Abstract With ReRAM being a non-volative memory technology, which features low power consumption, high scalability and allows for in-memory computing, it is a promising candidate for future computer architectures. Approximate computing is a design paradigm, which aims at reducing the complexity of hardware by trading off accuracy for area and/or delay. In this article, we introduce approximate computing techniques to in-memory computing. We extend existing compilation techniques for the Programmable Logic in-Memory (PLiM) computer architecture, by adapting state-of-the-art approximate computing techniques for arithmetic circuits. We use Cartesian Genetic Programming for the generation of approximate circuits and evaluate them using a Symbolic Computer Algebra-based technique with respect to error-metrics. In our experiments, we show that we can outperform state-of-the-art handcrafted approximate adder designs.
{"title":"Unlocking approximation for in-memory computing with Cartesian genetic programming and computer algebra for arithmetic circuits","authors":"Saman Froehlich, R. Drechsler","doi":"10.1515/itit-2021-0042","DOIUrl":"https://doi.org/10.1515/itit-2021-0042","url":null,"abstract":"Abstract With ReRAM being a non-volative memory technology, which features low power consumption, high scalability and allows for in-memory computing, it is a promising candidate for future computer architectures. Approximate computing is a design paradigm, which aims at reducing the complexity of hardware by trading off accuracy for area and/or delay. In this article, we introduce approximate computing techniques to in-memory computing. We extend existing compilation techniques for the Programmable Logic in-Memory (PLiM) computer architecture, by adapting state-of-the-art approximate computing techniques for arithmetic circuits. We use Cartesian Genetic Programming for the generation of approximate circuits and evaluate them using a Symbolic Computer Algebra-based technique with respect to error-metrics. In our experiments, we show that we can outperform state-of-the-art handcrafted approximate adder designs.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"64 1","pages":"99 - 107"},"PeriodicalIF":0.9,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46374296","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}
Abstract Chaotic Pseudo Random Number Generators have been seen as a promising candidate for secure random number generation. Using the logistic map as state transition function, we perform number generation experiments that illustrate the challenges when trying to do a replication study. Those challenges range from uncertainties about the rounding mode in arithmetic hardware over chosen number representations for variables to compiler or programmer decisions on evaluation order for arithmetic expressions. We find that different decisions lead to different streams with different security properties, where we focus on period length. However, descriptions in articles often are not detailed enough to deduce all decisions unambiguously. To address similar problems in other replication studies for security applications, we propose recommendations for descriptions of numerical experiments on security applications to avoid the above challenges. Moreover, we use the results to propose the use of higher-radix and mixed-radix representations to trade storage size for period length, and investigate if exploiting the symmetry of the logistic map function for number representation is advantageous.
{"title":"Replication study challenges and new number formats for chaotic pseudo random number generators","authors":"Carina Heßeling, J. Keller","doi":"10.1515/itit-2021-0065","DOIUrl":"https://doi.org/10.1515/itit-2021-0065","url":null,"abstract":"Abstract Chaotic Pseudo Random Number Generators have been seen as a promising candidate for secure random number generation. Using the logistic map as state transition function, we perform number generation experiments that illustrate the challenges when trying to do a replication study. Those challenges range from uncertainties about the rounding mode in arithmetic hardware over chosen number representations for variables to compiler or programmer decisions on evaluation order for arithmetic expressions. We find that different decisions lead to different streams with different security properties, where we focus on period length. However, descriptions in articles often are not detailed enough to deduce all decisions unambiguously. To address similar problems in other replication studies for security applications, we propose recommendations for descriptions of numerical experiments on security applications to avoid the above challenges. Moreover, we use the results to propose the use of higher-radix and mixed-radix representations to trade storage size for period length, and investigate if exploiting the symmetry of the logistic map function for number representation is advantageous.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"64 1","pages":"5 - 13"},"PeriodicalIF":0.9,"publicationDate":"2022-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45836262","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}
Alexandra Blair, Sai Yi Pan, Rajendra Subedi, Fei-Ju Yang, Nicole Aitken, Colin Steensma
Background: Despite early reports of social determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) burden, national Canadian reporting on COVID-19 inequalities has been limited. The objective of this study is to describe inequalities in COVID-19 mortality in Canada using preliminary data, as part of the Pan-Canadian Health Inequalities Reporting Initiative.
