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An integrated BCI-VR system design with game for motor imagery 5

An integrated BCI-VR system design with game for motor image...

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5th international conference on Artificial Intelligence and Computer Science, AICS 2023

作者： Chen, Shuyu Huang, Mengjie Zheng, Yuting Lu, Annan Yang, Rui School of Advanced Technology Xi’an Jiaotong-Liverpool University Jiangsu Suzhou215123 China School of Electrical Engineering Electronics and Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom Design School Xi’an Jiaotong-Liverpool University Jiangsu Suzhou215123 China

ISBN: (纸本)9781510668621

Brain-computer interface (BCI) provides a direct link for the interaction between the human brain and external devices. In the meanwhile, virtual reality (VR) offers people an immersive virtual experience with simulated environments. By combining these two technologies, integrated solutions have been raised, but most of the current solutions are only applicable in the laboratory setting. therefore, in this study, we proposed an integrated BCI-VR system for daily use based on dry electrodes. A game for motor imagery was also designed in the system through the classification of motor imagery signals. the proposed system shows potential as a practical platform in rehabilitation and other healthcare fields. © 2023 SPIE.

关键词： Brain computer interface

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Generation of Synthetic 5G Network dataset Using Generative Adversarial Network (GAN) 16

Generation of Synthetic 5G Network Dataset Using Generative ...

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16th IEEE Malaysia international conference on Communication, MICC 2023

作者： Khatiman, Muhammad Nur Aqmal Abu-Samah, Asma Azman, Muhammad Amin Nordin, Rosdiadee Abdullah, Nor Fadzilah Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Bangi Malaysia Universiti Kebangsaan Malaysia Wireless Research@UKM Faculty of Engineering and Built Environment Bangi Malaysia Universiti Putra Malaysia Faculty of Engineering Serdang Malaysia

ISBN: (纸本)9798350304343

While the Fifth Generation (5G) network is actively being deployed in most countries to create new possibilities for better lifestyle and economic development, it is a technology that is currently being a focal point for researchers across the world along with 6G. Starting from 3GPP Release-18, Artificial Intelligent (AI) and Machine Learning (ML) are identified as enabler towards intelligent network in 5G and beyond. Nevertheless, the models based on AI/ML need a sufficient amount of data for learning patterns and relationships, enabling them to provide precise predictions for unfamiliar data and situations. the existence of Generative Adversarial Network (GAN) helps solve the issue by generating fake data from an existing dataset to resemble real-world data to be used in training and testing of different algorithms. In this paper, the process of generating synthetic data of 5G network was demonstrated from an extensive test drive results that will encourage innovation in mobile communication. Generation of data use two types of GAN which are the Conditional Tabular GAN (CTGAN) and Topological Variational Autoencoder (TVAE). the two algorithms were compared based on statistical analysis such as the distribution and Pearson Correlation analysis. TVAE showed a better overall performance score (94.14%) over CTGAN (89.66%) when compared with the original data, but the CTGAN produced more similar distribution for certain individual columns. © 2023 IEEE.

关键词： 5G mobile communication systems

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Superior ML Model for Autism Spectrum Disease Prediction to Enhance the Scientific Trails 5

Superior ML Model for Autism Spectrum Disease Prediction to ...

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5th international conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Prasad, Kanakam Siva Rama Srinivasa Rao, N. Raj Kiran, K. Srinadh Reddy, K. Raghu Naga Sai, A. Srinivasulu, N. Pace Institute of Technology and Sciences Department of Cse India

ISBN: (纸本)9798350321425

Autism Spectrum Disorder (ASD) detection is difficult due to its complex nature and heterogeneous presentation. Machine learning (ML) techniques detect autism spectrum disorder from behavioral and clinical data. the K-Nearest Neighbor (KNN) algorithm with Chi-Square feature selection is proposed in this study for ASD detection. the KNN algorithm is a famous classification and regression machine learning algorithm. In autism detection, KNN can be used as a classification algorithm to determine whether or not a person has autism. the first step in implementing KNN for autism detection is to collect data on individuals with and without autism. this study's dataset includes 704 children aged 2 to 17, including 352 typically developing children and 352 children with ASD. Twenty features in the dataset are related to social interaction, communication, and behavior. To select the most relevant features for ASD detection, Chi-Square feature selection is used. the KNN algorithm is trained on the features chosen and then tested using 10-fold cross-validation. the results show that the KNN algorithm with Chi-Square feature selection detects ASD with an accuracy of 91.47%. Eye contact, gesturing, pointing, and social smiling are chosen features. Using ML techniques, the proposed method provides a promising approach for ASD detection. Using Chi-Square feature selection improves the KNN algorithm's performance by selecting the most relevant features for ASD detection. Future research can improve the performance of the proposed approach by incorporating new features and experimenting with different ML algorithms. © 2023 IEEE.

