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Maximizing Resource Efficiency in Cloud Data Centers through Knowledge-Based Flower Pollination Algorithm (KB-FPA)

computers, Materials & Continua 2024年第6期79卷 3757-3782页

作者： Nidhika Chauhan Navneet Kaur Kamaljit Singh Saini Sahil Verma Kavita Ruba Abu Khurma Pedro A.Castillo University Institute of Computing Department Chandigarh UniversityPunjab140413India Department of Computer Science and Engineering Chandigarh UniversityPunjab140413India Universidade Federal do Piauí TeresinaPiauí64049-550Brazil MEU Research Unit Faculty of Information TechnologyMiddle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Department of Computer Engineering Automatics and RoboticsUniversity of GranadaGranada18071Spain

Cloud computing is a dynamic and rapidly evolving field,where the demand for resources fluctuates *** paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing *** motivation stems from the pressing issue of accommodating fluctuating levels of user demand *** adhering to the proposed resource allocation method,we aim to achieve a substantial reduction in energy *** reduction hinges on the precise and efficient allocation of resources to the tasks that require those most,aligning with the broader goal of sustainable and eco-friendly cloud computing *** enhance the resource allocation process,we introduce a novel knowledge-based optimization *** this study,we rigorously evaluate its efficacy by comparing it to existing algorithms,including the Flower Pollination Algorithm(FPA),Spark Lion Whale Optimization(SLWO),and Firefly *** findings reveal that our proposed algorithm,Knowledge Based Flower Pollination Algorithm(KB-FPA),consistently outperforms these conventional methods in both resource allocation efficiency and energy consumption *** paper underscores the profound significance of resource allocation in the realm of cloud *** addressing the critical issue of adaptability and energy efficiency,it lays the groundwork for a more sustainable future in cloud computing *** contribution to the field lies in the introduction of a new resource allocation strategy,offering the potential for significantly improved efficiency and sustainability within cloud computing infrastructures.

关键词： Cloud computing resource allocation energy consumption optimization algorithm flower pollination algorithm

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Preprocessing Taste Data for Deep Neural Networks 14

Preprocessing Taste Data for Deep Neural Networks

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Lee, Hyunjong Jung, Han Hee Kwak, Jeongho Yea, Junwoo Choi, Jihwan P. Jang, Kyung-In Department of Electrical Engineering and Computer Science Daegu Korea Republic of Dgist Department of Robotics and Mechatronics Engineering Daegu Korea Republic of Dgist Department of Electrical Engineering and Computer Science Daegu Korea Republic of Department of Aerospace Engineering Dajeon Korea Republic of

ISBN: (纸本)9798350313277

Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks. © 2023 IEEE.

关键词： data augmentation deep learning preprocessing taste classification taste sensor wine

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Computational Approach for Automated Segmentation and Classification of Region of Interest in Lateral Breast Thermograms

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computers, Materials & Continua 2024年第9期80卷 4749-4765页

作者： Dennies Tsietso Abid Yahya Ravi Samikannu Basit Qureshi Muhammad Babar Department of Electrical Computer and Telecommunications EngineeringBotswana International University of Science and TechnologyPalapyePrivate Bag 16Botswana College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh11586Saudi Arabia

Breast cancer is one of the major health issues with high mortality rates and a substantial impact on patients and healthcare systems *** computer-Aided Diagnosis(CAD)tools,based on breast thermograms,have been developed for early detection of this ***,accurately segmenting the Region of Interest(ROI)fromthermograms remains *** paper presents an approach that leverages image acquisition protocol parameters to identify the lateral breast region and estimate its bottomboundary using a second-degree *** proposed method demonstrated high efficacy,achieving an impressive Jaccard coefficient of 86%and a Dice index of 92%when evaluated against manually created ground *** features were extracted from each view’s ROI,with significant features selected via Mutual Information for training Multi-Layer Perceptron(MLP)and K-Nearest Neighbors(KNN)*** findings revealed that the MLP classifier outperformed the KNN,achieving an accuracy of 86%,a specificity of 100%,and an Area Under the Curve(AUC)of *** consistency of the method across both sides of the breast suggests its viability as an auto-segmentation ***,the classification results suggests that lateral views of breast thermograms harbor valuable features that can significantly aid in the early detection of breast cancer.

