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A Proposed Architecture for Local-Host and AWS with Multiagent System

Intelligent Automation & Soft Computing 2023年第6期36卷 2787-2802页

作者： Jaspreet Chawla Anil Kr Ahlawat Department of Computer Science&Engineering JSS Academy of Technical EducationNoidaAffiliated to AKTULucknow201301India Department of Computer Science&Engineering KIET Group of InstitutionsGhaziabadAffiliated to AKTULucknow201001India

Cloud computing has become one of the leading technologies in the world *** benefits of cloud computing affect end users *** are several cloud computing frameworks,and each has ways of monitoring and providing *** computing eliminates customer requirements such as expensive system configuration and massive infrastructure while improving dependability and *** the user’s perspective,cloud computing makes it easy to upload multiagents and operate on different web *** this paper,the authors used a restful web service and an agent system to discuss,deployments,and analysis of load performance parameters like memory use,cen-tral processing unit(CPU)utilization,network latency,etc.,both on localhost and an Amazon Web Service Elastic Cloud Computing(AWS-EC2)*** Java Agent Development Environment(JADE)tool has been used to propose an archi-tecture and conduct a comparative study on both local and remote *** is an open-source tool for maintaining applications on AWS *** focus of the study should be to reduce the complexity and time of load perfor-mance parameters by using an agent system on a cloud server instead of establish-ing a massive infrastructure on a local system,even for a small application.

关键词： Amazon web service jade local host rest web service

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Interactive Agent Foundation Model: A Meta-Learning Strategy 3

Interactive Agent Foundation Model: A Meta-Learning Strategy

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Dwivedi, Mani Dwivedi, Anuj Kr. KIET Group of Institutions Delhi-NCR Department of Computer Science and Engineering Ghaziabad India Galgotias College of Engineering and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798331523893

Artificial intelligence (AI) systems are evolving from static, task-specific models to dynamic, agent-based systems that perform well in a variety of scenarios. We present an Interactive Agent Foundation Model using a novel multi-task agent training methodology that includes many pretraining techniques such as language modelling, visual masked autoencoders, and next-action prediction. This framework's adaptability and versatility have been shown in the robotics, gaming AI, and healthcare sectors, yielding results that are pertinent to the situation. Effective multimodal and multitask learning is made possible by utilizing a variety of data sources, such as textual information, gaming data, robotics sequences, and large-scale video datasets. Our method offers a viable way forward for creating adaptable, proactive, multimodal systems. © 2025 IEEE.

关键词： Robot learning

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Optimizing Artificial Neural Networks Trough Weight Adjustments 28th

Optimizing Artificial Neural Networks Trough Weight Adjustme...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Akber, Syed Muhammad Abrar Szczesna, Agnieszka Kazmi, Sadia Nishat Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Longer training times pose a significant challenge in artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative to reduce training times in ANNs to enhance the computational efficiency. The initialization of the weights between the layers in ANN plays a vital role in reducing training times. Appropriate weight initialization can help the network converge faster during the training by providing an optimum starting point for the network. Therefore, weight initialization techniques are essential for efficient training of ANNs. This paper revisits and implements different popular weight initialization techniques in ANNs and analyzes their impact on training time. Specifically, this paper implements Gaussian-based, Kaming-based, and Xavier-based weight initiation atop a popular DNN-based network. The experiments are conducted by employing a well-known dataset. The results show that the scenario when no weight initiation is applied consumed the highest training time, whereas different weight initiation techniques contribute in reducing the training times for the network. © 2024 The Authors.

关键词： Deep neural networks

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Preface to the 10th Anniversary Issue: Journal of Reliable Intelligent Environments

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Journal of Reliable Intelligent Environments 2024年第3期10卷 211-213页

作者： Augusto, Juan C. Coronato, Antonio Research Group on Development of Intelligent Environments Department of Computer Science Middlesex University London United Kingdom Università Giustino Fortunato Benevento Italy

A decade ago we started this technical journey to open a forum focused on the reliability of so-called Intelligent Environments. Now we organized an Anniversary Issue to celebrate the achievement of our community contributing to the scientific understanding and the innovation of this field. The content in this issue includes articles which project the views of some of our esteemed Editorial Board members. In this Preface note we consider these contributions and also reflect on the wider field and how it has changed since our first issue as well as providing an outlook of the area. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

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Augmenting IoT Intrusion Detection System Performance Using Deep Neural Network

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computers, Materials & Continua 2023年第1期74卷 1351-1374页

作者： Nasir Sayed Muhammad Shoaib Waqas Ahmed Sultan Noman Qasem Abdullah M.Albarrak Faisal Saeed Department of Computer Science Islamia College PeshawarPeshawar25120Pakistan Department of Computer Science CECOS University of IT and Emerging SciencesPeshawar25000Pakistan Department of Electrical Engineering HITEC University TaxilaTaxila47080Pakistan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK

