• Archives of design research
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• v.20 no.2 s.70
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• pp.65-76
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• 2007

The primary purpose of this study was to evolve integrated design process for Experiential Design which is based on the former study, 'The Influence of Cognitive Factors on the Creative Abilities in Design'. Experience is a transformation factor to all of the design processes, which has three phase of problem solving; Input, Process, and Output. We regard Experiential Design is a transforming process from concept to experience, and set up a mode) of Holistic Design Process (HDP), which consists of four domains: Four Causes, Thinking Modes, Sensory Modalities, and Creative Abilities. Revolving Sensory Modalities (SM), Creative Abilities (CA), and Thinking Modes (TM) around Product Design Specification (PDS) through a design process, Design Concepts ripen and mature into Externalization. Each component of Experiential Design (TM, SM, and CA) turns around the PDS. Here, experience is first perceived by the five senses. Then, the knowledge is formed, and the CA works for a problem solving. And TM controls all of these procedures. We regard these are a phenomenon of Experiential Design. The HDP can be helpful to develop valuable solutions and create a good experience.

• Youth Facilities and Environment
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• v.9 no.4
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• pp.49-55
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• 2011

The purpose of this study is to investigate and analysis importance for evaluation indicators in youth centers. The sample of it is 138 youth centers. Method of this analysis of importance for its indicators is AHP(Analytic Hierarchy Process). Evaluation domains in youth center are process evaluation, product evaluation, input evaluation and specialized program in order of importance. Also, it is important to evaluate in needs assessment, recruitment of youth instructor, participation of youth in decision making, connective project with schools, sanitation level of youth center, satisfaction research, efforts of improvement of youth center staff in evaluation indicators. The result of this study is that importance for evaluation indicators suggests developmental directivity in youth center management.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.232-235
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• 2015

Defect data contains experiential knowledge about specific work conditions. And the number of projects performed by a company is too limited for an individual to experience the various defects under the current complex construction environment. Therefore, in order to manage and prevent a reoccurrence of defects, a proper data feedback mechanism is required. However, most defect data are stored in unstructured ways, resulting in the fundamental problem of data utilization. In this paper, a new framework is proposed by using linked data technologies to improve defect data utilization. The target of this framework is to convert defect data to the ontology-based linked data format for sharing defect data from different data sources. To demonstrate it, some technical solutions are implemented by using real cases. The proposed approach can reduce data search time and improve the accuracy of search results as well. Moreover, the proposed approach can be applied to other domains that need to refer to external sources such as safety, specification, product, and regulation.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.915-922
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• 2006

Recently, the requirements of the embedded software are getting diverse as the diversity of embedded software application fields increases. The systematic development methods are issued to deal with the dependency between hardware and software. However, the existing development methods have not considered the software's close connection to hardware and the high-level reusability for common requirements of several similar domains. In this paper, we propose a design method of development process model of product lines to support an efficient development method for embedded software. For this, we firstly suggest a domain scoping method and an IDEF0(Integration DEFinition)-based business model for extracting the efficient requirements. Next, we present a component deriving method based on the service architecture and an architecture design method after considering the hardware dependency. And we explain the artifacts of MSDFS(Multi Sensor Data Fusion System) at each design step in order to show how the proposed model can be applied to the embedded software development.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.195-203
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• 2021

Recently, big data, a major technology in the IT field, has been expanding into various industrial sectors and research on how to utilize it is actively underway. In most Internet industries, user reviews help users make decisions about purchasing products. However, the process of screening positive, negative and helpful reviews from vast product reviews requires a lot of time in determining product purchases. Therefore, this paper designs and implements a system that analyzes and aggregates keywords using LDA, a big data analysis technology, to provide meaningful information to users. For the extraction of document topics, in this study, the domestic book industry is crawling data into domains, and big data analysis is conducted. This helps buyers by providing comprehensive information on products based on user review topics and appraisal words, and furthermore, the product's outlook can be identified through the review status analysis.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.115-122
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• 2019

In the online marketplace, consumers are exposed to various products and freely express opinions. As consumer product reviews have a important effect on the success of online markets and other consumers, online market needs to accurately analyze the consumers' emotions about their products. Text mining, which is one of the data analysis techniques, can analyze the consumer's reviews on the products and efficiently manage the products. Previous studies have analyzed specific domains and less than 20,000 data, despite the different accuracy of the analysis results depending on the data domain and size. Further, there are few studies on additional factors that can improve the accuracy of analysis. This study analyzed 72,530 review data of food product domain that was not mainly covered in previous studies by using ensemble technique. We also examined the influence of summary review on improving accuracy of analysis. As a result of the study, this study found that Boosting ensemble technique has the highest accuracy of analysis. In addition, the summary review contributed to improving accuracy of the analysis.

