• Title/Summary/Keyword: cognitive and language development

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The Clinical Utility of Korean Bayley Scales of Infant and Toddler Development-III - Focusing on using of the US norm - (베일리영유아발달검사 제3판(Bayley-III)의 미국 규준 적용의 문제: 미숙아 집단을 대상으로)

  • Lim, Yoo Jin;Bang, Hee Jeong;Lee, Soonhang
    • Korean journal of psychology:General
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    • v.36 no.1
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    • pp.81-107
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    • 2017
  • The study aims to investigate the clinical utility of Bayley-III using US norm in Korea. A total of 98 preterm infants and 93 term infants were assessed with the K-Bayley-III. The performance pattern of preterm infants was analyzed with mixed design ANOVA which examined the differences of scaled scores and composite scores of Bayley-III between full term- and preterm- infant group and within preterm infants group. Then, We have investigated agreement between classifications of delay made using the BSID-II and Bayley-III. In addition, ROC plots were constructed to identify a Bayley-III cut-off score with optimum diagnostic utility in this sample. The results were as follows. (1) Preterm infants have significantly lower function levels in areas of 5 scaled scores and 3 developmental indexes compared with infants born at term. Significant differences among scores within preterm infant group were also found. (2) Bayley-III had the higher scores of the Mental Development Index and Psychomotor Developmental Index comparing to the scores of K-BSID-II, and had the lower rates of developmental delay. (3) All scales of Bayley-III, Cognitive, Language and Motor scale had the appropriate level of discrimination, but the cut-off composite scores of Bayley-III were adjusted 13~28 points higher than 69 for prediction of delay, as defined by the K-BSID-II. It explains the lower rates of developmental delay using the standard of two standard deviation. This study has provided empirical data to inform that we must careful when interpreting the score for clinical applications, identified the discriminating power, and proposed more appropriate cut-off scores. In addition, discussion about the sampling for making the Korean norm of Bayley-III was provided. It is preferable that infants in Korea should use our own validated norms. The standardization process to get Korean normative data must be performed carefully.

Development of Beauty Experience Pattern Map Based on Consumer Emotions: Focusing on Cosmetics (소비자 감성 기반 뷰티 경험 패턴 맵 개발: 화장품을 중심으로)

  • Seo, Bong-Goon;Kim, Keon-Woo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.179-196
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    • 2019
  • Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

Knowledge Extraction Methodology and Framework from Wikipedia Articles for Construction of Knowledge-Base (지식베이스 구축을 위한 한국어 위키피디아의 학습 기반 지식추출 방법론 및 플랫폼 연구)

  • Kim, JaeHun;Lee, Myungjin
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.43-61
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    • 2019
  • Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

A Study on Women's Casino Security Employees (여성 카지노 시큐리티 종사원에 관한 연구)

  • Kim, Hyeong-seok
    • Korean Security Journal
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    • no.62
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    • pp.135-158
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    • 2020
  • In casinos, security personnel who manage the safety of customers and employees play a very important role. In particular, there is a high percentage of female employees in casinos, and because the ratio of female and male employees is similar, the probability of female customers or female employees experiencing accidents may be similar to or higher than that of males. Women's security agents who handle women's case accidents can provide female customers and employees with a security service that only women can do. However, most of the agents doing security work at casinos are male, and the proportion of women is very low. Therefore, this research is about employees who are currently working as women in casinos and conducted qualitative research to find out about various experiences they experienced while working in the casino. A total of five study participants were interviewed three times to analyze and categorize the data collected. The first question is the professor's recommendation, his personal information search and his acquaintance's recommendation. The second question, the factors behind the necessary skills at work, are various athletic skills, good physical conditions and foreign language skills. In the third question, the satisfaction factors of the task are the scarcity value of the work, the satisfaction of the pay, the suitability of the individual and the expectation of the future, and the unsatisfactory factors of the work are the risk of the work, the stress on the customer, the discrimination against the sex, the gaze around, the tiredness of the shift work. In the fourth question, factors on the need for female casino security agents are providing differentiated services to female customers, protecting female employees and providing opportunities for women in related majors. The results of this study were interviewed by an expert of more than 20 years in the casino security business, and female casino security agents said that since it is a necessary requirement, they should seek a direction for development through institutional and cognitive improvement.

