Cognitive Computing and Internet of Things最新文献

{"title":"Real-time remote stress monitoring based on specific stress modelling considering load characteristics of different military forces","authors":"A. Almer, A. Weber, Florian Haid, L. Paletta, M. Schneeberger, Stefan Ladstätter, D. Wallner, Paul Glanz, Philip Klöckl, Dominik Eder, T. Hölzl","doi":"10.54941/ahfe1003977","DOIUrl":"https://doi.org/10.54941/ahfe1003977","url":null,"abstract":"An ongoing challenge for the Military Task Forces is the management of personnel to optimise and maintain performance, whilst also ensuring ongoing health and wellbeing. In the course of intensive training and exercises as well as in real operational scenarios, soldiers often suffer physiological and psychological borderline stresses and also injuries during physical and combat-related training, with overuse injuries often occurring here. Innovative developments and research projects for the physiological monitoring of soldiers arise, based on innovative developments in the field of biosensor technology. Soldiers are at the center of deployed sociotechnical systems despite major innovations in the field of autonomous systems and artificial intelligence (Swiss, 2020). These are aspects and development approaches that are of great interest to military as well as civilian task forces. Motivation and Requirements: Military training and exercise missions as well as real deployment scenarios are often associated with a high degree of physical stress and responsibility and require a high level of mental performance and concentration. Reduced concentration and reaction cause delayed or possibly even wrong decisions, which can have fatal consequences. The research project VitalMonitor therefore focuses on the development of a (i) real-time monitoring system, which analyses changes in physiological parameters from heart rate, heart rate variability, skin conductance, core body temperature, etc., (ii) decision support tool for mission commanders to determine optimal work-rest-cycles preventing physical overstraining in trainings and missions (iii) personalized physical fitness training for soldiers to control their individual stress situation in a targeted manner avoiding poor performance. Methods and Results: In order to be able to make concrete statements about a current, individual stress situation for the soldiers of different task forces, it is necessary to characterize the work stress and to develop specific load and stress models. Basically, here is a relevant difference in the stress models if we compare e.g. CBRN group, light infantry forces and special military forces in the operational loads. In a first step, an attempt was made to create a so-called expert model for the load characteristics on the basis of extensive expert knowledge and measured values collected in the context of various stress tests with various military task forces. The focus was initially on the CBRN task force and further extensive tests were carried out as part of the VitalMonitor project.The basis for the creation of a specific stress model is the comprehensive analysis of the scenario-related work conditions, the psychological and cognitive stress as well as the physiological stress and the interrelationships that occur. The use of an available innovative bio-sensor technology must enable the remote measurement of vital values of the soldiers in the different deployment s","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117170928","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}

{"title":"Digital Shadows and Twins for Human Experts and Data-Driven Services in a Framework of Democratic AI-based Decision Support","authors":"L. Paletta, Herwig Zeiner, M. Schneeberger, Y. Quadri","doi":"10.54941/ahfe1003971","DOIUrl":"https://doi.org/10.54941/ahfe1003971","url":null,"abstract":"Current automated and hierarchical structured production processes can only insufficiently deal with the upcoming flexibilization, specifically regarding the requirements within Industry 5.0. The European project FAIRWork fosters the ‘democratization’ of decision-making in production processes, hence the participation of all involved stakeholders, by introducing a decentralized AI system. Hybrid decision-making faces the challenge first to digitally represent the relevant actors – here we propose the use of digital twins – and the interpretation of that digital twin, by a human expert or by a computer algorithm, to achieve better decisions. Research on existing sensors and data technology is required. In particular, the digital representation of human operators requires so called “Intelligent Sensor Boxes”.Method: ‘Intelligent Sensor Boxes’ are firstly determined by a dedicated group of sensors, such as, low-cost sensors, biosensors, wearables, human sensors, or even virtual sensors. Specific attention is dedicated to the development of the ‘Digital Human Sensor’ (DHS) applying AI-enabled Human Factors measurement technology. Each instantiation of a DHS provides a digital vector of Human Factors state estimates, such as, digital biomarkers on physiological strain, affective state, concentration, cognitive workload, situation awareness, fatigue. On the basis of these vectors, we determine cost function parameters associated with typical (inter-)actions in the work environment. We outline an advanced approach to represent cognitive strain by studying workload related to task switching, multitasking and interruption as well as monotony effects. Furthermore, we will investigate cognitive strain in the context of environmental parameters, such as, air quality, and combine IOT with wearable bio-sensor shirts, smartwatches with biosensors, eye tracking glasses, digital events, and spatiotemporal patterns from human-machine interaction. Cost functions for optimization algorithms can be related to well-being of the worker, this allows data processing with the goal to optimize according to several input factors using data that are derived from humans or from machines like lines and robots. Those data are described with corresponding meta data to result in a descriptive data lake. Such meta data correspond to domain specific models like the production process, the working environment model, or resources models. Data processing and optimization algorithms can then be applied on this data lake. This task complements existing data with human based sensor data and provided adapted data mining tools.Results: We present relevant methodologies for human-centered wearable or mobile measurement technologies for psychological and ecological constructs as typical instantiations of the novel framework. Furthermore, the embedding of the schema of ‘Intelligent Sensor Boxes’ into the framework of ‘Democratic AI-based Decision Support’ (DAI-DDS) is sketched and argued. An ","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124972496","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}

