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Showing 121–132 of 180 results
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TDOA based Geolocation using IRLS Algorithm
Open AccessAbstract: The geolocation method using the wireless signal processing system is widely used in many industrial areas. The time difference of arrival (TDOA) method is one of the most commonly used geolocation methods. The TDOA signal based geolocation system can estimate the position of a mobile object by using at least three base stations in two dimensional spaces. In geolocation problem, the precise estimation of mobile’s position is the most significant issue.The measurement noise that is contained in measured TDOA data causes the estimation inaccuracy in a mobile geolocation. In this paper, the objective function that represents the scalar error of position estimation is formulated using the concept of p Lp -norm approximation. Also, we suggest the iterative reweighted least square (IRLS) scheme for minimizing of the objective function. The optimal solution can be obtained using the limited measurement data through the reweighted iteration process of the IRLS scheme.
Keywords: Geolocation; Time difference of arrival; Iterated reweighted least square; Obtimization
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Analyzing the Advantages of Utilizing State Representations in a Probabilistic Reversal Learning Task
Open AccessAbstract: Cognitive flexibility is the ability to adaptively change behaviors in the face of dynamically changing circumstances. To explore the neural basis and computational account of this ability, a probabilistic reversal learning task was employed as the experimental paradigm. Recent studies suggest that a subject may utilize not only a reward history but also a “state representation” of a task to successfully solve one. However, the specific advantages or impact of state representations in task solving are still not fully understood. In this study, we investigated this matter by computer simulations, in which we used two types of reinforcement learning models, a model with state representations and one without. As a result of the simulations, we found that state representations make a learning agent robust against an increasingly difficult task, especially when the number of sampling time in each state is reduced. Based on the results, we propose a hypothesis for the acquisition process of state representations and discuss the experimental design to test it.
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Developing A Simplified Maintenance & Rehabilitation Activity Prioritization Tool for Afghanistan Roads
Open AccessAbstract: Roads are one of the most important factor of life, and maintenance & rehabilitation of them are very vital and challenging for a country. Afghanistan is one of those countries which face the challenges of low-budget, computerized office works and skilled personnel. Regarding to budget limitation pavement maintenance and rehabilitation activity prioritization is obligatory. Currently, a technology based, and simplified maintenance activity prioritization tool are an essential need of the country. The aim of this research is to develop a tool which prioritize the maintenance and rehabilitation activities by considering some factors such as pavement condition index, road width, traffic volume, residential importance as well as maintenance and rehabilitation cost. Since characterizing a model that presents each one of those variables was difficult, a simplified model named TOPSIS was denoted for the issue of prioritization. TOPSIS model lets you have a more precise ranking for the outcome. Considering the problem, Visual Basic have the ability to easily code any type of model and present a graphical display of the model. A source code was developed and Visual Basic was used for computations coding, graphical display of results and generating reports. The developed model indicates that more than two criteria/weighs are very important for prioritizing the alternatives/activities. The developed tool can prioritize the maintenance and rehabilitation activities and generate different database for further use in ArcGIS.
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A Comparative Study on the Performances of Q-Learning and Neural Q-Learning Agents toward Analysis of Emergency of Communication
Open AccessAbstract: In this paper, we suppose the gesture theory that is one theory on the origin of language, which tries to establish that 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 and what conditions are necessary to acquire usages of the actions as the symbols. To investigate them, we adopt a collision avoidance game and compare the performances of Q-learning agents with that of Neural Q-learning agents. In our simulation, we found that the Neural Q-learning agent’s ability to reach the goal place is higher than the Q-learning agent’s one. In contrast, the Neural Q-learning agent’s ability to avoid collisions is lower than the Q-learning agent’s one. If the inconsistencies in the learning data sets of the Neural Q-learning agent, however, can be resolved, the agent has enough potential to improve its ability for collision avoidance. Therefore, we conclude that the most suitable agent to analyze the emergence of communication is the Neural Q-learning agent who changed a feed forward type neural network into a recurrent type neural network that can resolve the inconsistencies in the learning data sets.
