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Cloudification of the Internet of Things (CIoT)

作者： Mau-Luen Tham Chee Hong Lean Wei-Sean Lim Rong-Chuan Leong Yasunori Owada Myint Myint Sein Department of Electrical and Electronic Engineering Universiti Tunku Abdul Rahman Kajang Malaysia Resilient ICT Research Center National Institute of Information and Communications Technology (NICT) Tokyo Japan Geographical Information System University of Computer Studies Yangon (UCSY) Myanmar

When a natural disaster event happens, it could trigger regional cellular network outages and hence disable network communication within the affected area. If a resilient network is implemented, alert messages with sufficient information can be sent over the Internet to provide a nationwide response. Japan National Institute of Information and Communication technology (NICT) has invented a resilient network framework called NerveNet, which supports robust communications via mesh networking. Using their technology as the communication platform, disaster nodes could be installed at disaster hotspots to send out disaster information or even provide lightweight Internet services. NerveNet can support data synchronization using Wi-Fi and LoRa. The former is used to provide wide bandwidth but low-range data transmission, whereas the latter enables narrow-bandwidth data transmission in coverage of kilometers, which is suitable for crucial or emergency disaster data updates.

关键词： Wireless communication Web and internet services Telecommunications Information and communication technology ITU Synchronization Data communication

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DL-SLOT: Dynamic LiDAR SLAM and object tracking based on collaborative graph optimization

arXiv

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arXiv 2022年

作者： Tian, Xuebo Zhu, Zhongyang Zhao, Junqiao Tian, Gengxuan Ye, Chen Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Institute of Intelligent Vehicles Tongji University Shanghai China

Ego-pose estimation and dynamic object tracking are two critical problems for autonomous driving systems. The solutions to these problems are generally based on their respective assumptions, i.e., the static world assumption for simultaneous localization and mapping (SLAM) and the accurate ego-pose assumption for object tracking. However, these assumptions are challenging to hold in dynamic road scenarios, where SLAM and object tracking become closely correlated. Therefore, we propose DL-SLOT, a dynamic LiDAR SLAM and object tracking method, to simultaneously address these two coupled problems. This method integrates the state estimations of both the autonomous vehicle and the stationary and dynamic objects in the environment into a unified optimization framework. First, we used object detection to identify all points belonging to potentially dynamic objects. Subsequently, a LiDAR odometry was conducted using the filtered point cloud. Simultaneously, we proposed a sliding window-based object association method that accurately associates objects according to the historical trajectories of tracked objects. The ego-states and those of the stationary and dynamic objects are integrated into the sliding window-based collaborative graph optimization. The stationary objects are subsequently restored from the potentially dynamic object set. Finally, a global pose-graph is implemented to eliminate the accumulated error. Experiments on KITTI datasets demonstrate that our method achieves better accuracy than SLAM and object tracking baseline methods. This confirms that solving SLAM and object tracking simultaneously is mutually advantageous, dramatically improving the robustness and accuracy of SLAM and object tracking in dynamic road scenarios. Copyright © 2022, The Authors. All rights reserved.

关键词： Optical radar

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Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting

Single Block Encoder-Decoder Transformer Model for Multi-Ste...

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IEEE Symposium on computers & Informatics (ISCI)

作者： Mas Omar Fitri Yakub Mohamad Sofian Abu Talip Mohd Nazmin Maslan Vijay Kumar Sinha Muljono Muljono WEE Laboratory Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Department of Electronic System Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Faculty of Industrial and Manufacturing Technology and Engineering Universiti Teknikal Malaysia Melaka Malaysia Department of Computer Science & Engineering School of Engineering & Technology Chitkara University Himachal Pradesh India Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350353853

