• International conference on construction engineering and project management
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• 2024.07a
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• pp.375-382
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• 2024

Large Language Models (LLMs) still encounter challenges in comprehending domain-specific expressions within construction documents. Analogous to humans acquiring unfamiliar expressions from dictionaries, language models could assimilate domain-specific expressions through the use of a thesaurus. Numerous prior studies have developed construction thesauri; however, a practical issue arises in effectively leveraging these resources for instructing language models. Given that the thesaurus primarily outlines relationships between terms without indicating their relative importance, language models may struggle in discerning which terms to retain or replace. This research aims to establish a robust framework for guiding language models using the information from the thesaurus. For instance, a term would be associated with a list of similar terms while also being included in the lists of other related terms. The relative significance among terms could be ascertained by employing similarity scores normalized according to relevance ranks. Consequently, a term exhibiting a positive margin of normalized similarity scores (termed a pivot term) could semantically replace other related terms, thereby enabling LLMs to comprehend domain-specific terms through these pivotal terms. The outcome of this research presents a practical methodology for utilizing domain-specific thesauri to train LLMs and analyze construction documents. Ongoing evaluation involves validating the accuracy of the thesaurus-applied LLM (e.g., S-BERT) in identifying similarities within construction specification provisions. This outcome holds potential for the construction industry by enhancing LLMs' understanding of construction documents and subsequently improving text mining performance and project management efficiency.

• Therapeutic Science for Rehabilitation
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• v.3 no.2
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• pp.5-48
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• 2014

Introduction : One of the important domains in OT is performance skills which include sensory perceptual skills, motor and praxis skills, emotional regulation skills, cognitive skills, and communication/social skills. All of these skills are support ed by integrated neurological processes. Body : Stereology robust tool when employed to investigate morphological changes in neurons, cortex area, and specific parts of brain involved in special brain function. Stereology is an interdisciplinary field focused or analyzing biological tissue with the three-dimensional interpretation of planer sections by using estimating method and mathematically unbiased sampling. With the unbiased stereological method based on probability theory, researchers can estimate morphological and anatomical changes in biological reference areas accurately and efficiently. Changes in anatomical and cytoarchitectural parameters, such as volume, number, and length, affect specific brain function related to the brain area. Occupational therapists provide treatment to improve functions for participation of occupation in neurological disorder. The functional improvements in neurological disorder reflect neurobiological changes because functional difficulties, such as motor cognitive disorder, are due to neurological disturbances. Thus, combination of two kinds of evidence, neurological changes and functional improvement, provide fundamental evidence for OT intervention in neurological disorder. Even though most of stereological studies are in animal model and in postmortem human because of practical and ethical issues, stereology provides fundamental knowledge to support OT theory and practice. Conclusion : Therefore, stereology informs translation from neuroscience to OT based on structure-function relationship in performance skills and experience-dependent neural plasticity.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.123-137
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• 2018

A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.51-64
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• 2009

A location tracking sensor such as GPS, INS, Radar, and optical equipments is used in tracking Maneuvering Targets with a multi-sensor, and such systems are used to track, detect, and control UAV, guided missile, and spaceship. Until now, Most of the studies related to tracking Maneuvering Targets are on fusing multiple Radars, or adding a supplementary sensor to INS and GPS. However, A study is required to change the degree of application in fusions since the system property and error property are different from sensors. In this paper, we perform the error analysis of the sensor properties by adding a ground radar to GPS and INS for improving the tracking performance by multi-sensor fusion, and suggest the tracking algorithm that improves the precision and stability by changing the sensor probability of each sensor according to the error. For evaluation, we extract the altitude values in a simulation for the trajectory of UAV and apply the suggested algorithm to carry out the performance analysis. In this study, we change the weight of the evaluated values according to the degree of error between the navigation information of each sensor to improve the precision of navigation information, and made it possible to have a strong tracking which is not affected by external purposed environmental change and disturbance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.450-456
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• 2016

STDR (sequence time domain reflectometry) to detect a cable fault using a pseudo noise sequence as a reference signal, and time correlation analysis between the reference signal and reflection signal is robust to noisy environments and can detect intermittent faults including open faults and short circuits. On the other hand, if the distance of the fault location is far away or the fault type is a soft fault, attenuation of the reflected signal becomes larger; hence the correlation coefficient in the STDR becomes smaller, which makes fault detection difficult and the measurement error larger. In addition, automation of the fault location by detection of phase and peak value becomes difficult. Therefore, to improve the cable fault detection of a conventional STDR, this paper proposes the algorithm in that the peak value of the correlation coefficient of the reference signal is detected, and a peak value of the correlation coefficient of the reflected signal is then detected after removing the reference signal. The performance of the proposed method was validated experimentally in low-voltage power cables. The performance evaluation showed that the proposed method can identify whether a fault occurred more accurately and can track the fault locations better than conventional STDR despite the signal attenuation. In addition, there was no error of an automatic fault type and its location by the detection of the phase and peak value through the elimination of the reference signal and normalization of the correlation coefficient.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.156-170
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• 2006

Determining the best visibility positions on terrain surface has been one of the frequently used analytical issues in GIS visibility analysis and the search for a solution has been carried out effectively using spatial search techniques. However, the spatial search process provides operational and methodological challenges for finding computational algorithms suitable for solving the best visibility site problem. For this problem, current GIS visibility analysis has not been successful due to limited algorithmic structure and operational performance. To meet these challenges, this paper suggests four algorithms explored robust search techniques: an extensive iterative search technique; a conventional solution based on the Tornqvist algorithm; genetic algorithm; and simulated annealing technique. The solution performance of these algorithms is compared on a set of visibility location problems and the experiment results demonstrate the useful feasibility. Finally, this paper presents the potential applicability of the new spatial search techniques for GIS visibility analysis by which the new search algorithms are of particular useful for tackling extensive visibility optimization problems as the next GIS analysis tool.

