Pub Date : 1900-01-01DOI: 10.1109/SAMI.2017.7880299
L. Vokorokos, Z. Bilanová, Daniel Mihályi
The features of linear predicate logic (based on propositional linear logic enriched by the first order predicate logic principles) are implemented in logic programming language called Vorvan. Subsequently, the time-space extension of linear logic — Ludics theory, is applied to selected clause of given language.
{"title":"Hanoi towers in resource oriented perspective","authors":"L. Vokorokos, Z. Bilanová, Daniel Mihályi","doi":"10.1109/SAMI.2017.7880299","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880299","url":null,"abstract":"The features of linear predicate logic (based on propositional linear logic enriched by the first order predicate logic principles) are implemented in logic programming language called Vorvan. Subsequently, the time-space extension of linear logic — Ludics theory, is applied to selected clause of given language.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131378499","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880323
Yatish Bathla, M. Takács
Behavior Modeling is always a attentive task in the complex product modeling. It is difficult to monitor different kind of behavior of a product in the physical environment. In the RFLP (Requirement Functional Logical Physical) structure, behavior modeling is accomplished in Function and Logical level. There are several ways to monitor the behavior of a product. In this paper, author made an effort to monitor the behavior of a product system by proposing the Requirement, Function and Logical Block corresponds to RFLP structure and then monitor and improve the behavior of a product by using soft computing. In this context, Mamdani FIS (Fuzzy Inference System) and Adaptive Nuero FIS are used, which can evaluate the system behavior. Soft Computing, not only provide the solution of system behavior monitoring but also improve the performance of a system in terms of behavior such that product system are able to work efficiently.
{"title":"Evaluating product system behavior using soft computing in product structure modeling","authors":"Yatish Bathla, M. Takács","doi":"10.1109/SAMI.2017.7880323","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880323","url":null,"abstract":"Behavior Modeling is always a attentive task in the complex product modeling. It is difficult to monitor different kind of behavior of a product in the physical environment. In the RFLP (Requirement Functional Logical Physical) structure, behavior modeling is accomplished in Function and Logical level. There are several ways to monitor the behavior of a product. In this paper, author made an effort to monitor the behavior of a product system by proposing the Requirement, Function and Logical Block corresponds to RFLP structure and then monitor and improve the behavior of a product by using soft computing. In this context, Mamdani FIS (Fuzzy Inference System) and Adaptive Nuero FIS are used, which can evaluate the system behavior. Soft Computing, not only provide the solution of system behavior monitoring but also improve the performance of a system in terms of behavior such that product system are able to work efficiently.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122375755","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880347
Michal Smolik, V. Skala
The Radial Basis Function (RBF) interpolation is a common technique for scattered data interpolation. We present and test an approach of RBF interpolation on a sphere which uses the spherical distance on the surface of the sphere instead of the Euclidian distance. We show how the interpolation of vector field data depends on the value of shape parameter of RBF and find the optimal shape parameter for our experiments.
{"title":"Spherical RBF vector field interpolation: Experimental study","authors":"Michal Smolik, V. Skala","doi":"10.1109/SAMI.2017.7880347","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880347","url":null,"abstract":"The Radial Basis Function (RBF) interpolation is a common technique for scattered data interpolation. We present and test an approach of RBF interpolation on a sphere which uses the spherical distance on the surface of the sphere instead of the Euclidian distance. We show how the interpolation of vector field data depends on the value of shape parameter of RBF and find the optimal shape parameter for our experiments.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132425821","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880339
Dan-Adrian Duţescu, M. Radac, R. Precup
Model predictive control (MPC) represents a powerful technique for controlling a system that has an accurate mathematical model for describing its behavior. MPC implies solving an optimization problem (OP) in order to minimize some user defined objective function (OF) subjected to constraints on the characteristic variables. This paper presents a real-time implementation of a nonlinear MPC on a twin rotor aerodynamic system (TRAS). The mathematical model of TRAS is a nonlinear one and has only four measurable states out of six. In order to benefit from state-of-the-art OP solvers, online linearization of the TRAS mathematical model is used both for transforming the OP into a convex one and also for optimal estimation of the states using and Extended Kalman Filter (EKF) approach. Detailed implementation and validation of the proposed MPC approach is offered with insightful discussions.