ISBN: (纸本)9798350353860

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this purpose, the potential of Transformer models remains underexplored. This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of a singular horizon-step forecasting method for multi-step traffic flow forecasting using a proposed Single Block Encoder-Decoder Transformer model optimised with a Grid Search algorithm. Results demonstrate that this model can enhance forecasting accuracy compared to the state-of-the-art LSTM model typically used for multi-step forecasting. The model effectively captures long-range temporal dependencies within a single road traffic flow dataset. It was tested on hourly traffic flow data to forecast the next 24 hours for the I5-North freeway in California, sourced from the Caltrans Performance Measurement system. The optimal configuration included an embedding dimension of 32, a feed-forward dimension of 128, and 8 attention heads. Results show a significant improvement, with a 4.7% reduction in Root Mean Squared Error compared to an LSTM model with two hidden layers of 100 neurons each, showcasing the potential of Single Block Encoder-Decoder Transformer models for real-world traffic prediction applications.

关键词： Accuracy Neurons Transportation Predictive models Traffic control Transformers Road traffic

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The Dynamic Control of Hybrid Energy Storage Sysem for Mild HEV

The Dynamic Control of Hybrid Energy Storage Sysem for Mild ...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Baek-Haeng Lee Dong-Hyun Shin Hyun-Sik Song Jin-Beom Jeong Hee-Jun Kim Byeong-Woo Kim Department of Electronic Electrical Hanyang University South Korea KOREA Electronics System R&D Center Korea Automotive Technology Institute (KATECH) Division of Electrical Engineering and Computer Science Hanyang University School of Electrical Engineering Ulsan University

To improve the cycle life and efficiency of an energy storage system for HEV, a dynamic control system consisted of a switch between battery and ultracapacitor module and a controller is proposed, which is appropriate for mild hybrid vehicle with 42 V power net. The switch can be controlled based on the status of the battery and the ultracapacitor module, and a control algorithm that could largely decrease the number of high charging current peak is also implemented. Therefore the cycle life of the battery can be improved such that it is suitable for a mild hybrid vehicle with frequent engine start-stop and regenerative-braking. Also, by maximizing the use of the ultracapacitor, the system efficiency during high current charging and discharging operation is improved. Finally, this system has the effects that improves the efficiency of energy storage system and reduces the fuel consumption of a vehicle. To verify the validity of the proposed system, this paper presented cycles test results of different energy storage systems: a simple VRLA battery, hybrid energy pack (HEP, a VRLA battery in parallel with Ultracapacitor) and a HEP with a switch that controlled by energy management system (EMS). From the experimental result, it was proved the effectiveness of the algorithm.

关键词： Energy storage Hybrid electric vehicles Switches Supercapacitors Control systems Vehicle dynamics Battery powered vehicles Engines Fuels system testing

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Parallel Acceleration of Real-time Feature Extraction Based on SURF Algorithm

Parallel Acceleration of Real-time Feature Extraction Based ...

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International Conference on computer Research and Development (ICCRD)

作者： Jiyang Yu Dan Huang Jinyang Li Wenjie Li Xianjie Wang Xiaolong Shi China Academy of Space Technology Beijing Institute of Spacecraft System Engineering Beijing China China Research and Development Academy of Machinery Equipment Chongqing University of Technology Beijing Chongqing China Intelligent Equipment Research Department Chongqing Feima Innovation Research Institute Chongqing China College of Computer Science and Engineering Chongqing University of Technology Chongqing China

Visual feature extraction is the key to target registration calculation. Compared with SIFT, SURF feature extraction algorithm has less computational complexity and better applicability when image signal-to-noise ratio is low. In this paper, an FPGA-based SURF algorithm for real-time feature extraction and parallel acceleration is designed for large-field scene registration applications of space targets. Firstly, the application scenario of space target is analyzed, and the grayscale features of the data containing the target used for registration are counted. Then, the five main parts of SURF algorithm were analyzed, and the algorithm was simplified based on the gray feature of the image. Finally, according to the simplified results, the parallel pipeline architecture of each module is designed based on FPGA. SURF computing modules are also given in this paper the design of the architecture and data flow of information, in XC7K325 completed the whole design of experiment, the results show that the design for 1024 × 1024 pixel image, single frame image processing time need only 51 us, resource usage is not more than 18.6%, power consumption is not more than 7.5 W, The computational efficiency is 87% higher than the previous design. Low signal-to-noise ratio (SNR) was used to simulate space target scene data for simulation test calculation, and the SURF descriptor error was less than 3%, ensuring the system's calculation error while effectively utilizing resources.

