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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： De Silva, Ravindi Zaslavsky, Arkady Loke, Seng W. Jayaraman, Prem Prakash Deakin University School of Information Technology Melbourne Australia Swinburne University of Technology Department of Computer Science and Software Engineering Melbourne Australia

ISBN: (纸本)9798350351637

The rapid expansion of Internet of Things (IoT) applications necessitates the demand for efficient IoT middleware platforms, especially Context Management Platforms (CMPs) for accessing real-time contextual information. Current IoT middleware evaluation methods lack accessibility, posing a significant challenge for standardized performance analysis of CMPs. This paper introduces a novel scenario-based context query generation approach for assessing the data retrieval performance of a CMP. The proposed approach enables scene creation using either IoT data or real-world images, employing both data-driven and image-driven scene generation methods. This paper presents the challenges, limitations, and applicability of each approach in scene generation through a qualitative evaluation. The scenes are transformed into scene graphs, enabling inference to identify situations. Both approaches generate queries reflecting dynamic real-world situations, allowing for random query loads to evaluate CMPs fairly. This paper validates the proposed approach using real-world IoT datasets and camera images with a focus on bicycle riding safety use cases. The evaluation provides insights into the contextual completeness of scene graph representations crucial for accurately capturing real-world situations. The proposed approach generates queries of varying complexity, with the only difference being the underlying mechanism of scenario generation, providing a streamlined and user-friendly method for evaluating the data retrieval performance of CMPs. © 2024 IEEE.

关键词： Middleware

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Multivariate Time Series Anomaly Detection Based on Graph Neural Network and Grated Neural Network

Multivariate Time Series Anomaly Detection Based on Graph Ne...

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2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Zhang, Renbin Zhou, Zelin Zuo, Yicong Cui, Yuhang Zhang, Zishi Ministry of Education China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Anhui Hefei230601 China School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9781510666597

Multivariate time series anomaly detection aims to identify time periods in time series data that are abnormal or deviate from historical data patterns. The increasing dimension of multivariate time series data and the complex temporal dependence relationships make anomaly detection more difficult. Therefore, dealing with the temporal and spatial dependence of the time series data becomes the key to anomaly detection. In this paper, we propose an anomaly detection model GNN-GRUAD based on Graph Neural Network and Gate Recurrent Unit, which can obtain the graph structure of inter-feature dependencies without relying on a priori knowledge, and use it together with the temporal data as the input of the graph neural network to capture the data's spatial dependence relationships. The model also incorporates GRU to model the temporal dependencies of the data, to finally predict the data and achieve anomaly detection based on the prediction error. This paper compares with several other baseline models on the SWaT and WADI datasets, and the model in this paper achieves good anomaly detection performance with an improvement of 0.37% and 7.02% compared to the best baseline on the two publicly available datasets, respectively. © 2023 SPIE.

关键词： Time series

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A Learning Sentiment Database for Machine Learning 3

A Learning Sentiment Database for Machine Learning

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3rd International conference on computer, Big Data and Artificial Intelligence, ICCBDAI 2022

作者： Zhang, Jing Hu, Siquan Shi, Zhiguo Han, Shumin School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Innovation School University of Science and Technology Beijing Foshan China

Learners' affective states play a crucial role in learning evaluation, and the external expressions that can directly reflect affect are facial expressions. However, the sample size of the database for the learning process of learners is limited, and most of the existing expression databases are the expressions of ordinary people, which is difficult to support an in-depth study of the emotional states of learners in learning scenarios. In order to better study the influence of learners' emotion on the learning state, we built a learning expression database for machine learning, and at the same time labeled the data with expression-emotion state, and finally formed a database of 8,000 expression images containing 36 learners, which is important for studying learners' emotion state under learning scenarios. © Published under licence by IOP Publishing Ltd.

