2021 Systems and Information Engineering Design Symposium (SIEDS)最新文献

{"title":"Designing, Modeling and Simulating a New Plant Producing Coal-Derived \"Green\" Products","authors":"Javier Langarica, M. Perlow, Alexander Solomon, Derek Ripp","doi":"10.1109/SIEDS52267.2021.9483728","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483728","url":null,"abstract":"As many institutions are moving towards decarbonization, the coal industry is slowly declining and exploring new markets. During the last three years, teams from The George Washington University and Mississippi State University have worked on a joint research program that aims to produce three new environmentally friendly products derived from coal. These patented products could potentially revitalize the coal industry. However, there is currently no existing production plant design, which is paramount to succeeding in this new market. The production plant consists of three production lines, one for each product. Every production line is unique and creates products with different properties using the same raw material. However, some processing units are used repeatedly by the same production line or even different production lines, while the project budget currently only allows the purchase and operation of one processing unit of each type. A plant design was laid out to represent the processing unit availability in the plant while meeting the specifications of each production line. The design was then modeled using the simulation software Simio to create a prototype of the real-life plant. The simulation of this model projected the production performance of the plant under the current design conditions. Three new alternative models were then simulated to explore productivity variations resulting from the addition of production silos to the plant. Production silos were demonstrated as an effective technique to increase productivity and utilization of specific processing units, while maintaining the same processing unit availability and staying within the budget.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127053328","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":"Predicting Survivability in Lost Person Cases","authors":"M. Pajewski, Chirag Kulkarni, Nikhil Daga, Ronak Rijhwani","doi":"10.1109/SIEDS52267.2021.9483790","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483790","url":null,"abstract":"Over 600,000 people go missing each year in the United States. These events can cover situations anywhere from a young child going missing in a park to a group of hikers getting lost on a trail. dbS Productions has collected data on 16,863 searches over the past 30 years to generate an international database for use by search and rescue teams. The data recorded include a variety of fields such as subject category, terrain, sex, weight, and search hours. The data set is currently being underutilized by search and rescue teams due to a lack of applicable predictive tools built upon the aforementioned data. These search and rescue teams are also often volunteer-based and face great resource limitations in their operations. A tool is needed to predict the probability of a missing person’s survival for the operation’s coordinator to aid in resource allocation and the decision to continue or terminate search missions, which can be costly. This paper details an effort to create such a survivability predictor to help with this goal.We applied an Boosted Tree implementation of an Accelerated Failure Time (AFT) model to estimate the probability that a lost person would be found over time, given personal information about the subject, the location, and weather. We engineered several categorical variables and obtained weather data through the National Weather Service API to improve the model performance.Our engineered model recorded a C-index score of .67, which indicates a relatively robust model where industry standard considers 0.7 as \"good\" and 0.5 on par with random guessing. An analysis of the feature weights suggested that subject age, temperature, population density, mental fitness, and sex are the most critical indicators of survival in a missing person incident.Future work should involve incorporating more specific weather data, such as wind speeds and precipitation, into the model to improve prediction accuracy. Further research directions may include building a geo-spatial model to predict potential paths taken by a missing person based on initial location and the same predictors used in the survivability model.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125854076","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":"Destination Selection in Environmental Migration with TOPSIS","authors":"Emma Kuttler, Buket Cilali, K. Barker","doi":"10.1109/SIEDS52267.2021.9483764","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483764","url":null,"abstract":"The effects of climate change will lead to the forced displacement of millions and will cause dramatic changes to human settlement and migration patterns. The most vulnerable populations will travel as environmental migrants through a complicated quasi-governmental resettlement system of aid camps in the hope of finding long-term placements. These people deserve safe housing and the location they permanently settle in has critical socio-political impacts. Prior research has generally focused on post-conflict or post-disaster relief location selection for a facility at a single point in time or single-period refugee resettlement, with even less work dedicated to environmental migration. Furthermore, the scale of this work is typically limited to a city or country with the geographic area available for relocation remaining static, while in a climate change scenario the habitable land changes over time. We extend the problem of single-period resettlement to multi-period resettlement using the technique for order preference by similarity to ideal solution (TOPSIS), a straightforward multi-criteria decision-making method. We propose a method to iterate resettlement across multiple