• Computers and Concrete
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• v.32 no.3
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• pp.233-246
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• 2023

Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R²) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.704-719
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• 2024

Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.41-46
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• 2008

Generally optical components are fabricated by grinding, lapping and polishing processes. Those processes take long time to obtain optical high surface quality. In the case of large optical components, the on-machine measurement is strongly recommended because the workpiece is fragile and difficult to set up for fabricating and measuring. This paper is concerned about a swing-arm mechanism which can be used for on-machine measurement of a surface profile with a sensing probe end-effect, and also for grinding or lapping the surface with a corresponding tool. The measuring accuracy and uncertainty using a swing arm type profilometer have been studied. The experimental results show that this method is useful specially in lapping process with the accuracy of $5{\mu}m$. Those inspection data are provided for correcting the residual figuring error in next processes.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1307-1312
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• 2004

Word sense disambiguation is one of the most important problems in natural language processing research topics such as information retrieval and machine translation. Many approaches can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledge-based, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy. The purpose of this paper is to compare three famous machine learning techniques, Snow, SVM and Naive Bayes in Word-Sense Disambiguation on Thai language. 10 ambiguous words are selected to test with word and POS features. The results show that SVM algorithm gives the best results in solving of Thai WSD and the accuracy rate is approximately 83-96%.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.215-220
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• 2002

Recently, linear motor has been developed for linear motion of machine tools. Linear motor is useful to design the linear motion, high speed and high accuracy, because of the simple system not required the additional mechanical part such as coupling and ballscrew. This paper tested performance of linear motor relevant to motioning and positioning table such as F.R.F., step response and positional accuracy Linear motion system using linear motor requires the effective cooling system because it cause to decrease the positional error and to protect the motor coil. Therefore the positional error measurement was made to evaluate the effect of the temperature variation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.305-311
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• 1993

In recent years, it has been variously developed for testing the accuracy of circular motion of NC machine tools, for example Telescoping Ball Bar Method by Bryan,Circular Test Method by Knapp and r $_{- \theta}$ Mathod by Tsutsumi etc., but it is not yet settled in the code of measuring methods of motion errors of NC machine tools, because of errors of measuring units and sensors, and also especially the difficulties of centering of measuring units. In this paper, in use of magnetic type linear scale with resolution of 0.5 .mu. m and tick pulses come out from computer, it has become possible for detecting of linear displacement of radial errors and measuring of revolution angle of circular motion of NC machine tools.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.85-90
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• 2001

Recent general Press brake has many problems in cutting high accurate products in the progress of industry. Previous hand-operated press brake needs many pre-processing works to adjust bending ang1e and marking-off works to calculate bending length. Also, the hand-operating work makes many geometric errors and has difficulty for variety-mass production. To solve these problems, this paper proposes Computer Numerical Control (CNC) general press brake and development of servo-control system based on database for reduction of geometric errors and pre-processing work time and high accuracy bending work.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.165-168
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• 1995

The quality of products is depend on the performance of machine and machining conditions. In this study the runout of spindel is selected as a parameter through which we could appreciate the workability of machine and the quality of products. Throigh the runout of high speed machining center on freeload machining, the revolution accuracy and the characteristics in connection with spindle speed are evaluated. It was experimented flat and ball end milling for estimating machine accuracy and workability by measuring spindel runout. In end, This paper shows the effects of runout on surface roughness through analysis of runout and roughness profiles.

• Journal of KSNVE
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• v.8 no.2
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• pp.324-330
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• 1998

The forced vibration analysis of the outer-clamped spinnig annular disk with arbitrary in-plane is formulated to investigate the influence of non-uniform tension on the cutting accuracy of wafer cutting machine. The arbitrary in-plan force along the outer edge of an annular plate is expressed as a Fourier series. Galerkin method and modal superposition method are employed to obtain the forced responses under the static force and the impulse force in astationary coordinate. Through qualitative and quantitative analyses, it can be found that forced and impulse responses are sensitive to the non-uniformity of in-plane force, which can bring a bad effect to the accuracy of wafer cutting process. Also, in case of a spinning disk with non-uniform in-plane force, critical speed is required to define in a different way, compared with conventional definition in axi-symmetrical spinning disk.