• Journal of the Korean earth science society
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• v.34 no.6
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• pp.588-601
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• 2013

In geophysics and geophysical exploration fields, we can use information about inclination and azimuth in various ways. These include borehole deviation logging for inversion process, real-time data acquisition system, geophysical monitoring system, and so on. This type of information is also necessarily used in the directional drilling of shale gas fields. We thus need to develop a subminiature, low-powered, multi-functional inclination and azimuth measurement system for geophysical exploration fields. In this paper, to develop real-time measurement system, we adopt the high performance low power Micro Control Unit (made with state-of-the-art Complementary Metal Oxide Semiconductor technology) and newly released Micro Electro Mechanical Systems Attitude Heading Reference System sensors. We present test results on the development of a multifunctional real-time inclination and azimuth measurement system. The developed system has an ultra-slim body so as to be installed in 42mm sonde. Also, this system allows us to acquire data in real-time and to easily expand its application by synchronizing with a depth encoder or Differential Global Positioning System.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.863-872
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• 2015

Kernel rootkit is recognized as one of the most severe and widespread threats to corrupt the integrity of an operating system. Without an external monitor as a root of trust, it is not easy to detect kernel rootkits which can intercept and modify communications at the interfaces between operating system components. To provide such a monitor isolated from an operating system that can be compromised, most existing solutions are based on external hardware. Unlike those solutions, we develop a kernel introspection system based on the ARM TrustZone technology without incurring extra hardware cost, which can provide a secure memory space in isolation from the rest of the system. We particularly use a secure timer to implement an autonomous switch between secure and non-secure modes. To ensure integrity of reference, this system measured reference from vmlinux which is a kernel original image. In addition, the flexibility of monitoring block size can be configured for efficient kernel introspection system. The experimental results show that a secure kernel introspection system is provided without incurring any significant performance penalty (maximum 6% decrease in execution time compared with the normal operating system).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.423-430
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• 2013

Recently, the personal identification technologies using vein pattern of back of the hand, palm, and finger have been developed actively because it has the advantage that the vein blood vessel in the body is impossible to damage, make a replication and forge. However, it is difficult to extract clearly the vein region from captured vein images through common image prcessing based region segmentation method, because of the light scattering and non-uniform internal tissue by skin layer and inside layer skeleton, etc. Especially, it takes a long time for processing time and makes a discontinuity of blood vessel just in a image because it has non-uniform illumination due to use a locally different adaptive threshold for the binarization of acquired finger-vein image. To solve this problem, we propose illumination normalization based fast method for extracting the finger-vein region. The proposed method has advantages compared to the previous methods as follows. Firstly, for remove a non-uniform illumination of the captured vein image, we obtain a illumination component of the captured vein image by using a low-pass filter. Secondly, by extracting the finger-vein path using one time binarization of a single threshold selection, we were able to reduce the processing time. Through experimental results, we confirmed that the accuracy of extracting the finger-vein region was increased and the processing time was shortened than prior methods.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.349-358
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• 2007

Ethernet Passive Optical Network(EPON), which is one of PON technologies for realizing FTTx(Fiber-To-The-Curb/Home/Office), can cost-effectively construct optical access networks. In addition, EPON can provide high transmission rate up to 10Gbps and it is compatible with existing customer devices equipped with Ethernet card. To effectively control frame transmission from ONUs to OLT EPON can use Multi-Point Control Protocol(MPCP) with additional control functions in addition to Media Access Control(MAC) protocol function. For EPON, many researches on intra- and inter-ONU scheduling algorithms have been performed. Among the inter-ONU scheduling algorithms, IPS(Interleaved Polling with Stop) based on polling scheme is efficient because OLT assigns available time portion to each ONU given the request information from all ONUs. Since the IPS needs an idle time period on uplink between two consecutive frame transmission periods, it wastes time without frame transmissions. In this paper, we propose a dynamic bandwidth allocation algorithm to increase the channel utilization on uplink and evaluate its performance using simulations. The simulation results show that the proposed Two-phase Cycle Danamic Bandwidth Allocation(TCDBA) algorithm improves the throughput about 15%, compared with the IPS and Fast Gate Dynamic Bandwidth Allocation(FGDBA). Also, the average transmission time of the proposed algorithm is lower than those of other schemes.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.271-281
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• 2006