planning periods and incorporate geospatial, cultural, environmental, and capacity criteria. The set of alternatives, or destinations countries, will change with each planning period to represent the changing habitable environment. Ratios of weights between iterations remain constant. TOPSIS will produce a ranked list of destination sites. The methodology will be illustrated with a generated data set using a set of vulnerable source locations and a set of destination sites, both of which will change in each planning period. We found more variation in the rankings between periods than with standard TOPSIS, as well as greater sensitivity to weights. This work can be applied to any sort of long-term multi-criteria location selection problems (e.g., store openings and closings under changing consumer demand).","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116542504","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":"Supervised Machine Learning and Deep Learning Classification Techniques to Identify Scholarly and Research Content","authors":"Hufei Chang, Yihnew Eshetu, Celeste Lemrow","doi":"10.1109/SIEDS52267.2021.9483792","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483792","url":null,"abstract":"The Internet Archive (IA), one of the largest open-access digital libraries, offers 28 million books and texts as part of its effort to provide an open, comprehensive digital library. As it organizes its archive to support increased accessibility of scholarly content to support research, it confronts both a need to efficiently identify and organize academic documents and to ensure an inclusive corpus of scholarly work that reflects a \"long tail distribution,\" ranging from high-visibility, frequently-accessed documents to documents with low visibility and usage. At the same time, it is important to ensure that artifacts labeled as research meet widely-accepted criteria and standards of rigor for research or academic work to maintain the credibility of that collection as a legitimate repository for scholarship. Our project identifies effective supervised machine learning and deep learning classification techniques to quickly and correctly identify research products, while also ensuring inclusivity along the entire long-tail spectrum. Using data extraction and feature engineering techniques, we identify lexical and structural features such as number of pages, size, and keywords that indicate structure and content that conforms to research product criteria. We compare performance among machine learning classification algorithms and identify an efficient set of visual and linguistic features for accurate identification, and then use image classification for more challenging cases, particularly for papers written in non-Romance languages. We use a large dataset of PDF files from the Internet Archive, but our research offers broader implications for library science and information retrieval. We hypothesize that key lexical markers and visual document dimensions, extracted through PDF parsing and feature engineering as part of data processing, can be efficiently extracted from a corpus of documents and combined effectively for a high level of accurate classification.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123008388","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":"Process Mining and Simulation for a p-Time Petri Net Model with Hybrid Resources","authors":"Felipe Nedopetalski, Joslaine Cristina Jeske de Freitas","doi":"10.1109/SIEDS52267.2021.9483768","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483768","url":null,"abstract":"Process mining can be understood as a tool to extract useful information from processes that already happened and make decisions to improve performance of processes. The main three techniques while applying process mining to event logs are process discovery, process enhancement and conformance checking. Among many different applications that process mining can be applied to, in this paper, process mining is used to discover the model from event logs generated from simulations of the \"Handle Complaint Process\" Workflow net based on a p-time Petri net model with hybrid resources. This net discovered with process mining must be similar to the original one due event logs used to generate it are created from the simulation. There is no doubt that process mining has become increasingly useful for the future of Workflow nets especially when it is followed by simulation. Process mining can discover processes from event logs, find deviations and produce a better workflow while simulation can test new scenarios and hypotheses. With both working together product owners can reach a pretty good process excellence. The \"Handle Complaint Process\" Workflow net based on a p-time Petri net model with hybrid resources tries to solve the real time scheduling problem of Workflow Management Systems. The approach made in this work in particular, utilizes discrete + continuous resources and real time to decide when to fire a transition in the Workflow net. To generate the event logs from the simulation of the Workflow net, some functions were added in order to capture the identification number of each token, the path made by it, as well as the timestamp in the moment the transition was fired and the person or system responsible for the activity. This Workflow net was simulated using CPN Tools. The logs generated from the simulation were converted using the ProM Import tool and the process mining discovery technique was applied using ProM. The use of event logs of a business process model is a way to detect deviations from the expected behavior. Based on these deviations, the process can be changed in order to achieve excellence. The logs from the p-net model with hybrid resources tries to simulate, in a better way, the human behavior. As the model generated from the logs is similar to the original one, the conversion is correct. As a future work proposal, we will compare a real event log with the results achieved with this work to see the efficiency in simulating a process model with hybrid resources.