Ponències/Comunicacions de congressoshttp://hdl.handle.net/2117/35012024-03-28T15:00:19Z2024-03-28T15:00:19ZPRESISTANT : data pre-processing assistantBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsMunir, Rana FaisalWrembel, Roberthttp://hdl.handle.net/2117/1279842021-06-20T05:51:16Z2019-01-31T10:45:47ZPRESISTANT : data pre-processing assistant
Bilalli, Besim; Abelló Gamazo, Alberto; Aluja Banet, Tomàs; Munir, Rana Faisal; Wrembel, Robert
A concrete classification algorithm may perform differently on datasets with different characteristics, e.g., it might perform better on a dataset with continuous attributes rather than with categorical attributes, or the other way around. Typically, in order to improve the results, datasets need to be pre-processed. Taking into account all the possible pre-processing operators, there exists a staggeringly large number of alternatives and non-experienced users become overwhelmed. Trial and error is not feasible in the presence of big amounts of data. We developed a method and tool—PRESISTANT, with the aim of answering the need for user assistance during data pre-processing. Leveraging ideas from meta-learning, PRESISTANT is capable of assisting the user by recommending pre-processing operators that ultimately improve the classification performance. The user selects a classification algorithm, from the ones considered, and then PRESISTANT proposes candidate transformations to improve the result of the analysis. In the demonstration, participants will experience, at first hand, how PRESISTANT easily and effectively ranks the pre-processing operators.
2019-01-31T10:45:47ZBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsMunir, Rana FaisalWrembel, RobertA concrete classification algorithm may perform differently on datasets with different characteristics, e.g., it might perform better on a dataset with continuous attributes rather than with categorical attributes, or the other way around. Typically, in order to improve the results, datasets need to be pre-processed. Taking into account all the possible pre-processing operators, there exists a staggeringly large number of alternatives and non-experienced users become overwhelmed. Trial and error is not feasible in the presence of big amounts of data. We developed a method and tool—PRESISTANT, with the aim of answering the need for user assistance during data pre-processing. Leveraging ideas from meta-learning, PRESISTANT is capable of assisting the user by recommending pre-processing operators that ultimately improve the classification performance. The user selects a classification algorithm, from the ones considered, and then PRESISTANT proposes candidate transformations to improve the result of the analysis. In the demonstration, participants will experience, at first hand, how PRESISTANT easily and effectively ranks the pre-processing operators.Modelling and analysis of intermodal passenger operations in a cruise terminal to prevent traffic congestion and enhance quality of service using discrete event simulationFigueras Jové, JaumeGuasch Petit, AntonioCasanovas Garcia, Josephttp://hdl.handle.net/2117/1271872021-02-11T11:50:43Z2019-01-18T11:56:34ZModelling and analysis of intermodal passenger operations in a cruise terminal to prevent traffic congestion and enhance quality of service using discrete event simulation
Figueras Jové, Jaume; Guasch Petit, Antonio; Casanovas Garcia, Josep
In this paper we present a discrete event simulation model of a cruise terminal for decision support and
strategic planning. The main objective is to provide an analysis tool for systems with high capacity
constraints, heterogeneous subsystems, time-dependent demand and stochastic passenger transfer and travel
times. Cruise terminals are connected by bus to a transport interchange or intermobility center where
passengers are transferred to taxis. All terminals are affected by capacity constraints such as the number of
bus platforms for passenger pick-up and drop-off and the limited queuing capacity for taxis and passengers.
Passenger arrivals are time-dependent and cruise-type-dependent. The purpose of this model is to support
the strategic decision-making process through what-if-scenarios. Decisions involve determining the
required number of bus platforms, taxi buffer sizes and passenger distribution policies, among other factors.
The results identified and proposed the solution of bottlenecks and enabled a sensitivity analysis to be
performed.
2019-01-18T11:56:34ZFigueras Jové, JaumeGuasch Petit, AntonioCasanovas Garcia, JosepIn this paper we present a discrete event simulation model of a cruise terminal for decision support and
strategic planning. The main objective is to provide an analysis tool for systems with high capacity
constraints, heterogeneous subsystems, time-dependent demand and stochastic passenger transfer and travel
times. Cruise terminals are connected by bus to a transport interchange or intermobility center where
passengers are transferred to taxis. All terminals are affected by capacity constraints such as the number of
bus platforms for passenger pick-up and drop-off and the limited queuing capacity for taxis and passengers.
