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Path Priority Routing Protocol for Underwater Wireless Sensor Network

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IEEE Internet of Things Journal 2025年

作者： Ogundile, Olayinka Babalola, Oluwaseyi Agboola, Emmanuel Ogundile, Olabisi Davidson, Innocent Tai Solarin University of Education Department of Industrial Technical Education Nigeria Cape Peninsula University of Technology French-South African Institute of Technology Department of Electrical Electronic and Computer Engineering Bellville South Africa Bournemouth University Department of Computing and Informatics Bournemouth United Kingdom Government Senior College Ketu-Epe Nigeria

Underwater wireless sensor networks (UWSNs) are rapidly expanding, enabling advancements in marine technologies like seabed excavation, seismic monitoring, and environmental monitoring. UWSNs consist of small, battery-powered devices that communicate to forward data to a base station. Due to their seabed location, replacing batteries is challenging, making energy-efficient (E-E) communication crucial to extending the network’s lifespan. Many routing protocols have been developed to address the challenges of underwater communication, but balancing energy consumption while maintaining high-quality service (QoS) remains difficult, especially in large-scale UWSNs. This article introduces a path priority routing protocol (PPRP) for UWSNs, which adapts the mobile selective-path priority table (MSPT) routing protocol from terrestrial wireless sensor networks (WSNs) to underwater conditions. The PPRP prioritises paths to the base station using simple yet effective rules, reducing overall energy consumption while balancing QoS requirements. Comparative analysis with recent routing protocols show that the PPRP is a performance-efficient alternative routing protocol for UWSNs. © 2014 IEEE.

关键词： Sensor nodes

The Localized Subtraction Approach For EEG and MEG Forward Modeling

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arXiv 2023年

作者： Höltershinken, Malte B. Lange, Pia Erdbrügger, Tim Buschermöhle, Yvonne Wallois, Fabrice Buyx, Alena Pursiainen, Sampsa Vorwerk, Johannes Engwer, Christian Wolters, Carsten H. Institute for Biomagnetism and Biosignalanalysis University of Münster Münster Germany Institute of Medical Informatics University of Münster Münster Germany Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience University of Münster Münster Germany INSERM U1105 Research Group on Multimodal Analysis of Brain Function Jules Verne University of Picardie Amiens France Pediatric functional exploration of the nervous system department CHU Picardie Amiens France Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Computing Sciences Unit Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Institute of Electrical and Biomedical Engineering Private University for Health Sciences Medical Informatics and Technology Hall in Tyrol Austria Faculty of Mathematics and Computer Science University of Münster Münster Germany

In FEM-based EEG and MEG source analysis, the subtraction approach has been proposed to simulate sensor measurements generated by neural activity. While this approach possesses a rigorous foundation and produces accurate results, its major downside is that it is computationally prohibitively expensive in practical applications. To overcome this, we developed a new approach, called the localized subtraction approach. This approach is designed to preserve the mathematical foundation of the subtraction approach, while also leading to sparse right-hand sides in the FEM formulation, making it efficiently computable. We achieve this by introducing a cut-off into the subtraction, restricting its influence to the immediate neighborhood of the source. In this work, this approach will be presented, analyzed, and compared to other state-of-the-art FEM right-hand side approaches. Furthermore, we discuss how to arrive at an efficient and stable implementation. We perform validation in multi-layer sphere models where analytical solutions exist. There, we demonstrate that the localized subtraction approach is vastly more efficient than the subtraction approach. Moreover, we find that for the EEG forward problem, the localized subtraction approach is less dependent on the global structure of the FEM mesh, while the subtraction approach is sensitive to the mesh structure even at a distance to the source. Additionally, we show the localized subtraction approach to rival, and in many cases even surpass, the other investigated approaches in terms of accuracy. Especially for the MEG forward problem, where Biot-Savart’s law is employed, we show the localized subtraction approach and the subtraction approach to produce highly accurate approximations of the volume currents close to the source. The localized subtraction approach thus reduces the computational cost of the subtraction approach to an extent that makes it usable in practical applications without sacrificing the rigorousness and

关键词： Mesh generation

Exploring Grounding Abilities in Vision-Language Models through Contextual Perception

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Xu, Wei Zhou, Tianfei Zhang, Taoyuan Li, Jie Chen, Peiyin Pan, Jia Liu, Xiaofeng Hohai University College of Artificial Intelligence and Automation Changzhou213022 China Beijing Institute of Technology Department of Computer Science China De Anza College CA United States Nanjing Medical University Engineering Research Center of Intelligent Theranostics Technology and Instruments Ministry of Education Nanjing211166 China Nanjing Medical University School of Biomedical Engineering and Informatics Nanjing211166 China University of Hong Kong Department of Computer Science Hong Kong

