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Solar Beam Uniformity Measurement System 3

Solar Beam Uniformity Measurement System

引用

3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Phani Veera Prasad, Lanke Venkata Siva Reddy, R. Kulkarni, Chidambar Govindan, P. ISRO U R Rao Satellite Centre Bangalore India REVA University School of ECE Bangalore India

ISBN: (纸本)9798350338607

Solar beam uniformity measurement is performed for finding uniformity of 4m dia. The Solar beam is generated with the help of 10 nos. of Xenon arc lamps. This is carried out in preparation for the Thermal Balance Test (TBT) on Satellites and their Appendages. The objective of the measurement system is to find out the uniformity of the solar beam within its specified limits of the reference plane of the Chamber. X and Y-axis scanning on a Beam plane methodology are used for taking the data in different positions of the reference plane. This uniformity information is base for designing the Thermal sub-system as it directly impacts the functionality and accuracy of the Thermal design of the Spacecraft [3]. This paper presents the design and implementation of a solar beam uniformity measurement system at Large Space Simulation Chamber (LSSC), U R Rao Satellite Centre (URSC), Bangalore. © 2023 IEEE.

关键词： signal encoding

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Electrocardiogram signal processing and recognition techniques based on the ESPRIT algorithm 3

Electrocardiogram signal processing and recognition techniqu...

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3rd international conference on Biomedical and Intelligent Systems, IC-BIS 2024

作者： Zhao, Qianting Ping, Qingwei School of Medical Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781510681279

The characteristics of electrocardiogram (ECG) signal play a crucial role in assessing human health. Accurate identification of frequency components within ECG signal can greatly assist physicians in evaluating patients' health conditions and devising appropriate treatment strategies. The process of acquiring ECG signal involves the following several stages: signal acquisition, preprocessing, feature extraction and classification. However, existing feature extraction methods have limitations, which can compromise their effectiveness for clinical applications. The ESPRIT algorithm, based on eigen decomposition of correlation matrices, offers a solution for signal feature estimation. It enables the computation of signal frequency, phase, power, and other parameters, making it particularly useful in array signal processing for precise parameter estimation even with limited data. To address these limitations, this paper proposes a novel feature analysis method based on the ESPRIT algorithm. Our goal is to overcome the shortcomings of conventional feature extraction techniques, which are often computationally intensive, require extensive calculations, and may not accurately extract electrocardiogram signal features. The proposed method was evaluated using data from the MIT-BIH database, demonstrating the ESPRIT algorithm's ability to accurately estimate frequencies. These results provide critical insights and guidance that can enhance the accuracy of ECG signal acquisition. © 2024 SPIE.

关键词： Electrocardiograms

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Research on transmission control technology of microwave signal with high density 3

Research on transmission control technology of microwave sig...

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3rd international conference on High Performance Computing and Communication Engineering, HPCCE 2023

作者： Cong, Tianru The 723 Institute of China State Shipbuilding Corporation Jiangsu Yangzhou225101 China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

Microwave signals transmitted through optical fibers have the advantages of large communication capacity, low transmission loss, high bandwidth, easy maintenance, and high security. The coherent light detection technology of microwave signals solves the problems of low direct detection sensitivity and limited power, and is therefore widely used in wireless communication systems, radar systems, satellite communication systems, and other fields. This article first provides a theoretical analysis of three modulation methods (AM, PM, FM) and coherent detection methods of homodyne and heterodyne. By observing spectral changes, coherent demodulation theories corresponding to three modulation methods were derived, and the results showed that amplitude modulation is the most suitable method for microwave signal transmission. The study analyzed the nonlinear characteristics generated by MZ modulators on LiNbO3 substrate during the modulation process, and pointed out that the greater the deviation between the modulation signal and the standard operating point, the worse the linear effect. The research results indicate that using microwave signal fiber optic transmission technology to replace traditional single microwave transmission and processing technology can effectively reduce energy consumption in long-distance signal transmission, improve the efficiency, security, and confidentiality of signal transmission. © 2024 SPIE.

关键词： Niobium compounds

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data-driven visual analytics of Human Mobility data and green cover using Image processing for Smart Cities 3

Data-driven visual analytics of Human Mobility data and gree...

