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An Intelligent Robust One Dimensional HAR-CNN Model for Human Activity Recognition using Wearable sensor Data 4

An Intelligent Robust One Dimensional HAR-CNN Model for Huma...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Deepan, P. Santhosh Kumar, R. Rajalingam, B. Kumar Patra, P. Santosh Ponnuthurai, S. St. Martins Engineering College India Roever Engineering College India

ISBN: (纸本)9781665474368

One of the biggest new trends in artificial intelligence is the ability to recognise people's movements and take their actions into account. It can be used in a variety of ways, including for surveillance, security, human-computer interaction, and content-based video retrieval. there have been a number of researchers that have presented vision-based techniques to human activity recognition. Several challenges need to be addressed in the creation of a vision-based human activity recognition system, including illumination variations in human activity recognition, interclass similarity between scenes, the environment and recording setting, and temporal variation. To overcome the above mentioned problem, by capturing or sensing human actions with help of wearable sensors, wearable devices, or IoT devices. sensor data, particularly one-dimensional time series data, are used in the work of human activity recognition. Using 1D-Convolutional Neural Network (CNN) models, this works aims to propose a new approach for identifying human activities. the Wireless sensor Data Mining (WISDM) dataset is utilised to train and test the 1D-CNN model in this dissertation. the proposed HAR-CNN model has a 95.2%of accuracy, which is far higher than that of conventional methods. © 2022 ieee.

关键词： Neural network models

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A Reliable and efficient data transfer on wireless sensor networks by using Optimization algorithms 4

A Reliable and efficient data transfer on wireless sensor ne...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Saravanan, T. Rajulu, G. Govinda Gitam School of Technology Department of CSE Bengaluru India St. Martin's Engineering College Department of CSE Secunderabad India

ISBN: (纸本)9781665474368

Wireless sensor Network technologies that require collecting all node-generated data without any losses like structural monitoring. Since wireless networks and resource constraints present additional challenges, point-to-point transmission, which is employed in the network for sustainable communication, becomes extremely ineffective in Wireless sensor Networks. We investigate elements that determine reliability and explore effective combinations of possible solutions. You can implement information redundancy techniques like rebroadcasting and destruction of data techniques. Additionally, route maintenance, which explores an alternate hop and several faults, minimizes packet drops. In this paper, we evaluated several machine learning optimization algorithms for efficient and reliable data transfer in wireless networks. Our simulation results prove that each opportunity overcomes different types of flaws that occurred by the existing techniques. the Arithmetic Optimization Algorithm, Particle Swarm Optimization, and Shuffled Complex Evolution Algorithm is efficient in obtaining reliability, achieving very high reliability by enduring packet losses, and it responds very instantly to link failures. that's the proposed combination of optimization algorithms that can prove more than 90% memory consumption with Time, High Speed, and Accuracy by providing an alternative to point-to-point communication over multiple nodes in the network. © 2022 ieee.

关键词： Data transfer

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SpecTextor: End-to-End Attention-based Mechanism for Dense Text Generation in Sports Journalism 8

SpecTextor: End-to-End Attention-based Mechanism for Dense T...

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8th ieee international conference on Smart computing (SMARTCOMP)

作者： Ghosh, Indrajeet Ivler, Matthew Ramamurthy, Sreenivasan Ramasamy Roy, Nirmalya Univ Maryland Baltimore Cty Mobile Pervas & Sensor Comp Lab Baltimore MD 21228 USA Univ Maryland Baltimore Cty Ctr Real Time Distributed Sensing & Auton Cards Baltimore MD 21228 USA Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21228 USA Pomona Coll Dept Comp Sci Claremont CA 91711 USA