Vision language models (VLMs) have demonstrated strong general capabilities and achieved great success in areas such as image understanding and reasoning. Visual prompts enhance the focus of VLMs on designated areas, but their fine-grained grounding has not been fully developed. Recent research has used Set-of-Mark (SoM) approach to unleash the grounding capabilities of Generative Pre-trained Transformer-4 with Vision (GPT-4V), achieving significant benchmark performance. However, SoM still has problems with label offset and hallucination of vision language models, and the grounding ability of VLMs remains limited, making it challenging to handle complex scenarios in human-robot interaction. To address these limitations and provide more accurate and less hallucinatory results, we propose Contextual Set-of-Mark (ConSoM), a new SoM-based prompting mechanism that leverages dual-image inputs and contextual semantic information of images. Experiments demonstrate that ConSoM has distinct advantages in visual grounding, improving by 11% compared to the baseline on the dataset Refcocog. Furthermore, we evaluated ConSoM’s grounding abilities in five indoor scenarios, where it exhibited strong robustness in complex environments and under occlusion conditions. We also introduced a scalable annotation method for pixel-level question-answering dataset. The accuracy, scalability, and depth of world knowledge make ConSoM a highly effective approach for future human-robot interactions. © 2016 IEEE.

关键词： Human robot interaction

Deep Learning for Predictive Analytics in Reversible Steganography

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arXiv 2021年

作者： Chang, Ching-Chun Wang, Xu Chen, Sisheng Echizen, Isao Sanchez, Victor Li, Chang-Tsun National Institute of Informatics Tokyo Japan Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan School of Information Science and Engineering University of Jinan Jinan China School of Big Data and Artificial Intelligence Fujian Polytechnic Normal University Fuzhou China Department of Computer Science University of Warwick Coventry United Kingdom School of Information Technology Deakin University Geelong Australia

Deep learning is regarded as a promising solution for reversible steganography. There is an accelerating trend of representing a reversible steo-system by monolithic neural networks, which bypass intermediate operations in traditional pipelines of reversible steganography. This end-to-end paradigm, however, suffers from imperfect reversibility. By contrast, the modular paradigm that incorporates neural networks into modules of traditional pipelines can stably guarantee reversibility with mathematical explainability. Prediction-error modulation is a well-established reversible steganography pipeline for digital images. It consists of a predictive analytics module and a reversible coding module. Given that reversibility is governed independently by the coding module, we narrow our focus to the incorporation of neural networks into the analytics module, which serves the purpose of predicting pixel intensities and a pivotal role in determining capacity and imperceptibility. The objective of this study is to evaluate the impacts of different training configurations upon predictive accuracy of neural networks and provide practical insights. In particular, we investigate how different initialisation strategies for input images may affect the learning process and how different training strategies for dual-layer prediction respond to the problem of distributional shift. Furthermore, we compare steganographic performance of various model architectures with different loss functions. Copyright © 2021, The Authors. All rights reserved.

关键词： Pipelines

Real-time and ultrafast optical pulse quantization based on slicing the supercontinuum

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Chinese Optics Letters 2021年第8期19卷 69-74页

作者： Ya Guo Qiang Cai Zhiwei Jia Bingjie Xu Zhensen Gao Qianwu Zhang Ruonan Zhang Adonis Bogris K.Alan Shore Yuncai Wang Pu Li Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710072China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUnited Kingdom

All-optical analog-to-digital conversion is a paramount issue in modern science. How to implement real-time and ultrafast quantization to optical pulses with different intensities in an all-optical domain is a central problem. Here, we report a realtime demonstration of an all-optical quantization scheme based on slicing the supercontinuum in a nonlinear fiber. In comparison with previous schemes through off-line analysis of the power of different optical spectral components in the supercontinuum, this, to the best of our knowledge, is the first demonstration of such functionality online in the time ***, the extinction ratio among the quantized outputs can exceed 10 d B, which further confirms the feasibility of the proposed quantization scheme. The current 3 bit resolution in the proof-of-principle experiment is limited by the current experimental condition, but it can be expected to be greatly enhanced through improving both the spectral width of the generated supercontinuum and the number of filtering channels used.

关键词： all-optical analog-to-digital conversion photonic quantization all-optical signal processing supercontinuum generation

An analysis of protected health information leakage in deep-learning based de-identification algorithms

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arXiv 2021年

作者： Seyedi, Salman Xiong, Li Nemati, Shamim Clifford, Gari D. Department of Biomedical Informatics Emory University AtlantaGA30322 United States Department of Computer Science Emory University AtlantaGA30322 United States Department of Biomedical Informatics University of California San Diego Health San diegoCA92037 United States Department of Biomedical Engineering Georgia Institute of Technology AtlantaGA30308 United States

