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8th International Conference on Contemporary Information Technology and Mathematics, ICCITM 2022

作者： Hasan, Mohammed Zaki Al-Rizzo, Hussain Allawi, Manar Mozahim Univeristy of Mosul College of Computer Science Mosul Iraq University of Arkansas Dcstem College System Engineering Dept Little RockAR United States

ISBN: (纸本)9798350334869

Internet of Things (IoT) for environmental applications such as smart homes, campuses, cities, and health care systems are used to connect various wireless devices. Despite the use of the same devices, the reusability of these applications enables developers and software engineers to make enhancements to the development process according to the requirements of end users. However, the large number of variations in IoT technologies makes it hard for the developers or software engineers to select the default features in each application because of compatibility issues among devices. In this paper, Software Product Line (SPL) approach is proposed to design and manage the variabilities and commonalities among smart home applications. An embedded feature selection mechanism is proposed to classify the services by selecting the optimal subset feature. The selected subset features are those that are highly correlated and consistent with other features. The dataset is generated using open smart home simulator (OpenSHS) for daily activities within the virtual environment. The subset of features is evaluated by the level of consistency in each service. Weka data mining tool is used to find the classifier such as Bayes network and decision table which achieve the best accuracies on the dataset obtained in order to support services for residents in smart home applications. The approach adopted is based on a set of predefined performance metrics in order to compare the results for each classifier in terms of its ability to classify the services. It has been found that the Bayes network achieves an accuracy over 84.0% while the decision table achieved an accuracy over 83.0%. © 2022 IEEE.

关键词： Feature Selection

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Opnet: Deep Occlusion Perception Network with Boundary Awareness for Amodal Instance Segmentation

Opnet: Deep Occlusion Perception Network with Boundary Aware...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shihui Zhang Ziteng Xue Yuhong Jiang Houlin Wang School of Information Science and Engineering Yanshan University Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province

The Amodal Instance Segmentation (AIS) task aims to infer the visible and occluded regions of an object instance. Existing AIS methods typically focus on directly predicting visible and occluded regions or leveraging prior knowledge to guide predictions. However, these methods often ignore the perception of occluded views, leading to inaccurate results. To address this issue and achieve high-quality AIS, we propose a boundary-aware Occlusion Perception Network (OPNet). OPNet consists of three main components: the Dynamic Feature Augmentation Pyramid (DFAP), the Dual-path Boundary Aware Module (DBAM), and the Shape-guide Refinement Module (SRM). Specifically, DBAM employs an occlusion-perception strategy to learn discriminative features with boundary information, enabling it to distinguish occlusion from multiple views. Additionally, DFAP and SRM optimize the results by enhancing feature aggregation and imposing geometric constraints. Experiments on the D2SA, KINS, and CWALT datasets show that OPNet significantly outperforms state-of-the-art AIS methods that without prior knowledge. Code is available at https://***/ZitengXue/OPNet.

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On the Outage of Far-Reach Communications via RIS-Empowered Satellites

On the Outage of Far-Reach Communications via RIS-Empowered ...

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2024 IEEE Pacific Rim Conference on Communications, computers and Signal Processing, PACRIM 2024

作者： Wang, Fan Jiang, Ruihong Liu, Yuan Bao, Tingnan Peng, Mugen Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Research Center for Space Computing System Zhejiang Laboratory Hangzhou311100 China School of Electrical Engineering and Computer Science University of Ottawa OttawaON Canada

ISBN: (纸本)9798350362312

The rising demand for reliable, high-bandwidth satellite communications in far-reach areas drives the integration of low earth orbit (LEO) satellites into future 6G networks. In this paper, we investigate the deployment of reconfigurable intelligent surface (RIS) technology and rate splitting multiple access (RSMA) within LEO satellite systems to improve communication quality and system capacity. We derive closed-form expressions for outage probability (OP) and reliable throughput that validate the theoretical advantages of these technologies under various signal-to-noise ratio conditions. Numerical results demonstrate that, compared with traditional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) approaches, our RSMA and RIS-integrated framework significantly can reduce OP and enhance reliable throughput with an appropriate power-splitting factor, showcasing its superiority in RIS-enabled satellite communication scenarios. © 2024 IEEE.

