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检索条件"任意字段=5th International Conference on Informational Processing in Sensor Networks"

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An Efficient Accelerator with Winograd for Novel Convolutional Neural networks 5

An Efficient Accelerator with Winograd for Novel Convolution...

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5th international conference on Circuits, Systems and Simulation (ICCSS)

作者： Lin, Zhijian Zhang, Meng Weng, Dongpeng Liu, Fei Southeast Univ Natl ASIC Engn Technol Res Ctr Sch Microelectron Nanjing Peoples R China Southeast Univ Natl ASIC Engn Technol Res Ctr Sch Elect Sci & Engn Nanjing Peoples R China

ISBN: (纸本)9781665481199

In recent years, the current trend of Convolutional Neural networks (CNNs) is toward lower computational cost to achieve lightweight. In lightweight convolutional neural networks, the depthwise separable convolution (DSC) is becoming the mainstream method. But in DSC, the pointwise convolution (PWC) with 1 x 1 filters still has abundant parameters and computation. In this paper, an more efficient convolution algorithm is proposed to replace PWC, named kernel shared group convolution (KSGC). KSGC is used to combine channel information, which can be seen as the same convolution kernel sliding on the channel. In addition, Winograd algorithm is used to mitigate the number of multiplications required by KSGC in this paper. A CNN accelerator using a novel processing element (PE) performs 1-D Winograd in KSGC was implemented on a Ultra96-V2 field-programmable gate array (FPGA).At 200MHz clock frequency, the acceler-ator achieved computational performance of 52.7GOPS and performance-power ratio of 10.42GOPS/W.

关键词： Winograd algorithm hardware accelerator kernel sharing group convolution

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A new method for diagnosing insulation failures in battery packs based on BiLSTM networks 5

A new method for diagnosing insulation failures in battery p...

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2024 5th international conference on Electrical, Electronic Information and Communication Engineering, EEICE 2024

作者： Li, Yanming Duan, Liyuan Zhang, Sining Song, Keling China Northern Vehicle Research Institute Beijing100000 China Northeastern University Liaoning Shenyang110819 China

Power batteries need to meet the high voltage and large capacity requirements of automobiles, especially under high voltage. their insulation performance requirements are more stringent. the essay first establishes a mold suitable for insulation failure diagnosis basis the second-order thevenin equivalent model. then, the BiLSTM network structure is introduced to construct an insulation failure diagnosis model based on BiLSTM. this model enhances the model's ability to capture data by bidirectional processing of past and future time series of battery pack insulation data. Finally, the proposed method was validated under different operating conditions. the results showed that the error of the method remained at a low level under both static and dynamic conditions, fully demonstrating the effectiveness of the method in improving prediction accuracy and applicability. © Published under licence by IOP Publishing Ltd.

关键词： Battery Pack

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Automatic Personal Annotation from Head Pose in Multi-View Systems 5

Automatic Personal Annotation from Head Pose in Multi-View S...

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5th IEEE international conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Vachev, Krasimir Mironov, Rumen Hristov, Plamen Technical University of Sofia Faculty of Telecommunications Radio Communications and Video Technologies Department Sofia1000 Bulgaria

ISBN: (纸本)9798350352863

We developed an algorithm for automatic personal annotation for multi-view systems. Several problems arise when the annotation process is implemented in such a system. One of these problems is connected to the credibility criterion - the selection of optimal head poses. Another problem is connected to the number of images sufficient for the multi-view system to recognize the individual. An additional challenge is how to organize and store the extracted face images. Our algorithm applies a combination of CNN and SVM for the annotation. With the help of a Kinect sensor, the person is detected and his face is localized. the algorithm annotates the poses on the basis of the three angles of the head - yaw, pitch and roll. they are recorded in the database with the corresponding angles. the neural network was tested first on the CroppedYale B dataset and then on a dataset created by Kinect. After tuning the network's parameters, almost all images with varying poses were classified correctly. Experiments were also made to find the range of angles, suited for the accurate annotation. With additional tests, the minimal number of images for individuals sufficient to train the network, was explored as well. © 2024 IEEE.

关键词： Convolutional neural networks

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Locating the Rumor Source in Social networks using Timestamps 5

Locating the Rumor Source in Social Networks using Timestamp...

