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Artificial intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： K Nattar Karman V. Velmurugan Kommisetti Murthy Raju T. Sajana V. Vijayalakshmi JoshuvaArockia Dhanraj Departmeru of Artificial Intelligence and Machine Learning Saveetha School of Engineering Chennai Tamil Nadu India Department of Electronics and Communication Engineering Vel Tech Rangarajan and Dr.Sagunthala R&D Institute of science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering Shri Vishnu Engineering College for Women West Godavari Andhra Pradesh India Department of Artificial Intelligence and Data Science KoneruLakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Chennai Tamil Nadu India

In general, applications on a densely populated network are slower. When there are no opportunities to interact with the devices on the network, the user is forced to communicate at some cost. Thus, the inconsistency that exists there increases the cost over that dense network. The single way to evaluate prospect usage is to look at that have used in the earlier period. This paper proposes an upgraded approach to upgrading existing services within the Ultra Dense cloud Network (UDN). In this way the cost for the services available there is calculated in advance and a system is developed to manage it effectively. This proposed method clearly shows that the effective cost can be managed by combining high-costservices and low-costservices separately. This will help to manage the various communication processes to achieve high effectiveness in Ultra Dense cloud Network (UDN). The proposed method achieves 93.28% of Cost-effective Data Management.49% of Application log failure, 42 % of system log failure, 98% of network log management, 96% of security log management, 99% cost effective management.

关键词： Costs Mobility models machine learning Knowledge discovery Scheduling Energy efficiency Concurrent engineering

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Precise Facial Landmark Detection by Reference Heatmap Transformer

arXiv

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arXiv 2023年

作者： Wan, Jun Liu, Jun Zhou, Jie Lai, Zhihui Shen, Linlin Sun, Hang Xiong, Ping Min, Wenwen The School of Information and Safety Engineering Zhongnan University of Economics and Law Wuhan430073 China The Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore The College of Computer Science and Software Engineering Shen zhen University Shenzhen518060 China The Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518060 China College of Computer and Information Technology China Three Gorges University HuBei Yichang China The School of Information Science and Engineering Yunnan University Yunnan Kunming650091 China

Most facial landmark detection methods predict landmarks by mapping the input facial appearance features to landmark heatmaps and have achieved promising results. However, when the face image is suffering from large poses, heavy occlusions and complicated illuminations, they cannot learn discriminative feature representations and effective facial shape constraints, nor can they accurately predict the value of each element in the landmark heatmap, limiting their detection accuracy. To address this problem, we propose a novel Reference Heatmap Transformer (RHT) by introducing reference heatmap information for more precise facial landmark detection. The proposed RHT consists of a Soft Transformation Module (STM) and a Hard Transformation Module (HTM), which can cooperate with each other to encourage the accurate transformation of the reference heatmap information and facial shape constraints. Then, a Multi-Scale Feature Fusion Module (MSFFM) is proposed to fuse the transformed heatmap features and the semantic features learned from the original face images to enhance feature representations for producing more accurate target heatmaps. To the best of our knowledge, this is the first study to explore how to enhance facial landmark detection by transforming the reference heatmap information. The experimental results from challenging benchmark datasets demonstrate that our proposed method outperforms the state-of-the-art methods in the literature. Copyright © 2023, The Authors. All rights reserved.

关键词： Face recognition

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Integrated IoT-Based Smart Home Security System: Real-Time Hazard Detection and Alerts Using Multi-Sensor Fusion

Integrated IoT-Based Smart Home Security System: Real-Time H...

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Intelligent & Innovative Practices in engineering & Management (IIPEM), International Conference on

作者： A M S V Sushma A Aswini Priyanka A N G Lakshmi Narendra Khatri Harish Sharma Department of Electrical and Electronics Engineering S R K R Engineering College Bhimavaram Andhra Pradesh India Department of Computer Science and Design Engineering S R K R Engineering College Bhimavaram Andhra Pradesh India Department of Electronics and Communication Engineering Sir C.R. Reddy College Engineering Bhimavaram Andhra Pradesh India Department of Mechatronics Manipal Institute of Technology Manipal Acacdemy of Higher Education Manipal India Department of Artificial Intelligence and Machine Learning School of Computer Science and Engineering Manipal University Jaipur Jaipur India

