• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.451-464
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• 2016

Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).

• Interdisciplinary Bio Central
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• v.4 no.3
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• pp.8.1-8.7
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• 2012

The motor neuron degeneration 2 (mnd2) mice carry a point mutation of A to T nucleotide transversion at the serine 276 residue of high temperature requirement A2 (HtrA2), resulting in losses of an AluI restriction enzyme site (5'AGCT3') and the HtrA2 serine protease activity. Moreover, dysfunctions of HtrA2 are known to be intimately associated with the pathogenesis of neurodegenerative diseases, including Parkinson's disease. Thus, this mnd2 mouse is an invaluable model for understanding the physiological role of HtrA2 and its pathological role in neurodegenerative diseases. Nevertheless, many molecular and cellular biologists in this field have limited experience in working with mutant mouse models due to the necessity of acquired years of the special techniques and knowledges. Herein, using the mnd2 mouse model as an example, we describe easy-to-use standard protocols for web-based analyses of target genes, such as HtrA2, and a novel approach for simple and accurate PCR-AluI-RFLP-based genotype analysis of mnd2 mice. In addition, band resolution of AluI-RFLP fragments was improved in 12% polyacrylamide gel running in 1X Tris-Glycine SDS buffer. Our study indicates that this PCR-AluI-RFLP genotype analysis method can be easily applied by the molecular and cellular biologist to conduct biomedical science studies using the other mutant mouse models.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.411-422
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• 2017

Current policies for sharing bandwidth increase average throughput and improve utilization of the bandwidth in the local network. However, with these policies, a central administer, which is responsible for allocating bandwidth to each network flow, cannot allocate resources based on user characteristics. Thus, it leads to unfair bandwidth allocation because it does not guarantee services based on user characteristics. Therefore, we propose a novel negotiation method to share the bandwidth in a limited bandwidth network, in which, a user negotiates with other users to gain more resource. Ideally, we use a fuzzy system to infer and determine whether a device will request bandwidth or not based on the current usage of the given device. We conduct two experiments consisting of a video streaming simulation in OPNET and a real-time video streaming in WebRTC. The results of the experiment indicate that the proposed method can flexibly share the bandwidth utilization based on user's requirement in the network.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.46-63
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• 2022

With the rapid development of digital technology and the growing trend to integrate it into the medical field, recent studies suggest language rehabilitation for people with aphasia using virtual reality (VR), augmented reality (AR) and mobile applications. This study conducted a scoping review to summarize the features of digital technology-based language rehabilitation for aphasia in the last four years (2018-2021) and draw implications for future research. A total of 20 papers met the selection criteria among the documents retrieved from the Web of Science, CINAHL, and RISS. This review demonstrates that digital technology could offer unique treatment content by gamification, individualization, and creating a realistic communication environment, and by utilizing them in various ways. Therefore, we expect digital technology-based language rehabilitation for aphasia could supplement the limitations of conventional language rehabilitation and provide a novel perspective on development of treatment content.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.164-172
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• 2014

Recently, as the number of IoT (Internet of Things) devices for personal or home intelligence increases, the need for unified control and cooperative utilization is required. This paper presents a novel idea, proposes methods for virtualizing Internet of Things (IoT) devices and hosting them on the home AP instead of relying on a cloud service or purchasing a new device to do so. For this, the process and profile of the IoT gadgets need to be virtualized into JavaScript-based objects. Then, to execute and control the instances of the virtualized IoT objects on the wireless AP, a novel instance management method and their interfaces are designed. The implementation and performance section demonstrates the proposed system's stability and operability by showing the stress test results while the wireless AP is running for its wireless routing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.175-182
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• 2010

The paper presents a novel algorithm for face and iris detection with the application for driver iris monitoring. The proposed algorithm consists of the following major steps: Skin-color segmentation, facial features segmentation, and iris positioning. For the skin-segmentation we applied a multi-layer perceptron to approximate the statistical probability of certain skin-colors, and filter out those with low probabilities. The next step segments the face region into the following categories: eye, mouth, eye brow, and remaining facial regions. For this purpose we propose a novel segmentation technique based on estimation of facial class probability density functions (PDF). Each facial class PDF is estimated on the basis of salient features extracted from a corresponding facial image region. Then pixels are classified according to the highest probability selected from four estimated PDFs. The final step applies the circular Hough transform to the detected eye regions to extract the position and radius of the iris. We tested our system on two data sets. The first one is obtained from the Web and contains faces under different illuminations. The second dataset was collected by us. It contains images obtained from video sequences recorded by a CCD camera while a driver was driving a car. The experimental results are presented, showing high detection rates.

