• Title/Summary/Keyword: Effective Uses

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Changes in Properties of Deer Antler by Proteolysis and Extraction Conditions (녹용의 단백질가수분해 및 추출조건에 따른 특성 변화)

  • Kim, Jae-Hwa;Yoo, Cheol-Jae;Sin, Kyung-A;Jang, Se-Young;Park, Nan-Young;Jeong, Yong-Jin
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.40 no.1
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    • pp.89-93
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    • 2011
  • This study was conducted to investigate the proteolysis and extraction conditions of deer antler for application of food materials. ProteAX (A) was the most effective enzyme for proteolysis of deer antler and the proteolysis condition was 0.5% (w/w) for enzyme concentration and 5 hr for proteolysis time. The effect of mixing enzyme ProteAX (A)+KFEN 2 (C) treatment in $60^{\circ}C$, 5 hr was investigated; soluble solid and protein content were the highest with A 0.5% (w/w) and B 0.5% (w/w) concentration. Result for DAH (deer antler hydrolysate) and DA (deer antler) prepared with extraction in $95^{\circ}C$ atmospheric pressure (AP, 6~18 hr) and extraction under $120^{\circ}C$ pressure condition (UP, 15~60 min) after hydrolysis on preceding established condition descriptions indicated that difference in pH according to enzyme treatment and extraction conditions was not significant. Sugar content of DA was $1.5^{\circ}Brix$, DA-UP (under pressure) and DAH-AP (atmospheric pressure) were $2.2^{\circ}Brix$; the highest sugar content of $2.7^{\circ}Brix$ was observed in DAH-UP for 60 min extraction. Also total free sugar, crude protein and collagen content were the highest in DAH-UP for 60 min recording at 1.97%, 742.7 mg/100 g and 498.8 mg/100 g, respectively. From these results, deer antler hydrolysate prepared with extraction under pressure was the most effective for functional characteristics enhancement. Hereafter, various practical uses of materials with enhanced characteristics of antler is expected.

Nuclear Terrorism and Global Initiative to Combat Nuclear Terrorism(GICNT): Threats, Responses and Implications for Korea (핵테러리즘과 세계핵테러방지구상(GICNT): 위협, 대응 및 한국에 대한 함의)

  • Yoon, Tae-Young
    • Korean Security Journal
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    • no.26
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    • pp.29-58
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    • 2011
  • Since 11 September 2001, warnings of risk in the nexus of terrorism and nuclear weapons and materials which poses one of the gravest threats to the international community have continued. The purpose of this study is to analyze the aim, principles, characteristics, activities, impediments to progress and developmental recommendation of the Global Initiative to Combat Nuclear Terrorism(GICNT). In addition, it suggests implications of the GICNT for the ROK policy. International community will need a comprehensive strategy with four key elements to accomplish the GICNT: (1) securing and reducing nuclear stockpiles around the world, (2) countering terrorist nuclear plots, (3) preventing and deterring state transfers of nuclear weapons or materials to terrorists, (4) interdicting nuclear smuggling. Moreover, other steps should be taken to build the needed sense of urgency, including: (1) analysis and assessment through joint threat briefing for real nuclear threat possibility, (2) nuclear terrorism exercises, (3) fast-paced nuclear security reviews, (4) realistic testing of nuclear security performance to defeat insider or outsider threats, (5) preparing shared database of threats and incidents. As for the ROK, main concerns are transfer of North Korea's nuclear weapons, materials and technology to international terror groups and attacks on nuclear facilities and uses of nuclear devices. As the 5th nuclear country, the ROK has strengthened systems of physical protection and nuclear counterterrorism based on the international conventions. In order to comprehensive and effective prevention of nuclear terrorism, the ROK has to strengthen nuclear detection instruments and mobile radiation monitoring system in airports, ports, road networks, and national critical infrastructures. Furthermore, it has to draw up effective crisis management manual and prepare nuclear counterterrorism exercises and operational postures. The fundamental key to the prevention, detection and response to nuclear terrorism which leads to catastrophic impacts is to establish not only domestic law, institution and systems, but also strengthen international cooperation.

