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PPC-US-LSF3DOD: A Pseudo-Point-Clouds based Unsupervised and Scalable Late-sensor-Fusion Method for 3D Obstacle Detection 5

PPC-US-LSF3DOD: A Pseudo-Point-Clouds based Unsupervised and...

引用

5th international conference on Robotics and Computer Vision, ICRCV 2023

作者： Zhang, Bowen Tanaka, Masahiro Graduate School of Natural Science Konan University Kobe Japan

ISBN: (纸本)9798350326369

To get the 3D coordinates and sizes of multi-scale obstacles, we propose an unsupervised and scalable late sensor fusion method using pseudo point clouds obtained from the stereo camera. In order to obtain high-quality depth maps and point clouds, we first perform various preprocessing and postprocessing on them, such as Speckle filter, probabilistic denoising, etc. then we propose a multi-scale method for the problem of different ground heights and different scales of point cloud clustering. In addition, we also utilize an RGB monocular camera aligned with a stereo camera for late sensor fusion, which enables partially unlabeled point cloud obstacles to be assigned to a category. Our experimental results show that the proposed system achieves superior results on mobility scooters and electric wheelchairs without requiring a lot of computing resources and equipment costs. © 2023 ieee.

关键词： Computer vision

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A Low-cost, Flexible Electrochemical sensor for Nitrate Detection in Water 5

A Low-cost, Flexible Electrochemical Sensor for Nitrate Dete...

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5th ieee international conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Riam, Shah Zayed Islam, Md. Najmul Inam, A.K.M. Sarwar Tabassum, Shawana The University of Texas at Tyler Department of Electrical Engineering TylerTX75799 United States

ISBN: (纸本)9781665457330

this study presents the development and evaluation of a flexible, screen-printed electrochemical sensor for detecting nitrate levels in water. the sensor was composed of a working and a reference electrode. the working electrode was coated with a nanocomposite of poly(3-octyl-thiophene) and molybdenum disulfide and a nitrate-selective layer to improve sensitivity and selectivity. the sensor demonstrated high sensitivity of 9.91 mV/ppm and 8.99 mV/ppm when tested in deionized and lake water, respectively. Additionally, the sensor exhibited excellent repeatability under bending deformations and stability underwater for up to 4 days. Overall, this work offers a scalable and cost-effective solution for continuous monitoring of nitrate levels in direct lake water. © 2023 ieee.

关键词： Nitrates

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Bio sensor Technology Applications and Development in Process Industry 5

Bio Sensor Technology Applications and Development in Proces...

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5th international conference on Smart systems and Inventive Technology, ICSSIT 2023

作者： Walke, Santosh Mandake, Manoj B. National University of Science and Technology College of Engineering Faculty Mechanical and Industrial Engineering Department Muscat Oman Bharati Vidyapeeth College of Engineering Department of Chemical Engineering Maharashtra Navi Mumbai India

ISBN: (纸本)9781665474672

sensors, as the basic technology of Electronics, can not only endure harsh exterior environment tests, but also acquire information properly and promptly, which is a crucial assurance for electronics rapid development. India now produces different types of sensors, including force sensitivity, color sensitivity, biological sensitivity, sensitive to voltage, too. these sensors are being used in a growing number of applications. In order to speed up the development of high quality in the field of electronics, this study, which is based on the current use of sensors, examines the problems that exist in practical operation to scientifically point out the development direction of sensor technology. © 2023 ieee.

关键词： Timing circuits

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SMVAR: A Novel RNN Accelerator Based on Non-blocking Data Distribution Structure 25

SMVAR: A Novel RNN Accelerator Based on Non-blocking Data Di...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Xu, Jinwei Jiang, Jingfei Xu, Shiyao Gao, Lei National University of Defense Technology Science and Technology on Parallel and Distributed Laboratory Hunan Changsha China

ISBN: (纸本)9798350330014

Recurrent neural networks (RNNs) have become common models in the field of artificial intelligence to process temporal sequence task, such as speech recognition, text analysis, natural language processing, etc. To speedup RNNs inference, previous research proposed model sparse pruning techniques. However, the pruning rate of existing sparse pruning algorithms will be affected by pruning granularity and hardware friendliness. In order to approximate nonstructured pruning algorithm, this paper proposes Large Region Balanced Sparse (LRBS) pruning method, which does not limit sub-matrix shape and effectively improves pruning rate. Furthermore, we propose Sparse Matrix Vector Multiplication Accelerator for RNNs (SMVAR), which adopt non-blocking data distribution structure to solve the problem of efficient execution of large region irreg-ular matrix multiplication. To further improve the accelerator performance, SMVAR fine-grained adjusts the pipeline between macro-operations to reduce the idle of compute components. In addition, according to the coarse-grained block characteristics of LRBS algorithm, we develop the coarse-grained parallelism of accelerator with multiply compute units(CUs) structure. Experiments show that the pruning rate of our proposed LRBS is 1.25x-2.5x higher than that of the existing pruning algorithms. Compared with the existing work, the execution efficiency is improved by more than 2.02x-35.9x in the same application scenario. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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Detection of Dental Cavity using Wireless sensor based Technology 5