{"title":"A Critical Overview of Studies on Eye Tracking and Visual Hierarchy","authors":"Amic G. Ho","doi":"10.54941/ahfe1003295","DOIUrl":"https://doi.org/10.54941/ahfe1003295","url":null,"abstract":"This paper offers a thorough evaluation of recent eye-tracking studies in the area of visual hierarchy. The review’s specific goal is to investigate how eye-tracking technology might be used to study cognitive processes in the visual hierarchy while using pertinent characteristics. 30 papers, encompassing 36 investigations, were examined for this purpose. There are some noteworthy findings. Using eye-tracking technologies to investigate visual hierarchies has gained a lot of attention recently. Typically, the research included university students, scientific content, and chronological frequency count ranges of eye-tracking metrics. Insights into cognitive processes including selection, organisation, and integration might be gleaned by monitoring eye movement patterns. Visual hierarchy principles, visual content, individual differences; and visual hierarchy principles, visual content. To provide recommendations for future research and practises, specific gaps in the literature and implications of previous results on visual hierarchy design were also identified.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128260873","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}

{"title":"Mild Dementia Decision Support from AI-based Digital Biomarkers using Mobile Playful Exercises with High Adherence","authors":"M. Pszeida, L. Paletta, S. Russegger, T. Orgel, S. Draxler, M. Koini, Martin Berger, M. Fellner, S. Spat, Sandra Schuessler, J. Zuschnegg, Bernhard Strobl, Karin Ploder, Maria M Hofmarcher Holzhacker","doi":"10.54941/ahfe1003970","DOIUrl":"https://doi.org/10.54941/ahfe1003970","url":null,"abstract":"Early detection of cognitive decline and monitoring of cognitive functioning in mild dementia are fundamental for timely adaptation of lifestyle and intervention strategies. The development of digital dementia biomarkers through playful exercises with high adherence rate was a key objective of the national project multimodAAL (no. FFG 875345). The results of a study on computer-based cognitive and physical training (CCPT) in persons diagnosed with mild Alzheimer’s disease (PwAD) are presented.Method: Tablet-PC-based intervention was applied within 6 months in Austria, engaging PwADs living at home by means of playful multimodal training and activation (n=11; female N=8, male N=3; age M=76.6 / SD=9.2 years, MMSE score M=21.50 / SD=4.41). PwADs interacted with a prototypical version of the BRAINMEE app that included a suite of cognitive exercises (puzzle, pairs, text gap filling) based on audiovisual information. The playful training app was introduced and assisted by mobile care professionals with weekly visits, however, PwDs played alone between these visits.Result: PwADs applied training with high adherence, finalizing M=72 (M=32) digital exercises per day within the first (last) month of the study. Duration of using exercise type ‘outsider’(p=.028*) and ‘quiz’ (p=.001**), averaged about 2 week figures, each provided statistically significant correlations (Spearman) with MMSE test scores, as well as ‘spot-the-difference’ (p=.003**) with Trail Making Test A, ‘outsider’ (p=.005**) with Auditory Verbal Learning Test (AVLT), respectively. A neural network (Support Vector Machine, linear kernel, 11-fold cross validation) using duration of use of ‘quiz’, ’outsider’ and ‘hearing’ (guessing animal sounds) as input data resulted in M=2.16 absolute error in MMSE score estimation on test data.Conclusion: The work outlined within the Austrian study on digital biomarker development indicates successful steps towards daily use of cognitive assessment using highly adherent playful training. The playful training app is applied in the European project MARA (no. FFG 886427) to enable continuous estimates of MCI’s mental state over time. The app was very well accepted by both PwADs and persons with MCI. It offers with its pervasive mental assessment tool a large potential for future long-term monitoring in dementia prevention, early detection as well as in numerous dementia care services.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126366638","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}

