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2nd IEEE International Conference on Advancements and Key Challenges in Green Energy and Computing, AKGEC 2024

作者： Kumar, Sambhu Singh, Prashant Kumar Kushwaha, Pankaj Prasad, Sanjeev Kumar Galgotias University School of Computer Application and Technology Greater Noida India

ISBN: (纸本)9798350390179

Early detection of the condition is critical to proper diabetes management and reducing risk for complications. A new concept for early prediction of diabetes is proposed in this study where the LSTM and CNN models are combined with Bi-LSTM. The target is to use the Adam optimizer for these models on top of improving this model, and testing it onto the PIMA Indian Diabetes Dataset. The CNNLSTM model is particularly well-suited for time dependent data as it has been designed to extract the spatial patterns from an input and in turn record memory of a problem across time steps. Meanwhile, with the data from both past and future, the CNN-Bi-LSTM model is capable of better prediction. From our experimental results, we can see that these hybrid models achieve superior performance over traditional machine learning algorithms and hence could serve as a powerful resource for predicting diabetes at an early stage. Thus the application of this approach is a new challenge and seems to have potential for improving early diagnosis in order to implement timely interventions in diabetes care. © 2024 IEEE.

关键词： Prediction models

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Pruning Optimization of Deep Learning Model Based on Generalization Estimation

Pruning Optimization of Deep Learning Model Based on General...

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2024 International Conference on Artificial Intelligence, Deep Learning and Neural Networks, AIDLNN 2024

作者： Li, Xuanzhe Ke, Wenjun Wen, Wantao Liu, Shaotong Sheng, Xiaojuan School of Computer Science and Engineering Southeast University China Beijing Institute of Computer Technology and Application China

ISBN: (纸本)9798331520816

Existing research has shown that deep learning models contain considerable redundancy, requiring compression optimization to eliminate unnecessary parameters and improve computational efficiency. In model compression through pruning, many existing methods often use loss values to guide the identification of sub-network models. However, low training loss does not necessarily indicate good generalization ability. Consequently, reducing model parameters while preserving strong generalization performance has become a key area of research. Addressing the challenge of ensuring strong generalization performance of submodels after optimization through deep learning model pruning, we propose a channel-structured generalization estimation model. The model architecture incorporates Fully Connected Neural Networks (FCNN) and Gated Recurrent Units (GRU) as modules for channel feature extraction. Additionally, we introduce a differentiable pruning algorithm based on generalization estimation. Experimental results demonstrate the capability of the channel-structured generalization estimation model in predicting the generalization gap via regression. Furthermore, the proposed differentiable pruning algorithm effectively safeguards the generalization capability of sub-models. We conduct pruning experiments on NiN-structured convolutional neural network models on two datasets, CIFAR-10 and SVHN. Comparative experimental results demonstrate the effectiveness of this approach: achieving a 0.72% accuracy improvement over the original model on CIFAR-10;and a 0.12% accuracy improvement over the base model on SVHN while reducing FLOPs by 50.2%, validating the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Contrastive Learning

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Understanding Fun in Cooking: Preliminary Study of Serious Games on Cooking Domain

Understanding Fun in Cooking: Preliminary Study of Serious G...

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2024 International Conference on Information technology Systems and Innovation, ICITSI 2024

作者： Halim, Steven Andrew Rumi, Jalaluddin Pratama, Galih Dea Ramdhan, Dimas Bina Nusantara University School of Computer Science Game Application & Technology Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798331511470

Cooking is an important life skill to master. Despite the importance, a study suggests that there is a decline in cooking skills between generations. In accordance with that, serious games emerge as a form of solution which has purposes to solve the problems in an entertaining way. Serious games are often presented to solve numerous real-life problems, such as education, medical, and even culinary. This literature review studies a few of the many benefits of serious games that may help solve problems in the realm of cooking. The study focuses primarily on cooking serious games due to their capabilities to solve problems in an entertaining manner. The result indicates that there are positive benefits in utilizing serious games to solve certain problems not only in cooking, but also other issues such as cognitive skills. The findings from this research are intended to be the preliminary in developing serious game to compensate the problem from cooking domain. © 2024 IEEE.

