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Design of Human Adaptive Mechatronics Controller for Upper Limb Motion Intention Prediction

computers, Materials & Continua 2022年第4期71卷 1171-1188页

作者： R.Joshua Samuel Raj J.Prince Antony Joel Salem Alelyani Mohammed Saleh Alsaqer C.Anand Deva Durai Department of Information Science&Engineering CMR Institute of TechnologyBengaluruIndia Department of Mechatronics Engineering Rajas Engineering CollegeTirunelveliIndia Center for Artificial Intelligence King Khalid UniversityAbhaKingdom of Saudi Arabia College of Computer Science King Khalid UniversityAbhaKingdom of Saudi Arabia

Human Adaptive Mechatronics(HAM)includes human and computer system in a closed *** person with disabilities,normally carry out their daily routines with some assistance to move their *** the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist *** rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity *** paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the *** characteristics extraction from EMG signal and prediction of optimal controller parameters are *** and frequency based approach of EMG signal are considered for feature *** models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are *** on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM ***,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb *** proposed model of human adaptive controller predicts the limb movement by 96%accuracy.

关键词： Exoskeleton electromyography(emg) human adaptive mechatronics occupational therapy motion prediction machine learning

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A Quantum-Inspired Approach to Emergency Patient Allocation Using Digital Annealing 4

A Quantum-Inspired Approach to Emergency Patient Allocation ...

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Ou, Chia-Ho Zhu, Bo-Yuan Huang, Zong-Wei Chen, Chih-Yu Chang, Ching-Ray Huang, Wen-Hsi Chen, Wei-Cheng National Pingtung University Department of Computer Science and Information Engineering Pingtung Taiwan Chung Yuan Christian University Quantum Information Center Taoyuan Taiwan Chung Yuan Christian University Department of Physics Taoyuan Taiwan

ISBN: (纸本)9798350343236

This paper presents a quantum-inspired optimization scheme for patient allocation, aimed at the expedient and efficient distribution of medical resources. The objective is to minimize patients' waiting times and optimize the usage of available medical capacity by allocating patients to the most appropriate hospitals based on the severity of their injuries. This allocation problem is situated within the urban context, seeking to minimize the distance between patients and hospitals. Traditionally, solving such large-scale allocation problems in expansive urban areas poses significant computational challenges. However, by incorporating quantum-inspired methods, we model this problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, which is solved using a digital annealer. We conducted an experimental study on the digital annealing device and compared its performance with that of a conventional simulated annealing algorithm. The results demonstrate that our proposed digital annealing approach to patient allocation offers superior performance and effectiveness. © 2023 IEEE.

关键词： Hospitals

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Design of Evolutionary Algorithm Based Unequal Clustering for Energy Aware Wireless Sensor networks

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computer Systems science & engineering 2023年第10期47卷 1283-1297页

作者： Mohammed Altaf Ahmed T.Satyanarayana Murthy Fayadh Alenezi E.Laxmi Lydia Seifedine Kadry Yena Kim Yunyoung Nam Department of Computer Engineering College of Computer Engineering&SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka 72388Saudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of ICT Convergence Soonchunhyang UniversityAsan 31538Korea

Wireless Sensor networks(WSN)play a vital role in several real-time applications ranging from military to *** the benefits of WSN,energy efficiency becomes a major part of the challenging issue in WSN,which necessitate proper load balancing amongst the clusters and serves a wider monitoring *** clustering technique for WSN has several benefits:lower delay,higher energy efficiency,and collision *** clustering protocol has several *** a large-scale network,cluster-based protocols mainly adapt multi-hop routing to save energy,leading to hot spot problems.A hot spot problem becomes a problem where a cluster node nearer to the base station(BS)tends to drain the energy much quicker than other nodes because of the need to implement more *** article introduces a Jumping Spider Optimization Based Unequal Clustering Protocol for Mitigating Hotspot Problems(JSOUCP-MHP)in *** JSO algorithm is stimulated by the characteristics of spiders naturally and mathematically modelled the hunting mechanism such as search,persecution,and jumping skills to attack *** presented JSOUCPMHP technique mainly resolves the hot spot issue for maximizing the network *** JSOUCP-MHP technique elects a proper set of cluster heads(CHs)using average residual energy(RE)to attain *** addition,the JSOUCP-MHP technique determines the cluster sizes based on two measures,i.e.,RE and distance to BS(DBS),showing the novelty of the *** proposed JSOUCP-MHP technique is examined under several experiments to ensure its *** comparison study shows the significance of the JSOUCPMHP technique over other models.

