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Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea department of Information convergence system Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

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Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

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Journal of Bionic engineering 2024年第1期21卷 447-485页

作者： Sanjay Bhardwaj Da-Hye Kim Dong-Seong Kim department of IT convergence engineering ICT Convergence Research CenterKumoh National Institute of TechnologyGumiSouth Korea

In industrial wireless networks,data transmitted from source to destination are highly *** often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet ***,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless *** term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for *** a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base *** includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue *** features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue *** analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and *** results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC ***,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ***,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other *** results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet *** proposed a

关键词： Dragonfly Damselfly Interaction Queuing delay Optimization Industrial wireless networks

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Evaluation of Pencil Lead Based Electrodes for Electrocardiogram Monitoring in Hot Spring

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Computers, Materials & Continua 2021年第2期66卷 1411-1425页

作者： Ratha Yeu Namhui Ra Seong-A Lee Yunyoung Nam department of ict convergence Rehabilitation engineering Soonchunhyang UniversityAsan31538Korea department of ict convergence Soonchunhyang UniversityAsan31538Korea department of Occupational Therapy Soonchunhyang UniversityAsan31538Korea department of Computer Science and engineering Soonchunhyang UniversityAsan31538Korea

Electrocardiogram(ECG)electrodes are conductive pads applied to the skin to measure cardiac ***/AgCl electrodes are the commercial product which widely used to obtain *** monitoring the ECG in a hot spring,Ag/AgCl electrodes must be waterproofed;however,this is time-consuming,and the adhesive may tear the skin on *** solving the problem,we developed the carbon pencil lead(CPL)electrodes for use in hot *** CPL and Ag/AgCl electrodes were connected to ECG100C’s *** Performance was evaluated in three conditions as following:hot spring water with and without bubble,and in cold *** each environment,the procedure was followed by three different protocols that are recording from the dry condition,hot spring water immersion with and without movement,post hot spring water *** dry and wet conditions,both electrodes can obtain the waveform of the ECG signal in which all PQRST waves were ***,the signal quality of both types of electrodes was different in water immersion with and without *** overall morphology obtained by Ag/AgCl electrodes was unstable higher than that of CPL electrodes in immersion without movement *** CPL electrodes provided better ECG waveform quality compared to Ag/AgCl electrodes in which the ECG signal had high waveforms distortion in water immersion with movement condition.

关键词： Carbon pencil lea ECG electrodes ECG monitoring hot spring water cold water hot spring water bubble

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A Deep Learning Hierarchical Ensemble for Remote Sensing Image Classification

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Computers, Materials & Continua 2022年第8期72卷 2649-2663页

作者： Seung-Yeon Hwang Jeong-Joon Kim department of Computer engineering Anyang UniversityAnyang-si14028Korea department of ict convergence engineering Anyang UniversityAnyang-si14028Korea

Artificial intelligence,which has recently emerged with the rapid development of information technology,is drawing attention as a tool for solving various problems demanded by society and *** particular,convolutional neural networks(CNNs),a type of deep learning technology,are highlighted in computer vision fields,such as image classification and recognition and object *** these CNN models requires a large amount of data,and a lack of data can lead to performance degradation problems due to *** CNN architecture development and optimization studies become active,ensemble techniques have emerged to perform image classification by combining features extracted from multiple CNN *** this study,data augmentation and contour image extraction were performed to overcome the data shortage *** addition,we propose a hierarchical ensemble technique to achieve high image classification accuracy,even if trained from a small amount of ***,we trained the UCMerced land use dataset and the contour images for each image on pretrained VGGNet,GoogLeNet,ResNet,DenseNet,and *** then apply a hierarchical ensemble technique to the number of cases in which each model can be *** experiments were performed in cases where the proportion of training datasets was 30%,50%,and 70%,resulting in a performance improvement of up to 4.68%compared to the average accuracy of the entire model.

