Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068180
A. Elkorany, Rehab M. Helmy, A. Saleeb, N. Areed
An EBG is designed at the ground plane of a pentagon microstrip patch antenna for detecting brain tumors. Two circular EBG types have been introduced. The first type is a rectangular lattice of holes which produced an increase in S11 by 19% at the same resonance frequency which is 3.9 GHz with and without tumor. The second one is a squared lattice of holes that presented an increase of 27 % in S11. It also provides a 2.9% shift in the resonant frequency at −10 dB on a head phantom with a brain tumor compared to without a tumor. The electric field, magnetic field, and current density are calculated in each type of EBG. A remarkable difference has been observed between with and without tumor especially on the squared lattice. One-, two-and four- elements linear antenna arrays are designed to be put at a 10-mm distance from the head phantom. The purpose of antenna arrays is to provide sufficient energy to penetrate human tissues. The directivity was increased as 6.65 dB, 8.5 dB, and 12 dB in one element, two elements, and four elements respectively. The S11 is calculated for each antenna on a head phantom with and without tumor. The S11 values are increased by 1.05dB, 2.73dB, and 4dB for the three cases respectively. Finally, the E and H fields, current density and specific absorption rate SAR are also calculated.
{"title":"Microstrip Patch Antenna Linear Arrays for Brain Tumor Detection","authors":"A. Elkorany, Rehab M. Helmy, A. Saleeb, N. Areed","doi":"10.1109/ICCES48960.2019.9068180","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068180","url":null,"abstract":"An EBG is designed at the ground plane of a pentagon microstrip patch antenna for detecting brain tumors. Two circular EBG types have been introduced. The first type is a rectangular lattice of holes which produced an increase in S11 by 19% at the same resonance frequency which is 3.9 GHz with and without tumor. The second one is a squared lattice of holes that presented an increase of 27 % in S11. It also provides a 2.9% shift in the resonant frequency at −10 dB on a head phantom with a brain tumor compared to without a tumor. The electric field, magnetic field, and current density are calculated in each type of EBG. A remarkable difference has been observed between with and without tumor especially on the squared lattice. One-, two-and four- elements linear antenna arrays are designed to be put at a 10-mm distance from the head phantom. The purpose of antenna arrays is to provide sufficient energy to penetrate human tissues. The directivity was increased as 6.65 dB, 8.5 dB, and 12 dB in one element, two elements, and four elements respectively. The S11 is calculated for each antenna on a head phantom with and without tumor. The S11 values are increased by 1.05dB, 2.73dB, and 4dB for the three cases respectively. Finally, the E and H fields, current density and specific absorption rate SAR are also calculated.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"249 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115005531","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068161
Lamiaa M. Elshenawy
Multivariate statistical process monitoring techniques have been developed to detect and isolate abnormal situations of modern industrial processes that became more complicated and are classified as large-scale systems. Several fault detection and isolation indices have been proposed for multivariate statistical process monitoring. This paper discusses these indices and compare their performances by applying for an industrial benchmark, the Tennessee Eastman chemical process. The efficiency of these indices is measured by four key performance indicators (KPIs), i.e., fault detection time delay, false alarm rate, missed detection rate, correct fault isolation.
{"title":"Fault Detection and Isolation Indices for Large-Scale Systems","authors":"Lamiaa M. Elshenawy","doi":"10.1109/ICCES48960.2019.9068161","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068161","url":null,"abstract":"Multivariate statistical process monitoring techniques have been developed to detect and isolate abnormal situations of modern industrial processes that became more complicated and are classified as large-scale systems. Several fault detection and isolation indices have been proposed for multivariate statistical process monitoring. This paper discusses these indices and compare their performances by applying for an industrial benchmark, the Tennessee Eastman chemical process. The efficiency of these indices is measured by four key performance indicators (KPIs), i.e., fault detection time delay, false alarm rate, missed detection rate, correct fault isolation.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123220196","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068152
Neveen M. Hussein, A. Hesham, Mohsen A. Rashawn
This paper presents Nonintrusive Load Monitoring (NILM) for electrical home appliances network which consists of a known set of devices. Hidden Markov Model (HMM) is used for system modeling. The proposed method enhances determining and defining all states for each device. First we classify each device states into a set of states not only the ON and OFF states in the form of variations in its active power ranges. AMPDS collected dataset is used in training and testing for six selected home devices in a certain household and is also compared to GREEND dataset showing the advantage of the variable observed power readings with those of constant power readings. Each device has different number of states. Then the proposed mechanism is used to minimize these states after understanding the behavior of each state into OFF and ON states only. This method provides high accuracy on the system level, the device level, state inference, power and state sequence estimation.
