Procedia Computer Science最新文献_第2页

Company perspectives of generative artificial intelligence in industrial work 工业生产中生成式人工智能的公司视角

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.085

Susanna Aromaa , Päivi Heikkilä , Marko Jurvansuu , Selen Pehlivan , Teijo Väärä , Marko Jurmu

{"title":"Company perspectives of generative artificial intelligence in industrial work","authors":"Susanna Aromaa , Päivi Heikkilä , Marko Jurvansuu , Selen Pehlivan , Teijo Väärä , Marko Jurmu","doi":"10.1016/j.procs.2025.01.085","DOIUrl":"10.1016/j.procs.2025.01.085","url":null,"abstract":"<div><div>The use of artificial intelligence (AI) technologies in the manufacturing industry is rapidly increasing. During this transformation, it can be difficult to understand how AI will change the way work is done. This study explores how generative AI could change manufacturing work. Data collection was conducted using interviews and a questionnaire with seven representatives from three industrial companies. They identified several application areas for GenAI in the industrial work context, such as design, planning, training, problem solving, coding and data management. They also expressed positive attitudes but raised concerns about trust, safety, acceptability and interoperability. Changes in work were identified as being more related to cognitive aspects such as changing the way of thinking and altering the interaction with people and machines. Therefore, human-AI design efforts should focus especially on cognitive ergonomics. Findings from this study can be used in the manufacturing industry when adopting AI, as well as in identifying research topics in the human-AI research community.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"253 ","pages":"Pages 217-226"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480192","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}

引用次数: 0

Integrating Chipless RFID Technology to Provide Seamless Data Interoperability for Textile Industry Circularity 集成无芯片RFID技术为纺织工业循环提供无缝数据互操作性

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.101

Maximilian Scholz, Omid Fatahi Valilai

{"title":"Integrating Chipless RFID Technology to Provide Seamless Data Interoperability for Textile Industry Circularity","authors":"Maximilian Scholz, Omid Fatahi Valilai","doi":"10.1016/j.procs.2025.01.101","DOIUrl":"10.1016/j.procs.2025.01.101","url":null,"abstract":"<div><div>The textile industry faces tremendous challenges when it comes to waste management and recycling. The current methods for textile companies and drop-off centres for sorting the textiles for recycling is largely through manual labour, which is inefficient and involves high costs. The bottleneck due to slow process for visual inspection creates bottlenecks for effective sorting. One idea to solve this problem is to use an embedded data mechanism in textile tags via radio frequency identification (RFID) chips. Considering the requirements of recycling processes, there is an essential need for RFID technologies which are compatible with recyclability of textile processes. Therefore, the need and demand for a sustainable solution for traceability and recycling via chipless RFID technologies is highly motivated. Moreover, the technology should be economically viable for industries for adoption. This study explores a new technological concept that offers a solution for the current problem of creating a circular economy in the textile industry with traceability of data. So, the study focuses on analysing how chipless RFID technology may be integrated into textiles with 3D printing technology. The research investigates 3D printing technology for providing the ability to create a fast, inexpensive, and detailed chipless RFID labelling solution for textile materials. Finally, the paper investigates the consumer populations readiness to adopt the technology by identifying pain points and outlining the integration of this technology into the textile industry.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"253 ","pages":"Pages 393-402"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480301","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}

引用次数: 0

Comparison of Material Fatigue Testing Strategies regarding Failure-Free Load Level of Steel Specimens using Bootstrapping and Statistical Models 基于自举模型和统计模型的钢试件无故障水平材料疲劳试验策略比较

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.095

Nikolaus Haselgruber , Gerhard Oertelt , Kristopher Boss

{"title":"Comparison of Material Fatigue Testing Strategies regarding Failure-Free Load Level of Steel Specimens using Bootstrapping and Statistical Models","authors":"Nikolaus Haselgruber , Gerhard Oertelt , Kristopher Boss","doi":"10.1016/j.procs.2025.01.095","DOIUrl":"10.1016/j.procs.2025.01.095","url":null,"abstract":"<div><div>The analysis of material fatigue data is an important step in the development of complex technical products to achieve a design which reliably withstands field load but avoids over-engineered and further unnecessary weight, energy consumption, and consequently, life cycle costs. The application of statistical methods helps to consider both, the variability of real-world load situations and the variability of material load capacity. However, to provide effective and accurate results, not only analysis methods but also data generation techniques should be selected with care. In this paper, we compare several material fatigue evaluation strategies, all consisting of a data generation/test part and an analysis part. E.g., stair-case, load-step and pearl-string as test procedures and Dixon-Mood analysis, lifetime-stress regression or the random fatigue limit model as analysis methods are investigated. The sensitivity on parameters which have to be set and the accuracy regarding load capacity as well as the required testing effort are compared. Load-step provides the most accurate estimation of the failure-free load level but is the most expensive method. Pearl-string and DoE provide similar results with much less effort and moderately higher uncertainty compared to load-step.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"253 ","pages":"Pages 323-335"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480303","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}