• International Journal of Oral Biology
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• v.42 no.2
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• pp.63-70
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• 2017

Selecting an appropriate antigen with optimal immunogenicity and physicochemical properties is a pivotal factor to develop a protein based subunit vaccine. Despite rapid progress in modern molecular cloning and recombinant protein technology, there remains a huge challenge for purifying and using protein antigens rich in hydrophobic domains, such as membrane associated proteins. To overcome current limitations using hydrophobic proteins as vaccine antigens, we adopted in silico analyses which included bioinformatic prediction and sequence-based protein 3D structure modeling, to develop a novel periodontitis subunit vaccine against the outer membrane protein FomA of Fusobacterium nucleatum. To generate an optimal antigen candidate, we predicted hydrophilicity and B cell epitope parameter by querying to web-based databases, and designed a truncated FomA (tFomA) candidate with better solubility and preserved B cell epitopes. The truncated recombinant protein was engineered to expose epitopes on the surface through simulating amino acid sequence-based 3D folding in aqueous environment. The recombinant tFomA was further expressed and purified, and its immunological properties were evaluated. In the mice intranasal vaccination study, tFomA significantly induced antigen-specific IgG and sIgA responses in both systemic and oral-mucosal compartments, respectively. Our results testify that intelligent in silico designing of antigens provide amenable vaccine epitopes from hard-to-manufacture hydrophobic domain rich microbial antigens.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.505-517
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• 2008

This paper proposes a rewriting algorithm of OWL-DL ontology query in SPARQL. Currently, to obtain inference results of given SPARQL queries, Web ontology repositories construct inference ontology models and match the SPARQL queries with the models. However, an inference model requires much larger space than its original base model, and reusability of the model is not available for other inferrable SPARQL queries. Therefore, the aforementioned approach is not suitable for large scale SPARQL query processing. To resolve tills issue, this paper proposes a novel SPARQL query rewriting algorithm that can obtain results by rewriting SPARQL queries and accomplishing query operations against the base ontology model. To achieve this goal, we first define OWL-DL inference rules and apply them on rewriting graph pattern in queries. The paper categorizes the inference rules and discusses on how these rules affect the query rewriting. To show the advantages of our proposal, a prototype system based on lena is implemented. For comparative evaluation, we conduct an experiment with a set of test queries and compare of our proposal with the previous approach. The evaluation result showed the proposed algorithm supports an improved performance in efficiency of the inferrable SPARQL query processing without loss of completeness and soundness.

• Science of Emotion and Sensibility
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• v.12 no.2
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• pp.215-224
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• 2009

This research extracted emotional words for measuring user's emotions expressed while using a cellular phone and a web. And then the emotional words were compared to find out whether the difference in emotional words by the type of products. The results of this study suggest that the hardware-oriented products used for specific purpose such as cellular phone extracted a lot of emotional words related to 'Satisfaction in Usability' and 'Pleasure'. 'Satisfaction in Usability' are conceived satisfying in usability or practicality of product. 'Pleasure' are pleasant emotions expressed while using a product. However the emotional words related to 'Aesthetics' and 'Novelty' were omitted. 'Aesthetics' are expressed by product's appearance and by various visual information while using a product. 'Novelty' are expressed by something that is novel and new that has never been experienced. On the other hand the software-oriented products used rather to find something better and new information than to perform specific tasks such as web extracted a lot of emotional words related to 'Novelty'. Therefore, the results of this research have found evidence that it is desirable to make a set of subjective evaluation scale by the type of products. When making the subjective evaluation scale, it is important to use appropriate emotional words for the purpose of use and the characteristics of those products.