• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.27-33
• /
• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.1-7
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Human Ecology Research
• /
• v.61 no.3
• /
• pp.389-399
• /
• 2023

Sustainable fashion products have different characteristics from typical fashion products. Therefore, this study focuses on shoes while exploring the expansion and development of sustainable fashion consumption as well as consumers' perceptions of the sustainability approaches practiced by shoe companies. In-depth interviews were conducted with 24 consumers, who had purchased sustainable shoes, in order to understand their purchase decision-making process and consumption characteristics, using the seven stages of the EBM model. In the "need recognition" stage, the survey participants' social background and family influences were categorized as macro factors, while their personal background influences were categorized as micro factors. In the "evaluation of alternatives" stage, participants reconfirmed whether or not to make a purchase based on the product's properties, such as price, brand value, and offered services. In the "purchase" stage, participants' purchase channels were determined according to their preferences as well as the selection pattern they followed until the final purchase within the chosen channel. In the "consumption" stage, the start of product ownership coincides with the start of using the products after making a purchase. In the "post-purchase assessment" stage, higher positive experiences led to a higher repurchase intention of sustainable shoes, while negative experiences caused participants to defer consumption and made them experience a sense of guilt for failing to consume sustainably. During the "post-purchase behavior" stage, which focused on the categories that the customers prioritized, many participants spread information about sustainable fashion to specific individuals through active online WOM behavior.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.210-216
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Korean Journal of Clinical Pharmacy
• /
• v.33 no.1
• /
• pp.43-50
• /
• 2023

Background and Objective: With the advancement of cancer treatments and increased life expectancy, managing breakthrough cancer pain (BTcP) is essential to improve the quality of life for cancer patients. This study aimed to compare the major rapid onset opioids in Korea based on their characteristics and costs to determine the best option for each patient. Methods: Based on sales information from IQVIA-MIDAS, sublingual fentanyl tablet (SLF), fentanyl buccal tablet (FBT), and oral transmucosal fentanyl citrate (OTFC) were selected as the top three drugs for the treatment of BTcP in Korea, considering them the most comparable drugs. The cost and cost-pain relief ratio of the drugs for short-term (1 month) and long-term (1 year) treatment were compared and the ease of administration based on various factors, including pharmacokinetics, onset of action, and administration procedures were evaluated. Results: SLF was evaluated as the best overall in terms of rapid onset of action, ease of administration, and drug cost and also had the highest market share. SLF had the lowest cost pain relief ratio for both the initial and supplemental treatment for the 1-month pain intensity difference 15 (PID15) ratio. However, for the 1-month PID30 ratio, SLF was not superior to OTFC or FBT. The longer the breakthrough cancer pain duration, the more cost-effective the other rapid onset opioids. Conclusion: The rapid onset opioids that fit the patient's breakthrough cancer pain pattern have the best cost-effectiveness.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.717-726
• /
• 2023

This study collected basic data for the design of and research and development for golf wear with an eye toward various consumer needs such as design, activity, function, comfort, and durability as requirements for golf wear. 64 men and women in their 40s, 50s, and 60s were surveyed on the state of wearing golf wear and their satisfaction of the garments. As a result, it was confirmed that the quality of golf wear participants currently possessed did not sufficiently satisfy the research group consumers. Therefore, research and development of golf wear for these consumers should be advanced, while considering reasonable price, age-appropriate design, pattern development, and material selection with keeping in mind the intended activity level as well as comfort. It was thought that the development of functional golf wear would contribute to more comfortable golf activities.

• Korean Journal of Community Nutrition
• /
• v.29 no.1
• /
• pp.34-50
• /
• 2024

Objectives: Transformation through a sustainable food system to provide healthy diets is essential for enhancing both human and planetary health. This study aimed to explain about sustainable diets and illustrate appropriate measurement of adherence to sustainable diets using a pre-existing index. Methods: For literature review, we used PubMed and Google Scholar databases by combining the search terms "development," "validation," "sustainable diet," "sustainable diet index," "planetary healthy diet," "EAT-Lancet diet," and "EAT-Lancet reference diet." For data presentation, we used data from National Health and Nutrition Examination Survey, 2017-2018, among adults aged 20 years and older (n = 3,920). Sustainable Diet Index-US (SDI-US), comprising four sub-indices corresponding to four dimensions of sustainable diets (nutritional quality, environmental impacts, affordability, and sociocultural practices), was calculated using data from 24-hour dietary recall interview, food expenditures, and food choices. A higher SDI-US score indicated greater adherence to sustainable diets (range: 4-20). This study also presented SDI-US scores according to the sociodemographic status. All analyses accounted for a complex survey design. Results: Of 148 papers, 16 were reviewed. Adherence to sustainable diets fell into 3 categories: EAT-Lancet reference diet-based (n = 8), Food and Agriculture Organization (FAO) definition-based (n = 4), and no specific guidelines but including the sustainability concept (n = 4). Importantly, FAO definition emphasizes on equal importance of four dimensions of diet (nutrition and health, economic, social and cultural, and environmental). The mean SDI-US score was 13 out of 20 points, and was higher in older, female, and highly educated adults than in their counterparts. Conclusions: This study highlighted that sustainable diets should be assessed using a multidimensional approach because of their complex nature. Currently, SDI can be a good option for operationalizing multidimensional sustainable diets. It is necessary to develop a Korean version of SDI through additional data collection, including environmental impact of food, food price, food budget, and use of ready-made products.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.19-28
• /
• 2012

