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Explainable AI-Driven machine learning Approach for Prediction of Acoustic-Based Fire Extinction 4

Explainable AI-Driven Machine Learning Approach for Predicti...

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4th international conference on Data Analytics for Business and Industry, ICDABI 2023

作者： Sarker, Baneswar Gupta, Suraj Singh, Gajendra Kumar, Piyush Maiti, J. Indian Institute of Technology Kharagpur Department of Industrial and Systems Engineering Kharagpur India Indian Institute of Technology Kharagpur Ranbir & Chitra Gupta School of Infrastructure Design & Mgmt. Kharagpur India Indian Institute of Technology Kharagpur Centre of Excellence in Safety Engineering and Analytics India Indian Institute of Technology Kharagpur Centre of Excellence in Safety Engineering and Analytics Department of Industrial and Systems Engineering Kharagpur India

ISBN: (纸本)9798350369786

Acoustic fire-extinguishing system is an alternative system for the safe handling and control of fire accidents by extinguishing different classes of fires. It is necessary to accurately identify and predict the extinction and non-extinction states of the flames based on certain characteristic features. It is also important to identify the most important features governing the classification of the states of the flame. Both of these can be achieved by the combination of deep learning techniques and explainable artificial intelligence (XAI). In this study, models like artificial neural networks (ANN) and convolution neural networks (CNN) were deployed on an experimental dataset to classify the extinction states of the flame based on features, namely, flame sizes, fuel type, airflow, decibel, frequencies, and distance range. On the implementation of ANN, 95% and 92% accuracy were obtained, while 97% and 98% accuracy were obtained on a CNN model, for the liquid and LPG fuels respectively. the application of XAI in this study indicates that distance range has the maximum impact among all features of the model. © 2023 IEEE.

关键词： Convolutional neural networks

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application research of hyperspectral remote sensing in the identification of stratigraphic boundaries alongside growing tunnels 4

Application research of hyperspectral remote sensing in the ...

引用

4th international conference on Telecommunications, Optics, and computer Science, TOCS 2023

作者： Bi, Xiaojia Jiang, Liangwen Dong, Qing He, Lei Wang, Dong China Railway ErYuan Engineering Group Co. Ltd Sichuan Chengdu China Beijing China School of Software Engineering Chengdu University of Information Technology Sichuan Chengdu China

ISBN: (数字)9781510679849

ISBN: (纸本)9781510679832

the geological survey along the large railway in China is difficult, the boundaries of many regional geological maps are unclear, and the geological mapping is very different. the use of hyperspectral remote sensing can greatly improve the survey accuracy in complex mountainous areas. In the identification of lithology and structure, hyperspectral remote sensing has certain advantages compared with multi-spectral satellite images. In this paper, the hyperspectral data of Gaofen-5 satellite is interpreted by a series of technical methods, such as data preprocessing, radiometric calibration, atmospheric correction, orthographic correction, image information enhancement, radiation homogenization processing, etc. According to different geological conditions, lithologic structure information by hyperspectral information enhancement technology in different regions and layers. Different geological units are effectively divided, the distribution characteristics of geological structure space are identified, and some stratigraphic boundaries of the original geological map are adjusted. this paper solves the problems that the survey personnel of long and large tunnels cannot reach, and the conventional survey methods cannot verify the stratigraphic boundaries and lithological characteristics. It also provides an important auxiliary reference value for the identification of surrounding rock of hyperspectral remote sensing. © 2024 SPIE.

关键词： Image enhancement

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Research and application of the Primary Harmonic Eliminator for the thermal Resistor 4

Research and Application of the Primary Harmonic Eliminator ...

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4th international conference on Advances in Electrical Engineering and computer applications, AEECA 2023

作者： Wei, Ying Niu, Bo Wang, Xiaokang Power Research Institute of State Grid Ningxia Power Co. Yinchuan China Wuzhong Power Company of State Grid Ningxia Power Co. Wuzhong China

ISBN: (纸本)9798350308082

In the neutral non-effective grounding system, the ferromagnetic resonance overvoltage of the electromagnetic voltage transformer appears the most frequently. the study shows that the SiC harmonic eliminator is connected between the primary neutral point of the electromagnetic voltage transformer and the ground, and the ferromagnetic resonance suppression through the voltage state applied to the two ends of the device during the resonance process is easy to fuse and burst during the resonance process. this paper presents a PTC harmonic eliminator, based on the correlation between temperature and electrical properties of thermistors, and the test shows that the PTC harmonic eliminator can suppress the excitation surge current below 0.2A in a short harmonic suppression time, and the surge suppression ability is better than the SiC harmonic eliminator, which can solve the problem of electromagnetic voltage transformer burst caused by the intermittent grounding of the system. the application of PTC harmonic eliminator in distribution network systems will effectively improve the operational stability of ungrounded neutral systems. © 2023 IEEE.