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Studies on Preventive Methods Against Concrete Corrosion by Sea Water (ll) (조수에 의한 콘크리트 침식방지법에 관한 연구(ll))

  • 고재군
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.15 no.2
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    • pp.3018-3030
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    • 1973
  • This study was carried out to investigate the effects of various mix designs of concrete on the compressive strengths and corrosive rates when the concretes were immersed in sea water of the West Sea, as the part of study related to durated to durability of concrete by action of the sea water. Concrete mix designs used in this study were ordinary Concrete mix, Concrete mixes with different admixtures such as fly ash, pozzolith and vinsol resin, and pozzolan concrete mix. The concrete specimens were made and cured for 7 days and 28 days in the fresh water in accordance with the Korean Standard specification for concrete. Compressive strengths of the specimens were measured after immersing the specimens for one year in fresh water and sea water which were placed indoors. The sea water used in this test was taken from the Bay of Ahsan. Corrosive rate was also tested after immersing the specimens in the same sea water and placed indoors for one year. The results obtained from the tests are summarized as follows; 1. Compressive strength of an ordinary concrete was the lowest of the various mix desings of concrete immersed both in the fresh water and the sea water. Therefore, the uses of pozzolan cement, fly ash, pozoolith and vinsol resin in mix design of concrete had and effect on increasing compressive strength. 2. Pozzolan concrete was the most effective on compressive strength in the fresh water, but it had less effect than concrete with fly ash admixture immersed in the sea water. 3. The use of fly ash admixture in mix design of concrete showed higher strength as the immersing age is longer both in fresh water and sea water than the other concretes besides pozzolan concrete, but the concretewith fly ash admixture had lower strength than pozzolan concrete in the sea water. Therefore, concrete with fly ash admixture might be better than the pozzolan concrete as far as durability of concrete to sea water was concerned. 4. The use of pozzolith admixture in mix design of concrete had less compressive strength than the use of pozzolan cement for fly ash admixture both in fresh water and sea water. However, the concrete with pozzolith admixture was much stronger than one with vinsol resin admixture in fresh water, but somewhat stronger in the sea water. 5. Though the use of vinsol resin admixture was more effective than ordinary concrete on compressive strength both in fresh water and sea water, it was the least compressive strength among the other concretes. 6. Relation between compressive strengths and absorption rates of every kind of concrete besides concrete with fly ash admixture showed a linear regression line and the compressive strength is highee as the absorption rate is lower. Concrete with fly ash admixture had extremely high strength in comparison with corresponding adsorption rates of the other concretes. 7. Corrosive appearance on the surface of concretes was not occured significantly when exposed to the sea water for one year, However, the specimens of concretes besides ordinary concrete were a little heavier than those cured in fresh water for 28 days.

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Shear Strength and Erosion Resistance Characteristics of Stabilized Green Soils (토양안정재를 혼합한 녹생토의 전단강도 및 침식저항특성)

  • Oh, Sewook;Jeon, Jinchul;Kim, Donggeun;Lee, Heonho;Kwon, Youngcheul
    • Journal of the Korean GEO-environmental Society
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    • v.16 no.12
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    • pp.45-52
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    • 2015
  • With the rising interest in the environment, more attention on ecological restoration for damaged slope surface to restore its original state has been drawn. Generally, the most useful method is vegetation based spray work. This method uses green soil including sewage sludge, sawdust, paper sludge, and weathered granite soil. However, because there are neither accurate information nor test values about green soil, green soil is often lost by environmental factors such as rainfalls and strong winds. To solve the problem of green soil, it is necessary to prepare design standards about green soil, and conduct studies to deal with green soil loss in consideration of various variables including basic material property, soil quality of slope surface, and weather. This study was conducted in the mixture of green soil and eco-friendly soil stabilizer. With green soil, basic material property test and compaction test were conducted for the analysis on the basic characteristics of green soil. In the mixture with soil stabilizer at a certain ratio, we conducted shear strength test depending on the ratio in order to analyze the maximum shear strength, cohesion and the change in internal friction angles. Furthermore, in the mixture ratio of green soil and soil stabilizer, which is the same as the ratio in the shear strength test, an inclination of slope surface was made in laboratory for the analysis on erosion and germination rate. Finally, this study evaluated the most effective and economic mixing ratio of soil stabilizer to cope with neighboring environmental factors. According to the test, the shear strength of green soil increased up to 51% rely onto the mixing ratio of and a curing period, and its cohesion and internal friction angle also gradually increases. It is judged that the mixture of soil stabilizer was effective in improving shear strength and thereby increased the stability of green soil.

