• Journal of the Korean Society of Safety
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• v.12 no.2
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• pp.80-86
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• 1997

In this paper, a temperature controller with monitor function is proposed for the electric furnace system. This controller includes holding and ramp control function, and the control program for the temperature process monitor of the electric furnace. For this purpose, the implementation and performance of auto tuning algorithms in a computer-based controller was studied in relation to the control of nonlinear electric furnace system which is characterized with large delay time. The control program for this controller programmed by c-language. To communicate a control and detection signals, between the controller and the electric furnace is implemented by the I/O data card. We apply the temperature controller to the practical electric furnace. As a result, the proposed controller shows the better status characteristic.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.48-50
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• 1994

In this paper, the optimal fuzzy controller of exciter and governor in synchronous generator improve the stability of power system with varying loads and disturbances in power system. Parameters of the proposed fuzzy controller were optimally self-tuned by the steepest descent method and were applied to power system stabilization. The related simulation results show that the proposed control technique are more powerful than the conventional ones for reductions of undershoot and for minimization of settling time.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2573-2575
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• 2001

아날로그 필터는 각종 시스템의 특히 입출력단에서 신호의 선택적 분리 및 잡음 특성을 개선하는 것으로 필수적인 구성체 이다. 아날로그 필터에는 여러 가지의 형태가 있으나 집적화가 가능하고 높은 주파수 영역에서도 사용이 가능한 Gm-C필터가 많이 연구되고 시스템에서 구현되어 지고 있다. 본 논문에서는 저주파에서 수백 MHz의 주파수 영역에서 동작이 가능한 아날로그 IC 필터인 Gm-C 필터의 새로운 튜닝구조를 제한 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5252-5268
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• 2018

To support a large-scale Hadoop cluster, Hadoop heartbeat messages are designed to deliver the significant messages, including task scheduling and completion messages, via piggybacking to reduce the number of messages received by the NameNode. Although Hadoop is designed and optimized for high-throughput computing via batch processing, the real-time processing of large amounts of data in Hadoop is increasingly important. This paper evaluates Hadoop's performance and costs when the heartbeat period is controlled to support latency sensitive applications. Through an empirical study based on Hadoop 2.0 (YARN) architecture, we improve Hadoop's I/O performance as well as application performance by up to 13 percent compared to the default configuration. We offer a guideline that predicts the performance, costs and limitations of the total system by controlling the heartbeat period using simple equations. We show that Hive performance can be improved by tuning Hadoop's heartbeat periods through extensive experiments.

• International Journal of High-Rise Buildings
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• v.9 no.4
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• pp.335-342
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• 2020

This article comes up with a new method which is based on the visual characteristic of the objects and machine learning technology to achieve semi-automated recognition of the personnel, machine & materials of the construction sites. Balancing the real-time performance and accuracy, using Faster RCNN (Faster Region-based Convolutional Neural Networks) with transfer learning method appears to be a rational choice. After fine-tuning an ImageNet pre-trained Faster RCNN and testing with it, the result shows that the precision ratio (mAP) has so far reached 67.62%, while the recall ratio (AR) has reached 56.23%. In other word, this recognizing method has achieved rational performance. Further inference with the video of the construction of Huoshenshan Hospital also indicates preliminary success.

• ETRI Journal
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• v.44 no.4
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• pp.560-572
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• 2022

H²RDC (heuristic handover based on RCC-DTSK-C), a heuristic algorithm based on a highly interpretable deep Takagi-Sugeno-Kang fuzzy classifier, is proposed for suppressing the mobile heterogeneous networks problem of frequent handover and handover ping-pong in the multibase-station scenario. This classifier uses a stack structure between subsystems to form a deep classifier before generating a base station (BS) priority sequence during the handover process, and adaptive handover hysteresis is calculated. Simulation results show that H²RDC allows user equipment to switch to the best antenna at the optimal time. In high-BS density load and mobility scenarios, the proposed algorithm's handover success rate is similar to those of classic algorithms such as best connection (BC), self tuning handover algorithm (STHA), and heuristic for handover based on AHP-TOPSIS-FUZZY (H²ATF). Moreover, the handover rate is 83% lower under H²RDC than under BC, whereas the handover ping-pong rate is 76% lower.

