Pub Date : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388400
A. Żywica, M. Ziółkowski, S. Gratkowski
This paper is devoted to the problem of the Lorentz force density distribution determination in a system consisting of non-concentrically oriented single and double layer conducting spheres. It is assumed that a low-conductivity object is placed in both static and pulsed uniform magnetic fields. Closed-form expressions for eddy current density and the Lorentz force density vectors are derived and validated by the finite element method (FEM). The analytical expressions presented in this paper can be deployed for determining the efficiency of numerical procedures applied to more complex configurations used in MAT-MI forward problem calculation.
{"title":"Transient Lorentz force density distribution in a single and double layer conducting spheres","authors":"A. Żywica, M. Ziółkowski, S. Gratkowski","doi":"10.1109/IIPHDW.2018.8388400","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388400","url":null,"abstract":"This paper is devoted to the problem of the Lorentz force density distribution determination in a system consisting of non-concentrically oriented single and double layer conducting spheres. It is assumed that a low-conductivity object is placed in both static and pulsed uniform magnetic fields. Closed-form expressions for eddy current density and the Lorentz force density vectors are derived and validated by the finite element method (FEM). The analytical expressions presented in this paper can be deployed for determining the efficiency of numerical procedures applied to more complex configurations used in MAT-MI forward problem calculation.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115540399","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388395
T. Rymarczyk
The article presents the idea of a distributed system for industrial and medical tomography. The paper shows examples of reconstruction of images made by the author using various tomographic techniques and reconstruction algorithms. Depending on specific technological tomography, both advantages and disadvantages can be observed in terms of accuracy, frequency and resolution of reproduced images. Knowledge of the characteristics of each tomographic technique allows you to choose the appropriate method of image reconstruction. The proposed model of the cyber-physical system consists of a set of sensors, processing unit, Big Data cluster, algorithms for processing data in the cloud and data analysis and visualization.
{"title":"Distributed systems for acquisition and analysis of multi-source data in industrial and medical tomography","authors":"T. Rymarczyk","doi":"10.1109/IIPHDW.2018.8388395","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388395","url":null,"abstract":"The article presents the idea of a distributed system for industrial and medical tomography. The paper shows examples of reconstruction of images made by the author using various tomographic techniques and reconstruction algorithms. Depending on specific technological tomography, both advantages and disadvantages can be observed in terms of accuracy, frequency and resolution of reproduced images. Knowledge of the characteristics of each tomographic technique allows you to choose the appropriate method of image reconstruction. The proposed model of the cyber-physical system consists of a set of sensors, processing unit, Big Data cluster, algorithms for processing data in the cloud and data analysis and visualization.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117280725","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388375
Damian Faustryjak, L. Jackowska-Strumillo, M. Majchrowicz
The article presents a new approach that combines two separate fields of stock exchange analysis. The aim of proposed solution is to support investors in their decisions and recommend to buy the assets which provide the greatest profits. To achieve this goal, decisive algorithms have been developed using artificial neural networks and technical analysis, which were used along with statistics that refer to the occurrence of single words in the fundamental analysis. Based on this, a model was prepared that in response gives a recommendation for future increases. The system consists of two algorithms. The first of them uses the LSTM (Long Short-Term Memory) artificial neural network. As inputs, information about the current closing price as well as technical analysis indicators along with the value of the current volume were used. The output has been specified as the closing price on the following day. In order to improve the response from the ANN (Artificial Neural Network), statistics of the occurrence of words in publications from last week were used. Subsequent signals gained much more importance if the volume of all transactions was much larger than the moving average of the last 15 periods and if the words that appeared in the last publication caused earlier increases. Additional information for the system are also data that come from Google Trends. This allows to verify the trend of interest and whether the published messages are important.