关键词： Ferromagnetic materials

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Diabetic Condition Classification using Supervised and Unsupervised machine learning Techniques: A Use Case for HealthTech Industry 4

Diabetic Condition Classification using Supervised and Unsup...

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4th IEEE international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Bongale, Anupkumar M. Biradar, Santoshkumar Pise, Priya Suke, Amita Priyadarshan Uke, Nilesh Dharrao, Deepak S. Symbiosis Institute Of Technology Department Of Aiml Pune Campus Pune India G H Raisoni College Of Engineering And Management Department Of Cyber Security And Data Science Pune Wagholi India Indira College Of Engineering And Management Department Of Ai And Ds Pune India Trinity Academy Of Engineering Pune India Symbiosis Institute Of Technology Department Of Cse Pune Campus Pune India

ISBN: (纸本)9798350384628

Diabetes is a very underestimated and, in many cases, an ignored disease. People do not understand the seriousness of diabetes. Many people think diabetes is just something because of which one cannot consume sweets. this, however, is not true. Diabetes is a very serious problem where symptoms can range from being very thirsty all the time to even death. there are many cases where diabetic people had to get their leg, or some other limb amputated because of it. thus, people have to be made cognizant of diabetes' seriousness. this article dives deep into this disease and lists the different types of diabetes, and the way people can know if they are diabetic. Also, there is an in-depth literature review of research papers ranging from 2002-2020. Furthermore, a deep dive in the project of diabetes prediction is present. the techniques used to classify into 'diabetic' or 'non-diabetic' are Random Forest, Logistic Regression and K Nearest Neighbor algorithms which all belong to the supervised machine learning algorithms. Logistic Regression uses sigmoid function to classify into different classes, Random Forest approach uses multiple Decision Trees and the majority decision of them all for the final output. Moreover, K Nearest Neighbor technique uses the concept of Euclidean Distance to decide which class is suitable for any new coming datapoint. © 2023 IEEE.

关键词： Decision trees

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ColCompNeT: Deep learning-Based Colorization-Based Coding Network 1

引用

4th international conference on machine Intelligence and Signal Processing, MISP 2022

作者： Mishra, Dipti Singh, Satish Kumar Mahindra University Hyderabad500043 India Indian Institute of Information Technology Allahabad Allahabad211012 India

ISBN: (数字)9789819900855

ISBN: (纸本)9789819900848

Converting a grayscale image to a visually plausible and perceptually meaningful color image is an exciting research topic in computer vision and graphics. However, predicting the chrominance channels from a grayscale image is an ill-posed problem, especially when the objective is to produce the same color as in the ground truth image, like for the application of compression using colorization or video/image restoration. Compression using colorization efficiently reduces the storage space and transmission bandwidth by two-thirds and maintains the image’s visual quality. However, colorizing decompressed gray images exactly as ground truth with maximum accuracy is a challenging task. In this paper, learning-based CNN network ColCompNeT has been proposed in which concept of parallel training of colorization and compression network is utilized. With the proposed algorithm, a maximum bit saving of 36.45% is achieved with the improved objective and subjective performance when compared with the state-of-the-art methods. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network coding

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Innovative application of Virtual Reality Technology in Digital Display of Intangible Cultural Heritage 4

Innovative Application of Virtual Reality Technology in Digi...

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4th international conference on computer Vision and Data Mining, ICCVDM 2023

作者： Yu, Ying Ren, Huixian College of Design and Art Shenyang Architecture University Hunnan Shenyang China

ISBN: (纸本)9781510674448

this thesis investigates the innovative application of virtual reality technology in the digital display of intangible cultural heritage. Intangible cultural heritage is an important part of human culture, and with the continuous development of digital technology, the protection and display of traditional intangible cultural heritage is facing new challenges. Virtual reality technology as an emerging technical means, its digital display is of great significance for the protection and inheritance of intangible cultural heritage, and its immersive and interactive features can bring a new experience for the display of intangible cultural heritage. this paper firstly introduces the basic principles and characteristics of virtual reality technology, and then explores the application methods and effects of virtual reality technology in the digital display of intangible cultural heritage. It is found that virtual reality technology can enhance the audience's cognition and understanding of intangible cultural heritage by simulating realistic scenes and providing interactive experiences. Finally, this paper proposes future directions and challenges for the development of virtual reality technology in the digital display of ICH, as well as suggestions for further research. this study is of great significance in promoting the protection and inheritance of intangible cultural heritage and the application of virtual reality technology in the cultural field. © 2024 SPIE.

关键词： Virtual reality

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Momentum on Sports Performance: machine learning and Multi-Aspect Analysis 4

Momentum on Sports Performance: Machine Learning and Multi-A...

