• Tunnel and Underground Space
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• v.30 no.1
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• pp.1-14
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• 2020

Microseismic monitoring is utilized for the performance verification and safety management of the structure by detecting fine levels of damage. In order to construct a highly reliable microseismic monitoring system, the role of signal conditioner is critical. The signal conditioner helps with accurate data collection and precision control of the device, and performs additional functions such as signal conversion, linearization, and amplification. In this technical report, noise reduction signal conditioner suitable for mining sites was developed and reviewed for the purpose of implementing more precise monitoring by supplementing the previously developed microseismic monitoring system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4933-4956
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• 2016

Use-After-Free (UAF) is a common lethal form of software vulnerability. By using tools such as Web Browser Fuzzing, a large amount of samples containing UAF vulnerabilities can be generated. To evaluate the threat level of vulnerability or to patch the vulnerabilities, automatic deduplication and exploitability determination should be carried out for these samples. There are some problems existing in current methods, including inadequate pertinence, lack of depth and precision of analysis, high time cost, and low accuracy. In this paper, in terms of key dangling pointer and crash context, we analyze four properties of similar samples of UAF vulnerability, explore the method of extracting and calculate clustering eigenvalues from these samples, perform clustering by fast search and find of density peaks on a large number of vulnerability samples. Samples were divided into different UAF vulnerability categories according to the clustering results, and the exploitability of these UAF vulnerabilities was determined by observing the shape of class cluster. Experimental results showed that the approach was applicable to the deduplication and exploitability determination of a large amount of UAF vulnerability samples, with high accuracy and low performance cost.

• Journal of the Korean Society for Heat Treatment
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• v.3 no.2
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• pp.10-19
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• 1990

The tempering behavoirs of 0.45% carbon steel treated by automatic progressive high frequency induction hardening equipment have been investigated. In order to examine the correlation of hardness with both tempering temperature and time, simple regression analysis has been made using the statistical quality control package. The maximum surface hardness value of induction hardened zone and its effective hardening depth have been determined to be Hv 810 and 0.76mm, respectively. The hardness obtained after tempering has been shown to vary lineary with tempering time at six different temperatures. The activation energies during tempering have been calculated to be 25.34kcal/mole, 32.73kcal/mole and 49.24kcal/mole for HRcs 60, 50 and 40, respectively, showing that tempering process occurs by a complex mechanism, The tempering hardness equation of $H=90.113{\sim}4.531{\times}10^{-3}$ [T(11.996+log t)] has proved to be in a reasonably good agreement with experimently determined data and it is also expected to be useful for the determination of tempering treatment conditions to obtain a required hardness value.

• Journal of Korean Neurosurgical Society
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• v.29 no.4
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• pp.491-499
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• 2000

Objective : In the cerebral aneurysm surgery, the goal is complete circulatory exclusion of the aneurysm without compromise of normal vessels. In an operating room, an operator should confirm the completeness and precision of the surgical result, before closing the wound. Object of this study was to determine which cases require intraoperative angiography. Methods : We reported our experience with 48 intraoperative angiographic studies performed during the surgical treatment of cerebral aneurysm of these 48 cases. There were 5 giant(10.4%), 15 globular(1.5-2.5cm)(31.25%) and 28 saccular(58.3%) aneurysm. We recorded the incidence of unexpected findings, such as residual aneurysms, major vessel occlusions. Using Fischer's exact test, we assessed whether unexpected angiographic findings showed any correlation with aneurysm site, size and clinical findings. Results : In 5 cases(10.4%), we detected unexpected angiographic findings which resulted in clip adjustment. By means of clip adjustment, an operator could restore the flow of two major arterial occlusion(4.2%) and also obliterate three persistent filling aneurysms(6.3%). Globular aneurysm was the only factor to predict unexpected angiographic findings(p<0.05). The subgroup of globular and giant aneurysm has a high risk of occlusion of the parent artery and its branches and/or residual aneurysm. There were two minor complications related to this procedure. Conclusion : Intraoperative assessment makes it possible to recognize and correct the technical defect. Particularly in globular aneurysm, we were able to prevent both the chance for another operation and the risk of postoperative complications.

• Korean Journal of Metals and Materials
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• v.50 no.1
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• pp.13-22
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• 2012

Forged and flat-bar rolled STD11 tool steel shows anisotropic dimensional change during heat treatment. The dimensional change in the rolling direction is larger than that in the transverse direction. The cause of the anisotropic dimensional change is that the steel is anisotropic in composition, microstructure and other properties. The decrease of anisotropic distortion in tool steel is important for making better precision cold working dies. In this study, the effect of ingot weight and hot rolling reduction ratio on the anisotropic dimensional change of STD11 during heat treatment has been studied. Dimensional change was evaluated by simulating a real heat treatment process, including gas quenching and tempering. Experimental results showed that all the rolled flat-bar products had anisotropic distortion to some degree, but the anisotropic distortion was reduced as hot rolling ratio increased. Ingot weight had a little effect on anisotropic distortion. Microstructural observation showed that the anisotropic dimensional change of STD11 tool steel was closely related to the amount, shape and distribution of coarse carbides.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• Computers and Concrete
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• v.32 no.3
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.59-66
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• 2023

The Golden Cross is commonly seen as a buy signal in financial markets, but its reliability for predicting stock price movements is limited due to market volatility. This paper introduces a time-invariant approach that considers the Golden Cross as a singular event. Utilizing LSTM neural networks, we forecast significant stock price changes following a Golden Cross occurrence. By comparing our approach with traditional time series analysis and using a confusion matrix for classification, we demonstrate its effectiveness in predicting post-event stock price trends. To conclude, this study proposes a model with a precision of 83%. By utilizing the model, investors can alleviate potential losses, rather than making buy decisions under all circumstances following a Golden Cross event.

• Analytical Science and Technology
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• v.36 no.5
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• pp.205-215
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• 2023

In the present study, an analytical method was proposed for detecting trifluralin in aquatic products at trace concentrations. The method employed QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) and gas chromatography coupled with tandem mass spectrometry (GC-MS/MS) as the sample preparation and measurement, respectively. The effect of the aqueous phase volume used in the QuEChERS was demonstrated, and the ratio of 10:10 (mL) between water and acetonitrile phase was used for 5 g of sample. Besides, dSPE using C18 and primary-secondary amine (PSA) was applied to remove the potential interferences from the food matrices, indicating no remarkable analyte loss. The linear range was built up from 0.50 ㎍ L^-1 to 3.0 ㎍ L^-1 (R² = 0.9993). Other criteria, i.e., repeatability (RSD_r = 0.86-1.96 %), reproducibility (RSD_R = 1.09-2.01 %), and recovery (over 90 %), were in accordance with Appendix F of AOAC (2016) for method performance. Although no trifluralin was detected for the commercial samples (fish, shrimp, and breaded shrimp), the spiked samples performed favorable recoveries and precision.