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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Giri, Rakesh Kumar Vittapu, Mani Sarma Dev, Anoop Shewale, Chaitali R. Majid, Mohd Aliff Abdul Kulkarni, Nandini Sunrise University Alwar Department of Computer Science and Engineering India Mallareddy Engineering College and Management Sciences Department of Computer Science and Engineering Kistapur Village Medchal Telangana Hyderabad India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura India Vishwakarma Institute of Technology Department of Information Technology Pune India University Teknology MARA Faculty of Hotel and Tourism Management Department of Foodservice Management Malaysia Symbiosis International University Department of Symbiosis School of Planning Architecture and Design Nagpur Nagpur India

ISBN: (纸本)9798350370249

Cross-layer Protocols for proper resource Allocation in Mobile Networks are a singular technique to enhance the efficiency of wireless networks. The method utilizes multiple layers of the radio protocol stack better to coordinate cell node scheduling and resource allocation. Using combining communication, routing, and scheduling functionalities in an unmarried protocol, pass-Layer Protocols for proper resource Allocation can offer a sizable will increase in the number of facts that may be transferred and the overall latency and throughput of the community. This technique can also enhance the radio interface's operation by lowering interference and encouraging collaborative communications. Eventually, by using facts and managing records from the communique and routing layers, go-Layer Protocols for proper resource Allocation can reduce the complexity of the community, even offering greater scalability. This paper affords unique cross-Layer Protocols for resource Allocation in Cellular Networks. The proposed protocol permits integrated resource allocation in the cell network environment, considering communication and computation layers. © 2024 IEEE.

关键词： Network layers

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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders

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computers and Electronics in Agriculture 2022年 200卷

作者： Cejrowski, Tymoteusz Szymański, Julian Faculty of Electronics Telecommunications and Informatics Department of Computer Architecture Gdańsk University of Technology Poland

Honeybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used for general honeybee colony state inference. Application of the classifier models for the hazardous situations detection without focusing on the model's genericity could result with systems that are not applicable in the real environment. Furthermore, the detection of a specific phenomenon does not provide researchers with any new conclusions about the honeybee colony life but only with the binary information about hazardous situation presence. In our research we propose a method for inferring the bee colony state using a sensitive contrastive autoencoder and an anomaly detection model. With presented approach, hive's internal state is modeled with the use of an autoencoder's latent vector extended with in-hive temperature dynamics. We test our methodology with a bee feeding experiment where the glucose syrup application was detected and the length of food intake was estimated. As our methodology has been applied successfully, we argue that contrastive autoencoders can be used for precise inference about the behavior of honeybees. © 2022 The Author(s)

关键词： Anomaly detection

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Living Lab Long-Term Sustainability in Hybrid Access Positive Energy Districts - A Prosumager Smart Fog Computing Perspective

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IEEE Internet of Things Journal 2023年第21期10卷 18898-18908页

作者： Vohnout, Rudolf Bukovsky, Ivo Chou, Shuo-Yan Geyer, Jakub Budik, Ondrej Sharma, Rohit Prokysek, Milos Horvath, Tomas Wyckmans, Annemie University of South Bohemia in České Budějovice Faculty of Science Department of Computer Science České Budějovice37005 Czech Republic National Taiwan University of Science and Technology Department of Industrial Management Taipei106 Taiwan SRM Institute of Science and Technology NCR Campus Department of Electronics and Communication Engineering Ghaziabad201204 India Brno University of Technology Department of Telecommunications Brno61600 Czech Republic CESNET a.l.e Department of Optical Networks Prague16000 Czech Republic NTNU-Norwegian University of Science and Technology Department of Architecture and Planning Trondheim7491 Norway

Living lab, one of the recent emerging smart city concepts, faces long-term sustainability challenges associated with its complexity and breadth of use. To be efficient, it must rely on comprehensive set of information distributed appropriately among all stakeholders to unleash its full innovation potential. This is especially true in the case of positive energy districts (PEDs), where timely data dissemination is essential for prosumager decisions and their greedy behavior. This article interconnects intelligent information exchange, supported by ultralow latency hybrid access network infrastructure, with the clever use of available fog computing resources to properly disseminate complex energy details to all participating entities. As the optimal task offloading for effective information distribution constitutes the convergence problem, we reintroduced higher order neural units. These units contribute to sustaining both computational and energy efficiency, as well as the balance of the entire system. We have achieved a reliable hourly energy consumption prediction with a computationally very lightweight alternative to commonly used deep neural network approaches that can be deployed on available smart appliances with ease. The application and simulation were performed on the data set provided by one of Europe's smart city pioneers, where the prosumager PED transition has already started. © 2023 IEEE.

关键词： Decision making

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Flower Classification Based on Improve VGG Networks with Attention 3

Flower Classification Based on Improve VGG Networks with Att...