关键词： Power demand Computational modeling Pipelines computer architecture Gray-scale Feature extraction Real-time systems

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Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation

arXiv

引用

arXiv 2024年

作者： Desu, Aditya He, Xuanli Xu, Qiongkai Lu, Wei School of Computing and Information System University of Melbourne Melbourne Australia Department of Computer Science University College London United Kingdom School of Computing FSE Macquarie University Sydney Australia StatNLP Research Group Singapore University of Technology and Design Singapore

As machine- and AI-generated content proliferates, protecting the intellectual property of generative models has become imperative, yet verifying data ownership poses formidable challenges, particularly in cases of unauthorized reuse of generated data. The challenge of verifying data ownership is further amplified by using Machine Learning as a Service (MLaaS), which often functions as a black-box system. Our work is dedicated to detecting data reuse from even an individual sample. Traditionally, watermarking has been leveraged to detect AI-generated content. However, unlike watermarking techniques that embed additional information as triggers into models or generated content, potentially compromising output quality, our approach identifies latent fingerprints inherently present within the outputs through re-generation. We propose an explainable verification procedure that attributes data ownership through regeneration, and further amplifies these fingerprints in the generative models through iterative data re-generation. This methodology is theoretically grounded and demonstrates viability and robustness using recent advanced text and image generative models. Our methodology is significant as it goes beyond protecting the intellectual property of APIs and addresses important issues such as the spread of misinformation and academic misconduct. It provides a useful tool to ensure the integrity of sources and authorship, expanding its application in different scenarios where authenticity and ownership verification are essential. © 2024, CC BY-NC-ND.

关键词： Authentication

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Missing step detection in a high speed micro stepping motor using current feedback

Missing step detection in a high speed micro stepping motor ...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Sung-Wook Moon Young-Jin Kim Yoon-Taek Lim Dong Hwan Kim NID Graduate School Seoul National University of Science and Technology Seoul South Korea Nano Manufacturing Research Center Seoul National University of Science and Technology Seoul South Korea Convex Computer Corporation Seoul South Korea Department of Mechanical System Design Engineering Seoul National University of Science and Technology Seoul South Korea

In this work, new approach of missing step detection without using costly encoder in a micro stepping motor is proposed. For a steeping motor driver, a MOSFET driven H-bridge driver was adopted, and sinusoidal type of current is controlled to implement the micro stepping. Also, in order to investigate the missing step the current flowing the coil which is generated from the operational amplifier was given feedback and the feedback data was analyzed to detect the missing step. As a sequence, the missing step was compensated as much as the amount of the missing steps, yielding the control of the desired micro stepping angle.

关键词： Coils Torque Position control Educational institutions MOSFET circuits Power electronics

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Data-driven protocol off-loading for Ad hoc networking environment

Data-driven protocol off-loading for Ad hoc networking envir...

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2008 International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA 2008

作者： Aoki, Kazuhiro Ishii, Hiroshi Mizuno, Osamu Iwata, Makoto Nishikawa, Hiroaki Information Infrastructure Laboratory Inc. Saiki 210-4 Tsukuba Ibaraki 300-0028 Japan School of Information Science and Technology Tokai University Kitakaname 1117 Hiratsuka Kanagawa 259-1292 Japan NTT Information Sharing Platform Laboratories Midori-cho 3-9-11 Musashino Tokyo 180-8585 Japan Department of Information System Engineering Kochi University of Technology Tosayamada-cho Miyanokuchi 185 Kami Kochi 782-8502 Japan Department of Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Ten'nodai 1-1-1 Tsukuba Ibaraki 305-8573 Japan

