Elias Kalapanidas - Academia.edu (original) (raw)

Papers by Elias Kalapanidas

Abstract. Feature selection is a process followed in order to improve the generalization and the ... more Abstract. Feature selection is a process followed in order to improve the generalization and the performance of several classification and/or regression algorithms. Feature selection processes are divided in two categories, the filter and the wrapper approach. The formal is performed independently of the learning algorithm while the later makes use of the algorithm in an iterative way. As [1] describe, the feature weighting algorithms are divided into two categories: the filtering methods and the wrapper methods. The former is a no-feedback, pre-selection approach where the selection of the feature subset is performed independently of the learning algorithm. The later is an iterative method that encapsulates the learning algorithm in the feature selection process.

Journal of Mental Health, 2012

Background: Previous review studies have suggested that computer games can serve as an alternativ... more Background: Previous review studies have suggested that computer games can serve as an alternative or additional form of treatment in several areas (schizophrenia, asthma or motor rehabilitation). Although several naturalistic studies have been conducted showing the usefulness of serious video games in the treatment of some abnormal behaviours, there is a lack of serious games specially designed for treating mental disorders. Aim: The purpose of our project was to develop and evaluate a serious video game designed to remediate attitudinal, behavioural and emotional processes of patients with impulse-related disorders. Method and results: The video game was created and developed within the European research project PlayMancer. It aims to prove potential capacity to change underlying attitudinal, behavioural and emotional processes of patients with impulse-related disorders. New interaction modes were provided by newly developed components, such as emotion recognition from speech, face and physiological reactions, while specific impulsive reactions were elicited. The video game uses biofeedback for helping patients to learn relaxation skills, acquire better self-control strategies and develop new emotional regulation strategies. In this article, we present a description of the video game used, rationale, user requirements, usability and preliminary data, in several mental disorders.

Studies in Health Technology and Informatics, 2009

Reviews and few non-controlled studies showed the effectiveness of several specific designed comp... more Reviews and few non-controlled studies showed the effectiveness of several specific designed computer video-games as an additional form of treatment in several areas. However, there is a lack in the literature of specially designed serious-games for treating mental disorders. Playmancer (ICT European initiative) aims to develop and assess a serious videogame that may help to treat underlying processes (e.g. lack of self-control strategies) in Eating and Impulse control disorders. Preliminary data will be shown.

Abstract. Serious games are about to enter the medical sector to give people with behavioural or ... more Abstract. Serious games are about to enter the medical sector to give people with behavioural or addictive disorders the ability to use them as part of health promotion and disease prevention. The PlayMancer framework will support physical rehabilitations and psycho-education programs thru a modular multiplayer networked 3D game based on the Universally Accessible Games (UA games) guidelines. 1

In the frame of air quality monitoring of urban areas, the task of short-term prediction of key-p... more In the frame of air quality monitoring of urban areas, the task of short-term prediction of key-pollutants concentrations is a daily activity of major importance. Automation of this process is desirable, but development of reliable predictive models with good performance, to support this task in operational basis presents many difficulties. In this paper we present and discuss the NEMO prototype that has been built in order to support short-term prediction of NO2 maximum concentration levels in Athens, Greece. NEMO is based on a case-based-reasoning approach combining heuristic and statistical techniques. The process of development of the system, its architecture and its performance, are described in this paper. NEMO performance is compared with that of a back propagating neural network, and a decision tree (CART). The overall performance of NEMO makes it a good candidate to support air pollution experts in operational conditions.

Feature selection for air quality forecasting:

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets. The results contain evaluation of classification criteria for every algorithm and noise level for the noise sensitivity study. The results suggest that the best algorithms per problem in terms of showing the lower RMS error are the decision table and the linear regression, for classification and regression problems respectively.

Feature selection is a process of determining the most relevant features of a given problem in or... more Feature selection is a process of determining the most relevant features of a given problem in order to improve the generalization and the performance of a relevant classification or regression algorithm.This paper focuses on the exploitation of a genetic algorithm following a wrapping iterative approach used to extract an optimal feature subset of a large database containing pollutant concentration measurements. The feature subset is fed to a machine learning algorithm in order to predict the daily maximum concentration of two air pollutants.The encoding problem of the complexity of representation of the features in the genomes is tackled. Results of the experimentation on a specific dataset of an air quality forecasting problem are presented, as well as some proposed alterations on the standard genetic algorithm that guided the process to a mature convergence and gave good solutions for this problem. A modified version of the initial algorithm is presented as well, implemented for...

