• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.46-54
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• 2021

As the realization of the 4th industrial revolution is approaching, the paradigm of the corporate work environment is changing to digital, from the traditional work environment. In particular, technologies like RPA(robotic process automation) and chatbot reduce the need for human labor or task by automating simple repetitive tasks, enabling humans to focus on more valuable tasks. In this study, corporates operating expense management services in public cloud computing environments develop a cloud module that simplifies expense report management by grafting robotic process automation and chatbot technology. According to the result of the expert evaluation, the developed system marked 80.3% of satisfaction levels and the highest satisfaction level 94% was confirmed in terms of easy of use. Based on the research result, future research can be suggested to expand the works occurring inside and outside the company to a single RPA environment by additionally linking the work system related to expense management.

• Journal of Korean Home Economics Education Association
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• v.22 no.2
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• pp.133-153
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• 2010

The purpose of this study is to find out the philosophy embedded in the newly revised 2007 Home Economics curriculum. Furthermore, it analyses the current situation and future tasks of textbooks in view of that philosophy. With this analysis it tries to give alternative teaching-learning strategies for making the best use of the existing textbooks. This study deals with the newly revised 2007 Home Economics curriculum. It also analyses the twelve sorts of textbooks for the first grade students in secondary schools, which are supposed to be based on that curriculum. As a research method this study takes a qualitative approach. As follows are the results of this study. First, in the character and objectives of the curriculum is embedded the critical science perspective of Home Economics curriculum. Second, the current situation and future tasks of the textbooks are analysed with the criteria by Yang, mi-kyung about textbook construction. And we have ascertained the following problems. The current textbooks are not well designed so that teachers have the appropriate orientation, encourage students to nurture the critical thinking abilities, and urge students to employ practical reasoning in the context of society, history and culture. Third, this study proposes five alternative teaching-learning strategies for making the best use of the current textbooks in order to tackle the above-mentioned problems.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.363-369
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• 2010

Demonstration-based learning has the advantage that a user can easily teach his/her robot new task knowledge just by demonstrating directly how to perform the task. However, many previous demonstration-based learning techniques used a kind of attribute-value vector model to represent their state spaces and policies. Due to the limitation of this model, they suffered from both low efficiency of the learning process and low reusability of the learned policy. In this paper, we present a new demonstration-based learning method, in which the relational model is adopted in place of the attribute-value model. Applying the relational instance-based learning to the training examples extracted from the records of the user demonstrations, the method derives a relational instance-based policy which can be easily utilized for other similar tasks in the same domain. A relational policy maps a context, represented as a pair of (state, goal), to a corresponding action to be executed. In this paper, we give a detail explanation of our demonstration-based relational policy learning method, and then analyze the effectiveness of our learning method through some experiments using a robot simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1234-1249
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• 2017

One of the difficulties developers encounter in maintaining tasks of a large-scale software system is the updating of suitable libraries on time. Developers tend to miss or make mistakes when searching for and choosing libraries during the development process, or there may not be a stable library for the developers to use. We present a novel approach for helping developers modify software easily and on time and avoid software failures. Using a tool previously built by us called GPES, we collected information of projects, such as abstract syntax trees, tokens, software metrics, relations, and evolutions, for our experiments. We analyzed the contexts of source codes in existing projects to predict changes automatically and to recommend suitable libraries for the projects. The collected data show that researchers can reduce the overall cost of data analysis by transforming the extracted data into the required input formats with a simple query-based implementation. Also, we manually evaluated how the extracted contexts are similar to the description and we found that a sufficient number of the words in the contexts is similar and it might help developers grasp the domain of the source codes easily.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.75-86
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• 2006

Target word selection is one of the most important and difficult tasks in English-Korean Machine Translation. It effects on the translation accuracy of machine translation systems. In this paper, we present a new approach to select Korean target word for an English noun with translation ambiguities using multiple knowledge such as verb frame patterns, sense vectors based on collocations, statistical Korean local context information and co-occurring POS information. Verb frame patterns constructed with dictionary and corpus play an important role in resolving the sparseness problem of collocation data. Sense vectors are a set of collocation data when an English word having target selection ambiguities is to be translated to specific Korean target word. Statistical Korean local context Information is an N-gram information generated using Korean corpus. The co-occurring POS information is a statistically significant POS clue which appears with ambiguous word. The experiment showed promising results for diverse sentences from web documents.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• Asia Marketing Journal
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• v.14 no.4
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• pp.117-142
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• 2013

