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Defect detection of raised fabrics based on improved EfficientNet 3

Defect detection of raised fabrics based on improved Efficie...

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2024 3rd international conference on Image processing, Object Detection, and Tracking, IPODT 2024

作者： Xu, Chang Jin, Shoufeng Zan, Jie College of Mechanical and Electrical Engineering Xi’an Polytechnic University Xi’an710060 China

ISBN: (数字)9781510685529

ISBN: (纸本)9781510685512

Aiming at the problem that the surface of pile fabrics is soft and delicate, which is difficult to detect defects, this paper proposes a defect detection model for pile fabrics based on the improved EfficientNet. A deep neural network leveraging EfficientNet as its core feature extraction network is devised, incorporating the enhanced I-SPP spatial pyramid pooling module to enhance adaptability and accommodate input data across various scales. The SE module and Swish activation function in the MBConv module are replaced with CA attention module and Mish activation function to improve the model robustness and detection efficiency. Experiments show that the method proposed in this article improves the EfficientNet model achieves a mean average accuracy of 88.5% on the test set. Compared with other neural network architectures, this method improves the accuracy and efficiency of detection, which can meet the needs of related production enterprises. © 2024 SPIE.

关键词： Defect detection data modeling 3D modeling Neural networks Visual process modeling Ablation Performance modeling Visualization Lithium Network architectures

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Brain Pathology Detection Using Convolutional Neural Network from EEG signal 3rd

Brain Pathology Detection Using Convolutional Neural Network...

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3rd international conference on Information Technology, InCITe 2023

作者： Kavitha, M. Cyndhiya, J. Janet Srinivasan, R. Kavitha, R. Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Instituteof Science and Technology Chennai India

ISBN: (纸本)9789819959969

The development of next generation wireless communication technology and Artificial Intelligence (AI) techniques to handle massive data has led to the usage of smart systems to improve the quality of human life. One such significant breakthrough is the use of smart healthcare systems. In this project, a Deep Learning (DL) based pathology detection system is suggested. Convolutional Neural Network (CNN) is used to classify and determine whether the signal belongs to a pathological individual or a normal one from the EEG (Electroencephalogram) signal. For this project, publicly available EEG signal data were used. The data signal is preprocessed to remove noise data using a Finite Impulse Response (FIR) filter. The dataset is divided in the ratio of 7:3 into train and test data. Using test data for validation, the model is found to predict at 98.0% accuracy, 96.67% specificity, and 100.0% sensitivity. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： FIR filters

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Precision-Aware data Management in Federated Cloud Environments: A Context-Aware Approach 3

Precision-Aware Data Management in Federated Cloud Environme...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Kolekar, Vikas K Sakhare, Sachin R SMT. Kashibai Navale College of Engineering Department of Computer Engineering Pune India Savitribai Phule Pune University Pune India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350343632

In the ever-evolving world of cloud computing, the management of data in federated cloud environments presents a complex challenge. Presented study investigates precision-aware data management techniques with the goal of improving the efficiency of federated cloud systems. Our work acknowledges the crucial significance of context-awareness in enhancing data operations and introduces an adaptive data management middleware. The precision-aware system caters to the requirement for accuracy and reliability in data processing by integrating sophisticated algorithms and techniques. Simultaneously, the integration of context-awareness ensures that data management strategies dynamically adapt to the changing contextual conditions within federated cloud environments. This strategy has two aspects, first to increase the accuracy of data operations and second to improve the overall responsiveness and adaptability of the system. Our study focuses on creating innovative middleware that can effortlessly integrate precision-aware and context-aware features. We assess the effectiveness of the proposed system by conducting empirical evaluations and analyzing real-world use cases. Our findings demonstrate that the system is capable of optimizing data management in diverse and dynamic federated cloud contexts. The results of this study enhance the progress of adaptive data management approaches by providing a detailed comprehension of the interaction between precision and context in federated cloud environments. Proposed work is important for research scholars, practitioners, and industry experts who are looking for creative ways to improve the performance and adaptability of data management systems in complex cloud environments. © 2023 IEEE.

关键词： Adaptive middleware Context-awareness data management Federated cloud environments Precision-awareness

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Solar Powered Smart Irrigation System Based on Internet of Things (IoT) Using Microcontroller 3

Solar Powered Smart Irrigation System Based on Internet of T...

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3rd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Niloy, Sifatuzzaman Sumona, Fahima Haque Khan, Mehedi Hasan Islam, Mohammad Zohurul Ahmad, Shameem Howlader, Sujan American International University Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

In this era of new technology, human life is getting simpler day by day due to the advancement in internet of things (IoT) technology. Similarly, the population is growing rapidly which results in the necessity of huge agricultural goods. Tomeet that need there is a need for making the irrigation process smart using IoT. This paper aims to design and implement an IoT based smart irrigation system, which can reduce manual labor and maximize the productivity of crops. This system is automatically controlled through microcontroller to monitor the moisture level of crops, humidity & temperature and send messages to the farmers about the agricultural field conditions through GSM system for their further perusal. The system is very simple, and it needs less power. Further, a sun tracking system is installed in the irrigative system which helpsthe solar panel to track the sun for powering up the irrigation system. The simulation of the overall system is conducted in Proteus platform and a prototype is developed to validate the performance of the system. From the results it has been observed that the system is able to monitor the agricultural fieldconditions accurately along with informing the farmers about the conditions for further actions. © 2023 IEEE.

