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Intelligent Algorithms for Computational Intelligence Systems (IACIS), International Conference on

作者： Rajya Lakshmi Gudivaka Raj Kumar Gudivaka Prashanth V Muntather Almusawi N. Naga Saranya Wipro Andhra Pradesh India Platinum Infosys Irving Texas USA Department of Electrical & Electronics Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Applications Saveetha College of Liberal Arts & Science SIMATS Chennai India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

In multi-robot space, conducting research is the critical task to perform flexible without presence of humans the multi-robots are used like landers and rovers for exploring the area which is unknown environment. The multi-robots face problems in exploring the area due improper planning and communication between the robots in specified paths. To solve the problem, Coordinated Multi-robot space Exploration Slime Mould Algorithm (CME-SMA) is proposed here. This integration includes a parallel communication protocol to enhance exploration efficiency and reduce computational complexity. The algorithm focuses on generating optimal collision-free paths in barrier-filled environments by first evaluating neighboring cells using deterministic CME for cost and utility values. SMA is then applied to refine the solutions further. The CME-SMA algorithm is validated through numerous simulations under various environmental conditions, demonstrating consistency in achieving expected outcomes such as exploration rate and time efficiency. The CME-SMA method explored the area is 98.79% with 0 failed run and execution time is 37.15 sec in map 1when compared with existing methods.

关键词： Protocols Costs Robot kinematics Computational modeling Disaster management Reconnaissance Robot sensing systems Space exploration Planning Faces

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Design of Digital Film and Television Projection System Based On Blockchain technology

Design of Digital Film and Television Projection System Base...

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Knowledge engineering and Communication Systems (ICKECS), International Conference on

作者： Xiaowen Liao Pandi Mao Daolian Xu School of Arts and Media Chongqing Metropolitan College of Science and Technology Chongqing China School of Electrical Engineering and Intelligent Manufacturing Chongqing Metropolitan College of Science and Technology Chongqing China College of Optoelectronic Engineering Chongqing University Chongqing China

Digital Rights Management (DRM) is widely used to protect digital content and has made a major contribution to protecting digital content. However, traditional DRM technology has shortcomings, such as centralized and opaque copyright and transaction information. In order to solve the security problem of centralized management of digital movies, a digital movie distribution system architecture based on blockchain technology is proposed. Provide authenticity and traceability of data and business logic in film trading, license certification, projection control and other fields. It is developed through the decentralized consensus mechanism and decentralized IPFS storage mechanism using smart contract scripts in the blockchain. Create efficient and accurate implementation and reduce manual intervention and authorization to ensure traffic control throughout the working day. Our mechanism allows rights holders to set prices for different content usage rules according to their own wishes. Customers have the flexibility to choose the usage rules they want to purchase. We have also developed a licensing framework based on blockchain, which is close to the current DRM standard and easy to promote.

关键词： Authorization Smart contracts Systems architecture Memory Licenses Copyright protection Traffic control

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Optimising Electric Charging Station Management for Green Transportation with Cloud-Based E-GraphSage Models

Optimising Electric Charging Station Management for Green Tr...

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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Shubhangi Shivaji Manjare V. K. Somasekhar Srinivas A. Thangam M. Udayakumar Jitendra Singh Soumya Mishra Department of Electrical Engineering DKTE Society's Textile and Engineering Institute Ichalakaranji India Department of Mathematics School of Liberal Arts and Sciences Mohan Babu University Tirupati India Department of Mathematics Pondicherry University-Community College Pondicherry University Community College Lawspet India Department of Mechanical Engineering University of Technology and Applied Sciences Salalah Oman Department of Computer Science and Engineering SRM Institute of Science and Technology Ghaziabad India Department of Electrical Engineering Quality Assurance Cell KIIT DU Bhubaneswar India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

The rapid expansion of EVs in recent years has caught the attention of markets, policymakers, the general public, and academia. Issues continue to arise despite the progress. The numerous complaints regarding the low battery life and long charging periods contribute to the problem of electric vehicle charging being an annoyance that discourages more people from purchasing these vehicles. The proposed procedure consists of three stages, which are preprocessing, feature extraction, and training the model. To ensure that the input data can be loaded into the developed model more effectively, preprocessing is an essential step. We begin by extracting three types of charging station features-geographic, traffic, and area-in order to address the data sparsity challenge. We used E-GraphSAGE to train the model. This cutting-edge method outperforms both AdaBoost and Random Forest in terms of average accuracy, coming in at 93.55%.

