Pub Date : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-116
G. Villavicencio
In this paper we set out the idea that the text plain nature of the software source code, as we know it today, is a strong obstacle for an effective maintenance. The reason is that all the software artifact elements, from the most complex to the simplest, are immediately available to the maintenance programmer. Such ease is deceitful since it allows the maintenance programmer to modify any component in any order. However, maintenance in any engineering field is inside-out intrinsically, and such essential characteristic should also be held in software maintenance. The maintenance scenario suggested here restricts modifications by the maintenance programmer and drives her to implement them following an order.
{"title":"Toward Ordering the Set of Modifications to Solve a Maintenance Request","authors":"G. Villavicencio","doi":"10.1109/COMPSAC48688.2020.0-116","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-116","url":null,"abstract":"In this paper we set out the idea that the text plain nature of the software source code, as we know it today, is a strong obstacle for an effective maintenance. The reason is that all the software artifact elements, from the most complex to the simplest, are immediately available to the maintenance programmer. Such ease is deceitful since it allows the maintenance programmer to modify any component in any order. However, maintenance in any engineering field is inside-out intrinsically, and such essential characteristic should also be held in software maintenance. The maintenance scenario suggested here restricts modifications by the maintenance programmer and drives her to implement them following an order.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115862792","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-142
Zheng Li, Xuewei Bai, Haifeng Wang, Yong Liu
Identifying the location of faults in real-world programs is one of the most costly processes during software debugging. In order to reduce debugging effort, many fault localization techniques have been proposed. One of the most widely studied technique is called Spectrum-based fault localization (SBFL), which uses the coverage information and execution results of test cases to do fault localization. Most SBFL techniques only consider the binary coverage information and ignore the execution frequency, so their fault localization accuracy is limited, especially when faults occur in the iteration entities or loop bodies. In this paper, we propose IRBFL, a novel fault localization technique based on information retrieval to extract information from execution frequencies of program entities. IRBFL uses mutation analysis to reduce the low suspicious classes, and then it adopts information retrieval techniques to calculate the suspiciousness value. We evaluate IRBFL on 205 real-world faults from 5 programs in Defects4J benchmark. The experimental results show that our proposed method outperforms the other five state-of-the-art SBFL techniques. More specifically, no matter in single-fault or multi-fault programs, IRBFL can identify 2 to 3 times more faulty methods than the other five SBFL techniques when checking the top 1 method. More empirical results in terms of other metrics, including acc@3, acc@5, EXAM, MRR, and MAP, also indicate that IRBFL technique is better than the other five SBFL techniques.
{"title":"IRBFL: An Information Retrieval Based Fault Localization Approach","authors":"Zheng Li, Xuewei Bai, Haifeng Wang, Yong Liu","doi":"10.1109/COMPSAC48688.2020.0-142","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-142","url":null,"abstract":"Identifying the location of faults in real-world programs is one of the most costly processes during software debugging. In order to reduce debugging effort, many fault localization techniques have been proposed. One of the most widely studied technique is called Spectrum-based fault localization (SBFL), which uses the coverage information and execution results of test cases to do fault localization. Most SBFL techniques only consider the binary coverage information and ignore the execution frequency, so their fault localization accuracy is limited, especially when faults occur in the iteration entities or loop bodies. In this paper, we propose IRBFL, a novel fault localization technique based on information retrieval to extract information from execution frequencies of program entities. IRBFL uses mutation analysis to reduce the low suspicious classes, and then it adopts information retrieval techniques to calculate the suspiciousness value. We evaluate IRBFL on 205 real-world faults from 5 programs in Defects4J benchmark. The experimental results show that our proposed method outperforms the other five state-of-the-art SBFL techniques. More specifically, no matter in single-fault or multi-fault programs, IRBFL can identify 2 to 3 times more faulty methods than the other five SBFL techniques when checking the top 1 method. More empirical results in terms of other metrics, including acc@3, acc@5, EXAM, MRR, and MAP, also indicate that IRBFL technique is better than the other five SBFL techniques.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116180523","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00040
Johannes Nau, Johannes Richter, Detlef Streitferdt, M. Kirchhoff
The inspection of printed circuit board assemblies gradually incorporates deep-learning-based classifiers. However, such classifiers require a vast dataset. To our knowledge, such a dataset is not available. This paper proposes a method to simulate the assembly process aiming at generating such a dataset. The simulation of the solder joint shape forming during reflow and the creation of a photorealistic rendering of the assembled board have the most significant impact on the visual appearance of the results. Therefore, this paper focuses on the simulation of these steps. The calculation of the solder joint shape requires minimizing the surface tension energy. For this, the algorithm discretizes the energy equations over a heightmap. The proposed software architecture for the simulation is highly extendable and facilitate future development. Experiments with the simulation of solder joints of a chip resistor show a remarkable similarity to real images from an automatic optical inspection machine.
