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Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

computer systems science & Engineering 2023年第5期45卷 1199-1210页

作者： Himanshu Sharma karthikeyan Rajagopal G.Gugapriya Rajneesh Pareek Arun Kumar HayaMesfer Alshahrani Mohamed K.Nour Hany Mahgoub Mohamed Mousa Anwer Mustafa Hilal Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia School of Electronics Engineering Vellore Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Electrical Engineering Department Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Multicarrier Waveform(MCW)has several advantages and plays a very important role in cellular *** generation(5G)MCW such as Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC)are thought to be important in 5G *** Peak to Average Power Ratio(PAPR)is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user *** paper presents a novel Divergence Selective Mapping(DSLM)and Divergence Partial Transmission Sequence(D-PTS)for 5G *** is seen that the proposed D-SLM and PTS lower PAPR with low computational *** work highlighted a combination of multi-data block partial transmit schemes along with tone *** this,an overlapping factor is used to determine the number of data blocks for every ***,considering only those data blocks that have minimum signal power,the use of DSLM and DPTS are required to eliminate the segment’s *** results reveal that the suggested hybrid technique proves to be better than the conventional PTS ***,the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing(OFDM)waveform.

关键词： 5G PAPR D-SLM D-PTS

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A Novel Cryptocurrency Prediction Method Using Optimum CNN

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computers, Materials & Continua 2022年第4期71卷 1051-1063页

作者： Syed H.Hasan Syeda Huyam Hasan Mohammed Salih Ahmed Syed Hamid Hasan Iowa State University AmesUSA University of Texas at Arlington USA Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

In recent years,cryptocurrency has become gradually more significant in economic regions *** cryptocurrencies,records are stored using a cryptographic *** main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social *** is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media ***,this work focuses on extracting Tweets and gathering data from different sources to classify them into positive,negative,and neutral categories,and further examining the correlations between cryptocurrency movements and Tweet *** paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction;this method is used to predict the prices of four cryptocurrencies,namely,Litecoin,Monero,Bitcoin,and *** results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%.The method is validated by comparison with existing methods using visualization tools.

关键词： Cryptocurrency litecoin monero bitcoin ethereum twitter optimal CNN price prediction sentiment analysis

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Effects of the Attunement of an Attack Target by Whispering in AIWolf 14

Effects of the Attunement of an Attack Target by Whispering ...

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14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Murakami, Tomohiro Nakao, Nozomi Miyake, Hikaru Murata, Hayate Amano, Itsuki Kojima, Taisei Ando, Keisuke Ito, Nobuhiro Aichi Institute of Technology Graduate School of Business Administration and Computer Science Toyota Japan Aichi Institute of Technology Department of Information Science Toyota Japan Aichi Institute of Technology Faculty of Information Science Toyota Japan

ISBN: (纸本)9798350324228

Recently, research on AIWolf, which is artificial intelligence that plays the Werewolf game, has attracted much attention. Werewolves in the Werewolf game should cooperate using 'whispers;' which are conversations among werewolves only. However, whispers have not been used effectively in the AIWolf Competition and little research has been conducted on this topic. Therefore, the purpose of this study is to clarify the effectiveness of strategies that use whispers in AIWolf. A wide variety of strategies use whispers, but we focus on unifying attack targets, which was shown to improve the winning rate in previous studies. In the strategy of unifying attack targets, the strategy of the guiding agents is important. Therefore, we used 13 AIWolf Competition finalists with a wide variety of strategies and added statements of whom to attack in whispers to each finalist as a guide for whom to attack. Because there are three werewolf competitions in the AIWolf Competition setting, we created two agents to be attuned to the attack target of one of the guiding agents. In an experiment, we used these agents in the same setting as in the AIWolf Competition, and analyzed the differences between when the attack targets were unified and when they were not. The results showed that when the werewolves were a combination of two attuning agents and one guiding agent, the werewolves' win rate increased by an average of 2.3 percentage points. We also found that attuning to the agent with a high winning rate or high success rate in attacks improved the winning rate. These results indicate that attuning only the attack targets of agents with high winning rates and high success rates in attacks led to higher winning rates. © 2023 IEEE.

