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International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Ananya Ganapathi Parikshith Sivakumar Divya K V Aditya Elango Hardik Gupta Dept. of Computer Science Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

The “ConfigMaster: An interactive solution for system management” is a simple utility written using Bash scripting. It is designed for Unix-like systems. The tool lets users easily configure system settings and do administrative tasks without having to remember complex commands. The tool minimizes user's work by automating tasks. The tool can be used even by users with very little technical knowledge, as it has a simple menu-based interface to manage things like network settings, software packages, and wireless connections directly from the terminal. By automating common tasks, the tool makes system management more efficient and accessible. By automating common tasks, the tool makes system management more efficient and accessible. It's very useful to simplify system configuration on Unix-like systems using scripting languages like Bash. “ConfigMaster” aims to offer a smooth user experience with the incorporation of core management principles from an operating system, such as disk scheduling, process synchronization, and memory management etc. Being flexible itself, this tool will bring further improvements to make effective responses to emerging user needs. The framework being flexible, it can be expanded to add new features to configure under different scenarios. By integrating essentials operating system operations, “ConfigMaster” enables users to efficiently perform system configurations along with promoting ease of use.

关键词： Wireless communication Productivity Knowledge engineering Software packages Operating systems Memory management User experience Hardware Synchronization Information technology

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Extractive Document Summarization with Advanced Deep Reinforcement Learning 6

Extractive Document Summarization with Advanced Deep Reinfor...

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6th International Conference on Contemporary computing and Informatics, IC3I 2023

作者： Chaitanya, Tekumudi Vivek Sai Surya Sindhu, Kolla Gnapika Ganesh, Bachu Natarajan, B. Elakkiya, R. Annamalai, R. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India BITS Pilani Department of Computer Science Dubai Campus Dubai345055 United Arab Emirates

ISBN: (纸本)9798350304480

Due to the exponential increase in the amount of information available on the internet, there has been an increasing interest in automatic text summarization in recent years. The goal of extractive text summarization is to generate a condensed version of a document while keeping its important points. It involves selecting the most relevant sentences from the document and arranging them in a coherent and concise manner. Using Deep Q-Networks (DQN), we provide a novel method for extracting text summarization in this research. In our suggested method, each phrase in the text is given a score depending on its importance to the summary, and the process of summarizing is seen as a sentence ranking problem. The DQN-based model is trained to learn the ranking function, where the reward signal is determined by the extent to which the resulting summary resembles the ground truth summary. We conduct experiments on the CNN/DailyMail dataset, which is a widely-accepted benchmark in this field, and compare our model with state-of-the-art extractive summarization systems and demonstrate that our approach outperforms them in terms of both automatic metrics and human evaluation. Our study highlights the potential of DQN-based models to significantly enhance the quality of extractive text summarization. Our findings suggest that our proposed approach provides a promising avenue for future research in the field of extractive text summarization. © 2023 IEEE.

关键词： BLEU Score DQN Extractive Text summarization RNN

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Quantum Error Correction for Kids

Quantum Error Correction for Kids

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Quantum computing and engineering (QCE), IEEE International Conference on

作者： Richard A. Wolf School of science and Engineering Irish Center for High-End Computing Galway Ireland

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

This extended abstract presents an intuitive gamified approach to one of the core concepts in quantum error correction: the stabiliser formalism. The game gradually builds up complexity and takes the players from classical repetition codes to Calderbank-Shor-Steane (CSS) codes. Through its lightweight mechanics, the game offers a glimpse into the notions of communication channel, noise and encoding as well as decoding. It is designed to be inclusive of a wide range of ages and abilities.

关键词： Surveys Codes Quantum computing Noise Games Receivers Encoding Error correction Decoding Complexity theory

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The Development of CNN-Based Food Scanning Model for Calorie Analysis: A Tool for Promoting Healthier Dietary Choices

The Development of CNN-Based Food Scanning Model for Calorie...

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Advancements in Smart, Secure and Intelligent computing (ASSIC), International Conference on

作者： Adarsh Kumar sahoo Nilamadhab Mishra School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India

The rising incidence of bad food patterns and accompanying health problems requires the creation of novel strategies to promote improved eating habits. This study paper describes the creation of a food scanning application for calorie analysis, which will be a useful tool for anyone looking to make informed dietary choices. To precisely estimate the calorie value of various food items, the application employs picture recognition technology, and a large food database. The paper describes the design and development process, which includes data gathering, image recognition algorithms, and application integration with existing nutritional datasets. Our research also analyzes the potential influence of such a tool on public health, emphasizing its role in raising awareness, facilitating self-monitoring, and supporting healthier eating choices. The findings show that technology could influence beneficial lifestyle choices and improve overall well-being.