关键词： Satellite communication systems

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Impact of Inertia Reduction on Small-Signal Stability and Controllability of Interconnected Synchronous Generators

Impact of Inertia Reduction on Small-Signal Stability and Co...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Antonija Šumiga Jožef Ritonja Boštjan Polajžer Croatian Transmission System Operator Zagreb Croatia Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The integration of renewable energy sources inherently reduces power system inertia, which can result in a higher rate of change of frequency. Moreover, reduced inertia also affects the small-signal stability and controllability of the interconnected synchronous generators (SGs). In this paper, we use the linear state-space model to show the impact of SGs’ inertia constants on eigenvalues, participation factors, and Gramian-based controllability metrics. Both a single-machine and an IEEE 9-bus system were analyzed. The results for the IEEE 9-bus system with three SGs show an optimal range of inertia constants to increase the damping of a specific mode and increase controllability. Thus, a framework for multi-objective optimization combining large-signal stability, small-signal stability, and controllability is proposed that can be applied to grid-forming converters.

关键词： Damping Measurement Europe Power system stability Controllability Stability analysis Synchronous generators Eigenvalues and eigenfunctions Optimization Grid forming

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Tensor MIMO Perfect-Equalizer Design Using New Projection-Based Method and Approximation-Error Analysis

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IEEE systems Journal 2024年第1期18卷 668-679页

作者： Chang, Shih-Yu Wu, Hsiao-Chun Kao, Yi-Chih San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Chungli32003 Taiwan National Yang Ming Chiao Tung University Network and System Division Information Technology Service Center Hsinchu30010 Taiwan

As real environments are quite complex, multiple-input-multiple-output (MIMO) channels should be characterized by the multidimensional-multirelational models. Tensor linear algebra has been emerging as a powerful and promising tool for such MIMO channel modeling and estimation. However, to the best of our knowledge, there hardly exists any algebraic framework of MIMO channel equalization when the channel is modeled as an arbitrary-dimensional transfer tensor (a tensor whose entries are all rational z-functions). In this work, we first propose a new method based on the projection, namely, 'projection-based method,' to determine whether a given transfer tensor is a full-rank tensor or not and carry out the inversion of an invertible transfer tensor. Our idea is employing the projection subspace of the system transfer tensor to simplify the pertinent inversion process. Second, we design the finite-impulse-response (FIR) realization to approximate the inverse of an arbitrary transfer tensor such that all entries of the approximated inverse transfer tensor are finite-degree polynomials of z. Third, we also analyze the computational and memory complexities required by our proposed new projection-based method for checking the full-rank condition of a given transfer tensor and for undertaking the tensor inversion. Our developed new theories and analysis in this work can be applied to determine the FIR model-orders of an approximated inverse MIMO transfer tensor often encountered in signal processing, control, communications, etc. © 2007-2012 IEEE.

关键词： FIR filters

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Multimodal Aspect-Based Sentiment Analysis under Conditional Relation 31

Multimodal Aspect-Based Sentiment Analysis under Conditional...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Liu, Xinjing Li, Ruifan Ye, Shuqin Zhang, Guangwei Wang, Xiaojie School of Artificial Intelligence Beijing University of Posts and Telecommunications China School of Computer Science Beijing University of Posts and Telecommunications China Engineering Research Center of Information Networks Ministry of Education China Key Laboratory of Interactive Technology and Experience System Ministry of Culture and Tourism China

ISBN: (纸本)9798891761964

Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to extract aspect terms from text-image pairs and identify their sentiments. Previous methods are based on the premise that the image contains the objects referred by the aspects within the text. However, this condition cannot always be met, resulting in a suboptimal performance. In this paper, we propose COnditional Relation based Sentiment Analysis framework (CORSA). Specifically, we design a conditional relation detector (CRD) to mitigate the impact of the unmet conditional image. Moreover, we design a visual object localizer (VOL) to locate the exact condition-related visual regions associated with the aspects. With CRD and VOL, our CORSA framework takes a multi-task form. In addition, to effectively learn CORSA we conduct two types of annotations. One is the conditional relation using a pretrained referring expression comprehension model;the other is the bounding boxes of visual objects by a pretrained object detection model. Experiments on our built C-MABSA dataset show that CORSA consistently outperforms existing methods. The code and data are available at https://***/Liuxj-Anya/CORSA. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays 2

Range-angle Imaging Based on the Prior of Target Scattering ...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Mei, Yongjie Zhang, Guangbin Huang, Tianyao Wang, Yan Beijng Institute of Technology School of Information and Electronics Beijing China Yangtze Delta Region Academy Beijing Institute of Technology Radar System and Intelligent Signal Processing Jiaxing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

We consider the problem of target range-angle imaging using distributed arrays. High resolution imaging requires a large array aperture. However, due to the limited number of array elements, the subarrays are usually sparsely located, which results in severe under-sampling and ambiguity problem, degrading the imaging performance. To this end, we propose a range-angle imaging method based on the prior of target scattering characteristic to resolve the ambiguity. The main idea is to use the information increment of priors to reduce the dependence on the measurements. Particularly, we first statistically extract the prior distribution of target scattering intensity by data analysis on the target images. Then we use these priors to design weighting parameters and achieve the ambiguity-free images by solving a weighted sparse recovery problem. Finally, numerical simulation results verify the feasibility of the proposed method. © 2024 IEEE.