{"title":"The influence of task complexity on acceptance and trust in human-robot interaction - gender and age differences","authors":"V. Wagner-Hartl, Ramona Schmid, Katharina Gleichauf","doi":"10.54941/ahfe1001846","DOIUrl":"https://doi.org/10.54941/ahfe1001846","url":null,"abstract":"An increase of human-robot collaboration is expected in the near future. Many people are already experiencing this in their working life, especially in the industrial context for example in production. As technology continues to improve, the number of scenarios and tasks in which humans and robots can interact with each other is also increasing. Therefore, it is important to focus on how humans and robots can work together in the future, while ensuring that negative emotions and mistrust towards this new form of work environment are avoided.The aim of the presented online study was therefore to get more insight in this important future field. Overall, 29 men and 42 women (N = 71) aged between 19 and 64 years (M = 31.44, SD = 13.30) participated in the study. All participants assessed four different scenarios were humans interact with robots in an industrial context. To assess the influence of task complexity on the subjectively assessed acceptance and trust, task complexity was increased with each scenario. The results show, significant assessment differences regarding the different levels of task complexity. Furthermore, women seem to assess the different interaction tasks as significantly more useful and satisfying than men. Regarding trust an interaction of age and gender can be shown.The results of the presented exploratory study can help to understand how the interaction of human and robots is seen today and shall help to get more insight in this important future field.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132427855","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}

{"title":"Development of an Automated Microclimate Adjustment System based on Concentration Levels of Students","authors":"Jasper Koh, Prasanna Thangaraja, Kenneth Y T Lim","doi":"10.54941/ahfe1003980","DOIUrl":"https://doi.org/10.54941/ahfe1003980","url":null,"abstract":"The microclimate of a classroom can significantly impact the students' concentration. As students ourselves, we have noticed this. For the same subject, we are concentrated in one period, then in another, we lose our attention very easily. This prompted us to investigate the relationship between students' concentration levels in relation to the microclimate. Through machine learning, specifically through facial recognition and computer vision, we aimed to investigate the students' concentration levels based on the number of blinks per minute. While researching ways to analyse concentration levels, we found multiple studies which found a correlation between blink frequency and concentration level. We found that when people are concentrated, they tend to blink less and vice versa. The relationship between microclimate climate and concentration was analysed by measuring the blinks per minute while changing the microclimate at the same time. The microclimate conditions were varied using an air conditioner where the temperature set varied from 19°C to 31°C. The microclimate was measured using the NodeMCU microcontroller board paired with SCD-30 and HM-3301 sensors from Grove. This allowed us to gather data such as temperature, relative humidity, carbon dioxide concentration, PM2.5 and PM10 readings. From this, it was found that the most significant microclimate condition that affects concentration levels is carbon dioxide concentration. As the concentration of carbon dioxide increases, the concentration of the participants decreases. The observed trend is supported by various studies as well. Simultaneously, as the microclimate conditions were being varied, we sent out a survey to find the thermal comfort level of the students, allowing us to gauge how they felt according to the environment. Thermal comfort is when a person feels comfortable with the thermal environment. Participants were tasked to do their work for a fixed duration while a sensor recorded the temperature and relative humidity of the place. For every hour, the participants were required to rank their thermal comfort by using the ASHRAE scale. This survey identified the comfort zone at an upper limit temperature of 28.9°C and relative humidity of 68.0% and a lower limit temperature of 26.2°C and relative humidity of 83.1%. With these findings, we created an automated system to alter microclimate conditions. The place will be a conducive environment for the students based on their concentration and the environmental data obtained from the sensors. The alteration of microclimate conditions was done by controlling the air conditioner using an infrared LED module connected to the NodeMCU that sent out the infrared codes according to the conditions of the room, allowing us to adjust the microclimate efficiently while fully utilising the various modes of the air conditioning system to save energy.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127966335","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}

{"title":"Computational Aesthetics of Visual Artworks: Review and Outlook","authors":"Pu Meng, Yueqi Liu, Liqun Zhang, Xiaodong Li","doi":"10.54941/ahfe1001833","DOIUrl":"https://doi.org/10.54941/ahfe1001833","url":null,"abstract":"Beauty has always been the goal of human activity. The meaning of beauty is defined during its creation. The discussion of beauty by mathematicians has created the computational aesthetics. This paper reviews the related works in computational aesthetics of visual arts and summarizes the features used in aesthetic measurement. The features extracted from the visual artworks are divided into five types including visual, compositional, statistical, perceptual and artistic features. Based on those features, the visual images are quantified and analyzed on their aesthetic and artistic properties. The previous studies are mostly focused on the aesthetics of art production, the continuous process for artistic creation cannot be represented. Moreover, new forms of visual arts such as generative art emerged, which provide new opportunities and challenges to the field of computational aesthetics. A prospective on the algorithms for the evaluation of this new forms of visual arts will be given.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126077664","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}

