• Journal of Hospice and Palliative Care
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• v.15 no.2
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• pp.68-76
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• 2012

Purpose: The study was designed to verify effects of aromatherapy on depression, anxiety and the autonomic nervous system in breast cancer patients who are undergoing adjuvant radiotherapy. Methods: Data were collected from November 2006 through March 2007 at the C university hospital in Seoul. The study included 33 patients and they were assigned to three groups. Group I had aroma oil inhalation for 2 minutes per time, three times a day for six weeks whereas Group II and a control group inhaled aroma oil for 2 minutes per time, once a day for six weeks. For Groups I and II, a mixture of lemon, lavender, rosewood and rose essential oils were used while control group inhaled tea tree oil. Results: Depression was significantly decreased in patients in the experimental groups only. In Groups I and II patients, anxiety level was lower than that in control patients. Patients in Groups I and II also showed stronger physical resistance to stress than control group patients. Conclusion: Aromatherapy should be considered as a method that can significantly decrease depression in breast cancer patients who are undergoing adjuvant radiotherapy.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1185-1194
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• 2011

This study was carried out to estimate carbon emission using LCA (Life Cycle Assessment) and to establish LCI (Life Cycle inventory) DB for lettuce production system in protected cultivation. The results of data collection for establishing LCI DB showed that the amount of fertilizer input for 1 kg lettuce production was the highest. The amounts of organic and chemical fertilizer input for 1 kg lettuce production were 7.85E-01 kg and 4.42E-02 kg, respectively. Both inputs of fertilizer and energy accounted for the largest share. The amount of field emission for $CO_2$, $CH_4$ and $N_2O$ for 1 kg lettuce production was 3.23E-02 kg. The result of LCI analysis focused on GHG (Greenhouse gas) showed that the emission value to produce 1 kg of lettuce was 8.65E-01 kg $CO_2$. The emission values of $CH_4$ and $N_2O$ to produce 1 kg of lettuce were 8.59E-03 kg $CH_4$ and 2.90E-04 kg $N_2O$, respectively. Fertilizer production process contributed most to GHG emission. Whereas, the amount of emitted nitrous oxide was the most during lettuce cropping stage due to nitrogen fertilization. When GHG was calculated in $CO_2$-equivalents, the carbon footprint from GHG was 1.14E-+00 kg $CO_2$-eq. $kg^{-1}$. Here, $CO_2$ accounted for 76% of the total GHG emissions from lettuce production system. Methane and nitrous oxide held 16%, 8% of it, respectively. The results of LCIA (Life Cycle Impact assessment) showed that GWP (Global Warming Potential) and POCP (Photochemical Ozon Creation Potential) were 1.14E+00 kg $CO_2$-eq. $kg^{-1}$ and 9.45E-05 kg $C_2H_4$-eq. $kg^{-1}$, respectively. Fertilizer production is the greatest contributor to the environmental impact, followed by energy production and agricultural material production.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.177-198
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• 2018

Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.502-509
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• 2013

To estimate greenhouse gas (GHG) emission, we established inventory of conventional rice cultivation from farmers in Gunsan and Iksan, Jeonbuk province in 2011~2012. This study was to calculate carbon footprint and to analyse the major factor of GHGs. We carried out a sensitivity analysis using the analyzed main factors of GHGs and estimated the mitigation potential of GHGs. Also we tried to suggest agricultural methods to reduce GHGs that farmers of this case study can apply. Carbon footprint of rice production unit of 1 kg was 2.21 kg $CO_2.-eq.kg^{-1}$. Although amount of $CO_2$ emissions is largest among GHGs, methane had the highest contribution of carbon footprint on rice production system after methane was converted to carbon dioxide equivalent ($CO_2$-eq.) multiplied by the global warming potential (GWP). Source of $CO_2$ in the cultivation of rice farming is incomplete combustion of fossil fuels used by agricultural machinery. Most of the $CH_4$ emitted during rice cultivation and major factor of $CH_4$ emission is flooded paddy field in anaerobic condition. Most of the $N_2O$ emitted from rice cultivation process and major sources of $N_2O$ emission is application of fertilizer such as compound fertilizer, urea, orgainc fertilizer, etc. As a result of sensitivity analysis due to the variation in energy consumption, diesel had the highest sensitivity among the energies inputs. If diesel consumption is reduced by 10%, it could be estimated that $CO_2$ potential reduction is about 2.5%. When application rate of compound fertilizer reduces by 10%, the potential reduction is calculated to be approximately 1% for $CO_2$ and approximately 1.8% for $N_2O$. When drainage duration is decreased until 10 days, methane emissions is reduced by approximately 4.5%. That is to say drainage days, tillage, and reducing diesel consumption were the main sources having the largest effect of GHG reduction due to changing amount of inputs. Accordingly, proposed methods to decrease GHG emissions were no-tillage, midsummer drainage, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.358-383
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• 2015