• Smart Media Journal
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• v.12 no.3
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• pp.112-119
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• 2023

Shrimp farming has been becoming a new source of income for fishermen in South Korea. It is often necessary for fishers to measure the size of the shrimp for the purpose to understand the growth rate of the shrimp and to determine the amount of food put into the breeding pond. Traditional methods rely on humans, which has huge time and labor costs. This paper proposes a deep learning-based method for calculating the size of shrimps automatically. Firstly, we use fine-tuning techniques to update the Mask RCNN model with our farm data, enabling it to segment shrimps and generate shrimp masks. We then use skeletonizing method and maximum inscribed circle to calculate the length and width of shrimp, respectively. Our method is simple yet effective, and most importantly, it requires a small hardware resource and is easy to deploy to shrimp farms.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.446-448
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• 2021

In training a deep learning model, it is crucial to tune various hyperparameters and gain speed and accuracy. While hyperparameters that mathematically induce convergence impact training speed, system parameters that affect host-to-device transfer are also crucial. Therefore, it is important to properly tune and select parameters that influence the data loader as a system parameter in overall time acceleration. We propose an automated framework called Num Worker Tuner (NWT) to address this problem. This method finds the appropriate number of multi-processing subprocesses through the search space and accelerates the learning through the number of subprocesses. Furthermore, this method allows memory efficiency and speed-up by tuning the system-dependent parameter, the number of multi-process spawns.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.4-5
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• 2015

Owning to rapid infrastructure development, Asia is experiencing dramatic economic growth. There are not a few cases in which, however, economic growth is achieved by increasing the external diseconomy. Pursuit of sustainable development is one of the most important issues for mankind. Under the post-industrial capitalism society, however, there seems a big risk of increase in the external diseconomy worldwide. The objectives of this manuscript are to discuss importance of risk management of construction practice in present and future. Regarding the latter, a particular attempt is made to discuss how project risk communication should be done to reduce the external diseconomy. Presently, one of the important issues in implementation of infrastructure projects is practice of risk management to properly manage time, cost, quality, and safety: mainly maximization of internal economy. Multi-party risk and uncertainty management process (MRUMP) is one of tolls to assist it. The idea on MRUMP can be used to reduce the external diseconomy through identifying, sharing, and tuning people's rhythms.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.459-466
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• 2017

Objective: This study examined two traffic signals with a countdown indicator in terms of driver's reaction time and subjective satisfaction score and their performance was compared with a standard traffic signal in driving simulation. Background: Dilemma zone is created when a traffic light changes at intersections. It often pushes drivers to rush in urgent and premature decision making whether to go or stop and thus induces unnecessary mental load among drivers, which may lead to sudden conflicts with following vehicles at intersections. Method: Forty college students (male: 20, female: 20) participated in this driving simulation study. Three traffic signals were employed: (1) standard traffic signal; (2) countdown-separated signal; and (3) countdown-overlaid signal. The countdown-separated and countdown-overlaid signals were designed to inform drivers of the remaining time of a green light before tuning to an amber light. Reaction times (sec) and satisfaction scores (7-point scale) for the two signals with a countdown indicator were compared with those for the standard traffic signal. Results: Reaction times of the countdown-separated (0.49 sec) and countdown-overlaid (0.43 sec) signals were significantly shorter than that of the standard signal (0.67 sec). Satisfaction scores of the countdown-separated (5.3 point) and countdown-overlaid (5.6 point) signals were greater than that of the standard signal (3.8 point). Lastly, the countdown-overlaid signal showed better performance than the countdown-separated signal, but their differences in reaction time (0.06 sec) and satisfaction score (0.3 point) were small. Conclusion: Traffic signals with a countdown indicator can improve drivers' reaction time and satisfaction score than the standard traffic signal. Application: Traffic signals with a countdown indicator will be useful for reducing the length of dilemma zone at intersections, by allowing drivers to predict the remaining time of a green light.