Detection of Dental Cavity using Wireless Sensor based Techn...

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5th ieee international conference on Advances in computing, Communication Control and Networking, ICAC3N 2023

作者： Kumari, Rani Astya, Parmanand Kantha, Praveen Kaur, Damandeep Chitkara University School Of Engineering & Technology Chitkara University Himachal Pradesh India Sharda University Department Of Computer Science And Engineering Greater Noida India Chitkara University Institute Of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9798350330861

Dental Cavities are most common persistent disorders across the lifespan and are mainly avoidable. Untreated tooth decay can develop in an abscess behind the gums, it's a type of infection that may be spread in to other regions of the mouth or between tooth and cause catastrophic, occasionally fatal consequences. Now days, dental caries is a common tooth decay issue and the people of all generations may be affected from this problem especially children. Because of its increasing incidence, successful intervention measures are required. To provide best care and early detection of cavities, wireless sensor technology has gained popularity in the dental industry. In an effort to avoid and diagnose dental caries in the first stage of cavity, this article suggests innovative and creative approach based on wireless sensors technology, cloud storage for patient data storage, telemedicine. this paper explain different types of sensors used in detection process of dental cavity. through this article, we suggest a sensor technology based dental cavity detection model and explain how we detect dental caries based on collected data by sensors. © 2023 ieee.

关键词： Hospital data processing

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the Impact of Alteration of Superframe Duration on the Consumption of Energy in the ieee 802.15.4 MAC 5

The Impact of Alteration of Superframe Duration on the Consu...

引用

5th international conference on Smart systems and Inventive Technology, ICSSIT 2023

作者： Pandey, Uma Shankar Soni, Gulshan Chandra, Saroj Kumar O.P. Jindal University School of Engineering Department of Cse Raigarh India

ISBN: (纸本)9781665474672

the modern healthcare monitoring system is getting benefited by new emerging technologies, such as tiny physiological sensors and the latest wireless technologies. the Wireless Body Area Networks (WBANs) introduce live tracing of vital signs, online diagnosis, and various other advantages when compared with the traditional system. the duty cycle (wake-up and sleep) performs a crucial function in the conservation of the limited battery power of physiological sensors. A scheme is introduced in this paper that adjusts the duration of superframe in the beaconenable mode of ieee 802.15.4 MAC. the proposed scheme's key objective is to prolong the lifetime of the physiological sensor by altering superframe duration. through extensive simulations, it is shown that the superframe duration may be appropriately adjusted to improve energy efficiency without significantly reducing network throughput. © 2023 ieee.

关键词： Medium access control

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Edge computing Based Real-Time Streaming Data Mining Method for Wireless sensor Networks 5th

Edge Computing Based Real-Time Streaming Data Mining Method ...

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5th EAI international conference on Advanced Hybrid Information Processing (ADHIP)

作者： Huang, Zhong-xing Ren, Xiao-li Zhou, Zai-ling Zhu, He Lin, Zhi-li Guangzhou Metro Design & Res Inst Co Ltd Guangzhou 510000 Peoples R China Zhongye Design Co Ltd Guangzhou 510000 Peoples R China

ISBN: (纸本)9783030945541;9783030945534

Traditional data mining techniques are difficult to be directly applied to wireless sensor networks because of the multidimensional and multilayered characteristics of wireless sensor networks. Based on the theory of edge computing, the framework of distributed data mining workflow in wireless sensor networks is optimized, and the flow of distributed data mining in wireless sensor networks is demonstrated. Finally, the design requirements of data mining methods are realized.