ISBN: (纸本)9781665481526

Language-guided smart systems can help to design next-generation human-machine interactive applications. the dense text description is one of the research areas where systems learn the semantic knowledge and visual features of each video frame and map them to describe the video's most relevant subjects and events. In this paper, we consider untrimmed sports videos as our case study. Generating dense descriptions in the sports domain to supplement journalistic works without relying on commentators and experts requires more investigation. Motivated by this, we propose an end-to-end automated text-generator, SpecTextor, that learns the semantic features from untrimmed videos of sports games and generates associated descriptive texts. the proposed approach considers the video as a sequence of frames and sequentially generates words. After splitting videos into frames, we use a pre-trained VGG-16 model for feature extraction and encoding the video frames. With these encoded frames, we posit a Long Short-Term Memory (LSTM) based attention-decoder pipeline that leverages soft-attention mechanism to map the semantic features with relevant textual descriptions to generate the explanation of the game. Because developing a comprehensive description of the game warrants training on a set of dense time-stamped captions, we leverage two available public datasets: ActivityNet Captions and Microsoft Video Description. In addition, we utilized two different decoding algorithms: beam search and greedy search and computed two evaluation metrics: BLEU and METEOR scores.

关键词： Sports Journalism Semantic Knowledge LSTM Soft-Attention Mechanism Beam Search Greedy Search Human-Machine Interactive Applications

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Design of distributed Offloading Algorithm Based on Mobile Edge computing Network

Design of Distributed Offloading Algorithm Based on Mobile E...

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Consumer Electronics and Computer Engineering (ICCECE), 2021 ieee international conference on

作者： Ling Xu Yingsheng Zhao Yiguo Mei Zhiguang Liu Hangzhou Dianzi University College of Communication Engineering Hangzhou China Huaxin Consulting Co. Ltd College of Mobile Research Hangzhou China

the paper models the interaction process between users and edge cloud based on the Stackelberg game. Firstly, the users' cost is modeled as a minimization problem with the amount of offloaded tasks of each user as a constraint and the revenue of edge cloud is modeled as a maximization problem with the computation capacity of the edge cloud server as a constraint. then, for the problem of minimizing users' cost, the paper derives the optimal offloading scheme under uniform pricing which follows the threshold strategy and gives the users' bandwidth allocation strategy. Finally, for the problem of maximizing the revenue of edge cloud, the paper substitutes the optimal offloading plan, and finds the optimal price. the paper compares the proposed distributed offloading algorithm with optimized bandwidth allocation with the fully local computing algorithm and the bandwidth sharing algorithm. the average user latency has been reduced by more than 30% and 20%, and the revenue of edge cloud has increased by more than 1.5 times.

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A Secure Authenticated Message Transfer in Vehicle to Grid Networks 4

A Secure Authenticated Message Transfer in Vehicle to Grid N...

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4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Sowmiya, L. Sekar, Rajasekaran Arun Subramaniam, Gnanasaravanan Purushothaman, A. Tiwari, Mohit Tiwari, Tripti M e Vlsi Design Kpr Institute of Engineering and Technology Coimbatore India Kpr Institute of Engineering and Technology Department of Ece Coimbatore India Karunya Institute of Technology and Sciences Department of Biomedical Engineering Coimbatore India Hindusthan Institute of Technology Department of Ece Coimbatore641032 India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering A-4 Rohtak Road Paschim Vihar Delhi India Institute of Management and Research Department of Management Studies Delhi India

ISBN: (纸本)9798350300093

Due to the recent emerging trends in technology, Vehicle to Grid (V2G) networks plays a major role in smart grid system. Now a days using of electric vehicles has increased than the usage of fuel-based automobiles under transportation. Electric vehicles mainly use electricity instead of fuels that is distributed by the charging terminal. Generally, the charging terminal will be situated in gasoline stations or on road sides and electric vehicles get charged at the stations. In V2G communication networks, the communication takes place between the charging terminal and the electric vehicle will be affected by several cyber-attacks. In addition to that, the electric vehicle owner's personal information should be kept secure. In this proposed system, charging terminal and electric vehicles initially register their identities at the control authority. Using of Anonymous mutual authentication scheme, the charging terminal and the electric vehicle authenticates with each other and establish protected communication between them. During Session Key Exchange protocol, the information passed from the charging terminal will be transferred to the electric vehicle with the help of session keys. Duplicate identity of the charging terminal and electric vehicle is created in order to protect the original identity of the users who are present in V2G networks. Proposed scheme gives strength against various security attacks and cost of the system is also reduced. the main aim of this proposed system is to maintain confidentiality and integrity among the V2G communication networks. © 2023 ieee.

