• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.227-235
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• 2010

This paper proposes the recommendation system which is advanced using RFM method and Association Rules in e-Commerce. Using a implicit method which is not used user's profile for rating, it is necessary for user to keep the RFM score and Association Rules about users and items based on the whole purchased data in order to recommend the items. This proposing system is possible to advance recommendation system using RFM method and Association Rules for cross-selling, and also this system can avoid the duplicated recommendation by the cross comparison with having recommended items before. And also, it's efficient for them to build the strategy for marketing and crm(customer relationship management). It can be improved and evaluated according to the criteria of logicality through the experiment with dataset collected in a cosmetic cyber shopping mall. Finally, it is able to realize the personalized recommendation system for one to one web marketing in e-Commerce.

• Environmental and Resource Economics Review
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• v.11 no.2
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• pp.211-231
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• 2002

This paper summarizes the results of a study that assess how a demand side management (DSM) system addresses key economic and environmental challenges facing in the Korean natural gas sector considering; ${\bullet}$ high discrepancies of seasonal consumption volume and of load factor in unmatured domestic LNG market, ${\bullet}$ unfavorable and volatile international LNG market, imposing with the contestable "take-or-pay" contract terms, ${\bullet}$ low profile of LNG and existence of market barriers against an optimal fuel mix status in the industrial energy sector. A particular focus of this study is to establish an 'extended' DSM system in the unmatured gas market, especially in industry sector, that could play a key role to assure an optimum fuel mix scheme. Under the concept of 'extended' DSM, a system dynamics modeling approach has been introduced to explore the option to maximize economic benefits in terms of the national energy system optimization, entailing different ways of commitments accounting for different DSM measures and time delay scenarios. The study concludes that policy options exist that can reduce inefficiencies in gas industry and end-use system at no net costs to national economy. The most scenarios find that, by the year 2015, it is possible to develop a substantial potential of increased industrial gas end-uses under more reliable and stable load patterns. Assessment of sensitivity analysis suggests that time delay factor, in formulating DSM scenarios, plays a key role to overcome various market barriers in domestic LNG market and provides a strong justification for the policy portfolios 'just in time' (time accurateness), which eventually contribute to establish an optimum fuel mix strategy. The study indicates also the needs of advanced studies based on SD approach to articulate uncertainty in unmatured energy market analysis, including gas.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.6
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• pp.874-880
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• 2019

Objective: Ozone is considered a strong antimicrobial agent with numerous potential applications in the food industry. However, its high oxidizing potential can induce alterations in foods by acting on the unsaturated fatty acids. The aim of this study was to investigate the effect of ozonation on the oxidative stability of chicken breast meat obtained from animals subjected to different feeding strategies. Methods: Samples were obtained from commercial hybrid chickens (ROSS 508), some of which were nourished with a feed enriched with fats of animal origin, while the lipid source was vegetal for the remaining birds. Samples of meat belonging to both groups were treated with ozone and then analysis was performed to evaluate alterations in physical properties, lipid content, fatty acid profile, and oxidation stability. Results: Ozone induced a significant reduction in drip loss in meat samples obtained from animals nourished with vegetable fats; this nutritional strategy also produced meats leaner and richer in polyunsaturated fatty acids. Thiobarbituric acid reactive substances, useful for the assessment of lipid oxidation, were higher in samples obtained from animals fed with vegetable fats with respect to diet based on the addition of animal fats. Conclusion: The ozone treatment improved the physical parameters of meat samples obtained from animals fed with vegetable fats, however the same samples showed a higher lipid oxidation compared to what observed in the case of the dietary intake of animal fats, probably as a consequence of the marked increase in polyunsaturated fatty acids which are more susceptible to peroxidation.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.37-44
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• 2022

Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Microbiology and Biotechnology Letters
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• v.38 no.4
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• pp.467-474
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• 2010

Cheonggukjang is one of the traditional fermented soy-based foods in Korean diets. Studies in cell cultures, humans have revealed anti-hypertension, anti-stress, anticancer, antioxidant, immune enhancing effects. Angelica gigas, Rehmanniae radix, and Red ginseng are popular medicinal plants and widely used for oriental medicine. In this study a strategy had been developed to mobilize beneficial phenolics from Angelica gigas, Rehmanniae radix, and Red ginseng combined with fermented soy by Cheonggukjang fermentation for antioxidant and Type II diabetes management. The quality and functional characteristics of Chenggukjang fermented with Angelica gigas, Rehmanniae radix and Red ginseng. Cheonggukjang (CKJ), Angelica gigas Cheonggukjang (CKJ-DD), Rehmanniae radix Cheonggukjang (CKJ-RG), Angelica gigas and Rehmanniae radix Cheonggukjang (CKJ-DD+RG) and Red ginseng Cheonggukjang (CKJ-RED) were evaluated. The mobilized phenolic profile was evaluated for antioxidant activity and the potential to inhibit ${\alpha}$-amylase linked to hyperglycaemia. This research has important implications for the development of functional soy-based-fermented foods enriched with Angelica gigas, Rehmanniae radix and Red ginseng phenolics for oxidative stress - induced diabetic complications. Furthermore, Hunter's color values of 5 types cheonggukjang, lightness (L-values), redness (a-values) and yellowness (b-values) were evaluated. Free amino acid content of CKJ-RED (0.993 mg/gd. w.) showed higher than that of CKJ (0.205 mg/g-d.w.).

