Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00021
Vedanshu Kumar, M. M. Tripathi
Artificial Neural Network (ANN) is used for electricity load forecasting for quite a time. ANN uses backpropagation for computing the gradient of the cost function. One obvious way to initialize weights and biases is to use Gaussian independent random variables, which is normalized to have zero mean and unit standard deviation. Issue with this kind of initialization is that it an exceptionally wide Gaussian distribution, not strongly peaked by any means. Another way to initialization of weights and biases for an ANN with n_in input weights would be to use random Gaussian variables with zero mean and 1/√n_in deviation. Case study utilizes half hourly electricity load data from five states in Australia to predict 48 hours ahead electricity load. In this paper a multi-objective cuckoo search algorithm is utilized for weights and biases initialization for quicker learning. The results show that the convergence time using proposed algorithm has reduced considerably as compared to Gaussian distribution initialization generally used in ANN.
{"title":"Weight and Bias Initialization of ANN for Load Forecasting using Cuckoo Search Algorithm","authors":"Vedanshu Kumar, M. M. Tripathi","doi":"10.1109/ICGHIT.2019.00021","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00021","url":null,"abstract":"Artificial Neural Network (ANN) is used for electricity load forecasting for quite a time. ANN uses backpropagation for computing the gradient of the cost function. One obvious way to initialize weights and biases is to use Gaussian independent random variables, which is normalized to have zero mean and unit standard deviation. Issue with this kind of initialization is that it an exceptionally wide Gaussian distribution, not strongly peaked by any means. Another way to initialization of weights and biases for an ANN with n_in input weights would be to use random Gaussian variables with zero mean and 1/√n_in deviation. Case study utilizes half hourly electricity load data from five states in Australia to predict 48 hours ahead electricity load. In this paper a multi-objective cuckoo search algorithm is utilized for weights and biases initialization for quicker learning. The results show that the convergence time using proposed algorithm has reduced considerably as compared to Gaussian distribution initialization generally used in ANN.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126307712","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00012
Mohd Ameerul Iman Mohd Ariff, Y. L. Then, F. Tay
LoRa is a proprietary technology developed by Cycleo SAS and it was acquired by Semtech in 2012. LoRa utilizes the license-free ISM band and by leveraging on LoRa's low power and long-distance transmission platform, it connects healthcare personnel in remote areas with medical specialist in urban areas in real time. A medical personal or a traditional midwife can consult medical specialist in the city regarding on a specific symptom or disease. We developed a device that is capable to send out request for emergency service, an e-stock management system and there is a medical symptom database built into it. The device is comprised of 2 Raspberry Pi model B, 7-inch touch screen and 2 Dragino LoRa/GPS shields operating at 915Mhz. A Graphical User Interface (GUI) was designed as a platform to connect the two users. We also evaluated the feasibility and practicality of this long-range transmission platform.
{"title":"Establish Connection Between Remote Areas and City to Improve Healthcare Services","authors":"Mohd Ameerul Iman Mohd Ariff, Y. L. Then, F. Tay","doi":"10.1109/ICGHIT.2019.00012","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00012","url":null,"abstract":"LoRa is a proprietary technology developed by Cycleo SAS and it was acquired by Semtech in 2012. LoRa utilizes the license-free ISM band and by leveraging on LoRa's low power and long-distance transmission platform, it connects healthcare personnel in remote areas with medical specialist in urban areas in real time. A medical personal or a traditional midwife can consult medical specialist in the city regarding on a specific symptom or disease. We developed a device that is capable to send out request for emergency service, an e-stock management system and there is a medical symptom database built into it. The device is comprised of 2 Raspberry Pi model B, 7-inch touch screen and 2 Dragino LoRa/GPS shields operating at 915Mhz. A Graphical User Interface (GUI) was designed as a platform to connect the two users. We also evaluated the feasibility and practicality of this long-range transmission platform.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133982566","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00009
S. Wong, B. Ooi, S. Liew
Proliferation of Internet-of-Thing (IoT) has introduced huge amounts of connected devices around the globe. All these connected devices are generating enormous amount of data in frequency of second or in some cases close to millisecond. It is a challenge to tackle the ingest of these "big data". We start to observe bottleneck in term of network bandwidth, storage space as well as computational cost. Therefore, people start putting attention into reducing the size of generated data before it flows to endpoints. We identify some works which work into this direction, however those solutions require certain requirements to be fulfilled, for instance space for caching and certain setup of hardware. This paper presents data reduction algorithm with realtime critical data forwarding. The experiment shows that by only forwarding 31% of data, in best case, we can achieve accuracy 0.97, at same time the algorithm detects critical data and forward to endpoint at real time.
