2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)最新文献_第3页

Comparative analysis of filipino-based rhinolalia aperta speech using mel frequency cepstral analysis and Perceptual Linear Prediction 使用mel频率倒谱分析和感知线性预测的菲律宾语鼻音aperta语音比较分析

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269507

Herbert Bonifaco, Kris Roy Guzman, J. Jara, Alberto Dominic Jasareno, Arthur Christian Zabala, Seigfred V. Prado, C. Buenaventura

{"title":"Comparative analysis of filipino-based rhinolalia aperta speech using mel frequency cepstral analysis and Perceptual Linear Prediction","authors":"Herbert Bonifaco, Kris Roy Guzman, J. Jara, Alberto Dominic Jasareno, Arthur Christian Zabala, Seigfred V. Prado, C. Buenaventura","doi":"10.1109/HNICEM.2017.8269507","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269507","url":null,"abstract":"In this work, a database collected from two different Filipino Cleft Palate patients was used to identify the discriminative features for hypernasal speech. Data from the Filipino Speech Corpus (FSC) were used as normal speech samples. The features identified were based from three feature extraction algorithms, Mel Frequency Cepstrum Coefficient (MFCC), Perceptual Linear Prediction (PLP), along with a MFCC-PLP hybrid feature extraction method, which was introduced in this study. Intraclass and interclass correlation among the speech samples, separating the two hypernasal speech samples and along with the normal speech samples were computed to determine the correlation of the speech samples to each other. This paper will also compare the differences between the extracted MFCC features, PLP features and a hybrid of MFCC and PLP features to determine the most discriminative features from hypernasal speech compared with normal speech and the most discriminative features from hypernasal speech obtained from different study volunteers through Analysis of Variance (ANOVA) statistical analysis. The p-values obtained from the ANOVA test will be the basis to determine which features provide a certain degree of significant difference between speech samples. The paper will also present and determine the most optimal and conclusive feature extraction method in analyzing speech samples using MATLAB and through correlation analysis.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122157719","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: 2

Microcontroller and app-based air quality monitoring system for particulate matter 2.5 (PM2.5) and particulate matter 1 (PM1) 基于微控制器和应用程序的PM2.5和PM1空气质量监测系统

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269517

Glenn O. Avendaño, Jennifer C. Dela Cruz, A. Ballado, L. G. R. Ulyzes, Audimar C. Paras Atienza, Brian Jose G. Regala, Ricardo C. Uy

{"title":"Microcontroller and app-based air quality monitoring system for particulate matter 2.5 (PM2.5) and particulate matter 1 (PM1)","authors":"Glenn O. Avendaño, Jennifer C. Dela Cruz, A. Ballado, L. G. R. Ulyzes, Audimar C. Paras Atienza, Brian Jose G. Regala, Ricardo C. Uy","doi":"10.1109/HNICEM.2017.8269517","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269517","url":null,"abstract":"Particulate matter,\" also known as particle pollution or PM, is a complex mixture of extremely small particles and liquid droplets. Particle pollution is made up of a number of components, including acids (such as nitrates and sulfates), organic chemicals, metals, and soil or dust particles. The size of particles is directly linked to their potential for causing health problems. Once inhaled, these particles can affect the heart and lungs and cause serious health effects. The purpose of the researchers is to provide a standalone device that can monitor Particulate Matter (PM) levels and provide a mobile application for end user to check the PM level of a specific location. The system of this project is a microcontroller based, and it has sensor that can detect concentrations of PM2.5 and PM1. For monitoring purposes, there will be a mobile application provided that shows real-time data gathered by the sensor. The device has a GSM MODULE that sends data to the Raspberry Pi(server) that is then connected to the internet. The mobile application receives real-time data from the sensor and gives notifications to the user if the concentration level of PM is still safe. The researchers conduct three tests in locations given by DENR. The three tests determine which location has high, medium and low concentration of Particulate Matter.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114235656","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: 9