关键词： Artificial intelligence

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eRock at Qur’an QA 2022: Contemporary Deep Neural Networks for Qur’an based Reading Comprehension Question Answers 5

eRock at Qur’an QA 2022: Contemporary Deep Neural Networks ...

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5th Workshop Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, OSACT 2022

作者： Aftab, Esha Malik, Muhammad Kamran Department of Computer Science Department of Information Technology Faculty of Computing and Information Technology University of the Punjab Lahore Pakistan

ISBN: (纸本)9791095546757

Question Answering (QA) has enticed the interest of NLP community in recent years. NLP enthusiasts are engineering new Models and fine-tuning the existing ones that can give out answers for the posed questions. The deep neural network models are found to perform exceptionally on QA tasks, but these models are also data intensive. For instance, BERT has outperformed many of its contemporary contenders on SQuAD dataset. In this work, we attempt at solving the closed domain reading comprehension Question Answering task on QRCD (Qur’anic Reading Comprehension Dataset) to extract an answer span from the provided passage, using BERT as a baseline model. We improved the model’s output by applying regularization techniques like weight-decay and data augmentation. Using different strategies we had 59% and 31% partial Reciprocal Ranking (pRR) on development and testing data splits respectively. © European Language Resources Association (ELRA).

关键词： Natural language processing systems

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The Correlation Between Architecture Smells, Package Stability and Reusability: A Case Study 4

The Correlation Between Architecture Smells, Package Stabili...

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4th IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2024

作者： Benidris, Mrwan Elfallah, Ehab A. Omar Cheema, Marwa Aslam Alsma, Mohammed Salah Addin Kadiki, Tareq Ziad Elbarsha, Abdelfattah University of Benghazi Faculty of Information Technology Dep. of Computer Science Libya Libyan International Medical University Faculty of Information Technology Dept. of Software Engineering Libya University of Benghazi Faculty of Public Health Health Informatics Department Libya

ISBN: (纸本)9798350372632

the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. Architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-depth research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic Dependency and Unstable Dependency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable Dependency and reusability. Finally, we found a slight negative correlation between package stability and reusability. © 2024 IEEE.

关键词： Reusability

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Secure Private Data Storage and File Sharing Using Homomorphic and Hybrid Hash-Based Cryptographic Technique in Cloud

Secure Private Data Storage and File Sharing Using Homomorph...

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International Conference on Computing and Machine Learning, CML 2024

作者： Senthil, G.A. Prabha, R. Monica, K.M. Priya, R. Mohana Kanna, R. Rajesh Department of Information Technology Agni College of Technology Chennai India Department of Electronics and Communication Engineering Sri SaiRam Institute of Technology Chennai India Department of Computer Science and Engineering Vellore Institute of Technology Chennai Campus Chennai India Salem India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Campus Chennai India

ISBN: (纸本)9789819765874

Data is a crucial asset in any business, and for some businesses, it ranks among the most valuable. More and more businesses want to keep their data on the cloud and securely and efficiently distribute it among their authorized staff. Data duplication across numerous local devices is one factor in the enormous amount of data that is expanding daily. Both databases and data are made available on a large scale through the Cloud. Storage infrastructure is employed in many different locations. Security concerns have prevented a broad adoption of the cloud computing architecture. This is because of the extensive use of the internet throughout the world;advancements in cryptography have become vital in addressing some of these security issues. Two-phase algorithms have been introduced for a protocol for safe data storage. The hybrid technique that has been presented seeks to boost the power of cloud storage by decreasing computation time and ciphertext size. In this project, users may store all sorts of files, establish an effective directory structure, and navigate it in a way that is remarkably comparable to any conventional Operating system, all in a cloud area. The system also demonstrates a method for secure sharing of personal digital content. Users may transfer files via various methods, including links and QR codes, all inside an easy-to-use single-page Angular UI, with enhanced security provided by AWS services. Our solution can offer some extra features like making lightweight sticky notes and sharing folders utilising a Nodejs server and a MongoDB in addition to these basic functions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud storage