关键词： cooking preliminary study serious game systematic literature review

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Real-time distance field acceleration based free-viewpoint video synthesis for large sports fields

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Computational Visual Media 2024年第2期10卷 331-353页

作者： Yanran Dai Jing Li Yuqi Jiang Haidong Qin Bang Liang Shikuan Hong Haozhe Pan Tao Yang School of Telecommunications Engineering Xidian UniversityXi’an 710071China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology SAIIPthe School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710129China

Free-viewpoint video allows the user to view objects from any virtual perspective,creating an immersive visual *** technology enhances the interactivity and freedom of multimedia ***,many free-viewpoint video synthesis methods hardly satisfy the requirement to work in real time with high precision,particularly for sports fields having large areas and numerous moving *** address these issues,we propose a freeviewpoint video synthesis method based on distance field *** central idea is to fuse multiview distance field information and use it to adjust the search step size *** step size search is used in two ways:for fast estimation of multiobject three-dimensional surfaces,and synthetic view rendering based on global occlusion *** have implemented our ideas using parallel computing for interactive display,using CUDA and OpenGL frameworks,and have used real-world and simulated experimental datasets for *** results show that the proposed method can render free-viewpoint videos with multiple objects on large sports fields at 25 ***,the visual quality of our synthetic novel viewpoint images exceeds that of state-of-the-art neural-rendering-based methods.

关键词： free-viewpoint video view synthesis camera array distance field sports video

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Multispectral point cloud superpoint segmentation

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Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral Information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

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Parameter sensitivity analysis of the myocardial cell models in ischemia and screening of drug targets

Parameter sensitivity analysis of the myocardial cell models...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Jun Liang, Cuiping Wang, Kuanquan School of Computer Science and Technology Harbin China Beijing Institute of Computer Technology and Application Beijing China

ISBN: (纸本)9798350337488

Previous studies have shown that coronary artery occlusion can cause myocardial ischemia, which can induce ventricular tachycardia or fibrillation. According to the time sequence, myocardial ischemia can be divided into different pathological stages: the ischemia 1a stage (0-15 minutes), the ischemia 1b stage (15-45 minutes), the short-term myocardial infarction (MI) (within a few days) and the long-term MI (within a few weeks). However, few studies give attention to antiarrhythmic drugs directly acting on ion channels for the treatment of myocardial ischemia. The main reason is that the effective targets in myocardial ischemia are unclear. Therefore, based on the technology of electrophysiological simulation, the paper modeled the human ventricular cell model in myocardial ischemia. On this basis, the parameter sensitivity of the model was analyzed and the effective drug targets are selected. Firstly, human ventricular cell models were modeled in ischemia 1a, ischemia 1b, short-term MI and long-term MI based on the experimental data. Then, the sensitivity analysis of output parameters (APA, APD and RP) of the cell model in ischemia was analyzed based on the Sobol method. The results of parameter sensitivity analysis in this paper showed that APD of cell models in ischemia 1a, ischemia 1b and short-term MI was the most sensitive to the change of IKATP, and APA and RP of cells were the most sensitive to the change of [K+]o. The parameter sensitivity analysis of the cell model in long-term MI showed that APD of cell models was sensitive to IKs and ICaL, and APA was most sensitive to INa. Therefore, according to the results of parameter sensitivity analysis, the possible effective targets for the treatment of myocardial ischemia can be preliminarily selected: [K+]o, IKATP, ICaL and INa © 2023 IEEE.

关键词： Myocardial infarction Myocardial ischemia Parameter sensitivity analysis Ventricular

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Ensemble Knowledge Distillation for Federated Semi-Supervised Image Classification

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Tsinghua Science and technology 2025年第1期30卷 112-123页

作者： Ertong Shang Hui Liu Jingyang Zhang Runqi Zhao Junzhao Du School of Computer Science and Technology Xidian UniversityXi’an 710126China Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of EducationXi’an 710126China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi’an 710126China

Federated learning is an emerging privacy-preserving distributed learning paradigm,in which many clients collaboratively train a shared global model under the orchestration of a remote *** current works on federated learning have focused on fully supervised learning settings,assuming that all the data are annotated with ground-truth ***,this work considers a more realistic and challenging setting,Federated Semi-Supervised Learning(FSSL),where clients have a large amount of unlabeled data and only the server hosts a small number of labeled *** to reasonably utilize the server-side labeled data and the client-side unlabeled data is the core challenge in this *** this paper,we propose a new FSSL algorithm for image classification based on consistency regularization and ensemble knowledge distillation,called *** algorithm uses the global model as the teacher in consistency regularization methods to enhance both the accuracy and stability of client-side unsupervised learning on unlabeled ***,we introduce an additional ensemble knowledge distillation loss to mitigate model overfitting during server-side retraining on labeled *** experiments on several image classification datasets show that our EKDFSSL outperforms current baseline methods.