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JICE Vol 2 Issue 4
Open AccessPublished 10th December 2016, ISSN 2432-5465 , Total Pages 8
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A Comparative Study on the Performances of Q-Learning and Neural Q-Learning Agents toward Analysis of Emergence of Communication
Open AccessAbstract: In this paper, we suppose the gesture theory that is one theory on the origin of language, which tries to establish that 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 and what conditions are necessary to acquire usages of the actions as the symbols. To investigate them, we adopt a collision avoidance game and compare the performances of Q-learning agents with that of Neural Q-learning agents. In our simulation, we found that the Neural Q-learning agent’s ability to reach the goal place is higher than the Q-learning agent’s one. In contrast, the Neural Q-learning agent’s ability to avoid collisions is lower than the Q-learning agent’s one. If the inconsistencies in the learning data sets of the Neural Q-learning agent, however, can be resolved, the agent has enough potential to improve its ability for collision avoidance. Therefore, we conclude that the most suitable agent to analyze the emergence of communication is the Neural Q-learning agent who changed a feed forward type neural network into a recurrent type neural network that can resolve the inconsistencies in the learning data sets.
Keywords: Q-learning, Neural Q-learning, Collision Avoidance Game, Reinforcement Learning Agents, Multi-Agent System.
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JICE Vol 2 Issue 3
Open AccessPublished 22nd April 2016, ISSN 2186-9162, Total Pages 4
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Compensation of Image Distortion on an Arbitrary Surface
Open AccessAbstract: When images are projected on an arbitrary surface, people expect to see distortion-free images. Therefore, we need to compensate for the geometric distortion on the camera image plane. To generate a geometric compensated image, we employ feature matching between a projector image and a camera image for comparing the position. In this paper, we propose a feature matching method using sequential binary point patterns without the projector and synchronized camera. We verify the proposed compensation method by experiments on the arbitrary surface.
Keywords: Image distortion compensation, binary pattern, arbitrary surface
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JICE Vol 2 Issue 2
Open AccessPublished 25th February 2016, ISSN 2186-9154, Total Pages 59
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Design and Implementation of a Life Test System for the Train Driver Controller
Open AccessAbstract: The train driver controller is a main electric appliance for the train speed controlling and
braking. Its reliability relates directly with the driving safety. The existing life-span test system of the
train driver controller can only detect the mechanical life-span. A new life-span test system is
developed which can detect not only the mechanical life-span, but also the life-span of the electrical components such as the internal cam contacts, potentiometers and so on. The new system is based on Labview. The modular design is applied and the system reliability is improved. Taking advantage ofLabview, it realizes more precious timing. The master-slave mode is applied to the network architecture of the system so as to test on multiple train driver controllers at the same time. Therefore the testing cost is reduced. The experiments show that the new life-span test system is an efficient workable platform which improves the productivity, reliability and maintainability of the train driver controller.
Keywords: Train driver controller; Life-span test system; Modular design; Time division multipiexing -
Design of an Intelligent Housekeeping Robot Based on IOT
Open AccessAbstract: This project has developed an IOT based indoor mobile robot, which is used for the
housekeeping service and called as “smart housekeeper”. The robot is equipped with the crawler
chassis structure and the head lifting machinery. It applies Cortex-M4 as the main controller, and
communicates with the outer by WiFi. A smart mobile phone is used as its head. People can operate the robot remotely by another smart mobile phone at any time. It can realize remote video searching, home appliance control, and indoor security. The experiment shows that it works well with all the functions.
Keywords: Housekeeping Robot; WiFi; Home Appliances Control; Video Transmission; Gas
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The Application of a Driving Circuit Based on 1ED020I12-FTA in PMSM
Open AccessAbstract: A new driving circuit based on the IGBT driving chip 1ED020I12-FTA is designed to drive the controller of the high power brushless DC motor in this article. The article has introduced overall design, the driving circuit and the experiments. The experiment results show that the driving circuit is able to drive PMSM motor very well, and it works well with good anti-disturbance, desaturation, electromagnetic isolation, overcurrent and overvoltage protection, Miller active clamp, and so on.
Keywords: high power driving; H bridge circuit; DC motor; pulse width modulation