• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• The Mathematical Education
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• v.59 no.1
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• pp.63-80
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• 2020

This study analyzed 3,114 articles published in KCI journals and 1,636 articles published in SSCI journals from 2000 to 2019 in order to compare domestic and international research trends of mathematics education using a topic modeling method. Results indicated that there were 16 similar research topics in domestic and international mathematics education journals: algebra/algebraic thinking, fraction, function/representation, statistics, geometry, problem-solving, model/modeling, proof, achievement effect/difference, affective factor, preservice teacher, teaching practice, textbook/curriculum, task analysis, assessment, and theory. Also, there were 7 distinct research topics in domestic and international mathematics education journals. Topics such as affective/cognitive domain and research trends, mathematics concept, class activity, number/operation, creativity/STEAM, proportional reasoning, and college/technology were identified from the domestic journals, whereas discourse/interaction, professional development, identity/equity, child thinking, semiotics/embodied cognition, intervention effect, and design/technology were the topics identified from the international journals. The topic related to preservice teacher was the most frequently addressed topic in both domestic and international research. The topic related to in-service teachers' professional development was the second most popular topic in international research, whereas it was not identified in domestic research. Domestic research in mathematics education tended to pay attention to the topics concerned with the mathematical competency, but it focused more on problem-solving and creativity/STEAM than other mathematical competencies. Rather, international research highlighted the topic related to equity and social justice.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.129-149
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• 2013

According to the development of new Information Technologies, firms consistently invest a significant amount of money in IT activities, such as establishing internal and external information systems. However, several anti-Information activities-such as hacking, leakage of information and system destruction-are also rapidly increasing, thus many firms are exposed to direct and indirect threats. Therefore, firms try to establish information security systems and manage these systems more effectively via an enterprise perspective. However, stakeholders or some managers have negative opinions about information security systems. Therefore, in this research, we study the relationship between multibusiness firms' performance and information security systems. Information security indicates physical and logical correspondence of information system department against threats and disaster. Studies on information security systems suggested frameworks such as IT Governance Cube and COBIT Framework to identify information security systems. Thus, this study define that information security systems is a controlled system on enterprise IT process and resource on IT Governance perspective rather than independent domain of IT. Thus, Information Security Systems should be understood as a subordinate concept of IT and business processes. In addition, this study incorporates information capability to information security system literature to show the positive relationship between Information Security Systems and Corporate Performance. The concept of information capability suggested that an interaction of human, information, technical and an effect on corporate performance using three types of capability (IT Practice, Information Management Practice, Information Behaviors and Values). Information capability is about firms' capability to manage IT infrastructure and information as well as individual employees who use IT infrastructure and information. Thus, this study uses information capability as a mediating variable for the relationship between information security systems and firms' performance. To investigate the relationship between Information Security Systems and multibusiness firms' performance, this study extends the IT relatedness concept into Information Security Systems. IT relatedness provides understanding of how corporations cope with conflicts between headquarters and business units to create a synergy effect and achieve high performance using IT resources. Based on the previous literature, this study develops the IT Security Relatedness model. IT Security Relatedness is our main independent variable, while Information Capability and Information Security Performance are mediating variables. To control for the common method bias, we collect each multibusiness firm's financial performance and use it as our dependent variable. We find that Information Security Systems influence Information Capability and Information Security Performance positively, and these two variables consequently influence Corporate Performance positively. In addition, this result indirectly shows that corporations under a multibusiness environment can obtain synergy effects using the integrated Information Security Systems. This positive impact of Information Security Systems on multibusiness firms' performance has an important implication to various stakeholders. Therefore, multibusiness firms need to establish Information Security Systems to achieve better financial performance.

• Experimental and Molecular Medicine
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• v.50 no.12
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• pp.1.1-1.14
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• 2018

DNA methylation is a regulatory mechanism in epigenetics that is frequently altered during human carcinogenesis. To detect critical methylation events associated with gastric cancer (GC), we compared three DNA methylomes from gastric mucosa (GM), intestinal metaplasia (IM), and gastric tumor (GT) cells that were microscopically dissected from an intestinal-type early gastric cancer (EGC) using methylated DNA binding domain sequencing (MBD-seq) and reduced representation bisulfite sequencing (RRBS) analysis. In this study, we focused on differentially methylated promoters (DMPs) that could be directly associated with gene expression. We detected 2,761 and 677 DMPs between the GT and GM by MBD-seq and RRBS, respectively, and for a total of 3,035 DMPs. Then, 514 (17%) of all DMPs were detected in the IM genome, which is a precancer of GC, supporting that some DMPs might represent an early event in gastric carcinogenesis. A pathway analysis of all DMPs demonstrated that 59 G protein-coupled receptor (GPCR) genes linked to the hypermethylated DMPs were significantly enriched in a neuroactive ligand-receptor interaction pathway. Furthermore, among the 59 GPCRs, six GI hormone receptor genes (NPY1R, PPYR1, PTGDR, PTGER2, PTGER3, and SSTR2) that play an inhibitory role in the secretion of gastrin or gastric acid were selected and validated as potential biomarkers for the diagnosis or prognosis of GC patients in two cohorts. These data suggest that the loss of function of gastrointestinal (GI) hormone receptors by promoter methylation may lead to gastric carcinogenesis because gastrin and gastric acid have been known to play a role in cell differentiation and carcinogenesis in the GI tract.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.178-188
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• 2019