关键词： Edge computing Wireless sensor network Data mining

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Intelligent System for distributed Deep Learning Training Traffic Optimization 24

Intelligent System for Distributed Deep Learning Training Tr...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Lu, Weipeng Wu, Shuang Ou, Junhui Niu, Bing He, Jin Song, Kevin Zheng, Xinwei Ustc Hefei China Vmware Beijing China

ISBN: (纸本)9798350319934

distributed training crossing multiple computing nodes and accelerators has been the mainstream solution for large model training. Precedent work on distributed deep learning (DDL) training acceleration has focused on improving the efficiency of communication and GPU resource scheduling, with little attention given to network bandwidth usage. However, due to cluster GPU fragmentation, more than one training job is frequently assigned to the same node to reduce waiting time. the competition for network bandwidth among various distributed training jobs becomes a problem that cannot be overlooked, and this competition results in a considerable reduction in training speed. We propose a system deployed in cluster nodes that includes traffic monitoring, classification, and prediction of DDL training status and implement a priority-based traffic scheduling policy that considers DDL training features. We demonstrate that this policy is beneficial compared to Linux's default policy, which can increase training speed by approximately 18%. Additionally, we increase the training speed by approximately 20% in the case of continuous background traffic by increasing the bandwidth priority during DDL training. © 2022 ieee.

关键词： Deep learning

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EPV-PBFT: PBFT Improved Consensus Algorithm for sensor Networks 5

EPV-PBFT: PBFT Improved Consensus Algorithm for Sensor Netwo...

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5th international conference on Applied Machine Learning, ICAML 2023

作者： Guo, Shangkun Yao, Zhongyuan Zhang, Yong Wang, Chao Guo, Xiaohan Si, Xueming Research Institute of Frontier Information Technology Zhongyuan University of Technology Zhengzhou450007 China Henan Key Laboratory of Network Cryptography Technology Zhengzhou450007 China Henan International Joint Laboratory of Blockchain and Data Sharing Zhengzhou450007 China

ISBN: (纸本)9798350341416

the decentralization and non-tampering characteristics of blockchain technology provide new ideas for solving the security and scalability problems in sensor networks. However, there are still some obstacles to the application of blockchain to sensor networks, sensor nodes usually have low power consumption, low computing power, low communication overhead and low storage capacity, but the existing blockchain consensus mechanism often requires nodes to have high computing power and communication capabilities, so proposing a blockchain consensus mechanism adapted to sensor nodes is one of the key problems to solve the integration of blockchain and sensor network. In order to reduce the computing and communication overhead of the blockchain consensus mechanism and improve the applicability of blockchain in the sensor network, this paper proposes a PBFT consensus optimization algorithm based on node state evaluation and voting mechanism, EPV-PBFT (Energy Pledge Voting-based Practical Byzantine Fault Tolerance). Based on the oracle super-linear staking mechanism and node residual energy state evaluation model, the algorithm performs malicious node screening and consensus node level authority division, so as to improve the node evil cost and communication efficiency. Further combine the verifiable mechanism and voting mechanism to improve the fault tolerance of the algorithm and reduce the communication overhead. Experimental data show that compared with the classical PBFT algorithm, the consensus optimization algorithm proposed in this paper can reduce the average overhead of 43.25% in terms of communication energy consumption, have shorter consensus delay and higher throughput, and can effectively support the management of blockchain network by sensor nodes. © 2023 ieee.

关键词： Blockchain

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Energy Harvesting Integrated sensor Node Architecture for Sustainable IoT Networks 5th

Energy Harvesting Integrated Sensor Node Architecture for S...

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5th international conference on Advances in distributed computing and Machine Learning, ICADCML 2024

作者： Gopikrishnan, S. Kokila, M. Rivera, Marco Wheeler, Patrick School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India Power Electronics Machines and Control PEMC Research Group University of Nottingham Nottingham United Kingdom Universidad de Talca Curicó Chile

ISBN: (纸本)9789819735228

Internet of things (IoT) is a life changing technology which is build on various devices which are connected to the Internet. Wireless sensor nodes (WSN) is one of such devices which plays a major role in deploying IoT in large scale of real-time even monitoring applications. But the energy limitations of those sensor nodes limits the features of IoT networks. Hence improving the energy limitations in WSN plays a vital role in last decade. this chapter presents the possibilities of enhance the energy limitations of sensor nodes with renewable energy resources. the proposed integrated architecture of this proposed model discusses the implementation of sensor node with flexible solar energy harvester module, multi mode communication capability and multi sensor data module. the special contribution in this chapter includes the hardware specification with budget analysis, sleep-awake strategy to effective use of energy and maximum possible data collection from the environment. the novelty and improvement of the proposed model has been proved with mathematical model as well as the real-time measurements from the prototype. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Solar energy

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