关键词： Database systems

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Autoencoder-based conditional optimal transport generative adversarial network for medical image generation

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Visual Informatics 2024年第1期8卷 15-25页

作者： Jun Wang Bohan Lei Liya Ding Xiaoyin Xu Xianfeng Gu Min Zhang School of Software Technology Zhejiang UniversityNingboZhejiangChina College of Computer Science&Technology Zhejiang UniversityHangzhouZhejiangChina Department of Pathology Sir Run Run Shaw HospitalZhejiang University School of MedicineHangzhouZhejiangChina College of Biomedical Engineering&Instrument Science Zhejiang UniversityHangzhouZhejiangChina Department of Computer Science State University of New York at Stony BrookStony BrookNYUSA

Medical image generation has recently garnered significant interest among ***,the primary generative models,such as Generative Adversarial Networks(GANs),often encounter challenges during training,including mode *** address these issues,we proposed the AECOT-GAN model(Autoencoder-based Conditional Optimal Transport Generative Adversarial Network)for the generation of medical images belonging to specific *** training process of our model comprises three fundamental *** training process of our model encompasses three fundamental ***,we employ an autoencoder model to obtain a low-dimensional manifold representation of real ***,we apply extended semi-discrete optimal transport to map Gaussian noise distribution to the latent space distribution and obtain corresponding labels *** procedure leads to the generation of new latent codes with known ***,we integrate a GAN to train the decoder further to generate medical *** evaluate the performance of the AE-COT-GAN model,we conducted experiments on two medical image datasets,namely DermaMNIST and *** model’s performance was compared with state-of-the-art generative *** show that the AE-COT-GAN model had excellent performance in generating medical ***,it effectively addressed the common issues associated with traditional GANs.

关键词： Medical image generation Mode collapse Mode mixing Optimal transport Generative adversarial networks

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Temperature Sensor Based on a Plasmonic MIM Waveguide with a Grill-Shaped Cavity 6

Temperature Sensor Based on a Plasmonic MIM Waveguide with a...

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6th Iranian International Conference on Microelectronics, IICM 2024

作者： Ahadi, Mahsa Ghanavati, Mohammad Vahed, Hamid Karami, Mohammad Azim Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran School of Electrical Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9798331511371

This paper presents the design and simulation of a plasmonic refractive index (RI) sensor and a temperature sensor. The suggested design comprises a MIM waveguide integrated with a grill-shaped rectangular cavity. Simulations were performed for two configurations: one with a solitary cavity and another with two cavities. The RI sensitivity was determined to be 1681.42 nm/RIU. In addition, temperature sensitivity was evaluated by employing two dielectric materials, namely ethanol and polydimethylsiloxane, which exhibited temperature sensitivities of 0.475 nm/°C and 0.67 nm/°C, respectively. The plasmonic sensor being suggested exhibits promising capabilities for utilization in nanosensing and industrial environments. © 2024 IEEE.

关键词： MIM devices

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Electron modulation by atomic Ir site decoration in porous Co/N co-doped carbon for electrocatalytic hydrogen evolution

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Nano Research 2023年第2期16卷 2011-2019页

作者： Youkui Zhang Zitong Yan Yeli Gao Yaqin Fu Wenhao Li Yunxiang Lin Chuanqiang Wu Yujuan Pu Tao Duan Li Song State Key Laboratory of Environment-Friendly Energy Materials National Co-Innovation Center for Nuclear Waste Disposal and Environmental SafetySouthwest University of Science and TechnologyMianyang 621010China National Synchrotron Radiation Laboratory Chinese Academy of Sciences(CAS)Center for Excellence in NanoscienceUniversity of Science and Technology of ChinaHefei 230029China Institute of Physical Science and Information Technology School of Materials Science and EngineeringAnhui Key Laboratory of Information Materials and DevicesKey Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationAnhui UniversityHefei 230601China College of Chemistry and Chemical Engineering Chongqing UniversityChongqing 401331China

