2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)最新文献_第10页

A Novel Low-Cost Monitoring System for Sleep Apnea Patients 一种新的低成本睡眠呼吸暂停患者监测系统

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101614

Saika Afrin Sumona, Wahida Binte Naz Aurthy

{"title":"A Novel Low-Cost Monitoring System for Sleep Apnea Patients","authors":"Saika Afrin Sumona, Wahida Binte Naz Aurthy","doi":"10.1109/ECCE57851.2023.10101614","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101614","url":null,"abstract":"Sleep apnea resulting from obstructions in the upper respiratory tract during sleep is one of the most common sleep disorders that result in poor sleep and a significant degradation of our quality of life. Sleep apnea patients have frequent pauses in breathing during sleeping and very often face snoring problem. Usually, these short lapses cause a person to wake up at irregular intervals reducing their sleep quality, the older patients, however, find it very difficult to cope with such sleep apnea periods. The traditional monitoring and detection system is both expensive and complicated to be used regularly and at home. This study proposes a novel, low-cost monitoring system for sleep apnea patients which comes in the form of a wearable belt incorporating 3 different sensors to collect physiological signals correlated to sleep apnea. Electrocardiogram (ECG) sensor, photoplethysmog-raphy (PPG) sensor, and accelerometer are used with a bluetooth sensor so that the obtained data can be easily sent to a computer or mobile application where physicians, nurses, caregivers can monitor the patients without being present all the time. Using the assortment of the physiological signals, the onset of sleep apnea can be easily detected and the concerned people can be alerted instantaneously. The proposed system is affordable and can be used at home very easily.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130263037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comparative Analysis on Predicting Brain Tumor from MRI FLAIR Images Using Deep Learning 基于深度学习的MRI FLAIR图像预测脑肿瘤的比较分析

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101559

Md. Shabir Khan Akash, Md. Al Mamun

{"title":"A Comparative Analysis on Predicting Brain Tumor from MRI FLAIR Images Using Deep Learning","authors":"Md. Shabir Khan Akash, Md. Al Mamun","doi":"10.1109/ECCE57851.2023.10101559","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101559","url":null,"abstract":"It is still challenging to differentiate between normal cells and tumor demarcation in everyday clinical practice. With the use of the FLAIR modality known as Fluid Attenuated Inversion Recovery, a medical professional can learn more about tumor infiltration. Because the preponderance of the cerebrospinal fluid effect can be suppressed by the FLAIR modality. Moreover, one of the advantages of using FLAIR images is that they can be used for both 3D and 2D medical imagery. Therefore, this paper explores the idea of assessing and predicting brain tumors by implementing several types of deep learning CNN architectures, such as VGG16, ResNet50, DenseNet121 and others in a user-friendly functional U-Net architecture. The flexibility of using different pre-trained neural network models in a single architecture is the key advantage of our U-Net architecture. Hyperparameters of the architecture are adjusted and fine-tuned for the segmentation process in order to extract the core features of the tumor contour according to our problem. Having said that, this study's segmentation result on the dice similarity coefficient is 0.9165, 0.9175, 0.9137 and 0.9148 in the BraTS 2018, 2019, 2020 and 2021 datasets respectively.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131328107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Performance Evaluation of an FPGA based EOG Signal Preprocessor 基于FPGA的EOG信号预处理器的设计与性能评估