引用次数: 0

Influence of process parameters and wall thicknesses on the properties of tool steel 1.2709 (X3NiCoMoTi18-9-5) processed by Selective Laser Melting 工艺参数和壁厚对选择性激光熔化加工1.2709 （X3NiCoMoTi18-9-5）工具钢性能的影响

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.147

Sara Halilovic , Norbert Wild , Marko Orsolic , Aziz Huskic

{"title":"Influence of process parameters and wall thicknesses on the properties of tool steel 1.2709 (X3NiCoMoTi18-9-5) processed by Selective Laser Melting","authors":"Sara Halilovic , Norbert Wild , Marko Orsolic , Aziz Huskic","doi":"10.1016/j.procs.2025.01.147","DOIUrl":"10.1016/j.procs.2025.01.147","url":null,"abstract":"<div><div>Selective Laser Melting (SLM) has gained significant importance as a manufacturing process for complex geometries and high-precision components. For tool steels such as 1.2709, which are valued for their high strength and hardness, optimizing the process parameters is essential to achieve the desired mechanical properties and minimize defects. The ability to control factors like wall thickness and energy density is essential for producing thin-walled components with high structural integrity and reliability. In this study, the influence of the selected process parameter and wall thickness on the fabrication of tool steel 1.2709 by SLM was investigated. The tool steel was processed using two different process parameters and eleven wall thicknesses ranging from 0.2 to 1.0 mm. The two process parameters V1 (87 J/mm<sup>3</sup>) and V2 (48 J/mm<sup>3</sup>) differ significantly in their energy density. The specimens were examined for their final wall thickness. Furthermore, the influence of the process parameter and the wall thickness on the mechanical properties, the defects and the microstructure were determined. The investigations revealed a fine dendritic microstructure in the as-built condition. Depending on the process parameter, the mechanical properties are weakened by the porosity observed in thinner wall thicknesses.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"253 ","pages":"Pages 853-862"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480507","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}

引用次数: 0

Circular Data Service Cards: A Card-Based Ideation Tool For Data Services Supporting The Twin Transition 循环数据服务卡：支持双转换的数据服务的基于卡片的构思工具

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.150

Gert Breitfuss , Lilia Yang , Viktoria Pammer-Schindler , Leonie Disch

{"title":"Circular Data Service Cards: A Card-Based Ideation Tool For Data Services Supporting The Twin Transition","authors":"Gert Breitfuss , Lilia Yang , Viktoria Pammer-Schindler , Leonie Disch","doi":"10.1016/j.procs.2025.01.150","DOIUrl":"10.1016/j.procs.2025.01.150","url":null,"abstract":"<div><div>The Twin Transition encompasses the progression of both digital and green transformations. The integration of data science, data analytics, and data services with Industry 4.0 principles significantly enhances the operational efficiency, decision-making, and sustainability of manufacturing systems. In the context of green transformation, Circular Economy (CE) business models aim to optimize resource use and reduce environmental impact. The development of data services and the application of artificial intelligence (AI) are essential for CE, as these technologies improve efficiency, traceability, and resource optimization. This paper presents the development process of the Circular Data Service Cards (DSC), an extension card set (20 newly designed cards, one new category) to the existing Data Service Cards (50 cards, grouped into 5 categories) to assist the co-creation process in developing data services that support the circular economy. The cards address the challenges of interdisciplinary collaboration (user-centered service design, data science and circular economy) and varying expertise levels essential for building a circular data-driven business. Alongside the developed sub-categories (new cards), the outcomes of this study provide a valuable enhancement of the existing DSC. Initial evaluation results indicate that the Circular DSC are perceived as both useful and user-friendly. This research contributes to the twin transition by providing an actionable tool to support the digital transformation and the development of circular data-driven services.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"253 ","pages":"Pages 882-891"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480510","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}

引用次数: 0

Classification of Sarcoma Based on Genomic Data Using Machine Learning Models 基于基因组数据的肉瘤分类使用机器学习模型

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2024.12.034

Pratham Gala , Yash Pandloskar , Shubham Godbole , Fayed Hakim , Pratik Kanani , Lakshmi Kurup