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3rd International Conference on computer Vision, Image and Deep Learning and International Conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Huo, Jiahao Qiao, Sijie Qian, Qicong Yang, Jiaxi School of Architectural Engineering Jinling Institute of Technology Nanjing China Xidian University School of Computer Science and Technology Xi'an China Wuhan University of Technology School of Naval Architecture Ocean and Energy Power Engineering Wuhan China Luoyang Normal University School of Information Technology Luoyang China

ISBN: (纸本)9781665459112

This paper mainly introduces an improved flower recognition method based on improved VGG Networks. There are problems with the existing flower recognition system. For example, recognition accuracy is poor for flowers with a similar appearance. Also, the model they use usually takes a long time for training. This study took into account the characteristics of the project and used the Mobile Network that is more lightweight than most of the other networks they normally used. In this case, this study ameliorates the network by adding the attentional mechanism. The proposed model adjusts the network architecture according to the learning results and expectations during the training process. The experiments show that the proposed model with the integration of the MobileNet is more accurate and efficient than other networks. The improved model with attention mechanism can be generalized to new flower datasets and correctly identify flower species in a noisy background, making it practical to apply the model in daily life. © 2022 IEEE.

关键词： Deep neural networks

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A Many-Objective Evolutionary Algorithm Based on Indicator Selection and Adaptive Angle Estimation

SSRN

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SSRN 2024年

作者： Wang, Qian Gu, Qinghua Zhou, Qing Xiong, Neal Naixue Liu, Di School of Management Xi’an University of Architecture and Technology Shaanxi Xi’an China School of Resources Engineering Xi’an University of Architecture and Technology Shaanxi Xi’an China Xi’an Key Laboratory for Intelligent Industrial Perception Calculation and Decision Xi’an University of Architecture and Technology Xi’an710055 China Department of Mathematics and Computer Science Northeastern State University TahlequahOK74464 United States

Currently, real-world complex engineering problems often have more than three objectives that need to be optimized simultaneously. Existing algorithms for solving them mostly rely on the shape of the Pareto front to maintain diversity, which makes it difficult to effectively balance the convergence and diversity of the solutions. To address the above problems, a many-objective evolutionary algorithm based on indicator selection and adaptive angle estimation (MaOEA-ISAE) is proposed in this paper. Firstly, a unit vector metric selection strategy is presented, which uses the favorable physical properties of the metric to identify dominant individuals, thus striking a balance between convergence and diversity. Then, to preserve the diversity of the population, an adaptive angle estimation strategy based on Pareto front curvature prediction is developed. The angular distances of individuals are adaptively measured according to the predicted curvature, thereby selecting individuals with good diversity in the dominant region. Besides, the algorithm has a simple evolutionary process, and no additional parameters are involved. Finally, the proposed MaOEA-ISAE is compared with five other representative many-objective evolutionary algorithms on test instances of 3-20 objectives with different Pareto front shapes. The experimental results show the strong competitiveness of the proposed algorithm on different Pareto front problems. © 2024, The Authors. All rights reserved.

关键词： Evolutionary algorithms

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Examining the Software Developers’ Perception in Open-Source Software of Blockchain Project Using Association Rules Mining 9th

Examining the Software Developers’ Perception in Open-Sourc...

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9th International Conference on Computing and Informatics, ICOCI 2023

作者： Abd Wahab, Alawiyah Hj. Ibrahim, Huda SarkinTudu, Shehu M. Romo, Bilyaminu A. School of Computing University Utara Malaysia Kedah Sintok06010 Malaysia Department of Computer and Information Technology Sokoto State University P.M.B 2134 Near Airport Road Sokoto State Sokoto Nigeria School of Architecture Computing and Engineering University of East London London United Kingdom

ISBN: (纸本)9789819995882

Developers are vital in enhancing blockchain projects like Bitcoin through feature additions, bug fixes, and performance optimization. However, comprehending developers’ perception of the growing amount of information regarding new features and bug fixes becomes challenging as blockchain projects gain popularity. Data mining, a technique that extracts valuable patterns and information from extensive data sets, assists in decision-making. The Apriori algorithm, widely used in data mining, uncovers association rules among sets of items. Despite its effectiveness, the Apriori algorithm remains relatively underutilized in the field of Open Source Software (OSS) developer turnover. Previous studies have employed approaches like mining software project repositories, social network analysis, quantitative data analysis, and surveys, which shed light on turnover but fail to reveal interesting relationships and patterns related to subjective factors and collaboration. To address this gap, this paper proposes combining survey data with association rule mining. This approach aims to identify co-occurrence patterns between specific personal and project-related variables (e.g., intention to learn or system integration). By analyzing these variables and their associations, the paper intends to provide valuable insights to project leaders, aiding decision-making in developer turnover management. Ultimately, this research contributes to enhancing the quality of blockchain projects. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Association rules

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Comparison of Metamerism Estimates in Video Paths using CAM's Models 9

Comparison of Metamerism Estimates in Video Paths using CAM'...

