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13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Çinar, Necip Kaya, Buket Kaya, Mehmet Dicle University Department of Computer Engineering Diyabakir Turkey Firat University Department of Electronics and Automation Elaziǧ Turkey Firat University Dept. of Computer Engineering Elaziǧ Turkey

Recently, with the production of high-capacity computers, artificial intelligence methods have been used in many areas. In particular, in the field of health, artificial intelligence methods are used to detect diseases and determine the treatments to be applied. Deep learning methods, a sub-branch of artificial intelligence, show a high success in diagnosing many diseases thanks to its deep CNN networks. In this study, firstly, it was tried to determine which deep learning methods are more successful for the detection of brain stroke from computerized tomography images. This study is of great importance in terms of determining which deep learning architectures we will focus on in our future studies on brain stroke. In this study, brain stroke disease was detected from CT images by using the five most common used models in the field of image processing, one of the deep learning methods. The pre-trained ResNetl01, VGG19, EfficientNet-B0, MobileNet-V2 and GoogleNet models were run with the same dataset and same parameters. As a result, the EfficientNet-B0 architecture showed the highest performance with 97.93% accuracy. ResNetl01, VGG19, MobileNet-V2 and GoogleNet models showed 94.32%, 97.28%, 92.30% and 91.61% accuracy rates, respectively. With this study, it was concluded that the EfficientNet architecture is more suitable for the detection of brain stroke disease from CT images. © 2023 IEEE.

关键词： Diagnosis

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Aerial Reliable Collaborative Communications for Terrestrial Mobile Users via Evolutionary Multi-Objective Deep Reinforcement Learning

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5731-5748页

作者： Sun, Geng Xiao, Jian Li, Jiahui Wang, Jiacheng Kang, Jiawen Niyato, Dusit Mao, Shiwen the College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China the College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore the School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore the School of Automation Guangdong University of Technology Guangzhou510641 China the Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States

—Unmanned aerial vehicles (UAVs) have emerged as the potential aerial base stations (BSs) to improve terrestrial communications. However, the limited onboard energy and antenna power of a UAV restrict its communication range and transmission capability. To address these limitations, this work employs collaborative beamforming through a UAV-enabled virtual antenna array to improve transmission performance from the UAV to terrestrial mobile users, under interference from non-associated BSs and dynamic channel conditions. Specifically, we introduce a memory-based random walk model to more accurately depict the mobility patterns of terrestrial mobile users. Following this, we formulate a multi-objective optimization problem (MOP) focused on maximizing the transmission rate while minimizing the flight energy consumption of the UAV swarm. Given the NP-hard nature of the formulated MOP and the highly dynamic environment, we transform this problem into a multi-objective Markov decision process and propose an improved evolutionary multi-objective reinforcement learning algorithm. Specifically, this algorithm introduces an evolutionary learning approach to obtain the approximate Pareto set for the formulated MOP. Moreover, the algorithm incorporates a long short-term memory network and hyper-sphere-based task selection method to discern the movement patterns of terrestrial mobile users and improve the diversity of the obtained Pareto set. Simulation results demonstrate that the proposed method effectively generates a diverse range of non-dominated policies and outperforms existing methods. Additional simulations demonstrate the scalability and robustness of the proposed CB-based method under different system parameters and various unexpected circumstances. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Markov processes

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Robot Hand-eye Calibration Method Incorporating Filtering Techniques 25

Robot Hand-eye Calibration Method Incorporating Filtering Te...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Guo, Peng Si, Weiyong Yang, Chenguang School Of Automation Science And Engineering South China University Of Technology Guangzhou China School Of Computer Science And Electronic Engineering University Of Essex Colchester United Kingdom University Of Liverpool Department Of Computer Science Liverpool United Kingdom

ISBN: (纸本)9798350340266

Hand-eye calibration is the foundation of visual servo for robotic tasks, aiming to determine the rigid transfor-mation matrix between the robot and the vision system. The accuracy of hand-eye calibration affects the robot's ability to accurately perform tasks. The classical form of the hand-eye calibration is to solve the equation 'AX = XB'. The algorithms for solving this problem mainly divided into two categorie: step-wise and simultaneous solutions for the rotation and translation components. Due to the noise in the collected data, the calculation accuracy is inevitably affected. In this paper, we introduce a filtering approach for hand-eye calibration. First, we design the movement path of the robot arm end effector, then summarize the variation patterns of parameters, and finally use these patterns to filter the actually collected data. Experimental results on our custom dataset and the robot arm platform demonstrate that our proposed method can reduce reprojection error and improve the accuracy of hand-eye calibration. © 2024 IEEE.