{"title":"Classification of Sarcoma Based on Genomic Data Using Machine Learning Models","authors":"Pratham Gala , Yash Pandloskar , Shubham Godbole , Fayed Hakim , Pratik Kanani , Lakshmi Kurup","doi":"10.1016/j.procs.2024.12.034","DOIUrl":"10.1016/j.procs.2024.12.034","url":null,"abstract":"<div><div>The proposed work provides a new machine-learnt classification approach for the various types of soft tissue sarcoma based on genomics data which addresses a considerable gap in sarcoma diagnostics. The previous studies have investigated various aspects of sarcoma but this study is unique in that it targets the predicting sarcoma variant types using genetic information, which has not been done before. Random Forest was used as the meta-estimator and a stacking ensemble model comprising of Random Forest, Extreme Gradient Boosting and LightGBM were used for this study. The model which was trained and validated on a complete dataset of 206 adult soft tissue sarcoma samples containing genomic alterations, transcriptomic, epigenomic and proteomic data achieved an accuracy of 89.44% at a precision level as high as 91%. Stratified k-fold cross validation is employed to ensure that class imbalance is not a hindrance to performance. This innovative approach outmatches single classifiers and traditional single model methods at great length hence making it possible and effective to use machine learning on genomic data for predicting sarcoma variants. Thus, the findings from this research could change cancer diagnosis forever; they promise more accurate classification as well as personalized treatment modalities while also providing a framework for analogous applications in other rare complex cancers.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"252 ","pages":"Pages 317-330"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376667","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}

引用次数: 0

Implementation of Multi-Label Fuzzy Classification System using Topic Detection Data set 基于主题检测数据集的多标签模糊分类系统实现

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2024.12.003

R. Kanagaraj , N. Krishnaraj , J. Selvakumar , J. Ramprasath

{"title":"Implementation of Multi-Label Fuzzy Classification System using Topic Detection Data set","authors":"R. Kanagaraj , N. Krishnaraj , J. Selvakumar , J. Ramprasath","doi":"10.1016/j.procs.2024.12.003","DOIUrl":"10.1016/j.procs.2024.12.003","url":null,"abstract":"<div><div>Multiclass Classification can be implemented by using consequent approaches to translate the multiclass problem into binary class classification problems and fuzzy classification methods. This work proposes a predictive analysis of the multiclass fuzzy Classification integrated with time series historical data and topic detection. The fuzzy classification techniques can be successfully applied to Topic detection and sub-topic detection. Text databases’ manual topic detection method must be more feasible, uncontrollable and effective. Thus, initiating the huge amount of data implemented by manual methods is idealistic. Fuzzy historical data is more significant for data analysis in different models to make predictions. Innumerable fuzzy logic on time series methods has been implemented for data prediction. A Multiclass Fuzzy Time Series Classification Algorithm has been implemented to analyze and predict the topic detection database. The outcomes of the Fuzzy classification technique have been implemented for the need for an extensive pattern of topic detection. An enhanced Multiclass Fuzzy Time Series Classification Algorithm has been applied to achieve the efficient de-fuzzification operation of the topic detection data set. To illuminate the forecasting method, the historical data of multi-labeled has been used for the predictive model. The investigation result illustrates that the MHTSC algorithm generates mode fuzzy classification and irregular rules, efficiently reducing the error rate from multi-labeled data.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"252 ","pages":"Pages 15-24"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376844","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}

引用次数: 0

A GAN-Enhanced Multimodal Diagnostic Framework Utilizing an Ensemble of BiLSTM, BiGRU, and RNN Models for Malaria and Dengue Detection 利用BiLSTM， BiGRU和RNN模型集成的gan增强多模态诊断框架用于疟疾和登革热检测