Usage prediction of appliances in filipino households using Bayesian algorithm 基于贝叶斯算法的菲律宾家庭电器使用预测

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269529

Ian Joseph J. Pastorfide, Juan Franco M. Revilla, Chantel Kim D. Santos, Jennica Tsubasa F. Takada, Daryl Alden S. Viray, Kanny Krizzy D. Serrano, Edison A. Roxas, A. Bandala, Angelo R. dela Cruz, R. R. Vicerra

{"title":"Usage prediction of appliances in filipino households using Bayesian algorithm","authors":"Ian Joseph J. Pastorfide, Juan Franco M. Revilla, Chantel Kim D. Santos, Jennica Tsubasa F. Takada, Daryl Alden S. Viray, Kanny Krizzy D. Serrano, Edison A. Roxas, A. Bandala, Angelo R. dela Cruz, R. R. Vicerra","doi":"10.1109/HNICEM.2017.8269529","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269529","url":null,"abstract":"The standby power accumulated after some time contributes to the wasted energy of a household and can be noticeable in a home's power consumption. In this study, the group aims to devise a standby power management system that is able to adapt constantly with one's changing lifestyle. To know the appliances available in households, a survey with 230 respondents was conducted and the most common appliances were taken into consideration. The power measurements of the appliances were also recorded using a power meter. The data log was conducted by members of different households for the activation of the appliances, the users, and the occupancy of the household. The mentioned factors from the usage log was then used on the Bayesian algorithm, which was used to calculate the probability of usage of the appliances. This learning prediction, in addition, to a power management system will minimize the power consumed by appliances in standby mode, thus saving energy and income.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"575 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116205477","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

Reinforced concrete ultimate bond strength model using hybrid neural network-genetic algorithm 基于混合神经网络遗传算法的钢筋混凝土极限粘结强度模型

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269560

J. P. M. Rinchon, N. Concha, M. Calilung

{"title":"Reinforced concrete ultimate bond strength model using hybrid neural network-genetic algorithm","authors":"J. P. M. Rinchon, N. Concha, M. Calilung","doi":"10.1109/HNICEM.2017.8269560","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269560","url":null,"abstract":"The bond strength in reinforced concrete is defined as resistance to slipping of the reinforcing steel bars from the concrete. This slipping resistance is one of the most important features in the performance of the reinforced concrete structure, particularly to its failure mode and mechanisms. In this study, a hybrid model using Artificial Neural Network (ANN) and Genetic Algorithm (GA) has been developed to predict and optimize the ultimate bond strength (tu) between the reinforcing bar and the concrete based on numerous variables that influence this property. These variables include 28-day cube compressive strength f'c), concrete cover (c), the diameter of reinforcing bar (db), embedded length (Lm), rib height (hr), and rib spacing (sr). ANN was utilized into the prediction of bond property between the reinforcing bar and concrete based on the aforesaid input variables. The ultimate bond strength predicted by ANN model exhibited reasonably accurate and good agreement with the experimental values. On the other hand, GA was deployed in the search for the optimal combination of the input variables which resulted in high bond strength performance. Optimization results showed that smaller hr and sr developed high quality of the bond between the reinforcing steel bar and the concrete.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116724367","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: 18

Surveillance systems integration for real time object identification using weighted bounding single neural network 基于加权边界单神经网络的监控系统集成实时目标识别

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269461

Ryann Alimuin, Aldrich Guiron, E. Dadios

引用次数: 1

Application of artificial neural network in determination of sorptivity model of concrete with varying percent of replacement of sand to copper slag 人工神经网络在铜渣掺砂率变化时混凝土吸附模型确定中的应用

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269537

Kim Paolo S. Aquino, Jessica S. Caisip, Aldrin Nicole I. Placiente, Erwin C. Reyes, M. Calilung