关键词： Breast cancer CAD machine learning ROI segmentation thermography

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Real-Time Operating System for Multitasking Control in the robotics and Automation Industry

Real-Time Operating System for Multitasking Control in the R...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Sayyad, Javed Jatti, Ashwini Attarde, Khush Ramesh, B.T. Deokar, Shubhangi Robotics and Automation Department Lavale Maharashtra Pune India Computer Science and Engineering Lavale Maharashtra Pune India

ISBN: (纸本)9781665474511

Real-Time Operating System (RTOS) is an Operating System (OS) that does a task in a constrained time. The RTOS is integrated with the microprocessor or microcontroller for specialized applications where the time-bound completion of the task is very much substantial. ESP32 is a microcontroller that comes with a package of advantageous and suitable features for RTOS. The ability of equipment like motors, sensors, and actuators to multitask is critical in the robotics and Automation (R&A) industry. In industries, a dedicated/centralized system allocated for a particular activity is not economically feasible;yet, when performing several tasks, some delay or lag is introduced in the task. Consequently, the proposed solution for industrial multitasking is cost-effective and efficient. The RTOS is suitable for machines constrained to do painstaking work, like a robotic arm or CNC drilling. In the R&A industry, a hardware interruption is often critical for an emergency, which may also be accomplished using RTOS. In such applications, implementing a software timer is also essential to delay a task for a period of time. Stepper and servo motors are widely employed in the R&A industries for various applications. This article presents the multitasking of four stepper motors and the introduction of a software timer, which will be developed when the stepper motor multitasking is implemented. For multitasking, the FreeRTOS library will be utilized. © 2023 IEEE.

关键词： Microcontrollers

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Comparative analysis of navigation algorithms for mobile robot

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Journal of Ambient Intelligence and Humanized Computing 2024年第12期15卷 3861-3871页

作者： Heng, Han Ghazali, Mohamad Hazwan Mohd Rahiman, Wan School of Electrical and Electronic Engineering Universiti Sains Malaysia Engineering Campus Penang Nibong Tebal14300 Malaysia Universiti Sains Malaysia Engineering Campus Penang Nibong Tebal14300 Malaysia Daffodil Robotics Lab Department of Computer Science and Engineering Daffodil International University Dhaka1216 Bangladesh

Various applications, including space exploration, transportation, factories, and the military, demand the presence of mobile robots. In those applications, navigation algorithms are essential for enabling mobile robots to operate efficiently and safely in static and dynamic environments. Due to the numerous navigation algorithms available, choosing a suitable and robust one for a specific mobile robot application can be challenging. Therefore, there is a pressing need to conduct a comparative analysis to evaluate the performance and adaptability of different navigation algorithms. This article presents a comparative study of five distinct algorithms in the domain of path planning, which are rapidly random tree (RRT), A*, genetic algorithm (GA), ant colony optimization (ACO), and particle swarm optimization (PSO). The investigation was conducted on three distinct maps, and the strengths and weaknesses of each algorithm are demonstrated. Findings show that increasing the step distance and number of iteration parameters will result in an increase in the planning time. Consequently, the obtained path lengths are also reduced except for the PSO algorithm. Findings show that in the three different environments considered in this paper, the GA exhibits better performance, where a 90% reduction in the planning time is achieved while obtaining the same path length as the A* algorithm, which is the shortest path. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Particle swarm optimization (PSO)

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Improving Sharpness-Aware Minimization by Lookahead 41

Improving Sharpness-Aware Minimization by Lookahead

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41st International Conference on Machine Learning, ICML 2024

作者： Yu, Runsheng Zhang, Youzhi Kwok, James T. Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation CAS Hong Kong