ISBN: (数字)9798350390049

ISBN: (纸本)9798350390056

This paper presents an innovative IoT-based smart home security system that integrates multiple sensors to detect various hazards and provide real-time alerts. Unlike traditional single-function systems, this solution combines motion detection via a PIR sensor, gas leak detection using an MQ-2 sensor, and fire detection through an IR flame sensor into a single, affordable package. The Arduino UNO serves as the central controller, interfaced with a GSM module for instantaneous SMS notifications and supported by an on-site buzzer alarm. Extensive testing in diverse environments demonstrates the system’s exceptional performance, detecting intrusions in under 2 seconds and reporting threats with approximately 89% accuracy, while minimizing false alarms. The integration of smart power management techniques reduces energy consumption compared to conventional systems. This approach not only enhances home security but also offers a scalable and easily deployable solution for both residential and commercial settings. This work addresses the urgent need for an affordable, multi-functional smart home security system and provides a robust framework for future IoT-driven safety solutions.

关键词： Accuracy Fires Smart homes Sensor systems Real-time systems Threat assessment Security Intelligent sensors Gas detectors Testing

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machine learning with Monarch Butterfly Optimization for Prediction of Emergency Patient Admission Status

Machine learning with Monarch Butterfly Optimization for Pre...

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International Conference on Electronics, Communication and Computing Technologies (ICECCT)

作者： S. Vijayarangam S. Vasundhara Nihar Ranjan Beherac Shyamali Das Shanker Chandre R. Rajagopal Department of Computer Science and Engineering Sri Indu College of Engineering and Technology Hyderabad Telangana India Department of Humanities and Mathematics G.Narayanamma Institute of Technology and Science Hyderabad Telangana India Swiss School of Business and Management Geneva Petit-Lancy Switzerland Department of Artificial Intelligence and Machine Learning CMR Institute of Technology AECS layout Bangalore Karnataka India Department of Computer Science & Artificial Intelligence SR University Warangal Telangana India Department of Computer Science & Engineering Alliance College of Engineering & Design Alliance University Bengaluru Karnataka India

Emergency admission is one of the most important resources of healthcare expenditure. The accessibility of predictive methods is support to recognize the admission status of arriving patients and the patient mix that supports managing downstream resources and decreasing overpopulation at emergency department (ED) by restriction boarding delays. In recent times, machine learning (ML) techniques are well enhanced and executed in several applications like health protection, cancer detection, and hospital operations. But, most difficult problem with ML is that each technique has parameter and without optimizing the parameter, attaining a higher accuracy method develops very complex. This study introduces machine learning with Monarch Butterfly Optimization for Prediction of Emergency Patient Admission Status (MLMBO-PEP A) technique. The presented MLMBO-PEP A technique can predict the admission status of the emergency patient. In the presented MLMBO-PEP A technique, data normalization is initially performed to scale the medical data. For predictive process, the MLMBO-PEP A technique uses Dendritic Neuron Model (DRN). The MBO technique is used to optimize the forecasting outcomes of the DRN model. A widespread simulation study is performed for ensuring the better performance of the MLMBO-PEP A technique. The resultant values implied the improved efficacy of the MLMBO-PEP A technique under different evaluation metrics.

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Development of a Collaborative Wheeled Mobile Robot: design Considerations, Drive Unit Torque Control, and Preliminary Result

Development of a Collaborative Wheeled Mobile Robot: Design ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Mehmet C. Yildirim Mohamadreza Sabaghian Thore Goll Clemens Kö ssler Christoph Jä hne Abdalla Swikir Andriy Sarabakha Sami Haddadin Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich (TUM) Munich Germany Franka Emika GmbH Munich Germany Department of Electrical and Electronic Engineering Omar Al-Mukhtar University (OMU) AlBaida Libya School of Electrical and Electronic Engineering (EEE) Nanyang Technological University (NTU) Singapore

Nowadays, wheeled mobile robots constitute a considerable portion of robots in industrial applications. Generally, regardless of their purpose, these systems are not designed to physically interact with humans, other robots, or the environment. In this study, we present a novel safe autonomous mobile - SAM - robot, which is a torque-controlled compliant robot that is conceived for safe human-robot interaction. This work provides an overview of the development philosophy of the system, its mechanical and mechatronics structure along with control and navigation architecture. Preliminary results show the advantages of the proposed mobile robot while interacting with its surroundings. We believe that this study will bring the wheeled mobile robots one step closer to the proactive interaction with their environment and humans surrounding them.

