• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1338-1343
• /
• 2003

Data is the expression of the language or numerical values that show some characteristics. And information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns and make decisions. Today, knowledge extraction and application of the knowledge are broadly accomplished to improve the comprehension and to elevate the performance of systems in several industrial fields. The knowledge extraction could be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge can be drawn by rules. Clustering (CU, input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for expression the knowledge by rules. In this paper, the various approaches of the knowledge extraction are examined by categories that separate the methods by the applied industrial fields. Also, the several test data and the experimental results are compared and analysed based upon the applied techniques that include CL, ISP, NF, NN, EM, and so on.

• Journal of Communications and Networks
• /
• v.6 no.3
• /
• pp.258-268
• /
• 2004

We demonstrate rotationally invariant space-time (ST) trellis codes with a 4-D rectangular signal constellation for data transmission over fading channels using two transmit antennas. The rotational invariance is a good property to have that may alleviate the task of the carrier phase tracking circuit in the receiver. The transmitted data stream is segmented into eight bit blocks and quadrature amplitude modulated using a 256 point 4-D signal constellation whose 2-D constituent constellation is a 16 point square constellation doubly partitioned. The 4-D signal constellation is simply the Cartesian product of the 2-D signal constellation with it-self and has 32 subsets. The partition is performed on one side into four subsets A, B, C, and D with increased minimum-squared Euclidian distance, and on the other side into four rings, where each ring includes four points of equal energy. We propose both linear and nonlinear ST trellis codes and perform simulations using an appropriate multiple-input multiple-output (MIMO) channel model. The 4-D ST codes constructed here demonstrate about the same frame error rate (FER) performance as their 2-D counterparts, having however the added value of rotational invariance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.2
• /
• pp.99-107
• /
• 2024

The recent digital transformation in many industries has led to an explosion of data, which has exponentially increased the amount of data that companies need to generate and process. As a result, enterprises are leveraging ERP systems to manage and analyze large amounts of data in real time. However, due to cost and time issues in processing large amounts of data in existing ERP systems, it is essential to apply data archiving technology that can compress and store data in real time in existing systems. Therefore, this paper aims to identify the trends of the target technology by utilizing patent data on ERP-based real-time data archiving technology, analyze the core patents, and create new core patents based on them.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.4B
• /
• pp.646-680
• /
• 2000

In this paper, we discuss the design and implementation of a concurrency control manager for a main memory DBMS(MMDBMS). Since an MMDBMS, unlike a disk-based DBMS, performs all of data update or retrieval operations by accessing main memory only, the portion of the cost for concurrency control in the total cost for a data update or retrieval is fairly high. Thus, the development of an efficient concurrency control manager highly accelerates the performance of the entire system. Our concurrency control manager employs the 2-phase locking protocol, and has the following characteristics. First, it adapts the partition, an allocation unit of main memory, as a locking granule, and thus, effectively adjusts the trade-off between the system concurrency and locking cost through the analysis of applications. Second, it enjoys low locking costs by maintaining the lock information directly in the partition itself. Third, it provides the latch as a mechanism for physical consistency of system data. Our latch supports both of the shared and exclusive modes, and maximizes the CPU utilization by combining the Bakery algorithm and Unix semaphore facility. Fourth, for solving the deadlock problem, it periodically examines whether a system is in a deadlock state using lock waiting information. In addition, we discuss various issues arising in development such as mutual exclusion of a transaction table, mutual exclusion of indexes and system catalogs, and realtime application supports.