关键词： Microcontrollers

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Prospect of Hybrid Power Generation in Nijhum Dwip Utilizing Renewable Resources 3

Prospect of Hybrid Power Generation in Nijhum Dwip Utilizing...

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3rd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Miah, Md. Salim Choudhury, Irfan Ahmed Reza, Md. Sharon Al Joha, Md. Abdullah Islam, Sayeed Islam, Md. Fokhrul Electrical and Electronic Engineering Islamic University of Technology Gazipur Bangladesh Institute of Energy University of Dhaka Dhaka Bangladesh Electrical and Electronic Engineering Manarat International University Dhaka Bangladesh

ISBN: (纸本)9798350346435

Recently, Bangladesh has seen development towards connecting the electric supply grid to extremely remote places. But the sudden energy crisis and the increased price of fossil fuels have forced the authorities to shed some & even total load in those areas where the economic return is not feasible. Consequently, people of such places are back to getting electricity through diesel generators, which are not economically viable and environmentally unfriendly. Nijhum Dwip is one such places. This study proposes a renewable resources hybrid model alternative focusing on a community of 50 households using HOMER software. The model consists of a battery, converter, diesel generator, and solar PV system along with a wind turbine & it aims to satisfy the demand of 48.33 KWh/d primary load and 7.37 KW peak load. The best configuration by HOMER in terms of lowest COE (Cost of Energy) and NPC (Net Present Cost) are found to be US$ 0.39 and US$ 115339, respectively & CO2emission is reduced by 15 tons. © 2023 IEEE.

关键词： Solar energy

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Design of underground multi-mode remote transmission sub system 3

Design of underground multi-mode remote transmission sub sys...

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3rd international conference on Digital signal and Computer Communications, DSCC 2023

作者： Jin, Wenhao Yan, Zhengguo Zhang, Ying Li, Jinjiang Key Laboratory of Shaanxi Province for Measurement and Control Technology of Oil and Gas Wells Xi'an Shiyou University Shaanxi Xi'an710065 China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

Downhole TV plays an important role in oil exploitation, among which it is a key part of downhole TV. At present, most of the downhole TV industry uses armored cable for data transmission, but with the development of technology, it has begun to be equipped with optical fiber in the field working environment, and continuous tubing also began to be equipped with optical fibers. Based on this situation, this paper introduces a system design of photoelectric multi-mode remote *** paper first introduces the principle of data coding and demodulation. After analyzing the characteristics of data transmission, TC-PAM coding modulation mode is adopted, and during the cable transmission, the cable has adaptive technology to improve the decoding accuracy of the decoding terminal during high-speed data transmission in the deep well test channel ***, the working principle and system composition of teletransmission section are introduced, and the design and system design requirements of photoelectric composite cable, the selection of core modules and the design method of temperature and pressure resistance of the system are also given. Finally, the field environment test verifies the stable operation of the system and the feasibility of the design method. © 2023 SPIE.

关键词： data transfer

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A Denoising Scheme for Core Earth Current of Power Transformers 3

A Denoising Scheme for Core Earth Current of Power Transform...

引用

3rd international conference on Electrical Engineering and Control Science, IC2ECS 2023

作者： Wu, Zhe Li, Zhaohui Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China

ISBN: (纸本)9798350382426

The core earth current (CEC) is composed of a variety of components, some of which can reflect the health status of power transformers, such as the power frequency and its harmonic components can reflect power transformer core grounding state and core saturation degree, and some pulse components can reflect partial discharge in power transformers. Some high-frequency components can reflect the external shock (very fast transient overvoltage, lighting, etc.) suffered by power transformers. There are also some noise components introduced by ambient environment and measurement system. The existing CEC monitoring devices focus on part of the components, such as the power frequency and its harmonic components or partial discharge pulse component. Both devices are difficult to catch all anomalies in CEC. A current transformer (10Hz-200kHz) is used to sense CEC continuously to catch all abnormal waveforms in CEC. In order to extract the pulse components in CEC, a denoising scheme based on mathematical morphological (MM) filter and wavelet shrinkage is devoted. MM filter can suppress the low frequency component while maintaining the integrity of pulse components. For the purpose of filtering out the white noise in the signal and preserve the complete pulse waveform as much as possible, a new wavelet selection method that the optimum wavelet at each level is selected as the one maximizing the energy ratio of detailed coefficients beside and inside the range formed by the threshold is devoted. Simulated data and field data are used to compare several different wavelet selection methods, and the experimental results show that the pulse distortion extracted by this method is smaller than other methods. © 2023 IEEE.