{"title":"Simulating the Printed Circuit Board Assembly Process for Image Generation","authors":"Johannes Nau, Johannes Richter, Detlef Streitferdt, M. Kirchhoff","doi":"10.1109/COMPSAC48688.2020.00040","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00040","url":null,"abstract":"The inspection of printed circuit board assemblies gradually incorporates deep-learning-based classifiers. However, such classifiers require a vast dataset. To our knowledge, such a dataset is not available. This paper proposes a method to simulate the assembly process aiming at generating such a dataset. The simulation of the solder joint shape forming during reflow and the creation of a photorealistic rendering of the assembled board have the most significant impact on the visual appearance of the results. Therefore, this paper focuses on the simulation of these steps. The calculation of the solder joint shape requires minimizing the surface tension energy. For this, the algorithm discretizes the energy equations over a heightmap. The proposed software architecture for the simulation is highly extendable and facilitate future development. Experiments with the simulation of solder joints of a chip resistor show a remarkable similarity to real images from an automatic optical inspection machine.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116310444","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}
Emerging byte-addressable non-volatile memory (NVM) has the advantages of fast, cheap and persistent, and is considered as the next generation of persistent memory. However, existing NVM-based filesystems cannot adapt well for mobile devices, and not to mention the consideration for mobile application characteristics. In this paper, we propose an efficient and durable in-memory file system named as Mobi-PMFS for mobile devices. Proposed Mobi-PMFS is not only adaptive to ARM architecture, but also customized according to mobile application features. A wear-aware three-list space management scheme including a switching allocation algorithm is proposed to provide optimum performance for mobile systems while keeping the durability of NVM. Experimental results show that Mobi-PMFS is 8x times and 1.2x faster than EXT4-SSD and EXT4-DAX, and provides 11x wear-leveling improvement compared with the original PMFS.
{"title":"Mobi-PMFS: An Efficient and Durable In-Memory File System for Mobile Devices","authors":"Chunhua Xiao, Fangzhu Lin, Xiaoxiang Fu, Ting Wu, Yuanjun Zhu, Weichen Liu","doi":"10.1109/COMPSAC48688.2020.00286","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00286","url":null,"abstract":"Emerging byte-addressable non-volatile memory (NVM) has the advantages of fast, cheap and persistent, and is considered as the next generation of persistent memory. However, existing NVM-based filesystems cannot adapt well for mobile devices, and not to mention the consideration for mobile application characteristics. In this paper, we propose an efficient and durable in-memory file system named as Mobi-PMFS for mobile devices. Proposed Mobi-PMFS is not only adaptive to ARM architecture, but also customized according to mobile application features. A wear-aware three-list space management scheme including a switching allocation algorithm is proposed to provide optimum performance for mobile systems while keeping the durability of NVM. Experimental results show that Mobi-PMFS is 8x times and 1.2x faster than EXT4-SSD and EXT4-DAX, and provides 11x wear-leveling improvement compared with the original PMFS.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123663802","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-12
Nadiyah Johnson, Joseph Coelho, Md Fitrat Hossain, Thomas Kissane, Wylie Frydrychowi, Madiraju Praveen, Zeno Franco, Katinka Hooyer, Priyanka Annapureddy, Sheikh Iqbal Ahamed
Millions of US service members have been deployed to Iraq and Afghanistan over the past decade. When returning home, many veterans experience difficulties reintegrating into civilian society. Veterans are often faced with challenges finding employment, completing higher education and reconnecting to friends and family. These challenges often result in or exacerbate existing mental health issues. Post-Traumatic Stress Disorder (PTSD) is a mental disorder that impacts between 15-20% of veterans. It is a national priority to find innovative solutions to PTSD experienced by veterans returning from their duty. There is very little research on identifying Angry Outburst (AOB) specific pre-crisis data in social media posts, within the veteran community, as a preventative measure against escalated at-risk behavior and negative outcomes. In this paper, we outline a threephase approach to identify veteran AOB specific pre-crisis text data. The key objective of our study is to examine twitter posts to reveal how anger is expressed by both the veteran population and civilians. We identify a lexicon of terms that are more common among veterans with PTSD prone to AOB. Our study emphasizes the difference in language used on social media between both veteran and civilian population. We expand the knowledge base of AOB specific pre-crisis events on social media within veteran communities. This research will contribute to a broader study on building preventative mHealth systems to combat PTSD in veterans.