Methods: Two provisional Canadian Vital Statistics Death Database integrations were used. Data concerning deaths between January 1 and July 4, 2020, among private-dwelling residents were linked to individual-level data from the 2016 short-form Census, and disaggregated by sex and low-income status, dwelling type, household type and size. Data concerning deaths between January 1 and August 31, 2020 linked to 2016 Census area data were disaggregated by sex and neighbourhood ethno-cultural composition quintiles (based on the proportion of residents who are recent immigrants, visible minorities, born outside of Canada, with no knowledge of English or French), income quintiles and urban residence. The COVID-19 age-standardized mortality rate (per 100,000 population) differences and ratios between groups were estimated.
Results: As of July/August 2020, apartment dwellers, residents of urban centres, neighbourhoods with the highest ethno-cultural composition or lowest income experienced 14 to 30 more COVID-19-related deaths/100,000 compared with reference groups (residents of single-detached homes, outside of urban centres, with lowest ethno-cultural concentration or highest income, respectively). Per 100,000 population, sex/gender inequalities were also larger in these four groups (11 to 18 more male than female deaths) than in the reference groups (two to four more male than female deaths).
Conclusion: These findings highlight how populations facing socioeconomic disadvantage have experienced a higher overall burden of deaths. Areas for future research are discussed to guide health equity-informed pandemic response.
{"title":"Social inequalities in COVID-19 mortality by area and individual-level characteristics in Canada, January to July/August 2020: Results from two national data integrations.","authors":"Alexandra Blair, Sai Yi Pan, Rajendra Subedi, Fei-Ju Yang, Nicole Aitken, Colin Steensma","doi":"10.14745/ccdr.v48i01a05","DOIUrl":"10.14745/ccdr.v48i01a05","url":null,"abstract":"<p><strong>Background: </strong>Despite early reports of social determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) burden, national Canadian reporting on COVID-19 inequalities has been limited. The objective of this study is to describe inequalities in COVID-19 mortality in Canada using preliminary data, as part of the Pan-Canadian Health Inequalities Reporting Initiative.</p><p><strong>Methods: </strong>Two provisional Canadian Vital Statistics Death Database integrations were used. Data concerning deaths between January 1 and July 4, 2020, among private-dwelling residents were linked to individual-level data from the 2016 short-form Census, and disaggregated by sex and low-income status, dwelling type, household type and size. Data concerning deaths between January 1 and August 31, 2020 linked to 2016 Census area data were disaggregated by sex and neighbourhood ethno-cultural composition quintiles (based on the proportion of residents who are recent immigrants, visible minorities, born outside of Canada, with no knowledge of English or French), income quintiles and urban residence. The COVID-19 age-standardized mortality rate (per 100,000 population) differences and ratios between groups were estimated.</p><p><strong>Results: </strong>As of July/August 2020, apartment dwellers, residents of urban centres, neighbourhoods with the highest ethno-cultural composition or lowest income experienced 14 to 30 more COVID-19-related deaths/100,000 compared with reference groups (residents of single-detached homes, outside of urban centres, with lowest ethno-cultural concentration or highest income, respectively). Per 100,000 population, sex/gender inequalities were also larger in these four groups (11 to 18 more male than female deaths) than in the reference groups (two to four more male than female deaths).</p><p><strong>Conclusion: </strong>These findings highlight how populations facing socioeconomic disadvantage have experienced a higher overall burden of deaths. Areas for future research are discussed to guide health equity-informed pandemic response.</p>","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"58 1","pages":"27-38"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88935145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The digital transformation generates huge amounts of heterogeneous data across the industrial value chain, from simulation data in engineering, over sensor data in manufacturing to telemetry data on product use. Extracting insights from these data constitutes a critical success factor for industrial enterprises, e. g., to optimize processes and enhance product features. This is referred to as industrial analytics, i. e., data analytics for industrial value creation. Industrial analytics is an interdisciplinary subject area between data science and industrial engineering and is at the core of Industry 4.0. Yet, existing literature on industrial analytics is fragmented and specialized. To address this issue, this paper presents a holistic overview of the field of industrial analytics integrating both current research as well as industry experiences on real-world industrial analytics projects. We define key terms, describe typical use cases and discuss characteristics of industrial analytics. Moreover, we present a conceptual framework for industrial analytics that structures essential elements, e. g., data platforms and data roles. Finally, we conclude and highlight future research directions.