After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

• Journal of the Korean Society of Food Culture
• /
• v.13 no.4
• /
• pp.267-274
• /
• 1998

The consumption patterns of the minimally processed fruits and vegetables were surveyed in this present study. Eighty four women who were resident in either Seoul and Kyongki-do in Korea were participants in this study as respondents to our various questionnaire. The result are summarized as follows; The respondents had a preference for a supermarket (46.4%) as the place of purchase (or fruits and vegetables and the frequency of purchase was two or three times per week. The residents of apartment preferred department stores and supermarkets to stalls in the immediate residential area (p<.05). Fifty percents of the unmarried women respondents indicated that they only purchased once a week. Approximately 70% of the respondents rated quality considerations over the price and quantity when they choose their fruits and vegetables. This behavioral tendency was stronger for the residents of the apartment and amongst the more highly educated women. The type of fruits and vegetables purchased were mainly unprocessed. However, minimally processed products appeared to be popular especially among unmarried or married who did not have children, were highly educated and aged between 20 and 30. These observations are supported by data in which 82% of respondents whose ages were ranged between 20 and 30, with high educational backgrounds and who had experienced in the purchase of minimally processed fruits and vegetables. The motivation for purchasing minimally processed fruits and vegetables generally resulted from a consideration of the saving in cooking time, the ease of handling and the desire to serve appropriate portions. On the other hand, the reasons for not purchasing minimally processed fruits and vegetables were the comparatively high price, a perception of unsanitary handling and pack size that were considered too small. Ninety-three percent of the respondents exhibited a positive response to the need for minimally processed fruits and vegetables. Freshness was considered to be the most important factor when purchasing these products. The preferred price for the minimally processed fruits and vegetables was approximately $110{\sim}120%$ of that for the unprocessed products.

• Journal of the Korean association of regional geographers
• /
• v.5 no.1
• /
• pp.101-120
• /
• 1999

The purpose of this study is to analyze the impact of agricultural polices on the change of regional structure based on the specialization during the productivism period. Analysis are carried on through the comparison of distribution in 1950s and 1997. Since the 1950s, governmental policy has played a leading role in shaping the pattern of farming in Great Britain. The range of British measures have also been employed in an attempt to improve the efficiency of agriculture and raise farm income. Three fairly distinct phase can be identified in the developing relationship between government policies and British agriculture in the postwar period. In the 1st phase, The Agricultural Act of 1947 laid the foundations for agricultural productivism in Great Britain until membership of the EC. This was to be achieved through the system of price support and guaranteed prices and the means of a series of grants and subsidies. Guaranteed prices encouraged farmenrs to intensify production and specialize in either cereal farming or milk-beef enterprise. The former favoured eastern areas, whereas the latter favoured western areas. Various grants and subsidies were made available to farmers during this period, again as a way of increasing efficiency and farm incomes. Many policies, such as Calf Subsidy and the Ploughing Grant, Hill cow and Hill Sheep Schemes and the Hill Farming and Livestock Rearing Grant was provided. Some of these policies favoured western uplands, whilst the others was biased towards the Lake District. Concentration of farms occured especially in near the London Metropolitan Area and south part of Scotland. In the 2nd stage after the membership of EC, very high guaranteed price created a relatively risk-free environment, so farmers intensified production and levels of self-sufficiency for most agriculture risen considerably. As farmers were being paid high prices for as much as they could produce, the policy favoured areas of larger-scale farming in eastern Britain. As a result of increasing regional disparities in agriculture, the CAP became more geographically sensitive in 1975 with the setting up of the Less Favoured Areas(LFAs). But they are biased towards the larger farms, because such farms have more crops and/or livestock, but small farms with low incomes are in most need of support. Specialization of cereals such wheat and barely was occured, but these two cereal crops have experienced rather different trend since 1950s. Under the CAP, farmers have been paid higher guaranteed prices for wheat than for barely because of the relative shortage of wheat in the EC. And more barely were cultivated as feedstuffs for livestock by home-grown cereals. In the 1950s dairying was already declining in what was to become the arable areas of southern and eastern England. By the mid-1980s, the pastral core had maintained its dominance, but the pastoral periphery had easily surpassed arable England as the second most important dairying district. Pig farming had become increasingly concentrated in intensive units in the main cereal areas of eastern England. These results show that the measure of agricultural policy induced the concentration and specialization implicitly. Measures for increasing demand, reducing supply or raising farm incomes are favoured by large scale farming. And price support induced specialization of farming. And technology for specialization are diffused and induced geographical specialization. This is the process of change of regional structure through the specialization.