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101512

Diba Das, Aditta Chowdhury, A. I. Sanka, M. Chowdhury

{"title":"Design and Performance Evaluation of an FPGA based EOG Signal Preprocessor","authors":"Diba Das, Aditta Chowdhury, A. I. Sanka, M. Chowdhury","doi":"10.1109/ECCE57851.2023.10101512","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101512","url":null,"abstract":"Electrooculogram (EOG) is an electrophysiological signal produced around the eyes due to eyeball motion. This signal can be utilized to study eye movements which is bene-ficial in many medical and bio-electrical applications such as controlling human-computer interfaces and diagnosing different ocular diseases. However, the EOG is often contaminated with high-frequency motion artifacts, 50/60 Hz grid interference, and baseline wander. Hence, the collected signals are required to be preprocessed before finally being used in applications. This paper proposes an efficient FPGA-based EOG processor for fast and real-time processing of EOG signals, especially for medical diagnosis. To the best of our knowledge, this is the first work to implement EOG serial preprocessing by FIR and IIR filters on FPGA. MATLAB's FDA tool is used for mathematical validation and primary simulation. The proposed system was implemented on the Xilinx Zynq-7000 FPGA by hardware/software co-design. By statistical analysis, the software and hardware results were found to have the Pearson Correlation Coefficient of 0.99 and a Mean Root Squared Error in the 10–3 range. The resource utilization and power consumption are presented. The on-chip power consumption for this design is 0.271 watts where dynamic power is 0.163 watts (60%), and static power is 0.108 watts (40%). Performance evaluation and comparative study of the software-hardware results revealed the efficacy of the designed EOG preprocessor.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134245191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Security of an Audio using Multiple Watermarking 使用多重水印的音频安全性

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101632

Amita Singha, M. A. Ullah

引用次数: 0

Study of Different Candidates of Modulation Schemes for 5G Communication Systems 5G通信系统中不同候选调制方案的研究

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101611

Tamanna Sultana, Rahela Akhter Akhi, Jubayed Hossain Turag, Suhail Najeeb

{"title":"Study of Different Candidates of Modulation Schemes for 5G Communication Systems","authors":"Tamanna Sultana, Rahela Akhter Akhi, Jubayed Hossain Turag, Suhail Najeeb","doi":"10.1109/ECCE57851.2023.10101611","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101611","url":null,"abstract":"Digital modulation schemes determine how bits are mapped to the phase and amplitude of transmitted signals. This research comprehensively analyzes the necessity of studying various modulation schemes and a comparative investigation using appropriate simulations. The goal is to obtain the most effective modulation scheme for 5G technology. In the development phase of 5G technology, different candidates of modulation schemes like OFDM, F-OFDM, UFMC, FBMC, and others are being studied. For 5G communication, the modulation scheme that performs effectively across all dimensions will be evaluated. This research aims to compare several 4G and 5G modulation methods to determine the best modulation strategy for 5G technology. The comparative research for modulation schemes was carried out using modern technologies. Here, we transmit 5G data to evaluate the performance of several 4G and 5G modulation schemes to determine which Modulation Scheme is best for implementing 5G technology. Our research covered three modulation schemes: OFDM, F-OFDM, and UFMC. We employed PSD, PAPR, BER, and Constellation Diagrams to compare OFDM, which is currently used in 4G technology, with F-OFDM and UFMC, respectively. Following the comparative investigation, we discovered that F-OFDM significantly outperforms UFMC and OFDM, both modulation techniques. We also determined that F-OFDM promises enhanced efficiency in 5G technology by accurately proving all simulations for a potential application.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115680785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Alzheimer's Disease Classification From 2D MRI Brain Scans Using Convolutional Neural Networks 使用卷积神经网络从二维MRI脑扫描中分类阿尔茨海默病

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101539

R. A. Hridhee, Biddut Bhowmik, Q. D. Hossain

{"title":"Alzheimer's Disease Classification From 2D MRI Brain Scans Using Convolutional Neural Networks","authors":"R. A. Hridhee, Biddut Bhowmik, Q. D. Hossain","doi":"10.1109/ECCE57851.2023.10101539","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101539","url":null,"abstract":"Alzheimer's Disease (AD) is a neurological disorder which causes brain cells to die, resulting in memory loss associ-ated with cognitive impairment. Typical symptoms of Alzheimer's disease are- memory loss, language difficulties, and impulsive or erratic behaviour. AD varies from a mild disorder to moderate deterioration, until a severe cognitive impairment finally occurs. Currently, there is no cure to this disease. Only early diagnosis can help provide timely medical support and facilitate necessary healthcare. Magnetic Resonance Imaging (MRI) is widely used in the diagnosis of Alzheimer's Disease. Several image processing techniques are used to develop automated systems for detection and classification of AD from brain MRI. In this paper, we proposed three Convolutional Neural Network (CNN) models to detect and classify four stages of Alzheimer's disease from 2D MRI. We used the VGG16 and the Xception models with transfer learning approach, and a fully customised CNN model for the classification task. The customised model performed the best with accuracy of 0.9477, and F1-score of 0.9481. The proposed method performed better than the conventional Support Vector Machine (SVM) techniques. It is less complex, and less time consuming with better efficiencies than CNN techniques utilizing 3D MRI images.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125913962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

