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The Implementation of Octave-S in the Risk Management Measurement of information system in the Department of Communication, Informatics, and Statistics 4th

The Implementation of Octave-S in the Risk Management Measur...

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4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Sukardi, Oggsa Gaol, Ford Lumban Matsuo, Tokuro Master of Information System Management Binus Graduate Programs Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Binus Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

An information system is an important part in an organization to support business processes and to achieve its vision and mission. The information system nowadays has been one of the assets that ought to be protected by an organization. The Department of Communication, Informatics, and Statistics has the information system supporting its various operational activities. In order to protect the information system, OCTAVE-S method as the management method is used. It is expected that the OCTAVE-S method can manage the risks to the information system as the asset by specifying the possible risks and developing countermeasures and mitigation plans for each of the risks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Risk management

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An improved multi-attribute decision-making based network selection algorithm for heterogeneous vehicular network

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Frontiers of computer Science 2022年第3期16卷 211-213页

作者： Lei NIE Bo LIU Peng LI Heng HE Libing WU School of Computer Science and Technology Wuhan University of Science and TechnologyWuhan 430065China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430065China School of Cyber Science and Engineering and School of Computer Science Wuhan UniversityWuhan 430072China Shenzhen Research Institute of Wuhan University Shenzhen 518057China

1 Introduction With sharply rising quantity of urban vehicles over the past few decades,traffic jams and safety have gradually become outstanding *** recent years,Vehicular Ad hoc Network(VANET)is appeared and utilized to solve traffic related *** is a type of self-organized and open-structured network,and provides Vehicle-to-Everything(V2X)*** all kinds of applications in VANET rely on efficient data transmission and interaction[1-3].

关键词： network sharply utilized

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of engineering & technology 2023.

关键词： Machine learning

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Convolutions of String Data Structures: A Case Study of Finding Number of Palindrome Substrings in a String 5

Convolutions of String Data Structures: A Case Study of Find...

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5th International Conference on Advancement in Data Science, E-Learning and information systems, ICADEIS 2023

作者： Kumar, Kamal Jain, Anuj Kumar Tiwari, Raj Gaurang Jain, Nitin Witarsyah, Deden Misra, Alok National Institute of Technology Uttarakhand Dept. of Computer Science and Engineering Uttarakhand Srinagar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Manav Rachna International Institute of Research and Studies Career Development Centre Haryana Faridabad India Telkom University Information System Departement Bandung Indonesia

ISBN: (纸本)9798350303414

In computer science, substring search or string Matching is a vulnerable problem when text resources are very large. Productivity of diverse scraping applications depend on the effectiveness of searching algorithms. Palindrome string finding is one of these problems which has its use in many applications. The problem is about finding the number of palindrome substrings within a string. This paper discusses a naive and dynamic programming-based algorithm for finding several palindrome strings. The time complexity of algorithm has also been analyzed and an effort has been made to improve it. © 2023 IEEE.

关键词： Dynamic programming

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A Development of 5G Wireless Sensor Network using Man Design 4

A Development of 5G Wireless Sensor Network using Man Design

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

作者： Vennila, C. Almusawi, Muntather Kumar, K. Sriram Priya, B. Rawat, Vidhi Amirthayogam, G. Prince Shri Venkateshwara Padmavathy Engineering College Department of S&h TN India The Islamic University of Babylon College of Technical Engineering Department of Computers Techniques Engineering Babylon Iraq Karpagam Institute of Technology Department of Information Technology TN India Nehru Institute of Engineering and Technology Department of Computer Science and Business System Tamil Nadu T.M.Palayam India Ies College of Technology Department of Electrical & Electronics Engg Madhya Pradesh Bhopal India Department of Information Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350360165

This article investigates the key drivers influencing the design of the forthcoming Metropolitan Area Network (MAN), focusing on the integration of two pivotal elements: Cloud Radio Access Network (C-RAN) for 5G implementation and the deployment of edge computing. As we delve into these aspects, the article systematically uncovers the crucial architectural components essential for effectively addressing the challenges inherent in implementing C-RAN and edge computing. Through this strategic approach, the objective is to ensure a cost-effective solution that aligns with the specific requirements of these applications. The article aims to provide insights into the symbiotic relationship between CRAN and 5G, emphasizing their collaborative role in enhancing network efficiency. Simultaneously, it underscores the significance of edge computing, highlighting its potential to optimize data processing and reduce latency within the evolving landscape of metropolitan networks. This comprehensive exploration contributes to a nuanced understanding of the future MAN design, grounded in innovative solutions and considerations for seamless integration. © 2024 IEEE.