{"title":"States and Power Consumption Estimation for NILM","authors":"Neveen M. Hussein, A. Hesham, Mohsen A. Rashawn","doi":"10.1109/ICCES48960.2019.9068152","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068152","url":null,"abstract":"This paper presents Nonintrusive Load Monitoring (NILM) for electrical home appliances network which consists of a known set of devices. Hidden Markov Model (HMM) is used for system modeling. The proposed method enhances determining and defining all states for each device. First we classify each device states into a set of states not only the ON and OFF states in the form of variations in its active power ranges. AMPDS collected dataset is used in training and testing for six selected home devices in a certain household and is also compared to GREEND dataset showing the advantage of the variable observed power readings with those of constant power readings. Each device has different number of states. Then the proposed mechanism is used to minimize these states after understanding the behavior of each state into OFF and ON states only. This method provides high accuracy on the system level, the device level, state inference, power and state sequence estimation.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128064807","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068170
Diaa A. Noby, Ahmed K. F. Khattab
This paper presents an extensive study of the different ways the Internet of Things (IoT) applications exploit the recently developed blockchain technology. Even though the blockchain technology was originally presented as a security mechanism, its numerous benefits such as decentralization, immutability, persistence, anonymity and auditability can be used by IoT systems in different ways. More specifically, we classify the ways IoT systems exploit blockchain into three categories: resource management, decentralized information sharing, and IoT security. The comprehensive study of the applications of the blockchain technology in the different IoT domains presented in this paper sheds the light on the future research directions in the integration of the two technologies.
{"title":"A Survey of Blockchain Applications in IoT Systems","authors":"Diaa A. Noby, Ahmed K. F. Khattab","doi":"10.1109/ICCES48960.2019.9068170","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068170","url":null,"abstract":"This paper presents an extensive study of the different ways the Internet of Things (IoT) applications exploit the recently developed blockchain technology. Even though the blockchain technology was originally presented as a security mechanism, its numerous benefits such as decentralization, immutability, persistence, anonymity and auditability can be used by IoT systems in different ways. More specifically, we classify the ways IoT systems exploit blockchain into three categories: resource management, decentralized information sharing, and IoT security. The comprehensive study of the applications of the blockchain technology in the different IoT domains presented in this paper sheds the light on the future research directions in the integration of the two technologies.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131417125","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068151
Mohamed M. Ahmed, Hassan Bedour, S. M. Hassan
Due to the vast developments in the media communication field and the quality of the visual imaging, image data compression has been one of the most interesting field. The main purpose of the image compression is to produce a very low bit rate while achieving a high quality of the reconstructed images. Image compression are used for all fields of media communication such as medical image recognition, multimedia, digital image processing. There are different algorithms for compression and reconstruction. One of these methods is the Orthogonal Matching Pursuit that is used mainly in the reconstruction of the radar signal. This paper discloses a new methodology for image compression and reconstruction to enhance the performance while at the same time reducing the bit data size. This kind of reconstruction algorithm is based upon multistage compression and OMP reconstruction. The Matlab Simulation and the FPGA implementation will be provided in this paper to validate the concept of this paper.
