• Journal of Environmental Health Sciences
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• v.38 no.6
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• pp.550-560
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• 2012

Objectives: QSAR methodology was applied to explain two different sets of acceptable daily intake (ADI) data of 74 pesticides proposed by both the USEPA and WHO in terms of setting guidelines for food and drinking water. Methods: A subset of calculated descriptors was selected from Dragon$^{(R)}$ software. QSARs were then developed utilizing a statistical technique, genetic algorithm-multiple linear regression (GA-MLR). The differences in each specific model in the prediction of the ADI of the pesticides were discussed. Results: The stepwise multiple linear regression analysis resulted in a statistically significant QSAR model with five descriptors. Resultant QSAR models were robust, showing good utility across multiple classes of pesticide compounds. The applicability domain was also defined. The proposed models were robust and satisfactory. Conclusions: The QSAR model could be a feasible and effective tool for predicting ADI and for the comparison of logADIEPA to logADIWHO. The statistical results agree with the fact that USEPA focuses on more subtle endpoints than does WHO.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.37-47
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• 2014

We propose a new generic design methodology for different types of PSS. Product - Service System (PSS) has received much attention recently from academia and industry because of its benefits. PSS can provide customers values and functionalities, as well as physical products, to fulfill economic, social and environmental goals. Many methodologies have been proposed for designing PSSs. Most of the existing methodologies are domain specific and were proposed to solve specific problems in certain projects. Some methodologies are generic but they provide neither guideline to practitioners and designers nor reflect the differences in various PSS types. As a generic approach to guide practitioners and designers in designing PSS effectively, the proposed methodology also takes into account user involvement, business model and organizational structure. The proposed methodology is demonstrated through design examples of different types of PSSs.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.4
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• pp.49-62
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• 2020

This research investigates how interest develops across a set of tasks within a course defined by a specific knowledge domain. The current study examined the relationships among self-concept, self-efficacy, Korea-related factors, and evaluation, in the context of learning about the Hanbok costume at Chinese universities. A survey (n=300) was conducted using an online survey website (www.sojump.com) from the 1st to the 25th of June. The structural equation model (SEM) analysis, including total and specific forms of self-evaluation with Hanbok courses, showed that self-concept was positively associated with self-efficacy. Conversely, K-culture interest and K-country image did not significantly affect self-efficacy in clothing, but positively affected Hanbok's self-efficacy. Meanwhile, the more self-efficacy perceived, the higher the level of evaluation. Overall, our findings imply that supporting the students' Korean culture interest, country image perception, and self-concept for regulation can enhance self-evaluation and self-realization success. Theoretical and practical implications for Hanbok courses are discussed.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.126-133
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• 2024

Large language models (LLMs) have revolutionized the global landscape of technology beyond natural language processing. Owing to their extensive pre-training on vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without additional fine-tuning. General-purpose chatbots based on LLMs can optimize the efficiency of radiologists in terms of their professional work and research endeavors. Importantly, these LLMs are on a trajectory of rapid evolution, wherein challenges such as "hallucination," high training cost, and efficiency issues are addressed, along with the inclusion of multimodal inputs. In this review, we aim to offer conceptual knowledge and actionable guidance to radiologists interested in utilizing LLMs through a succinct overview of the topic and a summary of radiology-specific aspects, from the beginning to potential future directions.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.115-122
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• 2004

Software system modeling has a goal for finding and solving system's problems by describing and analyzing system model in formal notations. Petri nets, as graphical formalism, have been used in describing and analyzing the software systems such as parallel systems, real-time system, and protocols. In the analysis of Petri nets, general system properties such as deadlock and liveness are analyzed by the reachability analysis. On the other side, specific properties such as functional requirements and constraints are checked by model-checking. However, since these analysis methods are based on enumeration of ail possible states, there nay be state explosion problem, which means that system states exponentially increase as the size of system is larger. In this paper, we propose a new method for mechanically checking system properties with avoiding state explosion problem. At first, system properties are described in property nets then the system model and the property net are composed and analyzed. In the compositional analysis, system parts irrelevant to the specific property are reduced to minimize the analysis domain of the system. And it is possible to mechanically check whether a specific property is satisfied or not.