Due to their low power consumption and limited computing power,Internet of Things(IoT)devices are difficult to ***,the rapid growth of IoT devices in homes increases the risk of *** detection systems(IDS)are commonly employed to prevent *** systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate *** have been made in the past to detect new attacks using machine learning and deep learning techniques,however,these efforts have been *** this paper,we propose two deep learning models to automatically detect various types of intrusion attacks in IoT ***,we experimentally evaluate the use of two Convolutional Neural Networks(CNN)to detect nine distinct types of attacks listed in the NF-UNSW-NB15-v2 *** accomplish this goal,the network stream data were initially converted to twodimensional images,which were then used to train the neural network *** also propose two baseline models to demonstrate the performance of the proposed ***,both models achieve high accuracy in detecting the majority of these nine attacks.

关键词： Internet of things intrusion detection system deep learning convolutional neural network supervised learning

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NR-Router+: Enhanced Non-Regular Electrode Routing With Optimal Pin Selection for Electrowetting-on-Dielectric Chips

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2024年第9期43卷 2606-2619页

作者： Pan, Youlin Liu, Genggeng Huang, Xing Li, Zipeng Huang, Hsin-Chuan Liang, Chi-Chun Wang, Qining Kim, Chang-Jin Ho, Tsung-Yi Northwestern Polytechnical University School of Computer Science Xi'an710072 China Fuzhou University College of Computer and Data Science Fuzhou350116 China Apple Inc. Silicon Engineering Group CupertinoCA95014 United States National Tsing Hua University Department of Computer Science Hsinchu300044 Taiwan University of California at Los Angeles Mechanical and Aerospace Engineering Department Los AngelesCA90095 United States The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong Hong Kong

With the advances in microfluidics, electrowetting-on-dielectric (EWOD) chips have widely been applied to various biological and chemical laboratory protocols. Glass-based EWOD chips with nonregular electrodes are proposed, which allow more reliable droplet operations and facilitate the integration of optical sensors for many biochemical applications. Furthermore, nonregular electrode designs are utilized in EWOD chips, e.g., interdigitated electrodes for more reliable droplet manipulation, custom shaped electrodes for specific applications like concentric heating, etc. However, due to the technical challenges of fabricating multilayer interconnection on the glass substrate, e.g., unreliable process and high cost, both control electrodes and wires are fabricated with a single-layer configuration, which poses significant challenges to pin selection for nonregular electrodes. In this article, we propose a minimum-cost flow-based routing algorithm called NR-Router+ that features efficient and robust routing for single-layer EWOD chips with nonregular electrodes. To the best of our knowledge, this is the first work that overcomes the aforementioned challenges. We construct a minimum-cost flow algorithm to generate optimal routing paths followed by a light-weight model to handle flow capacity. A grid reduction strategy is proposed to reduce the computational overhead. Additionally, a flow collocation algorithm based on integer linear programming is presented to efficiently prevent wire overlapping. Experimental results show that NR-Router+ achieves 100% routability while minimizing wirelength with shorter run time. Moreover, NR-Router+ can generate mask files feasible for manufacturing via adjustments of design parameters, thus demonstrating its robustness and efficiency. © 1982-2012 IEEE.

关键词： Electrodes

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Robust Interactive Method for Hand Gestures Recognition Using Machine Learning

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computers, Materials & Continua 2022年第7期72卷 577-595页

作者： Amal Abdullah Mohammed Alteaimi Mohamed Tahar Ben Othman Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia BIND Research Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia

The Hand Gestures Recognition(HGR)System can be employed to facilitate communication between humans and computers instead of using special input and output *** devices may complicate communication with computers especially for people with *** gestures can be defined as a natural human-to-human communication method,which also can be used in human-computer *** researchers developed various techniques and methods that aimed to understand and recognize specific hand gestures by employing one or two machine learning algorithms with a reasonable *** aims to develop a powerful hand gesture recognition model with a 100%recognition *** proposed an ensemble classification model that combines the most powerful machine learning classifiers to obtain diversity and improve *** majority voting method was used to aggregate accuracies produced by each classifier and get the final classification *** model was trained using a self-constructed dataset containing 1600 images of ten different hand *** employing of canny’s edge detector and histogram of oriented gradient method was a great combination with the ensemble classifier and the recognition *** experimental results had shown the robustness of our proposed *** Regression and Support Vector Machine have achieved 100%*** developed model was validated using two public datasets,and the findings have proved that our model outperformed other compared studies.

