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Machine Learning-based Automated System for Subjective Answer Evaluation 9

Machine Learning-based Automated System for Subjective Answe...

引用

9th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2023

作者： Dodia, Shubham Spoorthy, V. Chandak, Trupti National Institute of Technology Karnataka Dept. of Computer Science and Engineering Surathkal Mangalore India National Institute of Technology Karnataka Dept. of Information Technology Surathkal Mangalore India

ISBN: (纸本)9798350334395

An examination is a useful tool for assessing students' knowledge. Evaluation of exams is a difficult and time-consuming process. The automatic examination of answer scripts makes this task easier for teachers, reducing the amount of effort and time required. The existing literature has a number of methods that have been proposed for evaluating responses to objective questions using machine learning. However, more work needs to be done on evaluating answers to descriptive questions. This study suggests a way to evaluate students' answers to questions of a descriptive kind without using traditional paper or pencil by teachers. Instead, a computer acts as a teacher and grades the students' submissions. The primary objective is to communicate the outcomes of subjective responses using Bidirectional Encoder Representations from Transformers (BERT), cosine, and Jaccard distance. The proposed model achieved an accuracy of 91%, an error of 9.01, a precision of 83%, and a recall of 79%, respectively. The suggested model has provided the best results in comparison with state-of-the-art systems. © 2023 IEEE.

关键词： Machine learning

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Near-Optimal Swapping and Purifying Strategy for All-Optical-Switching Entanglement Routing

Near-Optimal Swapping and Purifying Strategy for All-Optical...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Huang, Shao-Min Hsu, Tang-Ming Du, Jing-Jhih Kuo, Jian-Jhih Wang, Chih-Yu Academia Sinica Research Center for Information Technology Innovation Taipei City Taiwan National Chung Cheng University Dept. of Computer Science and Information Engineering Chiayi Taiwan

ISBN: (纸本)9798350351255

Entangled pairs serve as the cornerstone for secure data transmission. All-optical-switching technology on nodes enables the entangling signals to bypass nodes and build ultra-long entangled pairs. Nevertheless, entangled pairs suffer from decoherence over distance, causing inadequate fidelity and potentially compromising transmission quality. To address the challenges, we employ entanglement purification to enhance fidelity to meet the threshold. However, the purification process consumes additional entangled pairs and may fail. Besides, the purification efficiency would be poor if the input pairs have low fidelity. Thus, it is unavoidable to divide the path into sub-paths with appropriate lengths for better purification efficiency and then merge them into a longer entangled pair by swapping. The novel optimization problem DOSP then emerges: maximizing the probability while adhering to fidelity constraints. To tackle the DOSP efficiently, we propose a (1-δ)-approximation algorithm NSPS to consider the probability and fidelity jointly, where is a positive user-defined constant. Finally, the simulation results manifest that the NSPS can outperform the existing methods by at least 70%. © 2024 IEEE.

关键词： Quantum entanglement

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A Lightweight-CNN Model for Efficient Lung Cancer Detection and Grad-CAM Visualization 2

A Lightweight-CNN Model for Efficient Lung Cancer Detection ...

引用

2nd International Conference on information and Communication technology for Sustainable Development, ICICT4SD 2023

作者： Tasmim Bakchy, Sagor Chandro Peyal, Hasibul Islam Islam, Md. Injamul Yeamin, Golam Kibria Miraz, Shafiun Abdal, Md. Nazmul Rajshahi University of Engineering & Technology Dept. of Electrical & Computer Engineering Rajshahi Bangladesh Uttara University Dept. of Computer Science & Engineering Dhaka Bangladesh Rajshahi University of Engineering & Technology Dept. of Electrical & Electronic Engineering Rajshahi Bangladesh Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350358667

The lungs' abnormal cell growth leads to the development of lung cancer. Early cancer identification could make treatment easier, potentially saving millions of lives annually. This study's main goal is to more rapidly and effectively classify various types of lung cancer by employing a lightweight, computationally efficient convolutional neural network (CNN) model to categorize three different types of lung cancer. With an outstanding validation accuracy of 99.48%, the suggested model surpasses the achievements of previous works. The 15,000 CT scan images in our dataset include three different forms of lung cancer. The proposed model performs exceptionally well, as evidenced by its astounding precision, recall, and F1-score, all above 99%, and by its flawless Area Under Curve (AUC) score of 100%. The proposed model has fewer parameters than the existing transfer learning models. Gradient Weighted Class Activation Mapping (Grad-CAM) was used to create class activation maps, which were then used to create a heatmap to display the classification zone. © 2023 IEEE.