关键词： federated learning semi-supervised learning federated semi-supervised learning knowledge distillation

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"Nyctophy": Assessing the effectiveness of serious game for nyctophobia based on virtual reality by usability and heart rate monitoring 9th

"Nyctophy": Assessing the effectiveness of serious game for ...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Ardiyanto, Elshad Ryan Alexander, Patrick Putra, Edyth Novian Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Nyctophobia is a phobia of the dark and is common among children but also found in adults. While the phobia itself is commonly known, the diversity of its treatment is still minimal. As technology has reached its highest point, numerous inventions and innovations have emerged in the medical sector. This study aimed to examine the usability of Virtual Reality and Keyboard and Mouse as an interface using the Extended Reality Game Usability Questionnaire (XR-GUQ) in Nyctophobia therapy and to analyze the heart rate response, impact, and implications using t-test Paired/Wilcoxon Signed Rank. Thirty-four Bina Nusantara University students from various backgrounds completed the test using interfaces and a smartwatch. They were divided into two groups, high- and low fear, using the modified Acrophobia Questionnaire (AQ), which resulted in a significant difference. The XR-GUQ result was insignificant in all variables, which indicates similar usability scores on both interfaces. The t-test Paired/Wilcoxon Signed Rank test revealed a significant difference between the high- and low-fear groups when using the Virtual Reality interface compared to the Keyboard and Mouse interface. This significant difference was found within each group regardless of the interface used. This research shows similar scores in terms of usability but a significant difference in heart rate response with the help of a serious game to give a new sensation of phobia therapy. © 2024 The Authors.

关键词： Serious games

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Smart Health Diagnosis:Harnessing Data Mining for Predictive Healthcare 1

Smart Health Diagnosis:Harnessing Data Mining for Predictive...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Indrakumari, R. Pandey, Vishal Sinha, Ashish Kumar Kumar, Ankesh Galgotias University School of Computer Science and Engineering India Galgotias University School of Computing Application and Technology India

ISBN: (纸本)9798350356816

The use of Smart Health Diagnosis: Data Mining for Predictive Healthcare is to provide a user- friendly and easily accessible platform where individuals can get instant health advice through an intelligent online healthcare system. By the analysis of the reported symptoms, the system can predict potential future diseases and provide relevant recommendations to healthcare providers on courses of action. Intelligent methods accurately determine potential interferences based on patient symptoms. Medical record database was used and symptoms were assigned to underlying diseases using Naive Bayesian calculations. Fast, reliable access to health care is a cornerstone of individual and social health but many people face barriers in receiving timely care. We are trying to solve these problems by introducing Health Prediction System, a revolutionary online healthcare solution that uses data mining for quick support and customized recommendations. © 2024 IEEE.

关键词： Electronic health record

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Optimized BP Neural Network Based on GA Genetic Algorithm for Generator Speed Prediction

Optimized BP Neural Network Based on GA Genetic Algorithm fo...

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2023 IEEE International Conference on Sensors, Electronics and computer Engineering, ICSECE 2023

作者： Yue, Junrong Jining University School of Mathematics and Computer Application Technology Jining China

ISBN: (纸本)9798350313734

This study aims to optimize the dispatching operation and control of power system to reduce the increased operation cost caused by the uncertainty and volatility of wind power. To achieve this goal, a data model is proposed based on GA genetic algorithm optimized BP neural network. It can predict generator speed and perform network-wide power balancing, thus ensuring the safe and stable operation of the system. The study proceeds in three stages. First, data cleaning and pre-processing are performed on the data obtained from Kaggle. Second, a BP neural network model with 11 input indicators, such as the temperature of generator winding 1 and 2, rotor speed, and hub temperature, is constructed. The output of the model is the generator speed. The weights and thresholds of the BP neural network are optimized by genetic algorithm. Finally, we verify the effectiveness of our approach. By comparing the prediction results based on the BP model only, we demonstrate that the root mean square error of the proposed method is reduced by 31.28%. This confirms that the proposed model is an effective and feasible method for predicting generator speed. In summary, the proposed data model based on GA genetic algorithm optimized BP neural network can provide improved control over wind power variability and reduce operational costs. The results of this study pave the way for further research and application of advanced modeling and optimization techniques in power systems. © 2023 IEEE.

关键词： Neural networks

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