{"title":"Forward forecast of stock prices using LSTM neural networks with statistical analysis of published messages","authors":"Damian Faustryjak, L. Jackowska-Strumillo, M. Majchrowicz","doi":"10.1109/IIPHDW.2018.8388375","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388375","url":null,"abstract":"The article presents a new approach that combines two separate fields of stock exchange analysis. The aim of proposed solution is to support investors in their decisions and recommend to buy the assets which provide the greatest profits. To achieve this goal, decisive algorithms have been developed using artificial neural networks and technical analysis, which were used along with statistics that refer to the occurrence of single words in the fundamental analysis. Based on this, a model was prepared that in response gives a recommendation for future increases. The system consists of two algorithms. The first of them uses the LSTM (Long Short-Term Memory) artificial neural network. As inputs, information about the current closing price as well as technical analysis indicators along with the value of the current volume were used. The output has been specified as the closing price on the following day. In order to improve the response from the ANN (Artificial Neural Network), statistics of the occurrence of words in publications from last week were used. Subsequent signals gained much more importance if the volume of all transactions was much larger than the moving average of the last 15 periods and if the words that appeared in the last publication caused earlier increases. Additional information for the system are also data that come from Google Trends. This allows to verify the trend of interest and whether the published messages are important.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133643079","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388381
Piotr Gas, B. Szymanik
Ablation is commonly used medical procedure for removal of liver tumors. It is minimally invasive technique that is based on the insertion of a thin needle antenna into malignant tissue and heating the region of interest by microwaves. The aim of this work is to optimize shape of a microwave antenna with 50-ohm feed and multiple air gaps. Fundamental sizes of cylindrical antenna should be changed, in particular dimensions of antenna slots and distances between them. Change of the geometry should be done in such a way as to obtain the best impedance matching of the antenna-tissue system. Therefore, 511-scattering parameter will be used in the objective function. Importantly, the antenna operates at working frequency equal to 2.45 GHz.
{"title":"Shape optimization of the multi-slot coaxial antenna for local hepatic heating during microwave ablation","authors":"Piotr Gas, B. Szymanik","doi":"10.1109/IIPHDW.2018.8388381","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388381","url":null,"abstract":"Ablation is commonly used medical procedure for removal of liver tumors. It is minimally invasive technique that is based on the insertion of a thin needle antenna into malignant tissue and heating the region of interest by microwaves. The aim of this work is to optimize shape of a microwave antenna with 50-ohm feed and multiple air gaps. Fundamental sizes of cylindrical antenna should be changed, in particular dimensions of antenna slots and distances between them. Change of the geometry should be done in such a way as to obtain the best impedance matching of the antenna-tissue system. Therefore, 511-scattering parameter will be used in the objective function. Importantly, the antenna operates at working frequency equal to 2.45 GHz.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278344","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388350
T. Rymarczyk, P. Adamkiewicz, E. Kozłowski
The highly correlated predictors with each other's in linear models do not allow to determine the precisely influences of these predictors on the output variable. Directly application the least square method to estimate the unknown parameters may lead to a poor prediction. The addition of penalty depending on quantities of parameters to the least square criterion allows us to determine the biased estimators but also to reduce the variance of estimators. The Least Angle Regression was used to reconstruct the image in electrical impedance tomography.
{"title":"Application of least angle regression methods for image reconstruction in EIT","authors":"T. Rymarczyk, P. Adamkiewicz, E. Kozłowski","doi":"10.1109/IIPHDW.2018.8388350","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388350","url":null,"abstract":"The highly correlated predictors with each other's in linear models do not allow to determine the precisely influences of these predictors on the output variable. Directly application the least square method to estimate the unknown parameters may lead to a poor prediction. The addition of penalty depending on quantities of parameters to the least square criterion allows us to determine the biased estimators but also to reduce the variance of estimators. The Least Angle Regression was used to reconstruct the image in electrical impedance tomography.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124847116","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388336
G. Psuj, Michal Maciusowicz
The application range of Barkhausen noise (BN) technique to nondestructive examination of steel condition or properties is constantly growing. However, the stochastic nature of Barkhausen's noise forces utilization of advanced data processing techniques to extract the knowledge allowing quantitative description of observed signals. Many factors can affect various properties of BN signals derived from time and frequency domain. Therefore, both modes should be considered during feature extraction process. In this paper, in order to combine the information provided in time and frequency regimes, a detailed analysis of time-frequency representation of Barkhausen noise signals allowing quantitative evaluation was carried out. The processing procedures were presented and utilized for estimation of damage progress of stress loaded steel samples. The results were shown and discussed.
