• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.50-55
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• 2011

This research is to apply the adaptive control of neuron networks for the real-time attitude control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of attitude control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. In this research we used the response property curve of the robot instead of the activation function of neural network algorithms, so the adaptive control system of neural networks constructed without the information of modeling can perform a real-time control. The proposed adaptive control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.149-156
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• 2011

This paper reveals a distance estimation algorithm based on multi-code ultrasonic and wireless sensor network. For measuring the distances among the sensor nodes, each ultrasonic transmitter transmits multi-code ultrasonic signal simultaneously. Receivers use cross correlation method to separate the coded signals. The information of measured distances is broadcasted to each sensor node by wireless sensor network. The wireless sensor network measures the distance among the sensor nodes using the received signal strength of the broadcasting. The multi-code ultrasonic have a limitation of measurable distance. And the received signal strength is affected from an environment. This paper measures a distance using ultrasonic and a received signal strength in short range. These measured data are applied to the least square estimation algorithm. By the expansion of the fitting curve, a distance measurement in long range using the received signal strength is compensated. The coupled system reduce the error to an acceptable level.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.999-1007
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• 2012

Multi-precision multiplication over public key cryptography should be considered for performance enhancement due to its computational complexity. Particularly, embedded device is not suitable to execute high complex computation, public key cryptography, because of its limited computational power and capacity. To overcome this flaw, research on multi-precision multiplication with fast computation and small capacity is actively being conducted. In the paper, we explore the cutting-edge technology of multi-precision multiplication for efficient implementation of public key cryptography over sensor network. This survey report will be used for further research on implementation of public key cryptography over sensor network.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.101-110
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• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1526-1537
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• 2021

Due to the difference between the underwater communication environment and the terrestrial communication environment, the radio communication mainly used on the ground cannot be used in underwater. For this reason, in the underwater communication environment, various communication media such as acoustic waves, infrared rays, light and so on has been studied, but there exist several difficulties in operating them individually due to their physical limitations. The concept for overcoming these difficulties is the very underwater multi-media communication, a method to select a communication medium best suitable for the current underwater environment among underwater communication multimedia whenever there occurs underwater communication failure. In this paper, we present an underwater multi-media communication network based on star topology and a fragmentation and reassembly technique to solve the problems caused by the different MTU (Maximum Transmission Unit) sizes among different underwater communication media. We also present the estimations and analysis on processing times in each of fragmentation and reassembly and the total data amount for transmitting fragments in our proposed underwater multi-media communication network.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.491-497
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• 2012

Network coding is that the nodes can combine and mix the packets rather than merely forward them. Therefore, network coding is expected to improve throughput and channel efficiency in the wireless network. Relevant researches have been carried out to adapt network coding to wireless multi-hop network. In this paper, we designed the network coding for bidirectional traffic service in routing layer and IP layer of Ad-hoc network. From the simulation result, the traffic load and the end to end distance effect the performance of the network coding. As end to end distance and the traffic load become larger, the gain of network coding become more increased.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.6-11
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• 2013

Network Coding (NC) is a new paradigm for network communication. In network coding, intermediate nodes create new packets by algebraically combining ingress packets and send it to its neighbor node by broadcast manner. NC has rapidly emerged as a major research area in information theory due to its wide applicability to communication through real networks. Network coding is expected to improve throughput and channel efficiency in the wireless multi-hop network. Many researches have been carried out to employ network coding to wireless ad-hoc network. In this paper, we proposed a dynamic queue management to improve coding opportunistic to enhance efficiency of NC. In our design, intermediate nodes are buffering incoming packets to encode queue. We expect that the proposed algorithm shall improve encoding rate of network coded packet and also reduce end to end latency. From the simulation, the proposed algorithm achieved better performance in terms of coding gain and packet delivery rate than static queue management scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.179-189
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• 1994

A two-phase neural network finds exact feasible solutions for a constrained optimization programming problem. The time-varying programming neural network is a modified steepest-gradient algorithm which solves time-varying optimization problems. In this paper, we propose a time-varying two-phase optimization neural network which incorporates the merits of the two-phase neural network and the time-varying neural network. The proposed algorithm is applied to system identification and function approximation using a multi-layer perceptron. Particularly training of a multi-layer perceptrion is regarded as a time-varying optimization problem. Our algorithm can also be applied to the case where the weights are constrained. Simulation results prove the proposed algorithm is efficient for solving various optimization problems.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.523-529
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• 2011

In this paper an inter-layer protocol, referred to as a Multi-Network Selector (MNS) is proposed for multiband maritime networks. A MNS is located between the data-link layer and the network layer and performs vertical handover when a ship moves another radio network. In order to provide seamless data transfer to different radio networks, the MNS uses received signal strength (RSS) and ship's location information as decision parameters for vertical handover, which can avoid ping-pong effect and reduces handover latency. In addition, we present related issues in order to implement the MNS for a multiband maritime network.