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130636891","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":"Energy Supply Readiness Across Climate Change and Energy Demand Scenarios in the Columbia River Basin","authors":"C. Bailey, Samantha Garcia, Hong Liang, Kenneth Ross, J. Quinn","doi":"10.1109/SIEDS52267.2021.9483778","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483778","url":null,"abstract":"The Columbia River Power system is the country’s largest renewable energy system, spanning several states and two countries. It provides one of the fastest growing regions in the continent with clean, reliable energy and protects thousands of square miles of land from flooding. The reservoirs on the Columbia River and its tributaries are responsible for many critical functions, such as flood prevention and mitigation, water quality and quantity assurance, and salmon reproduction. Despite these other objectives, the Columbia River Power system is the backbone of the region’s energy supply, providing baseload when other renewable energy sources, namely wind and to a smaller extent solar, are unavailable. When hydropower cannot fill the gap, natural gas must instead, increasing reliance on fossil fuels. The objective of our project is to analyze the energy output of the Columbia River Basin across multiple different climate change and energy demand scenarios to understand the impact that each of these possible futures has on the region’s ability to transition to a cleaner energy future while meeting potentially growing demands. By utilizing multiple scenarios, uncertainty around hydrometeorological and socioeconomic conditions can be quantified and addressed.In this study, we analyze outputs in the middle of the 21st century from the California and West Coast Power System (CAPOW) model, customized to reflect each climate change and energy demand combination. Energy demand scenarios are quantified by Shared Socioeconomic Pathways (SSP) and climate change scenarios by CMIP5 Representative Concentration Pathways (RCP), providing projected trends until the end of the century. By varying low, middle, and high pathways across both the SSPs and RCPs, we can gain insights into the Pacific Northwest’s energy health. This research has the potential to identify shortcomings in the current energy infrastructure, project the benefits and consequences of alternative development pathways, and increase understanding of the Columbia River Power system’s greatest sensitivities (climatic or socioeconomic). Future work can build off of this knowledge to design more robust reservoir operating policies in the Columbia River Basin.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126372742","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":"Is my User Impaired? Designing Adaptive Automation that Monitors the User’s State","authors":"Jenna E. Cotter, A. Atchley, B. Banz, N. Tenhundfeld","doi":"10.1109/SIEDS52267.2021.9483731","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483731","url":null,"abstract":"According to the United States Department of Justice, 28 people in the United States die every day because of drunk driving. As self-driving vehicles become more prevalent, the ability for automated cars to determine when the driver is impaired and to then take control, could save many lives. Past research has looked at the certain indicators for impaired driving, but to date there has been relatively little consideration of the potential interaction between an impaired driver and a self-driving vehicle. In this paper, we will review the existing literature in order to recap the possible approaches vehicle manufacturers could take in establishing that a driver is impaired: physiological, behavioral, and vigilance monitoring. These approaches will be contrasted with one another. Following the review, we will propose several design solutions to be developed and tested. These solutions include a ‘full’, ‘partial’, and ‘supervisory’ takeover by the vehicle. Our full takeover proposed design will provide no opportunity for driver input at any point. Our partial takeover proposed design will involve a full takeover, but with additional impairment tests that the driver can perform in order to demonstrate capacity to drive. Finally, our supervisory takeover proposed design will involve the system actively monitoring performance in order to more quickly engage safety procedures (e.g. lane keep and emergency braking). The relative benefits and consequences of each design will be discussed with an eye towards existing theories on human-automation interaction. Finally, we will propose a path forward for design and testing. Taken together, this paper will present a novel consideration of a new avenue for human-machine teaming. Such considerations could be instrumental in saving thousands of lives each year, and helping to prevent countless other injuries.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121595260","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":"Integrating Modularity for Mass Customization of IoT Wireless Sensor Systems","authors":"Derek D’Alessandro, W. Gunderson, Ethan Staten, Yann Kelsen Donastien, P. Rodríguez, R. Bailey","doi":"10.1109/SIEDS52267.2021.9483737","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483737","url":null,"abstract":"As data collection and analysis grows in demand across a diverse spectrum of industries, data is collected from many sensors at different ranges with different quantities and types of data. One general approach taken by commercial firms to integrate wireless sensor data is to develop proprietary \"ecosystems\" of products; home automation companies like NEST, home security companies like SimpliSafe, and agricultural companies like Davis Instruments each require that customers use their hubs with their peripheral sensors. The work in this paper applies a flipped approach where a heterogeneous set of sensors from a range of suppliers connects to a hub over a variety of wireless protocols. The design of the