关键词： Feature Selection

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ConvNeXt-CBAM: Integrating CBAM and Near-Infrared data for Improved Land Cover Classification 5

ConvNeXt-CBAM: Integrating CBAM and Near-Infrared Data for I...

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5th international conference on Control, Robotics, and Intelligent System, CCRIS 2024

作者： Xu, Shihao Yan, Yue Liu, Xiaolin He, Haixingyue The Artificial Intelligence College of Chongqing Technology and Business University Chongqing China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

To address issues such as low classification accuracy caused by small differences in infrared absorption spectra and severe spectral data overlap during land cover classification, this study proposes a land cover classification method based on the ConvNeXt framework, using near-infrared spectral data released by Eurostat as the research object. this method realizes the rapid differentiation of arable land, forest land, and grassland. the method uses short-time Fourier transform preprocessing to convert one-dimensional infrared absorption spectral data into two-dimensional images, optimizes and improves the ConvNeXt Block module, and integrates the CBAM attention module with it to enhance the model’s feature extraction capability and improve model accuracy. Finally, the original activation function GELU is replaced with the PReLU activation function to increase the neural network model’s nonlinear variability, improving model accuracy and efficiency. the results show that this method achieves a land cover classification accuracy of 86.58%, which is 26.60%, 20.25%, 15.38%, 4.72%, and 2.56% higher than common classification models CNN 1, CNN 2, VGG16, ResNet50, and ConvNeXt-t, respectively, verifying its accuracy and reliability in land cover classification, and providing new ideas and methods for land cover classification. © 2024 SPIE.

关键词： Infrared absorption

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A Comparison of Publish-Subscribe and Client-Server Models for Streaming IoT Telemetry data 5th

A Comparison of Publish-Subscribe and Client-Server Models f...

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5th EAI international conference on Emerging Technologies for Developing Countries, AFRICATEK 2022

作者： Ajayi, Olasupo Bagula, Antoine Bode, Joshua Damon, Moegammad Department of Computer Science University of the Western Cape Cape Town South Africa

ISBN: (纸本)9783031358821

In recent years, the Internet of things (IoT) has become a household name both in research and commercial domains. there are numerous practical applications of IoT, ranging from sophisticated solutions in big factories to simple smart homes devices, such as temperature monitors. Common to these solutions is the need to transmit data from a sensing source to a different location where the data is read, processed, analyzed, or simply stored. Numerous models and protocols have been developed to ferry IoT data, including queueing, client-server, and publish-subscribe models, all with their merits and demerits. In this paper, a comparison of two models for transmitting live/streaming IoT telemetry data is done. the Message Queue Telemetry Transport (MQTT), a publish-subscribe model, is compared with WebSocket, a client-server model, in terms of throughput, round trip time and system utilization. Obtained results reveal that MQTT is more suited for transmitting live IoT data than WebSocket, as it had better throughput, utilized less system resource, however it was slightly slower than WebSocket. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Internet of things

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Reliable Biometric Authentication with Privacy Protection 5th

Reliable Biometric Authentication with Privacy Protection

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5th international conference on Communication, Device and Networking, ICCDN 2021

作者： Sharma, Shilpi Barman Dhall, Ishika Nayak, Soumya Ranjan Chatterjee, Pushpita Amity School of Engineering and Technology Amity University Uttar Pradesh Noida India Tennessee State University NashvilleTN United States

ISBN: (纸本)9789811920035

Objectives To study and compare different types of biometric systems and to obtain the result for the same, this paper has discussed the need of biometrics, ways of performing it and the best type of biometrics that should be implemented. Methods and findings: We used various statistics, graphical and tabular representations for showing data studied from different papers and reviewing them. Instances of infringements of right to privacy and protection of personal data are proliferating. Biometric systems are identity authentication systems for information assurance and protection via biological traits since they are unique. technology is rapidly advancing in every field and choosing passwords are not enough. Biometric systems are the best approach to keep data safe, and it also makes the accessing of data simple. Everything has its own pros and cons so;we will be discussing the pros and cons of various biometric technologies in order to determine the best among them. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Biometrics

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Research on database Language Query Method Based on Cloud Computing Platform 5th

Research on Database Language Query Method Based on Cloud Co...

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5th EAI international conference on Multimedia technology and Enhanced Learning, ICMTEL 2023

作者： Gong, Shao Long, Caofang Jin, Weijia School of Humanities and Communication University of Sanya Sanya572022 China School of Information and Intelligence Engineering University of Sanya Sanya572022 China Zhejiang Tongji Vocational College of Science and Technology Hangzhou311231 China

ISBN: (纸本)9783031505768

Some database language query methods have the problems of time cost and resource occupation. Under this background, a database language query method based on cloud computing platform is designed. Convert the formally described information into data that can be stored, extract the semantic Web hierarchy, and establish relationships with real objects, identify the potential association features of database words and sentences, restore the original orthogonal semantic structure space, build ontology annotation model based on cloud computing platform, transplant HanLP’s neural network dependency syntax analysis tool, and design language query methods. Test results: the average time cost and resource utilization of the database language query method designed this time are 1720 ms and 42.36% respectively, which shows that the database language query method designed this time is more effective under the technical support of the cloud computing platform. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Cloud computing

