• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.25-31
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• 2014

In this paper, a modified Alford loop antenna for on-body communication system is proposed. The proposed antenna operating in the ISM band is designed with consideration of human body effect. One of advantages of the Alford loop antenna structure is low-profile, however the Alford loop antenna is not suitable for on-body devices since it does not have a ground plane for other electronic part of on-body system and requires balanced feeding structure. To be embedded on on-body devices, the proposed antenna is design with the unbalanced feed structure and ground. The performance of the proposed antenna is simulated and measured when it is placed on the human body phantom to consider the effect of the human body. The proposed antenna a 10 dB return loss bandwidth over the ISM band and monopole-like radiation pattern with low-profile. The antenna has the surface of appropriate for on-body communication environment.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.157-166
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• 2013

This paper proposes a non-intrusive speech quality estimation method considering the effects of packet loss to perceptual quality. Packet loss is a major reason of quality degradation in a packet based speech communications network, whose effects are different according to the input speech characteristics or the performance of the embedded packet loss concealment (PLC) algorithm. For the quality estimation system that involves packet loss effects, we first observe the packet loss of G.729 codec which is one of narrowband codec in VoIP system. In order to quantify the lost packet affects, we design a classification algorithm only using speech parameters of G.729 decoder. Then, the degradation values of each class are iteratively selected that maximizes the correlation with the degradation PESQ-LQ scores, and total quality degradation is modeled by the weighted sum. From analyzing the correlation measures, we obtained correlation values of 0.8950 for the intrusive model and 0.8911 for the non-intrusive method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.725-734
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• 2016

SCADA(Supervisory Control and Data Acquisition) system is widely used for remote monitoring and control throughout the domestic industry. Due to a recent breach of security on SCADA systems, such as Stuxnet, the need of correctly established secure certification of a control system is growing. Currently, EDSA-CRT (Embedded Device Security Assurance-Communication Robustness Test), which tests the ability to provide core services properly in a normal/abnormal network protocol, is only focused on the testing of IP-based protocols such as IP, ARP, TCP, etc. Thus, in this paper, we propose test requirements for DNP3 protocol based on EDSA-CRT. Our analysis show that the specific test cases provide plentiful evidences that DNP3 should follow based on its functional requirements. As a result, we propose 33 specific test case for DNP3 protocol.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.384-389
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• 2005

The objective on this project is to develop a cooperative Field Robot (FR), by using a customize Open Control Platform (OCP) as design and development process. An OCP is a CORBA-based solution for networked control system, which facilitates the transitioning of control designs to embedded targets. In order to achieve the cooperation surveillance system, two FRs are distributed by navigation messages (GPS and sensor data) using CORBA event-channel communication, while graphical information from IR night vision camera is distributed using CORBA Asynchronous Method Invocation (AMI). The QoS features of AMI in the network are to provide the additional delivery method for distributing an IR camera Images will be evaluate in this experiment. In this paper also presents an empirical performance evaluation from the variable chunk sizes were compared with the number of clients and message latency, some of the measurement data's are summarized in the following paragraph. In the AMI buffers size measurement, when the chuck sizes were change, the message latency is significantly change according to it frame size. The smaller frame size between 256 bytes to 512 bytes is more efficient fur the message size below 2Mbytes, but it average performance in the large of message size a bigger frame size is more efficient. For the several destination, the same experiment using 512 bytes to 2 Mbytes frame with 2 to 5 destinations are presented. For the message size bigger than 2Mbytes, the AMI are still able to meet requirement far more than 5 clients simultaneously.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.57-62
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• 2014

Recently, research activities to develop services for providing safety information to the drivers in fast moving vehicles based on various wireless network technologies such as DSRC (Dedicated Short Range Communication), IEEE 802.11p WAVE (Wireless Access for Vehicular Environment) are widely being carried out. This paper presents a proof-of-concept model based on a robot-car for Dilemma Zone Decision Assistant Service using the wireless LAN technology. The proposed model system consists of a robot-car based on an embedded Linux OS equipped with a WiFi interface and an on-board unit emulator, an Android-based remote controller to model a human driver interface, a laptop computer to run a model traffic signal controller and signal lights, and a WiFi access point to model a road-side unit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1859-1867
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• 2021

Multi LiDAR sensors are being mounted on autonomous vehicles, and a system to multi LiDAR sensors data is required. When sensors data is transmitted or processed to the main processor, a huge amount of data causes a load on the transport network or data processing. In order to minimize the number of load overhead into LiDAR sensor processors, only semantic data is transmitted through data comparison between frames in LiDAR data. When data from 4 LiDAR sensors are processed in a static environment without moving objects and a dynamic environment in which a person moves within sensor's field of view, in a static experiment environment, the transmitted data reduced by 89.5% from 232,104 to 26,110 bytes. In dynamic environment, it was possible to reduce the transmitted data by 88.1% to 29,179 bytes.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.141-148
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• 2021

This paper presents a method to detect zebra-crossing using deep learning which combines SegNet and ResNet. For the blind, a safe crossing system is important to know exactly where the zebra-crossings are. Zebra-crossing detection by deep learning can be a good solution to this problem and robotic vision-based assistive technologies sprung up over the past few years, which focused on specific scene objects using monocular detectors. These traditional methods have achieved significant results with relatively long processing times, and enhanced the zebra-crossing perception to a large extent. However, running all detectors jointly incurs a long latency and becomes computationally prohibitive on wearable embedded systems. In this paper, we propose a model for fast and stable segmentation of zebra-crossing from captured images. The model is improved based on a combination of SegNet and ResNet and consists of three steps. First, the input image is subsampled to extract image features and the convolutional neural network of ResNet is modified to make it the new encoder. Second, through the SegNet original up-sampling network, the abstract features are restored to the original image size. Finally, the method classifies all pixels and calculates the accuracy of each pixel. The experimental results prove the efficiency of the modified semantic segmentation algorithm with a relatively high computing speed.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.283-291
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• 2011

As the construction industry has recently been transformed by the emergence of ubiquitous and intelligent technology, there have been major changes in the management methods employed. Specifically, next-generation construction management systems have been developed that collect and analyze many pieces of information in real time by using various wireless sensors and networks. The purpose of this study is to understand the current status of Ubiquitous Sensor Networks (USN) in the construction sector, and to gain fundamental data for a system of measuring concrete curing temperature in a construction site that employs a USN. By investigating the application status of USN, it was confirmed that USN has mainly been applied to the maintenance of facilities, safety management, and quality control. In addition, a field experiment in which the curing temperature of concrete was measured using a USN was carried out to evaluate two systems with wireless sensor networks, and the applicability of these systems on site was confirmed. However, it is estimated that the embedded wireless sensor type is affected by metal equipment on site, internal battery of sensor and concrete depth, and studies to provide more stable system by USN are thus required.