{"title":"Model predictive control of a nonlinear laboratory twin rotor aero-dynamical system","authors":"Dan-Adrian Duţescu, M. Radac, R. Precup","doi":"10.1109/SAMI.2017.7880339","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880339","url":null,"abstract":"Model predictive control (MPC) represents a powerful technique for controlling a system that has an accurate mathematical model for describing its behavior. MPC implies solving an optimization problem (OP) in order to minimize some user defined objective function (OF) subjected to constraints on the characteristic variables. This paper presents a real-time implementation of a nonlinear MPC on a twin rotor aerodynamic system (TRAS). The mathematical model of TRAS is a nonlinear one and has only four measurable states out of six. In order to benefit from state-of-the-art OP solvers, online linearization of the TRAS mathematical model is used both for transforming the OP into a convex one and also for optimal estimation of the states using and Extended Kalman Filter (EKF) approach. Detailed implementation and validation of the proposed MPC approach is offered with insightful discussions.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133385752","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880317
N. Kumar, M. Takács, Z. Vámossy
In this paper, a Simulink model for the robot navigation in unknown environment is presented. The robot navigation is handled by two controllers: pure pursuit and fuzzy logic controller. The pure pursuit controller computes a direct path from start to goal position without considering the obstacles in the path. For obstacle avoidance in robot navigation, the fuzzy logic controller is taken. This fuzzy logic controller takes the input from the laser sensor of the robot and gives the change in the angular velocity as output to the robot to avoid the obstacle. The navigation paths resulting from the proposed Simulink model, with and without obstacles in the paths, are shown in figures.
{"title":"Robot navigation in unknown environment using fuzzy logic","authors":"N. Kumar, M. Takács, Z. Vámossy","doi":"10.1109/SAMI.2017.7880317","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880317","url":null,"abstract":"In this paper, a Simulink model for the robot navigation in unknown environment is presented. The robot navigation is handled by two controllers: pure pursuit and fuzzy logic controller. The pure pursuit controller computes a direct path from start to goal position without considering the obstacles in the path. For obstacle avoidance in robot navigation, the fuzzy logic controller is taken. This fuzzy logic controller takes the input from the laser sensor of the robot and gives the change in the angular velocity as output to the robot to avoid the obstacle. The navigation paths resulting from the proposed Simulink model, with and without obstacles in the paths, are shown in figures.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081135","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880318
Daniel W. Carruth, Cindy L. Bethel
As robotic systems become increasingly sophisticated, there is strong interest in deploying them in challenging and stressful environments. There are many potential advantages for the use of robotic systems in law enforcement and military operations. Robotic systems can provide the ability to perceive and act at a safe distance. However, achieving the full potential of robotic systems integration presents significant research challenges. The authors have observed field evaluations of candidate robotic systems, assessed potential roles for robots in tactical operations, evaluated standard and novel command and control interfaces, investigated levels of automation, and developed intelligent systems to support robot operations. Recently, a 6-month evaluation of an iterative development process for a command and control interface for distractionary devices (lights and sounds) was completed. Effective integration of a robotic system presents significant communication and machine intelligence challenges. A fully integrated robotic system should be able to understand and participate in actions as a team member with limited direct communication. This requires that the robot demonstrate scene understanding, situation awareness, knowledge of tactical operations, and more. The authors will discuss lessons learned and identify opportunities for future research to expand the capabilities of tactical robotic systems.
{"title":"Challenges with the integration of robotics into tactical team operations","authors":"Daniel W. Carruth, Cindy L. Bethel","doi":"10.1109/SAMI.2017.7880318","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880318","url":null,"abstract":"As robotic systems become increasingly sophisticated, there is strong interest in deploying them in challenging and stressful environments. There are many potential advantages for the use of robotic systems in law enforcement and military operations. Robotic systems can provide the ability to perceive and act at a safe distance. However, achieving the full potential of robotic systems integration presents significant research challenges. The authors have observed field evaluations of candidate robotic systems, assessed potential roles for robots in tactical operations, evaluated standard and novel command and control interfaces, investigated levels of automation, and developed intelligent systems to support robot operations. Recently, a 6-month evaluation of an iterative development process for a command and control interface for distractionary devices (lights and sounds) was completed. Effective integration of a robotic system presents significant communication and machine intelligence challenges. A fully integrated robotic system should be able to understand and participate in actions as a team member with limited direct communication. This requires that the robot demonstrate scene understanding, situation awareness, knowledge of tactical operations, and more. The authors will discuss lessons learned and identify opportunities for future research to expand the capabilities of tactical robotic systems.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116645893","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880279
M. Sarnovský, David Bajus
Presented paper describes the use of clustering methods in building environment analysis task. The presented approach is based on modeling of the sensor data containing information about humidity and temperature. Such models are then used to describe the level of the comfort of particular environment. K-means clustering algorithm was used to create those models. The paper then presents and describes a method of user interaction with the environment model. User feed-back represents how the user feels in the current environment. Feedback is then collected and evaluated. Based on the feedback, models can trigger the change of current environment or during the time, re-compute themselves in order to pro-vide more precise building environment representation. Our solution was based on real sensor data obtained from university buildings and presented solution was implemented on top of Hadoop cluster using Mahout library for machine learning.