The concept of 'carbon footprint' has been developed as a means of quantifying the specific emissions of the greenhouse gases (GHGs) that cause global warming. Although there are still neither clear definitions of the term nor rules for units or the scope of its estimation, it is broadly accepted that the carbon footprint is the total amount of GHGs, expressed as $CO_2$ equivalents, emitted into the atmosphere directly or indirectly at all processes of the production by an individual or organization. According to the ISO/TS 14067, the carbon footprint of a product is calculated by multiplying the units of activity of processes that emit GHGs by emission factor of the processes, and by summing them up. Based on this, 'carbon labelling' system has been implemented in various ways over the world to provide consumers the opportunities of comparison and choice, and to encourage voluntary activities of producers to reduce GHG emissions. In the agricultural sector, as a judgment basis to help purchaser with ethical consumption, 'low-carbon agricultural and livestock products certification' system is expected to have more utilization value. In this process, the 'cradle to gate' approach (which excludes stages for usage and disposal) is mainly used to set the boundaries of the life cycle assessment for agricultural products. The estimation of carbon footprint for the entire agricultural and forestry sector should take both removals and emissions into account in the "National Greenhouse Gas Inventory Report". The carbon accumulation in the biomass of perennial trees in cropland should be considered also to reduce the total GHG emissions. In order to accomplish this, tower-based flux measurements can be used, which provide a direct quantification of $CO_2$ exchange during the entire life cycle. Carbon footprint information can be combined with other indicators to develop more holistic assessment indicators for sustainable agricultural and forestry ecosystems.

• Korean Journal of Environmental Biology
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• v.27 no.1
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• pp.6-19
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• 2009

We investigated the macrozoobenthos at major two harbors of Korea in July and August 2007 in order to check the changes in the species composition due to the invasive species and to make a species inventory at each harbor system. At the Incheon Harbor, a total of 88 species was sampled with abundance of 3,212 ind. m$^{-2}$ and biomass of 239 g m$^{-2}$. The most dominant species was Tharyx sp. belong to polychaete taxa, followed by Chaetozone setosa in the harbor area. The dominant species of outer area were Musculus senhousia and Sternaspis scutata. The diversity index ranged between 0.9$\sim$2.4, and evenness index between 0.3$\sim$0.9, and richness index between 1.8$\sim$3.9. Benthic pollution index ranged between 16$\sim$74. The highest benthic pollution index was at station 4. On the other hand the lowest value was at station 6, where a large amount of M. senhousia belong to mollusca occurred. At the Busan Harbor, a total of 89 species was sampled with density of 1,845 ind. m$^{-2}$ and biomass of 133.6 g m$^{-2}$ in August 2007. The most dominant species was Tharyx sp., followed by M. japonica and Cirratulus cirrata within harbor area. M. japonica was dominant species in the outer area. The diversity index ranged between 0.7$\sim$2.2, evenness index between 0.3$\sim$1.0, and richness index between 1.1$\sim$4.1. Benthic pollution index ranged between 31$\sim$90. The lowest benthic pollution index was found at site 2 within harbor area.

• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.1-10
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• 2013

RFID(Radio Frequency Identification) system is non-contact identification technology. A basic RFID system consists of a reader, and a set of tags. RFID tags can be divided into active and passive tags. Active tags with power source allows their own operation execution and passive tags are small and low-cost. So passive tags are more suitable for distribution industry than active tags. A reader processes the information receiving from tags. RFID system achieves a fast identification of multiple tags using radio frequency. RFID systems has been applied into a variety of fields such as distribution, logistics, transportation, inventory management, access control, finance and etc. To encourage the introduction of RFID systems, several problems (price, size, power consumption, security) should be resolved. In this paper, we proposed an algorithm to significantly alleviate the collision problem caused by simultaneous responses of multiple tags. In the RFID systems, in anti-collision schemes, there are three methods: probabilistic, deterministic, and hybrid. In this paper, we introduce ALOHA-based protocol as a probabilistic method, and Tree-based protocol as a deterministic one. In Aloha-based protocols, time is divided into multiple slots. Tags randomly select their own IDs and transmit it. But Aloha-based protocol cannot guarantee that all tags are identified because they are probabilistic methods. In contrast, Tree-based protocols guarantee that a reader identifies all tags within the transmission range of the reader. In Tree-based protocols, a reader sends a query, and tags respond it with their own IDs. When a reader sends a query and two or more tags respond, a collision occurs. Then the reader makes and sends a new query. Frequent collisions make the identification performance degrade. Therefore, to identify tags quickly, it is necessary to reduce collisions efficiently. Each RFID tag has an ID of 96bit EPC(Electronic Product Code). The tags in a company or manufacturer have similar tag IDs with the same prefix. Unnecessary collisions occur while identifying multiple tags using Query Tree protocol. It results in growth of query-responses and idle time, which the identification time significantly increases. To solve this problem, Collision Tree protocol and M-ary Query Tree protocol have been proposed. However, in Collision Tree protocol and Query Tree protocol, only one bit is identified during one query-response. And, when similar tag IDs exist, M-ary Query Tree Protocol generates unnecessary query-responses. In this paper, we propose Adaptive M-ary Query Tree protocol that improves the identification performance using m-bit recognition, collision information of tag IDs, and prediction technique. We compare our proposed scheme with other Tree-based protocols under the same conditions. We show that our proposed scheme outperforms others in terms of identification time and identification efficiency.