Pub Date : 2013-11-01DOI: 10.1109/CINTI.2013.6705247
Michal Fornadel, P. Lacko, A. Danko
The paper proposes an approach for predicting application upgrade time that is being upgraded from one version to another. The focus is primarily concentrated on applications with upgrades consisting mainly of upgrading the relational database. Chosen application databases have the same schema but the content of tables varies. Data from the upgrades are processed and the proposed solution predicting duration of upgrade for the database which is set to be upgraded provides an estimation whose accuracy is dependent on the number of performed upgrades. The solution is demonstrated on particular enterprise application.
{"title":"Estimation of legacy application upgrade time using evolutionary approach","authors":"Michal Fornadel, P. Lacko, A. Danko","doi":"10.1109/CINTI.2013.6705247","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705247","url":null,"abstract":"The paper proposes an approach for predicting application upgrade time that is being upgraded from one version to another. The focus is primarily concentrated on applications with upgrades consisting mainly of upgrading the relational database. Chosen application databases have the same schema but the content of tables varies. Data from the upgrades are processed and the proposed solution predicting duration of upgrade for the database which is set to be upgraded provides an estimation whose accuracy is dependent on the number of performed upgrades. The solution is demonstrated on particular enterprise application.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123539102","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705242
M. Burda
The aim of this paper is to present a bitwise approach on evaluation of fuzzy t-norms. T-norms are functions that generalize the notion of conjunction, and as such play an important role in fuzzy association rule mining process. Efficient algorithms for batch evaluation of the most common t-norms is proposed that minimizes computation time as well as memory space requirements at the cost of user-adjustable loss of precision of the membership degrees.
{"title":"Fast evaluation of t-norms for fuzzy association rules mining","authors":"M. Burda","doi":"10.1109/CINTI.2013.6705242","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705242","url":null,"abstract":"The aim of this paper is to present a bitwise approach on evaluation of fuzzy t-norms. T-norms are functions that generalize the notion of conjunction, and as such play an important role in fuzzy association rule mining process. Efficient algorithms for batch evaluation of the most common t-norms is proposed that minimizes computation time as well as memory space requirements at the cost of user-adjustable loss of precision of the membership degrees.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126253817","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705256
Cristian Cosariu, L. Prodan, M. Vladutiu
This paper describes an adaptive algorithm that can be used to optimize traffic movements by controlling the traffic signal operations in an intersection and sets the framework for adjacent intersections. Inter-traffic signal communication is used to respond to traffic changes by deriving new timings. We illustrate the proposed solution through a case study conducted over the city of Timisoara, Romania. Our algorithm was tested using the VISSIM simulator and results show improvements in reducing waiting times and queue lengths over the currently deployed solution based on fixed time plans.
{"title":"Toward traffic movement optimization using adaptive inter-traffic signaling","authors":"Cristian Cosariu, L. Prodan, M. Vladutiu","doi":"10.1109/CINTI.2013.6705256","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705256","url":null,"abstract":"This paper describes an adaptive algorithm that can be used to optimize traffic movements by controlling the traffic signal operations in an intersection and sets the framework for adjacent intersections. Inter-traffic signal communication is used to respond to traffic changes by deriving new timings. We illustrate the proposed solution through a case study conducted over the city of Timisoara, Romania. Our algorithm was tested using the VISSIM simulator and results show improvements in reducing waiting times and queue lengths over the currently deployed solution based on fixed time plans.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127243540","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705219
Balázs Varga, B. Németh, P. Gáspár
The paper proposes the modeling and control design of an active anti-roll bar actuator. The vehicle dynamic system improves the roll stability of a light commercial vehicle generating an active torque on the chassis, provided by an electro-hydraulic actuator. The actuator control system must guarantee the generation of the required active torque, satisfying the input limits of the actuator. The actuation of electro-hydraulic system is described by fluid dynamical, electrical and mechanical equations. The input of the formulated state-space actuator model is the valve current, while the output is the generated active torque. The tracking controller of the actuator is designed based on constrained Linear Quadratic (LQ) method. The designed controller guarantees the tracking performance and the avoidance of constraint violation simultaneously. The operation of the designed control system is illustrated through simulation examples.