hub, therefore, needs to easily accommodate a wide range of communication and wireless protocols. The focus of this work is on exploring how modularity can be designed into the architecture of a product to facilitate quick and low-cost customization of the hub to a particular need.This particular work focuses on designing such a hub for various low-power wide-area network (LPWAN) applications. LPWANs are technologies and protocols that have longer ranges and lower power usage than higher bandwidth protocols like Wi-Fi. LPWANs, like LoRa, specialize in applications where many sensors are distributed over larger distances and, due to the small amounts of data they intermittently send, require less power. This modular hub needs to be able to recognize the type of radio connected to it and the type of communication (I2C, SPI, UART) used by the radio. Such recognition will enable variable quantities of different radios to be connected to the hub without significant redesign of the electronics or the firmware. Furthermore, the housing for the hub needs to be sufficiently modular so that any radio could be inserted without requiring a new design. Using custom components in only certain interfaces is central to the electronics design, and such modularity depends heavily on the firmware. With respect to the housing, a key trade-off for integrating modularity is accommodating variability in radios while maintaining ergonomic design. A key consideration in both housing and electronic design is incorporating modularity only where needed, and creating components in-house when necessary.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133313611","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 User Interface Informing Medical Staff on Continuous Indoor Environmental Quality to Support Patient Care and Airborne Disease Mitigation","authors":"Jacob Rantas, David Wang, Will Jarrard, James Sterchi, Alan Wang, Mahsa Pahlavikhah Varnosfaderani, Arsalan Heydarian","doi":"10.1109/SIEDS52267.2021.9483774","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483774","url":null,"abstract":"This project seeks to investigate the under addressed issue of indoor environmental quality (IEQ) and the impacts these factors can have on human health. The recent COVID-19 pandemic has once again brought to the forefront the importance of maintaining a healthy indoor environment. Specifically, the improvement of indoor air flow has shown to reduce the risk of airborne virus exposure. This is extremely important in the context of hospitals, which contain high concentrations of atrisk individuals. Thus, the need to create a healthy indoor space is critical to improve public health and COVID-19 mitigation efforts. To create knowledge and provide insight on environmental qualities in the hospital setting, the authors have designed and built an interface to deploy in the University of Virginia Hospital Emergency Department (ED). The interface will display room-specific light, noise, temperature, CO2, humidity, VOC, and PM2.5 levels measured by the low-cost Awair Omni sensor. These insights will assist ED clinicians in mitigating disease-spread and improving patient health and satisfaction while reducing caregiver burden. The team addressed the problem through agile development involving localized sensor deployment and analysis, discovery interviews with hospital clinicians and data scientists throughout, and the implementation of a human-design centered Django interface application. Furthermore, a literature survey was conducted to ascertain appropriate thresholds for the different environmental factors. Together, this work demonstrates opportunities to assist and improve patient care with environmental data.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132682700","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 Toolkit for the Spatiotemporal Analysis of Eutrophication Using Multispectral Imagery Collected from Drones","authors":"J. Barajas, Christian A. Detweiler, Cailyn Lager, Charles Seaver, Mark Vakarchuk, J. Henriques, Jason Forsyth","doi":"10.1109/SIEDS52267.2021.9483788","DOIUrl":"https://doi.org/10.1109/SIEDS52267.2021.9483788","url":null,"abstract":"This paper describes a toolkit for analyzing changes in algae levels in bodies of water as an indicator of eutrophication. Eutrophication is caused by the excessive nutrient loading in a lake or other body of water, frequently due to fertilizer runoff. The enriched water can cause dense growth of plant life (e.g. algae blooms) in the water. When this growth dies, the bacteria associated with decomposition consumes oxygen from the water, which can create a hypoxic environment (i.e. insufficient oxygen to sustain life). Not only is this an environmental problem, but also an economic problem. The estimated cost of damage mediated by eutrophication in the U.S. alone is approximately $2.2 billion annually. These costs come from a variety of factors: parks losing revenue from forced closure, clean up, and removal of algae. The key components of the system discussed in this paper are a drone, multispectral camera, and a spatial and temporal analysis software toolkit. The multispectral camera stores images on a removable SD card that are then imported into ArcGIS. Analysis is done through a custom Python toolkit created to determine vegetation health levels in bodies of water. The key focus of analysis is using the normalized difference vegetation index (NDVI) values captured from multispectral imaging to compare the different vegetation levels across various flight days. This system can help users combat eutrophication by allowing them to identify patterns and trends in the algal growth in bodies of water they manage in near real time. This may help, for example, identify patterns in fertilization and algal growth, and ultimately aid in keeping bodies of water healthy.","PeriodicalId":426747,"journal":{"name":"2021 Systems and Information Engineering Design Symposium (SIEDS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131663782","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}