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4th international conference on Big Data, Artificial Intelligence and Risk Management, ICBAR 2024

作者： Li, Junxiao Tan, Xin Yi, Lanfang Ma, Qianting College of Finance Nanjing Agricultural University Jiangsu Nanjing China College of Artificial Intelligence Nanjing Agricultural University Jiangsu Nanjing China

ISBN: (纸本)9798400709753

this study examines the multidimensional influence of momentum on competitive sports performance through a holistic analytical lens. Commencing with the application of the Information Entropy Weight Technique for Order Preference by Similarity to Ideal Solution (IEW-TOPSIS), it meticulously measures momentum by integrating psychological components, scoring trends, and skill indicators. this refined measurement approach enables an exhaustive exploration of athletes' variable performance throughout competitive *** on this groundwork, a Multilayer Perceptron (MLP) model is employed to forecast player performance with notable precision, reinforcing its efficacy as a predictive instrument. the research extends to strategy formulation, leveraging opponents' historical data, athletes' self-reflections, and pivotal momentum transitions to inform tactical strategies, thereby augmenting decision-making *** generalizability is demonstrated through successful application to additional tennis matches, albeit suggesting calibration with specific match category data for enhanced accuracy. Sensitivity analyses confirm the robustness of the IEW-TOPSIS and MLP models across varied parameters and data distributions, positioning them as valuable tools for coaching and athlete enhancement in diverse competitive scenarios. © 2024 Copyright held by the owner/author(s).

关键词： correlation coefficient IEW-TOPSIS Momentum Multilayer Perceptro

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Research on the Design of Education Games for Vocabulary learning from the Perspective of Intrinsic Motivation theory 4

Research on the Design of Education Games for Vocabulary Lea...

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4th international conference on computer Science and Technologies in Education, CSTE 2022

作者： Xiang, Yu Northwest Normal University Institute of Educational Technology Lanzhou China

ISBN: (数字)9781665481885

ISBN: (纸本)9781665481885

With the development of information technology and multi-disciplinary, educational games are considered to have good educational potential and educational value. On the basis of sorting out the connotation of educational games and analyzing the common problems of existing educational games, combined with the theory of intrinsic motivation, this paper proposes a design of Education Games for Vocabulary learning, provides a practical case for the specific application of intrinsic motivation theory, and summarizes the use of intrinsic motivation in games. Motivation theory develops practical strategies for educational game design. © 2022 IEEE.

关键词： E-learning

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A Review on Social Awareness Navigation for Service Robots 16th

A Review on Social Awareness Navigation for Service Robots

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16th international conference on Social Robotics, ICSR + BioMed 2024

作者： Shi, Haoyu Yu, Weiwei Madani, Kurosh School of Mechanical Engineering Northwestern Polytechnical University Xi’an China UPEC University Vitry-sur-Seine France

ISBN: (纸本)9789819789627

this review summarizes the research progress in socially aware navigation for social service robots, focusing on the establishment of human-robot interaction models, the application of subjective emotion state recognition in socially aware navigation, and the implementation of socially aware navigation under various learning frameworks. First, it explains the construction of navigation based on the Social Force Model and trajectory prediction models along with their respective applicable environments. Next, the paper introduces how different emotion recognition technologies accurately perceive human emotions to assist in the realization of socially aware navigation. Finally, it comprehensively analyzes the advantages and challenges of using supervised learning, reinforcement learning, and preference learning in achieving socially aware navigation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Deep learning model for rice disease detection 4

Deep learning model for rice disease detection

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4th international conference on Testing Technology and Automation Engineering, TTAE 2024

作者： Cao, Bo Li, Yuheng Yang, Zhenyu Zhong, Ming Wang, Meng Hainan University Haikou570228 China Key Laboratory of Internet Information Retrieval of Hainan Province Haikou570228 China Sanya Nanfan Research Institute Hainan University Sanya572025 China Hainan Guangling Hi-Tech Industrial Co. Ltd. Lingshui572400 China

ISBN: (数字)9781510686656

ISBN: (纸本)9781510686649

Common diseases of rice include blight, brown, dead heart, downy mildew, etc. these diseases can cause damage to rice leaves. If not recognized in time, it will lead to a decrease in rice yield and even the death of part or the entire crop in the land. Using deep learning technology to monitor rice crop diseases can provide early warning of rice crops, and then promptly specify prevention strategies when diseases occur, helping farmers and agricultural management departments to make scientific decisions to improve the efficiency and sustainability of rice production. Based on the core concept of ecological and environmental protection, we proposed an innovation to the You Only Look Once (YOLOv8) technical framework, focusing on optimizing the accurate identification technology of rice diseases and pests. this improvement aims to promote the sustainable development of agricultural production in a more environmentally friendly and efficient way. this article uses the improved You Only Look Once (YOLOv8) model to accurately detect the disease types in the collected data set. this article uses multi-scale convolution kernels and Attention to improve the C2f module of the yolov8 model. the improved model is in the data set An accuracy rate of 96.4% was achieved. this research helps to gain a deeper understanding of the applicability of computer vision in crop disease detection and further explore its application potential in agricultural production. © 2024 SPIE.

关键词： Diseases and disorders Object detection Data modeling Convolution Performance modeling Agriculture Deep learning Education and training

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