关键词： Hand gesture recognition canny edge detector histogram of oriented gradient ensemble classifier majority voting

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An IoT-Based Approach to Measure the Effectiveness of Traditionally Prepared Compost in Indian Villages 1

An IoT-Based Approach to Measure the Effectiveness of Tradit...

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

作者： Bhardwaj, Manish Singh, Shweta Tripathi, Arun Kumar Ujjawal Goel, Sparsh Kumar, Ankit KIET Group of Institutions Department of Computer Science and Information Technology Delhi-NCR region Ghaziabad India KIET Group of Institutions Department of Computer Applications Delhi-NCR region Ghaziabad India

ISBN: (纸本)9798350353648

The Smart Compost Monitoring system helps to monitor and check the compost made by the amateur or low knowledgeable farmers and enthusiasts and an ideal ratio achievement is the subject of the current invention, The innovation is built on using several sensors to monitor and track record for the required amount of nutrition as well as the compulsory elements for acquiring an ideal compost the invention is not only limited to the Rural Areas it can be deployed to the Urban areas as well. The suggested technology will use a special machine learning algorithm to take the readings from the compost and compare it with the previously fetched ideal ratios and provide the difference that is to be then fulfilled by the farmer. Every crop with different requirements will have selected predefined ratios to be reached and monitored and different prerequisites will be achieved before fully deploying the system. Furthermore, the paper can be a precise assessment of crucial parameters such as the carbon-tonitrogen (C/N) ratio and pH levels, ensuring accuracy in composting endeavours. The proposed architecture not only promises immediate assistance to those in need of natural compost but also eliminates the necessity for users to meticulously maintain nutritional levels during the composting process. By alerting users of any incompatible manure with their intended crops and confirming when optimal levels are achieved, the system offers comprehensive support throughout the composting journey. IoT enables us to have a Arduino unit directly installed in soil range of the crop land and by using the combined the range definitions of different sensors we are able to record the metrics of the sensors and then compare those with the predefined ones. © 2024 IEEE.

关键词： Patents and inventions

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Preserving Information Integrity: Analyzing the Impact of Deepfake Videos on Social Media Trust and Security

Preserving Information Integrity: Analyzing the Impact of De...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Sheikh, Mohammed Firdos Alam Bhuyan, Ajatray Swagat Dhiman, Ankita Sharma, Chandni Diya Joshi, Mayurika Ritu Department of Computer Science & Engineering Poornima University Jaipur India Department of Computer Science & Engineering Chandigarh University Punjab India Ambala Haryana Mullana India Department of Computer Science & Engineering Graphic Era Hill University Haldwani India Department of Computer Science & Engineering Chandigarh College of Engineering Chandigarh Group of Colleges Jhanjeri140307 India

ISBN: (纸本)9798350374933

The proliferation of deepfake videos on social media has raised huge issues about disinformation, identity manipulation, and fraud. Advanced AI techniques now enable the creation of pretty convincing fake films, posing threats to character and countrywide security, eroding consider in digital media, and undermining online discourse. This research paper aims to develop a strong deepfake detection set of rules that leverages superior laptop vision and device getting to know strategies to accurately pick out manipulated films on social media. We will look at the unfold of deepfakes throughout social media platforms, examine their effect on on line discourse, and evaluate the effectiveness of our detection set of rules on numerous platforms. Furthermore, we will provide insights and recommendations for social media organizations, policymakers, and users to mitigate the dangers associated with deepfakes. Our last intention is to make contributions to a safer and greater honest on line surroundings with the aid of combating the spread of deepfakes and disinformation. The study will include a comprehensive literature evaluation on deepfake detection and social media vulnerabilities, experiments and analyses on a massive dataset of deepfake and real motion pictures, visualizations and information illustrating the spread and effect of deepfakes, and an assessment of our detection algorithm’s performance the use of metrics such as accuracy, precision, consider, and F1-score. Relevant legal guidelines, rules, and ethical guidelines related to deepfakes and social media may also be cited. © 2024 IEEE.

关键词： artificial intelligence computer vision deepfake detection identity manipulation social media

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Estimating Risk-aware Flexibility Areas for Electric Vehicle Charging Pools via AC Stochastic Optimal Power Flow

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1247-1256页

作者： Juan S.Giraldo Nataly Bañol Arias Pedro P.Vergara Maria Vlasiou Gerwin Hoogsteen Johann L.Hurink Energy Transition Studies Group Netherlands Organisation for Applied Scientific Research(TNO)Amsterdam1043 NTThe Netherlands Department of Electrical Engineering Mathematics and Computer ScienceUniversity of TwenteEnschede7522 NBThe Netherlands Intelligent Electrical Power Grids Group Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft2628 CDThe Netherlands

This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.

关键词： Electric vehicle flexibility management stochastic optimal power flow(SOPF) risk awareness compensation mechanism

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