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A Hybrid Marine Predator Algorithm for Thermal-aware Routing Scheme in Wireless Body Area Networks

Journal of Bionic engineering 2023年第1期20卷 81-104页

作者： Tao Hai Jincheng Zhou Mohammad Masdari Haydar Abdulameer Marhoon School of Computer and Information Qiannan Normal University for NationalitiesDuyun558000GuizhouChina Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun558000GuizhouChina Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Universiti Teknologi MARA40450Shah AlamSelangorMalaysia Department of Computer Engineering Islamic Azad UniversityUrmia BranchUrmiaIran Information and Communication Technology Research Group Scientific Research CenterAl-Ayen UniversityThi-QarIraq College of Computer Sciences and Information Technology University of KerbalaKarbalaIraq

Thermal-aware routing protocols in WBANs consider temperature factors in the routing process for preventing overheating of the tissues surrounding the sensor ***,providing an energy-efficient and thermal-aware routing in WBANs is a challenging *** deal with this problem,this article presents a novel temperature-aware routing protocol that applies Mamdani-based Fuzzy Logic Controllers(FLCs)for selecting the next forwarding node in routing data *** FLCs apply five important input factors such as the priority of the packet,and sensor node's remaining energy,temperature,distance,and link path ***,a new hybrid version of the Marine Predator Algorithm(MPA),named MPAOA is presented by combining the exploration and exploitation phases of the MPA and Arithmetic Optimization Algorithm(AOA).This algorithm is effectively applied for selecting the best possible set of fuzzy rules for FLCs and tuning their fuzzy *** experiments conducted in the Castalia simulator exhibit that the proposed temperature and priority-aware routing scheme can outperform other well-known routing schemes such as LATOR,TTRP,TAEO,ATAR,and EOCC-TARA in terms of metrics such as sensor nodes lifetime,the average temperature of the sensor nodes,and the percentage of the packets routed through non-overheated ***,it is shown that the MPAOA outperforms other algorithms such as Bat Algorithm(BA),Genetic Algorithm(GA),AOA,and MPA regarding the specified metrics.

关键词： WBANs Multi-hop routing Temperature Priority Fuzzy logic Bio-inspiration

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EnsembleCAM: Unified Visualization for Explainable Cervical Cancer Identification

EnsembleCAM: Unified Visualization for Explainable Cervical ...

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International Research Conference on Smart Computing and systems engineering (SCSE)

作者： Niruthikka Sritharan Nishaanthini Gnanavel Prathushan Inparaj Dulani Meedeniya Pratheepan Yogarajah Department of Computer Science and Engineering University of Moratuwa Moratuwa Sri Lanka School of Computing Engineering and Intelligent Systems Ulster University Londonderry United Kingdom

ISBN: (数字)9798350375688

ISBN: (纸本)9798350375695

Cervical cancer, which is ranked fourth among cancers affecting women, is highly treatable when detected early through the pap smear test. Deep Learning (DL) models, particularly Convolutional Neural Networks (CNNs), analyze pap smear images, yet their "Black-Box" nature raises transparency concerns in medical diagnostics. This paper introduces a solution named EnsembleCAM to enhance interpretability by unifying visual explanations through the combination of diverse Class Activation Maps (CAMs). Using the Herlev Dataset, we employ data pre-processing, data augmentation techniques, develop an XceptionNet based binary classification model with an accuracy of 89% and apply GradCAM, GradCAM++, Score-CAM, Eigen-CAM and LayerCAM on this classifier. Then, the novel EnsembleCAM is constructed taking the median of activation maps from the five individual CAM methods. The analysis of activation maps of each CAM method and EnsembleCAM confirmed that in activation maps of EnsembleCAM, higher activation values were more concentrated around the nucleus which is the most important region in indicating cervical malignancy. The evaluation using pixel flipping performance metric also proved that the EnsembleCAM effectively recognises regions vital to the model's decision-making through its steepest drop in the mean prediction score when the pixels in the region contributing most to the model's decision were flipped.

关键词： Visualization Decision making Closed box Predictive models Cams Reliability Medical diagnosis

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AGVs vs AMRs: A Comparative Study of Fleet Performance and Flexibility

AGVs vs AMRs: A Comparative Study of Fleet Performance and F...