关键词： Neural network models

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Quantum Error Correction Based Entanglement Routing in Socially-Aware Quantum Networks

Quantum Error Correction Based Entanglement Routing in Socia...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Huang, Shao-Min Chien, Ming-Huang Wen, Ting-Yuan Wang, Qian-Jing Kuo, Jian-Jhih National Chung Cheng University Dept. of Computer Science and Information Engineering Chiayi Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei City Taiwan

ISBN: (纸本)9798350351255

Quantum teleportation enables high-security communications via quantum entanglement. However, decoherence, signal decay, and environmental interference may cause imperfect entangled pairs with low fidelity. Such entangled pairs may easily generate errors when used to teleport data qubits and cause fatal computation errors on quantum computers. Fortunately, data qubits can be encoded via quantum error correction (QEC) code to recover the detected error to some extent. Nevertheless, letting any repeaters process data qubits is dangerous because malicious repeaters may peep at, destroy, or fake the data qubits. Thus, in this paper, we propose a novel QEC-enabled routing framework MOON facilitated with the concept of social networks (SNs) for quantum networks (QNs). MOON selects only trusted repeaters to process data qubits and exhibits elastic routing with QEC to maximize the throughput without errors. Last, simulation results show that our framework can outperform existing approaches by up to 34% on network throughput without errors. © 2024 IEEE.

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Real-Time Clickstream Data Processing and Visualization Using Apache Tools 7

Real-Time Clickstream Data Processing and Visualization Usin...

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2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Patil, T.B. Anand, Keshav Bhateja, Aditya Jamal, Kashif Sawant-Patil, S.T. Paygude, Priyanka College of Engineering Dept. of Information Technology Pune India

ISBN: (纸本)9798350304268

In the modern digital generation, clickstream data analytics is a crucial component of online selling and purchasing platforms. It offers useful information for enhancing user experience, conversion rates, website design, and keeping track of the success of digital marketing efforts. A data warehouse is required to store and analyze clickstream data, which requires a lengthy and complex ETL process. Two of the leading large data processing tools and distributed streaming systems are Spark and Kafka. This paper presents a comprehensive examination of recent research pertaining to clickstream data analytics, real-time data visualization, data lifecycle management utilizing Apache technologies. Based on the review, the paper proposes an architecture that can aid organizations and local merchants in effectively visualizing the performance of their products. This paper provides a valuable resource for researchers and practitioners seeking to explore the latest developments in their future work. © 2023 IEEE.

关键词： click streaming continuous data integration data lifecycle data transform data warehouse extract load real-time data visualization transform

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Leveraging Smart Video-Based Learning to Enhance Student Engagement and Collaboration 6

Leveraging Smart Video-Based Learning to Enhance Student Eng...

引用

6th International Conference on Advancements in Computing, ICAC 2024

作者： Serasinghe, Chanukya Perera, Nashali Samarasinghe, Devindu Muthusinghe, Madusha Wijesundara, Malitha Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Humanities and Sciences Malabe Sri Lanka

ISBN: (纸本)9798331517878

The COVID-19 pandemic has expedited the shift in education to online learning, which has exposed shortcomings in virtual learning environments' personalization and engagement. This research addresses these issues by developing a web application designed to enhance student engagement and learning efficiency. The system has gamified collaboration features, video chapter segmentation, and personalized video recommendation system. The methodology comprises models for generating chapter titles and for precise video transcription, and machine learning algorithms for tailored suggestions depending on user input. Interactive Questions and Answers modules and real-time synchronized video playback are included. The results demonstrate how the system's personalized content, interactive tests, and teamwork tools increase user engagement and comprehension. The efficacy of personalized material and real-time synchronization in enhancing learning results is discussed. This innovative approach offers a comprehensive solution to the challenges of online education, creating a more immersive and interactive learning experience. © 2024 IEEE.

关键词： Federated learning

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Authorizable Tripartite Entanglement Routing via 3-GHZ State in Quantum Networks

Authorizable Tripartite Entanglement Routing via 3-GHZ State...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Huang, Shao-Min Wei, Ching-Ting Zhan, Kai-Xu Le Touze, Juliette Chou Kuo, Jian-Jhih Wang, Chih-Yu National Chung Cheng University Dept. of Computer Science and Information Engineering Chiayi Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei City Taiwan

ISBN: (纸本)9798350351255

Traditional end-to-end entanglement typically operates between two parties. However, such a setup may fall short when three parties are involved. GHZ states, a multi-qubit entangled state, provide an approach to such a problem. A fusion node is first chosen, and then the paths from all end nodes to the fusion node are fused to create an entangled state between all parties. The selection of the fusion node becomes critical since it highly affects the success probability of the whole process. Thus, in this paper, we explore the promising scenario for multiple requests of authorizable tripartite teleportation and introduce a novel optimization problem to maximize the (expected) total profit for 3-GHZ requests. Via extensive simulation results, we show that our algorithm can outperform existing approaches significantly. © 2024 IEEE.

