• Land and Housing Review
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• v.2 no.4
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• pp.315-324
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• 2011

In the merged organization, the efforts of integration such as various PMI activities, etc. are exerted and the performance of PMI can be judged by evaluating the effectiveness of an organization. In this paper, the empirical analysis was conducted to see what effects of 'planned PMI activities' and 'voluntary integration efforts' have on the effectiveness of an organization which is 'Organizational Commitment', 'Job Satisfaction', 'Emotional Integration' and 'Shared Value Recognition'. The survey was made on the employees of LH, which is a representative case of public corporation advancement, and SPSS 17.0 and AMOS 17 were used for the analysis. As a result of the analysis of a structural equation model, it indicated that both 'planned PMI activities' and 'voluntary integration efforts' have direct influence on 4 indices of effectiveness of an organization respectively. In particular, it was found that 'planned PMI activities' affects 'Shared Value Recognition' the most and 'voluntary integration efforts' has the largest effect on 'Emotional Integration'. Through this study, it was verified that voluntary integration efforts of members as well as the planed formal PMI activities are also very important factor of effect on the integration performance of an organization.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.1-20
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• 2020

Purpose - This paper shows an unexplored area related to involuntary delisting. Specifically, this research investigates the effect of target firm information asymmetry on the likelihood that the acquirer or newly merged firm will be forcibly delisted post-merger. Design/methodology/approach - The research uses a sample gathered on local US mergers and acquisitions from the Thomson Reuters Securities Data Company (SDC) Platinum Mergers and Acquisitions database. It applies the logistic regression with industry and year effects and corrects the error term using clustering at the industry level. The research also matches the forced delisted firms to control firms based on industry, acquisition completion year, and firm size and then employs a matched sample analysis. Findings - Findings show that M&As between firms where the target firm is opaque and burdened with high information asymmetry issues are likely to be paid for using majority stock and that M&As involving such opaque targets also have a higher likelihood of getting delisted post-merger. Research implications or Originality - Our results are relevant given the very nature of M&As which involve two players: the acquirer and target who both may have different incentives. Acquirers especially have the tendency to suffer losses and even get delisted if they over-pay for or get merged to a poor target which conceals its poor performance evidenced by higher accruals quality.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.79.4-80
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• 2021

Sunspots' subsurface structure is an important subject to explain their stability and energy transport. Previous studies suggested two models for the subsurface structure of sunspots: monolithic model and cluster model. However, it is not revealed which model is more plausible so far. We obtain clues about the subsurface structure of sunspots by analyzing the motion of umbral flashes observed by the IRIS Mg II 2796Å slit-jaw images (SJI). The umbral flashes are believed as shock phenomena developed from upward propagating slow magnetohydrodynamic (MHD) waves. If the MHD waves are generated by convective motion below sunspots, the apparent origin of the umbral flashes known as oscillation center will indicate the horizontal position of convection cells. Thus, the distribution of the oscillation centers is useful to investigate the subsurface structure of sunspots. We analyze the spatial distribution of oscillation centers in the merged sunspot. As a result, we found that the oscillation centers distributed over the whole umbra regardless of the convergent interface between two merged sunspots. It implies that the subsurface structure of the sunspot is not much different from the convergent interface, and supports that many field-free gaps may exist below the umbra as the cluster model expected. For more concrete results, we should confirm that the oscillation centers determined by the umbral flashes accurately reflect the position of wave sources.

• Journal of Hydrogen and New Energy
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• v.34 no.6
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• pp.748-757
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• 2023

Numerical analysis was conducted to confirm the characteristics of extinction behavior in NH₃/CH₄ counterflow symmetrical flames. Numerical simulations were run on CHEMKIN-PRO, using the OPPDIF code, with Okafor's mechanisms, which had the lowest error rate compared to Colson's experimental data in the our previous part I study. The chemical interactions of merged flames were examined by analyzing the production rate of major chemical species and key radicals with the volume fractional percentage of ammonia and global strain rate. The interaction phenomenon of the flames could be identified by observing the main chemical reaction path of the merged flames at the stagnation plane.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.29-38
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• 2011

In order to derive domain-independent heuristics from the specification of a planning problem, it is required to relax the given problem and then solve the relaxed one. In this paper, we present a new planning graph, Merged Planning Graph(MPG), and GD heuristics for solving contingent planning problems with both uncertainty about the initial state and non-deterministic action effects. The merged planning graph is an extended one to be applied to the contingent planning problems from the relaxed planning graph, which is a common means to get effective heuristics for solving the classical planning problems. In order to get heuristics for solving the contingent planning problems with sensing actions and non-deterministic actions, the new graph utilizes additionally the effect-merge relaxations of these actions as well as the traditional delete relaxations. Proceeding parallel to the forward expansion of the merged planning graph, the computation of GD heuristic excludes the unnecessary redundant cost from estimating the minimal reachability cost to achieve the overall set of goals by analyzing interdependencies among goals or subgoals. Therefore, GD heuristics have the advantage that they usually require less computation time than the overlap heuristics, but are more informative than the max and the additive heuristics. In this paper, we explain the experimental analysis to show the accuracy and the search efficiency of the GD heuristics.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.903-906
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• 1998

We propose a new method for merging partical regions which have similar motion characteristics. In the proposed method, the trajectories of each partial regions are computed and the regions consisting a same object are merged by a similarity function defined in this paper. The similarity function is defined to take into consideration the motion characteristics of the trajectories. The proposed method shows good performance when the regions of an object show little variation in size and shape.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.1
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• pp.36-47
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• 2000

DEA has been effectively applied to various areas which need the evaluation of relative efficiency. We propose a DEA model based on fuzzy LP in order to consider uncertain synergy effects due to M&A of existing organization. We apply the suggested approach to forecasting the efficiency of merged academic departments in a university in Korea. We expect that our approach can be utilized to effectively realign existing departments.

• KCID journal
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• v.9 no.1
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• pp.70-81
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• 2002

Based on the innovation of national infrastructure, 187 Water sectors were merged into 87 branch offices and many employees were released institutions, since 1999. In Dongjin Branch Office where most. of irrigation water comes from Seomjin River Dam, it w