• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.524-530
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• 2015

A log is for text monitoring and perceiving the issues of a system during the development and operation of a program. Based on the log, system developers and operators can trace the cause of an issue. In the development phase, it is relatively simple for a log to be traced while there are only a small number of personnel uses of a system such as developers and testers. However, it is the difficult to trace a log when many people can use the system in the operation phase. In major cases, because a log cannot be tracked, even tracing is dropped. This study proposed a simplified tracing of a log during the system operation. Thus, the purpose is to create a log on the run time based on an ID/IP, using features provided by the Logback. It saves an ID/IP of the tracking user on a DB, and loads the user's ID/IP onto the memory to trace once WAS starts running. Before the online service operates, an Interceptor is executed to decide whether to load a log file, and then it generates the service requested by a certain user in a separate log file. The load is insignificant since the arithmetic operation occurs in a JVM, although every service must pass through the Interceptor to be executed.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.570-581
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• 2015

In recent years, many institutions predict that cloud services and big data will be popular IT trends in the near future. A number of leading IT vendors are focusing on practical solutions and services for cloud and big data. In addition, cloud has the advantage of unrestricted in selecting resources for business model based on a variety of internet-based technologies which is the reason that provisioning and virtualization technologies for active resource expansion has been attracting attention as a leading technology above all the other technologies. Big data took data prediction model to another level by providing the base for the analysis of unstructured data that could not have been analyzed in the past. Since what cloud services and big data have in common is the services and analysis based on mass amount of data, efficient operation and designing of mass data has become a critical issue from the early stage of development. Thus, in this paper, I would like to establish data processing architecture based on technological requirements of mass data for cloud and big data services. Particularly, I would like to introduce requirements that must be met in order for distributed file system to engage in cloud computing, and efficient compression technology requirements of mass data for big data and cloud computing in terms of cost-saving, as well as technological requirements of open-source-based system such as Hadoop eco system distributed file system and memory database that are available in cloud computing.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.332-340
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• 2003

XML is an emerging internet standard for data representation and exchange on the web. Recently, many researches on storing XML documents are in progress. Since XML documents have an implicit semantic schema, it is difficult to store XML data into a DBMS or File System. This paper introduces XDOM, object repositories for the DOM object, which stores an object for persistency support. As XDOM does not require the burdensome design of a fixed schema unlike the legacy DBMS, can store schema-less XML documents. And it can help XML applications to access the DOM object transparently from the object repositories below memory. XDOM introduced in this paper is implemented in pure Java and evaluated using experiments.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.91-117
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• 2007

This study was to compare the contents and practical problems addressed, the process of teaching-learning method, and evaluation method of Korean Home Economics curriculum and of the Oregon and Ohio's Practical Problem Focused Family & Consumer Sciences Curricula. The results are as follows. First, contents of Korean curriculum are organized by major sub-concepts of Home Economics academic discipline whereas curricular of both Oregon and Ohio states are organized by practical problems. Oregon uses the practical problems which integrate multi-subjects and Ohio uses ones which are good for the contents of the module by integrating concerns or interests which are lower or detailed level (related interests). Since it differentiates interest and module and used them based on the basic concept of Family and Consumer Science, Ohio's approach could be easier for Korean teachers and students to adopt. Second, the teaching-learning process in Korean home economics classroom is mostly teacher-centered which hinders students to develop higher order thinking skills. It is recommended to use student-centered learning activities. State of Oregon and Ohio's teaching-learning process brings up the ability of problem-solving by letting students clearly analyze practical problems proposed, solve problems by themselves through group discussions and various activities, and apply what they learn to other problems. Third, Korean evaluation system is heavily rely on summative evaluation such as written tests. It is highly recommended to facilitate various performance assessment tools. Since state of Oregon and Ohio both use practical problems, they evaluate students mainly based on their activity rather than written tests. The tools for evaluation include project documents, reports of learning activity, self-evaluation, evaluation of discussion activity, peer evaluation in a group for each students for their performance, assessment about module, and written tests as well.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.151-160
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• 2005