When using a distributed system, it is very important to know the intention of a target ship in order to prevent collisions. The action taken by a certain ship for collision avoidance and the action of the target ship it intends to avoid influence each other. However, it is difficult to establish a collision avoidance plan in consideration of multiple-ship situations for this reason. To solve this problem, a Distributed Stochastic Search Algorithm (DSSA) has been proposed. A DSSA searches for a course that can most reduce cost through repeated information exchange with target ships, and then indicates whether the current course should be maintained or a new course should be chosen according to probability and constraints. However, it has not been proven how the parameters used in DSSA affect collision avoidance actions. Therefore, in this paper, I have investigated the effect of the parameters and weight factors of DSSA. Experiments were conducted by combining parameters (time window, safe domain, detection range) and weight factors for encounters of two ships in head-on, crossing, and overtaking situations. A total of 24,000 experiments were conducted: 8,000 iterations for each situation. As a result, no collision occurred in any experiment conducted using DSSA. Costs have been shown to increase if a ship gives a large weight to its destination, i.e., takes selfish behavior. The more lasting the expected position of the target ship, the smaller the sailing distance and the number of message exchanges. The larger the detection range, the safer the interaction.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.457-464
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• 2021

The advent of the big data era has enabled the rapid development of deep learning that learns rules by itself from data. In particular, the performance of CNN algorithms has reached the level of self-adjusting the source data itself. However, the existing image processing method only deals with the image data itself, and does not sufficiently consider the heterogeneous environment in which the image is generated. Images generated in a heterogeneous environment may have the same information, but their features may be expressed differently depending on the photographing environment. This means that not only the different environmental information of each image but also the same information are represented by different features, which may degrade the performance of the image analysis model. Therefore, in this paper, we propose a method to improve the performance of the image color constancy model based on Adversarial Learning that uses image data generated in a heterogeneous environment simultaneously. Specifically, the proposed methodology operates with the interaction of the 'Domain Discriminator' that predicts the environment in which the image was taken and the 'Illumination Estimator' that predicts the lighting value. As a result of conducting an experiment on 7,022 images taken in heterogeneous environments to evaluate the performance of the proposed methodology, the proposed methodology showed superior performance in terms of Angular Error compared to the existing methods.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.109-117
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• 2021

Recently, the use of speech-based interfaces is increasing as a means for human-computer interaction (HCI). Accordingly, interest in post-processors for correcting errors in speech recognition results is also increasing. However, a lot of human-labor is required for data construction. in order to manufacture a sequence to sequence (S2S) based speech recognition post-processor. To this end, to alleviate the limitations of the existing construction methodology, a new data construction method called Back TranScription (BTS) was proposed. BTS refers to a technology that combines TTS and STT technology to create a pseudo parallel corpus. This methodology eliminates the role of a phonetic transcriptor and can automatically generate vast amounts of training data, saving the cost. This paper verified through experiments that data should be constructed in consideration of text style and domain rather than constructing data without any criteria by extending the existing BTS research.

• Journal of the Korean Chemical Society
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• v.66 no.2
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• pp.107-123
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• 2022

The purpose of this study is to investigate the effects of learning using computer-based science inquiry program. To this end, the three lessons computer-based science inquiry were developed in domain of material's properties. The developed program was put into K middle school located in Seoul and the effects were verified. For the experimental group, the three lessons computer-based science inquiry related to the separation of mixture were introduced, and for the comparison group, the contents presented in the textbook were introduced as a teacher-centered teaching method. To verify the effects of the program, 2-way ANCOVA was performed on positive experiences about science and science core competency, and 2-way ANOVA was performed on academic achievement. As a result of the study, there were significant differences between the two groups in positive experiernces about science and scientific core competencies and academic achievement (p<.05), and group^*gender interaction effect was only significant in academic achievement (p<.05). From the results of this study, we could see the possibility of using a computer-based science inquiry program as a chemistry teaching method that enables sustainable scientific inquiry.

• Journal of Life Science
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• v.32 no.3
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• pp.241-248
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• 2022

NF-κB acts as a critical transcription factor in inflammation and innate immunity, and it is also closely involved in cell survival and tumorigenesis via induction of anti-apoptotic genes. In these processes, NF-κB cooperates with multiple other signaling molecules and pathways, and although many studies have demonstrated that Hsp90 regulates NF-κB activity, the exact mechanism is unclear. In this study, we investigated the relationship between Hsp90 and IKKγ in the regulation of NF-κB using expression plasmids of IKK complex components. Wild-type and deletion mutants of IKKγ were expressed together with Hsp90, and the combined regulatory effect of Hsp90 and IKKγ on NF-κB activation was assayed. The results show that Hsp90 activates NF-κB by promoting the phosphorylation and degradation of IκBα and that activation of NF-κB by NIK and LPS was increased by Hsp90. IKKγ elevated the effect of Hsp90 on NF-κB activation by increasing phosphorylation and degradation of IκBα. The positive regulation on NF-κB by Hsp90 and IKKγ was also proved in analysis with IKKβ-EE, the constitutively active form of IKKβ. In experiments with the deletion mutants of IKKγ, the N-terminal IKKβ binding domain, C-terminal leucine zipper, and zinc finger domains of IKKγ were found not necessary for the positive regulation of NF-κB activity. Additionally, the expression of pro-inflammatory cytokines was synergistically elevated by Hsp90 and IKKγ. These results indicate that inhibiting the interaction between Hsp90 and IKKγ is a possible strategic method for controlling NF-κB and related diseases.