SHD: Development of an Smart Headband for Deafblind People SHD:一种用于聋哑人的智能发带的开发

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101656

Md. Rahatul Islam, Md Araf Israk, Ferdib-Al-Islam, Jimmy Majumder, Shahid Rahman

{"title":"SHD: Development of an Smart Headband for Deafblind People","authors":"Md. Rahatul Islam, Md Araf Israk, Ferdib-Al-Islam, Jimmy Majumder, Shahid Rahman","doi":"10.1109/ECCE57851.2023.10101656","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101656","url":null,"abstract":"In this paper, we have developed a device for the blind and deaf to detect the location of loud sounds. Deaf people in our country face various problems due to their hearing loss. They cannot hear when someone calls them, so they burden society. Inaudibility of car horns (unless honked loudly) leads to various accidents. This device will free them from these problems. Blind people can easily cross the road and walk using this device. Here we used an STM32F401CC microcontroller, LM358P IC, condenser mic, vibrator, some resistors, some capacitors, and some connectors. This device uses six sound detector vibrator circuits, which become a complete device by programming with Arduino IDE. Input is taken from six different mics. The maximum and minimum readings of the mic are extracted. The audio level is derived from the difference between the highest and lowest values 1000 times. Among the six devices with higher audio levels, the vibrator in that circuit will turn on, i.e., the sound intensity will be higher in that direction and will vibrate at that point. Then the deafblind people (users) will know from which direction the sound is coming. This device is cost-effective. According to the feature analysis, this work outperforms the previous works.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127572954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ensemble Based Machine Learning Model for Early Detection of Mother's Delivery Mode 基于集成的早期检测母亲分娩模式的机器学习模型

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101558

M. Hasan, Md Jakaria Zobair, Sumya Akter, Mahir Ashef, Nazrin Akter, Nahid Binte Sadia

{"title":"Ensemble Based Machine Learning Model for Early Detection of Mother's Delivery Mode","authors":"M. Hasan, Md Jakaria Zobair, Sumya Akter, Mahir Ashef, Nazrin Akter, Nahid Binte Sadia","doi":"10.1109/ECCE57851.2023.10101558","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101558","url":null,"abstract":"The mother's mode of delivery greatly impacts the relationship between the newborn baby and the mother, as well as the mother's and baby's health. Currently, the cesarean rate is increasing at an alarming rate. The inability to predict the mother's health status and mode of delivery are mainly responsible for this situation. Support Vector Machine (SVM), Decision Tree, Random Forest (RF), Gradient Boosting Classifier(GBC), Logistic Regression, Gaussian Naive Bayes, Stochastic Gradient Descent, CatBoost (CB), Adaptive Boosting (AB), Gaussian Naïve Bayes, Extreme Gradient Boosting(XGB) are used to predict the mother's mode of delivery. This study also proposed an ensemble machine learning algorithm that stacked the SVC, XGB, and RF together and named the ensemble SVXGBRF. To preprocess the dataset, we use a pipeline that basic preprocessing techniques, data balancing and feature selection. Our proposed SVXGBRF classifiers show 95.52% accuracy, 96% precision, recall, f1 score, and 99% AUC score. SVXGBRF shows its superiority, where most models show an accuracy of less than 90% except RF, GBC, CB, and AB. Eventually, this research could be utilized to develop a decision-support system for reducing the number of cesarean sections by trying to extract insights from complex data patterns.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117066897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of the Performance of Machine Learning and Deep Learning Techniques for Predicting Rainfall: An Illustrative Case Study from Australia 预测降雨的机器学习和深度学习技术的性能评估:来自澳大利亚的说明性案例研究