关键词： Wireless sensor networks energy efficiency cluster heads unequal clustering hot spot issue lifetime enhancement

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Tabletop Automated TCSPS Measurement System for Characterizing Single-Photon Emitters

Tabletop Automated TCSPS Measurement System for Characterizi...

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2024 Latin America Optics and Photonics Conference, LAOP 2024

作者： Lagutchev, Alexei S. Bogdanov, Simeon I. Boltasseva, Alexandra Shalaev, Vladimir M. School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Oak RidgeTN37931 United States Department of Electrical and Computer Engineering Nick Holonyak Jr. Micro and Nanotechnology Laboratory Illinois Quantum Information Science and Technology Center University of Illinois at Urbana-Champaign UrbanaIL60801 United States

We report on a table-top system for characterizing single photon emitter fluorescence lifetimes, spectra, photon correlation and spin properties. Measurements are facilitated by automation and machine learning. ©...

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Quantum-Inspired Optimization for Task Scheduling in Software Development Projects 4

Quantum-Inspired Optimization for Task Scheduling in Softwar...

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Ou, Chia-Ho Li, Yu-Hong Chen, Chih-Yu Wu, Chi-Hsuan Tsai, Yu-Chen Yan, Zhi-You Chang, Ching-Ray National Pingtung University Department of Computer Science and Information Engineering Pingtung Taiwan Chung Yuan Christian University Quantum Information Center Taoyuan Taiwan Chung Yuan Christian University Department of Physics Taoyuan Taiwan

ISBN: (纸本)9798350343236

Software project development, characterized by numerous tasks and several engineers, necessitates effective project scheduling and personnel allocation for successful and timely completion. Tackling the inherent complexities of Software Project Scheduling (SPS) including personnel quality requirements and capability constraints is of paramount importance for software companies. This study aims to engineer robust project scheduling to enhance task completion efficiency, reduce resource waste, and ensure the punctual delivery of project milestones. Our proposed solution models the problem as a Software Project Scheduling Problem (SPSP), subsequently transformed into a Quadratic Unconstrained Binary Optimization (QUBO) model using quantum-inspired techniques. This model is then solved using a digital annealing device. We examine our proposed quantum-inspired method's effectiveness in solving SPSP through this experimental implementation, comparing its performance with the Simulated Annealing (SA) algorithm. The experimental findings reveal that the objective function, encapsulating the weighted sum of all job personnel costs and job end times, produced superior outcomes under the Digital Annealing (DA) algorithm compared to the SA algorithm. Moreover, the DA algorithm demonstrated greater stability and reduced runtime as the volume of input data expanded. © 2023 IEEE.

关键词： Simulated annealing

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Vidu4D: single generated video to high-fidelity 4D reconstruction with dynamic Gaussian surfels 24

Vidu4D: single generated video to high-fidelity 4D reconstru...

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Proceedings of the 38th International Conference on Neural information Processing Systems

作者： Yikai Wang Xinzhou Wang Zilong Chen Zhengyi Wang Fuchun Sun Jun Zhu Department of Computer Science and Technology BNRist Center Tsinghua University Department of Computer Science and Technology BNRist Center Tsinghua University and ShengShu and College of Electronic and Information Engineering Tongji University Department of Computer Science and Technology BNRist Center Tsinghua University and ShengShu