关键词： Calibration

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India's Stake in Emerging Technology - A Review 18

India's Stake in Emerging Technology - A Review

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Singh, Sugandha China Ramu, S. Lalit, Ruchika Sgt University Department of Computer Science and Engineering Gurugram India Chaitanya Bharathi Institute of Technology Department of Computer Science and Engineering Hyderabad India University School of Automation and Robotics Ggsipu East Campus New Delhi India

ISBN: (纸本)9789380544519

Emerging technologies of today are altering the way we think about the built environment. In the meantime, many technologies have undergone revolutionary changes, and India, an expanding nation, offers opportunities for development in several new areas. The goal of the study is to show how organizations need to adapt their perspective and create new strategies for emerging technologies such as artificial intelligence (AI), machine learning (ML), big data, quantum, and space exploration in light of the swift advancements in technology. This paper presents that although India has come across a lot of advancements in this era of emerging technology, certain challenges have been faced in aspects like adapting, feasibility, and approval which brought many changes across the country, which in turn is impacting the pace to transform the country towards Industry 4.0 and Industry 5.0. Therefore a study is presented to understand the impact of emerging technologies for countries coming up as Industry 4.0 and Industry 5.0. This paper emphasizes on for India's initiatives for emerging technologies to come up as VIKSIT BHARAT @2047. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Artificial Intelligence Big Data Fabrication Hypersonic platforms Industry 4.0 and Industry 5.0 Quantum computing

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Computing Technology Acoustic Inversion engineering Seismic Data and Its Application for Construction Purposes 16

Computing Technology Acoustic Inversion Engineering Seismic ...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Goshko, Elena Yu. Zerkal, Sergey M. Ivanov, Sergey S. Automation and Computer Engineering Novosibirsk State Technical University Novosibirsk Russia Department of Computer Science Siberian University of Consumer Cooperation Novosibirsk Russia

ISBN: (纸本)9798350330885

The Shallow-depth engineering seismic studies are carried out in the upper part of the geological section, which is characterized by sharp vertical and horizontal variability of the physical properties of rocks. Additional difficulties in observing and recording caused by seismic vibrations of the soil are associated with the influence of unavoidable interference: ground (wind, sound noise), geological interference (noise of rock cracking during unloading of tectonic stress), man-made interference (the influence of power lines on signal reception, trembling of the soil during the work of construction or quarry mechanisms, cars, trains). The allocation of a useful signal against the background of interference requires the organization of seismic work with repeated repetition of excitations - the accumulation of signals, as well as the development of special computational algorithms and the use of new technologies for processing engineering seismic data. The article considers a computational algorithm of acoustic inversion, which transforms a wave seismic section into a discrete section of pulsed reactions of the medium - effective reflection coefficients. It has a compact discrete appearance and is easier for visual observation and further physico-geological interpretation. The computer technology of application of the acoustic inversion algorithm is implemented. The application of this technology to real engineering seismic data obtained on the territory of the construction of a high-rise building made it possible to determine the parameters of the geological foundation lying under the ground surface of the construction site, namely: the depth of occurrence, relief, areas of increased disintegration. The established properties of the geological foundation are necessary for the analysis of the strength and stability of soils during the construction and operation of a high-rise structure for its safety. © 2023 IEEE.

关键词： Foundations

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Trust Assessment Model for Visual Image-Based Human-Robot Interaction Under Known and Unknown Threats 16th

Trust Assessment Model for Visual Image-Based Human-Robot I...

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16th International Conference on Social Robotics, ICSR + BioMed 2024

作者： Li, Heqing Li, Xinde Liu, Erfeng Ge, Shuzhi Sam School of Cyber Science and Engineering Southeast University Nanjing China School of Automation Southeast University Nanjing China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

ISBN: (纸本)9789819789627

Visual imagery is a critical perceptual source in human-robot interaction (HRI), extensively applied in various domains such as robotic navigation, target detection, and task planning. Aerial robots, also known as UAVs, are the typical representatives of teleoperation robots. The substantial distance between humans and remotely operated robots, coupled with the dynamic and open environments these robots navigate, exposes image-based HRI to significant security risks from both known and unknown threats. The trustworthiness of data sources is a fundamental prerequisite for ensuring the security of HRI systems. However, the multidimensionality of trust factors and the uncertainty of trust evidence have constrained its practical application. To advance this field, we have innovatively proposed a trust evaluation scheme based on multidimensional evidence fusion within the Belief Functions (BFs) framework. This scheme constructs an adaptive trust evaluation model capable of addressing both known and unknown threats. For known threats, we developed coarse-grained multidimensional trust elements and employed multiple lightweight SVM submodels to construct Basic Belief Assignments (BBAs), thereby achieving direct trust modeling and enabling rapid trust evaluation of images. Conversely, for unknown threats, we utilized pretrained models to establish fine-grained multidimensional trust elements, implementing indirect trust modeling through trust recommendation, thus facilitating indirect trust evaluation of images. We further combined direct and indirect trust to derive a overall trust assessment of the images, achieving adaptive dynamic trust evaluation in image-based HRI. Additionally, to more accurately represent image trustworthiness, we introduced a BBAs weighted fusion method, which aids in more rational trust aggregation. To validate the efficacy of our proposed method, we conducted experiments on a real aerial image dataset. The results demonstrate that our approach ef

关键词： Human robot interaction

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A Constraints-based Dynamic Time Warping Method for Gesture Recognition with Kinect 23

A Constraints-based Dynamic Time Warping Method for Gesture ...

