• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.6
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• pp.197-205
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• 2018

Recently, remodeling is increasing due to aging of buildings. Therefore, the importance of quality control of structures has been raised, and interest in safety diagnosis and evaluation of structures has been increasing. In order to accurately diagnose old buildings, a diagnostic evaluation technique is needed to evaluate the defects of structures in advance. In addition, as the safety diagnostic criteria for reconstruction are improved and the weight of structural safety is increased, researches on safety diagnosis techniques of structures that are faster and more reliable are needed. In this study, we tried to estimate the compressive strength by examining the correlation between ultrasonic pulse velocity and compressive strength of a 1 story structure consisting of vertical and horizontal members of reinforced concrete using ultrasonic pulse velocity method, which is one of the nondestructive testing methods. The purpose of this study is to examine the applicability in the field. As a result, the estimated average error rate of the compressive strength of the structure using the ultrasonic pulse velocity method was 28.7%, which confirmed the applicability in the field. However, in order to increase the accuracy of the estimation, the necessity of the reliable diagnostic method using the composite nondestructive testing method was confirmed.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.1-21
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• 2023

This study specifically reviewed the performance of the ranking schemes as an efficient feature selection method for text classification. Until now, feature ranking schemes are mostly based on document frequency, and relatively few cases have used the term frequency. Therefore, the performance of single ranking metrics using term frequency and document frequency individually was examined as a feature selection method for text classification, and then the performance of combination ranking schemes using both was reviewed. Specifically, a classification experiment was conducted in an environment using two data sets (Reuters-21578, 20NG) and five classifiers (SVM, NB, ROC, TRA, RNN), and to secure the reliability of the results, 5-Fold cross-validation and t-test were applied. As a result, as a single ranking scheme, the document frequency-based single ranking metric (chi) showed good performance overall. In addition, it was found that there was no significant difference between the highest-performance single ranking and the combination ranking schemes. Therefore, in an environment where sufficient learning documents can be secured in text classification, it is more efficient to use a single ranking metric (chi) based on document frequency as a feature selection method.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.215-223
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• 2006

The Total Maximum Daily Load(TMDL) Act just implemented as a new tool of watershed based water quality management, in Korea. Thus, there are a number of pending questions to resolve for successful settlement of the TMDL. The allocation of pollution source is a exceedingly sensitive issue on local development planning. The simple area-based allocation (SAA) is conventional method to allocate the administrational pollution information to watershed based information. The SAA has a limitation that it can't consider the characteristics of spatial distribution of pollution source and it has caused more uncertainty of TMDL. This study was performed to reduce the uncertainty of watershed-based pollution information using the spatial distribution-based allocation(SDA). In the specific area where pollution source is concentrated such as urbanized region, it has been certified that SDA could reduce a tolerance of pollution information dramatically. As a result of study, SDA is expected a effective tool for TMDL and to solve the conflict between development and protection.

• Journal of Environmental Policy
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• v.9 no.1
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• pp.83-107
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• 2010

Urbanized environments are constructed to estimate peak flow and cost savings in response to possible BMP allocation at a watershed scale. The main goal is to explore the proper allocation of sub-watershed level BMPs for peak flow attenuation at a watershed scale. Since several individual site scale BMPs work as a form of aggregated BMPs at a sub-watershed scale, it is a question as to how to properly allocate the sub-watershed level BMPs at a watershed scale. The Hydrological Simulation Program-FORTRAN (HSPF) is set up for a hypothetically urbanized watershed. A peak flow is determined to be the primary variable of interest and targeted to characterize the spatial distribution of aggregated BMPs. Construction cost of a regional pond forms the basis of the economic valuation. The results indicate that when total size of BMPs is constant in the entire watershed, (1) it is most effective to have aggregated BMPs in some upper sub-watersheds while the BMPs in either the mainstem sub-watershed or a single sub-watershed are the least effective choices for peak flow attenuation at a watershed scale; (2) savings exist between allocation differences and reduced peak flow increases cost savings. The largest saving is found in the strategy of aggregated BMPs in some upper sub-watersheds. These findings, however, call for follow-up site specific case studies revisiting the watershed scale impacts of BMP allocation. Then, it will be argued that location and extent of decentralization are considerable policy variables for an alternative stormwater management policy at a watershed scale.

