• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.179-196
• /
• 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.

• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.45-52
• /
• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Spatial Information Research
• /
• v.20 no.5
• /
• pp.99-109
• /
• 2012

Recently, due to the growth of social media and spread of smart-phone, the amount of data has considerably increased by full use of SNS (Social Network Service). According to it, the Big Data concept is come up and many researchers are seeking solutions to make the best use of big data. To maximize the creative value of the big data held by many companies, it is required to combine them with existing data. The physical and theoretical storage structures of data sources are so different that a system which can integrate and manage them is needed. In order to process big data, MapReduce is developed as a system which has advantages over processing data fast by distributed processing. However, it is difficult to construct and store a system for all key words. Due to the process of storage and search, it is to some extent difficult to do real-time processing. And it makes extra expenses to process complex event without structure of processing different data. In order to solve this problem, the existing Complex Event Processing System is supposed to be used. When it comes to complex event processing system, it gets data from different sources and combines them with each other to make it possible to do complex event processing that is useful for real-time processing specially in stream data. Nevertheless, unstructured data based on text of SNS and internet articles is managed as text type and there is a need to compare strings every time the query processing should be done. And it results in poor performance. Therefore, we try to make it possible to manage unstructured data and do query process fast in complex event processing system. And we extend the data complex function for giving theoretical schema of string. It is completed by changing the string key word into integer type with filtering which uses keyword set. In addition, by using the Complex Event Processing System and processing stream data at real-time of in-memory, we try to reduce the time of reading the query processing after it is stored in the disk.

• Journal of Bio-Environment Control
• /
• v.27 no.3
• /
• pp.253-259
• /
• 2018

This study set out to select a system to realize an optimal environment for strawberry cultivation greenhouses based on data about the growth and development of strawberry and its environment and to provide basic data for the research of its improved productivity. For these purposes, the investigator conducted a field survey with greenhouses for strawberry cultivation in western Gyeongnam. The findings show that farmers in their fifties and sixties accounted for the biggest part in the age groups of strawberry farmers. While those who were under 50 were accounted for approximately 67.5%, those who were 60 or older accounted for 32.5%. As for cultivation experiences, the majority of the farmers had ten years of cultivation experiences or less with some having 30 years of cultivation experiences or more. All the farmers built an arch type single span greenhouse. Those who used nutrient solutions were about 75.0%, being more than those who used soil. All of the farmers that used a nutrient solution adopted an elevated hydroponic system. The single span greenhouses were in the range of 7.5~8.5m, 1.3~1.8m and 2.5~3.5m for width, eaves, and ridge height, respectively, regardless of survey areas. The rafters interval was about 0.7~0.8m. In elevated hydroponic cultivation, the width, height, and interval of the beds were about 0.25m, 1.2m and 1.0m, respectively. As for the strawberry varieties, the domestic ones accounted for approximately 97.5% with Seolhyang being the most favorite one at about 65.0%. As for the internal environment factors of greenhouses, 38 farmers measured only temperature and relatively humidity. As for hydroponics, the farmers used a hydroponics control system. Except for the farmers that introduced a smart farm system for temperature and humidity control, approximately 85.0% controlled temperature and humidity only with a control panel for side windows and ventilation fans. As for heating and heat insulation, all of the farmers were using water curtains with many farmers using an oil or electric boiler, radiating lamp or non-woven fabric, as well, when necessary.

• Proceedings of the Korean Ceranic Society Conference
• /
• 2005.06a
• /
• pp.1-112
• /
• 2005