关键词： Quantum entanglement

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Frame Acceleration and Super Resolution for video Enhancement Using GAN 8

Frame Acceleration and Super Resolution for video Enhancemen...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Lokhande, Sharayu Maity, Ankush Lenka, Sourabh Kumar Pious, Roshan Choudhary, Vishal Pawar, Shilpa Army Institute of Technology Dept. of Computer Engineering Pune India Army Institute of Technology Dept. of Electronics & Telecommunication Pune India

ISBN: (纸本)9798350391770

Low-resolution (LR) videos are common in various applications, including surveillance and video conferencing, primarily due to bandwidth constraints or older recording technologies. This research introduces a novel approach for enhancing the quality of LR videos by leveraging Generative Adversarial Networks (GANs) equipped with MeanShift loss, perceptual loss, Total Variation (TV) Loss, and a modified VGG19 architecture. By processing each frame of an LR video through our model, we achieve significant improvements in visual quality, detail sharpness, and temporal consistency, resulting in high-resolution (HR) videos that are both visually pleasing and realistic. The conventional approach to video enhancement, particularly when employing deep learning models like GANs, involves processing high volumes of data, which can be computationally intensive and time-consuming. This challenge is compounded in real-time applications or environments lacking powerful graphical processing units (GPUs). Our research proposes a novel solution by extracting frames from low-resolution (LR) videos, enhancing each frame individually, and then recombining them into a high-resolution (HR) video. This method offers a significant reduction in computational requirements, making high-quality video enhancement accessible on less capable hardware and suitable for real-time processing. © 2024 IEEE.

关键词： Generative adversarial networks

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Development of Extraction Technique for Diagnosing Kidney Abnormalities by Using Ultrasound Images 8

Development of Extraction Technique for Diagnosing Kidney Ab...

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8th International Conference on information technology, information Systems and Electrical engineering, ICITISEE 2024

作者： Zain, Ruri Hartika Sumijan Defit, Sarjon Universitas Putra Indonesia Yptk Faculty of Computer Science Dept. Information Technology Padang Indonesia

ISBN: (纸本)9798350368970

Kidney disease is a health problem consisting of kidney failure, where it is caused by a complication of decreased kidney function. To prevent serious complications, kidney disorders must be diagnosed quickly and automatically. The aim of this study was to develop an extraction method to diagnose kidney abnormalities in ultrasound images from 102 patients. Researchers proposed the development of an extraction technique by using a combination of the Grey Level Co-Occurrence Matrix (GLCM), Scale Invariant Feature Transform (SIFT) method and the Canny method. The statistical-based GLCM feature extraction method used a pixel value matrix that had a certain score and forms the angle of the kidney image pattern. The research shows that the SIFT algorithm is effective for object recognition and it is robust to changes in rotation and scaling of kidney images. Canny is also known as optimal edge detection, localizing edge points and providing only one response for one edge of the image. Based on the tests, it is found that the process of detecting kidney abnormalities quickly and accurately. it increases the efficiency of the medical role in decision making. This automatic system analyses and identifies kidneys based on existing abnormalities with maximum accuracy such as cysts, kidney stones, cancer and tumours as abnormalities in the kidneys. In addition, the automated kidney diagnosis system will help radiologists and nephrologists in reducing inadequate nephrology problems and discrepancies. © 2024 IEEE.

关键词： Ultrasonic imaging

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Experimental Approach to Internal Security Threats for 5G-Advanced Core Networks 35

Experimental Approach to Internal Security Threats for 5G-Ad...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Park, Jaehyoung Kim, Jihye Woo, Seungchan Park, Kyungmin Kim, Jonghyun Lee, Jong-Hyouk Sejong University Dept. of Computer and Information Security & Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Dept. of Computer and Information Security Seoul Korea Republic of Sejong University Dept. of Computer and Information Security & Convergence Engineering for Metaverse Seoul Korea Republic of Electronics and Telecommunications Research Institute Daejeon Korea Republic of

ISBN: (纸本)9798350362244

As we embrace the dawn of the 5G era, the fusion of Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies has heralded a new epoch in network architecture. This provides indispensable capabilities and virtualized infrastructure to meet the burgeoning demands of modern networks. Yet, with each stride forward in mobile communication technology, security threats loom larger, casting a shadow over the very fabric of our networks. In this context, identifying and addressing these threats is crucial as it plays a key role in enhancing the security of a 5G-Advanced and a next 6G mobile communication technologies. Therefore, this paper undertakes an investigative journey to explore security threats introduced by SDN/NFV technologies in the 5G-Advanced core networks. Through our simulations, we unveil a need for fortified security technologies within the 5G-Advanced core networks, illuminating a path towards the creation of bespoke datasets tailored for the trends of 5G-Advanced security research. © 2024 IEEE.

关键词： 5G mobile communication systems

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