{"title":"Understanding Veterans Expression of Anger Using Social Media Analysis","authors":"Nadiyah Johnson, Joseph Coelho, Md Fitrat Hossain, Thomas Kissane, Wylie Frydrychowi, Madiraju Praveen, Zeno Franco, Katinka Hooyer, Priyanka Annapureddy, Sheikh Iqbal Ahamed","doi":"10.1109/COMPSAC48688.2020.00-12","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-12","url":null,"abstract":"Millions of US service members have been deployed to Iraq and Afghanistan over the past decade. When returning home, many veterans experience difficulties reintegrating into civilian society. Veterans are often faced with challenges finding employment, completing higher education and reconnecting to friends and family. These challenges often result in or exacerbate existing mental health issues. Post-Traumatic Stress Disorder (PTSD) is a mental disorder that impacts between 15-20% of veterans. It is a national priority to find innovative solutions to PTSD experienced by veterans returning from their duty. There is very little research on identifying Angry Outburst (AOB) specific pre-crisis data in social media posts, within the veteran community, as a preventative measure against escalated at-risk behavior and negative outcomes. In this paper, we outline a threephase approach to identify veteran AOB specific pre-crisis text data. The key objective of our study is to examine twitter posts to reveal how anger is expressed by both the veteran population and civilians. We identify a lexicon of terms that are more common among veterans with PTSD prone to AOB. Our study emphasizes the difference in language used on social media between both veteran and civilian population. We expand the knowledge base of AOB specific pre-crisis events on social media within veteran communities. This research will contribute to a broader study on building preventative mHealth systems to combat PTSD in veterans.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"265 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121895851","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-91
Priscila M. Kai, R. M. Costa, Bruna M. de Oliveira, D. Fernandes, J. P. Félix, Fabrízzio Soares
Remote sensing techniques by satellite imagery have been widely applied in various fields of agrarian sciences due to allowing real-time information, allowing data retention in a given region without the need for displacement, avoiding costs, and also enabling the creation of more efficient methods for the task of monitoring crops. In special to remote sensing applied to sugarcane varietal identification, the possibility of discrimination among the varieties is important due to allows the monitoring of the crop growth concerning characteristics by plants, measures controls, and the preservation of copyright of developed varieties. Among the researches involving studies with sugar cane regarding varietal identification, the purpose of the paper implies to present a review of the literature, conferring methods, and checking state of the art about the subject of discrimination of sugarcane varieties by remote sensing.
{"title":"Discrimination of Sugarcane Varieties by Remote Sensing: A Review of Literature","authors":"Priscila M. Kai, R. M. Costa, Bruna M. de Oliveira, D. Fernandes, J. P. Félix, Fabrízzio Soares","doi":"10.1109/COMPSAC48688.2020.00-91","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-91","url":null,"abstract":"Remote sensing techniques by satellite imagery have been widely applied in various fields of agrarian sciences due to allowing real-time information, allowing data retention in a given region without the need for displacement, avoiding costs, and also enabling the creation of more efficient methods for the task of monitoring crops. In special to remote sensing applied to sugarcane varietal identification, the possibility of discrimination among the varieties is important due to allows the monitoring of the crop growth concerning characteristics by plants, measures controls, and the preservation of copyright of developed varieties. Among the researches involving studies with sugar cane regarding varietal identification, the purpose of the paper implies to present a review of the literature, conferring methods, and checking state of the art about the subject of discrimination of sugarcane varieties by remote sensing.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128366119","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-75
Zimo Zhu, A. Thavaneswaran, Alex Paseka, J. Frank, R. Thulasiram
Recently there has been a growing interest in using machine learning methods with empirical variance covariance matrix of returns to study Markovitz portfolio optimization. The statistical technique of graphical LASSO (GL) for stock selection in the portfolio assumes that the asset returns are normally distributed, independent random variables with constant variance. In this paper sign correlations and the autocorrelations of the absolute values of the returns are used to show that the returns are non-normal with time-varying volatility. We use the recently proposed data-driven exponentially weighted moving average (DDEWMA) volatility model to estimate the covariance matrix of asset returns in Markowitz portfolio optimization. Empirical results with big data (consists of 444 stocks for a period of 7 years downloaded from Yahoo Finance) show that the proposed DDEWMA variance covariance matrix model outperforms (larger Sharpe ratio) the model with empirical variance covariance matrix.
{"title":"Portfolio Optimization Using a Novel Data-Driven EWMA Covariance Model with Big Data","authors":"Zimo Zhu, A. Thavaneswaran, Alex Paseka, J. Frank, R. Thulasiram","doi":"10.1109/COMPSAC48688.2020.00-75","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-75","url":null,"abstract":"Recently there has been a growing interest in using machine learning methods with empirical variance covariance matrix of returns to study Markovitz portfolio optimization. The statistical technique of graphical LASSO (GL) for stock selection in the portfolio assumes that the asset returns are normally distributed, independent random variables with constant variance. In this paper sign correlations and the autocorrelations of the absolute values of the returns are used to show that the returns are non-normal with time-varying volatility. We use the recently proposed data-driven exponentially weighted moving average (DDEWMA) volatility model to estimate the covariance matrix of asset returns in Markowitz portfolio optimization. Empirical results with big data (consists of 444 stocks for a period of 7 years downloaded from Yahoo Finance) show that the proposed DDEWMA variance covariance matrix model outperforms (larger Sharpe ratio) the model with empirical variance covariance matrix.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128871785","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-93
Jayesh Patel
In the Information Age, Machine learning (ML) provides a competitive advantage to any business. Machine learning applications are not limited to driverless cars or online recommendations but are widely used in healthcare, social services, government systems, telecommunications, and so on. As many enterprises are trying to step up machine learning applications, it is critical to have a long-term strategy. Most of the enterprises are not able to truly realize the fruits of ML capabilities due to its complexity. It is easier to access a variety of data today due to data democratization, distributed storage, technological advancements, and big data applications. Despite easier data access and recent advancements in ML, developers still spend most of the time in data cleansing, data preparation, and data modeling for ML applications. These steps are often repeated and result in identical features. As identical features can have inconsistent processing while testing and training, more issues pop up at later stages in ML application development. The unification of ML features is an effective way to address these issues. This paper presents details about numerous methods to achieve ML features unification.
{"title":"Unification of Machine Learning Features","authors":"Jayesh Patel","doi":"10.1109/COMPSAC48688.2020.00-93","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-93","url":null,"abstract":"In the Information Age, Machine learning (ML) provides a competitive advantage to any business. Machine learning applications are not limited to driverless cars or online recommendations but are widely used in healthcare, social services, government systems, telecommunications, and so on. As many enterprises are trying to step up machine learning applications, it is critical to have a long-term strategy. Most of the enterprises are not able to truly realize the fruits of ML capabilities due to its complexity. It is easier to access a variety of data today due to data democratization, distributed storage, technological advancements, and big data applications. Despite easier data access and recent advancements in ML, developers still spend most of the time in data cleansing, data preparation, and data modeling for ML applications. These steps are often repeated and result in identical features. As identical features can have inconsistent processing while testing and training, more issues pop up at later stages in ML application development. The unification of ML features is an effective way to address these issues. This paper presents details about numerous methods to achieve ML features unification.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132505161","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-178
Guillaume Gingras, Mehdi Adda, A. Bouzouane
Ambient Assisted Living (AAL) in general and Activity Recognition (AR) in particular are active fields of research that aim at assisting people in their Activities of Daily Living (ADL). In recent years, we have seen an increased interest in their applicability to the rural seniors who are slowly losing their autonomy due to aging and chronic diseases. One research venue is to aggregate and seek for correlations between the physiological data that serves to monitor the health of the elderly, their ADLs, their movements and any other data that may be collected about their immediate environment. In this paper, we are tackling the possibility of developing a non-intrusive and affordable system based on embedded health, movement, activity and location sensors. Furthermore, we discuss the main concepts behind the creation of a layered, flexible and highly modular architecture that focuses on how the integration of newly combined sensor data can be achieved. Using a mobile phone application prototype, our work has shown that we can integrate two non-invasive technologies that are not necessarily the newest, but the most affordable, scalable and ready to be deployed in real life settings.
