Georgios A. Dafoulas, C. Maia, Almaas A. Ali, J. Augusto, Victor Lopez Cabrera
This paper discusses on-going research in the ways Global Software Engineering (GSE) teams collaborate for a range of software development tasks. The paper focuses on providing the means for observing and understanding GSE team member collaboration including team coordination and member communication. Initially the paper provides the background on social and human issues relating to GSE collaboration. Next the paper describes a pilot study involving a simulation of virtual GSE teams working together with the use of asynchronous and synchronous communication over a virtual learning environment. The study considered the use of multiple data collection techniques recordings of SCRUM meetings, design and implementation tasks. Next, the paper discusses the use of a multi-sensor for observing human and social aspects of project management in GSE teams. The scope of the study is to provide the means for gathering data regarding GSE team coordination for project managers including member emotions, participation pattern in team discussions and potentially stress levels.
{"title":"Understanding Collaboration in Global Software Engineering (GSE) Teams with the Use of Sensors: Introducing a Multi-sensor Setting for Observing Social and Human Aspects in Project Management","authors":"Georgios A. Dafoulas, C. Maia, Almaas A. Ali, J. Augusto, Victor Lopez Cabrera","doi":"10.1109/IE.2017.40","DOIUrl":"https://doi.org/10.1109/IE.2017.40","url":null,"abstract":"This paper discusses on-going research in the ways Global Software Engineering (GSE) teams collaborate for a range of software development tasks. The paper focuses on providing the means for observing and understanding GSE team member collaboration including team coordination and member communication. Initially the paper provides the background on social and human issues relating to GSE collaboration. Next the paper describes a pilot study involving a simulation of virtual GSE teams working together with the use of asynchronous and synchronous communication over a virtual learning environment. The study considered the use of multiple data collection techniques recordings of SCRUM meetings, design and implementation tasks. Next, the paper discusses the use of a multi-sensor for observing human and social aspects of project management in GSE teams. The scope of the study is to provide the means for gathering data regarding GSE team coordination for project managers including member emotions, participation pattern in team discussions and potentially stress levels.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121770799","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}
Kenzhegali Nurgaliyev, D. D. Mauro, Nawaz Khan, J. Augusto
In this work we will examine and develop a system that can assist people in Activities of Daily Life (ADL). This study focuses on resolving conflicts for the requests from different users' profiles, for instance - elderly, adult and young. The objective of the system is to present a dialogue manager which is able to detect multi-user semantic conflict and to resolve the conflict for improved dialogue informing about its decisions using a system interface avatar. The system is also able to prioritize requests that occurred among the services of multiple home appliances, as well as to deal with conflicting entities involving a single device. We investigated whether the multi-user context awareness by a Virtual Assistant adds value to the Smart Home concept in recognizing multi-user conflicts dynamically. This work has proposed a preference based method for resolving conflict and evaluated the developed system in a smart home environment.
{"title":"Improved Multi-user Interaction in a Smart Environment Through a Preference-Based Conflict Resolution Virtual Assistant","authors":"Kenzhegali Nurgaliyev, D. D. Mauro, Nawaz Khan, J. Augusto","doi":"10.1109/IE.2017.21","DOIUrl":"https://doi.org/10.1109/IE.2017.21","url":null,"abstract":"In this work we will examine and develop a system that can assist people in Activities of Daily Life (ADL). This study focuses on resolving conflicts for the requests from different users' profiles, for instance - elderly, adult and young. The objective of the system is to present a dialogue manager which is able to detect multi-user semantic conflict and to resolve the conflict for improved dialogue informing about its decisions using a system interface avatar. The system is also able to prioritize requests that occurred among the services of multiple home appliances, as well as to deal with conflicting entities involving a single device. We investigated whether the multi-user context awareness by a Virtual Assistant adds value to the Smart Home concept in recognizing multi-user conflicts dynamically. This work has proposed a preference based method for resolving conflict and evaluated the developed system in a smart home environment.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127490879","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}
Jason J. Jung, Minsung Hong, O-Joun Lee, Jae-Hong Park, Chang Choi
Recently, most of context-aware services are trying to exploit the emotional contexts of the target users. The aim of this conceptual paper is to discuss affective lifelogging framework which can recognize the emotions by integrating multimodal information from multiple sources. Moreover, we will mention the open problems on affective lifelogging.