关键词： ambiguity distributed array Range-angle imaging the prior of target scattering characteristics weight

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An intelligent cylindrical reflector for airborne virus detection 20

An intelligent cylindrical reflector for airborne virus dete...

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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Hadded, Ahmed Ayed, Mossaad Ben Alshaya, Shaya A. Sfax University Computer and Embedded System Laboratory National Engineering School of Sfax Sfax3038 Tunisia Sousse University Electronic Industrial ENISo Tunisia Sfax University Tunisia Computer and Embedded System Laboratory ENIS Sfax3038 Tunisia Majmaah University Digital Transformation and E-Transactions Faculty of Sciences and Humanities Sciences Prince Sultan University Department of Computer Science Majmaah11952 Saudi Arabia

ISBN: (纸本)9798350332568

In 2020, the world suffered from the COVID-19 pandemic. This situation highlighted the considerable need for systems to detect viruses quickly. Providing an accurate e-health system that detects, monitors, and controls virus spread became necessary. Countries attempt to reduce the virus's spread using basic processes such as quarantine and lockdown. Early virus detection is requested to reduce the threat and decrease the propagation of the pandemic. This paper proposes an attempt to avoid speed-up spreading based on airborne virus detection. The suggested detection based on the SiNW-FET biosensor is not approved as a standardized diagnostic test. To support the airborne detection methodology, a metasurface technology based on Reflector cylindrical antenna with a sensing unit is proposed to detect viruses. The proposal considered the propagation delays and concentration of a virus. Conducted results prove that the receiver's volume is considered a primary key to an accurate detection rather than the virus's concentration. © 2023 IEEE.

关键词： Reflection

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Fake Reviews Detection with Hybrid Features Using Time-Sequential Deep Learning Model 3

Fake Reviews Detection with Hybrid Features Using Time-Seque...

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3rd IEEE International Conference on Human-Machine systems, ICHMS 2022

作者： Weng, Yu-Liang Chien, Shih-Yi Lin, Szu-Yin National Chengchi University Department of Management Information System Taipei Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan Taiwan

ISBN: (数字)9781665452380

ISBN: (纸本)9781665452380

This study aims to train a time-sequential deep learning model to classify reviews as genuine or fake. The real-life dataset from Yelp contains review text and user behavior, which are taken together as features within the LSTM model. The results suggest that a time-sequential model such as LSTM is promising to predict fake reviews with an 89% accuracy score. Besides, the textual features represented in word embedding vectors perform better than user behavior features. The results provided by deep learning models are expected to extend further to explainable AI (XAI) in future work. © 2022 IEEE.

关键词： Long short-term memory

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APNet: Adaptive Patch-based Network for Microaneurysm Detection in Fundus Images

APNet: Adaptive Patch-based Network for Microaneurysm Detect...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Xinpeng Zhang Congcong Wang Yilin Han Shengyong Chen Engineering Research Center of Learning-Based Intelligent System Ministry of Education School of Computer Science and Engineering of Tianjin University of Technology Tianjin China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Microaneurysms (MAs) in fundus images are a crucial indicator for the early detection of diabetes and the treatment of diabetic retinopathy. In this paper, we propose an efficient method for microaneurysms detection. We propose an Att-UCtransnet network to extract the MA candidate region, where only positive samples which contain at least one microaneurysm are chosen. Inspired by the concept of the effective receptive field (ERF), we design an algorithm to adaptively select the appropriate patch size, preserving crucial information around the microaneurysm while minimizing interference from irrelevant environments. Besides, we introduce a classification network for accurate mass detection in whole fundus images. Extensive experiments conducted on four publicly available datasets demonstrate that our method outperforms the state-of-the-art approaches in MA detection.

关键词： Training Industrial electronics Diabetic retinopathy Adaptive systems Accuracy Interference Manuals

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