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3rd International Conference on Testing Technology and Automation engineering, TTAE 2023

作者： Wang, Wanting Wang, Siming Han, Taoguo School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China College of Computer and control engineering Northeast Forestry University Harbin150000 China

ISBN: (纸本)9781510674769

This paper presents a novel approach to address the lateral control issue in trajectory tracking for autonomous cars. Traditional model-free adaptive control algorithms have some limitations, prompting the development of an enhanced data-driven model-free adaptive control scheme. More precisely, inside a specified trajectory, the vehicle's issue of lateral control is converted into a problem of tracking the preview-deviation-angle. A dynamic linearized data model is developed for the lateral control of autonomous cars, taking into account the input and output data. To enhance the steering angle control rate, a time-varying proportional control term is incorporated. An enhanced trajectory tracking control technique for the MFAC system is proposed, followed by a demonstration of its convergence. The simulation findings demonstrate that the IMFAC scheme exhibits a superior output response compared to both MFAC and PID in both low-speed and high-speed scenarios. Furthermore, the IMFAC system is capable of achieving autonomous vehicle path tracking. © 2024 SPIE.

关键词： Autonomous vehicles

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Classification of Unbalanced Data Based on Bayesian Optimal Neural Network Model

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第3期9卷 1427-1440页

作者： Ye, Li-Zhu Alkawaz, Mohammed Hazim Johar, Md Gapar Md School of Information Technology and Engineering Guangzhou College of Commerce Guangzhou511363 China School of Graduate Studies Management and Science University 40100 Shah Alam Selangor Malaysia Department of Computer Science College of Education for Pure Science University of Mosul Mosul41002 Iraq Software Engineering and Digital Innovation Center Management and Science University Shah Alam40100 Malaysia

Aiming at the unbalanced problem of big data classification, this paper proposes a classification method of unbalanced data on the ground of Bayesian optimal neural network model. The method firstly uses Optimized Graph Convolutional Network (OGCN) network to carry out message passing mechanism in data graph, designs neural network model with self-attention pooling and mean maximization pooling, and then uses Bayes optimization to update the posterior probability of optimization function by constantly updating the probability model and evaluating the objective function. Effectively solve the problem of speed and optimal solution of hyperparameter optimization in the neural network model. Secondly, the model is used for data set training to obtain the weight of the entire network. Secondly, the unbalanced data is mixed sampling to reduce the number of negative samples. Finally, the capability of the model was verified on the CiteSeer dataset. Experimental results showed that the accuracy rate, accuracy rate and recall rate of the proposed algorithm were 0.974, 0.982 and 0.973, respectively, which effectively improved the accuracy rate, accuracy rate and recall rate of unbalanced data classification compared with other algorithms. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Neural network models

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A Survey on the Emerging Trend of Human Microchip Implants And Their Potential

A Survey on the Emerging Trend of Human Microchip Implants A...

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Al Mansouri, Ltifa Mohammed Khalifa Alnajjar, Fady College of It United Arab Emirates University Department of Computer Science and Software Engineering Al Ain United Arab Emirates

ISBN: (纸本)9781665454742

Human microchip implants are small devices that are implanted into the body for various purposes including storing and transmitting information, monitoring health or location, and providing access to facilities or systems. Although human microchip implants offer numerous advantages, their adoption remains low in the public sector. This article presents a comprehensive survey on the emerging trend of human microchip implants and their potential uses in various fields. In addition to introducing the general concept of microchip implants, the work discusses their current and potential future applications. To better understand the direction of this trend, recent case studies of existing applications of human microchip implants are analyzed and presented. The article also explores the barriers to the adoption of human microchip implants and discusses their potential impact on humans, whether positive or negative. © 2023 IEEE.

关键词： Near field communication

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Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation 28th

Self-Sampling Training and Evaluation for the Accuracy-Bi...