{"title":"Towards Affective Lifelogging with Information Fusion","authors":"Jason J. Jung, Minsung Hong, O-Joun Lee, Jae-Hong Park, Chang Choi","doi":"10.1109/IE.2017.25","DOIUrl":"https://doi.org/10.1109/IE.2017.25","url":null,"abstract":"Recently, most of context-aware services are trying to exploit the emotional contexts of the target users. The aim of this conceptual paper is to discuss affective lifelogging framework which can recognize the emotions by integrating multimodal information from multiple sources. Moreover, we will mention the open problems on affective lifelogging.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126981891","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}
Jani Bizjak, A. Gradišek, Luka Stepancic, H. Gjoreski, M. Gams, Karmen Goljuf
Information technologies can assist the elderly in their daily lives and thus improve their quality of life. Here, we present a system that was developed within the framework of the EU H2020 project IN LIFE to make the elderly feel more secure. The system consists of a smartwatch, a tablet, and a web portal for carers. The smartwatch has several functionalities; the most important are automatic fall detection, SOS button, communication with carers, location detection in case of emergency, and general activity monitoring. The smartwatch communicates with the server via GSM, therefore it does not depend on wireless internet or Bluetooth connection. The tablet acts as a virtual doorman and also as an interface for the carer, while the portal acts as a central information hub for notifications, scheduling of tasks, and user overview. We present the initial feedback from the users in a pilot study and discuss some modifications that we carried out considering this feedback.
{"title":"Intelligent System to Assist the Independent Living of the Elderly","authors":"Jani Bizjak, A. Gradišek, Luka Stepancic, H. Gjoreski, M. Gams, Karmen Goljuf","doi":"10.1109/IE.2017.12","DOIUrl":"https://doi.org/10.1109/IE.2017.12","url":null,"abstract":"Information technologies can assist the elderly in their daily lives and thus improve their quality of life. Here, we present a system that was developed within the framework of the EU H2020 project IN LIFE to make the elderly feel more secure. The system consists of a smartwatch, a tablet, and a web portal for carers. The smartwatch has several functionalities; the most important are automatic fall detection, SOS button, communication with carers, location detection in case of emergency, and general activity monitoring. The smartwatch communicates with the server via GSM, therefore it does not depend on wireless internet or Bluetooth connection. The tablet acts as a virtual doorman and also as an interface for the carer, while the portal acts as a central information hub for notifications, scheduling of tasks, and user overview. We present the initial feedback from the users in a pilot study and discuss some modifications that we carried out considering this feedback.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132215219","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}
A. Bueno-Crespo, Raquel Martínez-España, Isabel Maria Timon-Perez, Jesús A. Soto
The numerical value discretization is an important task of the data preprocessing phase within the intelligent data analysis. This process allows us to reduce the number of values (among other advantages) with which techniques work, reducing the computational cost when it comes to working with large amounts of data. In this paper a numerical value discretization technique is proposed. Specifically, we discretize numerical values using a type of Cauchy distribution obtained from fuzzy clustering technique, being this technique a modification of the well-known Fuzzy C-Means clustering technique. Finally, to test the quality of the membership function we use a neural network technique over several datasets. The results obtained are compared and validated by means of statistical tests, obtaining satisfactory results.
{"title":"Discretizing Numerical Values by a Fuzzy Clustering Technique","authors":"A. Bueno-Crespo, Raquel Martínez-España, Isabel Maria Timon-Perez, Jesús A. Soto","doi":"10.1109/IE.2017.37","DOIUrl":"https://doi.org/10.1109/IE.2017.37","url":null,"abstract":"The numerical value discretization is an important task of the data preprocessing phase within the intelligent data analysis. This process allows us to reduce the number of values (among other advantages) with which techniques work, reducing the computational cost when it comes to working with large amounts of data. In this paper a numerical value discretization technique is proposed. Specifically, we discretize numerical values using a type of Cauchy distribution obtained from fuzzy clustering technique, being this technique a modification of the well-known Fuzzy C-Means clustering technique. Finally, to test the quality of the membership function we use a neural network technique over several datasets. The results obtained are compared and validated by means of statistical tests, obtaining satisfactory results.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"23 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133616474","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}
Magdalena Cantabella, Elisabeth Dominguez de la Fuente, Raquel Martínez-España, Belén Ayuso, Andrés Muñoz
The behavior of university students is a field of study on the rise, whose main objective is the search for patterns that help improve their learning process. This paper analyzes the use of Learning Management Systems (LMS) in Higher Education and the interactions with their different tools from the students' viewpoint. For the analysis of the student activity statistical techniques and algorithms are extending to be used for big data platform. The information extracted from each student is based both on the events held in each session and on the number of sessions held. The analyzed data belongs to subjects of different modalities (on-campus, blended, online). The results of the methods are compared and discussed regarding the learning modalities. The results are interpreted in a discussion focus obtaining satisfactory knowledge for the identification of patterns of behavior.