{"title":"Building environment analysis based on clustering methods from sensor data on top of the Hadoop platform","authors":"M. Sarnovský, David Bajus","doi":"10.1109/SAMI.2017.7880279","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880279","url":null,"abstract":"Presented paper describes the use of clustering methods in building environment analysis task. The presented approach is based on modeling of the sensor data containing information about humidity and temperature. Such models are then used to describe the level of the comfort of particular environment. K-means clustering algorithm was used to create those models. The paper then presents and describes a method of user interaction with the environment model. User feed-back represents how the user feels in the current environment. Feedback is then collected and evaluated. Based on the feedback, models can trigger the change of current environment or during the time, re-compute themselves in order to pro-vide more precise building environment representation. Our solution was based on real sensor data obtained from university buildings and presented solution was implemented on top of Hadoop cluster using Mahout library for machine learning.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114417896","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880337
M. Miskuf, P. Michalik, I. Zolotová
This paper focuses on use of Matlab for data mining. There is wide range of data mining software where free or cheaper solutions offer similar possibilities. We wanted to try Matlab for these purposes. Our data consists of parameters, which describes cloud usage at IT company that offers cloud services. We used phases from the CRISP-DM methodology in our work. We built clustering and classification models that use functions of the Statistics and Machine Learning Toolbox. In the conclusion we summarize our outcomes, weather Matlab is appropriate to data analysis based on conducted experiments.
{"title":"Data mining in cloud usage data with Matlab's statistics and machine learning toolbox","authors":"M. Miskuf, P. Michalik, I. Zolotová","doi":"10.1109/SAMI.2017.7880337","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880337","url":null,"abstract":"This paper focuses on use of Matlab for data mining. There is wide range of data mining software where free or cheaper solutions offer similar possibilities. We wanted to try Matlab for these purposes. Our data consists of parameters, which describes cloud usage at IT company that offers cloud services. We used phases from the CRISP-DM methodology in our work. We built clustering and classification models that use functions of the Statistics and Machine Learning Toolbox. In the conclusion we summarize our outcomes, weather Matlab is appropriate to data analysis based on conducted experiments.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127045560","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880320
B. Czakó, K. Kósi
In the past few years quadcopters have become an integral part of life. There are many applications for these objects including entertaining purpose, agricultural monitoring, or gathering information from places what humans can not reach. An interesting problem is controlling these vehicles from remote locations in order to follow a desired trajectory. While many solutions exist to this task the vast majority of them heavily rely on linear control methods which are susceptible to parameter uncertainties or outer disturbances, which affect the tracking capability of the quadcopter adversely. In this paper a novel nonlinear approach, called Robust Fixed Point Transformation based adaptive control (RFPT) is presented which can provide remedy to the above mentioned disturbances.
{"title":"Novel method for quadcopter controlling using nonlinear adaptive control based on robust fixed point transformation phenomena","authors":"B. Czakó, K. Kósi","doi":"10.1109/SAMI.2017.7880320","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880320","url":null,"abstract":"In the past few years quadcopters have become an integral part of life. There are many applications for these objects including entertaining purpose, agricultural monitoring, or gathering information from places what humans can not reach. An interesting problem is controlling these vehicles from remote locations in order to follow a desired trajectory. While many solutions exist to this task the vast majority of them heavily rely on linear control methods which are susceptible to parameter uncertainties or outer disturbances, which affect the tracking capability of the quadcopter adversely. In this paper a novel nonlinear approach, called Robust Fixed Point Transformation based adaptive control (RFPT) is presented which can provide remedy to the above mentioned disturbances.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126234574","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 : 1900-01-01DOI: 10.1109/SAMI.2017.7880354
M. Franeková, P. Holecko, E. Bubeníková, A. Kanáliková
In the paper the authors focus on models construction of transport scenarios with orientation to security analysis of C2C communications. In the practical part two transport scenarios are analysed on a sample of real captured transport data via Riverbed Modeler tool. The computational complexity of ECDSA digital signature schemes was determined according to several selected EC curves and the efficiency of a PC. For the worst case transport scenario, the parameters throughput of network and delay between transmitted and received messages were analysed according to the number of nodes and message lengths.
{"title":"Transport scenarios analysis within C2C communications focusing on security aspects","authors":"M. Franeková, P. Holecko, E. Bubeníková, A. Kanáliková","doi":"10.1109/SAMI.2017.7880354","DOIUrl":"https://doi.org/10.1109/SAMI.2017.7880354","url":null,"abstract":"In the paper the authors focus on models construction of transport scenarios with orientation to security analysis of C2C communications. In the practical part two transport scenarios are analysed on a sample of real captured transport data via Riverbed Modeler tool. The computational complexity of ECDSA digital signature schemes was determined according to several selected EC curves and the efficiency of a PC. For the worst case transport scenario, the parameters throughput of network and delay between transmitted and received messages were analysed according to the number of nodes and message lengths.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123285662","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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