The rational design of materials at atomic scale as efficient and stable electrocatalysts for hydrogen evolution reaction(HER)is critical for energy ***,we report a novel hybrid nanostructure with iridium(Ir)and cobalt(Co)atomic pair configuration anchored in porous nitrogen-doped carbon(pNC)nanosheets(denoted as IrCo-pNC)for electrocatalytic *** investigations and theoretical calculations reveal that the interaction between Ir and Co species in pNC promotes electron accumulation and depletion around isolated Ir and Co atoms,respectively,resulting in a local asymmetry electron density *** functional theory calculations also suggest that the electrons transfer from Co to adjacent Ir atom causing the down shift of the d-band center of Ir 5d in IrCo-pNC catalyst,thus optimizing the adsorption of hydrogen on Ir *** as-prepared IrCo-pNC exhibits significant HER performance with an overpotential of 21 mV to achieve a current density of 10 mA·cm^(−2)in 0.5 M *** work provides insight into the role of asymmetry electron density distribution in nanomaterials in regulating HER electrocatalysis.

关键词： electron modulation iridium decoration porous carbon electrocatalysis hydrogen evolution reaction

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Research on Frequency-Adaptive GNSS/IMU Coupled Conductor Galloping Monitoring technology 5

Research on Frequency-Adaptive GNSS/IMU Coupled Conductor Ga...

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5th International Conference on Clean Energy and Electric Power engineering, ICCEPE 2024

作者： Wang, Ning Wang, Zuomin Zhang, Ruiyong Li, Xin Chen, Zhengyu Li, Buhui Chen, Jie Wu, Cheng Zhao, Mengyao China Energy Engineering Group Jiangsu Power Design Institute Co. Ltd. China School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei230009 China

ISBN: (纸本)9798350390315

With the rapid development of power transmission line construction in China, the stable operation of overhead power transmission lines has become crucial for national energy security. The frequent occurrence of safety incidents in power transmission infrastructure due to conductor galloping has led to increased focus in power sectors. Addressing the deficiencies in accuracy and coverage of existing conductor galloping monitoring technologies, this paper presents a design for a four-split interval rod conductor galloping monitoring device. This device integrates multiple sensors and RTK-based positioning technology. Additionally, it employs a frequency-adaptive GNSS/IMU loosely coupled positioning technology, achieving high-precision measurement of the conductor's status and comprehensive monitoring coverage. Experimental results indicated that this device demonstrates substantial potential for practical engineering applications. © 2024 IEEE.

关键词： Precision engineering

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Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study 1

Assessing Cross-Cultural Alignment between ChatGPT and Human...

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1st Workshop on Cross-Cultural Considerations in NLP, C3NLP 2023

作者： Cao, Yong Zhou, Li Lee, Seolhwa Cabello, Laura Chen, Min Hershcovich, Daniel Huazhong University of Science and Technology China Department of Computer Science University of Copenhagen Denmark University of Electronic Science and Technology of China China Technical University of Darmstadt Germany School of Computer Science and Engineering South China University of Technology China

ISBN: (纸本)9781959429517

The recent release of ChatGPT has garnered widespread recognition for its exceptional ability to generate human-like responses in dialogue. Given its usage by users from various nations and its training on a vast multilingual corpus that incorporates diverse cultural and societal norms, it is crucial to evaluate its effectiveness in cultural adaptation. In this paper, we investigate the underlying cultural background of ChatGPT by analyzing its responses to questions designed to quantify human cultural differences. Our findings suggest that, when prompted with American context, ChatGPT exhibits a strong alignment with American culture, but it adapts less effectively to other cultural contexts. Furthermore, by using different prompts to probe the model, we show that English prompts reduce the variance in model responses, flattening out cultural differences and biasing them towards American culture. This study provides valuable insights into the cultural implications of ChatGPT and highlights the necessity of greater diversity and cultural awareness in language technologies. © 2023 Association for Computational Linguistics.