This report is results of a research on recent R&D trends in electroceramics, mainly focusing on the papers submitted to the organizing committee of the International Conference on Electroceramics 2005 (ICE-2005) which was held at Seoul on 12-15 June 2005. About 380 electroceramics researchers attended at the ICE-2005 from 17 countries including Korea, presenting and discussing their recent results. Therefore, we can easily understand the recent research trends in the field of electroceramics by analyses of the subject and contents of the submitted papers. In addition to the analyses of the papers submitted to the ICE-2005, we also collected some informations about domestic and international research trends to help readers understand this report easily. We analysed the R&D trends on the basis of four main categories, that is, informatics electroceramics, energy and environment ceramics, processing and characterization of electroceramics, and emerging fields of electroceramics. Each main category has several sub-categories again. The informatics ceramics category includes integrated dielectrics and ferroelectrics, oxide and nitride semiconductors, photonic and optoelectronic devices, multilayer electronic ceramics and devices, microwave dielectrics and high frequency devices, and piezoelectric and MEMS applications. The energy and environment ceramics category has four sub-categories, that is, rechargable battery, hydrogen storage, fuel cells, and advanced energy conversion concepts. In the processing and characterization category, there exist domain, strain, and epitaxial dynamics and engineering sub-category, innovative processing and synthesis sub-category, nanostructured materials and nanotechnology sub- category, single crystal growth and characterization sub-category, theory and modeling sub-category. Nanocrystalline electroceramics, electroceramics for smart sensors, and bioceramics sub-categories are included to the emerging fields category. We hope that this report give an opportunity to understand the international research trend, not only to Korean ceramics researchers but also to science and technology policy researchers.

• Journal of Energy Engineering
• /
• v.23 no.2
• /
• pp.125-148
• /
• 2014

This paper performs a historical analysis on the various factors contributing to the current carbon lock-in of Korean electricity industry by using techo-institutional complex. The possibilities of the industry's carbon lock-out toward more sustainable development are also investigated. It turns out that market, firm, consumer, and government factors are all responsible for the development of the carbon lock-in of Korean power industry; the Korean government consistently favoring large power plants based on the economy of scale; below-cost electricity tariff; inflation policy to suppress increases in power price; rapid demand growth in summer and winter seasons; rigidities of electricity tariff; and expansion of gas-fired and imported coal-fired large power plants. On the other hand, except for nuclear power generation and smart grid, environment laws and new and renewable energy laws are the other remaining factors contributing to the carbon lock-out. Considering three key points that Korea is an export-oriented economy, the generation mix is the most critical factor to decide the amounts of carbon emission in the power industry, and the share of industry and commercial power consumption is over 85%, it is unlikely that Korea will achieve the carbon lock-out of power industry in the near future. Therefore, there are needs for more integrated approaches from market, firm, consumer, and government all together in order to achieve the carbon lock-out in the electricity industry. Firstly, from the market perspective, it is necessary to persue more active new and renewable energy penetration and to guarantee consumer choices by mitigating the incumbent's monopoly power as in the OECD countries. Secondly, from the firm perspective, the promotion of distributed energy system is urgent, which includes new and renewable resources and demand resources. Thirdly, from the consumer perspective, more green choices in the power tariff and customer awareness on the carbon lock-out are needed. Lastly, the government shall urgently improve power planning frameworks to include the various externalities that were not properly reflected in the past such as environmental and social conflict costs.

• Journal of Embryo Transfer
• /
• v.29 no.3
• /
• pp.265-271
• /
• 2014

Implementation of smart embryo technologies in cattle e.g. ovum pick-up followed by in vitro embryo production (OPU-IVP). Seasonal variation is important factor for follicular growth, oocytes quality, quantity and developmental competence. Therefore the aim of present study was carried out to investigated whether the seasons (hot and cool) effect on follicular development, oocyte recovery and subsequent embryo development. Follicular oocytes were aspirated from Korean native cows (Hanwoo) by the ovum pick-up (OPU) method, which was performed 24 times during two different seasons, the hot (July to September) and cool (October to December), from OPU donors. The recovered oocytes were classified according to morphological categories and used for in vitro embryo production (IVEP). The mean number of total follicles was significantly higher (p<0.05) during the hot season ($18.32{\pm}2.26$) compared to cool season ($15.41{\pm}3.34$). Furthermore, seasons did not significantly effect on the number of oocytes recovered (hot season: 41.16% vs. cool season: 46.14%). However, the average number of Grade A oocytes was significantly greater during hot ($1.75{\pm}1.86$) season compared to the cool season ($1.00{\pm}1.46$), but there was no significant difference of other grades oocytes. The cleavage rate (hot: 66.67% vs. cool: 63.3%) and embryo development (hot: 58.95% vs. cool: 56.97%) did not differ significantly between the seasons. In conclusion, the results of present study suggest that the season (hot and cool) does not have effects on the oocyte recovery and embryo developmental competence of in vitro cultured embryos.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.221-238
• /
• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.6
• /
• pp.249-267
• /
• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.202-217
• /
• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.