关键词： Radio access networks

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Deep Learning Network for Vision-Based UAV Recognition

Deep Learning Network for Vision-Based UAV Recognition

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2023 IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023

作者： Prabhakar, Telagarapu Almutairi, Maryam Almutairi, Hissah Vasamsetti, Subrahmanyam Rao, M. V. Raghavendra Kunda, Aruna GMR Institute of Technology Vizianagaram District Andhra Pradesh Rajam532127 India College of Sciences and Humanities in Hawtat Bani Tamim Department of Information System Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia College of Computer and Information Technology Department of IS and IT Jazan University Jazan Saudi Arabia Godavari Institute of Engineering & Technology Department of Automobile Engineering Rajahmundry India

ISBN: (纸本)9781665462631

Unmanned aerial vehicles (UAVs) could be used carelessly or intentionally, which poses a serious risk to aviation safety. This makes automated UAV detection and tracking a crucial component of aerial security systems. Radar, radio frequency, and visible- and thermal-infrared imaging are often used technologies for UAV detection. Deep neural networks (DNNs) for the image-based object recognition have recently made advancements that make it possible to leverage For this detecting and tracking challenge, visual data. Through the encoder-decoder structure network, the suggested technique first estimates the distribution line area. The interference is eliminated using sampling clustering and image processing operations. Finally, based on the discovered distribution line, the UAV direction of tracking of the power line is determined. The approach can achieve a frame inspection speed of over 78 ms, a heading error of deviation range of (-1.53°, 1.36°), and a tracking rate of almost 99%. The results of the network and inspection technique dataset test demonstrate that the approach presented in this research may be used to check UAV distribution lines efficiently, swiftly, and accurately. © 2023 IEEE.

关键词： Aircraft detection

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Empowering Deaf Children with Sinhala Sign Language, Emotion Detection, and Sound Recognition

Empowering Deaf Children with Sinhala Sign Language, Emotion...

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Advancements in Computing (ICAC), International Conference on

作者： W.H.K Fernando P.L.D.N Perera M.I.N Fernando P.T.E.W Gunasekara Harinda Fernando Rivoni De Zoysa Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Android software for translating gestures in Sinhala Sign Language (SSL), and a mobile app for emotion recognition and text-tospeech in Sinhala. By promptly alerting caregivers to potential dangers, the sound recognition technology secures the security of deaf children at home, providing an invaluable layer of security. The Android software bridges the communication gap and improves family interactions by translating SSL gestures captured by the device's camera into textual representations. This promotes successful communication between deaf children and their parents. Convolutional Neural Networks (CNNs) are used in the mobile application to detect and understand emotions based on facial expressions. This enables non-verbal youngsters to communicate successfully through Sinhala textto-speech output with adaptive tone modulation. This research aims to build a caring and inclusive atmosphere, enabling increased independence and enhanced communication skills in deaf children by combining these advances. The suggested solutions could significantly improve the lives of deaf kids, providing them with opportunities for better learning, social interaction, and emotional health.

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Health Insurance Cost Prediction using Machine Learning 3

Health Insurance Cost Prediction using Machine Learning

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3rd International Conference for Emerging technology, INCET 2022

作者： Bhatia, Kashish Gill, Shabeg Singh Kamboj, Navneet Kumar, Manish Bhatia, Rajesh Kumar Punjabi University Department of Computer Science and Engineering Patiala India Indraprastha Institute of Information Technology Department of Computer Science and Engineering Delhi India Amazon Big Data Engineer Punjab Engineering College Department of Computer Science and Engineering Chandigarh India

ISBN: (纸本)9781665494991

This paper represents a machine learning-based health insurance prediction system. Recently, many attempts have been made to solve this problem, as after Covid-19 pandemic, health insurance has become one of the most prominent areas of research. We have used the USA's medical cost personal dataset from kaggle, having 1338 entries. Features in the dataset that are used for the prediction of insurance cost include: Age, Gender, BMI, Smoking Habit, number of children etc. We used linear regression and also determined the relation between price and these features. We trained the system using a 70-30 split and achieved an accuracy of 81.3%. © 2022 IEEE.

关键词： Health insurance

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Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis

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computer systems Science & engineering 2023年第10期47卷 1249-1266页

作者： Abdelwahed Motwakel Najm Alotaibi Eatedal Alabdulkreem Hussain Alshahrani MohamedAhmed Elfaki Mohamed K Nour Radwa Marzouk Mahmoud Othman Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies RiyadhSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)*** SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock *** researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and *** to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie *** current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)*** presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible ***,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed *** Deep Belief Network(DBN)model is utilized to analyse and classify the ***,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the *** experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR *** comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%.

关键词： Corpus linguistics sentiment analysis natural language processing deep learning word embedding

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