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3rd International Conference on Remote Sensing, Surveying, and Mapping, RSSM 2024

作者： Wang, Yujuan Peng, Ling Wu, Liangshun Hu, Juan Wang, Yu Zhang, Bin Guangzhou Xinhua University Guangdong Province Dongguan City China Real Estate Registration Center Huanggang Land and Resources Bureau Hubei Province Huanggang China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai City China Discipline Inspection and Supervision College Huanggang Normal University Hubei Province Huanggang China Network Information Center Xinjiang University of Political Science and Law Xinjiang Production and Construction Corps Tumushuke China Department of Computer Science City University of Hong Kong Hong Kong School of Remote Sensing and Information Engineering Wuhan University Wuhan City China

ISBN: (数字)9781510680081

ISBN: (纸本)9781510680074

This study underscores the significance of accurately identifying minute objects within satellite imagery. We propose an innovative GAN framework tailored for enhancing the detection of minute objects in such imagery. Our approach primarily emphasizes differentiating these objects from their surroundings by leveraging the core mechanisms of GANs. Moreover, we address the varied spectral characteristics of the background by integrating a similarity constraint into our GANs architecture. This strategy effectively distinguishes between the target object regions and non-object regions, significantly reducing the occurrence of false positives. Additionally, we employ a smoothness regularization technique to preserve the structural integrity of the detected objects. Through extensive experimentation on publicly available remote sensing datasets—spanning mineral, fabric, and vehicle detection—we compare our method quantitatively against conventional small object detection techniques and state-of-the-art GAN-based models. The comparative results consistently showcase the superior performance and robustness of our GAN-based approach in detecting minute objects within remote sensing imagery. © 2024 SPIE.

关键词： Remote sensing

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A Compact Dead-Zone-Free Multi-Channel Stimulation and Recording System for Precision Peripheral Nerve Modulation 46

A Compact Dead-Zone-Free Multi-Channel Stimulation and Recor...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Xing, Yanjie Chen, Weihuang Yu, Danlei Gao, Xiang Bao, Jieting Xu, Kedi Zhejiang China Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal Key Laboratory of Biomedical Engineering of Education Ministry Department of Biomedical Engineering Zhejiang University Hangzhou China Institute of Advanced Digital Technology and Instrument Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory for Network Multimedia Technologies Zhejiang University Hangzhou310027 China Binjiang Institude of Zhejiang University Hangzhou310027 China Nanhu Brain-computer interface institute Hangzhou311100 China Zhejiang University Hangzhou China The State Key Lab of Brain-Machine Intelligence Zhejiang University Hangzhou China

ISBN: (纸本)9798350371499

Peripheral nerve modulation has a certain potential in motor recovery, but the majority of systems suffer from the drawback of dead time caused by switching channels to achieve multi-channel stimulation. As a response to this challenge, we have developed a peripheral nerve modulation device with 64-channel recording and 16-channel stimulation without dead time. Through modulation of the rat sciatic nerve, we identified the crucial role of initial phase and amplitude in the outcomes of dual-channel combined stimulation. This design not only enhanced neural activation capabilities with constant power supply but also achieves more precise neural activation and reduces unintentional activation. © 2024 IEEE.

关键词： Recording instruments

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Ru Li Aimin Li Rong Fei Xie Guo Fang-Xiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions.

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Ensemble inequivalence and phase transitions in unlabeled networks

arXiv

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arXiv 2024年

作者： Evnin, Oleg Krioukov, Dmitri High Energy Physics Research Unit Faculty of Science Chulalongkorn University Bangkok Thailand Theoretische Natuurkunde Vrije Universiteit Brussel International Solvay Institutes Brussels Belgium Department of Physics Network Science Institute Department of Mathematics Department of Electrical and Computer Engineering Northeastern University BostonMA United States

We discover a first-order phase transition in the canonical ensemble of random unlabeled networks with a prescribed average number of links. The transition is caused by the nonconcavity of microcanonical entropy. Above the critical point, the canonical and microcanonical ensembles are equivalent and have a well-behaved thermodynamic limit. Below the critical point, the ensemble equivalence is broken, and the canonical ensemble is a mixture of phases: empty networks and networks with logarithmic average degrees. As a consequence, networks with bounded average degrees do not survive in the thermodynamic limit, decaying into the empty phase. The celebrated percolation transition in labeled networks is thus absent in unlabeled networks. In view of these differences between labeled and unlabeled ensembles, the question of which one should be used as a null model of different real-world networks cannot be ignored. Copyright © 2024, The Authors. All rights reserved.