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5th international conference on Computer, Communication, and Signal processing, ICCCSP 2021

作者： Devarapalli, Ravi Kishore Biswas, Anupam National Institute of Technology Silchar Department of Computer Science and Engineering Assam788010 India

ISBN: (纸本)9781665432771

We discuss the problem of locating the rumored origin in the social networks. Earlier works focused on network structure and sensor nodes;we concentrate on the timestamp of infected nodes. We recommend a two-stage algorithm to find the root node in a network using neighbor nodes' timestamp. In the first stage, discover the neighbor nodes with the minimal timestamp. Second, find the origin node using the minimal timestamp of the friend nodes. Simulations illustrate that our proposed two-stage algorithm works well and determines the root node within few hops. We evaluate our algorithm on small- scale networks, large-scale networks, and artificial networks. Our numerical results also show that our recommended two-stage algorithm operates well to discover the root node accurately, with a higher success rate and fewer distance error hops. © 2021 IEEE.

关键词： sensor nodes

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Wireless Sensing Network's Cyber Security Procedures: A Research 5

Wireless Sensing Network's Cyber Security Procedures: A Rese...

引用

5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Singh, Harveer Dhiman, Neha Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India Chandigarh Engineering College Department of Computer Science & Engineering Jhanjeri India

ISBN: (纸本)9798350398267

Because WSNs (wireless sensor networks) are connected to the internet, they are an effective network for solving practical issues. A lightweight, equipment sensor with computational possibilities and limited power supplies is available in WSN as new technologies develop quickly. However, there is a significant security issue with this network. Because of the wireless communication channel, it is now challenging to guard against numerous attacks like DoS (Denial of Service). As a consequence, several different methods for identifying DoS attacks have indeed been suggested. Several indicators, including bandwidth, PDR (packet delivery ratio), and E2E (end to end) latency are calculated to assess the impact of an attack on a network. the simulations make use of real-world datasets. Even while simulations demonstrate that DoS attacks make WSNs less resilient, certain systems have been shown to be good at spotting DoS attacks. © 2022 IEEE.

关键词： Wireless sensor networks

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Research on Cluster-Based Routing Protocol for Wireless sensor networks 5

Research on Cluster-Based Routing Protocol for Wireless Sens...

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5th IEEE international conference on Information Systems and Computer Aided Education, ICISCAE 2022

作者： Liu, Bangyan Zhang, Jiuchuan Zhu, Zhenxiong Chongqing University Chongqing400000 China University of Electronic Science and Technology of China Chengdu610000 China Nanjing Normal University Nanjing210028 China

ISBN: (数字)9781665481229

ISBN: (纸本)9781665481229

LEACH routing algorithm is an important routing algorithm in wireless sensor networks (WSN s), there exist imperfections in the LEACH algorithm, which can be summarized as the uneven number of cluster heads, the unreasonable distribution of cluster heads and inappropriate selection of cluster heads. Researchers has put forward algorithms based on LEACH as improvement. In this paper, we focused on analysis of inappropriate selection of clusters in LEACH routing algorithm from energy consumption approach. To solve this existing issue in LEACH routing algorithm, a new algorithm that maximum the efficiency of energy consumption is proposed in this paper, which is LEACH-OptCluster. this paper analyses the disadvantages of LEACH routing algorithm. LEACH-C routing algorithm is introduced as comparison with proposed algorithm. Simulation of LEACH-OptCluster is conducted through Matlab. With simulation results, further analysis indicates the proposed LEACH-OptCluster routing algorithm can prolong the WSNs network working time effectively through balancing the overall energy consumption of network nodes. © 2022 IEEE.

关键词： Wireless sensor networks

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FPGA based Smart and Sustainable Agriculture 36

FPGA based Smart and Sustainable Agriculture

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36th international conference on VLSI Design (VLSID) / 22nd international conference on Embedded Systems (ES)

作者： Peraka, Shyam Ali, S. K. Irfan Mogili, Durga Vasu Palivela, Ashok Kumar Reddy, Sudheer Bavisetti, Jyotsna Reddy, Dhanush Y. RGUKT Nuzvid Dept Elect & Commun Engn Nuzvid India RGUKT Nuzvid Dept Comp Sci & Engn Nuzvid India

ISBN: (纸本)9798350346787

the agriculture sector is one of the key areas of concern interlinked with most of the Sustainable Development Goals (SDGs), as stated by most organizations. However, technological advancements and agricultural intervention, particularly in developing and underdeveloped countries, are still in their early stages. IoT, cloud computing, data analysis, and other technologies are being widely used in most areas, where they are bringing significant changes in outcomes compared to previous conventional practices. It is also observed that there have been some initiations in bringing such technologies into agriculture to assist farmers, but they are not comprehensive and real-time working prototypes. Hence, we have come up with a novel, comprehensive solution to address different issues. the focus of the proposed paper is to develop and design a real-time prototype model implementing the following: 1. Control of the irrigation system based on crop stage requirements and other factors such as soil nature, humidity levels, rainfall levels, and so on. 2. Detection of weeds and disease using image processing and machine learning algorithms 3. Identification and recommendation of suitable crops based upon the nature of the soil, fertility levels, climatic conditions, water availability, etc. 4. Voice-based responsive system-mobile application or web-based application. the above tasks were successfully implemented and tested on the prototype developed with the help of the DE10 Nano Cyclone FPGA board. the sensors used in the project include the NPK sensor, moisture sensor, pH sensor, electric conductivity sensor, and water level sensor. Azure cloud services are used for the deployment of the website. the farmer is able to get the voice-based response through a mobile application developed for this purpose.