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28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Liu, Dugang Qiao, Yang Tang, Xing Chen, Liang He, Xiuqiang Pan, Weike Ming, Zhong College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen China FIT Tencent Shenzhen China

ISBN: (纸本)9783031306778

Research on debiased recommendation has shown promising results. However, some issues still need to be handled for its application in industrial recommendation. For example, most of the existing methods require some specific data, architectures and training methods. In this paper, we first argue through an online study that arbitrarily removing all the biases in industrial recommendation may not consistently yield a desired performance improvement. For the situation that a randomized dataset is not available, we propose a novel self-sampling training and evaluation (SSTE) framework to achieve the accuracy-bias tradeoff in recommendation, i.e., eliminate the harmful biases and preserve the beneficial ones. Specifically, SSTE uses a self-sampling module to generate some subsets with different degrees of bias from the original training and validation data. A self-training module infers the beneficial biases and learns better tradeoff based on these subsets, and a self-evaluation module aims to use these subsets to construct more plausible references to reflect the optimized model. Finally, we conduct extensive offline experiments on two datasets to verify the effectiveness of our SSTE. Moreover, we deploy our SSTE in homepage recommendation of a famous financial management product called Tencent Licaitong, and find very promising results in an online A/B test. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

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Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks

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computers, Materials & Continua 2022年第11期73卷 4179-4192页

作者： R.Uma Mageswari Sara A.Althubiti Fayadh Alenezi E.Laxmi Lydia Gyanendra Prasad Joshi Woong Cho Department of Computer Science and Engineering Vardhaman College of Engineering(Autonomous)HyderabadTelangana501218India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea

Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended *** the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target *** existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia *** energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network *** this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for *** proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum *** proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance *** simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.

关键词： Wireless multimedia sensor networks clustering spider monkey optimization algorithm energy efficiency metaheuristics quantum computing

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An Improved Fault-Tolerant control and Stabilization for Positive Polynomial Fuzzy Systems

An Improved Fault-Tolerant Control and Stabilization for Pos...

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2024 IEEE International Conference on control Science and Systems engineering, ICCSSE 2024

作者： Wang, Ziguang Meng, Aiwen Wang, Mingxuan Li, Zhiquan Yanshan University Key Laboratory of Industrial Computer Control Engineering of Hebei Province Hebei China College of Electronic and Information Engineering Hebei University Hebei China

ISBN: (纸本)9798331517199

This paper presents an improved analysis method to design a fault-tolerant controller for positive polynomial fuzzy systems based on static output feedback as well as actuator faults. Firstly, inspired by the property of fault matrix, a new approach of controller design is presented, and some constraint conditions are introduced to guarantee the stability conditions and posi-tivity conditions to be convex simultaneously. Furthermore, by comparing with the existing methods, this method not only can eliminate the binding to the input matrix B, but also is able to provide a wider range of stability region. Besides, to enhance the relaxation of the stability analysis, we introduce the up-to-date Taylor series membership functions (TSMFs) approximation method such that the information embedded in the membership functions and the state boundary information can be taken into the stability conditions. As a result, on the strength of Lyapunov stability theory, the stability analysis is performed via sum-of-squares (SOS) approach. Finally, a simulation example is given to illustrate the effectiveness and reliability of the proposed method. © 2024 IEEE.

关键词： Fuzzy systems

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UniL: Point Cloud Novelty Detection through Multimodal Pre-training 24

UniL: Point Cloud Novelty Detection through Multimodal Pre-t...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Wang, Yuhan Song, Mofei College of Software Engineering Southeast University Jiangsu Nanjing China Ministry of Education Jiangsu Nanjing China School of Computer Science and Engineering Southeast University Jiangsu Nanjing China

ISBN: (纸本)9798400706868

3D novelty detection plays a crucial role in various real-world applications, especially in safety-critical fields such as autonomous driving and intelligent surveillance systems. However, existing 3D novelty detection methods are constrained by the scarcity of 3D data, which may impede the model's ability to learn adequate representations, thereby impacting detection accuracy. To address this challenge, we propose a Unified Learning Framework (UniL) for facilitating novelty detection. During the pretraining phase, UniL assists the point cloud encoder in learning information from other modalities, aligning visual, textual, and 3D features within the same feature space. Additionally, we introduce a novel Multimodal Supervised Contrastive Loss (MSC Loss) to improve the model's ability to cluster samples from the same category in feature space by leveraging label information during pretraining. Furthermore, we propose a straightforward yet powerful scoring method, Depth Map Error (DME), which assesses the discrepancy between projected depth maps before and after point cloud reconstruction during novelty detection. Extensive experiments conducted on 3DOS have demonstrated the effectiveness of our approach, significantly enhancing the performance of the unsupervised VAE method in 3D novelty detection. Codes are avaliable at https://***/EugeneWon9/UniL. © 2024 ACM.