{"title":"AI-powered real-time analysis of human activity in videos via smartphone.","authors":"Rico Thomanek, Benny Platte, M. Baumgart, Christian Roschke, M. Ritter","doi":"10.54941/ahfe1003972","DOIUrl":"https://doi.org/10.54941/ahfe1003972","url":null,"abstract":"A major focus in computer vision research is the recognition of human activity based on visual information from audiovisual data using artificial intelligence. In this context, researchers are currently exploring image-based approaches using 3D CNNs, RNNs, or hybrid models with the intent of learning multiple levels of representation and abstraction that enable fully automated feature extraction and activity analysis based on them. Unfortunately, these architectures require powerful hardware to achieve the most real-time processing possible, making them difficult to deploy on smartphones. However, many video recordings are increasingly made with smartphones, so immediate classification of performed human activities and their tagging already during video recording would be useful for a variety of use cases. Especially in the mobile environment, a wide variety of use cases are therefore conceivable, such as the detection of correct motion sequences in the sports and health sector or the monitoring and automated alerting of security-relevant environments (e.g., demonstrations, festivals). However, this requires an efficient system architecture to perform real-time analysis despite limited hardware power. This paper addresses the approach of skeleton-based activity recognition on smartphones, where motion vectors of detected skeleton points are analyzed for their spatial and temporal expression rather than pixel-based information. In this process, the 3D-bone points of a recognized person are extracted using the AR framework integrated in the operating system and their motion data is analyzed in real time using a self-trained RNN. This purely numerical approach enables time-efficient real-time processing and activity classification. This system makes it possible to recognize a person in a live video stream recorded with a smartphone and classify the activity performed. By successfully deploying the system in several field tests, it can be shown both that the described approach works in principle and that it can be transferred to a resource-constrained mobile environment.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133678984","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}

{"title":"VR4care: Gender-sensitive Virtual Reality Technologies and Semantic Content Categories for Activation in Nursing Homes","authors":"L. Paletta, S. Reidl, S. Beranek, B. ., Msc ., R. Hartmann, Martin Sighart, Sebastian Mayer, Patricia Papic, Amir Dini, M. Pszeida, Sandra Schuessler, A. Haeussl, B. ., Beatrix Koch, Hermine Fürli, M. Schneeberger, M. Lenger, S. Russegger","doi":"10.54941/ahfe1001842","DOIUrl":"https://doi.org/10.54941/ahfe1001842","url":null,"abstract":"People living in long-term care facilities due to physical or mental impairments have few opportunities for self-determined activity. Virtual reality (VR) technologies offer a potential to expand individual experience through immersive presence in artificial environments, to activate mentally and to promote autonomy through the impact of self-efficacy. The overall goal of the Austrian project VR4Care was to research design basics for the development of a motivating, gender-sensitive, personalized and cost-effective VR technology to increase the activation and quality of life primarily of residents in inpatient long-term care. In the further development of VR for senior citizens, gender-specific differences were taken into account, such as gender-specific requirements for user interfaces, gender-specific preferences in interests with regard to content and different expectations of support when using the VR-based system.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129627746","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}

{"title":"Impact of real-time stress monitoring in people with an intellectual disability","authors":"Vera Van Der Nulft, Stefan de Vries, Josien Visschedijk, R. Smits, F. Meiland, E. Adam, H. Smaling, E. Meinders","doi":"10.54941/ahfe1003974","DOIUrl":"https://doi.org/10.54941/ahfe1003974","url":null,"abstract":"People with an intellectual disability are vulnerable to stress, which can result in challenging behaviour, such as apathy, self-harm, or aggression. By monitoring stress in real-time, professional caregivers can timely intervene to prevent escalations and improve the quality of life for both the client and themselves. The aim of this study was to investigate the impact of real-time stress monitoring using the stress-detection system HUME on the quality of life of people with a severe intellectual disability and their professional caregivers. The study comprised two parts. A case series study (n=12) was conducted with long-term care clients with intellectual disabilities to validate the HUME. HUME stress measurements, based on physiological data and trained artificial intelligence models, were collected, and compared with labelled video observations of professional caregivers. A second study was conducted to measure the impact of HUME and the induced interventions on quality of life. Physiology data and quality of life scores were collected. The HUME stress prediction was used 1) for early warning to deploy interventions based on what the professional caregiver deemed best, and 2) as an assessment tool to understand the effectiveness of care interventions. The quality of life for both the client (n=41) and professional caregiver (n=31) was evaluated via a questionnaire. Results showed that the HUME was able to detect stress in all cases, and stressful events detected by the HUME were consistent with the behavioural observations. The real-time stress monitoring using HUME, along with subsequent interventions, was effective. Clients with intellectual disabilities experienced reduced stress and an improvement in their perceived quality of life. Also, professional caregivers perceived an increase in the quality of life during the period the HUME was used. In most of the cases, HUME-based interventions led to a reduction in escalations, fixations, and self-harming behaviour. Further randomized controlled studies are needed to substantiate these results.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131576417","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}