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A Maximum Relevance Minimum Redundancy and Random Forest based feature selection and classification of gene expression data 5

A Maximum Relevance Minimum Redundancy and Random Forest bas...

引用

5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Kavitha, K.R. Kumar, Revathy Anil Mol, May C. Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350361155

Feature selection is essential for improving the accuracy of models and interpretability in the field of machine learning. This research paper investigates the application of Minimum Redundancy Maximum Relevance (mRmR) feature selection on gene expression datasets to enhance the performance of classification models. The study focuses on the critical task of identifying relevant genes that contribute significantly to the classification of biological samples. mRmR, known for its ability to select informative and non-redundant features, is employed to rank and select a subset of genes based on their relevance to the classification task. The performance of the mRmR-enhanced Random Forest model is evaluated and compared against a baseline model without feature selection. Along with random forest classifier, SVM and k-NN are also used for classification and their accuracies are being evaluated. The experimental results demonstrate the efficiency of the mRmR feature selection method in improving the classification performance of the three classification models on gene expression data. © 2024 IEEE.

关键词： Feature Selection

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Exploring AI Facial Recognition for Real-time Emotion Detection: Assessing Student Engagement in Online Learning Environments 3

Exploring AI Facial Recognition for Real-time Emotion Detect...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Shan, J. Eliyas, Sherin Hindustan Institute of Technology and Science Department of Computer Applications Tamil Nadu Chennai603103 India

ISBN: (纸本)9798350372120

AI facial recognition for real-time emotion detection in online learning environments intends to analyze students' sentiments throughout online classes, recognizing emotions such as focused, neutral, distracted, enraged, thrilled, or dissatisfied states. The proposed approach uses a generative model trained by conditional Generative Adversarial Networks (cGAN) to accomplish De-expression Residue Learning (DeRL), a facial expression recognition technique. DeRL prioritizes gathering residue for delicate emotion recognition by filtering expressive material and storing it in intermediary layers. This technology gives educators and researchers real-time insights into students' emotional states, allowing for a more thorough understanding of collective student involvement through the lens of socially shared control of learning. Experiments on seven facial expression databases, including two pre-training datasets, indicate that DeRL outperforms other methods in accurately recognizing and classifying students' emotions. The findings emphasize its ability to capture subtle feelings during online learning. The discussion dives into theoretical and practical implications, highlighting AI's potential to enhance the evaluation of student participation in online learning environments. The study concludes by providing relevant information for building tailored learning experiences, indicating a possible avenue for incorporating AI in the classroom. © 2024 IEEE.

关键词： Students

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Managing Cybersecurity Challenges on a Global Scale: Balancing Foreign Policy Priorities with the Rise of Digital Threats 1

Managing Cybersecurity Challenges on a Global Scale: Balanci...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Thejeshwar, S. Kannimoola, Jinesh M Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (纸本)9798350353648

This study represents an innovative examination of the potential intersections between Foreign Policy and Cyber Attacks. In today's rapidly evolving landscape, there has been a noticeable uptick in cyber assaults originating from both non-state and state entities. Nations are actively bolstering their cyber defences to safeguard their data sovereignty. Simultaneously, countries are augmenting their capabilities for both offensive and defensive cyber operations. This research delves into the alignment between a state's strategic vision and its employment of Advanced Persistent Threat (APT) groups to further its objectives in the cybersecurity realm. The authors seek to unravel the complexities of achieving Foreign Policy goals through cyber warfare, a nuanced tool that holds the potential to significantly impact nations. This study examines specific countries and their methods of achieving strategic aims through cyber warfare and also proposes a framework for analysing the future probability of attacks using a novel framework built by the authors using Natural Language Processing. © 2024 IEEE.

关键词： Cyber attacks

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A Methodical Approach to Healthcare Cybersecurity: Handling Current Risks and Advancements 6

A Methodical Approach to Healthcare Cybersecurity: Handling ...

