In this paper, we analyze a dynamic object manipulation (DOM) problem; throwing upward and catching a disc using two planar manipulators. The manipulators control the disc xy position dynamically and use its angular m...
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In this paper, we analyze a dynamic object manipulation (DOM) problem; throwing upward and catching a disc using two planar manipulators. The manipulators control the disc xy position dynamically and use its angular movement as a free parameter. We use a simple model for the system. Each manipulator has three links and three active joints. In addition, the disc has considerable radius and mass. Therefore, we design a simple mechanism in the palm to damp a portion of the impact
In this paper we have considered systems in which agents communicate via their environment. In these systems the agents do not have direct and explicit communication with each other and instead they have implicit comm...
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In this paper we have considered systems in which agents communicate via their environment. In these systems the agents do not have direct and explicit communication with each other and instead they have implicit communication which is performed via the environment they are located in. Different kinds of environment elements are considered to be changed while on the other hand for all of these situations there is a change in the environment and this change means potential stimuli that fires behaviors of agents for future. It is considered that if we can find a track of changes in the environment and find the roots of a movement in an agent that is originally made by another agent of the group
Several path-planning algorithms for mobile robots have been introduced. Proper architectures for mobile robots to implement the path-planning algorithms are also of interest. If the mobile robots are to perform compl...
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Several path-planning algorithms for mobile robots have been introduced. Proper architectures for mobile robots to implement the path-planning algorithms are also of interest. If the mobile robots are to perform complicated tasks including complex sensing and planning operations and have accepted performance, must be autonomous: capable of acquiring information and performing tasks without programmatic intervention. In this paper we employ a layered architecture for mobile robots to perform our previously introduced cellular automata based path planning technique. It employs an abstraction approach which makes the complexity manageable. The architecture has an important feature which is its internal artifacts; it has some beliefs about the world and these beliefs are represented in artifacts and most actions are planned and performed with respect to these artifacts
This paper presents a novel method for detecting multiple frontal faces in still images using multi-scale processing. The main characteristic of this algorithm is its stability in detecting faces with seldom false det...
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This paper presents a novel method for detecting multiple frontal faces in still images using multi-scale processing. The main characteristic of this algorithm is its stability in detecting faces with seldom false detections and a high correct detection rate. The novelty of this work comes from the utilization of multiscale detection and using two classifiers to reduce false detections. The algorithm generally has two stages: in the first stage, a face is detected in a unique scale and in the second stage, only the faces that are located in the neighbor scales are accepted as real faces. Consequently, a still image is first resized and scanned block wise, and then each enhanced block is tested for being face. One dimensional Harr wavelet is used for feature extraction, which gives appropriate discriminating features between the face and nonface classes. Detection results at each scale are accumulated in an internal database, so the ultimate detection is prepared based on the mutual detection information between consequent scales. To parameterize both the Bayesian and the simple proposed classifier, 2,643 faces were congregated from famous face databases and more than 10,000 non-face samples were selected from nature images. Experimental results using images gathered from known databases like MIT-CMU show great ability of the proposed algorithm in detecting faces.
In this paper, design principles and application of a thin and flexible intravascular top hat monopole probe with increased signal-to-noise ratio (SNR) and improved longitudinal and radial coverage are described and c...
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K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on...
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K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on information analysis step (2nd step) of K-BALL during which landmarks extracted in its first step are evaluated. We provide a framework in which rules are automatically generated based on estimated and derived models. We show that the rules based on the derived models can improve the overall success rate of K-BALL. Each rule evaluates the extracted points by producing an intermediate confidence factor (ICNF). A total confidence factor is calculated using ICNF's to facilitate the acceptance or rejection of a set of points as landmarks of interest. Using the rules merely based on the estimated models, simulation study produced an overall success rate of 91.8%. Using the rules based on both of the estimated and derived models, this rate increased to 92.5%
It has been previously shown that intensity and volume features of the hippocampus from MR images of the brain are useful in detecting the abnormality and consequently candidacy of the hippocampus for temporal lobe ep...
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It has been previously shown that intensity and volume features of the hippocampus from MR images of the brain are useful in detecting the abnormality and consequently candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. In this paper, we have studied and compared volume and texture features of hippocampus for TLE lateralization. Volume and some features describing the intensity non-uniformities are used. We use manual segmentation of the hippocampi from T1 weighted images and map them to the FLAIR images. Wavelet features as well as mean and variance of the hippocampus intensities of the FLAIR slices are used as texture features. A dataset of 55 patients with 28 right and 27 left abnormal sides was used in the experiments. Experimental results show that the volume and intensity features are useful in determining the abnormal side
In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw in...
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In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. Computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.
In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed mere...
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In this paper, a unique road contour extraction approach from high resolution satellite image is proposed, in which the road contour was extracted in two steps. Firstly, support vector machines (SVM) was employed merely to classify the image into two groups of categories: a road group and a non-road group. The identified road group images are the discrete and irregularly distributed sampled points, and they are an uncompleted data set for the road. Secondly, the road contour was extracted from the road group images using the tensor voting framework, since the tensor voting technique is superior to the traditional methods in extracting the geometrical structure from the uncompleted data set. The experimental results on the high resolution satellite image demonstrate that the proposed approach worked well with images comprised by both rural and urban area features.
This paper proposes a cooperative evolutionary method for optimizing the properties of an ANFIS-architecture-based model where only the input-output data of the identified system are available. The primary tasks of fu...
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