• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.29-36
• /
• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• Economic and Environmental Geology
• /
• v.42 no.5
• /
• pp.457-469
• /
• 2009

Applicability of bioleaching techniques using a sulfur-oxidizing bacteria, Acidithiobacillus thiooxidans, for remediation of shooting range soil contaminated with toxic heavy metals was investigated. The effects of sulfur concentration, the amount of bacterial inoculum and operation temperature on the efficiency of heavy metal solubilization were examined as well. As sulfur concentration and the amount of bacterial inoculum increased, the solubilization efficiency slightly increased; however, significant decrease of heavy metal extraction was observed with no addition of sulfur or bacterial inoculum. Bacteria solubilized the higher amount of heavy metals at $26^{\circ}C$ than $4^{\circ}C$. Lead showed the highest removal amount from the contaminated soil but the lowest removal efficiency when compared with Zn, Cu and Cr. It was likely due to formation of insoluble $PbSO_{4(s)}$ as precipitate or colloidal suspension. Sequential extraction of the microbially treated soil revealed that the proportion of readily extractable phases of Zn, Cu and Cr increased by bacterial leaching, and thus additional treatment or optimization of operation conditions such as leaching time were required for safe reuse of the soil. Bioleaching appeared to be a useful strategy for remediation of shooting range soil contaminated with heavy metals, and various operating conditions including concentration of sulfur input, inoculum volume of bacteria, and operation temperature exerted significant influence on bioleaching efficiency.

• Journal of Soil and Groundwater Environment
• /
• v.23 no.6
• /
• pp.90-103
• /
• 2018

Although fluoride is an essential trace element, ingestion of excessive amount of fluoride could have detrimental effect on human health. Generally, the bioavailability of fluoride in soils was low, but it could be harmful to the environment depending on the soil properties. Therefore, it is necessary to understand the concentration distribution, and fate and transport characteristics of fluoride to establish a resonable management strategy for fluoride pollution. This study was conducted to evaluate nationwide fluoride distribution in soils in Korea, as well as its fate and transport characteristics. The average background concentration was 204.5 (15.3~504.8) mg/kg, which is lower than the values of foreign soils. For the three regions of different land use, the average concentration was 229.6 mg/kg in region 1, 195.7 mg/kg in region 2, and 273.4 mg/kg in region 3. The concentration of fluoride was the highest in soils from Youngnam block within tectonic structure derived from metamorphic rocks. The results of sequential extraction to access F bioavailability showed fluoride in soils mainly existed as a residual form, which suggests the bioavailability of fluoride was relatively low. Soil properties such as soil pH, CEC, and clay content were found to affect F bioavailability of soil.

• Journal of Internet of Things and Convergence
• /
• v.10 no.3
• /
• pp.19-24
• /
• 2024

Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems

• Journal of Broadcast Engineering
• /
• v.22 no.2
• /
• pp.193-206
• /
• 2017

In this paper, we propose a rate control method based on the $R-{\lambda}$ model that supports a parallel encoding structure in GOP levels or IDR period levels for 4K UHD input video in real-time. For this, a slice-level bit allocation method is proposed for parallel encoding instead of sequential encoding. When a rate control algorithm is applied in the GOP level or IDR period level parallelism, the information of how many bits are consumed cannot be shared among the frames belonging to a same frame level except the lowest frame level of the hierarchical B structure. Therefore, it is impossible to manage the bit budget with the existing bit allocation method. In order to solve this problem, we improve the bit allocation procedure of the conventional ones that allocate target bits sequentially according to the encoding order. That is, the proposed bit allocation strategy is to assign the target bits in GOPs first, then to distribute the assigned target bits from the lowest depth level to the highest depth level of the HEVC hierarchical B structure within each GOP. In addition, we proposed a processing method that is used to improve subjective image qualities by allocating the bits according to the coding complexities of the frames. Experimental results show that the proposed bit allocation method works well for frame-level parallel HEVC software encoders and it is confirmed that the performance of our rate controller can be improved with a more elaborate bit allocation strategy by using the preprocessing results.

• Journal of Internet Computing and Services
• /
• v.20 no.4
• /
• pp.63-72
• /
• 2019

As a sub-concept of corporate or organization governance, business governance and IT governance have become major research topics in academia. However, despite the importance of process as a construct for mediating the domain between business and information technology, research on process governance is relatively inadequate. Process Governance focuses on activities that link business strategy with IT system implementation and explains the creation of corporate core values. The researcher studied the basic conceptual governance models of political science, sociology, public administration, and classified governance styles into six categories. The researcher focused on the series of metamodels. For examples, the traditional Strategy Alignment Model(SAM) by Henderson and Venkatraman which is replaced by the neo-SAM model, organizational governance network model, sequential organization governance model, organization governance meta model, process governance CUBE model, COSO and process governance CUBE comparison model, and finally Process Governance Framework and etc. The Major difference between SAM and neo-SAM model is Process Governance domain inserted between Business Governance and IT Governance. Among several metamodels, Process Governance framework, the core conceptual model consists of four activity dimensions: strategic aligning, human empowering, competency enhancing, and autonomous organizing. The researcher designed five variables for each activity dimensions, totally twenty variables. Besides four activity dimensions, there are six driving forces for Process Governance cycle: De-normalizing power, micro-power, vitalizing power, self-organizing power, normalizing power and sense-making. With four activity dimensions and six driving powers, an organization can maintain the flexibility of process governance cycle to cope with internal and external environmental changes. This study aims to propose the Process Governance competency model and Process Governance variables. The situation of the industry is changing from the function-oriented organization management to the process-oriented perspective. Process Governance framework proposed by the researcher will be the contextual reference models for the further diffusion of the research on Process Governance domain and the operational definition for the development of Process Governance measurement tools in detail.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.85-107
• /
• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Distribution Science
• /
• v.7 no.3
• /
• pp.71-100
• /
• 2009

The main purpose of this study is to define relevant factors that influence successful start-ups and management innovations of traditional markets from the point of market structures and relations. To do this, we devide an entrepreneurship of merchant into two factors, risk taking and managerial experience and choose product planning and its implementation to see merchandising of traditional markets. In this study we identify that several factors we chose are contributing to generating management performances through market promotional parameters. Also we confirm that image factors of traditional markets is consist of awareness and value of markets, and that these factors shows some sequential and continual patterns in the course of generating performances. In additions, it is identified that four independent factors have positive effects to star-up success; risk taking 0.29(t 2.61), managerial experience 0.04(t 1.79), merchandising implementation 0.374(t 2.61), market value 0.47(t 5.25), market awareness 0.22(t 2.30). This study can help merchants of traditional markets to make and change their market strategies, restructure their businesses and survive in the field. This also provide some ideas and guidances to relevant government agencies in formulating traditional market policies.

• Korean Journal of Soil Science and Fertilizer
• /
• v.32 no.4
• /
• pp.383-397
• /
• 1999

For sites to be investigated, the results of such an investigation can be used in determining foals for cleanup, quantifying risks, determining acceptable and unacceptable risk, and developing cleanup plans t hat do not cause unnecessary delays in the redevelopment and reuse of the property. To do this, it is essential that an appropriately detailed study of the site be performed to identify the cause, nature, and extent of contamination and the possible threats to the environment or to any people living or working nearby through the analysis of samples of soil and soil gas, groundwater, surface water, and sediment. The migration pathways of contaminants also are examined during this phase. Key aspects of cost-effective site assessment to help standardize and accelerate the evaluation of contaminated soils at sites are to provide a simple step-by-step methodology for environmental science/engineering professionals to calculate risk-based, site-specific soil levels for contaminants in soil. Its use may significantly reduce the time it takes to complete soil investigations and cleanup actions at some sites, as well as improve the consistency of these actions across the nation. To achieve the effective site assessment, it requires the criteria for choosing the type of standard and setting the magnitude of the standard come from different sources, depending on many factors including the nature of the contamination. A general scheme for site-specific assessment consists of sequential Phase I, II, and III, which is defined by workplan and soil screening levels. Phase I are conducted to identify and confirm a site's recognized environmental conditions resulting from past actions. If a Phase 1 identifies potential hazardous substances, a Phase II is usually conducted to confirm the absence, or presence and extent, of contamination. Phase II involve the collection and analysis of samples. And Phase III is to remediate the contaminated soils determined by Phase I and Phase II. However, important factors in determining whether a assessment standard is site-specific and suitable are (1) the spatial extent of the sampling and the size of the sample area; (2) the number of samples taken: (3) the strategy of taking samples: and (4) the way the data are analyzed. Although selected methods are recommended, application of quantitative methods is directed by users having prior training or experience for the dynamic site investigation process.