Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627444
Cuiling Li, Xiaofang Deng, Huiping Qin, Lin Zheng, Hongbing Qiu
Mobile edge computing(MEC)brings, besides various opportunities, challenges for the resource allocation. The heterogeneity of resources in multiple cells further exacerbates this challenge. For efficient resource utilization, in this paper, MEC is combined with cognitive radios (CRs) to improve better adaptation. In such a context, a computing offload and resource allocation mechanism is proposed, which can be formulated as user pairing scheme based on coalition game. Such an algorithm first match applicable neighbors for each secondary user(SU) in terms of pairing utility.then, compete optimal resources to computing offload within the cognitive edge computing, considering multiple optimization objectives that are derived from user needs. To obtain the optimal network welfare, a gradient descent algorithm of machine learning is proposed to acquire the near-optimal solution. The results of multiple runs of our simulation demonstrate that the algorithm is efficient, which can show better performance in terms of the network welfare compared to existing resource allocation algorithms.
{"title":"Joint Task offload and Resource Allocation for Cognitive Edge Computing Using AI Algorithm","authors":"Cuiling Li, Xiaofang Deng, Huiping Qin, Lin Zheng, Hongbing Qiu","doi":"10.1109/icisfall51598.2021.9627444","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627444","url":null,"abstract":"Mobile edge computing(MEC)brings, besides various opportunities, challenges for the resource allocation. The heterogeneity of resources in multiple cells further exacerbates this challenge. For efficient resource utilization, in this paper, MEC is combined with cognitive radios (CRs) to improve better adaptation. In such a context, a computing offload and resource allocation mechanism is proposed, which can be formulated as user pairing scheme based on coalition game. Such an algorithm first match applicable neighbors for each secondary user(SU) in terms of pairing utility.then, compete optimal resources to computing offload within the cognitive edge computing, considering multiple optimization objectives that are derived from user needs. To obtain the optimal network welfare, a gradient descent algorithm of machine learning is proposed to acquire the near-optimal solution. The results of multiple runs of our simulation demonstrate that the algorithm is efficient, which can show better performance in terms of the network welfare compared to existing resource allocation algorithms.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131490360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627426
Yi Zhao, Yun Hu, Jiayu Gong
Software industry is a key force leading a new round of technological revolution and occupies an important position in the development of the global economy. Software quality is of great significance to promote the healthy and orderly development of the software industry, and software testing is also a reliable means to ensure software quality. Standardization as a technical means to regulate software quality and software testing, can improve software product quality, reduce software development and testing costs. It can also provide guidance and support for the development of the software industry. This paper gives a detailed description of the international standardization of software quality and software testing and analyzes the relationship between software quality and software testing. Finally, it summarizes the problems and suggestions of software quality and testing standards. This paper is beneficial for demanders, developers, independent evaluation parties, quality assurance and control personnel to understand and use the relevant standards of software quality and testing.
{"title":"Research on International Standardization of Software Quality and Software Testing","authors":"Yi Zhao, Yun Hu, Jiayu Gong","doi":"10.1109/icisfall51598.2021.9627426","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627426","url":null,"abstract":"Software industry is a key force leading a new round of technological revolution and occupies an important position in the development of the global economy. Software quality is of great significance to promote the healthy and orderly development of the software industry, and software testing is also a reliable means to ensure software quality. Standardization as a technical means to regulate software quality and software testing, can improve software product quality, reduce software development and testing costs. It can also provide guidance and support for the development of the software industry. This paper gives a detailed description of the international standardization of software quality and software testing and analyzes the relationship between software quality and software testing. Finally, it summarizes the problems and suggestions of software quality and testing standards. This paper is beneficial for demanders, developers, independent evaluation parties, quality assurance and control personnel to understand and use the relevant standards of software quality and testing.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130420213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627409
Lipeng Gao, Sitong Sun, Fei Wang, Jun Zhu, Peng Luo
This paper proposed a novel approach for extracting road centerlines in the urban area. The proposed approach consists of three main blocks: (1) DSM data are added to the available high resolution remote sensing images (HRRSI) and the two types of data are fused by the Gram-Schmidt transformation; (2) A hierarchical road extraction method is proposed to extract the road centerlines. (3) Finally, an improved road trimming (IRT) algorithm is implemented for road centerline refining. Experimental results on four datasets show that the proposed method obtains competitively satisfactory results.