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Iberian Robotics Conference (ROBOT)

作者： Rita Tomé Silva Marina Brilhante Héber Sobreira Diogo Matos Pedro Costa Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto Portugal Centre of Robotics in Industry and Intelligent Systems INESC TEC Porto Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs) have emerged as key innovations in the industry world, with AMRs offering flexibility a nd adaptability for dynamic environments, while AGVs provide high accuracy for repetitive tasks; thus, this research proposes a study of fleets of both AGVs and AMRs to enhance productivity and efficiency in industrial settings. Several tests were performed where the duration of a mission, the success and collision rate, and the average number of disputes per mission were analyzed in order to obtain results. In conclusion, while AGVs tend to be more reliable and consistent in task completion, AMRs offer greater flexibility a nd speed.

关键词： Productivity Technological innovation Remotely guided vehicles Navigation Scalability Path planning Mobile robots Reliability Vehicle dynamics Autonomous robots

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Interpretable Cervical Cell Classification: A Comparative Analysis

Interpretable Cervical Cell Classification: A Comparative An...

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Advanced Research in Computing (ICARC), International Conference on

作者： Nishaanthini Gnanavel Prathushan Inparaj Niruthikka Sritharan Dulani Meedeniya Pratheepan Yogarajah Department of Computer Science and Engineering University of Moratuwa Moratuwa Sri Lanka School of Computing Engineering and Intelligent Systems Ulster University Londonderry United Kingdom

Cervical cancer is a significant global health issue, and traditional screening methods like Pap smears are labor-intensive and may miss some cases. Automation is needed, but it faces challenges in terms of interpretability and data availability. To address this, the paper proposes using Explainable Artificial Intelligence (XAI) techniques like GradCAM, GradCAM++, and LRP to improve the transparency and interpretability of a cervical cell classification model, making it a novel contribution to enhancing the trustworthiness of automated cervical cancer detection. Using the Herlev Dataset, we employ data pre-processing, data augmentation techniques and develop a binary classification model, achieving a 91.94% accuracy with VGG16. The qualitative analysis of XAI methods confirmed that the model relied on nucleus and cytoplasm features, key indicators of malignancy. The least mean image entropy of 2.4849 and steep prediction confidence drop with perturbations quantitatively proved Layer-wise Relevance Propagation (LRP) to be the most effective XAI technique for cervical cell classification.

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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Visual Odometry with Depth-Wise Separable Convolution and Quaternion Neural Networks 9

Visual Odometry with Depth-Wise Separable Convolution and Qu...

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9th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2022

作者： De Magistris, Giorgio Comminiello, Danilo Napoli, Christian Starczewski, Janusz T. Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Department of Information Engineering Electronics and Telecommunications Sapienza University of Rome Via Eudossiana 18 Rome00184 Italy Department of Intelligent Computer Systems Czestochowa University of Technology al.Armii Krajowej 36 Czestochowa42-200C Poland

Monocular visual odometry is a fundamental problem in computer vision and it was extensively studied in literature. The vast majority of visual odometry algorithms are based on a standard pipeline consisting in feature detection, feature matching, motion estimation and local optimization. Only recently, deep learning approaches have shown cutting-edge performance, replacing the standard pipeline with an end-to-end solution. One of the main advantages of deep learning approaches over the standard methods is the reduced inference time, that is an important requirement for the application of visual odometry in real-time. Less emphasis, however, has been placed on memory requirements and training efficiency. The memory footprint, in particular, is important for real world applications such as robot navigation or autonomous driving, where the devices have limited memory resources. In this paper we tackle both aspects introducing novel architectures based on Depth-Wise Separable Convolutional Neural Network and deep Quaternion Recurrent Convolutional Neural Network. In particular, we obtain equal or better accuracy with respect to the other state-of-the-art methods on the KITTI VO dataset with a reduction of the number of parameters and a speed-up in the inference time. © 2022 Copyright for this paper by its authors.

关键词： Pipelines

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Moss-Based Biotechnological Air Purification Control System

Moss-Based Biotechnological Air Purification Control System

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2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022

作者： Kusdavletov, Sanzhar Sapargali, Abdulla Yedilkhan, Didar Yermekov, Altynbek Astana IT University Department of Intelligent Systems and Cybersecurity Astana Kazakhstan Astana IT University Department of Computer Engineering Astana Kazakhstan Astana IT University 'Smart City' Research Center Astana Kazakhstan