{"title":"Industrial analytics – An overview","authors":"Christoph Gröger","doi":"10.1515/itit-2021-0066","DOIUrl":"https://doi.org/10.1515/itit-2021-0066","url":null,"abstract":"Abstract The digital transformation generates huge amounts of heterogeneous data across the industrial value chain, from simulation data in engineering, over sensor data in manufacturing to telemetry data on product use. Extracting insights from these data constitutes a critical success factor for industrial enterprises, e. g., to optimize processes and enhance product features. This is referred to as industrial analytics, i. e., data analytics for industrial value creation. Industrial analytics is an interdisciplinary subject area between data science and industrial engineering and is at the core of Industry 4.0. Yet, existing literature on industrial analytics is fragmented and specialized. To address this issue, this paper presents a holistic overview of the field of industrial analytics integrating both current research as well as industry experiences on real-world industrial analytics projects. We define key terms, describe typical use cases and discuss characteristics of industrial analytics. Moreover, we present a conceptual framework for industrial analytics that structures essential elements, e. g., data platforms and data roles. Finally, we conclude and highlight future research directions.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"64 1","pages":"55 - 65"},"PeriodicalIF":0.9,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43775620","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}
Abstract Human-Centered AI is a widely requested goal for AI applications. To reach this is explainable AI promises to help humans to understand the inner workings and decisions of AI systems. While different XAI techniques have been developed to shed light on AI systems, it is still unclear how end-users with no experience in machine learning perceive these. Psychological concepts like trust, mental models, and self-efficacy can serve as instruments to evaluate XAI approaches in empirical studies with end-users. First results in applications for education, healthcare, and industry suggest that one XAI does not fit all. Instead, the design of XAI has to consider user needs, personal background, and the specific task of the AI system.
{"title":"Towards Human-Centered AI: Psychological concepts as foundation for empirical XAI research","authors":"Katharina Weitz","doi":"10.1515/itit-2021-0047","DOIUrl":"https://doi.org/10.1515/itit-2021-0047","url":null,"abstract":"Abstract Human-Centered AI is a widely requested goal for AI applications. To reach this is explainable AI promises to help humans to understand the inner workings and decisions of AI systems. While different XAI techniques have been developed to shed light on AI systems, it is still unclear how end-users with no experience in machine learning perceive these. Psychological concepts like trust, mental models, and self-efficacy can serve as instruments to evaluate XAI approaches in empirical studies with end-users. First results in applications for education, healthcare, and industry suggest that one XAI does not fit all. Instead, the design of XAI has to consider user needs, personal background, and the specific task of the AI system.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"64 1","pages":"71 - 75"},"PeriodicalIF":0.9,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48220025","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}
Abstract Hybrid system dynamics arises when discrete actions meet continuous behaviour due to physical processes and continuous control. A natural domain of such systems are emerging smart technologies which add elements of intelligence, co-operation, and adaptivity to physical entities. Various flavours of hybrid automata have been suggested as a means to formally analyse dynamics of such systems. In this article, we present our current work on a revised formal model that is able to represent state tracking and estimation in hybrid systems and thereby enhancing precision of verification verdicts.