• Journal of Food Hygiene and Safety
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• v.37 no.1
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• pp.15-20
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• 2022

The purpose of this study was to compare the conventional culture method, enzyme immune method and the PCR method using species-specific primer in the analysis on the Salmonella spp. found in domestically distributed pet foods. For the study, Salmonella spp. were detected from 175 samples. From the conventional culture method and the PCR method, two samples (jerky and corn gluten) were determined as positive. Also, from the enzyme immune method, one sample (corn gluten) was test-positive. The study revealed that application of the PCR method with species-specific primer allows better distinguishment between the species of the strain collected from the samples than the conventional culture method and/or the enzyme immune method.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.2
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• pp.184-190
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• 2008

Various ECT techniques have been applied basically to assess the integrity of steam generator tithing in nuclear power plant. Among these techniques, the bobbin probe technique is applied generally to examine the volumetric flaws such as a crack-like defect and wear which is generally occurred on steam generator tubing, and additionally MRPC probe is used to examine closely tile top of tubesheet and bending regions due to the high possibility of cracking. Dent and bulge also may be formed on tube during installation process and operation of steam generator, but the dent and bulge indications greater than specific size criteria are recorded on examination report because these indications are not considered as flaw. These indications can be easily detected with bobbin probe and approximately sized with profile bobbin probe, but the size and shape can not be accurately verified. Accordingly, in this study, the $8{\times}1$ multi-array EC probe was designed to increase the measurement accuracy of the sectional profiling EC testing of tube. As a result, we would like to propose the application of $8{\times}1$ multi-array EC probe for the measurement of size and shape of profile change on steam generator tube in OPR-1000 nuclear power plant.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.207-215
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• 2021

A forklift is an industrial vehicle with a power-operated fork for lifting and moving heavy loads over short distances. A significant number of accidents are caused by forklifts every year. Most of them are known to be caused by the unsafe acts of workers. However, only a few studies have focused on the risks of forklift work from the perspective of human error. In addition, various methods have been developed to analyze the risk of human error, while it is hard to find studies that directly compare the effectiveness or strengths/weaknesses of those methods. This study aims to analyze risk factors related to unsafe behavior in forklift operations using two representative human error analysis techniques, i.e., .SHERPA and HE-HAZOP, and compare their advantages and disadvantages. The analysis was performed on three main forklift operations ('unloading from the truck', 'moving and loading into the storage', and 'loading on the truck'). As a result, 118 errors and 34 remedial measures were derived by SHERPA. Through HAZOP, 139 errors and 54 measures were derived. The two techniques were compared in terms of the number of results and the method of deriving errors and remedial measures, cause analysis, and risk assessment. This study might be used to reduce human error related disasters in workplaces using forklifts. In order to provide a guide for choosing an appropriate analysis method, more comparative studies on different techniques involving wide range of tasks are needed in the future.

• Journal of IKEEE
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• v.25 no.4
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• pp.689-696
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• 2021

In this paper, in order to apply Prognostics and Health Management(PHM) to an electronic system or circuit, a circuit capable of detecting and predicting defect characteristics inside the system or circuit is implemented, and the results are described. In the previous study, we demonstrated that the frequency of the amplitude of S-parameter changed as the circuit defect progressed. These characteristics were measured by network analyser. but in this study, even if the same defect detection method is used, a circuit is proposed to check the progress of the defect, the remaining time, and the occurrence of the defect without large measurement devices. The circuit is designed to detect the change in impedance that generates changes of S-parameter, and it is verified through simulation using the measurement results of Bond-wires.