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2024.12.039

Rathnakar Achary, Chetan J Shelke, Alluru Lekhya

{"title":"A GAN-Enhanced Multimodal Diagnostic Framework Utilizing an Ensemble of BiLSTM, BiGRU, and RNN Models for Malaria and Dengue Detection","authors":"Rathnakar Achary, Chetan J Shelke, Alluru Lekhya","doi":"10.1016/j.procs.2024.12.039","DOIUrl":"10.1016/j.procs.2024.12.039","url":null,"abstract":"<div><div>Quick detection of Malaria and Dengue is crucial for doctors to start treatment and manage patients effectively. As patient conditions become more complex with overlapping symptoms, traditional diagnostic tools become inefficient, slow, and less accurate. Modernizing diagnostics with AI-powered systems is essential. Inaccurate or delayed diagnoses lead to transmission and sustained spread of these diseases. Improving diagnostic tools with accuracy, precision, recall, and speed enhances patient outcomes, reduces infection spread, and streamlines health sector operations. Despite advances, current diagnostic algorithms have weaknesses, especially in applying machine learning to diverse datasets at granular levels. Continuous effort is needed to improve accuracy and recall. This research proposes a GAN-Based Synthesized Multimodal Diagnostic System, combining BiLSTM, BiGRU, and RNN approaches. Utilizing GANs for data augmentation and recurrent networks, this framework shows innovative infectious disease detection. It improves diagnostic precision by 4.9%, accuracy by 3.5%, recall by 3.5%, and AUC by 4.5%, while reducing the gap between disease progression and detection by 8.3%. These outcomes can reduce triage time, misdiagnoses, and lead to faster, quality healthcare. The GAN-Enhanced Multimodal Diagnostic Framework shows promise for diagnosing Malaria, Dengue, and other infectious diseases.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"252 ","pages":"Pages 381-393"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376857","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}

引用次数: 0

Stray Dog Detection System using YOLOv5 使用YOLOv5的流浪狗检测系统

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.041

Ashwini Bhosale , Pranav Shinde , Yash Firke , Shivprasad Patil , Pranav Mitake , Samruddhi Shinde

{"title":"Stray Dog Detection System using YOLOv5","authors":"Ashwini Bhosale , Pranav Shinde , Yash Firke , Shivprasad Patil , Pranav Mitake , Samruddhi Shinde","doi":"10.1016/j.procs.2025.01.041","DOIUrl":"10.1016/j.procs.2025.01.041","url":null,"abstract":"<div><div>Stray dogs present significant public health and safety risks, particularly in developing countries like India, where the stray dog population is the largest globally. This paper details the implementation of a Stray Dog Detection System using the YOLOv5 object detection model to automatically detect and track stray dogs in real time via CCTV feeds. YOLOv5’s high accuracy and real-time processing capabilities make it well-suited for detecting stray dogs in complex, crowded urban environments. The system leverages a YOLOv5 model trained on custom datasets tailored to local conditions, including specific dog breeds and deployment environments. It integrates an alert mechanism that triggers when stray dog populations surpass predefined thresholds, allowing timely interventions. Additionally, the system incorporates geographic mapping to provide data-driven insights for municipal authorities to manage stray populations effectively and ethically. Experimental results demonstrate an F1 score of 0.97, validating the system’s robustness for practical deployment. This paper discusses system architecture, implementation, and performance, highlighting its scalability and cost-effectiveness for humane stray dog population control.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"252 ","pages":"Pages 806-813"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376863","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}

引用次数: 0

Influencer Ranking Framework Using TH-DCNN for influence maximization 使用TH-DCNN实现影响力最大化的影响者排名框架

Procedia Computer Science Pub Date : 2025-01-01 DOI: 10.1016/j.procs.2025.01.018

Vishakha Shelke , Ashish Jadhav Dr.

{"title":"Influencer Ranking Framework Using TH-DCNN for influence maximization","authors":"Vishakha Shelke , Ashish Jadhav Dr.","doi":"10.1016/j.procs.2025.01.018","DOIUrl":"10.1016/j.procs.2025.01.018","url":null,"abstract":"<div><div>As the influencer gains more significance in social media marketing, companies raise their budgets for influencer campaigns. With business increasing day by day, finding efficient influencers is becoming the most prominent factor for success, but choosing the right influencer from these social media users is quite a challenge. This manuscript proposes a novel method to rank influencers by their effectiveness based on their posting behavior and social relations over time. Initially, the data from Twitter is collected from the Indian politics tweets and reactions dataset. This raw data undergoes preprocessing using various techniques including, tokenization, stemming, lemmatization, stop word removal, and data normalization using the Min-Max normalization approach to ensure the data is relevant and suitable format for analysis. Next, construct a heterogeneous network to represent the complex interactions between entities like users, tweets, hashtags, and mentions. Then Tree Hierarchical Deep Convolutional Neural Network (TH-DCNN) is applied to these networks to derive information representation for each influencer at each period. Finally, a Cosine similarity (CS) is used to learn from the network and predict the influencer rankings. The performance metrics such as accuracy, f1-score, mean average precision (MAP), Normalized Discounted Cumulative Gain (NDCG), Receiver Operating characteristic (ROC), Mean Reciprocal Rank (MRR), and Hit Rate are analyzed in experimental evaluations. The proposed method improved the accuracy compared with existing techniques.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"252 ","pages":"Pages 583-592"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143376898","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}

引用次数: 0