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CricPredict: Resource-Aware Prediction of T20 Cricket Match 4

CricPredict: Resource-Aware Prediction of T20 Cricket Match

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4th International Conference on Electrical engineering and Computer science, ICECOS 2024

作者： Kumar, Ashish Hassan, Bilal Wasiq, Muhammad Farooq School of Electronic Engineering Computer Science Queen Mary University London United Kingdom School of Computing and Digital Media London Metropolitan University London United Kingdom Department of Creative Technologies Air University Given Islamabad Pakistan

ISBN: (纸本)9798350368253

One of the key problems in cricket is the increasing number of abandoned matches due to unusual circumstances. There is a total of three different formats in cricket e.g., Test, ODI and T20 international. Usually, the Duckworth-Lewis (D/L) method is used to decide the outcome of the match in Test and ODI cricket, resulting in favour of one team like completed matches. In contrast to the traditional D/L method, we tried to incorporate players' performance indicators into our proposed architecture despite the traditional D/L method which only includes the current state of the match and determines the outcome. To accomplish this task, we tried multiple different machine learning techniques e.g., Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naive-Bayes, Linear Regression and Polynomial Regression and a deep learning model to predict the outcome of the match. To train and validate our developed architecture, we crawled data from the Indian Premier League (IPL) for the completed matches. Our proposed architecture takes complete matches as input and for the second batter, it predicts outcome at intermediate stages of matches. Later, the performance of our proposed architecture is computed using different performance indicators e.g., accuracy, Mean squared error etc. In our opinion, our proposed resource-Aware prediction architecture is a unique contribution of its kind in the field. © 2024 IEEE.

关键词： Mean square error

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Enhancing ResNet Architectures with Bayesian Optimized Stochastic Configuration Networks for Lung X-Ray Image Classification

Enhancing ResNet Architectures with Bayesian Optimized Stoch...

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International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Hengren Xu Jinchuan Zheng Zhenwei Cao Zhihong Man School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Australia

ISBN: (数字)9798350366204

ISBN: (纸本)9798350366211

This paper introduces the ResNet-BOSCN architecture, which integrates Bayesian Optimized Stochastic Configuration Networks (SCNs) with traditional Residual Networks (ResNet) to tackle the challenges of lung X-ray image classification. Unlike conventional methods, ResNet-BOSCN employs Bayesian Optimization to dynamically optimize the network's hidden node count, effectively addressing the complexities inherent in medical imaging datasets. This optimization enables the architecture to adapt more precisely to varying data characteristics, significantly enhancing classification accuracy. ResNet-BOSCN achieves an accuracy of 98.81% in three-class lung X-ray image classification, marking a substantial improvement over the standard ResNet101’s accuracy of 97.62%.

关键词： Accuracy Lungs Stochastic processes Robustness Bayes methods X-ray imaging Optimization Standards Image classification Residual neural networks

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A Bitcoin Address Multi-Classification Mechanism Based on Bipartite Graph-Based Maximization Consensus

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Computer Modeling in engineering & sciences 2024年第4期139卷 783-800页

作者： Lejun Zhang Junjie Zhang Kentaroh Toyoda Yuan Liu Jing Qiu Zhihong Tian Ran Guo College of Information Engineering Yangzhou UniversityYangzhou225127China Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou510006China Research and Development Center for E-Learning Ministry of EducationBeijing100039China Institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A∗STAR)Singapore138632Singapore School of Physics and Materials Science Guangzhou UniversityGuangzhou510006China

Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges,gambling,marketplaces,and also scams such as high-yield investment *** the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model *** engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small *** this paper,we address the problem of identifying multiple classes of Bitcoin services,and for the poor classification of individual addresses that do not have significant features,we propose a Bitcoin address identification scheme based on joint multi-model prediction using the mapping relationship between addresses and *** innovation of the method is to(1)Extract as many valuable features as possible when an address is given to facilitate the multi-class service identification task.(2)Unlike the general supervised model approach,this paper proposes a joint prediction scheme for multiple learners based on address-entity mapping ***,after obtaining the overall features,the address classification and entity clustering tasks are performed separately,and the results are subjected to graph-basedmaximization *** final result ismade to baseline the individual address classification results while satisfying the constraint of having similarly behaving entities as far as *** testing and evaluating over 26,000 Bitcoin addresses,our feature extraction method captures more useful *** addition,the combined multi-learner model obtained results that exceeded the baseline classifier reaching an accuracy of 77.4%.