Risk Factors for Hearing Loss in Very Low Birth Weight Infants: Results of Hearing Test in Infants <1,500 g (극소 저체중 출생아에서 청력 손상에 영향을 미치는 요인: 1,500 g미만의 청력 검사 결과)

  • Sung, Min-Jung;Han, Young-Mi;Park, Kyung-Hee;Lee, Il-Woo;Byun, Shin-Yun
    • Neonatal Medicine
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    • v.18 no.2
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    • pp.328-336
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    • 2011
  • Purpose: An association between very low birth weight infants(VLBWI) and hearing loss has long been recognized. Early identification and intervention for hearing loss benefits language and speech/cognitive development. We investigated the risk factors and clinical outcomes of hearing loss among VLBWI. Methods: We analyzed the results of auditory brainstem response (ABR) testing of VLBWI. These infants were admitted to the neonatal intensive care unit (NICU) of Pusan National University Yangsan Hospital between December 2008 and February 2011. A follow-up was conducted subsequently. Results: ABR evaluations were performed on 65 infants, and 31 showed abnormal results (47.7%). Among the 31 infants, 10 were classified with moderate/severe/profound hearing loss (15.4%). The infants with abnormal ABR had a higher incidence of low birth weight, prolonged ventilator care, cumulative dose of furosemide, and the lowest $PaO_2$ (P<0.05). Those with moderate/severe/profound hearing loss had a higher incidence of low Apgar scores at 5 minutes (odds ratio[OR],0.34; 95% confidence interval[CI],0.13-0.89), prolonged ventilator care (OR,1.06; 95% CI,1.01-1.12), and mild hearing loss compared to those without profound hearing loss. Follow-up evaluations on eight infants with ABR reveled improvements 5.6${\pm}$3.9 months later. One infant, who had profound hearing loss in both ears, used a hearing aid. Conclusion: Factors influencing hearing loss at the first VLBWI hearing screening test included lower Apgar scores at 5 min and prolonged use of a ventilator. Most VLBWI with hearing losses were expected to recover after several months of follow-up.

Analysis of newborn hearing screening using automated auditory brainstem response (자동화 청성뇌간반응을 이용한 신생아 청력선별검사 결과 분석)

  • Park, Sung Won;Yun, Byung Ho;Kim, Kyung Ah;Ko, Sun Young;Lee, Yeon Kyung;Shin, Son Moon;Hong, Sung Hwa
    • Clinical and Experimental Pediatrics
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    • v.49 no.10
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    • pp.1056-1060
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    • 2006
  • Purpose : As hearing ability affects language and cognitive development, early detection and intervention of congenital hearing defects is very important. We analyzed the result of newborn hearing screening using automated auditory brainstem response and estimated the incidence of congenital hearing defects in newborn infants in Korea. Methods : Hearing screening tests were done on 7,218 newborn infants who were delivered at Cheil General Hospital from July 1, 2004 to June 30, 2005. The first screening test was done on the second day of life with automated auditory brainstem response(AABR) using $ALGO{\bigcirc}^{(3)}$ Newborn hearing screener($Natus^{(R)}$ Medical Incorporated, San Carlos, USA) with 35 dB sound level. The newborn infants who did not pass the initial screening test took the second screening AABR test before discharge from the nursery. Infants who did not pass these screenings at the nursery were followed up at the Department of Otorhinolaryngology, Samsung Seoul Hospital. Results : Total 7,218 infants(83.3 percent of total 8,664 live births of the Cheil General Hospital) were screened in the nursery, and 55 of them failed to pass the newborn screening. Among 55 infants who were referred, six were lost during follow-up, and 14 were confirmed as hearing impaired. Six of them(42.8 percent) do not have any risk factors for hearing impairment. We can estimate that the incidence of hearing defects is about 1.9-2.8 per 1,000 live births. Conclusion : Automated auditory brainstem response is an effective tool to screen the hearing of newborn infants. Congenital hearing loss is more frequent than metabolic diseases on which screening tests are available in the newborn period. About 40 percent of infants who have hearing defects do not have any risk factors for hearing impairment. Therefore, universal newborn hearing screening must be recommended to all neonates.