Browsing by Subject "Knowledge based systems"

Now showing 1 - 9 of 9

Open Access
Autonomous multiple teams establishment for mobile sensor networks by SVMs within a potential field
(2012) Nazlibilek, S.
In this work, a new method and algorithm for autonomous teams establishment with mobile sensor network units by SVMs based on task allocations within a potential field is proposed. The sensor network deployed into the environment using the algorithm is composed of robot units with sensing capability of magnetic anomaly of the earth. A new algorithm is developed for task assignment. It is based on the optimization of weights between robots and tasks. The weights are composed of skill ratings of the robots and priorities of the tasks. Multiple teams of mobile units are established in a local area based on these mission vectors. A mission vector is the genetic and gained background information of the mobile units. The genetic background is the inherent structure of their knowledge base in a vector form but it can be dynamically updated with the information gained later on by experience. The mission is performed in a magnetic anomaly environment. The initial values of the mission vectors are loaded by the task assignment algorithm. The mission vectors are updated at the beginning of each sampling period of the motion. Then the teams of robots are created by the support vector machines. A linear optimal hyperplane is calculated by the use of SVM algorithm during training period. Then the robots are classified as teams by use of SVM mechanism embedded in the robots. The support vector machines are implemented in the robots by ordinary op-amps and basic logical gates. Team establishment is tested by simulations and a practical test-bed. Both simulations and the actual operation of the system prove that the system functions satisfactorily. © 2012 Elsevier Ltd. All rights reserved.
Open Access
Comparative analysis of different approaches to target differentiation and localization with sonar
(Elsevier, 2003) Barshan, B.; Ayrulu, B.
This study compares the performances of different methods for the differentiation and localization of commonly encountered features in indoor environments. Differentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identification, map building, navigation, obstacle avoidance, and target tracking. Different representations of amplitude and time-of-2ight measurement patterns experimentally acquired from a real sonar system are processed. The approaches compared in this study include the target differentiation algorithm, Dempster-Shafer evidential reasoning, different kinds of voting schemes, statistical pattern recognition techniques (k-nearest neighbor classifier, kernel estimator, parameterized density estimator, linear discriminant analysis, and fuzzy c-means clustering algorithm), and artificial neural networks. The neural networks are trained with different input signal representations obtained usingpre-processing techniques such as discrete ordinary and fractional Fourier, Hartley and wavelet transforms, and Kohonen's self-organizing feature map. The use of neural networks trained with the back-propagation algorithm, usually with fractional Fourier transform or wavelet pre-processing results in near perfect differentiation, around 85% correct range estimation and around 95% correct azimuth estimation, which would be satisfactory in a wide range of applications. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Open Access
An English-to-Turkish interlingual MT system
(Springer, 1998-10) Hakkani, Dilek Zeynep; Tür, Gökhan; Oflazer, Kemal; Mitamura, T.; Nyberg, E.H.
This paper describes the integration of a Turkish generation system with the KANT knowledge-based machine translation system to produce a prototype English-Turkish interlingua-based machine translation system. These two independently constructed systems were successfully integrated within a period of two months, through development of a module which maps KANT interlingua expressions to Turkish syntactic structures. The combined system is able to translate completely and correctly 44 of 52 benchmark sentences in the domain of broadcast news captions. This study is the first known application of knowledge-based machine translation from English to Turkish, and our initial results show promise for future development. © Springer-Verlag Berlin Heidelberg 1998.
Open Access
Integration of reasoning systems in architectural modeling activities
(Elsevier Science, 1998) Demirkan, H.
In the first phase of a design process, the designer understands the problem and assimilates it to a conceptual framework that is already known to him. Due to the nature of design problems, the reasoning methods and techniques for modeling are not uniform and clear. An integrated reasoning system is proposed for modeling the architectural processes. Such a system may help designers to make decisions based on past experiences as well as domain theory. The performance of the integration approach is compared with the pure case-based and rule-based reasoning systems to study the efficiency and effectiveness in the same domains. The study tried to identify the reasoning systems used by designers pertaining to the interior design applications. © 1998 Published by Elsevier Science B.V.
Open Access
Object based 3-D motion and structure estimation
(IEEE, 1996) Alatan, A. Aydın; Onural, Levent
Motion analysis is the most crucial part of object-based coding. A motion in 3-D environment can be analyzed better by using a 3-D motion model compared to its 2-D counterpart and hence may improve coding efficiency. Gibbs formulated joint segmentation and estimation of 2-D motion not only improves performance, but also generates robust point correspondences which are necessary for linear 3-D motion estimation algorithms. Estimated 3-D motion parameters are used to find the structure of the previously segmented objects by minimizing another Gibbs energy. Such an approach achieves error immunity compared to linear algorithms. Experimental results are promising and hence the proposed motion and structure analysis method is a candidate to be used in object-based (or even knowledge-based) video coding schemes.