Feature selection is a process followed in order to improve the generalization and the performanc... more Feature selection is a process followed in order to improve the generalization and the performance of several classification and/or regression algorithms. Feature selection processes are divided in two categories, the filter and the wrapper approach. The formal is performed independently of the learning algorithm while the later makes use of the algorithm in an iterative way. As [1] describe, the feature weighting algorithms are divided into two categories: the filtering methods and the wrapper methods. The former is a no-feedback, pre-selection approach where the selection of the feature subset is performed independently of the learning algorithm. The later is an iterative method that encapsulates the learning algorithm in the feature selection process.

2008 International Conference on Automated Solutions for Cross Media Content and Multi-Channel Distribution, 2008

Serious games are about to enter the medical sector to give people with behavioural or addictive ... more Serious games are about to enter the medical sector to give people with behavioural or addictive disorders the ability to use them as part of health promotion and disease prevention. The PlayMancer framework will support physical rehabilitations and psycho-education programs thru a modular multiplayer networked 3D game based on the Universally Accessible Games (UA games) guidelines.

ABSTRACT In this paper, a novel system utilizing virtual reality for enhancing music tuition syst... more ABSTRACT In this paper, a novel system utilizing virtual reality for enhancing music tuition systems will be described. The proposed system operates on music notation files and produces 3D animations of virtual hands, playing a virtual recorder. The work is supported by two applications: a) the Fingering Viewer, which visualizes the animations in a 3D world and b) the Movement Authoring Tool, which provides the user with the ability to author viewing positions and comments, and store the results in a dedicated file format. The whole system provides added value to traditional multimedia music tuition systems by exploiting the efficiency of virtual reality visualization techniques.

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets. The results contain evaluation of classification criteria for every algorithm and noise level for the noise sensitivity study. The results suggest that the best algorithms per problem in terms of showing the lower RMS error are the decision table and the linear regression, for classification and regression problems respectively. Research supported. . .

Management of urban atmospheric pollution necessitates advanced modeling and information processi... more Management of urban atmospheric pollution necessitates advanced modeling and information processing techniques. The design of the prototype system DNEMO, which is based on a distributed adaptive problem solving approach is the focus of the research reported in this paper. Issues covered in the paper relate to the distributed nature of this environmental problem, handling noise and uncertainty in monitoring data, achieving graceful degradation of performance and system robustness, adaptation of system performance to long-term evolution of the monitored phenomena. The research reported can be applicable to a broad class of Environmental Monitoring applications, since the problems addressed are common to many environmental problems. Mental states Commitment Skills Beliefs Goals Acquaintenances Behavior Communication Rule-base action Message sending Message processing Acq. addresses OutRouting InRouting Input buffer

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets ...

2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies, 2008

Having witnessed a rapid development of the digital media literacy in the modern society due to a... more Having witnessed a rapid development of the digital media literacy in the modern society due to a multitude of technological advances in the low-cost photography, cinematography and 2D/3D graphic design, there is a proliferation of high quality media content generated, ...

Proc. ACAI, 1999

Monitoring air quality is a necessary activity in many industrial and urban areas of our planet. ... more Monitoring air quality is a necessary activity in many industrial and urban areas of our planet. Air Quality OperationalCentres (AQOCs) are established for this purpose, in areas with serious air pollution problems. The AQOCsare operational units, responsible for managing monitoring networks, processing the collected information, eventuallyproviding on-line assessment of air pollution and its short-term and long-term evolution. Great volumes of dataare collected over time in these centres. One of the prime concerns of scientists in ...

Frontiers in Neuroengineering, Jan 1, 2009

Abstract. Reviews and few non-controlled studies showed the effectiveness of several specific des... more Abstract. Reviews and few non-controlled studies showed the effectiveness of several specific designed computer video-games as an additional form of treatment in several areas. However, there is a lack in the literature of specially designed serious-games for treating ...

Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts , Jan 1, 2008

Abstract The evolution of the Internet is being leaded by two main threads, one driven by industr... more Abstract The evolution of the Internet is being leaded by two main threads, one driven by industry through the evolution of networking infrastructures and the other driven by producers of content either in a professional or non professional way. Moreover, due to ...

Abstract. Feature selection is a process followed in order to improve the generalization and the ... more Abstract. Feature selection is a process followed in order to improve the generalization and the performance of several classification and/or regression algorithms. Feature selection processes are divided in two categories, the filter and the wrapper approach. The formal is performed independently of the learning algorithm while the later makes use of the algorithm in an iterative way. As [1] describe, the feature weighting algorithms are divided into two categories: the filtering methods and the wrapper methods. The former is a no-feedback, pre-selection approach where the selection of the feature subset is performed independently of the learning algorithm. The later is an iterative method that encapsulates the learning algorithm in the feature selection process.