关键词： Vehicle-to-grid

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distributed Optical Fiber Monitoring Technology for Monitoring the Ultra-high Temperature and Pressure in Exploitation by Fire Flooding 4

Distributed Optical Fiber Monitoring Technology for Monitori...

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4th international Academic Exchange conference on Science and Technology Innovation, IAECST 2022

作者： Zhang, Fuxing Li, Teng Drilling & Production Technology Institute of Liaohe Oilfield Company Panjin124100 China

ISBN: (纸本)9798350320008

Fire flooding, a key successive technology in later stage of thermal recovery of heavy oil, has entered the stage of industrialized field test. To make effective monitoring on ultra-high temperature and pressure in the process of ignition for fire flooding, gold coated pure silicon optical fiber was selected, a type of "1+6"structural twisted optical cable armored in steel tube was designed and intrinsic optical fiber F-P cavity pressure sensor with microgroove was developed. Further, 1064nm-wavelength laser device was selected as the core for demodulating gold coated optical fiber and distributed temperature demodulator under double actions of 1064nm-wavelength and 980nm-wavelength lasers was developed. On this basis, an ultra-high temperature and pressure monitoring system for exploitation by fire flooding was researched and developed. Based on the test results of temperature and pressure at each oil reservoir, the well depth was corrected in four steps, including depth correction after well completion, depth correction after setting by packer, depth correction at oil reservoir and verification after ignition. Moreover, the ignition scheme for fire flooding was optimized as per the law of well temperature changing with ignition time and well depth as shown dynamically in the spectrogram in order to guarantee the successful implementation of industrialized field test for fire flooding. © 2022 ieee.

关键词： Crude oil

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Evaluating Lightweight GAN- and Adapted CTGAN-Based Data Synthesis for Predictive Maintenance in High-Radiation Environments 11

Evaluating Lightweight GAN- and Adapted CTGAN-Based Data Syn...

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11th ieee/ACM international conference on Big Data computing, Applications and Technologies, BDCAT 2024

作者： Al-Hasan, Tamim M. Zhai, Xiaojun Mcdonald-Maier, Klaus D. Bensaali, Faycal Cryer, Alice University of Essex Colchester School of Computer Science and Electrical Engineering EssexCO4 3SQ United Kingdom Qatar University Al Tarfa College of Engineering Department of Electrical Engineering Doha Qatar United Kingdom Atomic Energy Authority Culham Science Centre Abingdon Remote Applications in Challenging Environments OxfordshireOX14 3DB United Kingdom

ISBN: (纸本)9798350367300

this paper presents a comparative analysis of two developed Generative Adversarial Network (GAN) architectures for synthesizing sensor data in predictive maintenance (PdM) applications within high-radiation environments. the study ad-dresses the challenge of data scarcity in such settings, where experimental runs are constrained by the risk of device failure and economic considerations. the two GAN models: GAN-1 uses the Conditional Tabular GAN (CTGAN) architecture, and GAN-2 employs a custom network. these models generated synthetic datasets that were used to train and evaluate three machine learning algorithms: Random Forest, k-Nearest Neighbours, and eXtreme Gradient Boosting. the performance of these PdM models trained on synthetic data was compared against models trained on the original limited dataset. Results demonstrate that GAN-1 produced synthetic data closely mirroring the characteristics of the original dataset, enabling PdM models to achieve comparable performance levels. this study highlights the potential of GAN-based data synthesis in enhancing PdM model development for high-radiation environments, offering a viable solution to the challenges of limited data availability in such harsh settings. the findings have significant implications for improving operational reliability and safety in nuclear and other extreme environments where electronic systems are deployed. © 2024 ieee.

关键词： Gamma rays

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DLT design and robustness verification based on random graph theory 4

DLT design and robustness verification based on random graph...