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6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Husain Bathushaw, M. Nagasundaram, S. Department of Computer Applications VELS Institute of Science Technology and Advanced Studies Pallavaram Chennai600117 India

ISBN: (纸本)9798331522667

The methods were evaluated using machine learning-driven interruption detection, blockchain-enhanced access control for inconsistency localization, and structured threat insight data in a simulated healthcare environment. With an accuracy range of 0.88-0.94 and lift specified between 0.75 and 1, knowledge values ranging from.86 to.92, and F1 scores between and above, the test results demonstrated that all computations were possible. BACA strengthened access control with blockchain;ADA surpassed expectations in identifying discrepancies;TIAA succeeded in risk insights management;and ML-IDS achieved outstanding results in intrusion detection. A comparison with related research highlights the significance of these algorithms in tackling specific cybersecurity issues in the healthcare sector. Because the proposed algorithms provide a holistic approach to safeguard confidential health information, ensure the validity of assessment models, and strengthen organizations against a range of dynamic cyberthreats, they are pertinent to the expanding discussion about cybersecurity in the healthcare industry. © 2025 IEEE.

关键词： Electronic health record

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The Development of Enhancement of Communication in Drones using Various Iot System 4

The Development of Enhancement of Communication in Drones us...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Adhitya Sathish Kumar, M. Chamoli, Sushant Eliyas, Sherin Hindustan Institute of Science and Technology and Science Department of Computer Applications Chennai India Department of Cse Graphic Era Hill University India Graphic Era Deemed to Be University Uttarakhand India Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350360165

Attacks on UAV communication, or unmanned aerial vehicles used in conjunction with radio signals for operations, are the points of the paper. In that way, UAV vehicles can be intercepted because of the use of that type of signal. Using a certain understanding of the specific communication protocol that is used by a UAV, attackers can design software tools to manipulate the intercepted signals. This may involve the forging of commands, modification of the telemetry data, or even the injection of malicious code into the UAV system. An unencrypted path of communication can lead the UAV vehicles to interception, making it possible for a person who conducts this illegal activity to perform further activities like hijacking the payload it's carrying or forcing it to crash, resulting in loss for the organization. But, this may give a big advantage to an organization because interception can be done in the different ways. This may be done by the other organization in the name of the other things happening so that the organization can detect that some intercepting is done, which it can detect using detection algorithms. And, of course, the more the implementation of the hybrid algorithm is done, the more secure it is from attacks, so it can be done secure by traditional algorithms-RSA-with modern algorithms, for instance, elliptic curve cryptography algorithms. By doing this, communication is made more secure with larger companies like Amazon and Walmart. Being these huge companies, it is better for them to use hybrid-based cryptographic algorithms in order to reduce the risk of interception that may put the organizations at jeopardy. © 2024 IEEE.

关键词： Intrusion detection

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Movie Recommendation System Based on Emotion Detection Using Machine Learning Techniques

Movie Recommendation System Based on Emotion Detection Using...

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2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Vaishnavi, S.R. Sreelakshmi, S. Anu Prabha, R.S. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Applications Amritapuri India

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382693

The face is a critical perspective in predicting human feelings and moods. More frequently than not human senti-ments are extricated with the utilization of the camera. Various applications are being made based on the location of human sentiments. A few applications of feeling revelation are trade notice suggestion, e-learning, mental clutter, sadness disclosure, criminal conduct discovery, etc. This paper presents a novel real-time emotion-based movie recommendation system that combines computer vision, deep learning, and image processing strategies. The system coordinating OpenCV near DeepFace for effective emotion examination utilizing webcam input, giving clients personalized movie recommendations based on their recognized enthusiastic states. The system commences by using OpenCV to capture real-time webcam feeds and utilizes a Haar-Cascade classifier for facial discovery. The recognized faces are analyzed for prevailing feelings utilizing the DeepFace library, empowering exact feeling distinguishing proof. Within the recommendation stage, the system joins content-based filtering by processing a movie dataset utilizing TF-IDF. Genres and plot keywords serve as features for building the TF-IDF matrix. Cosine similarities between the user's emotion vector and relevant movie genres are then calculated, coming about in a list of personalized movie rec-ommendations. Index Terms-FER, OpenCV, DeepFace, Haar-Cascade Algorithm, Content-Based Filtering, TF-IDF © 2024 IEEE.

关键词： Emotion recognition Visualization Webcams Face recognition Motion pictures Real-time systems Libraries

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SHAP and MIC based Hybrid Feature Selection Method and Classification of Gene Expression Data 5

SHAP and MIC based Hybrid Feature Selection Method and Class...

