• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.63-72
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• 2012

In livestock industry, damage caused by the epidemic diseases such as Foot-and-Mouth Disease (FMD), Highly-Pathogenic-Avian-Influenza (HPAI) and Porcine-Reproductive-and-Respiratory-Syndrome (PRRS) was very serious. The financial loss incurred from FMD alone which occurred on Nov. 2011 in Korea was estimated at 3 billion won, 23 % of annual livestock industry production. The livestock industry in Korea has greater risk of disease infection because of high density production, etc. Investigating the spread of livestock diseases should consider both direct and indirect contact as well as other various factors including airborne. Airborne infection of livestock disease was first hypothesised in the early 1900s, however, field experimental studies are still limited. Furthermore, no protocol is available in detecting airborne viruses in the field. In this study, effective virus samplers were investigated by comparative analysis of the type of samplers used detect to airborne virus. Laboratory experiments were conducted to compare virus samplers such as Bio-sampler, Dust-sampler, Compact-Cascade-Impactor (CCI) and Microflow in detecting PRRSV. Samples were analyzed by Reverse-Transcription PCR to assess the efficiency of the instrument in detecting the airborne virus. First, samples were classified into five levels according to light intensity of gel images and then the classified results were normalized. In every case, Bio-sampler and Dust-sampler were comparable with each other and have shown to be more effective than CCI and Microflow samplers.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.87-94
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• 2004

The software reliability growth model(SRGM) has been developed in order to estimate such reliability measures as remaining fault number, failure rate and reliability for the developing stage software. Almost of them assumed that the faults detected during testing were evetually removed. Namely, they have studied SRGM based on the assumption that the faults detected during testing were perfectly removed. The fault removing efficiency. however. IS imperfect and it is widely known as so in general. It is very difficult to remove detected fault perfectly because the fault detecting is not easy and new error may be introduced during debugging and correcting. Therefore, the fault detecting efficiency may influence the SRGM or cost of developing software. It is a very useful measure for the developing software. much helpful for the developer to evaluate the debugging efficiency, and, moreover, help to additional workloads necessary. Therefore. it is very important to evaluate the effect of imperfect dubugging in point of SRGM and cost. and may influence the optimal release time and operational budget. I extent and study the generally used reliability and cost models to the imperfect debugging range in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.703-710
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• 2010

In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue loaded on an excavator in advance. Generally, the larger data, the longer processing time, and the amount of the data used in this paper are also large, especially every sampling period, 1600 data are gathered and calculated. So this paper focuses on minimizing the number of required sensors by using the correlation function. From the cross correlation function, similar pattern sensors are eliminated and dissimilar pattern sensors are considered, and from the auto correlation function, the overload can be detected. To prove the efficiency of the proposed overload detecting algorithm, this paper shows the computer simulation results.

• Genomics & Informatics
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• v.21 no.4
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• pp.52.1-52.10
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• 2023

Accurate and efficient microbial diagnosis is crucial for effective molecular diagnostics, especially in the field of human healthcare. The gold standard equipment widely employed for detecting specific microorganisms in molecular diagnosis is quantitative real-time polymerase chain reaction (qRT-PCR). However, its limitations in low metagenomic DNA yield samples necessitate exploring alternative approaches. Digital PCR, by quantifying the number of copies of the target sequence, provides absolute quantification results for the bacterial strain. In this study, we compared the diagnostic efficiency of qRT-PCR and digital PCR in detecting a particular bacterial strain (Staphylococcus aureus), focusing on skin-derived DNA samples. Experimentally, specific primer for S. aureus were designed at transcription elongation factor (greA) gene and the target amplicon were cloned and sequenced to validate efficiency of specificity to the greA gene of S. aureus. To quantify the absolute amount of microorganisms present on the skin, the variable region 5 (V5) of the 16S rRNA gene was used, and primers for S. aureus identification were used to relative their amount in the subject's skin. The findings demonstrate the absolute convenience and efficiency of digital PCR in microbial diagnostics. We suggest that the high sensitivity and precise quantification provided by digital PCR could be a promising tool for detecting specific microorganisms, especially in skin-derived DNA samples with low metagenomic DNA yields, and that further research and implementation is needed to improve medical practice and diagnosis.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.147-150
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• 2000

Manual and predictive defrosting method is used in current refrigerators, which have several problems in terms of energy consumption and efficiency. fuming the defrosting system on by the amount of frost remains to be an important problem which has to be improved by refrigerator manufacturers. The sensing of the amount of frost by FDS(Frost Detecting Sensor) and its proper mounting point are investigated in the paper. Also the realization of actual defrosting system through experiments of operation, energy consumption and sensing mechanism is presented.