• Journal of Environmental Health Sciences
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• v.40 no.2
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• pp.114-126
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• 2014

Objectives: We aimed to develop a measurement method of five metabolites of trichloroethylene (TCE) in a concurrent biological sample, e.g., trichloroacetic acid (TCA), dichloroacetic acid (DCA), S-(1,2-dichlorovinyl) glutathione (DCVG), S-(1,2-dichlorovinyl)-L-cysteine (DCVC), and N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NAcDCVC) and to validate the method before application to pharmacokinetic study. Methods: TCE metabolites were simultaneously analyzed using high performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC-ESI-MS/MS) with as little as 50 ${\mu}L$ of serum and urine. DCA, TCA and NAcDCVC were extracted with diethyl ether, while DCVC and DCVG were extracted by solid phase extraction. This method was validated according to the guidelines for bioanalytical method validation of the Korean National Institute of Toxicological Research. Then, we determined the five metabolites in five strains of mice at 24 hr after exposure to 1 g TCE /kg body weight. Results: The limits of detection for the five metabolites in biological samples ranged from 0.001 to 0.076 nmol/mL, which is comparable to or better than those previously reported. Most calibration curves showed good linearity ($R^2=0.99$), and between-batch variation was less than 20% expressing acceptable robustness and reproducibility. Using this method, we found TCA and DCA were detected in all test mice at 24 hr after the oral administration while NAcDCVC and DCVC were detected in some strains, which showed strain-dependent metabolism of TCE. Conclusions: The present method could provide robust and accurate measurements of major key metabolites of TCE in biological media, which allowed concurrent analysis of TCE metabolism for limited amounts of biospecimens.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.440-449
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• 2008

In this paper, we propose a 16-QAM carrier recovery loop which is suitable for the implementation of Inmarsat M4 system receiver. Because the frequency offset of ${\pm}924\;Hz$ on signal bandwidth 33.6 kHz is recommended in Inmarsat M4 system specification, carrier recovery loop having stable operation in the channel environment with large relative frequency offset is required. the carrier recovery loop which adopts only PLL can't be stable in relatively large frequency offset environment. Therefore, we propose a carrier recovery loop which has stable operation in large relative frequency offset environment for Inmarsat M4 system. The proposed carrier recovery loop employed differential filter-based noncoherent UW detector which is robust to frequency offset, CP-AFC for initial frequency offset acquisition using UW signal, and 16-QAM DD-PLL for phase tracking using data signal to overcome large relative frequency offset and achieve stable carrier recovery performance. Simulation results show that the proposed carrier recovery loop has stable operation and satisfactory performance in large relative frequency offset environment for Inmarsat M4 system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.8 s.338
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• pp.35-42
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• 2005

This paper describes novel flip-flops with improved robustness and reduced power consumption. Variable sampling window flip-flop (VSWFF) adjusts the width of the sampling window according to input data, providing robust data latching as well as shorter hold time. The flip-flop also reduces power consumption for higher input switching activities as compared to the conventional low-power flip-flop. Clock swing-reduced variable sampling window flip-flop (CSR-VSWFF) reduces clock power consumption by allowing the use of a small swing clock. Unlike conventional reduced clock swing flip-flops, it requires no additional voltage higher than the supply voltage, eliminating design overhead related to the generation and distribution of this voltage. Simulation results indicate that the proposed flip-flops provide uniform latency for narrower sampling window and improved power-delay product as compared to conventional flip-flops. To evaluate the performance of the proposed flip-flops, test structures were designed and implemented in a $0.3\mu m$ CMOS process technology. Experimental result indicates that VSWFF yields power reduction for the maximum input switching activity, and a synchronous counter designed with CSR-VSWFF improves performance in terms of power consumption with no use of extra voltage higher than the supply voltage.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.83-90
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• 2010

Cancelable biometrics is a robust and secure biometric recognition method using revocable biometric template in order to prevent possible compromisation of the original biometric data. In this paper, we present a new cancelable bits extraction method for the facial data. We use our previous cancelable feature template for the bits extraction. The adopted cancelable template is generated from two different original face feature vectors extracted from two different appearance-based approaches. Each element of feature vectors is re-ordered, and the scrambled features are added. With the added feature, biometric bits string is extracted using helper data based method. In this technique, helper data is generated using statistical property of the added feature vector, which can be easily replaced with straightforward revocation. Because, the helper data only utilizes partial information of the added feature, our proposed method is a more secure method than our previous one. The proposed method utilizes the helper data to reduce feature variance within the same individual and increase the distinctiveness of bit strings of different individuals for good recognition performance. For a security evaluation of our proposed method, a scenario in which the system is compromised by an adversary is also considered. In our experiments, we analyze the proposed method with respect to performance and security using the extended YALEB face database