ISBN: (纸本)9798331314385

Video generative models are receiving particular attention given their ability to generate realistic and imaginative frames. Besides, these models are also observed to exhibit strong 3D consistency, significantly enhancing their potential to act as world simulators. In this work, we present Vidu4D, a novel reconstruction model that excels in accurately reconstructing 4D (i.e., sequential 3D) representations from single generated videos, addressing challenges associated with non-rigidity and frame distortion. This capability is pivotal for creating high-fidelity virtual contents that maintain both spatial and temporal coherence. At the core of Vidu4D is our proposed Dynamic Gaussian Surfels (DGS) technique. DGS optimizes time-varying warping functions to transform Gaussian surfels (surface elements) from a static state to a dynamically warped state. This transformation enables a precise depiction of motion and deformation over time. To preserve the structural integrity of surface-aligned Gaussian surfels, we design the warped-state geometric regularization based on continuous warping fields for estimating normals. Additionally, we learn refinements on rotation and scaling parameters of Gaussian surfels, which greatly alleviates texture flickering during the warping process and enhances the capture of fine-grained appearance details. Vidu4D also contains a novel initialization state that provides a proper start for the warping fields in DGS. Equipping Vidu4D with an existing video generative model, the overall framework demonstrates high-fidelity text-to-4D generation in both appearance and geometry. Project page: https://***.

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Optimizing Quality of Service Parameters for Optical networks 15

Optimizing Quality of Service Parameters for Optical Network...

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

作者： Khurana, Jatin Jayasree, S. Gupta, Shivangi Gowrishankar, J. Birare, Komal M. Balaji, N.V. Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India Jain [Deemed to be University School of Engineering and Technology Computer Science Engineering Karnataka Bangalore India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India

ISBN: (纸本)9798350370249

Optical networks are generally designed to offer best of provider (QoS) guarantees to users, which will deliver provider of the appropriate satisfactory. However, because of availability, capacity, and infrastructure constraints, those QoS parameters might not be without problems optimized. This paper explores exclusive strategies for optimizing the QoS parameters in optical networks. It examines numerous techniques inclusive of community slicing and clever manipulate for improving carrier availability, quit-to-end latency, and quit-to-end throughput. It also investigates a couple of routing strategies, together with redundant packet routing, multipath routing, and dynamic routing, to improve hyperlink and node reliabilities, and common hop-matter. Sooner or later, it discusses the potential of the use of disbursed manipulate algorithms for adjusting various QoS parameters in real-time. The paper draws on a spread of simulation situations to demonstrate the effectiveness of these optimization strategies and algorithms. Common, this paper gives an in-depth examination of the various optimization strategies to be had for boosting satisfactory of provider in optical networks. © 2024 IEEE.

关键词： Examination Manipulate Parameters Provider Reliabilities Throughput

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Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3086-3109页

作者： Yihang Hao Haofan Wang Xianggen Liu Wenrui Gai Shilong Hu Wencheng Liu Zhuang Miao Yu Gan Xianghua Yu Rongjia Shi Yongzhen Tan Ting Kang Ao Hai Yi Zhao Yihang Fu Yaling Tang Ling Ye Jin Liu Xinhua Liang Bowen Ke State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases West China Hospital of StomatologySichuan UniversityChengdu 610041China College of Computer Science Sichuan UniversityChengdu 610065China Department of Anesthesiology Laboratory of Anesthesia and Critical Care MedicineNational-Local Joint Engineering Research Centre of Translational Medicine of AnesthesiologyFrontiers Science Center for Disease-Related Molecular NetworkWest China HospitalSichuan UniversityChengdu 610041China

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic *** primary challenge is to integrate diverse pharmacophores within a single-molecule *** address this,we introduced DeepSA,a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine,a wellknown local *** integrates deep neural networks into metaheuristics,effectively constraining molecular space during compound *** framework employs a sophisticated objective function that accounts for scaffold preservation,anti-inflammatory properties,and covalent *** a sequence of local editing to navigate the molecular space,DeepSA successfully identified AT-17,a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal *** insights into AT-17 revealed its dual mode of action:selective inhibition of NaV1.7 and 1.8 channels,contributing to its prolonged local anesthetic effects,and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome *** findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery,particularly within stringent chemical constraints.

