Pub Date : 2017-03-08DOI: 10.1109/IEECON.2017.8075728
K. Janprom, S. Wangnippanto, W. Permpoonsinsup
In order to maintain a constant of temperature, the indoor climate is commonly controlled by air conditioning systems to keep occupants comfortable room in buildings. To achieve this issue, the control systems have applied to adaptable parameters to control the indoor climatic conditions. In this paper, PID (Proportional, Integral, Derivative) control logic is used to control the temperature. Embedded control system with PID controller and implementing in dSPACE is designed to minimize the oscillation effect within a range of 17°C–45°C. The result shows that the greater difference between setting temperature and observed temperature is steady state error less than 0.5°C. As a result, the designed system can be used to control and maintain an accurate indoor temperature.
{"title":"Embedded control system with PID controller for comfortable room","authors":"K. Janprom, S. Wangnippanto, W. Permpoonsinsup","doi":"10.1109/IEECON.2017.8075728","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075728","url":null,"abstract":"In order to maintain a constant of temperature, the indoor climate is commonly controlled by air conditioning systems to keep occupants comfortable room in buildings. To achieve this issue, the control systems have applied to adaptable parameters to control the indoor climatic conditions. In this paper, PID (Proportional, Integral, Derivative) control logic is used to control the temperature. Embedded control system with PID controller and implementing in dSPACE is designed to minimize the oscillation effect within a range of 17°C–45°C. The result shows that the greater difference between setting temperature and observed temperature is steady state error less than 0.5°C. As a result, the designed system can be used to control and maintain an accurate indoor temperature.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127049107","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075723
Kazuki Hanabusa, K. Higuchi, T. Kajikawa, S. Premrudeepreechacharn, K. Jirasereeamornkul
In late years a class-D amplifier has been used for a vibration generator and IGBT is often used for the switching element of the class-D amplifier. However, since the switching frequency of IGBT is limited low, it is difficult to make the bandwidth of the class-D amplifier wide. The bandwidth 5 kHz is required by the amplifier for the vibration generator with load impedance 2∼8 Ω. In this paper, it is shown that the bandwidth 5 kHz of the class-D amplifier can be realized by applying A2DOF control with the switching frequency 50 kHz. Since the output PWM frequency of a bridge circuit increase twice as much as IGBT switching frequency by using a double carrier PWM generating system, the sampling frequency of a controller can be increased twice as much as the switching frequency, i.e. is 100 kHz. Then the bandwidth 5 kHz of the class-D amplifier for the vibration generator with load impedance 2∼8 Ω can be realized by devising how to design A2DOF control. The controller is implemented in a DSP and it is shown from experiment that the desired performance is attained enough.
{"title":"Robust digital control of a class-D amplifier with low switching frequency for vibration generator","authors":"Kazuki Hanabusa, K. Higuchi, T. Kajikawa, S. Premrudeepreechacharn, K. Jirasereeamornkul","doi":"10.1109/IEECON.2017.8075723","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075723","url":null,"abstract":"In late years a class-D amplifier has been used for a vibration generator and IGBT is often used for the switching element of the class-D amplifier. However, since the switching frequency of IGBT is limited low, it is difficult to make the bandwidth of the class-D amplifier wide. The bandwidth 5 kHz is required by the amplifier for the vibration generator with load impedance 2∼8 Ω. In this paper, it is shown that the bandwidth 5 kHz of the class-D amplifier can be realized by applying A2DOF control with the switching frequency 50 kHz. Since the output PWM frequency of a bridge circuit increase twice as much as IGBT switching frequency by using a double carrier PWM generating system, the sampling frequency of a controller can be increased twice as much as the switching frequency, i.e. is 100 kHz. Then the bandwidth 5 kHz of the class-D amplifier for the vibration generator with load impedance 2∼8 Ω can be realized by devising how to design A2DOF control. The controller is implemented in a DSP and it is shown from experiment that the desired performance is attained enough.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"461 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120994527","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075832
S. Duangsuwan, P. Jamjareegulgarn
The massive MIMO technique has played the most important role in 5G wireless communication. It is anticipated that the new techniques employed in massive MIMO will not only improve peak service data rates significantly, but also enhance capacity, coverage, low-latency, efficiency flexibility, compatibility and convergence, thus meeting the focusing demands imposed by optimal detection. This paper presents the optimal detection of data symbol in massive MIMO for 5G wireless communication. Based on the frequency non-selective fading MIMO channel, we consider three difference detectors for recovering the transmitted data symbols and evaluate their performance for Rayleigh fading and additive white Gaussian noise (AWGN). At the results, we show that the probability of error rate (PER) performance of the detectors are significantly discussed.