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Cryo-CACTI: Cryogenic-Aware CACTI for Cache Modeling down to 10K in Advanced 7nm FinFETs

引用

IEEE Transactions on Computers 2025年

作者： Ravipati, Divya Praneetha van Santen, Victor M. Parihar, Shivendra Singh Chauhan, Yogesh Singh Panda, Preeti Ranjan Amrouch, Hussam Indian Institute of Technology Delhi Department of Computer Science and Engineering New Delhi India Technical University of Munich TUM School of Computation Information and Technology Chair of AI Processor Design Munich Institute of Robotics and Machine Intelligence Germany Kanpur Nanolab Department of Electrical Engineering Uttar Pradesh India

Cryogenic circuits are currently employed in fields such as quantum computing, particle detectors, magnetic resonance imaging, and space applications. While cryogenic circuits are being researched, there is limited work on designing cryogenic caches at temperatures below 77K. Moreover, there is no tool to estimate the delay, power, and area of cryogenic caches at advanced technology nodes. Our research focuses on the development of cryogenic caches tailored for the 7nm technology node, operating at 10K. However, a key challenge is the lack of cryogenic measurement data, especially in recent technologies. Consequently, through conducting our own FinFET transistor measurements, we calibrate cryogenic transistor models at 10K. With the 7nm cryogenic transistor data, we model Cryo-CACTI for cryogenic caches (due to cache’s vital role in improving performance and their considerable share in area and power of the processor). Using Cryo-CACTI, our evaluation reveals considerable improvements in the energy efficiency (up to 99%) of cryogenic caches of larger sizes compared to the caches at room temperature (300K). Additionally, we explore alternative cache configurations at circuit-level to optimize cryogenic operation. Furthermore, we use Cryo-CACTI to explore the performance/energy consumption of cryogenic caches while simulating workloads such as SPEC CPU2017 and machine learning via neural networks. © 1968-2012 IEEE.

关键词： Combinatorial circuits

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design and 3D Printing of Lower Limb Prosthetic Socket *

Design and 3D Printing of Lower Limb Prosthetic Socket *

引用

IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Sheng Li Bin Xie Ye Chen Xinyu Wu Guoxin Fang Yan Zhang Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China State Key Laboratory of Powder Metallurgy Central South University Changsha Hunan China

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

The prosthetic socket is a crucial interface connecting the residual limb to the prosthetic device, significantly affecting force transmission and wearer comfort. This work presents a comprehensive framework for design, simulation, and fabrication of the prosthetic socket. A 3D model of the residual limb, including the skeleton model and skin contour, is reconstructed from CT scan data. Using this model, the prosthetic socket and liner are designed based on biomechanical principles. The interaction force between the residual limb and the prosthetic socket and liner is simulated via finite element analysis (FEA) when the body weight of a below-knee amputee exerts on the prosthetic socket. Finally, the prosthetic socket and residual limb are fabricated using additive manufacturing (AM) technology, and a soft prosthetic liner is made of ethylene-vinyl-acetate (EVA) polymer. Clinical trials on a below-knee amputee were conducted to preliminarily test the prosthetic socket’s performance.

关键词： Limbs Solid modeling Sockets Biological system modeling Force Three-dimensional printing Skin Data models Finite element analysis Prosthetics

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SGCN:Sparse graph convolution network for pedestrian trajectory prediction

arXiv

引用

arXiv 2021年

作者： Shi, Liushuai Wang, Le Long, Chengjiang Zhou, Sanping Zhou, Mo Niu, Zhenxing Hua, Gang School of Software Engineering Xi'an Jiaotong University China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China JD Finance America Corporation Machine Intelligence Lab Alibaba Group China Wormpex AI Research

Pedestrian trajectory prediction is a key technology in autopilot, which remains to be very challenging due to complex interactions between pedestrians. However, previous works based on dense undirected interaction suffer from modeling superfluous interactions and neglect of trajectory motion tendency, and thus inevitably result in a considerable deviance from the reality. To cope with these issues, we present a Sparse Graph Convolution Network (SGCN) for pedestrian trajectory prediction. Specifically, the SGCN explicitly models the sparse directed interaction with a sparse directed spatial graph to capture adaptive interaction pedestrians. Meanwhile, we use a sparse directed temporal graph to model the motion tendency, thus to facilitate the prediction based on the observed direction. Finally, parameters of a bi-Gaussian distribution for trajectory prediction are estimated by fusing the above two sparse graphs. We evaluate our proposed method on the ETH and UCY datasets, and the experimental results show our method outperforms comparative state-of-the-art methods by 9% in Average Displacement Error (ADE) and 13% in Final Displacement Error (FDE). Notably, visualizations indicate that our method can capture adaptive interactions between pedestrians and their effective motion tendencies. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives

Integrated Bi-Manual Motion Generation and Control shaped fo...