The increasing complexity of algorithms for analyzing medical data, including de-identification tasks, raises the possibility that complex algorithms are learning not just the general representation of the problem, but specifics of given individuals within the data. Modern legal frameworks specifically prohibit the intentional or accidental distribution of patient data, but have not addressed this potential avenue for leakage of such protected health information. Modern deep learning algorithms have the highest potential of such leakage due to complexity of the models. Recent research in the field has highlighted such issues in non-medical data, but all analysis is likely to be data and algorithm specific. We, therefore, chose to analyze a state-of-the-art free-text de-identification algorithm based on LSTM (Long Short-Term Memory) and its potential in encoding any individual in the training set. Using the i2b2 Challenge Data, we trained, then analyzed the model to assess whether the output of the LSTM, before the compression layer of the classifier, could be used to estimate the membership of the training data. Furthermore, we used different attacks including membership inference attack method to attack the model. Results indicate that the attacks could not identify whether members of the training data were distinguishable from non-members based on the model output. This indicates that the model does not provide any strong evidence into the identification of the individuals in the training data set and there is not yet empirical evidence it is unsafe to distribute the model for general use. © 2021, CC BY-SA.

关键词： Learning algorithms

The Realization Factors of Taiwan's Low Altitude Airspace Economy and UAM: Analysis and Evaluation

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The Realization Factors of Taiwan's Low Altitude Airspace Ec...

IEEE International Conference on e-Business engineering (ICEBE)

作者： Tung-Ling Wu Chih-Ming Kung Guan-Ting Lin Kuen-Yu Tsai Guang-Yun Meng Yu-Che Huang Wan-Shu Cheng Institute of Transportation at Ministry of Transportation and Communications Taiwan R.O.C. Dep. Of Information Technology&Communication Shin Chin Univeristy Kaohsiung Campus Taiwan R.O.C. Dep. of Computer Science and Information Management Providence University Taichung Taiwan R.O.C. Department of Electrical Engineering National Taiwan Univeristy Taipei Taiwan R.O.C. Executive Officer Center for Research on High-Performance Remote Sensing and Urban Informatics NTU Taiwan R.O.C.

ISBN: (数字)9798350365856

ISBN: (纸本)9798350365863

Low altitude airspace economy applications will be of highly effective in a wide range of civil activities and will be a critical element in the smart cities of the future. In view of the main features of unmanned aerial vehicle (UAV), such as automatic piloting system, access to uninhabited areas, low cost compared to road and manned aircraft, shorter delivery time, and the ability to carry heavy payloads, it is important to recognize that UAVs can be used for a wide range of civil activities. With the development of these applications in full swing around the world, in addition to advanced communications technology and other related infrastructure, business demand and a favorable investment climate, clarity, definiteness and feasible regulations in the Taiwanese environment are also essential. Based on the premise of local economic strength, the technical level of the telecommunication industry, and commercial demands, Taiwan should establish a rational standard for the UAV regulatory system as soon as possible, so as to facilitate the development of UAM and to ensure the international competitiveness of the related technologies for market development,

关键词： Industries Technological innovation Transportation Autonomous aerial vehicles Regulation Communications technology Aircraft Standards Drones Investment

On multichromatic numbers of widely colorable graphs

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arXiv 2021年

作者： Gujgiczer, Anna Simonyi, Gábor Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary Alfréd Rényi Institute of Mathematics Budapest Hungary MTA-BME Lendület Arithmetic Combinatorics Research Group Hungary

A coloring is called s-wide if no walk of length 2s − 1 connects vertices of the same color. A graph is s-widely colorable with t colors if and only if it admits a homomorphism into a universal graph W (s, t). Tardif observed that the value of the rth multichromatic number χr(W (s, t)) of these graphs is at least t + 2(r − 1) and equality holds for r = s = 2. He asked whether there is equality also for r = s = 3. We show that χs(W (s, t)) = t+2(s−1) for all s thereby answering Tardif's question. We observe that for large r (with respect to s and t fixed) we cannot have equality and that for s fixed and t going to infinity the fractional chromatic number of W (s, t) also tends to infinity. The latter is a simple consequence of another result of Tardif on the fractional chromatic number of generalized Mycielski *** Codes 05C15 (Primary) 05C60, 05C72 (Secondary) Copyright © 2021, The Authors. All rights reserved.

关键词： Graphic methods

Correction to: Development of a behavioral trajectory measurement system (Bucket-ANTAM) for organisms moving in a two-dimensional plane

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Artificial Life and Robotics 2022年第3期28卷 642-642页

作者： Shirai, Kazuma Shimamura, Kazushi Koubara, Akihiro Shigaki, Shunsuke Fujisawa, Ryusuke Department of Creative Informatics Kyushu Institute of Technology Fukuoka Japan Department of Interdisciplinary Informatics Kyushu Institute of Technology Fukuoka Japan Graduate School of Engineering Science University of Osaka Osaka Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan