• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.5
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• pp.626-637
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• 2013

We measured the grain size, ignition loss (IL), chemical oxygen demand (COD), acid volatile sulfide (AVS) and trace metals (Al, Fe, Cu, Pb, Zn, Cd, Cr, Mn, Hg, and As) of intertidal surface sediment collected from 11 islands (62 stations) in the southern region of Jeollanam Province. The objective of this research was to evaluate the organic matter and trace metals contaminations of sediments from coastal island tidal flats. Surface sediment texture was characterized as follows: mud, sandy silt, muddy sand, and slightly gravelly sand facies. The finer sediments are mainly dominated in the northern part of each island. The concentrations of IL, COD, AVS and some trace metals (Al, Fe, Zn, Cr, Cu, and Hg) were higher in the northwestern part of Wan Island and the area between Gogeum and Sinji Islands, and were associated with relatively finer sediment, as compared to other locations. The concentrations of Mn, Pb, Cd, and As were higher in the northwestern and southeastern parts of Geoguem and Pyungil Islands, but were not correlated with mean grain size. Based on sediment quality guidelines (SQGs), the concentrations of trace metals were lower than the values of effect range low (ERL), used in United States, and threshold effects level (TEL), used in Korea, with exception of As. Similarly, the intertidal sediments were moderately contaminated with As, based on the the enrichment factor (EF) and the geoaccumulation index ($I_{geo}$). The high concentration of As in intertidal sediments from this study region may be due to the input of naturally or artificially contaminated submarine groundwater, contaminated waste from seaweed aquaculture operations and/or land-based seaweed processing facilities. Further studies are needed to identify the sources of As in this study region, and to determine the effects of As contamination on coastal ecosystem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.223-252
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• 2008

In this study, we attempt to propose a choice-based diffusion model with switching cost, which can be used to forecast the dynamic substitution and competition among previous and new products at both individual-level and aggregate level, especially when market data for new products is insufficient. Additionally, we apply the proposed model to the empirical case of substitution and competition among Analog Cable TV that represents previous fixed charged broadcasting service and Digital Cable TV and Internet Protocol TV (IPTV) that are new ones, verify the validities of our proposed model, and finally derive related empirical implications. For empirical application, we obtained data from survey conducted as follows. Survey was administered by Dongseo Research to 1,000 adults aging from 20 to 60 living in Seoul, Korea, in May of 2007, under the title of 'Demand analysis of next generation fixed interactive broadcasting services'. Conjoint survey modified as follows, was used. First, as the traditional approach in conjoint analysis, we extracted 16 hypothetical alternative cards from the orthogonal design using important attributes and levels of next generation interactive broadcasting services which were determined by previous literature review and experts' comments. Again, we divided 16 conjoint cards into 4 groups, and thus composed 4 choice sets with 4 alternatives each. Therefore, each respondent faces 4 different hypothetical choice situations. In addition to this, we added two ways of modification. First, we asked the respondents to include the status-quo broadcasting services they subscribe to, as another alternative in each choice set. As a result, respondents choose the most preferred alternative among 5 alternatives consisting of 1 alternative with current subscription and 4 hypothetical alternatives in 4 choice sets. Modification of traditional conjoint survey in this way enabled us to estimate the factors related to switching cost or switching threshold in addition to the effects of attributes. Also, by using both revealed preference data(1 alternative with current subscription) and stated preference data (4 hypothetical alternatives), additional advantages in terms of the estimation properties and more conservative and realistic forecast, can be achieved. Second, we asked the respondents to choose the most preferred alternative while considering their expected adoption timing or switching timing. Respondents are asked to report their expected adoption or switching timing among 14 half-year points after the introduction of next generation broadcasting services. As a result, for each respondent, 14 observations with 5 alternatives for each period, are obtained, which results in panel-type data. Finally, this panel-type data consisting of $4{\ast}14{\ast}1000=56000$observations is used for estimation of the individual-level consumer adoption model. From the results obtained by empirical application, in case of forecasting the demand of new products without considering existence of previous product(s) and(or) switching cost factors, it is found that overestimated speed of diffusion at introductory stage or distorted predictions can be obtained, and as such, validities of our proposed model in which both existence of previous products and switching cost factors are properly considered, are verified. Also, it is found that proposed model can produce flexible patterns of market evolution depending on the degree of the effects of consumer preferences for the attributes of the alternatives on individual-level state transition, rather than following S-shaped curve assumed a priori. Empirically, it is found that in various scenarios with diverse combinations of prices, IPTV is more likely to take advantageous positions over Digital Cable TV in obtaining subscribers. Meanwhile, despite inferiorities in many technological attributes, Analog Cable TV, which is regarded as previous product in our analysis, is likely to be substituted by new services gradually rather than abruptly thanks to the advantage in low service charge and existence of high switching cost in fixed charged broadcasting service market.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1997.11a
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• pp.3-31
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• 1997

Water has always played a significant role in the lives of people. In urbanised Rome, with its million people. sophisticated supply systems developed and then fled with the empire. only to be rediscovered later But it was the industrial Revolution commencing in the eighteenth century that ushered in major paradigm shifts In use and altitudes towards water. Rapid and concentrated urbanisation brought problems of expanded demands for drinking supplies, waste management and disease. The strategy of using water from local streams, springs and village wells collapsed under the onslaughts of rising urban demands and pollution due to poor waste disposal practices. Expanding travel (railways. and steamships) aided the spread of disease. In England. public health crises peaks, related to water-borne typhoid and the three major cholera outbreaks occurred in the late eighteenth and early nineteenth century respectively. Technological, engineering and institutional responses were successful in solving the public health problem. it is generally accepted that the putting of water into pipe networks both for a clean drinking supply, as well as using it as a transport medium for removal of human and other wastes, played a significant role in towering death rates due to waterborne diseases such as cholera and typhoid towards the end of the nineteenth century. Today, similar principles apply. A recent World Bank report Indicates that there can be upto 76％ reduction in illness when major water and sanitation improvements occur in developing countries. Water management, technology and thinking in Australia were relatively stable in the twentieth century up to the mid to late 1970s. Groundwater sources were investigated and developed for towns and agriculture. Dams were built, and pipe networks extended both for supply and waste water management. The management paradigms in Australia were essentially extensions of European strategies with the minor adaptions due to climate and hydrogeology. During the 1970s and 1980s in Australia, it was realised increasingly that a knowledge of groundwater and hydrogeological processes were critical to pollution prevention, the development of sound waste management and the problems of salinity. Many millions of dollars have been both saved and generated as a consequence. This is especially in relation to domestic waste management and the disposal of aluminium refinery waste in New South Wales. Major institutional changes in public sector water management are occurring in Australia. Upheveals and change have now reached ail states in Australia with various approaches being followed. Market thinking, corporatisation, privatisation, internationalisation, downsizing and environmental pressures are all playing their role in this paradigm shift. One casualty of this turmoil is the progressive erosion of the public sector skillbase and this may become a serious issue should a public health crisis occur such as a water borne disease. Such crises have arisen over recent times. A complete rethink of the urban water cycle is going on right now in Australia both at the State and Federal level. We are on the threshold of significant change in how we use and manage water, both as a supply and a waste transporter in Urban environments especially. Substantial replacement of the pipe system will be needed in 25 to 30 years time and this will cost billions of dollars. The competition for water between imgation needs and environmental requirements in Australia and overseas will continue to be an issue in rural areas. This will be especially heightened by the rising demand for irrigation produced food as the world's population grows. Rapid urbanisation and industrialisation in the emerging S.E Asian countries are currently producing considerable demands for water management skills and Infrastructure development. This trend e expected to grow. There are also severe water shortages in the Middle East to such an extent that wars may be fought over water issues. Environmental public health crises and shortages will help drive the trends.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.1-7
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• 2001

Total upland area for cultivating the vegetable crops in the Alpine soils of Northeastern South Korea has been extending its limit to meet the increasing demand of vegetable food in recent decades. About 70% of these alpine soils are located in over 7% of the slope and most of vegetable crops have been cultivated intensively without practicing the best management systems. Thus, soil erosion and continuous cropping system have degenerated the soil fertility and shown detrimental effects on water quality. We initiated an intensive and extensive investigation to characterize the fertility problems encountered in these uplands. Objectives of this paper were to characterize the fertility status in the Alpine soils cultivated with vegetable crops for many years and to provide the recommendations for adequate soil management measures including fertilization and erosion control. Soils in general have good drainage with textural classes of loam or sandy loam. Their topographical characteristics tended to lead them to shallow plow layers, and the steepness of the terrain created erosion hazard. Of the soils examined, about 11% of uplands over 30% gradient was found in need of an urgent reforestation. A high content of gravel and firm hardness of soil attributed to inhibit the utilization of farm machinery and plant-root development. The average soil pH 5.6 was slightly low relative to pH 5.70 of the national average. Organic matter content was high compared with 2.0% of national average, but decreased with the prolonged cultivation periods. Available $P_2O_5$ concentration was unusually high due to the consequence of over dose application with chemical and organic fertilizers. Exchangeable cations as Ca, Mg, and K were appeared to be decreased in these regions with prolonging the cultivation periods. There were no significant differences in cation exchange capacity (CEC) and electrical conductivity (EC) among locations. Heavy metal contents were mostly lower than the threshold of danger level designated by Soil Environment Conservation Law of South Korea. Results indicated that a proper countermeasure and the best management practice should be immediately implemented to conserve the top soil and fertility in the Alpine regions.