{"title":"A Gram-Schmidt Transformation-based Hierarchical Urban Road Centerline Extraction Method","authors":"Lipeng Gao, Sitong Sun, Fei Wang, Jun Zhu, Peng Luo","doi":"10.1109/icisfall51598.2021.9627409","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627409","url":null,"abstract":"This paper proposed a novel approach for extracting road centerlines in the urban area. The proposed approach consists of three main blocks: (1) DSM data are added to the available high resolution remote sensing images (HRRSI) and the two types of data are fused by the Gram-Schmidt transformation; (2) A hierarchical road extraction method is proposed to extract the road centerlines. (3) Finally, an improved road trimming (IRT) algorithm is implemented for road centerline refining. Experimental results on four datasets show that the proposed method obtains competitively satisfactory results.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115565241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627338
Jianxiang Cao, Miaoran Song, Wenqian Shang
Copyright infringements in the digital age are common, copyright detection plays an effective role in protecting copyright, and the results are often retained as evidence of infringement appeals. In this paper, we proposed a video copyright detection scheme combining on-chain and off-chain based on blockchain technology for the problems of undisclosed digital copyright detection process leading to unreliable and unverifiable results. Firstly, the feature fingerprints of the key frames are extracted from the video content under the blockchain, and then the smart contract was called to automatically perform copyright detection on the blockchain to ensure the originality of the copyrighted work and the verifiability of the detection result. Finally, the video feature value is permanently and immutably stored on the blockchain. Experimental results show that invoking the smart contract on the chain to automatically compare can not only ensure the accuracy rate, but also obtain credible detection results, ensure the transparency and fairness of the results, and also prove the feasibility of the scheme.
{"title":"Blockchain-Based Video Copyright Detection","authors":"Jianxiang Cao, Miaoran Song, Wenqian Shang","doi":"10.1109/icisfall51598.2021.9627338","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627338","url":null,"abstract":"Copyright infringements in the digital age are common, copyright detection plays an effective role in protecting copyright, and the results are often retained as evidence of infringement appeals. In this paper, we proposed a video copyright detection scheme combining on-chain and off-chain based on blockchain technology for the problems of undisclosed digital copyright detection process leading to unreliable and unverifiable results. Firstly, the feature fingerprints of the key frames are extracted from the video content under the blockchain, and then the smart contract was called to automatically perform copyright detection on the blockchain to ensure the originality of the copyrighted work and the verifiability of the detection result. Finally, the video feature value is permanently and immutably stored on the blockchain. Experimental results show that invoking the smart contract on the chain to automatically compare can not only ensure the accuracy rate, but also obtain credible detection results, ensure the transparency and fairness of the results, and also prove the feasibility of the scheme.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"411 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115998112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627463
Shikang Nie, Guangting Li, Xin Liu, Xin Zhang, Chenchen Lin, Yifeng He
This paper discusses in detail the development of several research hotspots of Low-Density Parity Check (LDPC) codes and their joint optimization design with other communication technologies, and points out that LDPC codes have broad development and application space in the future communication field.
{"title":"Research on LDPC channel coding technology in satellite communication system","authors":"Shikang Nie, Guangting Li, Xin Liu, Xin Zhang, Chenchen Lin, Yifeng He","doi":"10.1109/icisfall51598.2021.9627463","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627463","url":null,"abstract":"This paper discusses in detail the development of several research hotspots of Low-Density Parity Check (LDPC) codes and their joint optimization design with other communication technologies, and points out that LDPC codes have broad development and application space in the future communication field.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125004749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627454
Taozheng Zhang, Chen Shang
Nowadays, bidirectional long short-term memory neural network(Bi-LSTM) becomes the main structure for Chinese word segmentation tasks, which can obtain text information with time series. As a sequence model, the training speed of Bi-STM is very slow, while dilated convolution neural networks(DCNN) have a natural advantage in it which is designed to obtain information with a long length. In this paper, the sub-character information is concatenated with the ordinary features to enrich the input. Multiple contrast experiments are designed to verify the effect of applying DCNN and adding Conditional Random Fields (CRF). Experiments on the four datasets in SIGHAN2005 show that DCNN structure can improve the word segmentation effect in terms of F1 value and efficiency. The main advantage of the DCNN is that the speed is greatly faster than Bi-LSTM.