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9th IEEE International Conference on Problems of Infocommunications Science and technology, PIC S and T 2022

作者： Jawad, Aqeel Mahmood Hashim Qasim, Nameer Pyliavskyi, Volodymyr Al-Rafidain University College Department of Computer Technology Engineering Baghdad Iraq Cihan University of Sulaimaniya Department of Computer Science Sulaymaniyah Iraq Odesa State Academy of Civil Engineering and Architecture Department Information Technologies and Apply Mathematics Odesa Ukraine

ISBN: (纸本)9798350398915

The paper deals with the issues of metamerism in multimedia and telecommunication paths. Attention is focused on the end devices of the end-To-end path. A comparison is made in the assessments using traditional coordinate systems for representing colors, and in the coordinates of modern color models CAM16, CAM20u, ZCAM. Numerical differences in the obtained data are shown under the same input conditions. Statistical data of metamer estimates using Mac Adam ellipses are presented. A study was conducted in the work, showing that the spectral compositions of colors can be perceived as one color (based on McAdam's data), but when processed, their number can be different. Based on research, we can say that the differences can reach to 15%. When processing ZCAM models, the number of colors taken into account during transmission will be greater, which makes it possible to reduce the degree of influence of metamerism on color reproduction. © 2022 IEEE.

关键词： Color

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Distributed Learning by Local Training ADMM 63

Distributed Learning by Local Training ADMM

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Ren, Xiaoxing Bastianello, Nicola Johansson, Karl H. Parisini, Thomas Kth Royal Institute of Technology 2School of Electrical Engineering and Computer Science and Digital Futures Stockholm Sweden Imperial College London Department of Electrical and Electronic Engineering London United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Trieste Italy

ISBN: (纸本)9798350316339

In this paper, we focus on distributed learning over peer-to-peer networks. In particular, we address the challenge of expensive communications (which arise when e.g. training neural networks), by proposing a novel local training algorithm, LTADMM. We extend the distributed ADMM enabling the agents to perform multiple local gradient steps per communication round (local training). We present a preliminary convergence analysis of the algorithm under a graph regularity assumption, and show how the use of local training does not compromise the accuracy of the learned model. We compare the algorithm with the state of the art for a classification task, and in different set-ups. The results are very promising showing a great performance of LT-ADMM, and paving the way for future important theoretical developments. © 2024 IEEE.

关键词： Peer to peer networks

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QVal: A Novel Routing Algorithm for Dragonfly Networks

QVal: A Novel Routing Algorithm for Dragonfly Networks

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Javier Navaridas Jose A. Pascual Dept. of Computer Architecture and Technology University of the Basque Country (UPV/EHU) Donostia-San Sebastián Spain

Dragonfly is becoming one of the networks of choice for high-performance computer systems as it offers a sweet spot in terms of cost, simplicity, performance, fault-tolerance and power. In a Dragonfly topology, compute nodes are connected to routers forming fully-connected groups, which are then connected to every other group. This provides very high connectivity with very low diameter which are desired characteristics of high performance interconnection networks. In this work, we propose Quick Valiant, a new routing algorithms for dragonfly networks which leverages Valiant routing with novel proxy selection criteria which reduce the utilization of network resources and eases congestion under pathological loads. These criteria restrict the possible proxies to these that are adjacent to either the local or the remote router, codenamed QVL and QVR, respectively. We compare our proposals with canonical routing functions and observe reductions of average path length of up to 27% and throughput improvements of up to 46% when compared with Valiant routing. Out of these criteria, restricting to local proxies only, QVL, obtains the best results in all scenarios.

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Enhancing the Smart Readiness Indicator Scheme: Methodology Assessment through 20 Use Cases

Enhancing the Smart Readiness Indicator Scheme: Methodology ...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Afroditi Zamanidou Despoina Kothona Paris Fokaides Georgios C. Christoforidis Electrical & Computer Engineering Department Faculty of Engineering University of Western Macedonia Greece Faculty of Civil Engineering and Architecture Kaunas University of Technology Kaunas Lithuania

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

The European Union developed the Smart Readiness Indicator (SRI) to enhance energy efficiency and encourage the adoption of smart technologies in buildings, tackling their high energy usage and carbon emissions. This study evaluates the SRI methodology through the assessment of 20 diverse use cases, including residential and non-residential buildings, using Methods A and B of the SRI assessment scheme. Key variables such as climate zone, building type, year of construction, and the integration of smart-ready services were considered to ensure a comprehensive *** engineers assessed the buildings using the SRI EU Excel Tool and rated the methodology based on criteria including accuracy, usability, comprehensiveness, flexibility, and impact on decision-making. The results revealed high ratings for accuracy (45% rated as "Very Good" and 30% as "Excellent") and usability (50% rated as "Very Good"), while comprehensiveness was rated more moderately (40% "Good"). However, flexibility and adaptability emerged as areas requiring improvement, with 45% of assessments rated as "Fair." The SRI methodology demonstrated strong potential but requires further refinement to address the needs of diverse building types and more complex smart technologies. The study concludes that the SRI framework is a valuable tool for promoting energy efficiency and smart technology adoption across the EU building sector. However, additional research is recommended to integrate real-time data and automation technologies, and to enhance the framework's scalability and adaptability for future building systems.

关键词： Accuracy Automation Scalability Buildings Decision making Europe Solids Energy efficiency Real-time systems Usability

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