Open Access
Progression of color decision making in introductory design education
(Wiley, 2017-04) Ertez Ural, Sibel; Akbay, S.; Altay, Burçak
Color comprises both subjective and objective aspects within its contextual nature. Research on color design tends to explore this seemingly contradictory concerns from theoretical point of view, as well as architectural and design practice. The aim of this study was to observe subjective, intuitive or heuristic and objective, knowledge‐based or analytical attitudes toward color in design education. In the study 84 introductory design students were surveyed progressively to understand their color decision criteria after completion of three 2‐dimensional colored exercises, specific in terms of color education. Students' responses to open‐ended questions were coded according to the 5 categories, under 2 decision making processes derived from the literature; heuristic approach: preferential and symbolic criteria, and analytic reasoning: formal, thematic, and systematic criteria. A distinction between associative and emotional aspects of symbolic criteria was also revealed by the data analysis. The findings showed a shift from heuristic responses to analytic reasoning, as expected. Additionally, it is also investigated that students not only used heuristic approaches but also analytical components (formal and systematic) of color decision making in varying degrees as well, even before any color subjects covered. Thematic color decisions became a major part of the students' design considerations upon completion of color subjects. The observed increase in the number of color criteria interrelated by the students' among almost all categories explicated a complex decision making process particularly in color design and education. These findings were expected to lead to some further understanding in color decision making in design.
Open Access
Realistic modeling of spectator behavior for soccer videogames with CUDA
(2011) Ylmaz, E.; Molla, E.; Yıldız, C.; İşler V.
Soccer has always been one of the most popular videogame genres. When designing a soccer game, designers tend to focus on the game field and game play due to the limited computational resources, and thus the modelling of virtual spectators is paid less attention. In this study we present a novel approach to the modeling of spectator behavior, which treats each spectator as a unique individual. We also propose an independent software layer for sport-based games that simply obtains the game status from the game engine via a simple messaging protocol and computes the spectator behavior accordingly. The result is returned to the game engine, to be used in the animation and rendering of the spectators. Additionally, we offer a customizable spectator knowledge base with well structured XML to minimize coding efforts, while generating individualized behavior. The employed AI is based on fuzzy inference. In order to overcome additional demand for computing realistic spectator behavior, we use GPU parallel computing with CUDA. © 2011 Elsevier Ltd. All rights reserved.
Open Access
Rule-based target differentiation and position estimation based on infrared intensity measurements
(SPIE, 2003) Aytaç, T.; Barshan, B.
This study investigates the use of low-cost infrared sensors in the differentiation and localization of target primitives commonly encountered in indoor environments, such as planes, corners, edges, and cylinders. The intensity readings from such sensors are highly dependent on target location and properties in a way that cannot be represented in a simple manner, making the differentiation and localization difficult. We propose the use of angular intensity scans from two infrared sensors and present a rule-based algorithm to process them. The method can achieve position-invariant target differentiation without relying on the absolute return signal intensities of the infrared sensors. The method is verified experimentally. Planes, 90-deg corners, 90-deg edges, and cylinders are differentiated with correct rates of 90%, 100%, 82.5%, and 92.5%, respectively. Targets are localized with average absolute range and azimuth errors of 0.55 cm and 1.03 deg. The demonstration shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.
Open Access
Simultaneous 3-D motion estimation and wire-frame model adaptation including photometric effects for knowledge-based video coding
(IEEE, 1994) Bozdağı, Gözde; Tekalp, A. M.; Onural, Levent
We address the problem of 3-D motion estimation in the context of knowledge-based coding of facial image sequences. The proposed method handles the global and local motion estimation and the adaptation of a generic wire-frame to a particular speaker simultaneously within an optical flow based framework including the photometric effects of motion. We use a flexible wire-frame model whose local structure is characterized by the normal vectors of the patches which are related to the coordinates of the nodes. Geometrical constraints that describe the propagation of the movement of the nodes are introduced, which are then efficiently utilized to reduce the number of independent structure parameters. A stochastic relaxation algorithm has been used to determine optimum global motion estimates and the parameters describing the structure of the wire-frame model. For the initialization of the motion and structure parameters, a modified feature based algorithm is used. Experimental results with simulated facial image sequences are given.