目前，双向长短期记忆神经网络(Bi-LSTM)已成为汉语分词任务的主要结构，它可以获取具有时间序列的文本信息。作为一种序列模型，Bi-STM的训练速度非常慢，而扩展卷积神经网络(DCNN)在获取长长度信息方面具有天然的优势。本文将子字符信息与普通特征进行串联，丰富了输入内容。设计了多个对比实验来验证应用DCNN和添加条件随机场(Conditional Random field, CRF)的效果。在SIGHAN2005中四个数据集上的实验表明，DCNN结构可以在F1值和效率方面提高分词效果。DCNN的主要优点是速度比Bi-LSTM快得多。
{"title":"Chinese Word Segmentation for Sub-character Representation","authors":"Taozheng Zhang, Chen Shang","doi":"10.1109/icisfall51598.2021.9627454","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627454","url":null,"abstract":"Nowadays, bidirectional long short-term memory neural network(Bi-LSTM) becomes the main structure for Chinese word segmentation tasks, which can obtain text information with time series. As a sequence model, the training speed of Bi-STM is very slow, while dilated convolution neural networks(DCNN) have a natural advantage in it which is designed to obtain information with a long length. In this paper, the sub-character information is concatenated with the ordinary features to enrich the input. Multiple contrast experiments are designed to verify the effect of applying DCNN and adding Conditional Random Fields (CRF). Experiments on the four datasets in SIGHAN2005 show that DCNN structure can improve the word segmentation effect in terms of F1 value and efficiency. The main advantage of the DCNN is that the speed is greatly faster than Bi-LSTM.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131070312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627356
Wei Niu, Wei Huang, Juan Cheng
Aiming at the characteristics of large heterogeneity and strong time constraint of airborne electromechanical system, an electromechanical event model and collaborative modeling method based on CPS is proposed. According to the complex characteristics of electrical, gas and hydraulic components of electromechanical system, the model describes the time and space information, proposes the system modeling and processing based on event response, adopts a unified model to capture all kinds of events in electromechanical CPS application, and provides upper level services across applications and data sources, The problem of semantic diversity of spatiotemporal data and consistency of interaction semantics of various models in electromechanical CPS system simulation is solved.
{"title":"A Collaborative Modeling Method for Multi -behavior Models of Electromechanical CPS Systems","authors":"Wei Niu, Wei Huang, Juan Cheng","doi":"10.1109/icisfall51598.2021.9627356","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627356","url":null,"abstract":"Aiming at the characteristics of large heterogeneity and strong time constraint of airborne electromechanical system, an electromechanical event model and collaborative modeling method based on CPS is proposed. According to the complex characteristics of electrical, gas and hydraulic components of electromechanical system, the model describes the time and space information, proposes the system modeling and processing based on event response, adopts a unified model to capture all kinds of events in electromechanical CPS application, and provides upper level services across applications and data sources, The problem of semantic diversity of spatiotemporal data and consistency of interaction semantics of various models in electromechanical CPS system simulation is solved.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127732056","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}
License plate character segmentation links the function between license plate detection module and character recognition module. Variable-length license plate character segmentation is a challenging task due to the variations of license plate styles. In this paper, our work is focused on the character segmentation task. It is based on the detection results of “Region of Interest(ROI)” detection method. The main contributions include two parts. Firstly, a reference region is estimated according to candidate regions by median statistics of width and height. The reference region is used to compare with all the candidate regions, aiming to remove false positives. Secondly, a redundant region removal method is proposed. It is implemented by removing cross regions which are located at the same location of character. Experimental results on Macau license plates show that the proposed method achieves promising results with 99.37 % segmentation accuracy.
{"title":"Macau License Plate Character Segmentation Through ROI detection and Redundant Region Removal Method","authors":"Bingshu Wang, Yin-Ping Zhao, Jiangbin Zheng, Shuang Feng","doi":"10.1109/icisfall51598.2021.9627479","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627479","url":null,"abstract":"License plate character segmentation links the function between license plate detection module and character recognition module. Variable-length license plate character segmentation is a challenging task due to the variations of license plate styles. In this paper, our work is focused on the character segmentation task. It is based on the detection results of “Region of Interest(ROI)” detection method. The main contributions include two parts. Firstly, a reference region is estimated according to candidate regions by median statistics of width and height. The reference region is used to compare with all the candidate regions, aiming to remove false positives. Secondly, a redundant region removal method is proposed. It is implemented by removing cross regions which are located at the same location of character. Experimental results on Macau license plates show that the proposed method achieves promising results with 99.37 % segmentation accuracy.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130871591","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}
General purpose graphic processor unit (GPGPU) supports various applications' execution in different fields with high-performance computing capability due to its powerful parallel processing architecture. However, GPGPU parallel processing architecture also has the “memory wall” issue. When memory access in application is intensive or irregular, memory resource competition occurs and then degrade the performance of memory system. In addition, with multithreads' requirement for different on-chip resources such as register and warp slot being inconsistant, as well as the branch divergence irregular computing applications, the development of thread level parallelism (TLP) is severely restrited. Due to the restrictions of memory access and TLP, the acceleration capability of GPGPU large-scale parallel processing architecture has not been developed effectively. Alleviating memory resource contention and improving TLP is the performance optimization hotspot for current GPGPU architecture. In this paper we research how memory access optimization and TLP improvement could contribute to the optimization of parallel processing architecture performance. First we find that memory access optimization could be accomplished by three ways: reducing the number of global memory access, improving memory access latency hiding capability and optimizing cache subsystem performance. Then in order to improve TLP, optimizing thread allocation scheme, developing data approximation and redundancy, as well as compacting branch divergence, researches of these three aspects are surveyed. We also analyze the working mechanism, advantages and challenges of each research. At the end, we suggest the direction of future GPGPU parallel processing architecture optimization.