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A Mutual Authentication and Cross Verification Protocol for Securing Internet-of-Drones (IoD)

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computers, Materials & Continua 2022年第9期72卷 5845-5869页

作者： Saeed Ullah Jan Irshad Ahmed Abbasi Fahad Algarni Department of Computer Science&IT University of MalakandChakadara18800Pakistan Faculty of Science&Arts Belqarn Department of Computer ScienceUniversity of BishaSabtul Alaya 61985Saudi Arabia Faculty of Computing and Information Technology University of BishaBisha 67714Saudi Arabia

With the rapid miniaturization in sensor technology,Internet-ofDrones(IoD)has delighted researchers towards information transmission security among drones with the control station server(CSS).In IoD,the drone is different in shapes,sizes,characteristics,and *** can be classified on the purpose of its deployment,either in the civilian or military ***’s manufacturing,equipment installation,power supply,multi-rotor system,and embedded sensors are not issues for *** main thing is to utilize a drone for a complex and sensitive task using an infrastructureless/self-organization/resource-less network type called Flying Ad Hoc Network(FANET).Monitoring data transmission traffic,emergency and rescue operations,border surveillance,search and physical phenomenon sensing,and so on can be achieved by developing a robust mutual authentication and cross-verification scheme for IoD deployment civilian *** several protocols are available in the literature,they are either design issues or suffering from other vulnerabilities;still,no one claims with conviction about foolproof security ***,in this paper,the researchers highlighted the major deficits in prior protocols of the domain,i.e.,these protocols are either vulnerable to forgery,side channel,stolen-verifier attacks,or raised the outdated data transmission *** order to overcome these loopholes and provide a solution to the existing vulnerabilities,this paper proposed an improved and robust public key infrastructure(PKI)based authentication scheme for the IoD *** proposed protocol’s security analysis section has been conducted formally using BAN(Burrows-Abadi-Needham)logic,ProVerif2.03 simulation,and informally using discussion/pragmatic *** the performance analysis section of the paper has been assessed by considering storage,computation,and communication *** comparing the proposed protocol with prior works,it has been demonstrate

关键词： Cryptography authentication confidentiality reachability ZSP

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Security in the Age of Deepfakes: Detecting Manipulated Media with Neural Networks 1

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8th International Conference on information system Design and Intelligent Applications, ISDIA 2024

作者： Phatale, Utkarsh Limkar, Suresh Department of Computer Engineering AISSMS Institute of Information Technology Maharashtra Pune India Department of Computer Science and Engineering Central University of Jammu Jammu and Kashmir India

ISBN: (数字)9789819748921

ISBN: (纸本)9789819748914

The proliferation of deep fake technology presents a substantial peril to both individuals and society, underscoring the urgent requirement for the development of effective deep fake detection techniques. This study introduces a novel methodology that combines convolutional neural networks (CNNs) and deep convolutional generative adversarial networks (DCGANs) in order to improve the detection of deep fake videos. In this study, we present the findings of our research, which involved a comparative analysis of the CNN, recurrent neural network (RNN), and CNN-DCGAN models. The performance evaluation was conducted based on several metrics, including accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and Cohen’s Kappa. The accuracy of the DCGAN model reached 99.2%, establishing a benchmark for comparative analysis. Although the CNN and RNN models demonstrate satisfactory performance, the hybrid approach of CNN-DCGAN surpasses them in various metrics, thereby showcasing its potential for effective identification of deep fakes. This study emphasizes the efficacy of integrating convolutional neural networks (CNNs) for extracting features and deep convolutional generative adversarial networks (DCGANs) for generating synthetic data. This advancement holds promise for the development of more sophisticated and dependable deep fake detection systems, particularly in a time where the risk of manipulated media is escalating. © The Author(s).