{"title":"Application of artificial neural network in determination of sorptivity model of concrete with varying percent of replacement of sand to copper slag","authors":"Kim Paolo S. Aquino, Jessica S. Caisip, Aldrin Nicole I. Placiente, Erwin C. Reyes, M. Calilung","doi":"10.1109/HNICEM.2017.8269537","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269537","url":null,"abstract":"Many construction companies and individuals (construction designers) are still using spreadsheets and laboratory tests just to obtain a certain data. In the field of technologies, advancement will contribute to the improvement of designing structures in terms of usefulness and effectiveness. By using the principle of artificial neural network, this study developed a sorptivity model which gives immediate quantities with high accuracy and precision which are needed to attain appropriate sorptivity values of concrete design mix. In this study, 40 concrete samples with varying percent replacement of copper slag to sand were tested for sorptivity by following the ASTM C1585 which is the Standard Test Method for Measurement of Rate of Absorption of Water by Hydraulic-Cement Concretes. These values in turn were used in the development of the sorptivity model using Artificial Neural Network. This study used the software called Matrix Laboratory (MATLAB) to train several neural networks. Several numbers of neurons in the hidden layer were considered because there is no actual study that suggests that a certain number of nodes in the hidden layer produce the best model. A parametric testing was conducted to determine which of the parameters considered have the greatest significance to the target output. The predicted results of the best model were compared to the experimental values of sorptivity and produced a 2.36 percentage error. The study results suggest that ANN models could be used to predict the sorptivity value of a concrete sample. The model produced a good prediction result.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132813335","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

Modeling of a hybrid renewable power system for Calayan Island, Cagayan using the HOMER software 使用HOMER软件对卡加延岛的混合可再生能源系统进行建模

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269479

A. Rey, R. Santiago, M. Pacis

{"title":"Modeling of a hybrid renewable power system for Calayan Island, Cagayan using the HOMER software","authors":"A. Rey, R. Santiago, M. Pacis","doi":"10.1109/HNICEM.2017.8269479","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269479","url":null,"abstract":"The island of Calayan is locared 39 kilometers from the Babuyan Island directed west-south-west off the coast in the Philippines. Grid connectivity is nearly impossible since the island is far away from the mainland based on geographic location. The electricity demand in the area is fulfilled by stand-alone diesel generators but for limited hours only. Fortunately, a reliable and continuous supply of electricity is possible because the island is rich with renewable energy sources such as hydro, wind and solar. In this study, an attempt has been made to model a hybrid renewable power system to supply the electricity demand of the island in a reliable and sustainable manner. This hybrid system incorporates a combination of solar PV, wind turbines, diesel generators, micro-hydro plant and batteries. HOMER software is used to analyze and find out the best possible configuration based on the available renewable sources in the area. A 50 kW solar PV, 50×10 kW wind turbines, 1×180 kW and 1×120 kW diesel generators, 450×2 kWh batteries, 250 kW hydroelectric plant and a 150 kW converter hybrid system are found to be the best among all other configurations in terms of net present cost (NPC) and cost of energy (COE). This configuration gives the lowest COE at P11.89/kWh and NPC of P236M with a renewable fraction of 88%.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133270700","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: 9

Biodiversity sustainability using telemetry for the remote transmission of data from Lake Buhi, Camarines Sur 利用遥测技术远程传输南卡马内斯布希湖数据的生物多样性可持续性