{"title":"Design and Implementation of a Multistage Image Compression and Reconstruction System Based on the Orthogonal Matching Pursuit Using FPGA","authors":"Mohamed M. Ahmed, Hassan Bedour, S. M. Hassan","doi":"10.1109/ICCES48960.2019.9068151","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068151","url":null,"abstract":"Due to the vast developments in the media communication field and the quality of the visual imaging, image data compression has been one of the most interesting field. The main purpose of the image compression is to produce a very low bit rate while achieving a high quality of the reconstructed images. Image compression are used for all fields of media communication such as medical image recognition, multimedia, digital image processing. There are different algorithms for compression and reconstruction. One of these methods is the Orthogonal Matching Pursuit that is used mainly in the reconstruction of the radar signal. This paper discloses a new methodology for image compression and reconstruction to enhance the performance while at the same time reducing the bit data size. This kind of reconstruction algorithm is based upon multistage compression and OMP reconstruction. The Matlab Simulation and the FPGA implementation will be provided in this paper to validate the concept of this paper.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116831883","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068132
Fatma Mohamad, Khaled Hosny, T. Barakat
Power transformer is an essential part in any power plant, so continuous check of its reliability should be kept up. Dissolved Gas Analysis (DGA) is one of the most important techniques for detecting incipient faults of transformer that immersed in insulation oil. Some widely used conventional techniques based on DGA such as Roger's and IEC methods were developed to diagnose faults of power transformers. These methods succeeded noticeably to detect transformer's faults. However, they fail to detect the fault type if the measured ratios of gases slightly deviated from the crisp boundaries of ranges assigned by these methods. An Artificial Intelligent technique based method called fuzzy logic approach, which is the field of study in this paper is used to overcome the above mentioned drawback by fuzzifying the boundaries of ranges defined by these techniques. This paper presents a comparison between the results of conventional Roger's, IEC methods and the proposed fuzzy logic.
{"title":"Incipient Fault Detection of Electric Power Transformers Using Fuzzy Logic Based on Roger's and IEC Method","authors":"Fatma Mohamad, Khaled Hosny, T. Barakat","doi":"10.1109/ICCES48960.2019.9068132","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068132","url":null,"abstract":"Power transformer is an essential part in any power plant, so continuous check of its reliability should be kept up. Dissolved Gas Analysis (DGA) is one of the most important techniques for detecting incipient faults of transformer that immersed in insulation oil. Some widely used conventional techniques based on DGA such as Roger's and IEC methods were developed to diagnose faults of power transformers. These methods succeeded noticeably to detect transformer's faults. However, they fail to detect the fault type if the measured ratios of gases slightly deviated from the crisp boundaries of ranges assigned by these methods. An Artificial Intelligent technique based method called fuzzy logic approach, which is the field of study in this paper is used to overcome the above mentioned drawback by fuzzifying the boundaries of ranges defined by these techniques. This paper presents a comparison between the results of conventional Roger's, IEC methods and the proposed fuzzy logic.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116719121","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 : 2019-12-01DOI: 10.1109/icces48960.2019.9068127
Ashraf Salem, H. Abbas, M. El-Kharashi, Ayman M. Bahaa El-Din, Mohamad Taher
{"title":"Proceedings ICCES 2019 14th International Conference on Computer Engineering and Systems (ICCES)","authors":"Ashraf Salem, H. Abbas, M. El-Kharashi, Ayman M. Bahaa El-Din, Mohamad Taher","doi":"10.1109/icces48960.2019.9068127","DOIUrl":"https://doi.org/10.1109/icces48960.2019.9068127","url":null,"abstract":"","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"320 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121838937","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068125
Ahmed F. AbouElhamayed, Hani M. K. Mahdi, Cherif R. Salama
Solving the traffic congestion problem has many benefits financially and environmentally. The application of Artificial Intelligence to solving the traffic congestion problem has been going on for a while. However, most of the current research in this area depends on knowing lots of information about all vehicles in the network. While it produces promising results, applying these techniques in the current world is not easy. In this paper, we apply reinforcement learning to the field of traffic control under the assumption that only minimal information is available. Our approach produces results that are better than currently deployed fixed-time traffic lights without having heavy requirements. In our first test configuration, our agent's waiting time is 82.3% of the best fixed-time traffic lights' waiting time and the average CO2 emissions produced by our agent is 97.5% of the emissions produced by the best fixed-time traffic lights. This shows the potential of applying reinforcement learning to the traffic control problem with limited state.