{"title":"Analysis of time-frequency representation of Magnetic Barkhausen noise for the need of damage evaluation of steels elements","authors":"G. Psuj, Michal Maciusowicz","doi":"10.1109/IIPHDW.2018.8388336","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388336","url":null,"abstract":"The application range of Barkhausen noise (BN) technique to nondestructive examination of steel condition or properties is constantly growing. However, the stochastic nature of Barkhausen's noise forces utilization of advanced data processing techniques to extract the knowledge allowing quantitative description of observed signals. Many factors can affect various properties of BN signals derived from time and frequency domain. Therefore, both modes should be considered during feature extraction process. In this paper, in order to combine the information provided in time and frequency regimes, a detailed analysis of time-frequency representation of Barkhausen noise signals allowing quantitative evaluation was carried out. The processing procedures were presented and utilized for estimation of damage progress of stress loaded steel samples. The results were shown and discussed.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"14 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130224849","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388380
Gustaw Rzyman, G. Redlarski, Aleksander Palkowski, Piotr Tojza, M. Krawczuk, J. Siebert
Currently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for specific body parts. We have achieved satisfactory results for a wide range of patients. Using regression models, such as: support vector regression, multilayer perceptron regressor, stochastic gradient descent, or ridge regression, a fourfold decrease in errors proportion is achieved. Machine learning algorithms led to reduction from 1.2 to 8 times for mean estimation error.
{"title":"Computing methods for fast and precise body surface area estimation of selected body parts","authors":"Gustaw Rzyman, G. Redlarski, Aleksander Palkowski, Piotr Tojza, M. Krawczuk, J. Siebert","doi":"10.1109/IIPHDW.2018.8388380","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388380","url":null,"abstract":"Currently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for specific body parts. We have achieved satisfactory results for a wide range of patients. Using regression models, such as: support vector regression, multilayer perceptron regressor, stochastic gradient descent, or ridge regression, a fourfold decrease in errors proportion is achieved. Machine learning algorithms led to reduction from 1.2 to 8 times for mean estimation error.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129711036","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388370
Mateusz Perciński, M. Marcinkiewicz
This paper presents the architecture of the system of 1:10 scale autonomous car. It emphasizes how requirements-based approach was followed in project design phase not only to meet formal requirements of Carolo-Cup 2018 competition, but also to maximize vehicle performance. In competition events vehicles are supposed to operate in road-simulating environment, particularly to handle real-time navigation, static and dynamic obstacles avoiding, parking and following right of the road in intersections. In dynamic events quality of behavior and pace of performed actions are graded. Additional factors influencing final assessment are safety engineering, cost efficiency and knowledge management in team.
{"title":"Architecture of the system of 1:10 scale autonomous car — Requirements-based design and implementation","authors":"Mateusz Perciński, M. Marcinkiewicz","doi":"10.1109/IIPHDW.2018.8388370","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388370","url":null,"abstract":"This paper presents the architecture of the system of 1:10 scale autonomous car. It emphasizes how requirements-based approach was followed in project design phase not only to meet formal requirements of Carolo-Cup 2018 competition, but also to maximize vehicle performance. In competition events vehicles are supposed to operate in road-simulating environment, particularly to handle real-time navigation, static and dynamic obstacles avoiding, parking and following right of the road in intersections. In dynamic events quality of behavior and pace of performed actions are graded. Additional factors influencing final assessment are safety engineering, cost efficiency and knowledge management in team.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128850319","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388368
M. Panuszewska, B. Minch, W. Dzwinel
Even though the cancer mortality rate is slowly decreasing, it is still one of the leading causes of morbidity and mortality worldwide. One of the most common types of this disease is renal cancer, occurring in kidneys. A total of 63,340 new renal cancer cases (42,680 in men and 22,660 in women) and 14,970 deaths from renal cancer (10,010 men and 4,960 women) are projected to occur only in the US in 2018, with 1 in 48 lifetime risk for developing kidney cancer for men and 1 in 83 for women. Tumor growth is a complex, multiscale phenomena with many coupled microscopic and macroscopic factors that have to be accounted for while studying the disease. Despite a tremendous amount of work on understanding cancerogenesis and developing an effective anticancer therapies we still do not fully understand the mechanics of the malignant tissue development. Even though it is impossible to fully simulate and control cancer growth, numerical model allows for identification and investigation of the most crucial tumor growth factors and possible scenarios of its proliferation. The purpose of this article is to create model of renal tumor that uses the particle automata model[1,2]. We would also like to clarify if smooth particle hydrodynamics (SPH) method can be used to improve modelling of this particular biological process[3]. In the particle automata model both cancerous and healthy tissues are made of particles interacting with each other via spring harmonic forces and in SPH model we assume that biological tissues are represented as viscous fluids. In each model healthy tissue serves as an environment in which the renal tumor develops. Both healthy and cancerous cells have a life cycle in which they can be proliferating, dormant or necrotic. We use oxygen concentration, external pressure and time as restrictive factors for tissue growth. Herein we hope to reproduce in vivo tumor growth results inside in silico model and gain more insight into the rules governing the spread of the disease.