关键词： core earth current (CEC) mathematical morphology power transformers signal denoising wavelet shrinkage

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Impact of multi-GPUs and hyperparameters on parallel algorithms based on pytorch distributed 3

Impact of multi-GPUs and hyperparameters on parallel algorit...

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3rd international conference on signal processing and Machine Learning, CONF-SPML 2023

作者： Wei, Shiyu SWUFE-UD Institute of Data Science Southwestern University of Finance and Economics Chengdu610000 China

Neural networks, as powerful models for solving many genuine problems, are suffering from the issue of being too computationally intensive due to the excessive size of the models themselves and the large datasets used for training. This paper's work focuses on a parallel algorithm, experimented on the classical convolutional neural network LeNet-5, aiming to reduce the time it takes for the neural network to train. This applies a massively parallel GPU structure to take full advantage of its high computing power. Among the approaches to improve the performance of parallel algorithms, many efforts have been made to improve the design of parallel structures, while this work focuses more on the enhancement of parallel algorithms by reasonable settings of neural network hyperparameters. This paper tries to approach (1) reducing the running time by testing parallelism with different numbers of GPUs and (2) further investigating the relationship between parallelism and model accuracy degradation and experimentally deriving a parallel scheme that can reduce the training time while guaranteeing accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Graphics processing unit

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Deployment of Safety Predictive Analytics to Prevent Workplace Incidents and Promote Event Reduction: A Machine Learning Approach Towards a data-Driven Safety System 3

Deployment of Safety Predictive Analytics to Prevent Workpla...

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3rd international conference on Digital data processing, DDP 2023

作者： Hajar, Ait Lamkademe Ahmed, Naddami Karim, Choukri National Higher School of Electricity and Mechanics Hassan Ii University Laboratory of Advanced Research in Industrial and Logistics Engineering Casablanca Morocco Enset Mohammedia Hassan Ii University Eeis Laboratory Casablanca Morocco

ISBN: (纸本)9798350329018

With the ongoing era of digitization and the ability to bring together huge data sets, there is enormous potential for many industries and business functions to take advantage of their 'big data' sets by performing advanced analytics, allowing managers to make business decisions. When applied correctly, predictive analytics allow organizations to gain deep insight into their business and deploy their scarce resources in an optimal way (Predictive Solutions, 2012). Thus, improving safety in workplaces is no exception to using predictive analysis to predict and prevent events in real-time. Increasing process safety entails lowering the likelihood that hazardous environments may have negative effects. Unfortunately, it is impossible to measure the probability factor directly. The absence of an accident does not provide helpful information because Target Zero cannot be accomplished until the hazard is eliminated. On the other hand, numerous cause elements that could have been better monitored and controlled are discovered after a significant accident occurs. In this paper, we advocate for a proactive, dynamic system by embedding predictive analysis into two process stages. At the design stage, we suggest a predictive modeling process: 1. Define goals 2. Collect and preprocess data 3. Address missing data through data imputation 4. Build candidate predictive models 5. Train, test and cross-validate candidate models 6. Select 'the best' models based on multiple evaluation metrics 7. At runtime, consume the predictions from selected predictive models using the end-user interface. Depending on the data input and the time it takes for learning algorithms to learn, we claim the system can predict future potential input variables for the system in a single model and proactively adjust to meet intermediate and longterm goals and safety needs. A subset of data supports the proposal through in-sample validation. The validation through simulation was done based on actual data extr

关键词： data mining

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High Performance VLSI Architecture of FIR Filter for Seismic signal processing 3

High Performance VLSI Architecture of FIR Filter for Seismic...

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3rd international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Karunakaran, S. Electronics and Communication Engineering Vardhaman College of Engineering Hyderabad India

ISBN: (纸本)9781665494007

As a primary requirement, FIR filters(Finite Impulse response)used in real-time seismic alert systems are required to be low complexity, fast, and re-configurable. The CSE technique is commonly used to abate hardware complexity in digital FIR filters by decreasing logic operators and logic depths. In this paper, we present a new LO and LD minimization matrix grouped CSE algorithm that outperforms existing CSE algorithms. Additionally, the suggested design With low complexity and reduced truncation error, we developed a new biased-based rounding method that includes half units, as well as to lessen critical-path delay, use the cut-set retiming technique. This paper presents two hardware-efficient FIR filter topologies (I and II) that employ cut-set retiming, HUB rounding, and the canonical signed digit based MCSE algorithm. Additionally, architecture II implements a reconfigurable FIR filter in a hardware- efficient manner. FPGA and ASIC platforms are used to implement the architectures on the hardware side. Comparing the hardware implementation of proposed architectures, we mooted decrease of LOs, CPD, effective latency, area-delay product (ADP), and power- delay product using cutting-edge CSE- based architectures by a factor of 2 more than 35%, 47 %, 36 %, 34 %, and 29 %,*** comparison to the *** reconfigurable architecture II has an approximately 46 %, 10 %, and 11 % less in PDP, ADP and CPD. © 2023 IEEE.

关键词： FIR filters

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