ISBN: (纸本)1601320841

Pervasive networking environment as social infrastructure has been going to become a reality, especially through the recent considerable progress of semiconductor technology. Considering the case where next generation of pervasive networking is realized over ad hoc network suitable for emergency and some tentative event, some ofauthors study about an data- driven imprementation of Ad hoc and ubiquitous communication environment. It is very important to implement effective protocol handling and routing process in Ad hoc networking environment especially. This paper describes the effectiveness ofan implementation ofprotocol off-loader using networking-oriented data-driven processors CUE (Coordinating User's requirements and Engineering constraints). In Ad hoc network, it is necessary to realize connection-less protocol such as UDP/IPfor flexible routing and realtime communication. Firstly, this paper discusses data- driven implementation ofprotocol off-loader on CUE networking board to minimize overheads in protocol handling. Then this paper describes architecture of CUE-v2/CUE-v3 which is available version in CUE processors. This paper finally discusses effectiveness ofprotocol handling off-loader using CUE processor system. It shows that data-driven protocol off-loader can keep minimum turn-around time without runtime overheads.

关键词： Ad hoc networks

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Basketball player’s value evaluation by a networks-based variant parameter hidden markov model

arXiv

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arXiv 2020年

作者： Du, Xin Cai, Weihong Liu, Jianquan Yu, Ding Xu, Kai Li, Wei Department of Computer Science College of Engineering Shantou University China Big Data Research Institute Tong Xing Technology Corporation China System Platform Research Laboratories NEC Corporation Japan Graduate School of Science and Engineering Hosei University Japan

Determining the value of basketball players through analyzing the players’ behavior is important for the managers of modern basketball teams. However, conventional methods always utilize isolated statistical data, leading to ineffective and inaccurate evaluations. Existing models based on dynamic network theory offer major improvements to the results of such evaluations, but said models remain imprecise because they focus merely on evaluating the values of individual players rather than considering them within their current teams. To solve this problem, we propose an analysis and evaluation model based on networks and a hidden Markov model. To the best of our knowledge, we are the first to combine a network form representing the players who are playing with the use of a hidden Markov model to mine the network and generate the desired results. Applying our approach to SportVU data collected from the National Basketball Association shows that this analysis and evaluation model can effectively analyze the performance of each player in a game and provides an assistive tool for team managers. Copyright © 2020, The Authors. All rights reserved.

关键词： Hidden Markov models

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An artificial immune system strategy for robust chemical spectra classification via distributed heterogeneous sensors

An artificial immune system strategy for robust chemical spe...

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Congress on Evolutionary Computation

作者： M.A. Esslinger G.B. Lamont H.S. Abdel-Aty-Zohdy R.L. Ewing Department of Electrical and Computer Engineering Air Force Institute of Technology Dayton OH USA Microelectronics System Design Laboratory Oakland University Rochester MI Information Directorate Wright-Patterson AFB Air Force Research Laboratory Dayton Ohio USA

The timely detection and classification of biological agents in a hostile environment is critical for increasing protection in critical areas. This paper proposes a strategy for identifying biological agents via distributed sensors with an artificial immune system (AIS). The proposed system is composed of networked sensors and nodes, communicating via wireless or wired connections. Measurements are continually taken via dispersed redundant sensors strategically placed in threat areas. These sensors continually measure and categorize air or liquid samples, alerting surrounding nodes when possible biological agents are detected. Detection is based upon the biological immune system (BIS) model of antigens and antibodies, and alerts are generated when a measured sample is determined to be a valid biological agent (antigen). Biological agent signatures (antibodies) are continually distributed throughout the system to adapt to changes in the environment or to new antigens.

关键词： Chemical sensors Artificial immune systems Robustness Sensor systems Biosensors Chemical and biological sensors Wireless sensor networks Protection Wireless communication Area measurement

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