{"title":"Particle automata model of renal cancer progression","authors":"M. Panuszewska, B. Minch, W. Dzwinel","doi":"10.1109/IIPHDW.2018.8388368","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388368","url":null,"abstract":"Even though the cancer mortality rate is slowly decreasing, it is still one of the leading causes of morbidity and mortality worldwide. One of the most common types of this disease is renal cancer, occurring in kidneys. A total of 63,340 new renal cancer cases (42,680 in men and 22,660 in women) and 14,970 deaths from renal cancer (10,010 men and 4,960 women) are projected to occur only in the US in 2018, with 1 in 48 lifetime risk for developing kidney cancer for men and 1 in 83 for women. Tumor growth is a complex, multiscale phenomena with many coupled microscopic and macroscopic factors that have to be accounted for while studying the disease. Despite a tremendous amount of work on understanding cancerogenesis and developing an effective anticancer therapies we still do not fully understand the mechanics of the malignant tissue development. Even though it is impossible to fully simulate and control cancer growth, numerical model allows for identification and investigation of the most crucial tumor growth factors and possible scenarios of its proliferation. The purpose of this article is to create model of renal tumor that uses the particle automata model[1,2]. We would also like to clarify if smooth particle hydrodynamics (SPH) method can be used to improve modelling of this particular biological process[3]. In the particle automata model both cancerous and healthy tissues are made of particles interacting with each other via spring harmonic forces and in SPH model we assume that biological tissues are represented as viscous fluids. In each model healthy tissue serves as an environment in which the renal tumor develops. Both healthy and cancerous cells have a life cycle in which they can be proliferating, dormant or necrotic. We use oxygen concentration, external pressure and time as restrictive factors for tissue growth. Herein we hope to reproduce in vivo tumor growth results inside in silico model and gain more insight into the rules governing the spread of the disease.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126622149","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 : 2018-05-01DOI: 10.1109/IIPHDW.2018.8388355
T. Rymarczyk, K. Szulc
In this paper, mathematical methods based on level set method, shape and topological derivatives for solving inverse problems were presented in electrical impedance tomography. The topological derivative measures the sensitivity of the functional shape when the domain is disturbed by small inclusions, defects or cracks inside the tested object. The derivative of the shape, on the other hand, measures the sensitivity of the border perturbation. Combining the level set function, shape and topological derivative, we get an algorithm that is more flexible in shape change and is less sensitive to the local minimum.
{"title":"Solving inverse problem for electrical impedance tomography using topological derivative and level set method","authors":"T. Rymarczyk, K. Szulc","doi":"10.1109/IIPHDW.2018.8388355","DOIUrl":"https://doi.org/10.1109/IIPHDW.2018.8388355","url":null,"abstract":"In this paper, mathematical methods based on level set method, shape and topological derivatives for solving inverse problems were presented in electrical impedance tomography. The topological derivative measures the sensitivity of the functional shape when the domain is disturbed by small inclusions, defects or cracks inside the tested object. The derivative of the shape, on the other hand, measures the sensitivity of the border perturbation. Combining the level set function, shape and topological derivative, we get an algorithm that is more flexible in shape change and is less sensitive to the local minimum.","PeriodicalId":405270,"journal":{"name":"2018 International Interdisciplinary PhD Workshop (IIPhDW)","volume":"47 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125883623","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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