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3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Ramanathan, Sivasubramanian Syed, Kulsoom Chavan, Tejaswini B. Tech Computer Science & Business Systems SVKMs NMIMS Navi Mumbai Mumbai India School of Technology Management & Engineering SVKMs NMIMS Navi Mumbai Mumbai India

ISBN: (纸本)9798350338607

This research paper presents an approach to data-driven visual analytics of human mobility data using Kernel Density Estimation visualized through heatmaps, highlighting the need for exploration of forecasting methods and intuitive visualizations using the ARIMA model. A specific geographic area is chosen for the demonstration of the scope of the proposed system. The system is a web application developed using Streamlit, an open-source python framework. To effectively implement the smart city concept, it is crucial to integrate diverse IoT systems, data sources, data streams, and analytical tools into a unified and seamless platform that facilitates the collection, analysis and presentation of information related to urban systems and subsystems. We propose taking into consideration several attributes when analyzing human mobility patterns, such as vehicle/traffic density, modes of transport, transport data, demographics, latitude, and longitude. Additionally, the system utilizes image processing as an efficient method for calculating urban green cover using morphological operations that are computationally cheaper and easy to use as compared to traditional surveys that are time and resource intensive. This information is used to develop smart plans to sustain or increase green cover in select areas, leading to the creation of sustainable and green smart cities. © 2023 IEEE.

关键词： Smart city

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Deep Learning for Automated Image Captioning: A CNN and Transformer Model Analysis 3

Deep Learning for Automated Image Captioning: A CNN and Tran...

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3rd international conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Saarika, Kathula Varsha, Vasaraju Sri Harsha, P. Sheikh, Anjum Nabi Dept. Artificial Intelligence and Data Science Chaitanya Bharathi Institute of Technology India

ISBN: (纸本)9798331527549

Automatic image captioning is a multidisciplinary effort that combines machine learning, natural language processing, and computer vision in creating meaningful and context-rich captions for images. Within a short time, this research problem has garnered a lot of attention and new techniques are continuously being proposed. However, there are many dismaying factors as well. For instance, the current models still have a long way to go in attaining human accuracy. This paper seeks to conduct a systematic review of the recent trends and developments in the field of image captioning techniques and models with a focus on 2023 and 2024 by systematically analyzing the 13 publications located in Springer and IEEEXplore libraries. According to our research, Convolutional Neural Networks allow the identification of image content at an early stage, and Recurrent Neural Networks or Long Short-Term Memory networks usually appear at the text generation stage. The most common image datasets are MS COCO and Flickr8k. Almost all studies utilized the BLEU scores (1, 2, 3, and 4) mechanism. It is alleviated that CNN with LSTM models tends to perform better when compared to RNN-modeled networks. Attention mechanisms and Encoder-Decoder architecture are aggressively becoming the two major solutions to strengthening image captioning. This review will help and provide direction to those who are interested in practicing research that aims to promote the techniques and processes of automatic image captioning. © 2025 IEEE.

关键词： Convolutional neural networks

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An Iterative Recursive Algorithm for Big data System of Green Innovation Capability 3

An Iterative Recursive Algorithm for Big Data System of Gree...

引用

3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Wang, Shuo College of Finance and Economics Guangdong University of Science and Technology Dongguan China

ISBN: (纸本)9798350317022

In the process of corporate governance, there are problems of complex innovative data processing and inconsistent evaluation data, which is main affects the management in the company. To improve the corporate governance mechanism, this paper proposes an iterative recursive method as a bionic intelligent algorithm, iterative recursion method is a commonly used algorithmic thinking in the field of computer science, which has the potential to be widely used in optimization problems. This paper proposes the possibility of using iterative recursive methods for analysis and optimization. The results show that the iterative recursive method can accurately analyze the governance mechanism and improve the corporate governance ability, and its accuracy is very more the 95%, and better than the evaluation iterative recursion method of genetic algorithm can help enterprises achieve the goals of power decentralization, information transparency and governance efficiency improvement, and provide new ideas and methods for the improvement of corporate governance mechanism. © 2023 IEEE.

关键词： Corporate Governance Mechanism Decentralization Governance Efficiency Information Transparency Iterative Recursion Method Optimization

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Personnel Positioning System in signal Interference Environment of Substation 3

Personnel Positioning System in Signal Interference Environm...

