• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.27-33
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• 2002

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3855-3867
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• 2022

Name separation (splitting full names into surnames and given names) is not a tedious task in a multiethnic country because the procedure for splitting surnames and given names is ethnicity-specific. Malaysia has multiple main ethnic groups; therefore, separating Malaysian full names into surnames and given names proves a challenge. In this study, we develop a two-phase framework for Malaysian name separation using deep learning. In the initial phase, we predict the ethnicity of full names. We propose a recurrent neural network with long short-term memory network-based model with character embeddings for prediction. Based on the predicted ethnicity, we use a rule-based algorithm for splitting full names into surnames and given names in the second phase. We evaluate the performance of the proposed model against various machine learning models and demonstrate that it outperforms them by an average of 9%. Moreover, transfer learning and fine-tuning of the proposed model with an additional dataset results in an improvement of up to 7% on average.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.639-655
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• 2023

Recently, there has been a growing demand for underground space, leading to the utilization of earth retaining walls for deep excavations. Earth retaining walls are structures that are susceptible to displacement, and their measurement and management are carried out in accordance with the standards established by the Ministry of Land, Infrastructure, and Transport. However, managing displacement through measurement can be considered similar to post-processing. Therefore, in this study, we not only predicted the horizontal displacement of a retaining wall with ground anchors installed using machine learning, but also analyzed the impact of the prediction model based on data scaling and data splitting methods while learning measurement data using machine learning. Custom splitting was the most suitable method for learning and outputting measurement data. Data scaling demonstrated excellent performance, with an error within 1 and an R-squared value of 0.77 when the anchor tensile force and water pressure were standardized. Additionally, it predicted a negative displacement compared to a model that without scaling.

• Journal of KIISE:Software and Applications
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• v.37 no.11
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• pp.826-836
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• 2010

This paper proposes a hybrid machine translation system which integrates SMT, RBMT, and PBMT in serial manner. SMT in our project has been implemented as a Quasi-syntax-based system where monotone search is done, given a preprocessed string of foreign language. Preprocessing includes rule-based reordering, NE recognition, clausal splitting, and attaching pattern translation information at the end of the input text. For lengthy & complex sentences, clausal splitting turned out to generate better translation than normal input.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.19-25
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• 2019

We have developed a tool that uses finite element analysis (FEA) to rapidly evaluate a shaft-bearing system of machine tools. We extracted commercial data on suitable clamping units and defined the inner profile of the shaft to avoid needing direct user input to define the profile. We use a splitting algorithm to convert the shaft into beam elements with two diameters and length. To validate the tool, we used it to design and evaluate a shaft-bearing system and found that our tool automated the construction of an FE system model in a commercial FEA package as well as the static stiffness evaluation; both tasks were completed in seconds, demonstrating a significant reduction from the minutes normally required to complete these tasks manually.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.37-43
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• 2007

In this paper, laser vision sensor is used to detect some defects any $co_{2}$ welded specimen in hardware. But, as the best expression of defects of welded specimen, the concept of segment splitting method and mean distance are introduced in software. The developed GUI software is used for deriding whether any welded specimen makes as proper shape or detects in real time. The criteria are based upon ISO 5817 as limits of imperfections in metallic fusion welds.

• Explosives and Blasting
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• v.20 no.2
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• pp.7-19
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• 2002

The cut is placed high up in the section, the 1st sloping holes below the cut, and divided all the holes located below the 1st sloping holes into a certain area with longitudinal section, to lower pollution made from tunnel blasting. With the sequential blasting machine, after I first blasted holes around the cut holes by a pre-splitting method, blasted the cut area and the 1st sloping holes. The 1st and 2nd sloping holes divided areas are initiated gradually to free face upwards made by the cut. Especially, I pre-splinted contour holes previous blast the before sloping holes from the contours. The ground vibration from the earth surface just over the advance face decreased about 42.0% compare with the down blasting method under the condition of equal charge weight per delay. I controlled the crack and over break of the mother rock by pre-splitting contour holes before blast the first sloping holes from the contours. The peak values of noise and air blast by blasting decreased about 10dB more than the down blasting method. the noise and air blast diminished gradually as a round. The throw distance of the fly rock was decreased about 55%.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.9-18
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• 2007

There have been continuous efforts for automation of joint tracking system. This automation process is mainly used to do in root pass of gas metal arc welding in the field of heavy industry and shipbuilding etc. For automation, it is important using of vision sensor. Welding robot with vision sensor is used for weld seam tracking on welding fabrication. Recently, it is used to on post-weld inspection for weld quality evaluation. For real time seam tracking, it is very important role in vision process technique. Vision process is included in filtering and thinning, segmentation processing, feature extraction and recognition. In this paper, it has shown performance comparison results of seam tracking for real time root pass on gas metal arc welding. It can be concluded better segment splitting method than iterative averaging technique in the performance results of seam tracking.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.213-223
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• 1999

In this paper, input-output transmission characteristics of the Eclipse, which is a parallel machine tool capable of 5 face rapid machining, are investigated. By splitting the weighted Jacobian matrix into two parts, the force and moment transmission characteristics together with the velocity and angular velocity transmission characteristics are analyzed. A new manipulability measure, which combines the volume of the manipulability ellipsoid and the condition number of the splitted Jcobian matrix, is proposed. Two link parameters, the ratio of upper and lower platforms' radii and the length of a supporting link of the Eclipse, are designed by applying the new manipulability measure derived. Computer simulations are provided.