{"title":"Data Reduction with Real-Time Critical Data Forwarding for Internet-of-Things","authors":"S. Wong, B. Ooi, S. Liew","doi":"10.1109/ICGHIT.2019.00009","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00009","url":null,"abstract":"Proliferation of Internet-of-Thing (IoT) has introduced huge amounts of connected devices around the globe. All these connected devices are generating enormous amount of data in frequency of second or in some cases close to millisecond. It is a challenge to tackle the ingest of these \"big data\". We start to observe bottleneck in term of network bandwidth, storage space as well as computational cost. Therefore, people start putting attention into reducing the size of generated data before it flows to endpoints. We identify some works which work into this direction, however those solutions require certain requirements to be fulfilled, for instance space for caching and certain setup of hardware. This paper presents data reduction algorithm with realtime critical data forwarding. The experiment shows that by only forwarding 31% of data, in best case, we can achieve accuracy 0.97, at same time the algorithm detects critical data and forward to endpoint at real time.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115051272","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00031
Hanseong Lee, Hyung-Woo Lee
Executable binary files can be developed using cryptographic modules using open libraries such as OpenSSL and Crypto++ in Windows environments. To determine the embedded encryption algorithms and detect cryptographic modules used in binary files, a high degree of knowledge on internal structure is required in de-assembling and analyzing. And the reverse engineering process on executable binary file is very difficult. Therefore, we developed an automatic detection tool that can automatically detect the cryptographic algorithm to efficiently analyze cryptographic algorithms as a form of IDA plug-in module. This tool can be used to detect and track cryptographic algorithms used in arbitrary executables on Windows OS system.
{"title":"Automatic Detection of Cryptographic Algorithms in Executable Binary Files using Advanced Code Chain","authors":"Hanseong Lee, Hyung-Woo Lee","doi":"10.1109/ICGHIT.2019.00031","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00031","url":null,"abstract":"Executable binary files can be developed using cryptographic modules using open libraries such as OpenSSL and Crypto++ in Windows environments. To determine the embedded encryption algorithms and detect cryptographic modules used in binary files, a high degree of knowledge on internal structure is required in de-assembling and analyzing. And the reverse engineering process on executable binary file is very difficult. Therefore, we developed an automatic detection tool that can automatically detect the cryptographic algorithm to efficiently analyze cryptographic algorithms as a form of IDA plug-in module. This tool can be used to detect and track cryptographic algorithms used in arbitrary executables on Windows OS system.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133570658","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00027
Jae-Jeong Hwang, K. Rhee
For a design of the Gaussian forensic detection (GFD) in the altered digital images, this paper presents a feature vector that is defined as a blurring quantity by the window size of the Gaussian filtering. The window size is prepared ten types, and their blur quantity is computed by the Gaussian filtering, respectively. In the proposed scheme of the GFD, the defined 10-dim. feature vector of the image is trained in a SVM (Support Vector Machine) classifier for the Gaussian forensic detection of the forged images. In the experiment, the measured area under the curves (AUC) are above 0.9 from a classification point of view between the altered and Gaussian filtered image. Thus, the grade evaluation of the proposed method is rated as "Excellent (A)."