{"title":"Bayesian hybrid automata: Reconciling formal methods with metrology","authors":"P. Kröger, M. Fränzle","doi":"10.1515/itit-2021-0008","DOIUrl":"https://doi.org/10.1515/itit-2021-0008","url":null,"abstract":"Abstract Hybrid system dynamics arises when discrete actions meet continuous behaviour due to physical processes and continuous control. A natural domain of such systems are emerging smart technologies which add elements of intelligence, co-operation, and adaptivity to physical entities. Various flavours of hybrid automata have been suggested as a means to formally analyse dynamics of such systems. In this article, we present our current work on a revised formal model that is able to represent state tracking and estimation in hybrid systems and thereby enhancing precision of verification verdicts.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"63 1","pages":"265 - 275"},"PeriodicalIF":0.9,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47665248","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}
Abstract Functional architectures of cyber-physical systems increasingly comprise components that are generated by training and machine learning rather than by more traditional engineering approaches, as necessary in safety-critical application domains, poses various unsolved challenges. Commonly used computational structures underlying machine learning, like deep neural networks, still lack scalable automatic verification support. Due to size, non-linearity, and non-convexity, neural network verification is a challenge to state-of-art Mixed Integer linear programming (MILP) solvers and satisfiability modulo theories (SMT) solvers [2], [3]. In this research, we focus on artificial neural network with activation functions beyond the Rectified Linear Unit (ReLU). We are thus leaving the area of piecewise linear function supported by the majority of SMT solvers and specialized solvers for Artificial Neural Networks (ANNs), the successful like Reluplex solver [1]. A major part of this research is using the SMT solver iSAT [4] which aims at solving complex Boolean combinations of linear and non-linear constraint formulas (including transcendental functions), and therefore is suitable to verify the safety properties of a specific kind of neural network known as Multi-Layer Perceptron (MLP) which contain non-linear activation functions.
{"title":"Functional verification of cyber-physical systems containing machine-learnt components","authors":"Farzaneh Moradkhani, M. Fränzle","doi":"10.1515/itit-2021-0009","DOIUrl":"https://doi.org/10.1515/itit-2021-0009","url":null,"abstract":"Abstract Functional architectures of cyber-physical systems increasingly comprise components that are generated by training and machine learning rather than by more traditional engineering approaches, as necessary in safety-critical application domains, poses various unsolved challenges. Commonly used computational structures underlying machine learning, like deep neural networks, still lack scalable automatic verification support. Due to size, non-linearity, and non-convexity, neural network verification is a challenge to state-of-art Mixed Integer linear programming (MILP) solvers and satisfiability modulo theories (SMT) solvers [2], [3]. In this research, we focus on artificial neural network with activation functions beyond the Rectified Linear Unit (ReLU). We are thus leaving the area of piecewise linear function supported by the majority of SMT solvers and specialized solvers for Artificial Neural Networks (ANNs), the successful like Reluplex solver [1]. A major part of this research is using the SMT solver iSAT [4] which aims at solving complex Boolean combinations of linear and non-linear constraint formulas (including transcendental functions), and therefore is suitable to verify the safety properties of a specific kind of neural network known as Multi-Layer Perceptron (MLP) which contain non-linear activation functions.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"63 1","pages":"277 - 287"},"PeriodicalIF":0.9,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46407174","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}
E. Olderog, M. Fränzle, Oliver E. Theel, P. Kröger
Abstract This special issue presents seven overview articles on research conducted in the Research Training Group “System Correctness under Adverse Conditions” (SCARE) at the University of Oldenburg.