引用

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

作者： Zhang, Xiaolong Zhou, Tao Wang, Jing Wang, Tao State Grid Yangquan Power Supply Company Yangquan China

ISBN: (纸本)9798350382426

A solution is proposed to solve the problem of satellite signal failure and drift for personnel positioning in substations under semi-shaded environment. The scheme uses IMU (Inertial Measurement Unit) as the positioning compensation module of RTK, and adopts RTK/PDR (real-time dynamic/step Angle rate) joint positioning method to improve the positioning accuracy. In this way, we can effectively deal with the complex signal interference environment in the substation and ensure the accurate positioning of personnel. During the PDR positioning process, the heading angle has the property of scattering. Then, we used the gyroscope, accelerometer and magnetometer sensor output the output of the data fusion, building a complementary filter to enhance the precision of the step length of substation operation. We expect to use extended Kalman filters for RTK/PDR data fusion to achieve high-precision positioning of the whole scene of the substation. To verify the effectiveness of the algorithm, we carried out physical experiments based on the constructed precision positioning device. The results show that the proposed method can effectively achieve accurate positioning in the semi-sheltered space of the substation, achieving a positioning accuracy of 0.02 m. © 2023 IEEE.

关键词： data fusion Extended Kalman filter Step size estimation Substation position

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Deploying Diffusion Based Generation Model for Improved Training of GAN 3

Deploying Diffusion Based Generation Model for Improved Trai...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Harshitha, Duddukuri Yoga Gitam Deemed University Data Science Hyderabad India

ISBN: (纸本)9798350319125

This paper discovers the usage and studies the effect of diffusion based generation model to transform the raw training data of GAN into standard normal latent space. This improved the training stability and reduced resource utilization and played a crucial role in decreasing the training error. Papers till date have explored the use of generating models for generating the data it is trained on. The research done on natural language processing shows the significance of word embedding and transforming unstructured data into trainable domain [1], which involve in lot of resources for training, and there are very few papers on generalizing the process, as compared to the papers that exists on its applications. In this paper we are using diffusion based generation model as intermediate processing block on USDA food database. This offers insights into extending the application of GAN networks into fields that did not gain much attention till date. The main application is to prepare a meal plan by generating various combinations of dishes in the database so as to meet the nutritional needs. GAN that is trained directly on the food database was unstable and generated a huge error. The standard normalizing and de normalizing techniques were barely up to the help in decreasing the error. Instead of training the GAN to directly generate the data, we have stacked already trained diffusion based generation model at the end of GAN, that was trained to map the food data into latent space, and trained GAN network for time series generation of different food combinations that would meet the nutritional requirements. © 2023 IEEE.

关键词： data processing diffusion based generation embedding vectors GAN applications improving the training of GAN normalization

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Predictive Human Resource Analytics for Classification of Salaries in the Field of data Science 3

Predictive Human Resource Analytics for Classification of Sa...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Gill, Kanwarpartap Singh Anand, Vatsala Chauhan, Rahul Devliyal, Swati Gupta, Rupesh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350319125

The rapid growth of big data has led to a lack of jobs in the field of data science, resulting in a strong need for skilled experts to fill particular tasks in this domain. In order to get the aforementioned conclusions, an examination of the prevailing employment patterns in the field of data science was conducted, using a secondary dataset. The primary dashboard offered valuable analytics information for enhancing job security and fostering career advancement. Additionally, the study highlighted the key factors that are in high demand in the field of data science, which are crucial for constructing successful models. Various data pre-processing techniques were extensively used to effectively prepare and optimise the dataset for the stated goals of human resource analytics. The primary aim of this research is to do a thorough examination of human resource elements within the domain of data science employment. The present investigation will concentrate on the notable influence of specialised skill sets and their association with salary prediction. The results of this study demonstrate a considerable degree of precision, as seen by an 88 percent success rate achieved by the Random Forest Classifier. © 2023 IEEE.

关键词： Artificial Intelligence Classification Deep Learning Image processing Model Training Random Forest Remote Sensing Salary Prediction

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Some lessons learned reproducing human evaluation of a data-to-text system 3

Some lessons learned reproducing human evaluation of a data-...

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3rd Workshop on Human Evaluation of NLP Systems, HumEval 2023

作者： González-Corbelle, Javier Alonso-Moral, Jose M. Bugarín-Diz, A. Universidade de Santiago de Compostela Spain

ISBN: (纸本)9789544520885

This paper presents a human evaluation reproduction study regarding the data-to-text generation task. The evaluation focuses in counting the supported and contradicting facts generated by a neural data-to-text model with a macro planning stage. The model is tested generating sport summaries for the ROTOWIRE dataset. We first describe the approach to reproduction that is agreed in the context of the ReproHum project. Then, we detail the entire configuration of the original human evaluation and the adaptations that had to be made to reproduce such an evaluation. Finally, we compare the reproduction results with those reported in the paper that was taken as reference. © HumEval 2023 - Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems, associated with the 14th international conference on Recent Advances in Natural Language processing 2023, RANLP 2023.

关键词： Cell proliferation

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