• Genomics & Informatics
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• v.18 no.2
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• pp.23.1-23.6
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• 2020

The Human Phenotype Ontology (HPO) is the de facto standard ontology to describe human phenotypes in detail, and it is actively used, particularly in the field of rare disease diagnoses. For clinicians who are not fluent in English, the HPO has been translated into many languages, and there have been four initiatives to develop Japanese translations. At the Biomedical Linked Annotation Hackathon 6 (BLAH6), a rule-based approach was attempted to determine the preferable Japanese translation for each HPO term among the candidates developed by the four approaches. The relationship between the HPO and Mammalian Phenotype translations was also investigated, with the eventual goal of harmonizing the two translations to facilitate phenotype-based comparisons of species in Japanese through cross-species phenotype matching. In order to deal with the increase in the number of HPO terms and the need for manual curation, it would be useful to have a dictionary containing word-by-word correspondences and fixed translation phrases for English word order. These considerations seem applicable to HPO localization into other languages.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.85-94
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• 2016

We propose a model-based method for information alignment using educational standards as a case study. Discrepancies and inconsistencies in educational standards across different states/cities hinder the retrieval and sharing of educational resources. Unlike existing educational standards alignment systems that only give binary judgments (either "aligned" or "not-aligned"), our proposed system classifies each pair of educational standard statements in one of seven levels of alignments: Strongly Fully-aligned, Weakly Fully-aligned, Partially-$aligned^{***}$, Partially-$aligned^{**}$, Partially-$aligned^*$, Poorly-aligned, and Not-aligned. Such a 7-level categorization extends the notion of binary alignment and provides a finer-grained system for comparing educational standards that can broaden categories of resource discovery and retrieval. This study continues our previous use of mathematics education as a domain, because of its generally unambiguous concepts. We adopt a materialization pattern (MP) model developed in our earlier work to represent each standard statement as a verb-phrase graph and a noun-phrase graph; we align a pair of statements using graph matching based on Bloom's Taxonomy, WordNet, and taxonomy of mathematics concepts. Our experiments on data sets of mathematics educational standards show that our proposed system can provide alignment results with a high degree of agreement with domain expert's judgments.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.59-68
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• 2016

Context-aware services recognize the context of situation environments of users and provide useful services according to the context for users. Usual rule-based systems can be used for context-aware services with the specified rules that express context information and operations. This paper proposes a light-weight rule engine that minimizes memory consumption for resource-constrained smart things. The rule engine manages rules at the minimum condition level, removes memories for intermediate rule matching results, and uses hash tables to store rules and context information efficiently. The implemented engine is verified using a rule set of a mouse training system and experiment results shows the engines consumes very little memory compared to the existing Rete algorithm with some sacrifice of execution time.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.47-49
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• 2003

Automatic land use and land cover change (LUCC) detection via remotely sensed imagery has a wide application in the area of LUCC research, nature resource and environment monitoring and protection. Under the condition that one time (T1) data is existed land use and land cover maps, and another time (T2) data is remotely sensed imagery, how to detect change automatically is still an unresolved issue. This paper developed a land use and land cover class knowledge guided method for automatic change detection under this situation. Firstly, the land use and land cover map in T1 and remote sensing images in T2 were registered and superimposed precisely. Secondly, the remotely sensed knowledge database of all land use and land cover classes was constructed based on the unchanged parcels in T1 map. Thirdly, guided by T1 land use and land cover map, feature statistics for each parcel or pixel in RS images were extracted. Finally, land use and land cover changes were found and the change class was recognized through the automatic matching between the knowledge database of remote sensing information of land use & land cover classes and the extracted statistics in that parcel or pixel. Experimental results and some actual applications show the efficiency of this method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2240-2254
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• 2021

We investigate the channel allocation problem in an ultra-dense device-to-device (D2D) enabled cellular network in underlaying mode where multiple D2D users are forced to share the same channel. Two kinds of low complexity solutions, which just require partial channel state information (CSI) exchange, are devised to resolve the combinatorial optimization problem with the quality of service (QoS) guaranteeing. We begin by sorting the cellular users equipment (CUEs) links in sequence in a matric of interference tolerance for ensuring the SINR requirement. Moreover, the interference quota of CUEs is regarded as one kind of communication resource. Multiple D2D candidates compete for the interference quota to establish spectrum sharing links. Then base station calculates the occupation of interference quota by D2D users with partial CSI such as the interference channel gain of D2D users and the channel gain of D2D themselves, and carries out the channel allocation by setting different access priorities distribution. In this paper, we proposed two novel fast matching algorithms utilize partial information rather than global CSI exchanging, which reduce the computation complexity. Numerical results reveal that, our proposed algorithms achieve outstanding performance than the contrast algorithms including Hungarian algorithm in terms of throughput, fairness and access rate. Specifically, the performance of our proposed channel allocation algorithm is more superior in ultra-dense D2D scenarios.