{"title":"Searching for Behavior Patterns of Students in Different Training Modalities through Learning Management Systems","authors":"Magdalena Cantabella, Elisabeth Dominguez de la Fuente, Raquel Martínez-España, Belén Ayuso, Andrés Muñoz","doi":"10.1109/IE.2017.31","DOIUrl":"https://doi.org/10.1109/IE.2017.31","url":null,"abstract":"The behavior of university students is a field of study on the rise, whose main objective is the search for patterns that help improve their learning process. This paper analyzes the use of Learning Management Systems (LMS) in Higher Education and the interactions with their different tools from the students' viewpoint. For the analysis of the student activity statistical techniques and algorithms are extending to be used for big data platform. The information extracted from each student is based both on the events held in each session and on the number of sessions held. The analyzed data belongs to subjects of different modalities (on-campus, blended, online). The results of the methods are compared and discussed regarding the learning modalities. The results are interpreted in a discussion focus obtaining satisfactory knowledge for the identification of patterns of behavior.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"403 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116332363","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}
J. M. Cadenas, M. C. Garrido, Raquel Martínez-España, A. Muñoz
Currently, many of the elements that surround us in daily life need software systems that work from the information available in the domain (data-driven application domains) by performing a process of data mining from it. Between the data mining techniques used in everyday problems we find the k-Nearest Neighbors technique. However, in domains and real situations it is very common to find vague, ambiguous and noisy data, that is, imperfect information.Although this imperfect information is inevitable, most applications have traditionally ignored the need for developing appropriate approaches for representing and reasoning with such data imperfections. The soft computing field has dealt with the development of techniques that can work with this kind of information as discipline whose main characteristic is tolerance to inaccuracy and uncertainty.In this work, we extend the k-Nearest Neighbors technique using concepts and methods provided by Soft Computing. The aim is to carry out the processes of instance selection and classification in everyday problems from imperfect information making the technique more realistic.
{"title":"A More Realistic K-Nearest Neighbors Method and Its Possible Applications to Everyday Problems","authors":"J. M. Cadenas, M. C. Garrido, Raquel Martínez-España, A. Muñoz","doi":"10.1109/IE.2017.26","DOIUrl":"https://doi.org/10.1109/IE.2017.26","url":null,"abstract":"Currently, many of the elements that surround us in daily life need software systems that work from the information available in the domain (data-driven application domains) by performing a process of data mining from it. Between the data mining techniques used in everyday problems we find the k-Nearest Neighbors technique. However, in domains and real situations it is very common to find vague, ambiguous and noisy data, that is, imperfect information.Although this imperfect information is inevitable, most applications have traditionally ignored the need for developing appropriate approaches for representing and reasoning with such data imperfections. The soft computing field has dealt with the development of techniques that can work with this kind of information as discipline whose main characteristic is tolerance to inaccuracy and uncertainty.In this work, we extend the k-Nearest Neighbors technique using concepts and methods provided by Soft Computing. The aim is to carry out the processes of instance selection and classification in everyday problems from imperfect information making the technique more realistic.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125059435","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}
Recently, deep neural network based methods have been widely used in relation extraction, which is an important task for knowledge base population, question answering and other natural language applications, to learn proper features from entities pairs and other sentence parts to extract relations from text. As a kind of important information, the value of position is always been underestimated, which causes a low weight of position information in various models and finally hurts the performance of relation extraction task. To alleviate this issue, we propose a position-enhanced embedding model based on convolutional neural network. In this model, we split the sentence representation into three parts based on the entity pairs in the sentence, and use three independent convolutional networks to learn features. Furthermore, we concatenate the output from different branches and employ a softmax layer to compute the probability for each relation. Experimental results on wildly used datasets achieve considerable improvements on relation extraction as compared with baselines, which shows that our proposed model can make full use of position information.