关键词： Critical temperature

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Device Activity Detection in mMTC with Low-Resolution ADC: A New Protocol

arXiv

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arXiv 2023年

作者： Wang, Zhaorui Liu, Ya-Feng Wang, Ziyue Liu, Liang Pan, Haoyuan Cui, Shuguang The Future Network of Intelligence Institute The School of Science and Engineering The Chinese University of Hong Kong Shenzhen518172 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong College of Computer Science and Software Engineering Shenzhen University Shenzhen China

This paper investigates the effect of low-resolution analog-to-digital converters (ADCs) on device activity detection in massive machine-type communications (mMTC). The low-resolution ADCs induce two challenges on the device activity detection compared with the traditional setup with the assumption of infinite ADC resolution. First, the codebook design for signal quantization by the low-resolution ADC is particularly important since a good design of the codebook can lead to small quantization error on the received signal, which in turn has significant influence on the activity detector performance. To this end, prior information about the received signal power is needed, which depends on the number of active devices K. This is sharply different from the activity detection problem in traditional setups, in which the knowledge of K is not required by the BS as a prerequisite. Second, the covariance-based approach achieves good activity detection performance in traditional setups while it is not clear if it can still achieve good performance in this paper. To solve the above challenges, we propose a communication protocol that consists of an estimator for K and a detector for active device identities: 1) For the estimator, the technical difficulty is that the design of the ADC quantizer and the estimation of K are closely intertwined and doing one needs the information/execution from the other. We propose a progressive estimator which iteratively performs the estimation of K and the design of the ADC quantizer;2) For the activity detector, we propose a custom-designed stochastic gradient descent algorithm to estimate the active device identities. Numerical results demonstrate the effectiveness of the communication protocol. © 2023, CC BY.

关键词： Stochastic systems

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Navigation Design to Improve Interaction Technique in Multi-Browser Virtual Environment

Navigation Design to Improve Interaction Technique in Multi-...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Mochammad Hannats Hanafi Ichsan Cecilia Sik-Lanyi Tibor Guzsvinecz Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Veszprem Hungary Department of Informatics Faculty of Computer Science Brawijaya University Malang Indonesia Hungarian Research Network Budapest Hungary Department of Information Technology and its Applications Faculty of Information Technology University of Pannonia Zalaegerszeg Hungary

ISBN: (数字)9798350378245

ISBN: (纸本)9798350378252

Efficient, precise, and intuitive navigation in a Virtual Environment (VE) or in desktop Virtual Reality (VR) is critical to improving user experience. This research introduces three navigation designs for physical embodiment inside VE using a computer mouse for multi-browser VE in desktop VR based on navigation possibilities. Navigation is intended for the First-Person Shooter (FPS) perspective: Intuitive Navigation (IntuNav), Edge Shift Navigation (EdgeNav), and Twist Shift Navigation (TwistNav). IntuNav uses mouse x and y coordinate movements to move and rotate the camera. EdgeNav relies on the cursor positioning at the edge of the screen for camera rotation and movement. TwistNav uses a middle click and right mouse click for camera movement and rotation. The current navigation design has been implemented in Unity with C#. This research proposed three model designs based on feasible navigation possibilities, which shows that each navigation model has unique advantages that can be adapted to user needs and preferences. Based on the test results using the System Usability Scale, IntuNav and EdgeNav obtained good results and can be used for further development.

关键词： Solid modeling Adaptation models Navigation Virtual environments Cameras User experience C# languages Usability

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Feature selection in linear support vector machines via a hard cardinality constraint: A scalable conic decomposition approach

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European Journal of Operational Research 2025年

作者： Bomze, Immanuel D'Onofrio, Federico Palagi, Laura Peng, Bo Faculty of Mathematics and Research Network Data Science University of Vienna Oskar-Morgenstern-Platz 1 Wien1090 Austria Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy VGSCO University of Vienna Oskar-Morgenstern-Platz 1 Wien1090 Austria

In this paper, we study the embedded feature selection problem in linear Support Vector Machines (SVMs), in which a cardinality constraint is employed, leading to an interpretable classification model. The problem is NP-hard due to the presence of the cardinality constraint, even though the original linear SVM amounts to a problem solvable in polynomial time. To handle the hard problem, we first introduce two mixed-integer formulations for which novel semidefinite relaxations are proposed. Exploiting the sparsity pattern of the relaxations, we decompose the problems and obtain equivalent relaxations in a much smaller cone, making the conic approaches scalable. To make the best usage of the decomposed relaxations, we propose heuristics using the information of its optimal solution. Moreover, an exact procedure is proposed by solving a sequence of mixed-integer decomposed semidefinite optimization problems. Numerical results on classical benchmarking datasets are reported, showing the efficiency and effectiveness of our approach. © 2025

关键词： Mixed-integer linear programming

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Service-Oriented Multipath Scheduling for Integrated Satellite-Terrestrial networks

Service-Oriented Multipath Scheduling for Integrated Satelli...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Man Ouyang Ran Zhang Bingqing Wang Jiang Liu Weihua Zhuang State Key Laboratory of Networking and Switching Technology BUPT Beijing P.R.China Future Network Research Center Purple Mountain Laboratories Nanjing P.R.China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Low earth orbit (LEO) satellite networks can seamlessly supplement terrestrial networks by providing a high capacity, wide coverage, and cost-effective solution. Positioned to play a significant role in the upcoming 5G/6G era thanks to reduced launch expenses, LEO satellite networks offer benefits such as multi-path transmission, aggregated link bandwidth, redundant paths, and enhanced mobility support. These advantages necessitate further exploration in integrated satellite-terrestrial networks. In this work, we leverage network conditions, underlying link status, and real-time service characteristics to achieve effective synergy, aiming to fulfill application requirements. We formulate the service-oriented multi-path scheduling (SOMPS) problem as a bounded multi-knapsack problem and employ dynamic programming methods for its solution. Simulation results demonstrate that our proposed scheme provides high transmission rate, low latency, and customized information delivery for services, in comparison with baseline schemes.

