Showing 133–144 of 180 results
Application of A* Algorithm and Its Optimization MethodOpen Access
Abstract: Nowadays, the traffic congestion is becoming more and more serious. It is urgent to find a path planning algorithm with high efficiency. As a heuristic algorithm, A* algorithm can solve the
problem of path planning with high efficiency, and the design of heuristic function is particularly
important. By analyzing the problems of route planning, some improvements have been made in this paper: firstly, the evaluation function with two elements of distance and direction are considered; through the process of normalization, the problem of unified unit has been solved; secondly, use the smallest heap spatial to load the node information dynamically, and reduce the memory usage space.
Keywords: Heuristic algorithm, A* algorithm, cost function, smallest heap
Novel Design of a Wheelchair with Stair Climbing CapabilitiesOpen Access
Abstract: Stair climbing wheelchairs were created to help disabled people overcome one of the most common architectural barrier, stairs. Many types of devices have been developed using tracked, leg, leg-wheel and hybrid wheels to climb stairs but they are expensive, thus, out of the reach of the neediest. This paper presents a stair climbing wheelchair with four “X”-shaped wheel that uses its legs to climb and descend stairs. This mechanism maintains contact with the stairs during climbing activity to perform better at the climbing task. The seat of the wheelchair provides 1 DOF so that the inclination angle can be changed in order to correct the position of the center of gravity to be close to the center of the supporting polygon. An inertial measurement unit (IMU) sensor is used to detect the angle of the seat in relation to the ground and by using a motor utilizing PID control, automatically balance the seat in the horizontal position. In order to climb stairs smoothly, the angular position of the wheels should be the same, thus a PD control was implemented to control the position of the wheel so that they will be synchronized, therefore, capable of performing the climbing task at the same time and at the same position. Simulation and experimental results demonstrate the effectiveness of this mechanism and wheelchair.
Keywords: Disabled; stair; stairclimber; wheel-leg mechanism; wheelchair;
Control and Communication of a Multi-motor System based on LANOpen Access
Abstract: This paper establishes a multi-motor control system based on the local area network. It
introduces the control strategy and the master-slave network structure. It analyzes both the advantage and disadvantage of the traditional communication modes RS-422 and CAN. And based on the analysis, the paper puts forward a full-duplex communication method which combines the advantages of both RS-422 and CAN to achieve the network control for the multi-motor system.
Keywords: multi motor; master-slave network structure; LAN control; full duplex bus communication
Emergence of Proto-Communication using Action Primitives Symbolized in Recurrent Q-Learning AgentsOpen Access
Abstract: In this paper, we suppose the gesture theory that is one of the theories on the origin of
language, which tries to establish that the speech originated from gestures. Based on the theory, we assume that “actions” having some purposes can be used as “symbols” in the communication through a learning process. The purpose of this study is to clarify what abilities of agents are necessary to acquire usages of the actions as the symbols. To achieve the purpose, we adopt a collision avoidance game and recurrent Q-learning (RQL) agents as the game players. Our simulations showed that the RQL agents can emerge a proto-communication to avoid collision with opponent by using visual information that the opponent turns its own eye away from the agent through the learning process. Further, we found that the RQL agents also obtain a rotational behavior to avoid collision by expanding the maximum number of learning iteration.
Keywords: Collision Avoidance Game; Emergence of Proto-Communication; Neural Q-Learning
(NQL) Agents; Recurrent Q-Learning (RQL) Agents; Symbolization of Action Primitives
Parameter Optimization of the SVM for Big DataOpen Access
Abstract:The traditional SVM parameter optimization use a wide range of traversal algorithm or some intelligent iterative algorithm, generally need to consume great deal of time, it is not applicable to optimization parameters of big data sets .To get around this ,This paper presents a strategy of stepwise optimize parameters based on the contour plots of cross-validation accuracy. Generate 25 parameter combinations uniformly, output the contour plots of cross-validation accuracy, then narrowing the optimal region of the parameters, proceeding stepwise optimizing parameter, until the optimal parameters were found. Finally, use a 13910*128 data set to verify the algorithm, compare with the traditional grid search algorithm, the new method not only greatly shorten the time of SVM parameters optimization, and it can find the better parameter than the traditional methods. This paper provides an effective solution to optimize SVM parameters especially for large data.