A New Item Recommendation Procedure Using Preference Boundary

  • Kim, Hyea-Kyeong;Jang, Moon-Kyoung;Kim, Jae-Kyeong;Cho, Yoon-Ho
    • Asia pacific journal of information systems
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    • v.20 no.1
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    • pp.81-99
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    • 2010
  • Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

Effects of Storage Condition, Storage Period, and Priming on Seed Germination of Corylopsis coreana (저장방법 및 priming 처리가 히어리 종자 발아에 미치는 영향)

  • Kim, Hyoung Deug;Kim, Hong Lim;Kwack, Yong Bum;Choi, Young Hah;Lee, A Rong
    • FLOWER RESEARCH JOURNAL
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    • v.18 no.4
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    • pp.266-270
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    • 2010
  • Corylopsis coreana is an endangered Korean native plants. This is one of the genus that have high ornamental value for flowering plants available for garden shrub, bonsai, and pot plants. In this study, the methods to encourage seed germination rate were investigated for its ornamental uses. The germination rate of Corylopsis coreana seeds stored under dry-cold condition was very low, 12%, 12%, 8%, and 10%after 40, 70, 85, and 100 days storage respectively. But the germination rate of Corylopsis coreana seeds stored under wet-cold condition was higher than these, 20%, 54%, 78%, and 96% after 40, 70, 85, and 100 days storage respectively. Dry seeds sowed directly without $GA_3$ treatment showed no germination regardless of storage type(cold or room temp.) or storage periods. On the other hand, the soaking treatment with $GA_3$ 50~500 ppm for 24 hours was very effective to increase the germination rate. The most effective $GA_3$ levels was different by storage type(cold or room temp.) and storage periods. But the effect of $GA_3$ was decreased by prolonging of the storage period. Soaking treatment with $Ca(NO_3)_2$ 5, 10, 20 mM, $KNO_3$ 5, 10, 20 mM for 24 hours showed no effect.

Predicting the Effects of Agriculture Non-point Sources Best Management Practices (BMPs) on the Stream Water Quality using HSPF (HSPF를 이용한 농업비점오염원 최적관리방안에 따른 수질개선효과 예측)

  • Kyoung-Seok Lee;Dong Hoon Lee;Youngmi Ahn;Joo-Hyon Kang
    • Journal of Wetlands Research
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    • v.25 no.2
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    • pp.99-110
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    • 2023
  • Non-point source (NP) pollutants in an agricultural landuse are discharged from a large area compared to those in other land uses, and thus effective source control measures are needed. To develop appropriate control measures, it is necessary to quantify discharge load of each source and evaluate the degree of water quality improvement by implementing different options of the control measures. This study used Hydrological Simulation Program-FORTRAN (HSPF) to quantify pollutant discharge loads from different sources and effects of different control measures on water quality improvements, thereby supporting decision making in developing appropirate pollutant control strategies. The study area is the Gyeseong river watershed in Changnyeong county, Gyeongsangnam-do, with agricultural areas occupying the largest proportion (26.13%) of the total area except for the forest area. The main pollutant sources include chemical and liquid fertilizers for agricultural activities, and manure produced from small scale livestock facilities and applied to agriculture lands or stacked near the facilities. Source loads of chemical fertilizers, liquid fertilizers and livestock manure of small scale livestock facilities, and point sources such as municipal wastewater treatment plants (WWTPs), community WWTPs, private sewage treament plants were considered in the HSPF model setup. Especially, NITR and PHOS modules were used to simulate detailed fate and transport processes including vegitation uptake, nutrient deposition, adsorption/desorption, and loss by deep percolation. The HSPF model was calibrated and validated based on the observed data from 2015 to 2020 at the outlet of the watershed. The calibrated model showed reasonably good performance in simulating the flow and water quality. Five Pollutants control scenarios were established from three sectors: agriculture pollution management (drainge outlet control, and replacement of controlled release fertilizers), livestock pollution management (liquid fertilizer reduction, and 'manure management of small scale livestock facilities) and private STP management. Each pollutant control measure was further divided into short-term, mid-term, and long-term scenarios based on the potential achievement period. The simulation results showed that the most effective control measure is the replacement of controlled release fertilizers followed by the drainge outlet control and the manure management of small scale livestock facilities. Furthermore, the simulation showed that application of all the control measures in the entire watershed can decrease the annual TN and TP loads at the outlet by 40.6% and 41.1%, respectively, and the annual average concentrations of TN and TP at the outlet by 35.1% and 29.2%, respectively. This study supports decision makers in priotizing different pollutant control measures based on their predicted performance on the water quality improvements in an agriculturally dominated watershed.