{"title":"Detection of data symbol in a Massive MIMO systems for 5G wireless communication","authors":"S. Duangsuwan, P. Jamjareegulgarn","doi":"10.1109/IEECON.2017.8075832","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075832","url":null,"abstract":"The massive MIMO technique has played the most important role in 5G wireless communication. It is anticipated that the new techniques employed in massive MIMO will not only improve peak service data rates significantly, but also enhance capacity, coverage, low-latency, efficiency flexibility, compatibility and convergence, thus meeting the focusing demands imposed by optimal detection. This paper presents the optimal detection of data symbol in massive MIMO for 5G wireless communication. Based on the frequency non-selective fading MIMO channel, we consider three difference detectors for recovering the transmitted data symbols and evaluate their performance for Rayleigh fading and additive white Gaussian noise (AWGN). At the results, we show that the probability of error rate (PER) performance of the detectors are significantly discussed.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125381695","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075745
Chavaree Thueanpangthaim, Patumporn Wongyai, Kongpan Areerak, K. Areerak
This paper presents the maximum power point tracking for stand-alone photovoltaic system using current based technique. This method mitigates the disadvantage of conventional perturb and observe (P&O) technique in term of both transient and steady-state responses. The simulation results show that the proposed current based MPPT technique can provide the maximum power point value closed to the corresponding maximum power of photovoltaic for each irradiance. Both transient and steady state responses are better than those of conventional P&O technique.
{"title":"The maximum power point tracking for stand-alone photovoltaic system using current based approach","authors":"Chavaree Thueanpangthaim, Patumporn Wongyai, Kongpan Areerak, K. Areerak","doi":"10.1109/IEECON.2017.8075745","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075745","url":null,"abstract":"This paper presents the maximum power point tracking for stand-alone photovoltaic system using current based technique. This method mitigates the disadvantage of conventional perturb and observe (P&O) technique in term of both transient and steady-state responses. The simulation results show that the proposed current based MPPT technique can provide the maximum power point value closed to the corresponding maximum power of photovoltaic for each irradiance. Both transient and steady state responses are better than those of conventional P&O technique.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126740402","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075871
Nattakoon Meengoen, B. Wongkittisuksa, Sawit Tanthanuch
To verification of concept, a spectroscopic method for measurement of pH in human blood through the syringe based on backpropagation artificial neural network (BP-ANN). In this paper the feasibility of design and fabricate measurement of pH was consist of 5LEDs as light source, 2 photodiodes as sensor to measure the light intensity and calculate the blood pH. The spectral data of 48 subjects were measured. Principal component analysis (PCA) was applied to deduct the dimensional of collected spectral data to reduce the infestation of redundant data. In such cases, the principal component analysis has taken as inputs of BP-ANN to correlate and predict blood pH. The calculated blood pH by BP-ANN with PCA is quite a desirable with standard error of 0.015 and 0.023 919 in validation and testing, correlations coefficient (R) 0.992 and 0.919 in validation and testing. Inspecting the accuracy of BP-ANN model results produce by statistical analysis with a relative analytical error all under 3% in validation, and testing. The results are proved that a good correlation between absorbance data with actual pH, and the model is in good agreement. Hence, the method of BP-ANN with PCA is a potential for the absorbance detection of pH in human blood through the syringe.