Sharpness-Aware Minimization (SAM), which performs gradient descent on adversarially perturbed weights, can improve generalization by identifying flatter minima. However, recent studies have shown that SAM may suffer from convergence instability and oscillate around saddle points, resulting in slow convergence and inferior performance. To address this problem, we propose the use of a lookahead mechanism to gather more information about the landscape by looking further ahead, and thus find a better trajectory to converge. By examining the nature of SAM, we simplify the extrapolation procedure, resulting in a more efficient algorithm. Theoretical results show that the proposed method converges to a stationary point and is less prone to saddle points. Experiments on standard benchmark datasets also verify that the proposed method outperforms the SOTAs, and converge more effectively to flat minima. Copyright 2024 by the author(s)

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引用

33rd ACM Web Conference, WWW 2024

作者： Ma, Changyi Yu, Runsheng Zhang, Youzhi Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation CAS Hong Kong Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9798400701719

The similarity matrix is at the core of similarity search problems. However, incomplete observations are ubiquitous in real scenarios leading to a less accurate similarity matrix. To alleviate this problem, in this paper, based on the key insight that the similarity matrix enjoys both the symmetric and positive semi-definiteness (PSD) properties, we propose a novel similarity matrix calibration method, which is scalable, effective, and sound. Specifically, we establish the PSD property as a constraint for the similarity matrix calibration problem and propose a novel similarity matrix calibration method to estimate the similarity matrix, which approximates the unknown complete ground-truth similarity matrix. To enable a fast optimization process, we further develop a general approximated algorithm that bypasses the computation of singular values. Theoretical analysis ensures stable calibration performance and convergence speed. Extensive experiments of similarity matrix calibration on real-world datasets demonstrate that our proposed method outperforms baseline methods in terms of both accuracy and speed. © 2024 ACM.

关键词： Calibration

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Suitability of Sacrum Motion in Computing Dynamic Gait Stability Indices 12

Suitability of Sacrum Motion in Computing Dynamic Gait Stabi...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Liu, Ziqi Kuroda, Tomohito Okamoto, Shogo Akiyama, Yasuhiro Tokyo Metropolitan University Department of Computer Science Hino Japan Shinshu University Department of Mechanical Engineering and Robotics Ueda Japan

ISBN: (纸本)9798350340181

Gait stability indices are expected to preemptively detect people at high risk of falling. Among these, the margin of stability (MoS) is known as a valid index. Usually, the computation of MoS requires the motion-related information of multiple feature points of the body;however, we have been pursuing the use of only one feature point. We estimated the anterior and mediolateral MoS values from the velocity time series of the sacrum, knee, or toe using principal motion analysis. Based on open gait data for 60 people over 60 years of age, the sacrum was best suited for computing MoS in the anterior and mediolateral directions. The correlation coefficients between the estimated and observed values were 0.77 and 0.73, respectively. Our findings will help establish an easy-to-access and accurate measurement of MoS values using an inertial measurement unit attached to a body feature. © 2023 IEEE.

关键词： Stability

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Design and Development of a Device to Measure Tissue Strength in Experimental Animals 8

Design and Development of a Device to Measure Tissue Strengt...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and robotics, DISCOVER 2024

作者： Veeresha, R.K. Shastry, C.S. Moolya Shodhan, S. Karegoudra, Shilpa Kumar, Nithin Department of Robotics and Artificial Intelligence Udupi574110 India Paneer Deralakatte Mangalore575018 India Department of Mechanical Engineering Udupi574110 India Department of Computer Science and Engineering Udupi574110 India

ISBN: (纸本)9798350350593

Developing a wound strength measuring device for experimental animals involves a multidisciplinary approach that combines engineering, biology, and veterinary medicine. Such a device would help researchers assess the healing progress and strength of wounds in animals, enabling a better understanding of tissue regeneration and wound healing mechanisms. In this paper, We designed a mice holder along with a full experimental setup to apply load and measure the displacement automatically. Also, we carried out an experiment to measure load versus displacement. © 2024 IEEE.

关键词： Mammals

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Scanning the Issue - May 2025

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IEEE Transactions on Intelligent Transportation Systems 2025年第5期26卷 5627-5648页

作者： Simona Sacone Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genova Genova Italy

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