Customer Behavior Prediction of Binary Classification Model Using Unstructured Information and Convolution Neural Network: The Case of Online Storefront (비정형 정보와 CNN 기법을 활용한 이진 분류 모델의 고객 행태 예측: 전자상거래 사례를 중심으로)

  • Kim, Seungsoo;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.221-241
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    • 2018
  • Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

Media Habits of Sensation Seekers (감지추구자적매체습관(感知追求者的媒体习惯))

  • Blakeney, Alisha;Findley, Casey;Self, Donald R.;Ingram, Rhea;Garrett, Tony
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.2
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    • pp.179-187
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    • 2010
  • Understanding consumers' preferences and use of media types is imperative for marketing and advertising managers, especially in today's fragmented market. A clear understanding assists managers in making more effective selections of appropriate media outlets, yet individuals' choices of type and use of media are based on a variety of characteristics. This paper examines one personality trait, sensation seeking, which has not appeared in the literature examining "new" media preferences and use. Sensation seeking is a personality trait defined as "the need for varied, novel, and complex sensations and experiences and the willingness to take physical and social risks for the sake of such experiences" (Zuckerman 1979). Six hypotheses were developed from a review of the literature. Particular attention was given to the Uses and Gratification theory (Katz 1959), which explains various reasons why people choose media types and their motivations for using the different types of media. Current theory suggests that High Sensation Seekers (HSS), due to their needs for novelty, arousal and unconventional content and imagery, would exhibit higher frequency of use of new media. Specifically, we hypothesize that HSS will use the internet more than broadcast (H1a) or print media (H1b) and more than low (LSS) (H2a) or medium sensation seekers (MSS) (H2b). In addition, HSS have been found to be more social and have higher numbers of friends therefore are expected to use social networking websites such as Facebook/MySpace (H3) and chat rooms (H4) more than LSS (a) and MSS (b). Sensation seekers can manifest into a range of behaviors including disinhibition,. It is expected that alternative social networks such as Facebook/MySpace (H5) and chat rooms (H6) will be used more often for those who have higher levels of disinhibition than low (a) or medium (b) levels. Data were collected using an online survey of participants in extreme sports. In order to reach this group, an improved version of a snowball sampling technique, chain-referral method, was used to select respondents for this study. This method was chosen as it is regarded as being effective to reach otherwise hidden population groups (Heckathorn, 1997). A final usable sample of 1108 respondents, which was mainly young (56.36% under 34), male (86.1%) and middle class (58.7% with household incomes over USD 50,000) was consistent with previous studies on sensation seeking. Sensation seeking was captured using an existing measure, the Brief Sensation Seeking Scale (Hoyle et al., 2002). Media usage was captured by measuring the self reported usage of various media types. Results did not support H1a and b. HSS did not show higher levels of usage of alternative media such as the internet showing in fact lower mean levels of usage than all the other types of media. The highest media type used by HSS was print media, suggesting that there is a revolt against the mainstream. Results support H2a and b that HSS are more frequent users of the internet than LSS or MSS. Further analysis revealed that there are significant differences in the use of print media between HSS and LSS, suggesting that HSS may seek out more specialized print publications in their respective extreme sport activity. Hypothesis 3a and b showed that HSS use Facebook/MySpace more frequently than either LSS or MSS. There were no significant differences in the use of chat rooms between LSS and HSS, so as a consequence no support for H4a, although significant for MSS H4b. Respondents with varying levels of disinhibition were expected to have different levels of use of Facebook/MySpace and chat-rooms. There was support for the higher levels of use of Facebook/MySpace for those with high levels of disinhibition than low or medium levels, supporting H5a and b. Similarly there was support for H6b, Those with high levels of disinhibition use chat-rooms significantly more than those with medium levels but not for low levels (H6a). The findings are counterintuitive and give some interesting insights for managers. First, although HSS use online media more frequently than LSS or MSS, this groups use of online media is less than either print or broadcast media. The advertising executive should not place too much emphasis on online media for this important market segment. Second, social media, such as facebook/Myspace and chatrooms should be examined by managers as potential ways to reach this group. Finally, there is some implication for public policy by the higher levels of use of social media by those who are disinhibited. These individuals are more inclined to engage in more socially risky behavior which may have some dire implications, e.g. by internet predators or future employers. There is a limitation in the study in that only those who engage in extreme sports are included. This is by nature a HSS activity. A broader population is therefore needed to test if these results hold.