Journal of Mental Health, 2012

Background: Previous review studies have suggested that computer games can serve as an alternativ... more Background: Previous review studies have suggested that computer games can serve as an alternative or additional form of treatment in several areas (schizophrenia, asthma or motor rehabilitation). Although several naturalistic studies have been conducted showing the usefulness of serious video games in the treatment of some abnormal behaviours, there is a lack of serious games specially designed for treating mental disorders. Aim: The purpose of our project was to develop and evaluate a serious video game designed to remediate attitudinal, behavioural and emotional processes of patients with impulse-related disorders. Method and results: The video game was created and developed within the European research project PlayMancer. It aims to prove potential capacity to change underlying attitudinal, behavioural and emotional processes of patients with impulse-related disorders. New interaction modes were provided by newly developed components, such as emotion recognition from speech, face and physiological reactions, while specific impulsive reactions were elicited. The video game uses biofeedback for helping patients to learn relaxation skills, acquire better self-control strategies and develop new emotional regulation strategies. In this article, we present a description of the video game used, rationale, user requirements, usability and preliminary data, in several mental disorders.

Studies in Health Technology and Informatics, 2009

Reviews and few non-controlled studies showed the effectiveness of several specific designed comp... more Reviews and few non-controlled studies showed the effectiveness of several specific designed computer video-games as an additional form of treatment in several areas. However, there is a lack in the literature of specially designed serious-games for treating mental disorders. Playmancer (ICT European initiative) aims to develop and assess a serious videogame that may help to treat underlying processes (e.g. lack of self-control strategies) in Eating and Impulse control disorders. Preliminary data will be shown.

Abstract. Serious games are about to enter the medical sector to give people with behavioural or ... more Abstract. Serious games are about to enter the medical sector to give people with behavioural or addictive disorders the ability to use them as part of health promotion and disease prevention. The PlayMancer framework will support physical rehabilitations and psycho-education programs thru a modular multiplayer networked 3D game based on the Universally Accessible Games (UA games) guidelines. 1

In the frame of air quality monitoring of urban areas, the task of short-term prediction of key-p... more In the frame of air quality monitoring of urban areas, the task of short-term prediction of key-pollutants concentrations is a daily activity of major importance. Automation of this process is desirable, but development of reliable predictive models with good performance, to support this task in operational basis presents many difficulties. In this paper we present and discuss the NEMO prototype that has been built in order to support short-term prediction of NO2 maximum concentration levels in Athens, Greece. NEMO is based on a case-based-reasoning approach combining heuristic and statistical techniques. The process of development of the system, its architecture and its performance, are described in this paper. NEMO performance is compared with that of a back propagating neural network, and a decision tree (CART). The overall performance of NEMO makes it a good candidate to support air pollution experts in operational conditions.

Feature selection for air quality forecasting:

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets. The results contain evaluation of classification criteria for every algorithm and noise level for the noise sensitivity study. The results suggest that the best algorithms per problem in terms of showing the lower RMS error are the decision table and the linear regression, for classification and regression problems respectively.

Feature selection is a process of determining the most relevant features of a given problem in or... more Feature selection is a process of determining the most relevant features of a given problem in order to improve the generalization and the performance of a relevant classification or regression algorithm.This paper focuses on the exploitation of a genetic algorithm following a wrapping iterative approach used to extract an optimal feature subset of a large database containing pollutant concentration measurements. The feature subset is fed to a machine learning algorithm in order to predict the daily maximum concentration of two air pollutants.The encoding problem of the complexity of representation of the features in the genomes is tackled. Results of the experimentation on a specific dataset of an air quality forecasting problem are presented, as well as some proposed alterations on the standard genetic algorithm that guided the process to a mature convergence and gave good solutions for this problem. A modified version of the initial algorithm is presented as well, implemented for...

Feature selection is a process followed in order to improve the generalization and the performanc... more Feature selection is a process followed in order to improve the generalization and the performance of several classification and/or regression algorithms. Feature selection processes are divided in two categories, the filter and the wrapper approach. The formal is performed independently of the learning algorithm while the later makes use of the algorithm in an iterative way. As [1] describe, the feature weighting algorithms are divided into two categories: the filtering methods and the wrapper methods. The former is a no-feedback, pre-selection approach where the selection of the feature subset is performed independently of the learning algorithm. The later is an iterative method that encapsulates the learning algorithm in the feature selection process.