Brand orientation is a relatively new paradigm in marketing which was first introduced in the 1990s. Since then, an accumulating body of research has addressed the strategic importance of brand orientation. Although there is a growing body of literature on brand orientation, there have been no empirical studies examining the mediation effect of brand orientation on market orientation-performance relationship to date. Moreover, most studies on brand orientation have been carried out in the context of large enterprises. Hence, the aim of this research is to extend the literature and address market orientation, brand orientation, and firm performance against the backdrop of Korean SMEs. The authors empirically investigate the impact of market/brand orientation on organizational performance and the mediating role of brand orientation. They utilize 178 usable responses to test the four research hypotheses. The hypothesized model predicts that there is a positive association among market orientation, brand orientation, and firm performance. It is also expected that brand orientation mediates the relationship between market orientation and organizational performance. The statistical results based on PLS analysis confirm our prediction among the constructs in the research model. The empirical evidence provides significant theoretical and managerial implications for brand orientation among SMEs. The first theoretical implication is that we provide empirical evidence regarding the important role of brand orientation in explaining the multi-trait perspectives of strategic orientation. The second theoretical implication is that the concept of brand orientation can be empirically validated in the context of SMEs. In terms of managerial implications, managers of SMEs should attempt to build a brand-oriented corporate culture or mindset that places brand values and brand norms as the top priority among their company's tasks. In addition, managers should recognize that brand orientation is critical for SMEs as well as large enterprises. In the last section, the authors address limitations of the study and provide directions for further research.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.486-500
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• 2013

This study is conducted to examine how epistemic reasoning and argument structures of students vary according to data sources used in the process of argumentation implemented in the context of inquiry. To this end, three argument tasks using first-hand data and three argument tasks using second-hand data were developed and applied to the unit on 'Nutrition of Plants' for first year middle school students. According to the results of this study, epistemic reasoning of students manifested during the process of argumentation and varied according to data sources. While most students composed explanations with phenomenon-based or relation-based reasoning in argumentation using first-hand data, all the small groups composed explanations that included model-based reasoning in argumentation using second-hand data. In the case of arguments including phenomenon-based or relation-based reasoning, students described only observable characteristics, with warrants omitted from arguments in many cases. On the other hand, in the case of arguments that included model-based reasoning, explanations were composed by combining the results of observations with theoretical knowledge, with warrants more apparent in their arguments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1759-1772
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• 2023

Chinese named entity recognition (NER) is a challenging work that seeks to find, recognize and classify various types of information elements in unstructured text. Due to the Chinese text has no natural boundary like the spaces in the English text, Chinese named entity identification is much more difficult. At present, most deep learning based NER models are developed using a bidirectional long short-term memory network (BiLSTM), yet the performance still has some space to improve. To further improve their performance in Chinese NER tasks, we propose a new NER model, IDCNN-BiLSTM-Highway, which is a combination of the BiLSTM, the iterated dilated convolutional neural network (IDCNN) and the highway network. In our model, IDCNN is used to achieve multiscale context aggregation from a long sequence of words. Highway network is used to effectively connect different layers of networks, allowing information to pass through network layers smoothly without attenuation. Finally, the global optimum tag result is obtained by introducing conditional random field (CRF). The experimental results show that compared with other popular deep learning-based NER models, our model shows superior performance on two Chinese NER data sets: Resume and Yidu-S4k, The F1-scores are 94.98 and 77.59, respectively.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.727-739
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• 2003

In this paper, we propose a generation method of regression classes for adaptation in the HM-Net (Hidden Markov Network) system. The MLLR (Maximum Likelihood Linear Regression) adaptation approach is applied to the HM-Net speech recognition system for expressing the characteristics of speaker effectively and the use of HM-Net in various tasks. For the state level sharing, the context domain state splitting of PDT-SSS (Phonetic Decision Tree-based Successive State Splitting) algorithm, which has the contextual and time domain clustering, is adopted. In each state of contextual domain, the desired phoneme classes are determined by splitting the context information (classes) including target speaker's speech data. The number of adaptation parameters, such as means and variances, is autonomously controlled by contextual domain state splitting of PDT-SSS, depending on the context information and the amount of adaptation utterances from a new speaker. The experiments are performed to verify the effectiveness of the proposed method on the KLE (The center for Korean Language Engineering) 452 data and YNU (Yeungnam Dniv) 200 data. The experimental results show that the accuracies of phone, word, and sentence recognition system increased by 34∼37%, 9%, and 20%, respectively, Compared with performance according to the length of adaptation utterances, the performance are also significantly improved even in short adaptation utterances. Therefore, we can argue that the proposed regression class method is well applied to HM-Net speech recognition system employing MLLR speaker adaptation.