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BAF45D regulates spinal cord neural stem/progenitor cell fate through the SMAD-PAX6 axis

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Genes & Diseases 2023年第2期10卷 366-369页

作者： Xueying Chen Xiujuan Hu Jing Jiang Jie Tao Lihua Liu Shengyun Fang Yuxian Shen Qingsong Hu Chao Liu School of Basic Medical Sciences Anhui Medical UniversityHefeiAnhui 230032China Department of Histology and Embryology Institute of Stem Cell and Tissue EngineeringAnhui Medical UniversityHefeiAnhui 230032China Division of Life Sciences and Medicine University of Science and Technology of ChinaThe First Affiliated Hospital of USTCHefeiAnhui 230001China Institute of Clinical Pharmacology Anhui Medical UniversityHefeiAnhui 230032China Center for Biomedical Engineering and Technology University of MarylandBaltimoreMD 21201USA

Mutations in BRG1-associated factor 45D (BAF45D, also known as double PHD fingers 2 (DPF2)) are linked to Coffin-Siris syndrome (CSS).1 However, the underlying molecular mechanisms remain ill-defined. Here, we identified that wild-type but not CSS-associated BAF45D mutants increased the expression of PAX6,2 a neural stem cell marker, and phosphorylated SMAD3 (p-SMAD3) in spinal cord neural stem cells (NSCs) derived from H9 human embryonic stem cells. Both BAF45D and SMAD3 are required for the induction of p-SMAD3 and PAX6 together with STAT3 and SMAD7 by retinoic acid (RA). In the presence of RA, BAF45D knockdown decreased the expression of genes that regulate stem cell pluripotency. Moreover, the same genes in the spinal cord NSCs had more binding sites with BAF45D than those in H9 cells. Furthermore, Gene Ontology (GO) assay results indicated that BAF45D targets more pathways responsible for stem cell maintenance in NSCs. Finally, BAF45D is associated with BRG1, p-SMAD3, and PAX6. Together, these findings suggest a role for BAF45D in modulating PAX6 expression through SMAD signaling, highlighting the importance of BAF45D in neural stem/progenitor cell fate commitment.

关键词： PAX6 progenitor SMAD

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Container-based data-intensive application scheduling in hybrid cloud-edge collaborative environment

Container-based data-intensive application scheduling in hyb...

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作者： Tang, Bing Luo, Jincheng Zhang, Jiaming School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan China Hunan Key Laboratory for Service Computing and Novel Software Technology Hunan University of Science and Technology Hunan Xiangtan China School of Information and Communication Engineering Guangzhou Maritime University Guangdong Guangzhou China School of Information Engineering Wuhan University of Technology Hubei Wuhan China

Container virtualization technology represented by Docker has been widely used in the industry due to its advantages of lightweight, fast deployment, and easy portability. It can bring convenience to system deployment, operation, and maintenance. This article considers the implementation of AI-based IoT applications based on Docker and container technology in a cloud-edge collaborative environment. Three typical data-intensive applications, preprocessing, training, and inference in machine learning, are deployed using Docker containers. For these three types of tasks, this article proposes a container-based data-intensive application scheduling framework. Using an attribute-based data-driven method, a new scheduling approach considering multiple weighting factors is proposed, which is called DICS-OPT. The cloud nodes and edge nodes are scored and sorted uniformly. The container is scheduled to the node with the highest score, and then the task data is transmitted to the node to execute the task. NSGA-III-based genetic algorithm has been proposed to search for the optimal weighting factors. This article introduces the implementation of the prototype system and builds a cloud-edge collaborative testbed consisting of Raspberry Pis and PCs. The performance evaluation results indicates that the proposed scheduling approach outperforms existing approaches. Compared with existing approaches, DICS-OPT improves the average edge resource utilization by 10.05% to 69.04%, and saves the cloud resource cost by 16.02% to 36.68%. © 2023 John Wiley & Sons Ltd.

关键词： Edge computing

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