The exponential growth of Web users requires the web serves with high expandability and reliability. It leads to the excessive transmission traffic and system overload problems. To solve these problems, cluster systems are widely studied. In conventional cluster systems, when the request size is large owing to such types as multimedia and CGI, the particular server load and response time tend to increase even if the overall loads are distributed evenly. In this paper, a cluster system is proposed where each Web server in the system has different contents and loads are distributed efficiently using the Web server resource information such as CPU, memory and disk utilization. Web servers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Load unbalance among contents group owing to distribution of contents can be alleviated by reassignment of Web servers. Using a simulation method, we showed that our method shows up to $50\%$ about average throughput and processing time improvement comparing to systems using each LC method and RR method.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.20-25
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• 2016

With the advent of the era of digital big data, the Hadoop platform has become widely used in various fields. However, the Hadoop MapReduce framework suffers from problems related to the increase of the name node's main memory and map tasks for the processing of large number of small files. In addition, a method for running C++-based tasks in the MapReduce framework is required in order to conjugate GPUs supporting hardware-based data parallelism in the MapReduce framework. Therefore, in this paper, we present a face detection system that generates a sequence file for images to process big data for images in the Hadoop platform. The system also deals with tasks for GPU-based face detection in the MapReduce framework using Hadoop Pipes. We demonstrate a performance increase of around 6.8-fold as compared to a single CPU process.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.54-62
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• 2015

Although NAND flash-based SSD (Solid-State Drive) provides superior performance in comparison to HDD (Hard Disk Drive), it has a major drawback in write endurance. As a result, the lifetime of SSD is determined by the workload and thus it becomes a big challenge in current technology trend of such as the shifting from SLC (Single Level Cell) to MLC (Multi Level cell) and even TLC (Triple Level Cell). Most previous studies have dealt with wear-leveling or improving SSD lifetime regarding hardware architecture. In this paper, we propose the optimal configuration of host I/O stack focusing on file system, I/O scheduler, and link power management using JEDEC enterprise workloads in terms of WAF (Write Amplification Factor) which represents the efficiency perspective of SSD life time especially for host write processing into flash memory. Experimental analysis shows that the optimum configuration of I/O stack for the perspective of SSD lifetime is MinPower-Dead-XFS which prolongs the lifetime of SSD approximately 2.6 times in comparison with MaxPower-Cfq-Ext4, the best performance combination. Though the performance was reduced by 13%, this contributions demonstrates a considerable aspect of SSD lifetime in relation to I/O stack optimization.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.477-482
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• 2016

This paper presents a new method of parity storing for ECC(error correcting code) in SSD (solid-state drive) and suitable structure of the controller. In general usage of NAND flash memory, we partition a page into data and spare area. ECC parity is stored in the spare area. The method has overhead on area and timing due to access of the page memory discontinuously. This paper proposes a new parity policy storing method that reduces overhead and R(read)/W(write) timing by using whole page area continuously without partitioning. We analyzed overhead and R/W timing. As a result, the proposed parity storing has 13.6% less read access time than the conventional parity policy with 16KB page size. For 4GB video file transfer, it has about a minute less than the conventional parity policy. It will enhance the system performance because the read operation is key function in SSD.

• Journal of the Korea Computer Graphics Society
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• v.19 no.1
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• pp.11-20
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• 2013

This paper introduces a user interface for large 3D meshes in mobile systems, which have limited memory, screen size and battery power. A large 3D mesh is divided into partitions and simplified in multi-resolutions so a large file is transformed into a number of small data files and saved in a PC server. Only selected small files specified by the user are hierarchically transmitted to the mobile system for 3D browsing and rendering. A 3D preview in a pop-up shows a simplified mesh in the lowest resolution. The next step displays simplified meshes whose resolutions are automatically controlled by the user interactions. The last step is to render a set of detailed original partitions in a selected range. As a result, while minimizing using mobile system resources, our interface enables us to browse and display 3D meshes in mobile systems through real-time interactions. A mobile 3D viewer and a 3D app are also presented to show the utility of the proposed user interface.