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101560

Md Sakibul Islam, Afifa Hossain, A. Khatun, A. Kor

{"title":"Evaluation of the Performance of Machine Learning and Deep Learning Techniques for Predicting Rainfall: An Illustrative Case Study from Australia","authors":"Md Sakibul Islam, Afifa Hossain, A. Khatun, A. Kor","doi":"10.1109/ECCE57851.2023.10101560","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101560","url":null,"abstract":"Rainfall is a major factor in our ecological and environmental balance for a variety of reasons, including economy, agriculture, and cleanliness. It supplies the planet with essential fresh water, especially in areas where groundwater resources are scarce. Hence, a dependable prediction model for rainfall is essential, as it can help predict flooding and monitor pollutant levels. Historically, weather predictions were made using meteorological satellites. But now, with advancements in technology and data analysis, machine learning has been utilized in weather forecasting. However, accurately predicting rainfall remains a complex task and existing methods depend on complex models that may incur high costs due to their extensive computational requirements. This research assesses the effectiveness of both conventional machine learning algorithms and deep learning techniques as potential options, by conducting a comprehensive comparison using a uniform case study that analyzed ten years of rainfall data collected from various regions in Australia. Through the comparisons and evaluations, we aim at finding the most feasible method for the detection of weather patterns. The models' performance is measured using metrics such as loss, Mean Absolute Error, Mean Squared Error and Mean Squared Logarithmic Error. The results show that the proposed CNN model is the most accurate among all the models.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124405227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ferroelectric BiMnO3 in BSF layer and Zinc doped CdS in buffer layer: Boosting up the performance of CZTS solar cell BSF层中铁电BiMnO3和缓冲层中锌掺杂CdS:提高CZTS太阳能电池性能

2023 International Conference on Electrical, Computer and Communication Engineering (ECCE) Pub Date : 2023-02-23 DOI: 10.1109/ECCE57851.2023.10101529

Md. Asiful Islam Sakib, Md. Tamzid Ahmed, Jitu Prakash Dhar

{"title":"Ferroelectric BiMnO3 in BSF layer and Zinc doped CdS in buffer layer: Boosting up the performance of CZTS solar cell","authors":"Md. Asiful Islam Sakib, Md. Tamzid Ahmed, Jitu Prakash Dhar","doi":"10.1109/ECCE57851.2023.10101529","DOIUrl":"https://doi.org/10.1109/ECCE57851.2023.10101529","url":null,"abstract":"In this work, numerical modelling and simulation of CZTS solar cell has been performed using SCAPS-1D. The alternative of toxic CdS buffer layer with $text{Zn}_{mathrm{x}}text{Cd}_{1-mathrm{x}}mathrm{S}(mathrm{x}=0.1,0.2,0.3,0.6,0.8)$ buffer layer in CZTS solar cell. Here, the effect of zinc concentration in overall performance (open circuit voltage, short circuit current, fill factor, efficiency) of CZTS solar cell is experimented. In this work, the main attempt is to take the advantages of multiferroic properties of ferroelectric material BiMnO3 (BMO) in the back surface field (BSF) layer. The maximum performance is evaluated by varying the thickness and doping concentration of buffer layer, absorber layer and back surface field layer for the structure of $text{SnO}_{2}/text{Zn}_{2}text{SnO}_{4}/text{Zn}_{mathrm{x}}text{Cd}_{1-} {}_{mathrm{x}}mathrm{S}/text{CZTS}/text{BiMnO}_{3}/text{Cu}$ with and without BSF layer. With ferroelectric material in BSF layer, the J-V curves are investigated for cell structure and the optimal photovoltaic parameters have been achieved with efficiency of 24.18%, fill $text{factor}=87.15%, mathrm{J}_{text{sc}}=27.19$ mA/cm2 and $mathrm{V}_{text{oc}}=1.02mathrm{V}$. As compared to the high performance CZTS solar cell model presented in the reference model which had efficiency of 23.72% with CdS in buffer layer and Pt in BSF layer, the proposed solar cell model in this work with zinc doped CdS in buffer layer and ferroelectric BMO in BSF layer enhanced the solar cell efficiency upto 24.18%. Here, the optical properties layer by layer photon density is also observed for CZTS solar cell with zinc doped CdS in buffer layer and BMO in back surface field (BSF) layer.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125064939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0