2008 International Conference on Automated Solutions for Cross Media Content and Multi-Channel Distribution, 2008

Serious games are about to enter the medical sector to give people with behavioural or addictive ... more Serious games are about to enter the medical sector to give people with behavioural or addictive disorders the ability to use them as part of health promotion and disease prevention. The PlayMancer framework will support physical rehabilitations and psycho-education programs thru a modular multiplayer networked 3D game based on the Universally Accessible Games (UA games) guidelines.

ABSTRACT In this paper, a novel system utilizing virtual reality for enhancing music tuition syst... more ABSTRACT In this paper, a novel system utilizing virtual reality for enhancing music tuition systems will be described. The proposed system operates on music notation files and produces 3D animations of virtual hands, playing a virtual recorder. The work is supported by two applications: a) the Fingering Viewer, which visualizes the animations in a 3D world and b) the Movement Authoring Tool, which provides the user with the ability to author viewing positions and comments, and store the results in a dedicated file format. The whole system provides added value to traditional multimedia music tuition systems by exploiting the efficiency of virtual reality visualization techniques.

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets. The results contain evaluation of classification criteria for every algorithm and noise level for the noise sensitivity study. The results suggest that the best algorithms per problem in terms of showing the lower RMS error are the decision table and the linear regression, for classification and regression problems respectively. Research supported. . .

Management of urban atmospheric pollution necessitates advanced modeling and information processi... more Management of urban atmospheric pollution necessitates advanced modeling and information processing techniques. The design of the prototype system DNEMO, which is based on a distributed adaptive problem solving approach is the focus of the research reported in this paper. Issues covered in the paper relate to the distributed nature of this environmental problem, handling noise and uncertainty in monitoring data, achieving graceful degradation of performance and system robustness, adaptation of system performance to long-term evolution of the monitored phenomena. The research reported can be applicable to a broad class of Environmental Monitoring applications, since the problems addressed are common to many environmental problems. Mental states Commitment Skills Beliefs Goals Acquaintenances Behavior Communication Rule-base action Message sending Message processing Acq. addresses OutRouting InRouting Input buffer

In this study, results of a variety of ML algorithms are tested against artificially polluted dat... more In this study, results of a variety of ML algorithms are tested against artificially polluted datasets with noise. Two noise models are tested, each of these studied on a range of noise levels from 0 to 50algorithm, a linear regression algorithm, a decision tree, a M5 algorithm, a decision table classifier, a voting interval scheme as well as a hyper pipes classifier. The study is based on an environmental field of application employing data from two air quality prediction problems, a toxicity classification problem and four artificially produced datasets ...

2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies, 2008

Having witnessed a rapid development of the digital media literacy in the modern society due to a... more Having witnessed a rapid development of the digital media literacy in the modern society due to a multitude of technological advances in the low-cost photography, cinematography and 2D/3D graphic design, there is a proliferation of high quality media content generated, ...

Proc. ACAI, 1999

Monitoring air quality is a necessary activity in many industrial and urban areas of our planet. ... more Monitoring air quality is a necessary activity in many industrial and urban areas of our planet. Air Quality OperationalCentres (AQOCs) are established for this purpose, in areas with serious air pollution problems. The AQOCsare operational units, responsible for managing monitoring networks, processing the collected information, eventuallyproviding on-line assessment of air pollution and its short-term and long-term evolution. Great volumes of dataare collected over time in these centres. One of the prime concerns of scientists in ...

Frontiers in Neuroengineering, Jan 1, 2009

Abstract. Reviews and few non-controlled studies showed the effectiveness of several specific des... more Abstract. Reviews and few non-controlled studies showed the effectiveness of several specific designed computer video-games as an additional form of treatment in several areas. However, there is a lack in the literature of specially designed serious-games for treating ...

Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts , Jan 1, 2008

Abstract The evolution of the Internet is being leaded by two main threads, one driven by industr... more Abstract The evolution of the Internet is being leaded by two main threads, one driven by industry through the evolution of networking infrastructures and the other driven by producers of content either in a professional or non professional way. Moreover, due to ...

Public bodies retain, maintain and continue to acquire a wealth of information and content. To th... more Public bodies retain, maintain and continue to acquire a wealth of information and content. To the degree that this information is in digital form, and given the pervasive nature of ICT technologies, the value of public sector information (PSI) as a resource is constantly increasing. A large potential of exploiting PSI is remaining untapped, waiting for innovative applications to create added-value by reusing the datasets that are offered today in new and exciting ways.