{"title":"Measurement study of human blood pH based on optical technique by back propagation artificial neural network","authors":"Nattakoon Meengoen, B. Wongkittisuksa, Sawit Tanthanuch","doi":"10.1109/IEECON.2017.8075871","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075871","url":null,"abstract":"To verification of concept, a spectroscopic method for measurement of pH in human blood through the syringe based on backpropagation artificial neural network (BP-ANN). In this paper the feasibility of design and fabricate measurement of pH was consist of 5LEDs as light source, 2 photodiodes as sensor to measure the light intensity and calculate the blood pH. The spectral data of 48 subjects were measured. Principal component analysis (PCA) was applied to deduct the dimensional of collected spectral data to reduce the infestation of redundant data. In such cases, the principal component analysis has taken as inputs of BP-ANN to correlate and predict blood pH. The calculated blood pH by BP-ANN with PCA is quite a desirable with standard error of 0.015 and 0.023 919 in validation and testing, correlations coefficient (R) 0.992 and 0.919 in validation and testing. Inspecting the accuracy of BP-ANN model results produce by statistical analysis with a relative analytical error all under 3% in validation, and testing. The results are proved that a good correlation between absorbance data with actual pH, and the model is in good agreement. Hence, the method of BP-ANN with PCA is a potential for the absorbance detection of pH in human blood through the syringe.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"58 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126948453","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075849
Ittiporn Nokyotin, S. Koonkarnkhai, W. Wongtrairat, T. Sopon
In this paper, we compare the performance of the generalized belief propagation detector and the layered generalized belief propagation detector with a Log-MAP algorithm and max algorithm for the message passing on the factor graph. Which message-passing sequential of the LGBP detector is used to update the nodes sequentially instead of simultaneously in the factor graph. The simulation results show the performance bit error rate of the LGBP detector with the Log-MAP algorithm and max algorithm achieve the gains of about 0.2 dB, respectively, at BER = 10−5 over the GBP detector on the bit patterned media recording system at areal density 2 Tbits/in2.
{"title":"Layered generalized belief propagation detection on BPMR system with multi-track processing","authors":"Ittiporn Nokyotin, S. Koonkarnkhai, W. Wongtrairat, T. Sopon","doi":"10.1109/IEECON.2017.8075849","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075849","url":null,"abstract":"In this paper, we compare the performance of the generalized belief propagation detector and the layered generalized belief propagation detector with a Log-MAP algorithm and max algorithm for the message passing on the factor graph. Which message-passing sequential of the LGBP detector is used to update the nodes sequentially instead of simultaneously in the factor graph. The simulation results show the performance bit error rate of the LGBP detector with the Log-MAP algorithm and max algorithm achieve the gains of about 0.2 dB, respectively, at BER = 10−5 over the GBP detector on the bit patterned media recording system at areal density 2 Tbits/in2.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123016511","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}
This research presents electrical signal waveforms analysis and classification by applying the principle and theory of ANFIS. The input data for training and testing the network were processed by using Fast Fourier Transform. There are three input variables and one output for the network. From the experiment to determine the number of nodes in the 1st layer in order to obtain the optimal Mean Square Errors for analyze signal, the ANFIS learning, training function, genfis1 and learning function, Hybrid were used. The experimental result found that the best model consisted of the number of nodes to 3 models are 3-(6 6 6)-1, 3-(7 7 7)-1 and 3-(4 5 6)-1 input nodes, hidden nodes and output node, respectively. The transfer functions for output layer were linear function. The optimal MSE of training process were 6.62E-09, 3.32E-09 and 3.02E-08. The MSE of the test were 7.19E-09, 3.21E-09 and 2.46E-08, respectively. This provides the optimal percentage of Efficiency Index in the testing process. It showed that the proposed ANFIS can be used in signal pattern recognition in order to analyze and classify between good and bad signals.
{"title":"Application of adaptive network-based fuzzy inference system with fast Fourier transform for waveform analysis and classification","authors":"Adisorn Kamlungpetch, Prajuab Inrawong, Wutthichai Sa-nga-ngam","doi":"10.1109/IEECON.2017.8075886","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075886","url":null,"abstract":"This research presents electrical signal waveforms analysis and classification by applying the principle and theory of ANFIS. The input data for training and testing the network were processed by using Fast Fourier Transform. There are three input variables and one output for the network. From the experiment to determine the number of nodes in the 1st layer in order to obtain the optimal Mean Square Errors for analyze signal, the ANFIS learning, training function, genfis1 and learning function, Hybrid were used. The experimental result found that the best model consisted of the number of nodes to 3 models are 3-(6 6 6)-1, 3-(7 7 7)-1 and 3-(4 5 6)-1 input nodes, hidden nodes and output node, respectively. The transfer functions for output layer were linear function. The optimal MSE of training process were 6.62E-09, 3.32E-09 and 3.02E-08. The MSE of the test were 7.19E-09, 3.21E-09 and 2.46E-08, respectively. This provides the optimal percentage of Efficiency Index in the testing process. It showed that the proposed ANFIS can be used in signal pattern recognition in order to analyze and classify between good and bad signals.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117305386","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075839
S. Biswas
This IEEE 802.15.4 comes upon the LR-WPAN family which has low cost low power and the devices are battery driven with several applications. Here we analyze the MAC layer performance of such networks which use slotted CSMA/CA channel access mechanism. Our analysis is based on a OPNET simulation model, designed under star topology with a PAN coordinator and n no of transmitting nodes. Simulation has been done for different MAC parameter settings and for different number of n. Impact of hidden node is also considered. We also analyze the probability of receiving packet with the variation of different parameters.