关键词： Satellites Simulation Low earth orbit satellites Quality of service Space-air-ground integrated networks Dynamic scheduling Real-time systems Dynamic programming Low latency communication Interoperability

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G2Face: High-Fidelity Reversible Face Anonymization via Generative and Geometric Priors

arXiv

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arXiv 2024年

作者： Yang, Haoxin Xu, Xuemiao Xu, Cheng Zhang, Huaidong Qin, Jing Wang, Yi Heng, Pheng-Ann He, Shengfeng The School of Computer Science and Engineering South China University of Technology Guangzhou China Guangdong Engineering Center for Large Model and GenAI Technology State Key Laboratory of Subtropical Building and Urban Science China The Centre for Smart Health The Hong Kong Polytechnic University Hong Kong The School of Future Technology South China University of Technology Guangzhou China The School of Computer Science and Network Security Dongguan University of Technology Dongguan China The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong The School of Computing and Information Systems Singapore Management University Singapore

Reversible face anonymization, unlike traditional face pixelization, seeks to replace sensitive identity information in facial images with synthesized alternatives, preserving privacy without sacrificing image clarity. Traditional methods, such as encoder-decoder networks, often result in significant loss of facial details due to their limited learning capacity. Additionally, relying on latent manipulation in pre-trained GANs can lead to changes in ID-irrelevant attributes, adversely affecting data utility due to GAN inversion inaccuracies. This paper introduces G2Face, which leverages both generative and geometric priors to enhance identity manipulation, achieving high-quality reversible face anonymization without compromising data utility. We utilize a 3D face model to extract geometric information from the input face, integrating it with a pre-trained GAN-based decoder. This synergy of generative and geometric priors allows the decoder to produce realistic anonymized faces with consistent geometry. Moreover, multi-scale facial features are extracted from the original face and combined with the decoder using our novel identity-aware feature fusion blocks (IFF). This integration enables precise blending of the generated facial patterns with the original ID-irrelevant features, resulting in accurate identity manipulation. Extensive experiments demonstrate that our method outperforms existing state-of-the-art techniques in face anonymization and recovery, while preserving high data utility. Code is available at https://***/Harxis/G2Face. Copyright © 2024, The Authors. All rights reserved.

关键词： Anonymity

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Enhanced Prediction of Fuel Consumption and Carbon Emissions in Light-Duty Vehicles using Convolutional Recurrent Imputation network

Enhanced Prediction of Fuel Consumption and Carbon Emissions...

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International Conference on computer, Electrical & Communication engineering (ICCECE)

作者： T. Lalitha Jerzy Ryszard Szymański Marta Żurek-Mortka Mithileysh Sathiyanarayanan K. R. Srilekha Computer Science School of Information Science Presidency University Bengaluru Karnataka India Department of Electrical Drives and Industrial Electronics Faculty of Transport Electrical Engineering and Computer Sciences Casimir Pulaski University of Radom Poland Europe Lukasiewicz Research Network Institute for Sustainable Technologies Kazimierza Pułaskiego Radom Poland Europe MIT Square London I M.Tech Integrated(Software Engineering) VIT University Vellore Tamilnadu India

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

Fuel utilization and emission estimation are essential for assessing the consequence of materials and strict emission control measures due to the startling rate of weather changes. The world's socioeconomic issues are significantly impacted by the growing worldwide average temperature and its effects on climate change. The melting of the polar ice caps, that is a direct result of this rise, leads to a number of other problems, such as the polar animal’s death, coastal flooding, and exposure to bacteria and earliest microorganisms that are frozen in the snow and could cause many more global pandemics and invisible illnesses. In this paper, Enhanced Prediction of Fuel Consumption and Carbon Emissions in Light-Duty Vehicles using Dynamic Graph Convolutional Recurrent Imputation network (EP-FCCE-DGCRIN) are proposed.. The effectiveness of the EP-FCCE-DGCRIN technique is compared to other existing methods. This research offers evidence-based suggestions to lessen the environmental effects of vehicles for both manufacturers and consumers depending upon the outcomes of the Descriptive Statistics analysis.

关键词： Temperature measurement Pandemics Snow Sea measurements Carbon dioxide Imputation Fuels Vehicle dynamics Socioeconomics Meteorology

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