• Bulletin of the Korean Chemical Society
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• v.26 no.11
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• pp.1653-1668
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• 2005

Assembly of hybrid mesophases through the combination of amphiphilic block copolymers, acting as structuredirecting agents, and silicon sources using low acid catalyst concentration regimes is a versatile strategy to produce large quantities of high-quality ordered large-pore mesoporous silicas in a very reproducible manner. Controlling structural and textural properties is proven to be straightforward at low HCl concentrations with the adjustment of synthesis gel composition and the option of adding co-structure-directing molecules. In this account, we illustrate how various types of large-pore mesoporous silica can easily be prepared in high phase purity with tailored pore dimensions and tailored level of framework interconnectivity. Silica mesophases with two-dimensional hexagonal (p6mm) and three-dimensional cubi (Fm$\overline{3}$m, Im$\overline{3}$m and Ia$\overline{3}$d) symmetries are generated in aqueous solution by employing HCl concentrations in the range of 0.1−0.5 M and polyalkylene oxide-based triblock copolymers such as Pluronic P123 $(EO_{20}-PO_{70}-EO_{20})$ and Pluronic F127 $(EO_{106}-PO_{70}-EO_{106})$. Characterizations by powder X-ray diffraction, nitrogen physisorption, and transmission electron microscopy show that the mesoporous materials all possess high specific surface areas, high pore volumes and readily tunable pore diameters in narrow distribution of sizes ranging from 4 to 12 nm. Furthermore, we discuss our recent advances achieved in order to extend widely the phase domains in which single mesostructures are formed. Emphasis is put on the first synthetic product phase diagrams obtained in $SiO_2$-triblock copolymer-BuOH-$H_2O$ systems, with tuning amounts of butanol and silica source correspondingly. It is expected that the extended phase domains will allow designed synthesis of mesoporous silicas with targeted characteristics, offering vast prospects for future applications.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2001.11a
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• pp.102-102
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• 2001

Taurine (2-ethaneaminosulfonic acid) is one of the major intracellular ${\beta}$ -amino acids in mammals and is required for a number of biological processes including membrane stabilization, osmoregulation, antioxidation, detoxification, modulation of calcium flux and neurornodulation. The taurine transporter (TAUT) which contains 12 hydrophobic membrane-spanning domains has been cloned from dog kidney, rat brain, mouse brain, human thyroid, placenta and retina. In this study, The TAUT cDNA from the human intestinal epithelial cell, HT-29 was cloned and sequenced. Reverse-transcription polymerase chain reaction (RT-PCR) was performed to amplify partial cDNA encoding human intestinal TAUT. The coding region of the PCR product was 732 bp long. The primers were designed to encode highly conserved amino acid sequences near the transmembrane domains III (IPYFIFLF) and Ⅵ (KYKYNSYR) both in human and mouse. The TAUT cDNA amplified was ligated into the pGEX 4T-1 expression vector. The resulting sequence of human intestinal TAUT cDNA (Accession number of NCBI Genebank is AF346763) was identical to the sequences of the TAUTs previously determined in the human placenta and retina except 3 base pairs from that of the reported human thyroid. TAUT specific antibodies were generated to use them as biological tools in the studies of the biological role of TAUT. Peptides of 149-162 amino acid residue (14 amino acids) of the TAUT were synthesized. The synthetic peptide used in this study was LFQSFQKELPWAHC. This region was chosen not only to avoid putative glycosylation sites but also to exclude regions of known homology with GABA transporters in the extracellular hydrophilic domains. The synthetic peptide, TAUT-1 was conjugated with carrier protein, kehole lympet hemocyanin (KLH) to use as an antigen. When used for immunization on a rabbit to produce polyclonal antiserum, the conjugates elicited high -titered specific anti-TAUT-1 antibodies, which reacted well with the ovalbumin (OVA) conjugated peptides in ELISA. The KLH-conjugated peptide was also used as immunizing antigen in BALB/c mice to produce TAUT specific monoclonal antibodies. From the culture supernatant of the hybridoma, the specificity of anti-TAUT-1 monoclonal antibodies was confirmed by ELISA. Further applications of more tools in TAUT expression analysis will be performed such as western blotting and flow cytometry.

• Journal of Science Education
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• v.43 no.3
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• pp.363-381
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• 2019

This study aims to suggest an inclusive conceptual framework for the Nature of Technology (NOT) by examining literature and researches regarding NOT and then to analyze the conceptions of the students in Science and Engineering Department of a college based on the NOT framework. Findings are as follows: First, the conceptual framework of the NOT developed from the study has the five domains of NOT, which are Technology as Artifacts, Technology as Knowledge, Technology as Practice, Technology as History, and Technology as a part of Society. Second, the participants' conceptions of the NOT emphasize on three domains of the Technology as Practice (26.4%), Technology as a part of Society (25.8%), and Technology as Knowledge (24.3%) among the five domains of the NOT. Third, according to the microanalysis of the students' conceptions regarding NOT, students in Science and Engineering Department of a college possess concrete and various views of the NOT even though NOT is abstract and complex ideas. Specifically, they seem to recognize the NOT as a product of process and ability to utilize the technology for convenience of life.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.