{"title":"Relation Extraction via Position-Enhanced Convolutional Neural Network","authors":"Weiwei Shi, Sheng Gao","doi":"10.1109/IE.2017.28","DOIUrl":"https://doi.org/10.1109/IE.2017.28","url":null,"abstract":"Recently, deep neural network based methods have been widely used in relation extraction, which is an important task for knowledge base population, question answering and other natural language applications, to learn proper features from entities pairs and other sentence parts to extract relations from text. As a kind of important information, the value of position is always been underestimated, which causes a low weight of position information in various models and finally hurts the performance of relation extraction task. To alleviate this issue, we propose a position-enhanced embedding model based on convolutional neural network. In this model, we split the sentence representation into three parts based on the entity pairs in the sentence, and use three independent convolutional networks to learn features. Furthermore, we concatenate the output from different branches and employ a softmax layer to compute the probability for each relation. Experimental results on wildly used datasets achieve considerable improvements on relation extraction as compared with baselines, which shows that our proposed model can make full use of position information.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120942819","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}
Alicia Martínez, Virginia Ortiz, Hugo Estrada, Miguel Gonzalez
Social isolation is a problem that is accentuated in the stage of old age. This condition puts at risk the physical and mental integrity of older adults. This paper presents a predictive model for the automatic detection of social isolation in older adults. The predictive model was implemented in a mobile application that monitors communication and mobility activities performed by an older adult. The system also considers demographic aspects to improve the prediction results. The mobile application was also generated for a caregiver who is responsible for receiving notifications about the specific level of social isolation of the older adult. The predictive model was evaluated using an experimental group of older adults.
{"title":"A Predictive Model for Automatic Detection of Social Isolation in Older Adults","authors":"Alicia Martínez, Virginia Ortiz, Hugo Estrada, Miguel Gonzalez","doi":"10.1109/IE.2017.35","DOIUrl":"https://doi.org/10.1109/IE.2017.35","url":null,"abstract":"Social isolation is a problem that is accentuated in the stage of old age. This condition puts at risk the physical and mental integrity of older adults. This paper presents a predictive model for the automatic detection of social isolation in older adults. The predictive model was implemented in a mobile application that monitors communication and mobility activities performed by an older adult. The system also considers demographic aspects to improve the prediction results. The mobile application was also generated for a caregiver who is responsible for receiving notifications about the specific level of social isolation of the older adult. The predictive model was evaluated using an experimental group of older adults.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121775965","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}
Fábio Silva, Cesar Analide de Freitase Silva da Costa Rodrigues
The use of ubiquitous devices on large environment such as smart-cities enables opportunities to solve more complex problems and react to changes quicker. Namely the use of computational resources to assist the management of environment through predicament of parameters based on sustainable indicators applied to smart-cities. This paper considers the creation of a computational sustainability archetype platform which generates contexts supported by principles of computation sustainability and the assurance of sustainable scenarios. Context gathering and predicament is used based on indicators obtained from the environment over public services, sensors networks and ubiquitous devices which are used to create indicators based on the fusion of data.
{"title":"Computational Sustainability for Smart City Design","authors":"Fábio Silva, Cesar Analide de Freitase Silva da Costa Rodrigues","doi":"10.1109/IE.2017.11","DOIUrl":"https://doi.org/10.1109/IE.2017.11","url":null,"abstract":"The use of ubiquitous devices on large environment such as smart-cities enables opportunities to solve more complex problems and react to changes quicker. Namely the use of computational resources to assist the management of environment through predicament of parameters based on sustainable indicators applied to smart-cities. This paper considers the creation of a computational sustainability archetype platform which generates contexts supported by principles of computation sustainability and the assurance of sustainable scenarios. Context gathering and predicament is used based on indicators obtained from the environment over public services, sensors networks and ubiquitous devices which are used to create indicators based on the fusion of data.","PeriodicalId":306693,"journal":{"name":"2017 International Conference on Intelligent Environments (IE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117106508","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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