• Advances in nano research
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• v.12 no.1
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• pp.1-23
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• 2022

To date, nondestructive tests (NDT) applications and advances in detecting the dispersion and defections of the nano concrete (NC) materials fields are very limited. The current paper provides a review of the dispersion efficiency of nanomaterials in cement-based materials and how NDT can be efficiently used in detecting and visualizing the defections and dispersions of NC. The review identifies the characteristics of different types of nanoparticles used in NC. Nanomaterials influences on concrete characteristics and their dispersion degree are presented and discussed. The main aim of this article is to present and compare the common NDT that can be used for detecting and visualizing the defections and dispersions of different kinds of nanomaterials utilized in NC. The different microscopy and X-ray methods are explicitly reviewed and compared. Based on the collected data, it can be concluded that the fully detecting and visualizing of NC defections and dispersions have not been fully discovered and that needs further investigations. So, the distinction of this paper lies in defining NDT that can be employed for detecting and/or visualizing NC defections and dispersions.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.1-7
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• 2017

In this paper, we introduce three monitoring filtering techniques which reduce the overheads of dynamic data race detection. It is well known that detecting data races dynamically in multi-threaded programs is quite hard and troublesome task, because the dynamic detection techniques need to monitor all execution of a multi-threaded program and to analyse every conflicting memory and thread operations in the program. Thus, the main drawback of the dynamic analysis for detecting data races is the heavy additional time and space overheads for running the program. For the practicality, we also empirically compare the efficiency of three monitoring filtering techniques. The results using OpenMP benchmarks show that the filtering techniques are practical for dynamic data race detection, since they reduce the average runtime overhead to under 10% of that of the pure detection.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.93-103
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• 2020

The purpose of this study is to suggest a supervisory way to improve the efficiency of Building Supervision using Deep Learning, especially object detecting technology. Since the establishment of the Building Supervision system in Korea, it has been changed and improved many times systematically, but it is hard to find any improvement in terms of implementing methods. Therefore, the Supervision is until now the area where a lot of money, time and manpower are needed. This might give a room for superficial, formal and documentary supervision that could lead to faulty construction. This study suggests a way of Building Supervision which is more automatic and effective so that it can lead to save the time, effort and money. And the way is to detect the hoop-bars of a column and count the number of it automatically. For this study, we made a hoop-bar detecting network by transfor learnning of YOLOv2 network through MATLAB. Among many training experiments, relatively most accurate network was selected, and this network was able to detect rebar placement in building site pictures with the accuracy of 92.85% for similar images to those used in trainings, and 90% or more for new images at specific distance. It was also able to count the number of hoop-bars. The result showed the possibility of automatic Building Supervision and its efficiency improvement.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.396-402
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• 2005

The software reliability growth model(SRGM) has been developed in order to evaluate such measures as remaining fault number, fault rate, and reliability for the developing stage software. Most of the study literatures assumed that this detecting efficiency was perfect. However the actual fault detecting is generally imperfect, and widely known to many persons. It is not easy to develop and remove the fault existing in the software because the fault finding is difficult, and the exact solving method also not easy, and new fault may be introduced depending on the tester's capability. There, the fault removing efficiency influences the software reliability growth or developing cost of software. It is a very useful measure throughout the developing stage, much helpful for the developer to evaluate the debugging efficiency, and evaluate additional workload. Hence, the study for the imperfect debugging is important in point of software reliability and cost. This paper proposes that the fault debugging is imperfect and new fault may be introduced for the developing software during the developing stage.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.121-126
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• 2017

EES System support to maximize equipment efficiency by providing real-time information of main equipment which has a significant effect on product quality and productivity, and to prevent equipment failure by detecting equipment abnormality in advance. Smart Equipment Engineering System(S-EES) integrates the activities performed at equipment that are the core of production activities and manages them by system so as to maximize the efficiency of equipment and raise the quality level of products to one level. In other words, when the product is put into the equipment, the recipe is downloaded through the RMS, the recipe is set to the optimal condition through R2R(process control), and the system detects and controls the abnormality of the equipment during operation through the FDC function in real time it means. In this way, we are working with the suitable recipe that matches the lot of product, detecting the abnormality of the equipment during operation, preventing the product from being defective, and establishing a system to maximize the efficiency through real-time equipment management. In this study, we review the present status and problems of equipment management in actual production lines, collect the requirements of the manufacturing line for the PCB line, design and develop the system, The measurement model was studied.