{"title":"Low-Cost Traffic Control using Reinforcement Learning","authors":"Ahmed F. AbouElhamayed, Hani M. K. Mahdi, Cherif R. Salama","doi":"10.1109/ICCES48960.2019.9068125","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068125","url":null,"abstract":"Solving the traffic congestion problem has many benefits financially and environmentally. The application of Artificial Intelligence to solving the traffic congestion problem has been going on for a while. However, most of the current research in this area depends on knowing lots of information about all vehicles in the network. While it produces promising results, applying these techniques in the current world is not easy. In this paper, we apply reinforcement learning to the field of traffic control under the assumption that only minimal information is available. Our approach produces results that are better than currently deployed fixed-time traffic lights without having heavy requirements. In our first test configuration, our agent's waiting time is 82.3% of the best fixed-time traffic lights' waiting time and the average CO2 emissions produced by our agent is 97.5% of the emissions produced by the best fixed-time traffic lights. This shows the potential of applying reinforcement learning to the traffic control problem with limited state.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121857293","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068171
Amr M. Zaki, M. Khalil, Hazem M. Abbas
Abstractive text summarization is the task of generating a novel summary given an article, not by merely extracting and selecting text to produce a summary, but by actually creating and understating the given text to produce a summary. LSTM seq2seq encoder-decoder with attention models have proved successful in this task, but they suffer from some problems. In this work, we would go through multiple models to try and solve these problems, beginning with simple seq2seq with attention models to going to Pointer-Generator, to using a curriculum learning approach called Scheduled-Sampling, till we reach the new approaches of combining reinforcement learning with seq2seq. We have applied these models on multiple datasets for multiple languages, English and Arabic. We have also introduced a new novel method of working with agglutinative languages, it is a preprocessing technique that is applied to the dataset which increases the relevancy of the vocabulary, which effectively increases the efficiency of the text summarization without modifying the models, we call this technique advanced cleaning, we have applied it to the Arabic dataset, and it can then be applied to any other agglutinative language. We have built these models in Jupiter notebooks to run seamlessly on Google colaboratory.11https://medium.com/@theamrzaki22https://github.com/theamrzaki/text_summurization_abstractive_methods
{"title":"Deep Architectures for Abstractive Text Summarization in Multiple Languages","authors":"Amr M. Zaki, M. Khalil, Hazem M. Abbas","doi":"10.1109/ICCES48960.2019.9068171","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068171","url":null,"abstract":"Abstractive text summarization is the task of generating a novel summary given an article, not by merely extracting and selecting text to produce a summary, but by actually creating and understating the given text to produce a summary. LSTM seq2seq encoder-decoder with attention models have proved successful in this task, but they suffer from some problems. In this work, we would go through multiple models to try and solve these problems, beginning with simple seq2seq with attention models to going to Pointer-Generator, to using a curriculum learning approach called Scheduled-Sampling, till we reach the new approaches of combining reinforcement learning with seq2seq. We have applied these models on multiple datasets for multiple languages, English and Arabic. We have also introduced a new novel method of working with agglutinative languages, it is a preprocessing technique that is applied to the dataset which increases the relevancy of the vocabulary, which effectively increases the efficiency of the text summarization without modifying the models, we call this technique advanced cleaning, we have applied it to the Arabic dataset, and it can then be applied to any other agglutinative language. We have built these models in Jupiter notebooks to run seamlessly on Google colaboratory.11https://medium.com/@theamrzaki22https://github.com/theamrzaki/text_summurization_abstractive_methods","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131546681","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 : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068159
Marianne A. Azer, A. Elshafee
This research focuses on using quantifiable methods for using the IoT as a main support to firefighting/intruder detection. From our research, we have found numerous researches associated to supplying remote services by means of portable sensors and communication technologies. We represent in our research a unique Smart Firefighting/lntruder Detection System with the support of Fuzzy Logic Decision Control (FIDFUZ). The projected system has an innovative value which is the Fuzzy Logic Decision Support System application that deals with the predicted inaccuracy and the doubt in the sensor's information acquired, as well as minimizing the rate of false positive and true negative. FIDFUZ full architecture is presented, applied and checked by simulation and using real data.
{"title":"Design and Implementation of Robust Firefighting/Intruder Detection System Using Fuzzy Logic Decision Control (FIDFUZ)","authors":"Marianne A. Azer, A. Elshafee","doi":"10.1109/ICCES48960.2019.9068159","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068159","url":null,"abstract":"This research focuses on using quantifiable methods for using the IoT as a main support to firefighting/intruder detection. From our research, we have found numerous researches associated to supplying remote services by means of portable sensors and communication technologies. We represent in our research a unique Smart Firefighting/lntruder Detection System with the support of Fuzzy Logic Decision Control (FIDFUZ). The projected system has an innovative value which is the Fuzzy Logic Decision Support System application that deals with the predicted inaccuracy and the doubt in the sensor's information acquired, as well as minimizing the rate of false positive and true negative. FIDFUZ full architecture is presented, applied and checked by simulation and using real data.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128330582","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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