关键词： Self-supervised learning

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Learning Age of Information-Oriented Energy-Efficient Scheduling with Non-Orthogonal Multiple Access 13

Learning Age of Information-Oriented Energy-Efficient Schedu...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Li, Jinhua Cao, Yi Chan, Tse-Tin Pan, Haoyuan Shenzhen University College of Computer Science and Software Engineering Shenzhen China The Education University of Hong Kong Department of Mathematics and Information Technology Hong Kong

ISBN: (纸本)9798350355079

We propose a deep Q-network (DQN)-based user scheduling scheme aimed at low network-wide age of information (AoI) in a non-orthogonal multiple access (NOMA) uplink status update system. In our system, end users can harvest energy from wireless signals received on the radio-frequency band to extend the lifespan of their batteries. Given the battery replacement cost in many practical scenarios, our objective is to design a scheduling scheme to maintain a low AoI while efficiently utilizing energy harvesting and reducing the number of battery replacements. Considering the instantaneous AoI, remaining energy, and channel condition of end users, we model the user scheduling problem as a Markov decision process (MDP), which is solved by DQN. In particular, the choice of transmission power to save energy while enabling a high NOMA decoding rate is incorporated in the design of DQN. Experiments indicate that our DQN-based scheduling scheme achieves a low average AoI of the system with significantly fewer battery replacements compared to various benchmarking schemes. © 2024 IEEE.

关键词： Markov processes

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Automatic SQL Query Generation from Code Switched Natural Language Questions on Electronic Medical Records

Automatic SQL Query Generation from Code Switched Natural La...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Haodi Nie, Jinyin Liu, Zeming Lei, Dong Song, Yuanfeng Shenzhen University College of Computer and Software Engineering Shenzhen China Microsoft Beijing China WeBank Co. Ltd Ai Group Shenzhen China

ISBN: (纸本)9798350386226

Electronic Medical Records (EMRs) meticulously document patient information in relational databases, presenting a challenging task for medical professionals to effectively retrieve this data. Natural Language Question to SQL query (NL2SQL), a critical task in natural language processing (NLP), shows promising performance in addressing this challenge. However, existing medical NL2SQL studies often focus on generating SQL queries from monolingual questions in English. None of them have studied medical NL2SQL for the Chinese *** Chinese EMRs, the questions are primarily in Chinese, while many medical terms, such as drugs and diseases, are commonly described in English. This phenomenon is generally known as code-switching (CS) in the field. Given that underlying systems are typically monolingual, CS has proven to pose significant accuracy challenges, as observed in many tasks such as Automatic Speech Recognition (ASR) and Machine Translation (MT). However, the potential effects on EMRs NL2SQL have not been explored. In this study, we investigate the CS-NL2SQL problem, focusing on CS in the context of Chinese questions for the NL2SQL task on EMRs. To assess the model's performance on this task, we construct the first CS-NL2SQL dataset named CS-MIMICSQL in medical domains. We then explore different CS-NL2SQL architectures along two dimensions: cascaded (translation followed by SQL generation) vs. end-to-end. Our results demonstrate that the proposed end-to-end structure can outperform much better than the cascaded baselines. © 2024 IEEE.

关键词： Electronic health record

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MLPFormer: MLP-integrated transformer for colorectal histopathology whole slide image segmentation

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Neural Computing and Applications 2025年第6期37卷 4651-4661页

作者： Wang, Yuxuan Li, Dan Li, Xuechen Guo, Yan Zuo, Yanfei Shen, Linlin Department of Computer Science Wenzhou-Kean University Wenzhou China School of Electronics and Information Engineering Wuyi University Jiangmen China Department of Histo Pathology Shanghai Histo Pathology Diagnostic Center Shanghai China College of Computer Sicence and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classified into four different grades, i.e., background, normal, low and high level. However, due to the continuity of lesion development, tissue in different stages has high similarity. Recently, visual transformers have achieved impressive results in different visual tasks, due to their capacity of capturing long-range dependencies. However, due to computational cost, transformer cannot well extract detailed feature, which is important for lesion grading. To accurately segment pathological tissues with high similarity, in this work, we embed the multi-head MLP mixer module in the transformer network to extract cell and edge information. Furthermore, we propose a hierarchical MLP decoder to facilitate multi-scale feature fusion. The proposed transformer, namely MLPFormer, achieves remarkable results against competitive baselines on the Histo-CRC Biopsy dataset. The experimental results demonstrate that MLPFormer significantly outperforms the competitive baselines, i.e., a 3% dice improvement is achieved over the SegFormer series. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image segmentation

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