Analyzing the User Intention of Booth Recommender System in Smart Exhibition Environment (스마트 전시환경에서 부스 추천시스템의 사용자 의도에 관한 조사연구)

  • Choi, Jae Ho;Xiang, Jun-Yong;Moon, Hyun Sil;Choi, Il Young;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.153-169
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    • 2012
  • Exhibitions have played a key role of effective marketing activity which directly informs services and products to current and potential customers. Through participating in exhibitions, exhibitors have got the opportunity to make face-to-face contact so that they can secure the market share and improve their corporate images. According to this economic importance of exhibitions, show organizers try to adopt a new IT technology for improving their performance, and researchers have also studied services which can improve the satisfaction of visitors through analyzing visit patterns of visitors. Especially, as smart technologies make them monitor activities of visitors in real-time, they have considered booth recommender systems which infer preference of visitors and recommender proper service to them like on-line environment. However, while there are many studies which can improve their performance in the side of new technological development, they have not considered the choice factor of visitors for booth recommender systems. That is, studies for factors which can influence the development direction and effective diffusion of these systems are insufficient. Most of prior studies for the acceptance of new technologies and the continuous intention of use have adopted Technology Acceptance Model (TAM) and Extended Technology Acceptance Model (ETAM). Booth recommender systems may not be new technology because they are similar with commercial recommender systems such as book recommender systems, in the smart exhibition environment, they can be considered new technology. However, for considering the smart exhibition environment beyond TAM, measurements for the intention of reuse should focus on how booth recommender systems can provide correct information to visitors. In this study, through literature reviews, we draw factors which can influence the satisfaction and reuse intention of visitors for booth recommender systems, and design a model to forecast adaptation of visitors for booth recommendation in the exhibition environment. For these purposes, we conduct a survey for visitors who attended DMC Culture Open in November 2011 and experienced booth recommender systems using own smart phone, and examine hypothesis by regression analysis. As a result, factors which can influence the satisfaction of visitors for booth recommender systems are the effectiveness, perceived ease of use, argument quality, serendipity, and so on. Moreover, the satisfaction for booth recommender systems has a positive relationship with the development of reuse intention. For these results, we have some insights for booth recommender systems in the smart exhibition environment. First, this study gives shape to important factors which are considered when they establish strategies which induce visitors to consistently use booth recommender systems. Recently, although show organizers try to improve their performances using new IT technologies, their visitors have not felt the satisfaction from these efforts. At this point, this study can help them to provide services which can improve the satisfaction of visitors and make them last relationship with visitors. On the other hands, this study suggests that they managers along the using time of booth recommender systems. For example, in the early stage of the adoption, they should focus on the argument quality, perceived ease of use, and serendipity, so that improve the acceptance of booth recommender systems. After these stages, they should bridge the differences between expectation and perception for booth recommender systems, and lead continuous uses of visitors. However, this study has some limitations. We only use four factors which can influence the satisfaction of visitors. Therefore, we should development our model to consider important additional factors. And the exhibition in our experiments has small number of booths so that visitors may not need to booth recommender systems. In the future study, we will conduct experiments in the exhibition environment which has a larger scale.