{"title":"Control design of anti-roll bar actuator based on constrained LQ method","authors":"Balázs Varga, B. Németh, P. Gáspár","doi":"10.1109/CINTI.2013.6705219","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705219","url":null,"abstract":"The paper proposes the modeling and control design of an active anti-roll bar actuator. The vehicle dynamic system improves the roll stability of a light commercial vehicle generating an active torque on the chassis, provided by an electro-hydraulic actuator. The actuator control system must guarantee the generation of the required active torque, satisfying the input limits of the actuator. The actuation of electro-hydraulic system is described by fluid dynamical, electrical and mechanical equations. The input of the formulated state-space actuator model is the valve current, while the output is the generated active torque. The tracking controller of the actuator is designed based on constrained Linear Quadratic (LQ) method. The designed controller guarantees the tracking performance and the avoidance of constraint violation simultaneously. The operation of the designed control system is illustrated through simulation examples.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123845540","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705205
G. Windisch, M. Kozlovszky
Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.
{"title":"Improvement of texture based image segmentation algorithm for HE stained tissue samples","authors":"G. Windisch, M. Kozlovszky","doi":"10.1109/CINTI.2013.6705205","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705205","url":null,"abstract":"Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129277365","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705191
B. Villányi, P. Martinek
Schema matching has the task of identifying semantically related entities in schemas. In the classic approach, a semantic distance is established among schema entities of the input schemas, based on which values the entity pairs are classified as match or non-match by means of a threshold value. This approach is, however, cumbersome in some schema matching related problem, like the accuracy measure maximization and the cutting threshold problem. In our earlier works, we proposed the concept of the schema matching threshold function for such cases. We assumed that the schema matching threshold function is, however, highly related to the concept of fuzzy membership functions. This assumed relation has encouraged us to perform a comparison between the schema matching threshold function and the fuzzy membership function which comparison is the topic of this paper. We used ANFIS for obtaining membership functions which were mapped to adequate threshold functions in order to be able to compare them. The outcome of our comparative analysis was that these mapped function pairs significantly resemble to each other.
{"title":"A comparison of schema matching threshold function and ANFIS generated membership function","authors":"B. Villányi, P. Martinek","doi":"10.1109/CINTI.2013.6705191","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705191","url":null,"abstract":"Schema matching has the task of identifying semantically related entities in schemas. In the classic approach, a semantic distance is established among schema entities of the input schemas, based on which values the entity pairs are classified as match or non-match by means of a threshold value. This approach is, however, cumbersome in some schema matching related problem, like the accuracy measure maximization and the cutting threshold problem. In our earlier works, we proposed the concept of the schema matching threshold function for such cases. We assumed that the schema matching threshold function is, however, highly related to the concept of fuzzy membership functions. This assumed relation has encouraged us to perform a comparison between the schema matching threshold function and the fuzzy membership function which comparison is the topic of this paper. We used ANFIS for obtaining membership functions which were mapped to adequate threshold functions in order to be able to compare them. The outcome of our comparative analysis was that these mapped function pairs significantly resemble to each other.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127965008","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705175
V. Asari
The human brain processes enormous volumes of high-dimensional data for everyday perception. To humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. We present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in a low-dimensional image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural architecture. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural architecture, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self-organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on various databases show that the proposed nonlinear line attractor is able to successfully associate patterns and it provides better association when compared to other state of the art techniques. It shows that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.
{"title":"A nonlinear manifold learning strategy for lighting and orientation invariant pattern recognition","authors":"V. Asari","doi":"10.1109/CINTI.2013.6705175","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705175","url":null,"abstract":"The human brain processes enormous volumes of high-dimensional data for everyday perception. To humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. We present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in a low-dimensional image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural architecture. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural architecture, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self-organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on various databases show that the proposed nonlinear line attractor is able to successfully associate patterns and it provides better association when compared to other state of the art techniques. It shows that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126618051","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705235
M. Papoutsidakis, D. Piromalis, G. Chamilothoris
One of the numerous implementations, Intelligent Systems Lab of the Technological Institute of Piraeus, Greece, has recently accomplished are described in this paper. Within the area of small mobile robots design, the project combines computer science in modern network protocol communication and microcontroller based motion control tasks. The goal of building autonomous hand-on robotic platforms for multiple educational and every day applications in society, has long been an area of investigation and development for researchers and engineers. The presented pair of versatile robots in this project is designed to act as the “chase and hunter” application, which at least meets the requirements of constant need for evolution in the robotics domain. Low cost, though modern and up to date technology was used and all gear data will be explained in details as well as the performing scenario.
