resource scarce and vulnerable language and is spoken only by around a million people in the north-east Indian state of Tripura. Lots of unstructured textual data in Kokborok is now available however efficient data mining for such a resource is not applicable. Reasons are the absence of an efficient pre-processing step that can help in solving the information retrieval or natural language processing. In this work, we present a model of hybrid stemming algorithm for the vulnerable and resource-scarce Kokborok language and assess its performance using various methods. Evaluation of the hybrid stemmer was performed on a corpus of 52,482 words that resulted in achieving an accuracy of 89.28%. Recall and Precision of 89.28% and 89.61 %, respectively, with F1-measure of 89.44 has been found for the stemmer. © 2023 IEEE.

关键词： Data mining

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Femur Osteoporosis Risk Assessment through Deep Learning Models

Femur Osteoporosis Risk Assessment through Deep Learning Mod...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Kaur, Sandeep Singh, Jaspreet Guru Nanak Dev University Department Of Computer Engineering & Technology Punjab Amritsar India Chandigarh University Department Of Computer Science & Engineering Punjab Mohali India

ISBN: (纸本)9798350366846

One common health problem, especially among older people, is osteoporosis. This condition is marked by decreased bone density and an increased risk of fractures. Effective intervention and treatment rely on early diagnosis and risk assessment. Using deep learning models called Faster R-CNN (Region-based Convolutional Neural Networks), we provide a new method for assessing the risk of femoral osteoporosis in this research. The approach requires amassing X-ray pictures of the femur from a varied group of people, including those with varied levels of bone health. Image quality and feature normalization are improved using preprocessing approaches. In order to precisely identify and pinpoint areas of interest pertaining to structural integrity and bone density, the Faster R-CNN model is trained using annotated datasets. The Faster R-CNN model successfully identifies osteoporotic characteristics in femur X-rays, as shown by our findings. The model is able to differentiate between normal and osteoporotic bone structures with a high degree of sensitivity and specificity. The approach is also well-suited for clinical uses and large-scale screening programmes because of how quickly it can examine data. © 2024 IEEE.

关键词： Risk assessment

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Preserve the Medical Data using Secure Partially Homomorphic Encryption with Blockchain technology in Smart Healthcare 2

Preserve the Medical Data using Secure Partially Homomorphic...

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2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Kavitha, S. Pavithra, B.S. Shashikala, A.B. Jagadeesh, B.N. Mageswari, P. Uma Marichi, Dileep Nitte Meenakshi Institute Of Technology Department Of Mca Bengaluru India East West Institute Of Technology Department Of Computer Science And Engineering Bengaluru India Rns Institute Of Technology Department Of Information Science And Engineering Bengaluru India Presidency College Department Of Computer Applications Bangalore India

ISBN: (纸本)9798350381665

Healthcare information is vital for both individuals and service providers, necessitating secure sharing and maintenance of electronic healthcare records (EHR). Traditional EHR systems have relied on centralized architectures, such as the cloud, which may expose sensitive information to undisclosed intelligence. However, these systems have struggled to address the diverse needs of stakeholders while ensuring separation, security, and compliance with legal requirements. Blockchain technology offers a decentralized and distributed ledger system, providing secure, verifiable, and immutable data transfer capabilities. By employing cryptographic techniques like hashes, blockchain eliminates the need for a central authority, making data exploitation challenging and evident. This study proposes a blockchainbased architecture utilizing the Proof of Stake (POS) consensus mechanism to authenticate user identities and facilitate secure EHR exchange across multiple healthcare systems. Additionally, to enhance data security, Secure Partially Homomorphic Encryption (SPHE) is recommended for outsourced data, enabling users to perform operations on encrypted data. The proposed technique surpasses alternatives in terms of energy efficiency, authenticity, and protection of medical data. © 2024 IEEE.

关键词： Blockchain

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IIITDWD@LT-EDI-2023 Unveiling Depression: Using pre-trained language models for harnessing domain-specific features and context information 3

IIITDWD@LT-EDI-2023 Unveiling Depression: Using pre-trained ...

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3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Biradar, Shankar Saumya, Sunil Kavatagi, Sanjana Department of Computer Science and Engineering Indian Institute of Information Technology Karnatka Dharwad India Department of Computer Science and Engineering VTU Belagavi India

ISBN: (纸本)9789544520847

Depression is a global health crisis affecting millions. Workplace stress and unhealthy habits have risen, leading to more people with depressive symptoms. Early detection and prediction of depression are essential for timely intervention and support. Unfortunately, social stigma prevents many from seeking help, making early detection difficult. Therefore, alternative strategies for depression prediction, such as analysing social media posts, are being explored. LT-EDI@RANLP held a shared task to promote research in this field. Our team participated in the shared task and secured 21st rank with a macro F1 score of 0.36. This article summarises the model used in the shared task. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Natural language processing systems

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