• Title/Summary/Keyword: sequential association

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The Effects of the Type of Brand Extensions on Evaluations of Target Extension Product in Dissimilar Extensions: Focusing on the Moderating Role of Brand Concept and the Price of Target Extension Product (비유사 확장 시 브랜드확장 유형이 목표확장제품의 평가에 미치는 효과: 브랜드 컨셉과 목표확장제품 가격의 조절적 역할을 중심으로)

  • Jun, Sung-Youl;Huh, Jong-Ho;Jang, So-Hee
    • Asia Marketing Journal
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    • v.9 no.3
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    • pp.1-32
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    • 2007
  • In this study, we investigate the relative effectiveness of the two types of brand extensions (sequential extensions vs. direct extensions) in dissimilar extensions and examine the moderating role of two key variables - brand concept(functional brand vs. symbolic brand) and price of target extension product(low vs. high). The results from two experiments show that consumers evaluate the target extension product more favorably when brand is extended sequentially to dissimilar categories than when it is extended directly. However, the difference of target extension product evaluation between sequential extensions and direct extensions decrease when brand is symbolic and price of target extension product is high. Theoretical and managerial implications of the finding are discussed and inplications for future research are suggested.

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Effect of Adolescents' Perceived Parental Blame on Learned Helplessness: The Sequential Mediating Effects of Maladaptive Metacognitive Beliefs and Rumination (청소년이 지각한 부모의 비난이 학습된 무기력에 미치는 영향에서 역기능적 메타인지신념과 반추의 순차적 매개효과)

  • Jiyoon Kang;Min Ju Kang
    • Human Ecology Research
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    • v.62 no.1
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    • pp.101-120
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    • 2024
  • This study aimed to examine the effect of adolescents' perceived parental blame (criticism) on learned helplessness and to examine whether maladaptive metacognitive beliefs and rumination sequentially mediate the relationship between parental blame and learned helplessness. The participants were 316 adolescents (Mean age=16.7, SD=0.75; 137 male, 179 female) attending grades 1st and 2nd in high school in South Korea. The participants were selected using a snowball sampling method, while the data was collected via an online self-report questionnaire. This survey was completed by the participants and analyzed using SPSS 28.0, Amos 26.0 (IBM Co., Armonk, NY), and PROCESS macro version 4.2 (Model 6; Hayes, 2022). The main results are summarized as follows. Firstly, the adolescents' perceived paternal and maternal blame indicated significant direct effects on learned helplessness. Secondly, rumination mediated the effect of paternal and maternal blame on learned helplessness. Lastly, paternal and maternal blame significantly affected learned helplessness through the sequential mediating effects of maladaptive metacognitive beliefs and rumination. This study elucidates the causal structure among the various factors influencing learned helplessness in adolescents, focusing on parental blame, maladaptive metacognitive beliefs, and rumination. Furthermore, considering the verified sequential mediating effects of maladaptive metacognitive beliefs and rumination in the relationship between adolescents' perceived parental blame and learned helplessness, these findings suggest that modifying maladaptive metacognitive beliefs may help to reduce learned helplessness among adolescents who perceive high levels of parental blame.

A Study on the Hybrid Data Mining Mechanism Based on Association Rules and Fuzzy Neural Networks (연관규칙과 퍼지 인공신경망에 기반한 하이브리드 데이터마이닝 메커니즘에 관한 연구)

  • Kim Jin Sung
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.884-888
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    • 2003
  • In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

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A Topic Modeling-based Recommender System Considering Changes in User Preferences (고객 선호 변화를 고려한 토픽 모델링 기반 추천 시스템)

  • Kang, So Young;Kim, Jae Kyeong;Choi, Il Young;Kang, Chang Dong
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.43-56
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    • 2020
  • Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

The Concept and the Method of Conservation for the Traditional Korean Settlements - Based on the Case Study in Korea and China - (한국 전통마을의 보전 개념과 방법론 연구 - 한국.중국 전통마을의 사례연구를 바탕으로 -)

  • Lee, Ju-Ock;Han, Pil-Won
    • Journal of architectural history
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    • v.20 no.6
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    • pp.147-168
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    • 2011
  • The objective of this study is to establish the method of conservation for traditional Korean settlements, based on the field surveys on the representative traditional settlements in Korea and China. The method is approached from grasping the conservation mechanism in which non-physical aspects deeply influence physical ones. The study has analyzed the characteristics and problems in the current methods of conservation for the traditional settlements, through comparing conservation practices at the World Heritage-class settlements such as Yangdong, Hahoi, and Oeam villages in Korea and Xidi-cun, Hong-cun, and Dangjia-cun in China. As a consequence of the study, the conservation method for the traditional Korean settlements is established as follows; Firstly, the conservation targets are classified into 4 types in terms of the relations of elements; individual, correspondent, sequential, and network elements. Secondly, the conservation strategies include the structuralizations of targets, by means of sequencing and networking. Thirdly, the conservation programs are made in consideration of the sustenance, transformation, replacement, and extinction of traditional use patterns.