{"title":"Simulation model of beacon enabled 802.15.4 networks with OPNET modeler","authors":"S. Biswas","doi":"10.1109/IEECON.2017.8075839","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075839","url":null,"abstract":"This IEEE 802.15.4 comes upon the LR-WPAN family which has low cost low power and the devices are battery driven with several applications. Here we analyze the MAC layer performance of such networks which use slotted CSMA/CA channel access mechanism. Our analysis is based on a OPNET simulation model, designed under star topology with a PAN coordinator and n no of transmitting nodes. Simulation has been done for different MAC parameter settings and for different number of n. Impact of hidden node is also considered. We also analyze the probability of receiving packet with the variation of different parameters.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128327893","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075843
Surachai Tunsiri, S. Soysouvanh, S. Mitatha, P. Phongsanam, I. Muangsong
The multi-wavelength optical network security system generated by using an optical nonlinear material within the modified add-drop optical filter for network security is proposed. By using the dark-bright nonlinear pulse control, the optical multi-wavelength can be constructed and applied to securely transport within the network. The advantage is that the dark and bright nonlinear pair (components) can securely propagate for long distance without electromagnetic interference. In operation, the optical intensity from modified add-drop optical filter is established.
{"title":"Multi-wavelength optical network security generated by modified add-drop filter","authors":"Surachai Tunsiri, S. Soysouvanh, S. Mitatha, P. Phongsanam, I. Muangsong","doi":"10.1109/IEECON.2017.8075843","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075843","url":null,"abstract":"The multi-wavelength optical network security system generated by using an optical nonlinear material within the modified add-drop optical filter for network security is proposed. By using the dark-bright nonlinear pulse control, the optical multi-wavelength can be constructed and applied to securely transport within the network. The advantage is that the dark and bright nonlinear pair (components) can securely propagate for long distance without electromagnetic interference. In operation, the optical intensity from modified add-drop optical filter is established.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128638485","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 : 2017-03-01DOI: 10.1109/IEECON.2017.8075814
Kriangsak Palapanyakul, P. Siripongwutikorn
In a building office, an air-conditioning system is one of the systems that contributes most to the electrical energy expense. The ability to predict the short-term electrical energy consumption in an air-conditioning environment can provide valuable information in controlling electrical appliance usages so that the overall energy consumption can be kept at an acceptable level for most of the time. In this paper, we apply data mining techniques to the short-term prediction of energy consumption in air-conditioning rooms typically found in an office building. Energy consumption data and related variables in actual air-conditioning environments are collected, preprocessed, and fitted to three different models, including Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Bagged Decision Tree (BDT). Unlike previous works that use only temperature and humidity as predictors, we include additional factors such as room size and BTU of air-conditioning units to improve the prediction accuracy. Our results show that the highest accuracy is achieved by using the ANN model with all the predictors included.
{"title":"Prediction model of short-term electrical load in an air conditioning environment","authors":"Kriangsak Palapanyakul, P. Siripongwutikorn","doi":"10.1109/IEECON.2017.8075814","DOIUrl":"https://doi.org/10.1109/IEECON.2017.8075814","url":null,"abstract":"In a building office, an air-conditioning system is one of the systems that contributes most to the electrical energy expense. The ability to predict the short-term electrical energy consumption in an air-conditioning environment can provide valuable information in controlling electrical appliance usages so that the overall energy consumption can be kept at an acceptable level for most of the time. In this paper, we apply data mining techniques to the short-term prediction of energy consumption in air-conditioning rooms typically found in an office building. Energy consumption data and related variables in actual air-conditioning environments are collected, preprocessed, and fitted to three different models, including Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Bagged Decision Tree (BDT). Unlike previous works that use only temperature and humidity as predictors, we include additional factors such as room size and BTU of air-conditioning units to improve the prediction accuracy. Our results show that the highest accuracy is achieved by using the ANN model with all the predictors included.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129881524","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}
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