{"title":"System correctness under adverse conditions","authors":"E. Olderog, M. Fränzle, Oliver E. Theel, P. Kröger","doi":"10.1515/itit-2021-0043","DOIUrl":"https://doi.org/10.1515/itit-2021-0043","url":null,"abstract":"Abstract This special issue presents seven overview articles on research conducted in the Research Training Group “System Correctness under Adverse Conditions” (SCARE) at the University of Oldenburg.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"63 1","pages":"249 - 251"},"PeriodicalIF":0.9,"publicationDate":"2021-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45060351","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}
Abstract Delays in feedback dynamics of coupled dynamical systems arise regularly, especially in embedded control where the physical plant and the controller continuously interact through digital networks. Systems featuring delays are however notoriously difficult to analyze. Consequently, formal analysis often addresses simplified, delay-free substitute models, risking negligence of the adverse impact of delay on control performance. In this ongoing work, we demonstrate that for continuous systems such as delay differential equations, a major part of the delay-induced complexity can be reduced effectively when adding natural constraints to the model of the delayed feedback channel, namely that it transports a band-limited signal and implements a non-punctual, distributed delay. The reduction is based on a sampling approach which is applicable when the above conditions on the feedback are satisfied. We further discuss the possibilities of lifting this method to mixed discrete-continuous dynamics of delayed hybrid systems and the open issues thereof.
{"title":"A sampling-based approach for handling delays in continuous and hybrid systems","authors":"Erzana Berani Abdelwahab, M. Fränzle","doi":"10.1515/itit-2021-0010","DOIUrl":"https://doi.org/10.1515/itit-2021-0010","url":null,"abstract":"Abstract Delays in feedback dynamics of coupled dynamical systems arise regularly, especially in embedded control where the physical plant and the controller continuously interact through digital networks. Systems featuring delays are however notoriously difficult to analyze. Consequently, formal analysis often addresses simplified, delay-free substitute models, risking negligence of the adverse impact of delay on control performance. In this ongoing work, we demonstrate that for continuous systems such as delay differential equations, a major part of the delay-induced complexity can be reduced effectively when adding natural constraints to the model of the delayed feedback channel, namely that it transports a band-limited signal and implements a non-punctual, distributed delay. The reduction is based on a sampling approach which is applicable when the above conditions on the feedback are satisfied. We further discuss the possibilities of lifting this method to mixed discrete-continuous dynamics of delayed hybrid systems and the open issues thereof.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"63 1","pages":"289 - 298"},"PeriodicalIF":0.9,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47221404","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}
Abstract We present an approach for modeling adverse conditions by graph transformation systems. To this end, we introduce joint graph transformation systems which involve a system, an interfering environment, and an automaton modeling their interaction. For joint graph transformation systems, we present notions of correctness under adverse conditions. Some instances of correctness are expressible in LTL (linear temporal logic), or in CTL (computation tree logic), respectively. In these cases, verification of joint graph transformation systems is reduced to temporal model checking. To handle infinite state spaces, we incorporate the concept of well-structuredness. We discuss ideas for the verification of joint graph transformation systems using results based on well-structuredness.
{"title":"Infinite-state graph transformation systems under adverse conditions","authors":"Okan Özkan","doi":"10.1515/itit-2021-0011","DOIUrl":"https://doi.org/10.1515/itit-2021-0011","url":null,"abstract":"Abstract We present an approach for modeling adverse conditions by graph transformation systems. To this end, we introduce joint graph transformation systems which involve a system, an interfering environment, and an automaton modeling their interaction. For joint graph transformation systems, we present notions of correctness under adverse conditions. Some instances of correctness are expressible in LTL (linear temporal logic), or in CTL (computation tree logic), respectively. In these cases, verification of joint graph transformation systems is reduced to temporal model checking. To handle infinite state spaces, we incorporate the concept of well-structuredness. We discuss ideas for the verification of joint graph transformation systems using results based on well-structuredness.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":"63 1","pages":"311 - 320"},"PeriodicalIF":0.9,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42795593","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：