Heavy Metal Speciation in Soils from the janghang Smelter Area (장항 제련소 지역 토양의 중금속 오염에 대한 환경광물학적 연구)

  • 여상진;김수진
    • Journal of the Mineralogical Society of Korea
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    • v.10 no.2
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    • pp.139-147
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    • 1997
  • The Janghang smelter is the first lead, zinc and copper smelting facility in Korea which was operated for a half century from 1936 to 1989. The clay minerals and their heavy metal association in the soil profile around the smelter have been studied using XRD, EPMA, SEM-EDS, TEM, EPR and sequential extraction techniques. The soils in A horizon are highly acidic showing pH 4.45. The pH is going up with increasing depth. They have residual water contents of 1.18-1.51 wt%, loss on ignition of 6.32-7.79 wt%, and carbon contents of 0.08-0.88 wt%. Soils consist of quartz, feldspar, muscovite, kaolinite, vermiculite, biotite, chlorite, goethite and hematite in the decreasing abundance. The contents of clay minerals, especially vermiculite and chlorite, decrease with increasing depth. Sequential extraction experiments for the profile samples show that heavy metals (Zn, Cu, Pb, Cd) are highly concentrated in the A horizon of the soil profile as water-extractable (mostly amorphous), MgCl2-extractable (exchangeable in clay minerals), and organic phases. The heavy metal contents decrease with increasing depth. It suggests that the heavy metals are mainly associate with clay minerlas in an exchangeable state. It is also noted that heavy metals are highly concentrated in the manganese and iron oxide phases.

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Efficient continuous query processing technique based on selectivity for EPC data with time and location (시공간 EPC 데이터 처리를 위한 선택률 기반 효율적인 연속질의 처리 기법)

  • Chu, Byung-Jo;Hong, Bong-Hee;Kim, Gi-Hong
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.10a
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    • pp.100-105
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    • 2008
  • EPCglobal은 기업 간의 물류 활동 촉진과 글로벌 유통물류 시스템 구축을 위하여 EPCglobal Architecture Framework을 제시 하였다. EPCglobal Architecture Framework의 한 구성 요소인 EPCIS(Electronic Product Code Information Services)는 EPC, 시간, 위치와 같은 물류 관련 정보에 대해 저장 및 검색 서비스를 제공한다. EPCIS는 단발성 질의(poll)와 연속 질의(subscribe) 검색 서비스를 제공한다. EPCIS의 연속 질의는 시스템 자동화 및 재고 관리, 공급망 관리를 위해 다양한 응용에서 활용이 가능하다. 일반적으로 연속 질의 처리를 위해서는 등록된 연속 질의와 입력된 데이터를 순차적으로 비교하는 Sequential Matching 기법을 사용한다. Sequential Matching기법은 등록된 연속 질의 수가 증가 할 경우 많은 부하를 발생 시키고, 이로 인해 시스템 처리 지연이 발생한다. 본 논문에서는 EPCIS의 시공간 EPC 데이터의 연속질의 처리 성능 향상을 위해 선택률 기반 효율적인 연속질의 처리 기법을 제안한다. 13차원의 도메인을 여러 개의 질의 색인으로 구성하고, 등록된 질의 정보를 기반으로 선택률을 계산한다. 선택률에 의해 변경되는 동적 질의 실행 계획을 제안함으로써, EPCIS에서 시공간 EPC 데이터의 연속질의 처리에 대해 평균 60%의 성능이 향상이 가능하도록 하였다.