关键词： Training Accuracy Sensitivity Computational modeling Charging stations Feature extraction Electric vehicle charging Data models Data mining Load modeling

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An Enhanced Review Analysis of Security Issues Involved in Drones used with IOT technology and its Measures to Avoid Attacks

An Enhanced Review Analysis of Security Issues Involved in D...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Rishu Chabra Krishna Kant Dixit Devendra Singh G.Uday Kishore Kassem Al-Attabi G. Thiyagarajan Centre of Research Impact and Outreach Chitkara University Rajpura Punjab India Department of Electrical Engineering GLA University Mathura Department of Computer science & Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun India Department of CSE CMR College of Engineering & Technology The Islamic university Najaf Iraq School of Management-MBA S.A.College of Arts & Science Chennai Tamilnadu India

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

In the evolving landscape of the Internet of Drones (IoD), securing touchy and assignment-vital facts is paramount because of the wider assault floor and stringent electricity constraints specific to IoD networks. This paper introduces “IoD-Crypt,” a completely specific cryptographic framework engineered to address those traumatic situations by offering a strong, strength-inexperienced answer tailored for battery-confined IoD packages. Leveraging specialized precomputation strategies and self-certified cryptographic primitives, IoD-Crypt achieves notable computation and conversation efficiencies. By circumventing the rules of latest public key cryptography suites, the framework guarantees a immoderate stage of protection inside the random oracle model. Through complete implementations on everyday drone processors, which consist of eight-bit AVR and 32-bit ARM, IoD-Crypt demonstrates an remarkable reduce rate in energy consumption, as lots as forty eight times lower than conventional techniques. This massive development paves the manner for at ease, sustainable IoD operations, emphasizing the framework’s capability for big adoption and trying out.

关键词： Energy consumption Program processors Reviews Oral communication Public key cryptography Cryptography Internet of Things

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Development of Efficient Wireless Sensor Network for IoT Applications 3

Development of Efficient Wireless Sensor Network for IoT App...

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3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Shankar, S. Deepika, G. Devi, G. Ramesh, S. Srivastava, Suraj Kumar, S Sandeep Sri Krishna Arts and Science College Department of Electronics and Communication Systems Tamil Nadu Coimbatore641008 India St. Peter's Engineering College Department of Electronics and Communication Engineering Telangana Hyderabad500100 India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Dindigul624622 India Institute of Artificial Intelligence and Machine Learning Saveetha University Depattment of Computational Intelligence Tamil Nadu Chennai602105 India I.K. Gujral Punjab Technical University Department of Computer Science and Engineering Mohali Campus-1 Punjab Sahibzada Ajit Singh Nagar160055 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522502 India

ISBN: (纸本)9798350322842

This research study provides an overview of the effort that went into developing reliable 'Wireless sensor networks' for IoT applications, including both theoretical study and practical testing. The report also includes the findings of an analysis of variance and regression analysis, which pinpoint the significance of such aspects as network architecture, traffic load, and ambient conditions on the performance of Wireless Sensor Network (WSN). Finally, study provides a discussion on the future research directions, as well as the design and implementation of a Wireless Sensor Network (WSN) for Internet of Things (IoT) applications. © 2023 IEEE.

关键词： Electric power utilization

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Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression

arXiv

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arXiv 2023年

作者： Burakhan Koyuncu, A. Jia, Panqi Boev, Atanas Alshina, Elena Steinbach, Eckehard The Technical University of Munich School of Computation Information and Technology Department of Computer Engineering Media Technology Munich80333 Germany The Friedrich-Alexander University Department of Electrical-Electronic-Communication Engineering Multimedia Communications and Signal Processing Erlangen91058 Germany The Huawei Munich Research Center Munich80992 Germany

Entropy estimation is essential for the performance of learned image compression. It has been demonstrated that a transformer-based entropy model is of critical importance for achieving a high compression ratio, however, at the expense of a significant computational effort. In this work, we introduce the Efficient Contextformer (eContextformer) - a computationally efficient transformer-based autoregressive context model for learned image compression. The eContextformer efficiently fuses the patch-wise, checkered, and channel-wise grouping techniques for parallel context modeling, and introduces a shifted window spatio-channel attention mechanism. We explore better training strategies and architectural designs and introduce additional complexity optimizations. During decoding, the proposed optimization techniques dynamically scale the attention span and cache the previous attention computations, drastically reducing the model and runtime complexity. Compared to the non-parallel approach, our proposal has ∼145x lower model complexity and ∼210x faster decoding speed, and achieves higher average bit savings on Kodak, CLIC2020, and Tecnick datasets. Additionally, the low complexity of our context model enables online rate-distortion algorithms, which further improve the compression performance. We achieve up to 17% bitrate savings over the intra coding of Versatile Video Coding (VVC) Test Model (VTM) 16.2 and surpass various learning-based compression models. © 2023, CC BY-NC-ND.