{"title":"Gaussian Forensic Detection using Blur Quantity of Forgery Image","authors":"Jae-Jeong Hwang, K. Rhee","doi":"10.1109/ICGHIT.2019.00027","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00027","url":null,"abstract":"For a design of the Gaussian forensic detection (GFD) in the altered digital images, this paper presents a feature vector that is defined as a blurring quantity by the window size of the Gaussian filtering. The window size is prepared ten types, and their blur quantity is computed by the Gaussian filtering, respectively. In the proposed scheme of the GFD, the defined 10-dim. feature vector of the image is trained in a SVM (Support Vector Machine) classifier for the Gaussian forensic detection of the forged images. In the experiment, the measured area under the curves (AUC) are above 0.9 from a classification point of view between the altered and Gaussian filtered image. Thus, the grade evaluation of the proposed method is rated as \"Excellent (A).\"","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124185028","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00038
Z. Khan, T. Ganat, Juhairi Aris, S. Ridha
Discharge of produced water (PW) and drilling wastes from oil and gas industry has a major impact to the flora and fauna. The purpose of this study is to investigate the PW impact on the Mediterranean region and to provide alternative ways to detect the harmful parameters present in the produced water and drilling waste. Study shows the PW and drilling waste analysis in lab and it shows the idea of using smart phone to know all the harmful parameters. Varies sensors are connected to water to detect the harmful parameters and these sensors are connected to Arduino and data can be viewed on the smart phone through things speak App. PW is produced in large amounts and has a multifaceted composition, having various toxic organic and inorganic mixes. Currently PW is treated in conventional ways such as multiphase separators, cyclones, and coarse filters to meets the existing regulation for discharge. Therefore, these treatment ways do not achieve more restrictive limitations to dispose or reuse the PW. Drilling waste is composed of Polynuclear Aromatic Hydrocarbon (PAH), Aliphatic Hydrocarbon, and heavy metals such as barium, chromium, cadmium, lead, strontium, mercury, lead, zinc, manganese, arsenic, copper, and Iron which are toxic to the surrounding environment. Toxic materials, which can threat the environment, such as Sulphide reducing microorganism and bentonite and barite reduce plant growth. The toxicity of PW waste can be decreased when properly treated before disposing into the surrounding environment. Studies in some area of Mediterranean region have displayed high level of some heavy metals associated with PW and drilling waste with concentrations higher than world health organization (WHO) standard; these have harmful impact on the regional environment.
{"title":"Detecting Harmful Parameters of Produced Water and Drilling Waste from Smart Phone Through Things Speak App: Case Study from the Mediterranean Region","authors":"Z. Khan, T. Ganat, Juhairi Aris, S. Ridha","doi":"10.1109/ICGHIT.2019.00038","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00038","url":null,"abstract":"Discharge of produced water (PW) and drilling wastes from oil and gas industry has a major impact to the flora and fauna. The purpose of this study is to investigate the PW impact on the Mediterranean region and to provide alternative ways to detect the harmful parameters present in the produced water and drilling waste. Study shows the PW and drilling waste analysis in lab and it shows the idea of using smart phone to know all the harmful parameters. Varies sensors are connected to water to detect the harmful parameters and these sensors are connected to Arduino and data can be viewed on the smart phone through things speak App. PW is produced in large amounts and has a multifaceted composition, having various toxic organic and inorganic mixes. Currently PW is treated in conventional ways such as multiphase separators, cyclones, and coarse filters to meets the existing regulation for discharge. Therefore, these treatment ways do not achieve more restrictive limitations to dispose or reuse the PW. Drilling waste is composed of Polynuclear Aromatic Hydrocarbon (PAH), Aliphatic Hydrocarbon, and heavy metals such as barium, chromium, cadmium, lead, strontium, mercury, lead, zinc, manganese, arsenic, copper, and Iron which are toxic to the surrounding environment. Toxic materials, which can threat the environment, such as Sulphide reducing microorganism and bentonite and barite reduce plant growth. The toxicity of PW waste can be decreased when properly treated before disposing into the surrounding environment. Studies in some area of Mediterranean region have displayed high level of some heavy metals associated with PW and drilling waste with concentrations higher than world health organization (WHO) standard; these have harmful impact on the regional environment.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116002778","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00011
Kennedy Edemacu, Jong Wook Kim, Beakcheol Jang, H. Park
Extinction of wildlife animals is one of the well-documented problems the world is battling with currently. Africa which harbors a good number of these species is one of the regions most hit by this problem. To a greater extent, this is due to the continuous poaching practices in various African countries. The emergency of Internet-of-Things (IoT) technology has had a number of promising solutions to problems in many areas such as; environmental monitoring, traffic monitoring, smart health, waste management, e.t.c. Thus in this work, we design an IoT framework to curb the poaching practice in Africa. To improve the effectiveness of our system, we integrate a machine learning model to perform image analysis and classification task for the poacher detection purpose. A trial implementation of the framework is carried out and the results show a significant potential of IoT being used to enhance surveillance in game parks and reserves and hence, control the poaching problem.