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Dialog History Management for End-to-End Task-oriented Dialog Systems 5

Dialog History Management for End-to-End Task-oriented Dialo...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Nie, Shijia Li, Guanjun Zhang, Xuesong Zhang, Dawei Tao, Jianhua Lv, Zhao School of Computer Science and Technology Anhui University Hefei230601 China NLPR Institute of Automation Chinese Academy of Sciences Beijing100098 China

ISBN: (纸本)9781510662520

End-to-end task-oriented dialogue systems rely heavily on an understanding of the dialog history. this often faces the challenge of inferring which dialog history information is critical to generating responses. In this paper, we address this challenge by leveraging a dialog history manager component that dynamically focuses on dialog history memory. It performs multiple add and forget operations by fusing an enhanced entity representation of dialog history and knowledge base (KB) information as queries, remembering entities relevant to responses and filtering out unimportant information. Experimental results on an open task-oriented dialogue dataset show that our model outperforms the baseline system in terms of effectiveness and produces contextually consistent responses. © 2023 SPIE.

关键词： Knowledge based systems

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Artificial Intelligence Integrated with 5G for Future Wireless Networks 6

Artificial Intelligence Integrated with 5G for Future Wirele...

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6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Gunturu, Vijaya Ranga, Jarabala Murthy, C. Ravindra Swapna, B. Balaram, Allam Raja, Ch. Department of ECE SR University Telangana Warangal India Department of EEE Ramachandra College of Engineering Eluru AP India Department of ECE School of Engineering Mohan Babu University Erst While Sree Vidyanikethan Engineering College Andhra Pradesh Tirupati India Department of ECE Dr MGR Educational and Research Institute Chennai95 India Department of CSE MLR Institute of Technology Hyderabad500043 India Department of ECE Mahatma Gandhi Institute of Technology Hyderabad India

ISBN: (纸本)9798350398496

Artificial intelligence and fifth-generation mobile networks (5G) are two of the few technologies that work together so effectively. the complexity of a 5G ecosystem necessitates a level of service assurance that can't be met by human effort alone. Fifth-generation network operators will leverage AI for network diagnostics, cybersecurity, and personalized applications, all of which will radically alter the relationshipbetween businesses and their consumers. the facts that even more nearly half of internet services have already integrated another aspect of AI into its 5G networks demonstrates that the industry has already invested much in the coupling. At the core of the complementary connection between AI and 5G is the significance of data;5G opens a floodgate for data, something AI could then analyses as well as learn from more swiftly to create unique consumer experiences that were already suited to the numerous needs of consumers. As AI runs simulations for analysis, reasoning, data fitting, clustering, including optimization, the 5G network provides support in the background, increasing the reliability and significance of the findings. the eventual expansion of 5G-powered Internet of things (IoT) devices in settings as diverse as manufacturing floors and driverless cars will cause the volume of data to grow not linearly but exponentially. Reason being, 5G will provide for much quicker data transfers. All of these gadgets and their integrated sensors provide new data that can be used to train smarter computer systems. © 2023 IEEE.

关键词： 5G mobile communication systems

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Research on Imaging Algorithm of Industrial Pipeline Detection Based on List-Mode data 5

Research on Imaging Algorithm of Industrial Pipeline Detecti...

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5th international conference on Intelligent Control, Measurement and Signal Processing, ICMSP 2023

作者： Wang, Ming Zhao, Min Yao, Min Ma, Bolin Xiao, Hui College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350336030

In order to realize the y-photon nondestructive detection of industrial confined pipelines, it is necessary to construct large axial ring y-photon detectors, but with the increase of the axial length of the detectors, the acquisition of response lines will be truncated and missing, resulting in the degradation of the detection imaging quality in large axial space. In this paper, we propose a list-mode data-based imaging algorithm for industrial confined pipe detection, which makes full use of the list-mode to conform to the position and time information in the event and to reasonably assign the weights of the system matrix in the image reconstruction. When calculating the weight contribution of the pixels passing through a response line to that response line, only the pixels within the uncertainty range need to be calculated without the pixels corresponding to the complete response line, and the system matrix containing time-of-flight (TOF) information is obtained, thus effectively suppressing the noise caused by truncated and missing large axial spatial data. In addition, the parallel feature of CUDA is also used to divide the system matrix calculation process into small blocks that are independent of each other to achieve accelerated optimization of the algorithm. Finally, two industrial models are used for simulation experiments, and the experimental results show that the proposed method can significantly improve the resolution and spatial contrast of large axial spatial reconstruction images in industrial confined pipeline inspection, and can meet the demand of y-photon nondestructive inspection of industrial confined pipelines. © 2023 IEEE.

关键词： Photons

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