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269518

Celeste O. Martinez-Ojeda, Ramon G. Garcia, J. D. dela Cruz

{"title":"Biodiversity sustainability using telemetry for the remote transmission of data from Lake Buhi, Camarines Sur","authors":"Celeste O. Martinez-Ojeda, Ramon G. Garcia, J. D. dela Cruz","doi":"10.1109/HNICEM.2017.8269518","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269518","url":null,"abstract":"The biodiversity remediation strategies currently used at Lake Buhi, Camarines Sur shows that new techniques are required to solve the problems of decreasing level of dissolved oxygen, increasing carbon dioxide and varying pH values. One such technique that could be used involved the use of telemetry for the remote transmission of data. This method used reactive media, particularly the sensors, to evaluate contaminated lake water. The aims of this study were to develop a telemetric device for real time monitoring and identification of water quality problems; develop a complementary program using Visual Basic and microchip that could remotely monitor water quality through the use of a GSM module; and perform comparative evaluation of the results derived from the device with the results produced by the conventional methods. The comparative evaluations of the results derived from the device were in congruence with the existing method. Its lower variance proved the greater precision of the proposed device. Hence, the telemetry device could be considered as an alternative to the existing device and can be adopted for use by the different LGUs in the province for a more efficient monitoring of water quality in the province.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091939","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

TRANSPRO: An educational tool for the design and analysis of power transmission lines transspro:设计和分析输电线路的教育工具

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269544

G. F. Apolinario, M. Pacis

{"title":"TRANSPRO: An educational tool for the design and analysis of power transmission lines","authors":"G. F. Apolinario, M. Pacis","doi":"10.1109/HNICEM.2017.8269544","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269544","url":null,"abstract":"A power transmission network typically connects power plants to multiple substations near a populated area thus the need for efficient, reliable, and safe lines is of great importance. Hence, this study was done. The main topic of the study was the creation of TRANSPRO software in determining the performance of power transmission line and to make it safe and reliable. The methodology of the study is composed of conceptualizing, developing the software features, and gathering of information, deriving of formulas and constructing the structure of the software using Visual C# as programming language. Sample problems are applied to verify the outputs of the program and were also verified using TQNE9080 transmission line simulator for its performance and efficiency. A survey among Mapua Institute of Technology electrical engineering students and professors was likewise conducted to know if the software will be a helpful educational tool for the analysis and design of power transmission line. Hence, from the validation of theories with respect to TRANSPRO having a percentage difference of less than 1%, to the validation of data with TQNE9080 transmission trainer by graphical analysis and to the interpretation of surveys conducted to Electrical Engineering Students and Professors, TRANSPRO was accepted and could be used as an educational tool for the design and analysis of power transmission lines.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114314873","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

Information security technology for computer networks through classification of cyber-attacks using soft computing algorithms 计算机网络的信息安全技术，通过使用软计算算法对网络攻击进行分类

2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) Pub Date : 2017-12-01 DOI: 10.1109/HNICEM.2017.8269430

Jason A. Villaluna, F. Cruz

{"title":"Information security technology for computer networks through classification of cyber-attacks using soft computing algorithms","authors":"Jason A. Villaluna, F. Cruz","doi":"10.1109/HNICEM.2017.8269430","DOIUrl":"https://doi.org/10.1109/HNICEM.2017.8269430","url":null,"abstract":"The Internet is the global platform which revolutionized the computer and communications domain. Although it becomes one of the most useful tools in people's lives, the presence of cyber-attacks that can cause damage, modification, and theft of vital data and information over this platform has increased. Utilization of soft-computing based on the behavior of the network may detect new or modified old attacks. An information security system is developed for the recognition the network infrastructure's behavior. This is limited to Normal, DoS, Probe, U2R, and R2L. The packets on the network are processed in MATLAB and analyze using Fuzzy Logic, Artificial Neural Network, and Fuzzy-Neural Network. Different tests are done with different datasets of varied parameters. The best model for each algorithm, which is rendered from the tests, is used for the information security system. The cyber-attacks were identified within a short period: 51.64us for Fuzzy Logic, 1.34us for Artificial Neural Network, and 14.23us for the Fuzzy Neural Network. The detection rate and accuracy of the three algorithms are 94.84%, 98.51%, 98.60% and 89.74%, 96.09%, 96.19% respectively. The Fuzzy Neural Network has the best performance which used the advantage of Fuzzy Logic and Artificial Neural Network.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124814145","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: 4