{"title":"Toward a Non-Intrusive, Affordable Platform for Elderly Assistance and Health Monitoring","authors":"Guillaume Gingras, Mehdi Adda, A. Bouzouane","doi":"10.1109/COMPSAC48688.2020.0-178","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-178","url":null,"abstract":"Ambient Assisted Living (AAL) in general and Activity Recognition (AR) in particular are active fields of research that aim at assisting people in their Activities of Daily Living (ADL). In recent years, we have seen an increased interest in their applicability to the rural seniors who are slowly losing their autonomy due to aging and chronic diseases. One research venue is to aggregate and seek for correlations between the physiological data that serves to monitor the health of the elderly, their ADLs, their movements and any other data that may be collected about their immediate environment. In this paper, we are tackling the possibility of developing a non-intrusive and affordable system based on embedded health, movement, activity and location sensors. Furthermore, we discuss the main concepts behind the creation of a layered, flexible and highly modular architecture that focuses on how the integration of newly combined sensor data can be achieved. Using a mobile phone application prototype, our work has shown that we can integrate two non-invasive technologies that are not necessarily the newest, but the most affordable, scalable and ready to be deployed in real life settings.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131980788","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00023
A. R. Svaigen, L. M. Bine, W. I. S. Bine, L. B. Ruiz
This paper proposes the MannAccess, a novel low cost assistive educational tool of digital image for Visually Impaired (VI), aiding the teaching-learning process of visual content. It consists of an assistive environment composed of interactive software and a refreshable pin display with a novel 3-axis pin activation mechanism, decreasing its development cost substantially. The MannAccess allows the integration with different image recognition methods using a proposed image intermediary representation. In order to accomplish evaluations, we developed a prototype of MannAccess and integrated it with MannAR, an automata image recognition method. We carried out experiments with VI students which pointed out that our tool provided proper accessibility, usability, and user experience. In addition, we accomplished a monetary cost evaluation, indicating that MannAccess had the most accessible monetary cost compared to related devices. In a nutshell, MannAccess showed that it is possible to develop a low-cost assistive technology to aid the VI visual content education, integrating different image recognition methods in a single assistive tool.
{"title":"MannAccess: A Novel Low Cost Assistive Educational Tool of Digital Image for Visually Impaired","authors":"A. R. Svaigen, L. M. Bine, W. I. S. Bine, L. B. Ruiz","doi":"10.1109/COMPSAC48688.2020.00023","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00023","url":null,"abstract":"This paper proposes the MannAccess, a novel low cost assistive educational tool of digital image for Visually Impaired (VI), aiding the teaching-learning process of visual content. It consists of an assistive environment composed of interactive software and a refreshable pin display with a novel 3-axis pin activation mechanism, decreasing its development cost substantially. The MannAccess allows the integration with different image recognition methods using a proposed image intermediary representation. In order to accomplish evaluations, we developed a prototype of MannAccess and integrated it with MannAR, an automata image recognition method. We carried out experiments with VI students which pointed out that our tool provided proper accessibility, usability, and user experience. In addition, we accomplished a monetary cost evaluation, indicating that MannAccess had the most accessible monetary cost compared to related devices. In a nutshell, MannAccess showed that it is possible to develop a low-cost assistive technology to aid the VI visual content education, integrating different image recognition methods in a single assistive tool.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132260256","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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