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• KSBB Journal
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• v.20 no.3
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• pp.220-227
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• 2005

Doxorubicin is an anthracycline-family polyketide compound with a very potent anti-cancer activity, typically produced by Streptomyces peucetius. To understand the potential target biosynthetic genes critical for the doxorubicin everproduction, a doxorubicin-specific DNA microarray chip was fabricated and applied to reveal the growth-phase-dependent expression profiles of biosynthetic genes from two doxorubicin-overproducing strains along with the wild-type strain. Two doxorubicin-overproducing 5. peucetius strains were generated via over-expression of a dnrl (a doxorubicin-specific positive regulatory gene) and a doxA (a gene involved in the conversion from daunorubicin to doxorubicin) using a streptomycetes high expression vector containing a strong ermE promoter. Each doxorubicin-overproducing strain was quantitatively compared with the wild-type doxorubicin producer based on the growth-phase-dependent doxorubicin productivity as well as doxorubicin biosynthetic gene expression profiles. The doxorubicin-specific DNA microarray chip data revealed the early-and-steady expressions of the doxorubicin-specific regulatory gene (dnrl), the doxorubicin resistance genes (drrA, drrB, drrC), and the doxorubicin deoxysugar biosynthetic gene (dnmL) are critical for the doxorubicin overproduction in S. peucetius. These results provide that the relationship between the growth-phase-dependent doxorubicin productivity and the doxorubicin biosynthetic gene expression profiles should lead us a rational design of molecular genetic strain improvement strategy.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.37-57
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• 2018

With the spread of smart phones, interest in mobile media is on the increase as useful media recently. Mobile media is assessed as having differentiated advantages from existing media in that not only can they provide consumers with desired information anytime and anywhere but also real-time interaction is possible in them. So far, studies on mobile advertising were mostly researches analyzing satisfaction with, and acceptance of, mobile advertising based on survey, researches focusing on the factors affecting acceptance of mobile advertising messages and researches verifying the effect of mobile advertising on brand recall, advertising attitude and brand attitude through experiments. Most of the domestic mobile advertising studies related to advertisement effect and advertisement attitude have been conducted through experiments and surveys. The advertising effectiveness measure of the mobile ad used the attitude of the advertisement, purchase intention, etc. To date, there have been few studies on the effects of mobile advertising on actual advertising data to prove the characteristics of the advertising platform and to prove the relationship between the factors influencing the advertising effect and the factors. In order to explore advertising effect of mobile advertising platform currently commercialized, this study defined advertising characteristics and media characteristics from the perspective of advertiser, advertising platform and publisher and analyzed the influence of each characteristic on advertising effect. As the advertisement characteristics, we classified advertisement format classified by bar type and floating type, and advertisement material classified by image and text. We defined advertisement characteristics of advertisement platform as Hedonic and Utilitarian media characteristics. As a dependent variable, we use CTR, which is the ratio of response (click) to ad exposure. The theoretical background and the analysis of the mobile advertising business, the hypothesis that the advertisement effect is different according to the advertisement specification, the advertisement material, In the ad standard, bar ads are classified as static framing, Floating ads can be categorized as dynamic framing, and the hypothetical definition of floating advertisements, which are high-profile dynamic framing ads, is highly responsive. In advertising, images with high salience are defined to have higher ad response than text. In the media characteristics classified as practical / hedonic type, it is defined that the hedonic type media has a more relaxed tendency than the practical media, and there is a high possibility of receiving various information because there is no clear target. In addition, image material and hedonic media are defined to be highly effective in the interaction between advertisement specification and advertisement material, advertisement specifications and media characteristics, and advertisement material and media characteristics. As the result of regression analysis on each characteristic, material standard, which is a characteristic of mobile advertisement, and media characteristics separated into 'Hedonic' and 'Utilitarian' had significant influence on advertisement effect and mutual interaction effect was also confirmed. In the mobile advertising standard, the advertising effect of the floating advertisement is higher than that of the bar advertisement, Floating ads were more effective than text ads for image ads. In addition, it was confirmed that the advertising effect is higher in the practical media than the hedonic media. The research was carried out with the big data collected from the mobile advertising platform, and it was possible to grasp the advertising effect of the measure index standard which is used in the practical work which could not be grasped in the previous research. In other words, the study was conducted using the CTR, which is a measure of the effectiveness of the advertisement used in the online advertisement and the mobile advertisement, which are not dependent on the attitude of the ad, the attitude of the brand, and the purchase intention. This study suggests that CTR is used as a dependent variable of advertising effect based on actual data of mobile ad platform accumulated over a long period of time. The results of this study is expected to contribute to establishment of optimum advertisement strategy such as creation of advertising materials and planning of media which suit advertised products at the time of mobile advertisement.