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IEEE-RAS International Conference on Humanoid Robots

作者： Jonathan Vorndamme João Carvalho Riddhiman Laha Dorothea Koert Luis Figueredo Jan Peters Sami Haddadin Department of Computer Engineering Technische Universität München (TUM) TUM School of Computation Information and Technology (CIT) Munich Institute of Robotics and Machine Intelligence (MIRMI) Germany Intelligent Autonomous Systems group Technische Universitat Darmstadt (TUD) Germany Center for Cognitive Science TUD Germany

ISBN: (纸本)9798350309805

This work introduces a novel cooperative control framework that allows for real-time reactiveness and adaptation whilst satisfying implicit constraints stemming from proba-bilistic/stochastic trajectories. Stemming from task-oriented sampling and/or task-oriented demonstrations, e.g., learning based on motion primitives, such trajectories carry additional information often neglected during real-time control deployment. In particular, methods such as probabilistic movement primitives offer the advantage to capture the inherent stochasticity in human demonstrations - which in turn reflects human's understanding about task-variability and adaption possibilities. This information, however, is often poorly exploited and, mostly, used during offline trajectory planning stage. Our work instead introduces a novel real-time motion-generation strategy that explicitly exploits such information to improve trajectories according to changes in the environmental condition and robot task-space topology. The proposed solution is particularly well-suited for bi-manual and coordinated systems where the increased kinematic complexity, tightly-coupled constraints and reduced workspace have detrimental effects on the manipula-bility, joint-limits, and are even capable of causing unstable behavior and task-failure. Our methodology addresses these challenges, and improves performance and task-execution by taking the confidence range region explicitly into account whilst maneuvering towards better configurations. Furthermore, it can directly cope with different closed-chain kinematics and task-space topologies, resulting for instance from different grasps. Experimental evaluations on a bi-manual Franka panda robot show that the method can run in the inner control loop of the robot and enables successful execution of highly constrained tasks.

关键词： Trajectory planning Robot kinematics Humanoid robots Kinematics Probabilistic logic Real-time systems Trajectory

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Integrated framework for optimizing the viscoelastic response of laminated composites under hygrothermal conditions

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engineering Structures 2025年 338卷

作者： Ly, Duy-Khuong Vu, Ho-Nam Topal, Umut Han, Jang-Woo Lee, Jaehun Nguyen, Sy-Ngoc Laboratory for Computational Mechanics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Civil Engineering School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Civil Engineering Faculty of Technology Karadeniz Technical University Trabzon Turkey Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul04620 Korea Republic of Department of Mechanical Design Engineering Kumoh National Institute of Technology 39117 Korea Republic of Ho Chi Minh City Viet Nam Vietnam National University-Ho Chi Minh City Ho Chi Minh City Viet Nam

This study introduces an innovative computational framework aimed at optimizing the stacking sequences and thickness of laminated composite structures to achieve optimal viscoelastic responses under various hygrothermal conditions. It is worth noting that computational work for viscoelastic problems typically demands substantial effort and time due to repetitive numerical steps. When incorporating optimization into these problems, the computational requirements increase considerably, making traditional methods less suitable for practical engineering applications. Therefore, the present framework utilizes a smoothed finite element technique named smoothed cell element-discrete shear gap with fast convergence. To reduce the computational workload and avoid the recursive algorithm of viscoelasticity, the computational processes are performed in the transformed Laplace domain to linearize the stress–strain relationship in an integral form. Moreover, the framework is integrated with the balance-enhanced symbiotic organism search algorithm, a robust metaheuristic, to create an efficient optimization computational framework. Through systematic analysis, this research contributes to the advancement of composite material design by offering a practical and effective solution for addressing both viscoelastic behavior and hygrothermal considerations in thin laminated structures. © 2025 Elsevier Ltd

关键词： Delamination

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