关键词： Multifunctional drugs Deep simulated annealing Molecule generation Articaine derivatives AI-enhanced drug discovery

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Development of the Decision Systems for Cloud Security Based on AI and ML 12th

Development of the Decision Systems for Cloud Security Based...

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12th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2024

作者： Maral, Vikas Balasaheb Tambakhe, Manoj D. Dhage, Prashant Shukla, Jyoti Khalaf, Osamah Ibrahim Pise, Ganesh Shivaji Vishwakarma Institute of Information Technology Maharashtra Pune India Department of Information Technology Sipna College of Engineering and Technology Amravati Maharashtra Amravati India Pune India Department of Computer Science and Engineering Arya College of Engineering Jaipur India Department of Solar Al-Nahrain Research Center for Renewable Energy Al-Nahrain University Jadriya Baghdad Iraq Department of Information Technology PICT Maharashtra Pune India

ISBN: (纸本)9789819601387

One of the most important and crucial factors often considered in keeping a network secure is the adoption of an intrusion detection system. This process is commonly called as an IDS stage which is required to keep the network protected from certain attacks in real time. Due to the wide usage of cloud on a daily purpose, the platform is constantly evolving and becoming more advanced. This has helped the developers comprehend the necessity of advancing the process of IDS. However, there are certain obstacles and issues that might arise with its acceptance. One such factor is the problem of overhead. This problem of overhead occurs when the cloud server is overloaded with existing services and thereby cannot transit other services on urgency. In such a scenario, the working concept of an IDS comes into picture wherein this adaptive design helps the developers to overcome such issues and provide a conventional flow of services to the allocate resource. The primary purpose of the presented research paper is to adapt such a concept and therefore maximize the overall potential of the system. The author of the research paper also tends to enhance and increase the overall capacity required to identify the occurrence of such threats in an online manner which are expected to occur. A CICIDS2017 dataset is used to fulfill the purpose of the same and a recurring infrastructure is therefore built in order to understand the working nature of an intrusion detection system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： network intrusion

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Automated Fruit Classification Based on Deep Learning Utilizing Yolov8 10

Automated Fruit Classification Based on Deep Learning Utiliz...

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10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Dewi, Christine Kamlasi, Oksam M Chhabra, Gunjan Dai, Guowei Kaushik, Keshav Khan, Inam Ullah Satya Wacana Christian University Department of Information Technology Salatiga Indonesia Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Agricultural Information Institute of Caas National Agriculture Science Data Center Beijing China School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Seas Isra University Department of Electronic Engineering Campus Islamabad Pakistan

ISBN: (纸本)9798350382471

The act of fruit identification entails the discernment and classification of various fruit varieties, predicated upon their visual attributes. This task can be accomplished through various methods, including manual inspection, traditional computer vision techniques, and more advanced approaches using machine learning and deep learning. Our work recognized 15 types of fruit. Our experiment used the fruit imagery dataset, consisting of class Avocado, Banana, Cherry, Apple Braeburn, Apple golden 1, Apricot, Grape, Kiwi, Mango, Orange, Papaya, Peach, Pineapple, Pomegranate and Strawberry. Yolov8 is one of the most popular learning models in the field of object detection. Convolutional neural networks (CNNs), thus simultaneously predicting multiple bounding boxes and probability classes from these bounding boxes. Yolov8 trains the entire image and directly optimizes detection performance, modeled as a Convolutional neural network (CNN). The percentage of detection of test results using *** for each of the 15 categories of fruit images with the average accuracy above is 0.97%, so it can be said to be quite good. After collecting data, Train training and system design implementation of Val Test Convolutional neural networks (CNN) algorithms enabled machine learning and were successfully detected using yolov8n. During the experimental process, we employ 100 epochs with the use of Google Collaboratory. Google Collaboratory has provided GPUs up to 12GB, making it easier and speeding up the fruit detection process. © 2023 IEEE.

关键词： Classification Convolutional Neural network(CNN) Google Collaboratory YOLOv8

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