• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1555-1570
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• 2016

For monitoring forest fires, a real-time system to prevent fires in wider areas should be supported consistently. However, there has still been a lack of the support for real-time system related to forest fire monitoring. In addition, the 'real-time' processing in a forest fire detection system can lead to excessive consumption of energy. To solve these problems, the intelligent data acquisition of sensing nodes is required, and the maximum energy savings as well as rapid and accurate detection by flame sensors need to be done. In this regard, this paper proposes a node built-in filter algorithm for intelligent data collection of sensing nodes for the rapid detection of forest fires with focus on reducing the power consumption of the remote sensing nodes and providing efficient wireless sensor network-based forest environment monitoring in terms of data transmission, network stability and data acquisition. The experimental result showed that battery life can be extended through the intelligent sampling of remote sensing nodes, and the average accuracy of the measurement of flame detection based on the distance is 44%.

• Publications of The Korean Astronomical Society
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• v.28 no.1
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• pp.1-6
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• 2013

Real-time data reduction pipeline for the Korea Microlensing Telescope Network (KMTNet) was developed by Korea Astronomy and Space Science Institute (KASI). The main goal of the data reduction pipeline is to find variable objects and to record their light variation from the large amount of observation data of about 200 GB per night per site. To achieve the goal we adopt three strategic implementations: precision pointing of telescope using the cross correlation correction for target fields, realtime data transferring using kernel-level file handling and high speed network, and segment data processing architecture using the Sun-Grid engine. We tested performance of the pipeline using simulated data which represent the similar circumstance to CTIO (Cerro Tololo Inter-American Observatory), and we have found that it takes about eight hours for whole processing of one-night data. Therefore we conclude that the pipeline works without problem in real-time if the network speed is high enough, e.g., as high as in CTIO.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2325-2327
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• 2003

This thesis is concerned with the control of Arago's disk system using CAN(Controller Area Network). CAN protocol is used widely for the real time control in networked control systems(NCS). A networked control system using CAN is constructed to perform position control of Arago's disk. The mathematical model, of overall system is derived to design an appropriate controller analytical1y. Various operating points of the Arago's disk system in the real time control are chosen as stable region ($45^{\circ}$), marginal1y stable region($90^{\circ}$) and unstable region($120^{\circ}$), and the experiment for the position control of arago's disk system is done for each operating point. The performance of the suggested NCS is verified by experiments. It is shown that the NCS using CAN has stability and excel1ency in real time control.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.331-341
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• 2015

In this paper, real-time water quality monitoring system of small water supply facilities based on IEEE 802.15.4e-2012 DSME MAC and IEEE 802.15.4g-2012 PHY standard is presented, which is capable to acquire for highly reliable water quality information in the wide outdoor areas for effective water quality management of small water quality facilities is distributed in the long distance and remote areas. Previously, Long distance transmission is difficult in most water quality sensor module is using RS-485 protocol. But with this system, even in harsh outdoor environment, it is possible to establish a radio wave sensor in a wide area network, and not only water quality sensor shall be connected to the wireless system, but also wireless integrated management system shall provide more effective way of management of the numerous small water supply facilities spread throughout the community, so that the administrator can remotely monitor the data of water turbidity, pH, residual chlorine in the water-supply, water-level, and generate alarm to cope with risks. The management of small water facilities is done by residents will be very effective to notice water quality information of small water facilities to residents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.287-290
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• 2009

무선 통신 기술과 하드웨어의 발전으로 인해 무선 센서 네트워크를 위한 센서 노드들은 저전력화 및 소형화되었고, 사용 목적에 따라 많은 연구가 진행되고 있다. 최근 들어서는 온도나 가속도 등의 간단한 정보뿐만 아니라 이미지를 센싱할 수 있는 초소형 카메라 등을 이용한 멀티미디어 센서 네트워크에 대한 연구도 활발히 이루어지고 있다. 이미지 센싱에 있어서는 CCD Sensor에 비해 적은 전력을 소모하고 빠른 전송에 적합한 CMOS Sensor가 최근의 연구에 이용되고 있다. 이러한 추세에서 실시간의 데이터 검출을 위한 센서와 네트워크의 기능이 통합된 프로세서 구조의 기능이 요구되고 있다. 기존의 무선 이미지 전송 기술을 살펴보면 범용성 제어의 사용으로 데이터의 전송 처리를 위한 대역폭이 제한되고, 내부 메모리 또한 적은 용량으로 제한되어 있다. 한 예로 JPEG으로 압축된 이미지라도 데이터의 크기가 수 Kbytes에 이르기 때문에 전체 데이터를 한 번에 전송받지 못해 전송 속도나 패킷 정확도에 있어 효율이 떨어지게 된다. 따라서 실시간의 데이터의 전송에는 부족한 면이 있다. 본 논문에서는 CMOS Sensor Module을 이용하여 RT-WISN을 구성하였다. 구성된 센서 네트워크를 통하여 Peer to Peer에서 이미지의 데이터 크기에 따른 전송 시간을 측정하고 RT-WISN이 실시간 전송에 적합함을 보인다.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.695-705
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• 2019

The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.524-526
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• 2022

Considering QoS only considering real-time multimedia service, it is possible to adjust the number of terminals and ensure them appropriately, but this study considers complex services considering real-time multimedia service and general data service. Since the amount of physical network resources is limited, the guarantee of the desired QoS can not be achieved unless the appropriate CAC is done. However, given the traffic profile and QoS spec of the entire network resource and the current service being provided, and the traffic profile and QoS spec of the newly requested service, it is quite difficult to determine exactly whether the new service request is acceptable from this. To do this, it is necessary to study in various directions from mathematical analysis to various simulations and statistical research based on data obtained from actual network operation.

• Smart Structures and Systems
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• v.31 no.5
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.329-339
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• 2023

The objective of this study is to develop a Stability Evaluation System for retaining walls to assess their safety in real-time during excavation. A ground investigation is typically conducted before construction to gather information about the soil properties and predict wall stability. However, these properties may not accurately reflect the actual ground being excavated. To address this issue, the study employed a differential evolution algorithm to estimate the soil parameters of the actual ground. The estimated results were then used as input for an artificial neural network to evaluate the stability of the retaining walls. The study achieved an average accuracy of over 90% in predicting differential settlement, wall displacement, anchor force, and structural stability of the retaining walls. If implemented at actual excavation sites, this approach would enable real-time prediction of wall stability and facilitate effective safety management. Overall, the developed Stability Evaluation System offers a promising solution for ensuring the stability of retaining walls during construction. By incorporating real-time soil parameter analysis, it enhances the accuracy of stability predictions and contributes to proactive safety management in excavation projects.