关键词： Image classification deep learning CNNs hierarchical ensemble UC-Merced land use dataset contour image

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Data Augmentation Using Contour Image for Convolutional Neural Network

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Computers, Materials & Continua 2023年第6期75卷 4669-4680页

作者： Seung-Yeon Hwang Jeong-Joon Kim department of Computer engineering Anyang UniversityAnyang-si14058Korea department of ict convergence engineering Anyang UniversityAnyang-si14058Korea

With the development of artificial intelligence-related technologies such as deep learning,various organizations,including the government,are making various efforts to generate and manage big data for use in artificial ***,it is difficult to acquire big data due to various social problems and restrictions such as personal information *** are many problems in introducing technology in fields that do not have enough training data necessary to apply deep learning ***,this study proposes a mixed contour data augmentation technique,which is a data augmentation technique using contour images,to solve a problem caused by a lack of ***,a famous convolutional neural network(CNN)architecture,and CIFAR-10,a benchmark data set,are used for experimental performance evaluation to prove the superiority of the proposed *** to prove that high performance improvement can be achieved even with a small training dataset,the ratio of the training dataset was divided into 70%,50%,and 30%for comparative *** a result of applying the mixed contour data augmentation technique,it was possible to achieve a classification accuracy improvement of up to 4.64%and high accuracy even with a small amount of data *** addition,it is expected that the mixed contour data augmentation technique can be applied in various fields by proving the excellence of the proposed data augmentation technique using benchmark datasets.

关键词： Data augmentation image classification deep learning convolutional neural network mixed contour image benchmark dataset

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A Universal Activation Function for Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3553-3569页

作者： Seung-Yeon Hwang Jeong-Joon Kim department of Computer engineering Anyang UniversityAnyang-si14028Korea department of ict convergence engineering Anyang UniversityAnyang-si14028Korea

Recently,deep learning has achieved remarkable results in fields that require human cognitive ability,learning ability,and reasoning *** functions are very important because they provide the ability of artificial neural networks to learn complex patterns through *** activation functions are being studied to solve problems such as vanishing gradients and dying nodes that may occur in the deep learning ***,it takes a lot of time and effort for researchers to use the existing activation function in their ***,in this paper,we propose a universal activation function(UA)so that researchers can easily create and apply various activation functions and improve the performance of neural *** can generate new types of activation functions as well as functions like traditional activation functions by properly adjusting three *** famous Convolutional Neural Network(CNN)and benchmark datasetwere used to evaluate the experimental performance of the UA proposed in this *** compared the performance of the artificial neural network to which the traditional activation function is applied and the artificial neural network to which theUA is *** addition,we evaluated the performance of the new activation function generated by adjusting the hyperparameters of *** experimental performance evaluation results showed that the classification performance of CNNs improved by up to 5%through the UA,although most of them showed similar performance to the traditional activation function.

关键词： Deep learning activation function convolutional neural network benchmark datasets universal activation function

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Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

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Computer Modeling in engineering & Sciences 2024年第8期140卷 1729-1755页

作者： Awais Khan Chomyong Kim Jung-Yeon Kim Ahsan Aziz Yunyoung Nam department of ict convergence Soonchunhyang UniversityAsan31538Korea ict convergence Research Center Soonchunhyang UniversityAsan31538Korea Emotional and Intelligent Child Care convergence Research Center Soonchunhyang UniversityAsan31538Korea

Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by *** posture assessment remains challenging because of the complex nature of the human body and variations in sleep ***,this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification,thereby enhancing the analysis of body position and *** method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras,which depict six commonly adopted postures:supine,left log,right log,prone head,prone left,and prone *** study involves 10 participants under two conditions:with and without ***,the database is normalized into a video *** subsequent step entails training a fine-tuned,pretrained Visual Geometry Group(VGG16)and ResNet50 *** the third phase,the extracted features are utilized for *** fourth step of the proposed approach employs a serial fusion technique based on the normal distribution to merge the vectors derived from both the RGB and thermal ***,the fused vectors are passed to machine learning classifiers for final *** dataset,which includes human sleep postures used in this study’s experiments,achieved a 96.7%accuracy rate using the Quadratic Support Vector Machine(QSVM)without the ***,the Linear SVM,when utilized with a blanket,attained an accuracy of 96%.When normal distribution serial fusion was applied to the blanket features,it resulted in a remarkable average accuracy of 99%.