{"title":"A Survey of GPGPU Parallel Processing Architecture Performance Optimization","authors":"Shiwei Jia, Z. Tian, Yueyuan Ma, Chenglu Sun, Yimen Zhang, Yuming Zhang","doi":"10.1109/icisfall51598.2021.9627400","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627400","url":null,"abstract":"General purpose graphic processor unit (GPGPU) supports various applications' execution in different fields with high-performance computing capability due to its powerful parallel processing architecture. However, GPGPU parallel processing architecture also has the “memory wall” issue. When memory access in application is intensive or irregular, memory resource competition occurs and then degrade the performance of memory system. In addition, with multithreads' requirement for different on-chip resources such as register and warp slot being inconsistant, as well as the branch divergence irregular computing applications, the development of thread level parallelism (TLP) is severely restrited. Due to the restrictions of memory access and TLP, the acceleration capability of GPGPU large-scale parallel processing architecture has not been developed effectively. Alleviating memory resource contention and improving TLP is the performance optimization hotspot for current GPGPU architecture. In this paper we research how memory access optimization and TLP improvement could contribute to the optimization of parallel processing architecture performance. First we find that memory access optimization could be accomplished by three ways: reducing the number of global memory access, improving memory access latency hiding capability and optimizing cache subsystem performance. Then in order to improve TLP, optimizing thread allocation scheme, developing data approximation and redundancy, as well as compacting branch divergence, researches of these three aspects are surveyed. We also analyze the working mechanism, advantages and challenges of each research. At the end, we suggest the direction of future GPGPU parallel processing architecture optimization.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114290842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/icisfall51598.2021.9627412
A. Uribe-Quevedo, B. Kapralos, David Rojas Gualdron, A. Dubrowski, Sharman Perera, F. Alam, Simon Xu
The assessment of Virtual reality (VR) applications and serious games often relies on measures of usability, engagement, motion sickness, and cognitive and user performance to determine how the experience was perceived and whether the learning outcomes were met. In addition, physical and physiological information is captured to develop an understanding of behavioral patterns that can help improve the user experience. However, the acquisition of physiological information requires high-end equipment typically exclusive to industry and research institutions, a scenario that is changing as consumer-level VR technology, open electronics, and Makerspace are becoming more readily available. However, VR technology remains exclusive as hardware and interactions assume a one-size- fits-all approach with little customization that accounts for the inherent high user variability. While efforts are currently underway to make VR more inclusive and accessible, the solutions focus on specific user needs. This paper presents the prototyping of a framework consisting of three subsystems for factoring of upper limb ergonomics, skin response, and muscle activity, and gaze tracking as metrics to assist in VR task completion. Due to the preliminary nature of this work, we present a discussion on what we have learned so far through the development of these subsystems applied in three use cases.
{"title":"Physical and Physiological Data for Customizing Immersive VR Training","authors":"A. Uribe-Quevedo, B. Kapralos, David Rojas Gualdron, A. Dubrowski, Sharman Perera, F. Alam, Simon Xu","doi":"10.1109/icisfall51598.2021.9627412","DOIUrl":"https://doi.org/10.1109/icisfall51598.2021.9627412","url":null,"abstract":"The assessment of Virtual reality (VR) applications and serious games often relies on measures of usability, engagement, motion sickness, and cognitive and user performance to determine how the experience was perceived and whether the learning outcomes were met. In addition, physical and physiological information is captured to develop an understanding of behavioral patterns that can help improve the user experience. However, the acquisition of physiological information requires high-end equipment typically exclusive to industry and research institutions, a scenario that is changing as consumer-level VR technology, open electronics, and Makerspace are becoming more readily available. However, VR technology remains exclusive as hardware and interactions assume a one-size- fits-all approach with little customization that accounts for the inherent high user variability. While efforts are currently underway to make VR more inclusive and accessible, the solutions focus on specific user needs. This paper presents the prototyping of a framework consisting of three subsystems for factoring of upper limb ergonomics, skin response, and muscle activity, and gaze tracking as metrics to assist in VR task completion. Due to the preliminary nature of this work, we present a discussion on what we have learned so far through the development of these subsystems applied in three use cases.","PeriodicalId":240142,"journal":{"name":"2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122213540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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