Keywords: support vector machine, SVM , parameter optimization , big data
Development of English Learning System Using Subtitle of Japanese AnimeOpen Access
Abstract: This paper proposes a new method for learning English, by using English-subbed Japanese sounded cartoons (anime). In the proposed system, the English subtitles are recognized into text in real time and sent to the text-to-speech system. After that, the sound is generated and can be heard immediately, after Japanese sound. It means that, while the learner is watching anime, learner can hear the sound of English subtitles in immediately after he/she heard the sound of original Japanese. By hearing Japanese and English alternately a lot, finally the learner will be able to understand English. This system is suitable for everyone who wants to learn English while watching anime, including the child.
Keywords: English learning system; anime; subtitle recognition; text-to-speech
Research on Vehicle Actuated Coordinated Control Method Based on RFID Electronic TagOpen Access
Abstract: For traditional arterial road coordinated control with predetermined cycle, split, and offset
cannot adapt for dynamic real-time traffic flow. In addition traditional vehicle actuated coordinated
control will fail in oversaturated traffic status and other limitations. To overcome these limitations, this paper adopts active electronic tags to get the update ratio of the vehicles in the test range, changes time interval between vehicles as control basis in traditional vehicle actuated control theory, puts forward putting vehicle density as whether green light extension control basis by using RFID electronic tag in vehicle actuated control. When the vehicle density is higher than the setting threshold value, green light continues, on the contrary, switching the phase. The method not only can overcome the drawback that traditional vehicle actuated coordinated control will fail in oversaturated traffic status, but also can effectively improve the utilization of green light and decrease the average delay in the intersection, which has been verified by simulated experiment through VISSIM
Keywords: RFID; Coordinated control; Vehicle actuated control; Average delay
Hardware Design of the PMSM Control System Based on DSP and CPLDOpen Access
Abstract: This paper designs and realizes the hardware of a PMSM control system, in which DSP is the main controller and CPLD is the auxiliary logic controller. The proposed power driver consists of three independent H-bridge inverter drive circuits. The hardware are designed including the motor phase current detection, main voltage monitoring, signal acquisition of both rotor position and speed, overcurrent protection and other related circuits. The experimental results show that the motor controller is reliable and stable with strong practicability.
Keywords: Control System; CPLD; DSP; PMSM
JICE Vol 1 Issue 1Open Access
Published 25th December 2015, ISSN 2186-9162, Total Pages 65
Robust Keypoint Detection against Affine Transformation Using Moment Invariants on Intrinsic Mode FunctionOpen Access
Abstract: Scale Invariant Feature Transform (SIFT) is a method to detect and match invariant feature points on images, and is robust against contrast, rotation, and scale changes. However, SIFT cannot find many correct matching points between affine transformed images because this method employs Gaussian function for scale parameter which specifies a circle area on image planes. In this paper, we propose a method using Bi-dimensional Empirical Mode Decomposition (BEMD) for keypoint detection, where a given image is decomposed into Intrinsic Mode Functions (IMFs). Our method also employs Affine Moment Invariants (AMIs) instead of SIFT’s feature values. As a result, the proposed method detects more matching points than SIFT in a steep affine
Keywords: Empirical Mode Decomposition, Affine Moment Invariants.
Edge Reconstruction of LED Probes Using Various Segmentation and the Averaging of Sub-pixelsOpen Access
Abstract: LED probes are essential for testing the quality of LEDs, gaining its attention among industrial applications. Disturbance factors such as dust or noise affections may occur during the manufacturing process of the LED probes, which leads angle error to increase. With the increasing demand for LED probes, higher precision and efficiency are expected by users. Efficient method for edge detection and the preciseness of angle is crucial in our study. The previous study presented a method using Scharr edge detection and adaptive reconstruction. In this paper, we add a new method based on various segmentation and the averaging of sub-pixels (VSAS). Experimental results indicate that this method provides higher precision, with and an average error less than 1% compared to the other previous methods.
Keywords: Angle accuracy, edge detection, led, probe, sub-pixels, various segmentation
Multiscale Feature Representation for ECG-based Human IdentificationOpen Access
Abstract: ECG-based based human recognition is increasingly becoming a popular modality for
biometric authentication. Two important features of ECG signals are liveliness and the robustness
against falsification. However, ECG features vary due to muscle flexure, baseline wander, and other sources of noise. This paper presents a new method which extracts multiscale geometric features from ECG signals and apply them for human identification. A non-linear filter is applied for preprocessing the ECG signal. The refined ECG signal is then divided into multiple segments and feature matrix is computed by multiscale pattern extraction technique. Feature matrix is finally applied to a simple minimum distance to mean classifier adopting leave-one-out procedure. An experiment with 60 ECG signals from 60 subjects shows promising performance of the proposed method compared to the conventional ECG features.
Keywords: Binary patterns, multiscale representation, supervised classification, and human