关键词： DE10-Nano Cyclone V FPGA Azure Cloud sensors Crop Recommendation Smart Agriculture Sustainable Agriculture Soil Testing Smart Irrigation Weed Detection Disease Detection Voice commands Web Application Machine Learning Algorithms Convolution Neural networks Yolo V5 XG Boost

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Long Short-term Dynamic Graph Neural networks: for short-term intense rainfall forecasting 5

Long Short-term Dynamic Graph Neural Networks: for short-ter...

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5th international conference on Machine Learning and Natural Language processing (MLNLP)

作者： Xie, Huosheng Wang, WeiJie Fuzhou Univ Fuzhou Fujian Peoples R China

ISBN: (纸本)9781450399067

In practice, accurate and timely forecasting of short-term intense rainfall is critical, but the problem is extremely difficult because to its complicated spatial-temporal association. Although several spatial-temporal series forecasting methods have been used to rainfall prediction, these models continue to suffer from inadequate modeling of data's complicated intrinsic connection. We provide a new short-term intense rainfall prediction model that use two graph generators to model data correlations under distinct semantics, followed by a graph convolution module for information integration to fully extract data spatial-temporal information. Finally, a variant of recurrent neural network is employed to extract the temporal dependence. the experimental results on both datasets show that the model can model the spatial and temporal dependence across the data more effectively than the baseline model, and further improve the model's predictive performance for short-term intense rainfall.

关键词： Short-term intense rainfall spatial-temporal correlation Graph Convolution

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5th IEEE international conference on Artificial Intelligence and Big Data, ICAIBD 2022

作者： Zhengfang, He MacHica, Ivy Kim D. Zhimin, Bi Faculty College of Information and Computing Davao City Philippines Yunnan Technology and Business University School of Intelligent Science and Engineering Kunming China

ISBN: (纸本)9781665499132

Textual similarity measurement has become even more important in natural language processing for information retrieval. the improvement in the accuracy of machine translation is a prime reason for developing a two-stage model of fine-tuning Bidirectional Encoder Representation from Transformers (BERT) and training using the Double Siamese Text Convolutional Neural networks (DSTCNN). the first stage task is improved to use the output of each word of BERT as the input of the DSTCNN model. the DSTCNN model is proposed in the second stage task to determine the sequential and reverse relationship. the design motivation and detailed structure of the DSTCNN model are provided. Also, the STS-B dataset was used for the experiment. the Two-stages model achieved 88.1% Spearman's rank correlation coefficient, which increased by 1.6%, compared with the first-stage model. the experimental results show that using the two-stage model yields an improved performance compared to other algorithms. © 2022 IEEE.

关键词： Convolutional neural networks

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Context based Emotion Recognition from Bengali Text using Transformers 5

Context based Emotion Recognition from Bengali Text using Tr...

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

作者： Ahmed, Lopa Polok, Isbat Khan Islam, Md Adnanul Akhtaruzzaman, Md Mukta, Md. Saddam Hossain Rahman, Md. Mahbubur Military Institute of Science and Technology Dept. of Cse Dhaka Bangladesh United International University Dept. of Cse Dhaka Bangladesh

ISBN: (纸本)9781665474672

Every individual's everyday life has become a routine of expressing their ideas, opinions, emotions, and experiences through social networking sites and platforms on the internetin this era of rapid technological innovation. these points of view can be utilized to develop strategies for increasing efficiency in a range of fields, including business, politics, research, and analysis. Natural language processing (NLP) uses emotion detection to automatically monitor, evaluate, and categorize people's ideas and opinions in order to get a sense of how they feel. To date, a substantial amount of study has been done on the Emotion Recognition of the English language, with notable results. Unfortunately, there has been a scarcity of research on the Bangla language in the subject of Emotion Recognition. Despite the fact that social networks have increased the popularity of romanized Bangla among Bangla speakers, there is even less research on romanized Bangla text. As a result, the focus of this study was on emotion recognition for both raw and romanized Bangla texts. A corpus of romanized Bangla texts was created from a raw Bangla feeling corpus in this study. Datasets of military, medical, religious and general context are collected and tested with the Bidirectional Encoder Representations from Transformers. Finally, the outputs are studied and evaluated. © 2023 IEEE.

关键词： Emotion Recognition

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