关键词： Image compression

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The Ohio Child Speech Corpus

SSRN

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SSRN 2024年

作者： Wagner, Laura Alghowinhem, Sharifa Alwan, Abeer Bowdrie, Kristina Breazeal, Cynthia Clopper, Cynthia G. Fosler-Lussier, Eric Jamsek, Izabela A. Lander, Devan Ramnath, Rajiv Ross, Jory Department of Psychology The Ohio State University United States MIT Media Lab Massachusetts Institute of Technology United States Department of Electrical and Computer Engineering UCLA United States Department of Speech and Hearing Science The Ohio State University United States Department of Linguistics The Ohio State University United States Department of Computer Science and Engineering The Ohio State University United States

This paper reports on the creation of a new corpus of children’s speech, the Ohio Child Speech Corpus, which is publicly available on the Talkbank-CHILDES website. The audio corpus contains speech samples from 303 children ranging in age from 4 – 9 years old, all of whom participated in a seven-task elicitation protocol conducted in a science museum lab. An interactive social robot controlled by the researchers joined the sessions for approximately 60% of the children;analyses of one elicitation task (Narrative Pictures) found that the children spoke significantly more in the presence of the robot relative to its absence, but that the level of intensity of the robot’s involvement did not influence speech quantity. No effects of speech complexity (as measured by MLU) were found for the robot’s presence. In addition, the corpus was collected in the peri-pandemic era. Analyses of two school-readiness tasks, an Alphabet task and a Reading task, found that the children in this sample, who were primarily from highly educated families, were not negatively impacted in their pre-reading or reading abilities as a result of the disrupted schooling of the pandemic. These analyses demonstrate just two possible types of questions that this corpus could be used to investigate. © 2024, The Authors. All rights reserved.

关键词： Robots

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Optical Data Center Implementation within Data Center Networks Context Based on Mininet

Optical Data Center Implementation within Data Center Networ...

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electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Esraa Ali Abdulmahdi Adnan Hussein Ali Raed Khalid Ibrahim Ali Al-Askery Hayder Jasim Alhamdane Amal Ibrahim Mahmood Student at Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq Electrical Techniques Department Institute of Technology Middle Technical University Baghdad Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Department of Control and Automation Technical Engineering Electrical Engineering College Middle Technical University Baghdad Iraq College of Applied Arts Middle Technical University Baghdad Iraq Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

The technology of reconfigurable optical networks (RONs) is growing to be a promising solution to effectively cater to the rapidly increasing traffic generated by the digital society. Optical technology emerges as a viable alternative because to its capacity to offer a substantial bandwidth, little latency, and enhanced overall performance. Nevertheless, it is imperative to effectively manage the physical resources comprising a data center. This study provides an experimental demonstration of the RONs, which is enhanced by a control plane. The implementation relies on the monitoring of real-time network statistics. This enables the execution of various activities, including as network slice provisioning and reconfiguration, assignment of packet priority classes, and dynamic operations. These actions are performed to ensure the attainment of the desired Quality of Service level. The experimental results show the successfully implementation of RONs using Mininet Emulator and sFlow traffic monitoring technology. The results approve that optical datacenter has minimum delay with low OSNR even with long distance and fast switching time.

关键词： Data centers Optical switches Optical fiber networks Traffic control Real-time systems Service-oriented architecture Monitoring

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The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

The Goldilocks Framework: Towards Selecting the Optimal Appr...

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AI engineering - Software engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Rimman Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies’ industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.

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Challenges in developing and deploying AI in the engineering, procurement and construction industry

Challenges in developing and deploying AI in the engineering...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Rimma Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

AI in the engineering, Procurement and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Several research papers exist describing the potential of AI, and many surveys and white papers have been published indicating the challenges of AI deployment in the EPC industry. However, there is a recognizable shortage of in-depth studies of deployment experience in academic literature, particularly those focusing on the experiences of EPC companies involved in large-scale project execution with high safety standards, such as the petrochemical or energy sector. The novelty of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

关键词： Industries Procurement Companies Manuals Petrochemicals Software Safety

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