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A Sequential Analysis of Mother-Infant Interaction (연속적 분석법을 통한 어머니와 유아의 상호작용 연구)

  • Choae, Jin Kyong
    • Korean Journal of Child Studies
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    • v.6 no.1
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    • pp.3-16
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    • 1985
  • The purpose of this study was the application of sequential analysis to mother-infant interaction data, with particular reference to goodness of fit. The subjects of this study were 22 7- to 16-month-old infants(12 girls and 10 boys) and their mothers. Each mother-infant dyad was videotaped in a 5-min free-play session in the playroom. The videotaped data was transcribed on the behavioral checklist every 3 seconds. The recorded raw data were lagged by one time interval (3 sec.). Transitional probabilities from behavior at time t-1 to behavior at time t were gathered. The statistical analysis of frequency data and transitional probabilities consisted of Z test, t test, and sign test. It was found that regarding 1) direction of effect: the transitional probability of infant vocalization following maternal vocalization was significantly higher than the reverse; the transitional probability of a 'Coacting State' following a 'Mother Active State' was significantly higher than the reverse; the probability of a 'Mother Active State' following 'Quiescent State' was significantly higher than that of a 'Coacting State' following an 'Infant Active State'; 2) sex differences: male infants' transitional probability from an 'Infant Active State' to a 'Quiescent State' was significantly higher than that of female infants; 3) age differences: more than younger infants older infants had higher transitional probabilities from a 'Mother Active State' to a 'Coacting State', from a 'Parallel State' to a 'Coacting State', and from a 'Quiescent State' to a 'Parallel State'. These showed goodness of fit for sex and age differences, particularily for direction of effect.

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The Sequential Mediation Effects of Efficacy Belief about Play and Professional Recognition between Kindergarten Teacher's Emotional Intelligence and Teacher-child Interaction (유치원교사의 정서지능과 교사: 유아 상호작용 간의 관계에서 놀이교수효능감과 교직전문성 인식의 순차적 매개효과)

  • Chung, Mi Ra;Kim, Sei Kyung;Kim, Min Jeong
    • Korean Journal of Childcare and Education
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    • v.12 no.3
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    • pp.137-157
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    • 2016
  • This study examines the effects of teacher's emotional intelligence on teacher-child interaction through the sequential mediation effects of efficacy belief about play and professional recognition. Participants were 268 teachers working at kindergartens in Gyeonggi area. Data were analyzed by descriptive statistic, Pearson's product-moment correlation, and the structural equation model using the SPSS 21.0 and Mplus 6.12 program. The main findings of this study are as follows: First, in regards to the relationship between emotional intelligence and teacher-child interaction, a single mediation effect of efficacy belief about play is significant. But there is no significant mediation effect of the professional recognition. Second, in regards to the pathway from emotional intelligence to teacher-child interaction, the professional recognition precedent mediation model is statistically significant, but efficacy belief about the play precedent mediation model is not significant. Based on the results, a concluding discussion was made regarding methods toward enhancing interaction between teacher and child.

Angiotensin I-converting Enzyme Inhibitory Activities of Porcine Skeletal Muscle Proteins Following Enzyme Digestion

  • Katayama, K.;Fuchu, H.;Sakata, A.;Kawahara, S.;Yamauchi, K.;Kawamura, Y.;Muguruma, M.
    • Asian-Australasian Journal of Animal Sciences
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    • v.16 no.3
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    • pp.417-424
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    • 2003
  • Inhibitory activities against angiotensin I-converting enzyme (ACE) of enzymatic hydrolysates of porcine skeletal muscle proteins were investigated. Myosin B, myosin, actin, tropomyosin, troponin and water-soluble proteins extracted from pork loin were digested by eight kinds of proteases, including pepsin, $\alpha$-chymotrypsin, and trypsin. After digestion, hydrolysates produced from all proteins showed ACE inhibitory activities, and the peptic hydrolysate showed the strongest activity. In the case of myosin B, the molar concentration of peptic hydrolysate required to inhibit 50% of the activity increased gradually as digestion proceeded. The hydrolysates produced by sequential digestion with pepsin and $\alpha$-chymotrypsin, pepsin and trypsin or pepsin and pancreatin showed weaker activities than those by pepsin alone, suggesting that ACE inhibitory peptides from peptic digestion might lose their active sequences after digestion by the second protease. However, the hydrolysates produced by sequential digestion showed stronger activities than those by $\alpha$-chymotrypsin, trypsin or pancreatin alone. These results suggested that the hydrolysates of porcine meat were able to show ACE inhibitory activity, even if they were digested in vivo, and that pork might be a useful source of physiologically functional factors.