• The Journal of Bigdata
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• v.7 no.1
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• pp.89-97
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• 2022

Various efforts are needed to prevent accidents because ship collisions can cause various negative situations such as economic losses and casualties. Therefore, research to prevent accidents is being actively conducted, and in this study, new leading indicators for preventing ship collision accidents is proposed. In previous studies, the risk of collision was expressed in consideration of the distance between ships in a specific sea area, but there is a disadvantage that a new model needs to be developed to apply this to other sea areas. In this study, the density-based ship domain DESD (Density-based Empirical Ship Domain) including the environment and operating characteristics of the sea area was defined using AIS (Automatic Identification System) data, which is ship operation information. Deep clustering is applied to two-dimensional DESDs created for each sea area to cluster the seas with similar operating environments. Through the analysis of the relationship between clustered sea areas and ship collision accidents, it was statistically tested that the occurrence of accidents varies by characteristic of each sea area, and it was proved that DESD can be used as a leading indicator of accidents.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.403-418
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• 2012

In this paper, we attempted to theorize the synergy effect between the value creating attributes for digital convergence model in the service industry. Our investigation is based upon contingency fit theory to understand the strategic fit for the two inherent value attributes of fixed and mobile value, as well as resolving fundamental limitations of service processes. Empirical validation of the derived research model is analyzed using hierarchical regression method. The results indicate that the relative advantage of each value creating attributes are strongly associated with the characteristics of domain service industries, and compatibility is critical to user adoption of convergent service model. Moreover, the less significant statistical impact of the synergy between mobile and fixed value attributes and others implies that each value attribute uniquely contributes to particular IT convergence model, which thereby offers critical insight that focusing the convergent value in conjunction with specific application domain is the most appealing managerial focus. The findings provide useful insight for the further research in IT based industry convergent business model areas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1769-1776
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• 2022

Automatically summarizing long sentences is an important technique. The BART model is one of the widely used models in the summarization task. In general, in order to generate a summarization model of a specific domain, fine-tuning is performed by re-training a language model trained on a large dataset to fit the domain. The fine-tuning is usually done by changing the number of nodes in the last fully connected layer. However, in this paper, we propose a fine-tuning method by adding an attention layer, which has been recently applied to various models and shows good performance. In order to evaluate the performance of the proposed method, various experiments were conducted, such as accumulating layers deeper, fine-tuning without skip connections during the fine tuning process, and so on. As a result, the BART model using two attention layers with skip connection shows the best score.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.2
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• pp.35-42
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• 2010

In this study, crosstalk between dominant interconnect pairs in an A/D converter circuit is analyzed in frequency domain and effects of termination conditions on crosstalk are described, based on the practical circuit conditions. An A/D converter circuit is a mixed circuit where both clean and noisy signals coexist such that the circuit probably suffers from distortion by crosstalk. An analog input signal and the reference voltage signal, which dominate the overall conversion performance of the A/D converter circuit, are ready to be distorted by crosstalk and include specific termination conditions, such as non-matching and capacitive termination, respectively. Thus, this study presents the model of crosstalk considering impedance mismatch at both ends and analyzes effects of the practical termination conditions in the analog input and the reference voltage interconnects on crosstalk. A typical circuit configuration of the two interconnects is described and crosstalk including near-end and far-end termination impedances is modeled. Effects of the near-end impedance mismatch in the analog input interconnect and the far-end capacitive termination in the reference voltage interconnect are estimated in the frequency domain by using the model of crosstalk and experiments are performed to confirm the estimated results. Microstrip lines are used as interconnects, involving the increase of loss in high frequencies.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.335-346
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• 2008

Causal relations in ontology should be defined based on the inference types necessary to solve problems specific to application as well as domain. In this paper, we present a model to define and extract causal relations for application ontology for Question-Answering (QA) on fault-diagnosis of electronic devices. Causal categories are defined by analyzing generic patterns of QA application; the relations between concepts in the corpus belonging to the causal categories are defined as causal relations. Instances of casual relations are extracted using lexical patterns in the concept definitions of domain, and extended incrementally with information from thesaurus. On the evaluation by domain specialists, our model shows precision of 92.3% in classification of relations and precision of 80.7% in identifying causal relations at the extraction phase.