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3rd International Conference on Robotics and Control engineering, RobCE 2023

作者： Liu, Jiaojiao Lu, Xiong Yin, Hongbin Tao, Xianglin Zhang, Chuanlong Quigley, Aaron College of Automation Engineering Nanjing University of Aeronautics and Astronautics China School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9781450398107

Gesture recognition is still actively researched in non-contact human-computer interaction (HCI), where the Dynamic Time Warping (DTW) algorithm is commonly employed. However, the computation load of traditional DTW algorithms during the matching phase presents a challenge for gesture recognition, especially when the number of reference gestures in the template library increases. In order to solve this problem, a Constraints-based Dynamic Time Warping (CDTW) method is proposed in this paper, including Global-Path Constraint, First-Frame Constraint, and Feature-Vector Constraint. These three constraints are expected to limit the region of the warping path, exclude several reference gestures from the template library, and reduce computation load directly with reduced elements of the feature vector. To verify the proposed CDTW method, Microsoft Kinect-based comparative experiments with the traditional DTW method have been carried out. Experimental results show that our CDTW method boosts the efficiency of gesture recognition with a 17% decrease in recognition time and a 3% increase in average recognition accuracy, compared to the traditional DTW algorithm. © 2023 ACM.

关键词： Gesture recognition

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TEPG:a traffic engineering based power-aware greedy routing algorithm in backbone networks with bundled links

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Frontiers of computer Science 2024年第1期18卷 243-245页

作者： Jinhong ZHANG Xingwei WANG Ruixia LI Bo YI Min HUANG Dongxing SHUI School of Electronic and Information Engineering West Anhui UniversityLu’an 237012China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China School of Computer Science and Engineering Northeastern UniversityShenyang 110169China School of Information Science and Engineering Northeastern UniversityShenyang 110819China

1 Introduction and main contributions Various power-aware solutions have been proposed to address the alarming energy waste and consequent serious environmental issues since Gupta and Singh initiated the seminal study on green networking problem in *** of the researches concentrated their efforts on power-aware networking under the non-bundled link scenarios by leveraging the dynamic power management based Low Power Idle(LPI)policy which was defined and standardized in the IEEE 802.3az ***,in modern backbone networks,pairs of routers are typically connected,for each traffic direction,by multiple physical links that form one logical bundled link,which is the link aggregation technique defined and standardized in IEEE 802.1AX.

关键词： power bundle backbone

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Quality-Relevant Modeling and Monitoring of Industrial Cyber-Physical Systems: The Semi-Supervised Dynamic Latent Variable Models

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 39-47页

作者： Zhou, Le Wang, Yaoxin Wu, Yuanqing He, Shenghuang Song, Zhihuan Zhejiang University of Science and Technology Department of Automation and Electrical Engineering Hangzhou310023 China Guangdong University of Technology Department of Automation Guangzhou510006 China Dongguan University of Technology Department of Computer Science and Technology Dongguan523808 China Ningbo Industrial Internet Institute Ningbo315012 China Zhejiang University Department of Control Science and Engineering Hangzhou310027 China

In modern industrial cyber-physical systems, a mass of process variables has been obtained by the high-sampling online sensors. Meanwhile, the key quality indexes are usually obtained infrequently from the laboratory. Hence, these quality variables are with low sampling rate. To avail of the complete process and quality variables with various sampling rates in the dynamic processes, a set of semi-supervised dynamic latent variable models are proposed for dynamic modeling and quality-relevant monitoring. The proposed models have built a unified structure to consider both the auto-correlations and cross-correlations between the process and quality variables with unbalanced sampling sizes. Hence, the feature extraction of the time series data is dynamically adjusted under the guidance of the quality variables. Then, the quality-relevant monitoring schemes are proposed, which is validated by a numerical case and an actual wastewater treatment process. © 2024 IEEE. All rights reserved.

关键词： Indexes Probabilistic logic Kalman filters Noise Cyber-physical systems Analytical models Parameter estimation Time series analysis Process monitoring Numerical models

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Modeling a fuzzy expert system for predicting customers’ behavioral intention for restaurant business through parallel prediction of perceived values and satisfactions

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International Journal of Information Technology (Singapore) 2025年第2期17卷 1007-1014页

作者： Akhtaruzzaman, M. Shahryer, Fahim Halder, Sachitra Tanvin, Jamal Uddin Department of Computer Science and Engineering Military Institute of Science and Technology (MIST) Mirpur Cantonment Dhaka 1216 Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

This paper focuses on the modeling of a recommendation process for the restaurant industry. It is a challenge job for a restaurant owner to ascertain the intentions of customers to evaluate their services, further improve their profit margin. So, the objective of this study is to design a fuzzy-based prediction model of customers’ intentions for a fine dining experience. To facilitate a comparative analysis and to identify the optimal approach, various membership functions (MF) and de-fuzzification methods are employed along with the analysis of the correlational behavior among various input subsets. Results have shown that CoA method with triangular MF are well enough to implement the model. The fuzzy-correlation analysis presents various levels of membership strengths for a same recommendation score in some cases. Moreover, the evaluation of the proposed model based on a custom dataset shows prominent results with as 0.938. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Customer intension Customer satisfaction FIS Perceived value Recommendation

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