• Archives of design research
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• v.17 no.3
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• pp.353-362
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• 2004

This research has been done to evaluate the interior environmental factors in Gyungro-dang to suggest the advanced recommendations for them. For this research, the essential interior elements influencing on elderly's behavior were examined with the developed checklist, the lighting and color conditions of main hall at 14 facilities in Seoul area were analysed, and 124 subjects staying at Gyungro-dang were participated in questionaire survey for color preferences. Results showed that 1.The average installation rate of 39 items in checklist was 59%, the mandatory items such as accessible dimension were considered, but several items related to mobility and safety were not properly installed. Therefore not only guiding handrail and floor block to destination but also elimination of obstacles should be reconsidered. 2.The average of illuminances was 289 Lux dose to standard 300 Lux, but lighting quality was too low to support the activities of elderly users. The lighting control devices, combined lighting sources, and suitable lighting techniques should be applied for those facilities. 3.Most facilities were predominantly in warm colors in hue, medium or high value, low saturation, and natural atmosphere with similarity harmony. The color applications in those facilities were not functional, but similar as color preferences for the elderly except overall atmosphere. It is recommendable to include contrast harmony with classic or romantic mood.

• Science of Emotion and Sensibility
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• v.24 no.3
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• pp.71-80
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• 2021

Previous studies using facial expressions have revealed valence and arousal as two core dimensions of affective space. However, it remains unknown if the two dimensional structure is consistent across ages. This study investigated affective dimensions using six facial expressions (angry, disgusted, fearful, happy, neutral, and sad) at three ages (young, middle-aged, and old). Several studies previously required participants to directly rate subjective similarity between facial expression pairs. In this study, we collected indirect measures by asking participants to decide if a pair of two stimuli conveyed the same emotions. Multidimensional scaling showed that "angry-disgusted" and "sad-disgusted" pairs are similar at all three ages. In addition, "angry-sad," "angry-neutral," "neutral-sad," and "disgusted-fearful" pairs were similar at old age. When two faces in a pair reflect the same emotion, "sad" was the most inaccurate in old age, suggesting that the ability to recognize "sad" decreases with old age. This study suggested that the general two-core dimension structure is robust across all age groups with the exception of specific emotions.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.1
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• pp.29-44
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• 1995

A model experiment on the pair midwater trawl net applicable to 800 PS class Korean pair bottom trawlers was carried out in the special-prepared experimental thank. the tank was prepared as a reverse trapezoid shape in its vertical section by digging out flat soil. The dimension of the tank showed the 9.6 W$\times$43.0 L(m) of the upper fringe and the 4.8 W$\times$38.0 L(m) of the bottom with 3.0m in depth. The depth of water was maintained 2.7m during experiment. The model net was prepared based on the Tauti's similarity law of fishing gear in 1/30 scale considering the dimension of the experimental tank. Mouth performance of the model net during towing were determined by the photographs taken in front of the net mouth with the combinations of towing velocity, warp length and distance between paired boats. The results obtained can be summarized as follows: 1. Vertical opening of the model nets A and B was varied in the range of 0.18~0.88 m and 0.21~0.78 m (which can be converted into 5.4~26.4m and 6.3~23.4 m in the full-scale net) respectively, and was varied predominantly by towing speed. Vertical opening (H which is appendixed m for the model net. f for the full-scale net. A and B for the types of the model net) can be expressed as the function of towing velocity$V_t$as in the model net $V_t$ : m/ sec)$H_{mA}$=1.67$e^{-1.65V_t}$ $H_{mB}$=1.15$e^{-1.13V_t}$, in the full-scale net ($V_t$ : k't) $H_{fA}$=50.27$e^-0.37V_t$ $H_{fB}$=34.46$e^{-0.26Vt}$. 2. Horizontal opening of the model nets An and b was varied in the range of 1.03~1.54m and 1.04~1.55 m (which can be converted into 30.9~46.2 m and 31.2~46.5m in the full-scale net) respectively, and was varied predominantly by distance between paired boats. Horizontal opening (W, appendixes are as same as the former) an be expressed as the function of distance between paired boats $D_b$as in the model net $W_{mA}$=0.69+0.09$D_b$ $W{mB}$=0.73+0.09$D_b$, in the full-scale net $W_{fA}$=20.81+0.09$D_b$ $W_{fB}$=22.11+0.09$D_b$ 3. Net opening area of the model net A and B was varied in the range of 0.28~1.04 $m^2$ and 0.33~0.94$m^2$(which can be converted into 252~936$m^2$ and 297~846$m^2$ in the full-scale net) respectively, and was varied predominantly by towing velocity. Net opening area ($S$, appendixes are as same as the former) van be expressed as the function of towing velocity$V_t$ as in the model net $v_t$ : m/sec) $S_{Ma}$=2.01$e^{-1.54V_T}$ $S_{mA}$=1.40$e^{-1.65V_t}$, in the full-scale net ($V_t$ : k't) $S_{fA}$=1.807$e^-0.35V_t$ $S_{fA}$=1.265$e^{-0.24V_t}$. 4. Filtering volume of the model nets A and B was varied in the range of 0.32~0.55 $m^3$ and 0.37~0.55$m^3$(which can be converted into 8.640~14.850 $m^3$ and 9.990~14.850$m3$in the full~scale net) respectively, and was predominantly varied by towing speed. filtering volume of the model net-A showed the maximum at the towing speed 0.69 m/sec(3 k't in the full-scale net), compared with that of the model net B showed at 0.92 m/sec(4 k't in the full-scale net).

• Progress in Medical Physics
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• v.26 no.1
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• pp.42-51
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• 2015

In proton therapy, verification of proton dose distribution is important to treat cancer precisely and to enhance patients' safety. To verify proton dose distribution, in a previous study, our team incorporated a vertically-aligned one-dimensional array detection system. We measured 2D prompt-gamma distribution moving the developed detection system in the longitudinal direction and verified similarity between 2D prompt-gamma distribution and 2D proton dose distribution. In the present, we have developed two-dimension prompt-gamma measurement system consisted of a 2D parallel-hole collimator, 2D array-type NaI(Tl) scintillators, and multi-anode PMT (MA-PMT) to measure 2D prompt-gamma distribution in real time. The developed measurement system was tested with $^{22}Na$ (0.511 and 1.275 MeV) and $^{137}Cs$ (0.662 MeV) gamma sources, and the energy resolutions of 0.511, 0.662 and 1.275 MeV were $10.9%{\pm}0.23p%$, $9.8%{\pm}0.18p%$ and $6.4%{\pm}0.24p%$, respectively. Further, the energy resolution of the high gamma energy (3.416 MeV) of double escape peak from Am-Be source was $11.4%{\pm}3.6p%$. To estimate the performance of the developed measurement system, we measured 2D prompt-gamma distribution generated by PMMA phantom irradiated with 45 MeV proton beam of 0.5 nA. As a result of comparing a EBT film result, 2D prompt-gamma distribution measured for $9{\times}10^9$ protons is similar to 2D proton dose distribution. In addition, the 45 MeV estimated beam range by profile distribution of 2D prompt gamma distribution was $17.0{\pm}0.4mm$ and was intimately related with the proton beam range of 17.4 mm.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Distribution Research
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• v.16 no.4
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• pp.1-27
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• 2011

Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.155-174
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• 2022

From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (