Teaching engineering and technology subjects involves conveying understanding of abstract information structures and processes such as complex telecommunications protocols, complex mathematical concepts, and data stru...
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Teaching engineering and technology subjects involves conveying understanding of abstract information structures and processes such as complex telecommunications protocols, complex mathematical concepts, and data structures. These are multidimensional and can be difficult to grasp quickly. Supported by a Hewlett-Packard (HP) Technology for Teaching grant, the school of engineering and Technology at National University has embarked on a project to enable students to grasp these complex concepts more quickly and easily, using continuous dialog among students and instructors as the structures are first introduced and then examined from multiple perspectives through real-time interaction among students, small groups, and instructors. HP Wireless Tablet PCs are used to discuss and experiment with diagrams and processes in realtime. This allows combining lectures and problem-solving sessions into a single class session. Our hypothesis is that: 1) an in-depth learning of theory is accomplished, and 2) student engagement is enhanced. Presentation of theory by the instructor is integrated with application while the theory is still in the student's short-term memory. Students no longer have to wait for a separate session such as a recitation session to apply the concepts. This approach often takes less time. In addition to accelerating the learning process, expert instructors find this approach more rewarding as students grasp new concepts more quickly. Analysis of data captured from both students and instructors are presented to support our hypotheses, and our results are compared with similar research carried out by other universities. In addition, the level of interaction enabled by the use of HP Tablets in on-line classes is discussed. The best teaching tools available in existing on-line teaching platforms are compared with the additional tools available in on-site courses when every student has a wireless Tablet PC and specific recommendations are made to on-line teachi
Visual surveillance with dynamic background is one of the most active research topics in computer vision. Especially, researches for abandoned detection in the public place have been caused by preventing terror and ac...
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Visual surveillance with dynamic background is one of the most active research topics in computer vision. Especially, researches for abandoned detection in the public place have been caused by preventing terror and accident. Previous researches for abandoned detection have been based on a static image and used an image difference. In this paper we present an algorithm for a mobile robot and we use optical flow for detecting a static object and distances from abandoned objects. For this purpose, we find abandoned objects and predict a position of objects using a mobile robot visual system with a single camera.
Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in ...
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Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in object-tracking technology in computer vision fields. However, it has a drawback of getting into a bottleneck state when faced with a speedy object moving beyond its window size within one image frame interval time. The time required to calculate mean-shift vector could be much lessened with lesser memory when color model is adjusted to the previously known target information. This paper shows the building process of target-adjusted model with a non-uniform quantization. The target color model dealt in this paper is the one used for deriving mean-shift vector. It is a kernel model containing both the color and distance information. This paper gives scheme to efficiently deal with color information in the model. Through a proper selection of color bins, unimportant color values were reduced to a small amount. As a result, the computing time of the mean-shift vector in face-tracking was shortened while maintaining robustness and accuracy.
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, a...
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, and their structures incrementally are growing up from minimal structure. It is a non-mating method. It employs 5 mutation operators: add connection, add node, delete connection, delete node, and new initial weight. And the connection weight is trained by the simplified alopex method, which is a correlation based method for solving optimization problem. In AWMM, structural information is encoded to weighting matrix, and the matrix is augmenting as the hidden nodes are added.
In this paper, we proposed an analog neural controller (ANC) that is similar to physical modeling of the nervous system. ANC is composed of sensory neurons, motor neurons, synapses and dendrites. The functions of sens...
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ISBN:
(纸本)9812835768
In this paper, we proposed an analog neural controller (ANC) that is similar to physical modeling of the nervous system. ANC is composed of sensory neurons, motor neurons, synapses and dendrites. The functions of sensory neurons generate CPG signals and motor neurons change the sensory neuron signal for driving actuators. Synapses connect between neurons and the weigh to be given. Dendrites can accept external signal from the sensor. Because of parallel structure which is one of main characteristic of ANC, it is possible to walk by generating new pattern even though one of the neuron is out of working.
Lane detection is an essential component of autonomous mobile robot applications. Any lane detection method has to deal with the varying conditions of the lane and surrounding that the robot would encounter while movi...
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Lane detection is an essential component of autonomous mobile robot applications. Any lane detection method has to deal with the varying conditions of the lane and surrounding that the robot would encounter while moving. Lane detection procedure can provide estimates for the position and orientation of the robot within the lane and also can provide a reference system for locating other obstacles in the path of the robot. In this paper we present a method for lane detection in video frames of a camera mounted on top of the mobile robot. Given video input from the camera, the gradient of the current lane in the near field of view are automatically detected. Randomized Hough Transform is used for extracting parametric curves from the images acquired. A priori knowledge of the lane position is assumed for better accuracy of lane detection.
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna...
In this paper, a method of estimating both the position and the rotation angle of an object on a measurement stage was proposed. The system utilizes the radio communication technology and the directivity of an antenna. As a prototype system, a measurement stage (a circle 240mm in diameter) with 36 antennas that placed in each 10 degrees was developed. Two transmitter antennas are settled in a right angle on the stage as the target object, and the position and the rotation angle is estimated by measuring efficiency of the radio communication of each 36 antennas. The experimental result revealed that even when the estimated location is not so accurate (about a 30 mm error), the rotation angle is accurately estimated (about 2.33 degree error on average). The result suggests that the proposed method will be useful for estimating the location and the direction of an object.
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle...
In this paper, a handle-electrode system is proposed for obtaining the heart rate of a user while riding a bicycle. The system was designed to measure the user's heart rate by only gripping the handle of a bicycle. Three electrodes made from conductive cloth were adhered to the handle. A method detecting heart-rate from the obtained electrocardiogram was also proposed. To assess the applicability of the proposed system, a simple experiment was performed. The experiment was performed in four conditions of road surfaces; lawn, asphalt, a tiled, and an uneven road. Experimental result suggests that the proposed system can be useful for obtaining R waves while riding a bicycle.
Active appearance model (AAM) has been widely used in face tracking and recognition. However, accuracy and efficiency are always two main challenges with the AAM search. The paper therefore proposed a fast appearance-...
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ISBN:
(纸本)9781424422944
Active appearance model (AAM) has been widely used in face tracking and recognition. However, accuracy and efficiency are always two main challenges with the AAM search. The paper therefore proposed a fast appearance-model based 3D face tracking algorithm to track a face appearance with significant translation, rotation, and scaling activities by using stochastic meta-descent (SMD) optimization scheme to accelerate the appearance model search and to improve the tracking efficiency and accuracy. The proposed algorithm constructs an active face appearance model by using several semantic landmark points extracted from each frame and then processes the appearance model search to approximate the model translating, rotating, and scaling by using the SMD filter to minimize the appearance difference between the current model and the new observation. We compared the results with both a conventional AAM and a Camshift filter and found that our algorithm outperforms both two in terms of efficiency and accuracy in tracking a fast moving, rotating, and scaling face object in a video sequence.
Density functional theory can accurately predict chemical and mechanical properties of nanostructures, although at a high computational cost. A quasicontinuum-like framework is proposed to substantially increase the s...
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