• Korea Trade Review
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• v.44 no.4
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• pp.115-128
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• 2019

This article analyzes issues regarding the economic development of the arctic area with the aim of finding ways to help solve the problems and to support sustainable economic development of the arctic area. Some proposals are introduced for establishing a sound legal infrastructure of the Korea-Russia economic development of the arctic area. As Russia develops the Arctic area and the route through the Arctic area, Korea will gain the possibility of transportation efficiency, vitalization of international transaction, and finding new markets. Resource development in the North Pole is ongoing, with matching international transaction and economic benefits. To reflect the Korea-Russia interests and to sustain the effect, the legal infrastructure is inevitable. For example, it would be reinforced by pushing forward the Korea-Russia FTA. The legal infrastructure for economic cooperation of Korea and Russia has to reflect that 'the development of the Arctic area and making the route through the Arctic area' should increase the sustainability and vitality of international transaction. The legal infrastructure for economic benefits can also help mitigating non-economic arguments of international community such as the security risk in the Korean-peninsula and around the world.

• ETRI Journal
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• v.45 no.6
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• pp.963-973
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• 2023

Non-orthogonal multiple access (NOMA) is considered a key candidate technology for next-generation wireless communication systems due to its high spectral efficiency and massive connectivity. Incorporating the concepts of multiple-input-multiple-output (MIMO) into NOMA can further improve the system efficiency, but the hardware complexity increases. This study develops an energy-efficient (EE) subchannel assignment framework for MIMO-NOMA systems under the quality-of-service and interference constraints. This framework handles an energy-efficient co-training-based semi-supervised learning (EE-CSL) algorithm, which utilizes a small portion of existing labeled data generated by numerical iterative algorithms for training. To improve the learning performance of the proposed EE-CSL, initial assignment is performed by a many-to-one matching (MOM) algorithm. The MOM algorithm helps achieve a low complex solution. Simulation results illustrate that a lower computational complexity of the EE-CSL algorithm helps significantly minimize the energy consumption in a network. Furthermore, the sum rate of NOMA outperforms conventional orthogonal multiple access.

• Childhood Kidney Diseases
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• v.28 no.1
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• pp.8-15
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• 2024

With the rapid evolution of diagnostic tools, particularly next-generation sequencing, the identification of genetic diseases, predominantly those with pediatric-onset, has significantly advanced. However, this progress presents challenges that span from selecting appropriate tests to the final interpretation of results. This review examines various genetic testing methodologies, each with specific indications and characteristics, emphasizing the importance of selecting the appropriate genetic test in clinical practice, taking into account factors like detection range, cost, turnaround time, and specificity of the clinical diagnosis. Interpretation of variants has become more challenging, often requiring further validation and significant resource allocation. Laboratories primarily classify variants based on the American College of Medical Genetics and Genomics and the Association for Clinical Genomic Science guidelines, however, this process has limitations. This review underscores the critical role of clinicians in matching patient phenotypes with reported genes/variants and considering additional factors such as variable expressivity, disease pleiotropy, and incomplete penetrance. These considerations should be aligned with specific gene-disease characteristics and segregation results based on an extended pedigree. In conclusion, this review aims to enhance understanding of the complexities of clinical genetic testing, advocating for a multidisciplinary approach to ensure accurate diagnosis and effective management of rare genetic diseases.

• Journal of Navigation and Port Research
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• v.45 no.4
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• pp.186-193
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• 2021

To enhance the competitiveness of the Busan Port in accordance with changes in global shipping and port industry trends, the Busan New Port is promoting step-by-step integration and developing a port resource-sharing platform. However, inefficient resource-sharing can cause unnecessary additional costs or impede port productivity, so accurate supply and demand matching of shared resources is required. In this study, the supply and demand of port resources were investigated for employees of Busan New Port and North Port, and port resources that could be ideally shared through IPA(Importance Performance Analysis) were analyzed. As a result of analyzing the equipment in the port, Yard Tractor, Reach Stacker, and Top Handler were the top considerations, and for facilities in the port, berths and aprons, empty container yards, and refrigerated container yards were the most important considerations. As for the data in the port, gate status, equipment specifications, and berth and apron conditions were the top considerations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.27-43
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• 2024

Recently, the importance of trademarks as a core resource of corporate competitiveness to protect and differentiate products and services is increasing. Global companies are focusing hard to secure trademark rights to manage brands that reflect their core values and to respond to increasingly frequent trademark disputes, while start-ups and individuals are working hard to secure trademark to run stable businesses and attract investment funds. Meanwhile, this study conducts an empirical analysis to identify the relationship between the brand and business strategy of domestic venture startups. The analysis data used was the response data of 2,230 corporate companies from the 2021 Venture Business Precision Survey, and the propensity score matching method, structural equation model analysis, and binomial logit analysis were used as analysis methods. As a result of the analysis, it was confirmed that domestic venture startups' trademark ownership does not make a significant difference in terms of the level of business strategy. This was confirmed to be because the brands of domestic venture start-ups mainly advance their business strategies only through the internal competency process, while the advancement of business strategies through the external competency process is very minimal. Meanwhile, it was confirmed that the level of cost advantage strategy among the business strategy levels of venture start-ups strengthens the tendency to hold trademarks, indicating that the higher the completeness of the cost advantage level, the more likely it is to expand trademark ownership for stable sales and supply of products and services through trademark ownership and to convert to high value-added in the future.