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4th international Science and Technology conference "Modern Network Technologies", MoNeTec 2022

作者： Brooks, R.R. Clemson University Holcombe Department of Electrical and Computer Engineering ClemsonSC United States

ISBN: (数字)9781665472463

ISBN: (纸本)9781665472463

distributed Ledger Technology (DLT), commonly referred to as blockchains, provide a new approach to security. Rather than securing items by blocking access, data is made immutable by creating a massively distributed data structure. Entries are secured using cryptographic primitives. Coordination is done using consensus algorithms. We start by introducing random graph theory and presenting its major result: the emergence of a giant component. We explain how and when giant components arise. We explain why the existence, or not, of giant components result in the presence, or not, of graph properties of interest. We then introduce the most widely used consensus algorithms, concentrating on potential problems. We then describe a simple light weight mining (LWM) alternative. We use Erdös's random graph theory to prove the effectiveness and efficiency of LWM. this is an example of how random graph theory can be used to design and implement robust DLT systems © 2022 ieee.

关键词： distributed ledger

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Precise Fault Distance Prediction in distributed Generators-Integrated Transmission Lines Using CNN-LSTM Ensemble Networks 4

Precise Fault Distance Prediction in Distributed Generators-...

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4th international conference on Power, Control and computing Technologies, ICPC2T 2025

作者： Bais, Pavan Kumar Londhe, Narendra D. Electrical Engineering Department National Institute of Technology Raipur Raipur India

ISBN: (纸本)9798331530402

Precise fault distance estimation is critical for effective transmission system protection, especially in modern power systems with integrated distributed generators (DGs). As the global demand for energy continues to rise, the adoption of renewable energy sources and their integration into the grid has significantly increased. However, the presence of various DGs complicates fault distance estimation due to the diverse power flows and interactions between DGs and existing grid infrastructure. the integration of large-scale DGs introduces additional challenges in fault detection and location, as the dynamic behavior of these generators affects the fault characteristics. this paper focuses on precise fault distance estimation within the ieee-9 bus system, which includes two distinct DGs. the proposed solution leverages an ensemble deep learning approach, combining convolutional neural networks (CNNs) and long short-term memory (LSTM) networks. this hybrid CNN-LSTM model takes advantage of CNN's ability to extract spatial features and LSTM's strength in capturing temporal dependencies, making it well-suited for fault distance prediction. the model's performance is evaluated using mean absolute error (MAE), giving 0.6387 average MAE for the studied system. Comparative analysis with existing deep learning models and validated through OPAL-RT 4510 real-time simulator shows that the proposed model delivers superior performance, demonstrating its effectiveness in handling the complexities introduced by DG integration. © 2025 ieee.

关键词： Electric power system protection

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A WSN (Wireless sensor Network) Approach for Controlling the Actuator Wirelessly through Database Interaction 7

A WSN (Wireless Sensor Network) Approach for Controlling the...

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7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Bin Karim, Md. Asif Rahman, Md. Mukidur Shahriar, Saquib Islam, Md. Manirul Department of Mechatronics Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350341485

this research study explores the wireless sensor networking, where sensor data is transmitted to a local database via a nearby server. the primary focus of this research study is real-time environment monitoring systems and wireless control and actuation systems. this research study incorporates the DHT 11 (Temperature and Humidity) and MQ-6 (LPG Gas) sensors. Selecting an appropriate controller is crucial to attaining desired system attributes like high-speed precision and meeting requirements for precise motion control at high speeds. that is why the ESP-8266-based NodeMCU is adopted for this ***, both feedback and feedforward closed-loop control mechanisms are implemented. As a result, the system can either control the actuator itself or by user demand. Leveraging sensor-derived data, the controller can automatically trigger the actuation system precisely within estimated time. Further, this study also depicts a clear differentiation between conventional methods and the proposed novel approach. Moreover, an IP (Internet Protocol) based monitoring system allows to monitor the sensor-derived data instantly, even without internet connectivity. Notably, the entire system operates on solar power, ensuring uninterrupted functionality even during power outages. © 2023 ieee.

关键词： Internet protocols

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