{"title":"Low cost swarm robotic platforms operating with open-source software for cooperative applications","authors":"M. Papoutsidakis, D. Piromalis, G. Chamilothoris","doi":"10.1109/CINTI.2013.6705235","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705235","url":null,"abstract":"One of the numerous implementations, Intelligent Systems Lab of the Technological Institute of Piraeus, Greece, has recently accomplished are described in this paper. Within the area of small mobile robots design, the project combines computer science in modern network protocol communication and microcontroller based motion control tasks. The goal of building autonomous hand-on robotic platforms for multiple educational and every day applications in society, has long been an area of investigation and development for researchers and engineers. The presented pair of versatile robots in this project is designed to act as the “chase and hunter” application, which at least meets the requirements of constant need for evolution in the robotics domain. Low cost, though modern and up to date technology was used and all gear data will be explained in details as well as the performing scenario.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129837403","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705225
P. Eredics, T. Dobrowiecki
A wide variety of greenhouse temperature models have been proposed in the literature in the previous years. This paper proposes a hybrid modeling method incorporating a multilayer perceptron neural network and a radial basis function neural network aimed to be more accurate on input regions not covered by training data. The results show that the proposed method has better performance compared to the original physical-neural hybrid model if the input values are not far from the input range of the values used for training.
{"title":"Hybrid MLP-RBF model structure for short-term internal temperature prediction in greenhouse environments","authors":"P. Eredics, T. Dobrowiecki","doi":"10.1109/CINTI.2013.6705225","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705225","url":null,"abstract":"A wide variety of greenhouse temperature models have been proposed in the literature in the previous years. This paper proposes a hybrid modeling method incorporating a multilayer perceptron neural network and a radial basis function neural network aimed to be more accurate on input regions not covered by training data. The results show that the proposed method has better performance compared to the original physical-neural hybrid model if the input values are not far from the input range of the values used for training.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130704259","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 : 2013-11-01DOI: 10.1109/CINTI.2013.6705251
R. Boboc, Madalina-Ioana Toma, Alina Ninett Panfir, D. Talaba
Today's humanoid robots are used in many successful research topics. According to users needs these robots must be able to perform new tasks, and to adapt in a workspace. They have a similar appearance with human body. Thus the meaningful features of an humanoid robots are: the capability to imitate the user behavior, and the ability to learn new skills. In this paper, we propose to develop a robot system based on an humanoid robot that has abilities to learn new user skills by imitating human beings. To achieve this goal, we needed to design and to implement a new framework, which is able to teach an humanoid robot via user demonstration and to imitate movements of the human body. Therefore, the movements of the human body are automatically tracked using the Kinect sensor, and they teleoperate a whole body of a Nao robot. The results of experiments suggest that the feasibility of the proposed system is verified.
{"title":"Learning new skills by a humanoid robot through imitation","authors":"R. Boboc, Madalina-Ioana Toma, Alina Ninett Panfir, D. Talaba","doi":"10.1109/CINTI.2013.6705251","DOIUrl":"https://doi.org/10.1109/CINTI.2013.6705251","url":null,"abstract":"Today's humanoid robots are used in many successful research topics. According to users needs these robots must be able to perform new tasks, and to adapt in a workspace. They have a similar appearance with human body. Thus the meaningful features of an humanoid robots are: the capability to imitate the user behavior, and the ability to learn new skills. In this paper, we propose to develop a robot system based on an humanoid robot that has abilities to learn new user skills by imitating human beings. To achieve this goal, we needed to design and to implement a new framework, which is able to teach an humanoid robot via user demonstration and to imitate movements of the human body. Therefore, the movements of the human body are automatically tracked using the Kinect sensor, and they teleoperate a whole body of a Nao robot. The results of experiments suggest that the feasibility of the proposed system is verified.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132011763","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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