Passenger arrivals are time-dependent and cruise-type-dependent. The purpose of this model is to support
the strategic decision-making process through what-if-scenarios. Decisions involve determining the
required number of bus platforms, taxi buffer sizes and passenger distribution policies, among other factors.
The results identified and proposed the solution of bottlenecks and enabled a sensitivity analysis to be
performed.Agent-based simulation of large population dynamicsMontañola Sales, CristinaCasanovas Garcia, JosepCela Espín, José M.Onggo, B.S.S.Kaplan Marcusan, Adrianahttp://hdl.handle.net/2117/1057232021-02-11T06:05:08Z2017-06-22T08:51:32ZAgent-based simulation of large population dynamics
Montañola Sales, Cristina; Casanovas Garcia, Josep; Cela Espín, José M.; Onggo, B.S.S.; Kaplan Marcusan, Adriana
Agent-based modelling and simulation is a promising methodology that can be used in the study of population dynamics. One of the main obstacles hindering the use of agent-based simulation in practice is its scalability, especially if the analysis requires large-scale models. A possible solution is to run the agent-based models on top of a scalable parallel discrete-event simulation engine. In this paper we present a modelling and simulation platform implemented to provide a basic support for M&S of agent-based demographic systems. As a simulation application, we conducted a study to evaluate its performance in a parallel
environment: a supercomputer. A user interface was also designed to allow modellers to easily define models to describe different demographic processes and transparently run them on any computer architecture environment. Our results prove that agent-based modelling can work effectively in the study of demographic scenarios which can help to better family policy planning and analysis. Moreover, parallel environment looks suitable for the study of large-based individual-based simulations of this kind.
2017-06-22T08:51:32ZMontañola Sales, CristinaCasanovas Garcia, JosepCela Espín, José M.Onggo, B.S.S.Kaplan Marcusan, AdrianaAgent-based modelling and simulation is a promising methodology that can be used in the study of population dynamics. One of the main obstacles hindering the use of agent-based simulation in practice is its scalability, especially if the analysis requires large-scale models. A possible solution is to run the agent-based models on top of a scalable parallel discrete-event simulation engine. In this paper we present a modelling and simulation platform implemented to provide a basic support for M&S of agent-based demographic systems. As a simulation application, we conducted a study to evaluate its performance in a parallel
environment: a supercomputer. A user interface was also designed to allow modellers to easily define models to describe different demographic processes and transparently run them on any computer architecture environment. Our results prove that agent-based modelling can work effectively in the study of demographic scenarios which can help to better family policy planning and analysis. Moreover, parallel environment looks suitable for the study of large-based individual-based simulations of this kind.Parallel simulation of large population dynamicsMontañola Sales, CristinaCasanovas Garcia, JosepCela Espín, José M.Kaplan Marcusan, Adrianahttp://hdl.handle.net/2117/1057222021-02-11T08:15:36Z2017-06-22T08:47:21ZParallel simulation of large population dynamics
Montañola Sales, Cristina; Casanovas Garcia, Josep; Cela Espín, José M.; Kaplan Marcusan, Adriana
Agent-based modeling and simulation is a promising methodology that can be used in the study of population dynamics. We present the design and development of a simulation tool which provides basic support for
modeling and simulating agent-based demographic systems. Our results prove that agent-based modeling can work effectively in the study of demographic scenarios which can help to better policy planning
and analysis. Moreover, parallel environment looks suitable for the study of large-scale individual-based
simulations of this kind.
2017-06-22T08:47:21ZMontañola Sales, CristinaCasanovas Garcia, JosepCela Espín, José M.Kaplan Marcusan, AdrianaAgent-based modeling and simulation is a promising methodology that can be used in the study of population dynamics. We present the design and development of a simulation tool which provides basic support for
modeling and simulating agent-based demographic systems. Our results prove that agent-based modeling can work effectively in the study of demographic scenarios which can help to better policy planning
and analysis. Moreover, parallel environment looks suitable for the study of large-scale individual-based
simulations of this kind.Automated data pre-processing via meta-learningBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsWrembel, Roberthttp://hdl.handle.net/2117/1032552021-05-20T23:26:52Z2017-04-04T10:29:27ZAutomated data pre-processing via meta-learning
Bilalli, Besim; Abelló Gamazo, Alberto; Aluja Banet, Tomàs; Wrembel, Robert
A data mining algorithm may perform differently on datasets with different characteristics, e.g., it might perform better on a dataset with continuous attributes rather than with categorical attributes, or the other way around.