关键词： Human sleep posture VGG16 deep learning ResNet50 fusion machine learning

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A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

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Nano-Micro Letters 2025年第2期17卷 417-431页

作者： Yunjian Guo Kunpeng Li Wei Yue Nam‑Young Kim Yang Li Guozhen Shen Jong‑Chul Lee department of Electronic convergence engineering Kwangwoon UniversitySeoul 01897South Korea Radio Frequency Integrated Circuit(RFIC)Bio Centre Kwangwoon UniversitySeoul 01897South Korea department of Electronic engineering Kwangwoon UniversitySeoul 01897South Korea School of Microelectronics Shandong UniversityJinan 250101People’s Republic of China State Key Laboratory of Integrated Chips and systems Fudan UniversityShanghai 200433People’s Republic of China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081People’s Republic of China

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily *** existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple *** features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance *** wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist ***,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various *** system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and *** proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific *** utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

关键词： Wearable wristband Self-supervised contrastive learning Dynamic gesture Air-writing Human-machine interaction

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Planning for selective amygdalohippocampectomy involving less neuronal fiber damage based on brain connectivity using tractography

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Neural Regeneration Research 2015年第7期10卷 1107-1112页

作者： Seung-Hak Lee Mansu Kim Hyunjin Park department of Electronic Electrical and Computer engineering Sungkyunkwan University Graduate School of Human ict convergence Sungkyunkwan University School of Electronic and Electrical engineering Sungkyunkwan University

Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（***）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.

关键词： nerve regeneration epilepsy selective amygdalohippocampectomy diffusion tensor imaging tractography connectivity betweenness centrality magnetic resonance imaging network analysis temporal lobe surgery neuronal fibers neural regeneration

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Blue TiO2 polymorph: An efficient material for dye-sensitized solar cells fabricated using a low-temperature sintering process

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Progress in Natural Science:Materials International 2018年第5期28卷 548-553页

作者： Huy Hao Nguyen Gobinda Gyawali Tae Ho Kim Sami Bin Humam Soo Wohn Lee department of Environmental and Bio-chemical engineering Sun Moon University Division of Basic engineering Sun Moon University Division of Mechanics and ict convergence engineering Sun Moon University

Recently,surface-disordered or non-stoichiometric TiO2,such as blue TiO2（B-TiO2）,has received much attention owing to its unique properties,such as structural disorder near the surface and the existence of Ti3+ions and oxygen ***,surface-disordered TiO2has been applied for microwave absorption,photocatalysis,in photoelectrochemical sensors and rechargeable lithium-ion *** this work B-TiO2,a polymorph consisting of nanoparticles,nanotubes and nanosheets,was successfully synthesized and employed as a semiconductor layer in dye-sensitized solar cells（DSSCs）fabricated using a low-temperature heat treatment process（120°C）.Based on the analyses of the experimental results regarding the structure and those from the characterization of B-TiO2,and its application to DSSCs,it has been found that the B-TiO2material has an effect on electron-hole pair *** conversion efficiency of the B-TiO2DSSC（BTiO2-DSSC）was 6.18%,whereas that of the TiO2-P25 DSSC（P25-DSSC）was 3.61%,and that of the TiO2polymorph DSSC（PTiO2-DSSC）which is the precursor of B-TiO2was 4.51%.

关键词： Surface-disordered TiO2 Blue TiO2 Dye-sensitized solar cell(DSSC) Oxygen vacancy Efficiency

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