• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.370-375
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• 2010

인터넷의 영역이 확대됨에 따라 인터넷에서 다양하고 많은 정보를 제공받게 되었다. 뉴스의 영역도 그중 하나로 신문사, 방송사 등의 많은 언론사들이 인터넷으로 서비스를 확대함에 따라 뉴스 정보의 과다현상이 일어나게 되었다. 이 때문에 사용자는 방대한 뉴스들 중에서 원하는 뉴스만 걸러서 보기를 원하게 되었고 이를 위한 뉴스 필터링 방법이 연구되었다. 뉴스 필터링 기술들은 주로 사용자의 관심 사항을 예측하여 제공해 주는 뉴스 추천 시스템을 위한 기술 개발에 초점을 두었다. 그러나 기존의 뉴스 필터링 기술들은 사용자의 관심 있어할 만한 뉴스를 추천할 뿐, 관심 없는 뉴스를 제외시키지는 못한다. 예를들어, 어떤 특종 사건이 생기면 이 사건을 보도하기 위한 뉴스들이 각 언론사 마다 생성되고, 뉴스 추천서비스를 사용하는 사용자는 기존의 뉴스 필터링 방법에 의해 사용자가 관심 있다고 예측되는 이 사건에 대한 뉴스를 제공받게 된다. 그러나 사용자가 이미 추천된 뉴스 중 하나의 뉴스 혹은 그와 동일한 내용의 다른 언론사에서 제공되는 뉴스를 읽었다면 추천된 뉴스는 이미 알고 있는 정보이므로 사용자는 이 뉴스에 대하여 관심이 없을 것이다. 기존의 뉴스 필터링 방법은 추천 시 중복된 뉴스를 제거하지 못하는 문제점을 지닌다. 이 논문은 이러한 문제점을 해결하기 위해 육하원칙 기반의 필터링 방법을 제시하고, 실험을 통해 이 논문이 제시한 방법의 장단점을 보인다.

• Journal of Korean Library and Information Science Society
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• v.50 no.3
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• pp.71-95
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• 2019

With high interest in linked data, there are various attempts to accommodate the linked data model in cataloging process. This study intends to discuss how to adopt and make the best use of linked data based bibliographic framework in order to improve the quality of library catalogs and to enhance library services in Korean libraries. To the end, this study focuses on (1) discussion of the meaning of linked data from the library cataloging perspective, (2) tracking best practices for implementing and operating linked data among North American and Europe libraries and bibliographic networks (in detail, constructing various types of ontology, developing linked data model including BIBFRAME and OCLC linked model, and improving retrieval service and interface), and finally (3) exploring problems and the anticipated challenges to transition to the linked data model in Korea. The data for discussion were collected from literature review and case study.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.583-590
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• 2018

Genus Typha L. (Typhaceae; Cattail in common) is one of the hydrophytic plants found in semi-aquatic regions. About nine to 18 species of the genus exist all over the world. In Korea, the most commonly found cattail species are T. laxmanni and T. angustifolia. The aim of this study was to prepare a cDNA library and sequences and analyze expressed sequence tags (ESTs) from these species, T. laxmanni and T. angustifolia. In the case of T. laxmanni, we observed that 715 out of 742 ESTs had high quality sequences, whereas the remaining 27 ESTs were low quality sequences. In this study, we identified 77 contigs, 393 unassembled clones and 65.7% singletons. Furthermore, in the case of T. angustifolia, we recorded 992 high quality EST sequences, and by excluding 28 low quality sequences from among them, we retrieved 120 contigs, 348 unassembled clones and 48.9% singletons. The basic local alignment search tool (BLAST) and Kyoto encyclopedia of genes and genomes (KEGG) database results enabled us to identify the functional categories, i.e., molecular function (16.5%), biological process (22.2%) and cellular components (61.3%). In addition, between these two species, the no hits and anonymous genes were 4.2% and 11.7% and 6.2% and 11.2% in T. laxmanni and T. angustifolia, respectively, based on the BLAST results. The study concluded that they have certain species-specific genes. Hence, the results of this study on these two species could be a valuable resource for further studies.

• Mycobiology
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• v.46 no.4
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• pp.421-428
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• 2018

The white button mushroom (Agaricus bisporus) is one of the most widely cultivated species of edible mushroom. Despite its economic importance, relatively little is known about the genetic diversity of this species. Illumina paired-end sequencing produced 43,871,558 clean reads and 69,174 contigs were generated from five offspring. These contigs were subsequently assembled into 57,594 unigenes. The unigenes were annotated with reference genome in which 6,559 unigenes were associated with clusters, indicating orthologous genes. Gene ontology classification assigned many unigenes. Based on genome data of the five offspring, 44 polymorphic simple sequence repeat (SSR) markers were developed. The major allele frequency ranged from 0.42 to 0.92. The number of genotypes and the number of alleles ranged from 1 to 4, and from 2 to 4, respectively. The observed heterozygosity and the expected heterozygosity ranged from 0.00 to 1.00, and from 0.15 to 0.64, respectively. The polymorphic information content value ranged from 0.14 to 0.57. The genetic distances and UPGMA clustering discriminated offspring strains. The SSR markers developed in this study can be applied in polymorphism analyses of button mushroom and for cultivar discrimination.