关键词： Generative adversarial networks

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A Novel Cluster Analysis-Based Crop Dataset Recommendation Method in Precision Farming

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computer systems science & Engineering 2023年第9期46卷 3239-3260页

作者： K.R.Naveen Kumar Husam Lahza B.R.Sreenivasa Tawfeeq Shawly Ahmed A.Alsheikhy H.Arunkumar C.R.Nirmala Department of Computer Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArarSaudi Arabia

Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making *** agriculture uses datamining to advance agricultural *** farmers aren’t getting the most out of their land because they don’t use precision *** harvest crops without a well-planned recommendation *** crop production is calculated by combining environmental conditions and management behavior,yielding numerical and categorical *** existing research still needs to address data preprocessing and crop categorization/***,statistical analysis receives less attention,despite producing more accurate and valid *** study was conducted on a dataset about Karnataka state,India,with crops of eight parameters taken into account,namely the minimum amount of fertilizers required,such as nitrogen,phosphorus,potassium,and pH *** research considers rainfall,season,soil type,and temperature parameters to provide precise cultivation recommendations for high *** presented algorithm converts discrete numerals to factors first,then reduces ***,the algorithm generates six datasets,two fromCase-1(dataset withmany numeric variables),two from Case-2(dataset with many categorical variables),and one from Case-3(dataset with reduced factor variables).Finally,the algorithm outputs a class membership allocation based on an extended version of the K-means partitioning method with lambda *** presented work produces mixed-type datasets with precisely categorized crops by organizing data based on environmental conditions,soil nutrients,and ***,the prepared dataset solves the classification problem,leading to a model evaluation that selects the best dataset for precise crop prediction.

关键词： Data mining crop prediction k-prototypes k-means cluster machine learning

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Enhancing Video Anomaly Detection Using Spatio-Temporal Autoencoders and Convolutional LSTM Networks

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SN computer science 2024年第1期5卷 1-13页

作者： Almahadin, Ghayth Subburaj, Maheswari Hiari, Mohammad Sathasivam Singaram, Saranya Kolla, Bhanu Prakash Dadheech, Pankaj Vibhute, Amol D. Sengan, Sudhakar Department of Networks and Cybersecurity Faculty of Information Technology Al Ahliyya Amman University Country Amman Jordan School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai 600127 India Department of Networks and Cybersecurity Information Technology Al Ahliyya Amman University Amman Jordan Department Computing Technology School of Computing SRM Institute of Science and Technology Kattankulathur Campus Tamil Nadu Chennai 603203 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur 522302 India Department of Computer Science and Engineering Swami Keshvanand Institute of Technology Management and Gramothan (SKIT) Rajasthan Jaipur 302017 India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) MH Pune 411016 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India

Identifying suspicious activities or behaviors is essential in the domain of Anomaly Detection (AD). In crowded scenes, the presence of inter-object occlusions often complicates the detection of such behaviors. Therefore, developing a robust method capable of accurately detecting and locating anomalous activities within video sequences becomes crucial, especially in densely populated environments. This research initiative aims to address this challenge by proposing a novel approach focusing on AD behaviors in crowded settings. By leveraging a spatio-temporal method, the proposed approach harnesses the power of both spatial and temporal dimensions. This enables the method to effectively capture and analyze the intricate motion patterns and spatial information embedded within the continuous frames of video data. The objective is to create a comprehensive model that can efficiently detect and precisely locate anomalies within complex video sequences, specifically those featuring human crowds. The efficacy of the proposed model will be rigorously evaluated using a benchmark dataset encompassing diverse scenarios involving crowded environments. The dataset is designed to simulate real-world conditions where millions of video footage need to be continuously monitored in real time. The focus is on identifying anomalies, which might occur within short time frames, sometimes as brief as five minutes or even less. Given the challenges posed by the massive volume of data and the requirement for rapid AD, the research emphasizes the limitations of traditional Supervised Learning (SL) methods in this context. © 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Anomaly detection Autoencoders LSTM Machine learning Spatio-temporal features Suspicious activities

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