As a matter of fact, a dataset usually needs to be pre-processed. Taking into account all the possible pre-processing operators, there exists a staggeringly large number of alternatives and nonexperienced users become overwhelmed.
We show that this problem can be addressed by an automated approach, leveraging ideas from metalearning.
Specifically, we consider a wide range of data pre-processing techniques and a set of data mining algorithms. For each data mining algorithm and selected dataset, we are able to predict the transformations that improve the result
of the algorithm on the respective dataset. Our approach will help non-expert users to more effectively identify the transformations appropriate to their applications, and hence to achieve improved results.
The final publication is available at link.springer.com
2017-04-04T10:29:27ZBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsWrembel, RobertA data mining algorithm may perform differently on datasets with different characteristics, e.g., it might perform better on a dataset with continuous attributes rather than with categorical attributes, or the other way around.
As a matter of fact, a dataset usually needs to be pre-processed. Taking into account all the possible pre-processing operators, there exists a staggeringly large number of alternatives and nonexperienced users become overwhelmed.
We show that this problem can be addressed by an automated approach, leveraging ideas from metalearning.
Specifically, we consider a wide range of data pre-processing techniques and a set of data mining algorithms. For each data mining algorithm and selected dataset, we are able to predict the transformations that improve the result
of the algorithm on the respective dataset. Our approach will help non-expert users to more effectively identify the transformations appropriate to their applications, and hence to achieve improved results.Towards intelligent data analysis : the metadata challengeBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsWrembel, Roberthttp://hdl.handle.net/2117/1016762021-05-21T07:33:00Z2017-02-28T09:31:06ZTowards intelligent data analysis : the metadata challenge
Bilalli, Besim; Abelló Gamazo, Alberto; Aluja Banet, Tomàs; Wrembel, Robert
Once analyzed correctly, data can yield substantial benefits. The process of analyzing the data and transforming it into knowledge is known as Knowledge Discovery in Databases (KDD). The plethora and subtleties of algorithms in the different steps of KDD, render it challenging. An effective user support is of crucial importance, even more now, when the analysis is performed on Big Data. Metadata is the necessary component to drive the user support. In this paper we study the metadata required to provide user support on every stage of the KDD process. We show that intelligent systems addressing the problem of user assistance in KDD are incomplete in this regard. They do not use the whole potential of metadata to enable assistance during the whole process. We present a comprehensive classification of all the metadata required to provide user support. Furthermore, we present our implementation of a metadata repository for storing and managing this metadata and explain its benefits in a real Big Data analytics project.
2017-02-28T09:31:06ZBilalli, BesimAbelló Gamazo, AlbertoAluja Banet, TomàsWrembel, RobertOnce analyzed correctly, data can yield substantial benefits. The process of analyzing the data and transforming it into knowledge is known as Knowledge Discovery in Databases (KDD). The plethora and subtleties of algorithms in the different steps of KDD, render it challenging. An effective user support is of crucial importance, even more now, when the analysis is performed on Big Data. Metadata is the necessary component to drive the user support. In this paper we study the metadata required to provide user support on every stage of the KDD process. We show that intelligent systems addressing the problem of user assistance in KDD are incomplete in this regard. They do not use the whole potential of metadata to enable assistance during the whole process. We present a comprehensive classification of all the metadata required to provide user support. Furthermore, we present our implementation of a metadata repository for storing and managing this metadata and explain its benefits in a real Big Data analytics project.Analysis of the gamification applications to improve the energy savings in residential buildingsFonseca Casas, PauCasanovas Garcia, Josephttp://hdl.handle.net/2117/1004252021-02-11T04:06:03Z2017-02-01T09:31:22ZAnalysis of the gamification applications to improve the energy savings in residential buildings
Fonseca Casas, Pau; Casanovas Garcia, Josep
This paper proposes a set of metrics to evaluate and compare applications in a new but quickly developing field – energy management software (EMS) in residential buildings. The goal of the paper is to highlight tendencies and to detect drawbacks of pre sent applications to develop a new one taking into account the results of previous analysis. It shows a shortlist of applications examined. Provides the conclusion drawing to the metrics and proposes mai n issues to be considered in the development of a new application.