关键词： Bitcoin multi-service classification graph maximization consensus data security

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MuLAD: Multimodal Aggression Detection from Social Media Memes Exploiting Visual and Textual Features 27th

MuLAD: Multimodal Aggression Detection from Social Media Me...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Hasan, Md. Maruf Ahsan, Shawly Hoque, Mohammed Moshiul Dewan, M. Ali Akber Chittagong University of Engineering and Technology Chittagong4349 Bangladesh School of Computing and Information Systems Faculty of Science and Technology Athabasca University AthabascaABT9S 3A3 Canada

ISBN: (纸本)9783031781186

Aggression detection from memes is challenging due to their region-specific interpretation and multimodal nature. Detecting or classifying aggressive memes is complicated in low-resource languages (including Bengali) because benchmark datasets and primary language processing software are needed. This paper proposes an innovative meme classification technique that harnesses deep learning (DL) approaches to leverage memes’ visual and textual features in Bengali. Various DL frameworks, such as VGG16, VGG19, ResNet50, CNN, BiLSTM, and BiLSTM+CNN, extract visual and textual features from memes. A novel corpus named the Bengali Meme Dataset (AMemD) is also introduced, comprising a substantial amount of multimodal data, including text and image components. Experimental results on AMemD demonstrate the effectiveness of the proposed approach. The CNN combined with VGG16 obtained the highest f1-score of 0.738 among all multimodal techniques tested. This pioneering research offers valuable insights into the complex task of aggression detection from memes in Bengali and provides a foundation for future studies in this area. The dataset is available at https://***/Maruf089/Multimodal-Aggression-Detection. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Joint Microstrip Selection and Beamforming Design for MmWave Systems with Dynamic Metasurface Antennas 48

Joint Microstrip Selection and Beamforming Design for MmWave...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Huang, Wei Zhang, Haiyang Shlezinger, Nir Eldar, Yonina C. Hefei University of Technology School of Computing Science and Information Engineering Hefei China Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Ben-Gurion University of the Negev School of ECE Beer-Sheva Israel Weizmann Institute of Science Faculty of Math and CS Rehovot Israel

ISBN: (纸本)9781728163277

Dynamic metasurface antennas (DMAs) provide a new paradigm to realize large-scale antenna arrays for future wireless systems. In this paper, we study the downlink millimeter wave (mmWave) DMA systems with limited number of radio frequency (RF) chains. By using the specific DMA structure, an equivalent mmWave channel model with hybrid beamforming is first explicitly characterized. Based on that, we propose an effective joint microstrip selection and beamforming scheme to accommodate for the limited number of RF chains. A low-complexity digital beamforming solution with channel gain-based microstrip selection is developed, while the analog beamformer is obtained via a coordinate ascent method. The proposed scheme is numerically shown to approach the performance of DMAs without RF chain reduction, verifying the effectiveness of the proposed schemes. © 2023 IEEE.

关键词： Millimeter waves

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Enhanced Security Measures for Image Privacy: Encryption Perspectives

Enhanced Security Measures for Image Privacy: Encryption Per...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Omshith R Vemisetti Pavan Balaji Rayapudi Venkata Rahul Kumaran U Dept. of Computer Science & Engineering Amrita School of Computing Bengaluru India

A key technology in information security, picture encryption is intended to safeguard the integrity and confidentiality of digital photographs. Using a variety of cryptographic techniques and algorithms, the original image is transformed into an encrypted format throughout this process, making it more difficult for unauthorized users to view or understand the content. Secure communication, picture sharing, medical imaging, and many more fields requiring the protection of sensitive visual data find widespread use in image encryption. A key technology in information security, picture encryption is intended to safeguard the integrity and confidentiality of digital photographs. It also discusses the difficulties and potential paths for picture encryption, highlighting the rising demand for reliable, effective, and secure image encryption solutions in a world that is becoming more and more networked and data-driven. Advanced Encryption Standard (AES) is more secure than (Exclusive OR) XOR, Fernet.

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