ISBN: (数字)9781665456005

ISBN: (纸本)9781665456005

Nowadays, air pollution is one of the acute problems that humanity faces as the world further develops and more technology comes into use. Pollution is produced both outside and inside buildings mostly from the machinery we use for convenience. In this paper, a non-standard approach is being explored to solve the problem at hand. Since excessive ventilation can lead to more pollution and infection, and is also a loss of energy, it was decided to focus not on ventilation, but on air purification. To purify the air, a filter created by living plants has been used. For the project, we chose moss, which is unpretentious and small, unlike trees and bushes. Due to the autonomy and scale, our solution is easy to use and brings enormous ecological and social impact. During the research, a biotechnological prototype is created, where it is possible to observe and control moss growth and its productivity. For the algorithm to work correctly, data about the environment is required. For this reason, in this paper, we have described not only the modeling of the system we suggest but also the process of collecting information from the biofilter. By reducing pollution, we will shortly save and stabilize the ecological situation. In this project, the effective biofilter is developed based on various solutions from biology, control engineering, as well as internet of things fields. © 2022 IEEE.

关键词： Control systems

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Digital Twin Agent for Super-Aged Society

Digital Twin Agent for Super-Aged Society

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Kobayashi, Toru Fukae, Kazuki Imai, Tetsuo Arai, Kenichi Graduate School of Engineering Nagasaki University Division of Electrical Engineering and Computer Science Nagasaki Japan Hiroshima City University Graduate School of Information Sciences Department of Intelligent Systems Hiroshima Japan

ISBN: (纸本)9781665441544

We propose a digital twin agent that constructs elderly digital twins by digitally transforming daily life of the elderly. We developed the digital twin agent as an avatar run on a smartwatch. The digital twin agent provides cooperation support functions with the society to the elderly. Those support function histories will be integrated with the digital twin. The digital twin agent can also monitor indoor daily life activities using distributed small sensors inside home. Then, those monitoring results will be integrated with the same digital twin. We confirmed that the digital twin agent could provide cooperation support functions with the society through evaluation experiments in Nagasaki city in Japan. We also confirmed that the digital twin agent could construct the digital twin based on those support function histories and offer mental health support functions using the constructed digital twin. © 2022 IEEE.

关键词： Resource Description Framework (RDF)

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Risk-Aware Sensitive Property-Driven Resource Management in Cloud Datacenters

arXiv

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arXiv 2025年

作者： Felemban, Muhamad Almutairi, Abdulrahman Ghafoor, Arif Computer Engineering Department The Information and Computer Science Department The Interdisciplinary Research Center for Intelligent Secure Systems KFUPM Saudi Arabia Purdue University West LafayetteIN United States Computer Engineering Department The College of Computer and Information Science in King Saud University Riyadh Saudi Arabia

Organizations are increasingly moving towards the cloud computing paradigm, in which an on-demand access to a pool of shared configurable resources is provided. However, security challenges, which are particularly exacerbated by the multitenancy and virtualization features of cloud computing, present a major obstacle. In particular, sharing of resources among potentially untrusted tenants in access controlled cloud datacenters can result in increased risk of data leakage. To address such risk, we propose an efficient risk-aware sensitive property-driven virtual resource assignment mechanism for cloud datacenters. We have used two information-theoretic measures, i.e., KL-divergence and mutual information, to represent sensitive properties in the dataset. Based on the vulnerabilities of cloud architecture and the sensitive property profile, we have formulated the problem as a cost-drive optimization problem. The problem is shown to be NP-complete. Accordingly, we have proposed two heuristics and presented simulation based performance results for cloud datacenters with multiple sensitivity. © 2025, CC BY.

关键词： Cloud platforms

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Robust-MSA: Understanding the Impact of Modality Noise on Multimodal Sentiment Analysis 37

Robust-MSA: Understanding the Impact of Modality Noise on Mu...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Mao, Huisheng Zhang, Baozheng Xu, Hua Yuan, Ziqi Liu, Yihe State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing100084 China Beijing100084 China School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang050018 China

ISBN: (纸本)9781577358800

Improving model robustness against potential modality noise, as an essential step for adapting multimodal models to real-world applications, has received increasing attention among researchers. For Multimodal Sentiment Analysis (MSA), there is also a debate on whether multimodal models are more effective against noisy features than unimodal ones. Stressing on intuitive illustration and in-depth analysis of these concerns, we present Robust-MSA, an interactive platform that visualizes the impact of modality noise as well as simple defence methods to help researchers know better about how their models perform with imperfect real-world data. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Sentiment analysis

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