Recently the need for Location-Based Service (LBS) has increased due to the development and widespread use of the mobile devices (e.g., PDAs, cellular phones, labtop computers, GPS, and RFID etc). The core technology of LBS is a moving-objects database that stores and manages the positions of moving objects. To search for information quickly, the database needs to contain an index that supports both real-time position tracking and management of large numbers of updates. As a result, the index requires a structure operating in the main memory for real-time processing and requires a technique to migrate part of the index from the main memory to disk storage (or from disk storage to the main memory) to manage large volumes of data. To satisfy these requirements, this paper suggests a unified index scheme unifying the main memory and the disk as well as migration policies for migrating part of the index from the memory to the disk during a restriction in memory space. Migration policy determines a group of nodes, called the migration subtree, and migrates the group as a unit to reduce disk I/O. This method takes advantage of bulk operations and dynamic clustering. The unified index is created by applying various migration policies. This paper measures and compares the performance of the migration policies using experimental evaluation.

• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.614-630
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• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.117-127
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• 2001

The Main object of this research is directed to LG Oil company harbor in kwangyang-hang, where various ships ranging from 300 ton to 48000ton DWT use seven berths in the harbor. This harbor suffered from inefficient and unsafe management procedures since it is difficult to set guidelines for arrival and departure of ships according to the weather conditions and the current guidelines dose not offer clear basis of its implications. Therefore, it has long been suggested that these guidelines should be improved. This paper proposes a decision-support system, which can quantitatively decide the possibility of entry or departure on a harbor by analyzing the weather conditions (wind, current, and wave) and taking account of factors such as harbor characteristics, ship characteristics, weight condition, and operator characteristics. This system has been verified using 5$_{th}$ and 7$_{th}$ berth in Kwangyang-hang harbor. Machine learning technique using genetic programming(GP) is introduced to the system to quantitatively decide and produce results about the possibility of entry or arrival, and weighted linear associative memory (WLAM) method is also used to reduce the amount of calculation the GP has to perform. Group of additive genetic programming trees (GAGPT) is also used to improve learning performance by making it easy to find global optimum.mum.

• Journal of the Korean Society for information Management
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• v.37 no.3
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• pp.25-50
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• 2020

Since big data platform services for the public library began January 1, 2016, libraries have used big data to improve their work performance. This paper aims to examine the use cases of library big data and attempts to draw improvement plan to improve the effectiveness of library big data. For this purpose, first, we examine big data used while utilizing the library big data platform, the usage pattern of big data and services/policies drawn by big data analysis. Next, the limitations and advantages of the library big data platform are examined by comparing the data analysis of the integrated library management system (ILUS) currently used in public libraries and data analysis through the library big data platform. As a result of case analysis, big data usage patterns were found program planning and execution, collection, collection, and other types, and services/policies were summarized as customizing bookshelf themes for the book curation and reading promotion program, increasing collection utilization, and building a collection based on special topics. and disclosure of loan status data. As a result of the comparative analysis, ILUS is specialized in statistical analysis of library collection unit, and the big data platform enables selective and flexible analysis according to various attributes (age, gender, region, time of loan, etc.) reducing analysis time. Finally, the limitations revealed in case analysis and comparative analysis are summarized and suggestions for improvement are presented.

• Journal of KIISE:Information Networking
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• v.34 no.2
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• pp.120-133
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• 2007

A multicast tree includes several, possibly a large number of, paths connecting source-receiver pairs, and network failure may disable part of the multicast tree. Reconstruction of the entire multicast tree to recover from a component failure is highly undesirable, because some group members have to suffer service disruptions even though the communication paths to/from them are not affected by the failure. To limit reconfiguration region and to maximize the likelihood of successful reconfiguration, we propose and evaluate a pre-planned reconfiguration policy for QoS multicast sessions. Specifically, we equip a reconfiguration path (RP) with each end-to-end path that connects a source-receiver pair in the multicast tree, and reserve resources in advance along the RPs. Efficient resource-sharing techniques are applied to reduce the amount of resources reserved for RPs but not used in the absence of failures. This way, we prevent uncontrolled competition among different multicast sessions which may simultaneously try to recover from failures. We evaluate the performance of the proposed scheme using simulation on randomly-generated networks. We use the shortest-path routing for QoS multicast sessions, and simulate both source-based and shared multicast trees. The evaluation results indicates that successful pre-planned reconfiguration can be achieved for all group members with reasonable overhead. Our scheme is also shown to adapt well to dynamic changes of group membership.