• Molecules and Cells
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• v.42 no.4
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• pp.333-344
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• 2019

Various genetic and environmental factors are known to be associated with chronic obstructive pulmonary disease (COPD). We identified COPD-related differentially expressed genes (DEGs) using 189 samples accompanying either adenocarcinoma (AC) or squamous cell carcinoma (SC), comprising 91 normal and 98 COPD samples. DEGs were obtained from the intersection of two DEG sets separately identified for AC and SC to exclude the influence of different cancer backgrounds co-occurring with COPD. We also measured patient samples named group 'I', which were unable to be determined as normal or COPD based on alterations in gene expression. The Gene Ontology (GO) analysis revealed significant alterations in the expression of genes categorized with the 'cell adhesion', 'inflammatory response', and 'mitochondrial functions', i.e., well-known functions related to COPD, in samples from patients with COPD. Multi-omics data were subsequently integrated to decipher the upstream regulatory changes linked to the gene expression alterations in COPD. COPD-associated expression quantitative trait loci (eQTLs) were located at the upstream regulatory regions of 96 DEGs. Additionally, 45 previously identified COPD-related miRNAs were predicted to target 66 of the DEGs. The eQTLs and miRNAs might affect the expression of 'respiratory electron transport chain' genes and 'cell proliferation' genes, respectively, while both eQTLs and miRNAs might affect the expression of 'apoptosis' genes. We think that our present study will contribute to our understanding of the molecular etiology of COPD accompanying lung cancer.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1084-1094
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• 2019

Objective: The aim of this study was to select the candidate genes affecting meat quality and preliminarily explore the related molecular mechanisms in the Mashen pig. Methods: The present study explored genetic factors affecting meat quality in the Mashen pig using RNA sequencing (RNA-Seq). We sequenced the transcriptomes of 180-day-old Mashen and Large White pigs using longissimus dorsi to select differentially expressed genes (DEGs). Results: The results indicated that a total of 425 genes were differentially expressed between Mashen and Large White pigs. A gene ontology enrichment analysis revealed that DEGs were mainly enriched for biological processes associated with metabolism and muscle development, while a Kyoto encyclopedia of genes and genomes analysis showed that DEGs mainly participated in signaling pathways associated with amino acid metabolism, fatty acid metabolism, and skeletal muscle differentiation. A MCODE analysis of the protein-protein interaction network indicated that the four identified subsets of genes were mainly associated with translational initiation, skeletal muscle differentiation, amino acid metabolism, and oxidative phosphorylation pathways. Conclusion: Based on the analysis results, we selected glutamic-oxaloacetic transaminase 1, malate dehydrogenase 1, pyruvate dehydrogenase 1, pyruvate dehydrogenase kinase 4, and activator protein-1 as candidate genes affecting meat quality in pigs. A discussion of the related molecular mechanisms is provided to offer a theoretical basis for future studies on the improvement of meat quality in pigs.

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.74-78
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• 2019

As software becomes larger and network technology develops, the management of distributed data becomes more popular. Therefore, it is becoming increasingly important to use blockchain technology that can guarantee the integrity of data in various fields by utilizing existing infrastructure. Blockchain is a distributed computing technology that ensures that servers participating in a network maintain and manage data according to specific agreement algorithms and rules to ensure integrity. As smart contracts are applied, not only passwords but also various services to be applied to the code. In order to reinforce existing research on smart contract applied to the blockchain, we proposed a dynamic conditional rule of smart contract that can formalize rules of smart contract by introducing ontology and SWRL and manage rules dynamically in various situations. In the previous research, there is a module that receives the upper rule in the blockchain network, and the rule layer is formed according to this module. However, for every transaction request, it is a lot of resources to check the top rule in a blockchain network, or to provide it to every blockchain network by a reputable organization every time the rule is updated. To solve this problem, we propose to separate the module responsible for the upper rule into an independent server. Since the module responsible for the above rules is separated into servers, the rules underlying the service may be transformed or attacked in the middleware. Therefore, the security mechanism using TLS and PKI is added as an agent in consideration of the security factor. In this way, the benefits of computing resource management and security can be achieved at the same time.

• Database Research
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• v.34 no.3
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• pp.69-85
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• 2018

Many researches proposed federated query engines to perform query on several homogeneous or heterogeneous datasets simultaneously that significantly improve the quality of query results. The existing techniques allow querying only over a few heterogeneous datasets considering the static binding using the non-standard query. However, we observe that a simultaneous system considering the integration of heterogeneous metadata standards can offer better opportunity to generalize the query over any homogeneous and heterogeneous datasets. In this paper, we propose a transparent federated engine (DRAZ) to query over multiple data sources using SPARQL. In our system, we first develop the ontology for a non-RDF metadata standard based on the metadata kernel dictionary elements, which are standardized by the metadata provider. For a given SPARQL query, we translate any triple pattern into an API call to access the dataset of corresponding non-RDF metadata standard. We convert the results of every API call to N-triples and summarize the final results considering all triple patterns. We evaluated our proposed DRAZ using modified Fedbench benchmark queries over heterogeneous metadata standards, such as DCAT and DOI. We observed that DRAZ can achieve 70 to 100 percent correctness of the results despite the unavailability of the JOIN operations.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2049-2068
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• 2021

AI combined with NLP techniques has promoted the use of Virtual Assistants and have made people rely on them for many diverse uses. Conversational Agents are the most promising technique that assists computer users through their operation. An important challenge in developing Conversational Agents globally is transferring the groundbreaking expertise obtained in English to other languages. AI is making it possible to transfer this learning. There is a dire need to develop systems that understand secular languages. One such difficult language is Hindi, which is the fourth most spoken language in the world. Semantic similarity is an important part of Natural Language Processing, which involves applications such as ontology learning and information extraction, for developing conversational agents. Most of the research is concentrated on English and other European languages. This paper presents a Corpus-based word semantic similarity measure for Hindi. An experiment involving the translation of the English benchmark dataset to Hindi is performed, investigating the incorporation of the corpus, with human and machine similarity ratings. A significant correlation to the human intuition and the algorithm ratings has been calculated for analyzing the accuracy of the proposed similarity measures. The method can be adapted in various applications of word semantic similarity or module for any other language.