引用

5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Kavitha, K.R. Kumar, Revathy Anil May Mol, C. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Applications Amritapuri India

ISBN: (纸本)9798350376685

In the realm of machine learning, feature selection plays a pivotal role in enhancing model interpretability and performance. This research paper introduces an innovative feature selection algorithm leveraging Shapley values and Maximum Information Coefficient (MIC) for an iterative and dynamic approach. The algorithm aims to iteratively select features based on their Shapley values and update the importance of the remaining features considering the mutual information captured by MIC. The initial phase employs the Minimum Redundancy Maximum Relevance (mRMR) algorithm to select a set of features. Subsequently, Shapley values are calculated to gauge the individual contributions of each feature to model performance. The Dynamic Feature Index (DFI) is then introduced, combining Shapley values and MIC to iteratively select features with the highest DFI. Until a predetermined number of characteristics are chosen, the procedure is repeated, optimizing the feature subset for interpretability and model accuracy. Experimental validation on diverse datasets demonstrates the efficacy of the proposed algorithm in improving model interpretability while maintaining competitive predictive accuracy. The algorithm presents a novel and flexible framework for feature selection, offering a balance between interpretability and performance in machine learning applications. © 2024 IEEE.

关键词： Feature Selection

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Global Strategies in Addressing Cybersecurity Threats: Navigating the Intersection of Foreign Policy and Digital Attacks 15

Global Strategies in Addressing Cybersecurity Threats: Navig...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Thejeshwar, S. Kannimoola, Jinesh M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Applications Amritapuri India

ISBN: (纸本)9798350370249

This research marks a novel exploration into the potential connections between Foreign Policy and Cyber Attacks. In the contemporary landscape, there has been a notable surge in cyber-attacks from non-state and state actors. Nations are actively engaged in fortifying their cyber domains to protect their Data sovereignty. Concurrently, countries are enhancing their capacities for both offensive and defensive cyber warfare. This study investigates the alignment between a state's strategic vision and its utilization of Advanced Persistent Threat (APT) groups to achieve its objectives in the realm of cybersecurity. The authors have tried to explore the intricacies of Foreign Policy objectives being achieved through cyber-warfare. A subtle tool which can bring nation to it's knees is now becoming a force to reckon with. In this study, we have taken up certain countries and how they are achieving their goals by using cyber-warfare. © 2024 IEEE.

关键词： Cyber attacks

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Smart Healthcare Systems: A Survey of IoT and AI Technologies for Heart Disease Prediction

Smart Healthcare Systems: A Survey of IoT and AI Technologie...

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2024 International Conference on Advancements in Power, Communication and Intelligent Systems, APCI 2024

作者： Vishnu, K. Sebastian, Thomas Binu, P.K. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Applications Amritapuri India

ISBN: (纸本)9798350363289

The surge in heart-related issues is linked to lifestyle changes and increased fast food consumption. The convergence of cloud computing, IoT and machine learning for the prediction of cardio vascular disease is examined in this survey. In order to combat the worldwide increase in Cardio Vascular Disease, researchers are investigating novel strategies that make use of IoT sensors, ensemble approaches and machine learning for ongoing health monitoring. By combining these technologies, the IoT-ML-Cloud paradigm seeks to improve the accuracy of Cardio Vascular Disease prediction. It also emphasizes the importance of cloud computing and data mining for large-scale medical data analysis, as well as key findings from various ML algorithms in Cardio Vascular Disease diagnosis. © 2024 IEEE.

关键词： Electronic health record

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A MI and DenseNet Based Feature Selection and Classification of Gene Expression Data 5

A MI and DenseNet Based Feature Selection and Classification...

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5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Ardhra, G. Asha, A. Kavitha, K.R. Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361155

Introducing a groundbreaking approach, the paper unveils MI_DenseNet, a cancer classification procedure that employs mutual information and deep learning to achieve precise classification. The method involves preprocessing the data, converting it into 2D images, and utilizing a DenseNet model for *** experimental results demonstrate that MI_DenseNet outperforms another type of classification methods, showcasing best result. This study dives deep into the world of cancer analysis, where researchers mine data across different cancer types to unlock secrets hidden within. It emphasizes the crucial role of accurate early-stage cancer detection and prediction, not just for individual patients but for shaping the future of cancer research. © 2024 IEEE.

关键词： Classification (of information)

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