2017-02-01T09:31:22ZFonseca Casas, PauCasanovas Garcia, JosepThis paper proposes a set of metrics to evaluate and compare applications in a new but quickly developing field – energy management software (EMS) in residential buildings. The goal of the paper is to highlight tendencies and to detect drawbacks of pre sent applications to develop a new one taking into account the results of previous analysis. It shows a shortlist of applications examined. Provides the conclusion drawing to the metrics and proposes mai n issues to be considered in the development of a new application.Web simulation training environment for aircraft resource planning in wildfire eventsFigueras Jové, JaumeGuasch Petit, AntonioCasanovas Garcia, Josephttp://hdl.handle.net/2117/909442022-05-17T10:32:19Z2016-10-21T08:25:03ZWeb simulation training environment for aircraft resource planning in wildfire events
Figueras Jové, Jaume; Guasch Petit, Antonio; Casanovas Garcia, Josep
This poster presents a simulation tool developed in cooperation with the Catalonia firefighting authority to provide a training environment for firefighter air operations commanders in wildfire events. In case of a wildfire event multiple aircrafts are deployed, including a commandment aircraft, by the main operation center. Aircrafts tasks, deployments and schedules can be assigned by both the commandment aircraft and the main operation center. This center is also in charge of controlling the different simultaneous wildfire aircrafts being able to re-assign, land or re-schedule aircrafts from one wildfire to another. An on-line multi-user environment has been developed to manage and optimize the aircraft operations. The aim of this environment is to increase operations security and to relief the operators from errors and repetitive tasks. On top of the optimization environment a multi-user web based simulation tool has been developed in order to provide a training framework for firefighters air controllers.
2016-10-21T08:25:03ZFigueras Jové, JaumeGuasch Petit, AntonioCasanovas Garcia, JosepThis poster presents a simulation tool developed in cooperation with the Catalonia firefighting authority to provide a training environment for firefighter air operations commanders in wildfire events. In case of a wildfire event multiple aircrafts are deployed, including a commandment aircraft, by the main operation center. Aircrafts tasks, deployments and schedules can be assigned by both the commandment aircraft and the main operation center. This center is also in charge of controlling the different simultaneous wildfire aircrafts being able to re-assign, land or re-schedule aircrafts from one wildfire to another. An on-line multi-user environment has been developed to manage and optimize the aircraft operations. The aim of this environment is to increase operations security and to relief the operators from errors and repetitive tasks. On top of the optimization environment a multi-user web based simulation tool has been developed in order to provide a training framework for firefighters air controllers.Distributed experiment for the calculus of optimal values for energy consumption in buildingsFonseca Casas, PauFonseca Casas, AntoniGarrido Soriano, NúriaAina Ortiz, JoanaCasanovas Garcia, JosepSalom, Jaumehttp://hdl.handle.net/2117/819532021-02-11T09:45:13Z2016-01-25T12:35:58ZDistributed experiment for the calculus of optimal values for energy consumption in buildings
Fonseca Casas, Pau; Fonseca Casas, Antoni; Garrido Soriano, Núria; Aina Ortiz, Joana; Casanovas Garcia, Josep; Salom, Jaume
2016-01-25T12:35:58ZFonseca Casas, PauFonseca Casas, AntoniGarrido Soriano, NúriaAina Ortiz, JoanaCasanovas Garcia, JosepSalom, JaumeUPCEO, connecting statistics and people using RFonseca Casas, PauTormos, RaülCasanovas Garcia, Josephttp://hdl.handle.net/2117/819522021-02-11T03:53:43Z2016-01-25T12:19:30ZUPCEO, connecting statistics and people using R
Fonseca Casas, Pau; Tormos, Raül; Casanovas Garcia, Josep
A methodology and a tool that implements this methodology are developed using R to construct a web site that allows a lay user to consult statistical information owned by an institution and stored in a cloud database. This methodology was developed followin g the open - data philosophy and was implemented with open -source software using R as a key element. The proposed methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to another sta tistical center to enable open access to its data. The system is deployed on a cloud infrastructure that scales according to demand, implementing a 24/7 solution. A user (or a computer program) can access the information on the website using the R language as a communication channel or using a programming application interface. Additionally, in the R language, a common framework can be defined to structure the various processes involved in any statistical operation.
2016-01-25T12:19:30ZFonseca Casas, PauTormos, RaülCasanovas Garcia, JosepA methodology and a tool that implements this methodology are developed using R to construct a web site that allows a lay user to consult statistical information owned by an institution and stored in a cloud database. This methodology was developed followin g the open - data philosophy and was implemented with open -source software using R as a key element. The proposed methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to another sta tistical center to enable open access to its data. The system is deployed on a cloud infrastructure that scales according to demand, implementing a 24/7 solution. A user (or a computer program) can access the information on the website using the R language as a communication channel or using a programming application interface. Additionally, in the R language, a common framework can be defined to structure the various processes involved in any statistical operation.