{"title":"Poacher Detection in African Game Parks and Reserves with IoT: Machine Learning Approach","authors":"Kennedy Edemacu, Jong Wook Kim, Beakcheol Jang, H. Park","doi":"10.1109/ICGHIT.2019.00011","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00011","url":null,"abstract":"Extinction of wildlife animals is one of the well-documented problems the world is battling with currently. Africa which harbors a good number of these species is one of the regions most hit by this problem. To a greater extent, this is due to the continuous poaching practices in various African countries. The emergency of Internet-of-Things (IoT) technology has had a number of promising solutions to problems in many areas such as; environmental monitoring, traffic monitoring, smart health, waste management, e.t.c. Thus in this work, we design an IoT framework to curb the poaching practice in Africa. To improve the effectiveness of our system, we integrate a machine learning model to perform image analysis and classification task for the poacher detection purpose. A trial implementation of the framework is carried out and the results show a significant potential of IoT being used to enhance surveillance in game parks and reserves and hence, control the poaching problem.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121758162","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00018
Yongwoon Hwang, Doyoung Choi, Huicheol An, Seokjoo Shin, Chung-Ghiu Lee
This paper reports on the results of a developing Python-MATLAB interface program to implement optical wireless communication system simulation. We implement Python interface for entering input values and simulation environment variables for MATLAB. We operate MATLAB to numerical computing process about communication system simulation to generate a signal, to approximate channel characteristics and to recover the signal. Python passes input data and environment variables to MATLAB and displays output data and graphs from the simulation after MATLAB numerical computing.
{"title":"Development of Python-MATLAB Interface Program for Optical Communication System Simulation","authors":"Yongwoon Hwang, Doyoung Choi, Huicheol An, Seokjoo Shin, Chung-Ghiu Lee","doi":"10.1109/ICGHIT.2019.00018","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00018","url":null,"abstract":"This paper reports on the results of a developing Python-MATLAB interface program to implement optical wireless communication system simulation. We implement Python interface for entering input values and simulation environment variables for MATLAB. We operate MATLAB to numerical computing process about communication system simulation to generate a signal, to approximate channel characteristics and to recover the signal. Python passes input data and environment variables to MATLAB and displays output data and graphs from the simulation after MATLAB numerical computing.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133650552","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}
Pub Date : 2019-01-01DOI: 10.1109/ICGHIT.2019.00014
Jacqueline Lee Fang Ang, W. Lee, B. Ooi
The inaccuracy of the Global Positioning System (GPS) in indoor has sparked many researchers to advance into the development of Indoor Positioning System (IPS). However, from our literature review, one major problem is to compare the positioning accuracy of different approaches. Existing positioning accuracy from most of the existing works was evaluated in vastly different ways, using different test environments and there is no standard way to measure which makes comparison among different IPS a very challenging issue. Therefore, in this paper, a novel method for measuring and comparing the effectiveness of various IPS through a modelling technique is proposed, which is referred to as the GreyZone model. It is a model that is easy to understand and provides abstraction to the test environments and most important of all, various IPS approaches are comparable. To show the effectiveness of the model, several IPS approaches from existing works are evaluated. The differences between these indoor positioning approaches become apparent and subsequently comparable.
{"title":"GreyZone: A Novel Method for Measuring and Comparing Various Indoor Positioning Systems","authors":"Jacqueline Lee Fang Ang, W. Lee, B. Ooi","doi":"10.1109/ICGHIT.2019.00014","DOIUrl":"https://doi.org/10.1109/ICGHIT.2019.00014","url":null,"abstract":"The inaccuracy of the Global Positioning System (GPS) in indoor has sparked many researchers to advance into the development of Indoor Positioning System (IPS). However, from our literature review, one major problem is to compare the positioning accuracy of different approaches. Existing positioning accuracy from most of the existing works was evaluated in vastly different ways, using different test environments and there is no standard way to measure which makes comparison among different IPS a very challenging issue. Therefore, in this paper, a novel method for measuring and comparing the effectiveness of various IPS through a modelling technique is proposed, which is referred to as the GreyZone model. It is a model that is easy to understand and provides abstraction to the test environments and most important of all, various IPS approaches are comparable. To show the effectiveness of the model, several IPS approaches from existing works are evaluated. The differences between these indoor positioning approaches become apparent and subsequently comparable.","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122696629","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}
Pub Date : 2019-01-01DOI: 10.1109/icghit.2019.00001
{"title":"[Title page i]","authors":"","doi":"10.1109/icghit.2019.00001","DOIUrl":"https://doi.org/10.1109/icghit.2019.00001","url":null,"abstract":"","PeriodicalId":160708,"journal":{"name":"2019 International Conference on Green and Human Information Technology (ICGHIT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122117385","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：