• The KIPS Transactions:PartA
• /
• v.14A no.7
• /
• pp.443-450
• /
• 2007

Performance scalability and storage scalability become important in a large scale cluster of wireless internet proxy cache servers. Performance scalability means that the whole performance of the cluster increases linearly according as servers are added. Storage scalability means that the total size of cache storage in the cluster is constant, regardless of the number of cache servers used, if the whole cache data are partitioned and each partition is stored in each server, respectively. The Round-Robin based load balancing method generally used in a large scale server cluster shows the performance scalability but no storage scalability because all the requested URL data need to be stored in each server. The hashing based load balancing method shows storage scalability because all the requested URL data are partitioned and each partition is stored in each server, respectively. but, it shows no performance scalability in case of uneven pattern of client requests or Hot-Spot. In this paper, we propose a novel dynamic hashing method with performance and storage scalability. In a time interval, the proposed scheme keeps to find some of requested URLs allocated to overloaded servers and dynamically reallocate them to other less-loaded servers. We performed experiments using 16 PCs and experimental results show that the proposed method has the performance and storage scalability as different from the existing hashing method.

• Journal of Environmental Health Sciences
• /
• v.44 no.6
• /
• pp.548-555
• /
• 2018

Objectives: We conducted ecological risk assessment for cadmium, a heavy metal and carcinogen, to identify safety standards by environmental media and to determine its impact on ecosystems by estimating and evaluating exposure levels. Methods: Species sensitivity distributions (SSDs) were generated using ECOTOX DB. A hazardous concentration of 5% (HC5) protective of most species (95%) in the environment was estimated. Using this estimate, predicted no effect concentrations (PNECs) were calculated for aquatic organisms. Based on the calculated PNECs for aquatic organisms, PNEC values for soil and sediment were calculated using the partition coefficient. Predicted exposure concentrations (PECs) were also calculated from environmental monitoring data with hazard quotients (HQs) calculated using PNECs for environmental media. Results: Chronic toxicity data were categorized into four groups and 11 species. In species sensitivity distribution (SSD) analysis, HC5 was $0.340{\mu}g/L$. Based on this value, the PNEC value for aquatic organisms was calculated as $0.113{\mu}g/L$. PNEC values for soil and sediments using a partition coefficient were calculated as 15.02 mg/kg and 90.61 mg/kg, respectively. In an analysis of environmental monitoring data, PEC values were calculated as $0.017{\mu}g/L$ for water, 1.01 mg/kg for soil, and 0.521 mg/kg for sediment. Conclusions: HQs were 0.150, 0.067 and 0.006 for water, soil and sediment, respectively. HQs of secondary toxicity were 0.365 for birds and 0.024 for mammals. In principle, it is judged that an HQ above 1 indicates a high level of risk concern while an HQ less than 1 indicates an extremely low level of risk concern. Therefore, with HQs of cadmium in the environment being <1, its risk levels can be considered low for each media.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.8
• /
• pp.1505-1510
• /
• 2008

In large-scale wireless sensor networks, the deployed nodes cannot be replaced or recharged after first deployment. Also, dead nodes maγ lead to the partition of whole networks. While performing data dissemination under a battery power constraint, energy efficiency is a key design factor of routing protocol. As a solution for the efficient data dissemination, in this paper, we propose a protocol namely Hierarchical Data Dissemination (HDD) which provides scalable and efficient data delivery to multiple sources and mobile sinks. HDD uses the facts that sink nodes are central gathering Points and source-centric data forwarding paths are constructed and it is maintained with two-tier communications. The performance of HDD is compared with TTDD about the energy consumption, data delivery time and data success ration. The extensive simulation results show that HDD Routing Protocol outperforms TIDD by more than $1.5{\sim}3times$ on energy consumption.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.8
• /
• pp.535-544
• /
• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.443-446
• /
• 2007

The major purpose of the present study is to gauge the general applicability of cadastral surveying and LiDAR surveying. LiDAR survey is the method which obtains Geospatial information of the terrain. We will get a most topographic models at Digital Elevation Model(DEM) using LiDAR survey data. Also, we will consider both the surface parcel partition and volume parcel as a part of Geospatial relationship model. This study will focus on enhancing the efficiency and analysis of continual cadastral map and LiDAR DEM. I would like to close by proposing that LiDAR surveying will contribute in cadastral surveying.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.5
• /
• pp.1527-1535
• /
• 2012

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.