• Title/Summary/Keyword: Merge types

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A Parallel Algorithm for Image Segmentation on Mesh-connected MIMD System

  • Jeon, Byeong-Moon;Jeong, Chang-Sung
    • Journal of Korea Society of Industrial Information Systems
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    • v.3 no.1
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    • pp.258-268
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    • 1998
  • This paper presents two sequential advanced split and merge algorithms and a parallel image segmentation algorithm based on them. First, the two advanced methods are obtained from the combination of edge detection and classic split and merge to solve the inherent problems of the classical method. Besides, the parallel image segmentation algorithm on mesh-connected MIMD system considers three types in the merge stage to reduce the communication overhead between processors, such as intraprocessor merge, interprocessor with boundary merge, and interprocessor without boundary merge. Finally , we prove that the proposed algorithms achieve the improved performance by implementing them.

A Boolean Equivalence Testing Algorithm based on a Derivational Method

  • Moon, Gyo-Sik
    • Journal of Electrical Engineering and information Science
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    • v.2 no.5
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    • pp.1-8
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    • 1997
  • The main purpose of the Boolean equivalence problem is to verify that two Boolean expressions have the same functionality. Simulation has been extensively used as the standard method for the equivalence problem. Obviously, the number of tests required to perform a satisfactory coverage grows exponentially with the number of input variables. However, formal methods as opposed to simulation are getting more attention from the community. We propose a new algorithm called the Cover-Merge Algorithm based on a derivational method using the concept of cover and merge for the equivalence problem and investigate its theoretical aspects. Because of the difficulty of the problem, we emphasize simplification techniques in order to reduce the search space or problem size. Heuristics based on types of merges are developed to speed up the derivation process by allowing simplifications. In comparison with widely used technique called Binary Decision Diagram or BDD, the algorithm proposed outperforms BDD in nearly all cases of input including standard benchmark problems.

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An Empirical Analysis of the Characteristics of Acquiring Manufacturing Firms in Korea : The Focus on Environmental Factors and Firm Performance (합병한 국내 제조기업들의 특징에 관한 실증적 연구 : 환경적 요인과 기업성과를 중심으로)

  • Lee, Younsuk;Park, Soohoon
    • Korean Management Science Review
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    • v.32 no.2
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    • pp.91-109
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    • 2015
  • The M&A of firms has been emerged as the effective means of fast diversification and growth in dynamic environment. However, the empirical research about M&A in Korea has not been implemented rich due to the difficulty of obtaining M&A data. In this research, we empirically investigate the relationships among M&A, environment and firms' performance focused on Korean manufacturing firms, understanding the current practice of M&A in Korea. We use the Manufacturing Productivity Panel Survey Data, which are collected by Korea Productivity Center in 2013. The sample size is 575 and the sample is divided into M&A group and non-M&A group. We conduct logit analysis with the independent variables of environment factors (munificence, dynamic, uncertainty), and firms' performance (sales growth, ROS, labor productivity and Inventory turnover), and dependent variable of M&A group or non M&A group. The results show that M&A is closely related to environment feature and firm performance: M&A firms are likely to be the higher munificence and dynamic and the lower sales growth and higher profitability than non-M&A group. In addition, we also examine the characteristics of firms by M&A types (competitors, customer/supplier and firms from unrelated industry). These results imply that if firms confront the pressure of uncertainty (dynamic) and the lower growth, they tend to choose M&A. Futhermore, to profoundly understand the behavior of firms about M&A, it is required to classify the M&A firms by merge types.

Rule Based System for Selection of Foundation Types of Building Structures (건물의 기초 형식 선정을 위한 규칙 기반 시스템)

  • 김한수;최창근
    • Computational Structural Engineering
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    • v.9 no.1
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    • pp.23-32
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    • 1996
  • A rule based system for foundation design of building structures is developed with CLIPS in this study. The types of foundation and the allowable bearing capacity of supporting soil inferred by the rule based system for selection of foundation type, called SOFTEX, are transferred to a structural design program for building foundation. The allowable bearing capacity is calculated with N values of Standard Penetration Test. The foundation types such as independent spread footing, wall footing, combined footing and mat foundation can be inferred by the foundation merge procedure developed in this study. This procedure is based on the analysis data from the super structure and the estimated bearing capacity. By using this integrated system, structural engineers with less experience in foundation design can design the foundation system for the given superstructure and the site condition with relative ease.

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A Tombstone Filtered LSM-Tree for Stable Performance of KVS (키밸류 저장소 성능 제어를 위한 삭제 키 분리 LSM-Tree)

  • Lee, Eunji
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.4
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    • pp.17-22
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    • 2022
  • With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

Assessing the Effects of Knowledge Resource Complementarity on Organizational Performance in Merge and Acquisition (M&A): Focused on Electronic Commerce Industries (인수합병에 있어 지식자원 간 상호보완성이 인수합병성과에 미치는 영향 분석: 전자상거래 산업을 중심으로)

  • Choi, Byounggu
    • Knowledge Management Research
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    • v.14 no.1
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    • pp.95-119
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    • 2013
  • Although merger and acquisition (M&A) has been considered as an important means to improve firm performance, most prior empirical research have failed to prove the relationship between M&A and firm performance. In order to fill this gap, this study attempts to identify the effect of M&A on firm performance based on knowledge resources relatedness and complementarity theory. For this purpose, this study examines complementarity patterns of knowledge resources and their impacts on acquirer's performance using M&A announcements of electronic commerce industry from 2001 to 2007. The results of this study indicate complementarity among knowledge resources are positively related with acquirer's market value. This study contributes to expand knowledge management research by identifying the relationship among knowledge resources and their impacts on firm performance.

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Land Cover Clustering of NDVI-drived Phenological Features

  • Kim, Dong-Keun;Suh, Myoung-Seok;Park, Kyoung-Yoon
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.201-206
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    • 1998
  • In this paper, we have considered the method for clustering land cover types over the East Asia from AVHRR data. The feature vectors such that maximum NDVI, amplitude of NDVI, mean NDVI, and NDVI threshold are extracted from the 10-day composite by maximum value composite(MVC) for reducing the effect of cloud contaninations. To find the land cover clusters given by the feature vectors, we are adapted the self-organizing feature map(SOFM) clustering which is the mapping of an input vector space of n-dimensions into a one - or two-dimensional grid of output layer. The approach is to find first the clusters by the first layer SOFM and then merge several clusters of the first layer to a large cluster by the second layer SOFM. In experiments, we were used the 8-km AVHRR data for two years(1992-1993) over the East Asia.

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Performance Evaluation of SSD-Index Maintenance Schemes in IR Applications

  • Jin, Du-Seok;Jung, Hoe-Kyung
    • Journal of information and communication convergence engineering
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    • v.8 no.4
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    • pp.377-382
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    • 2010
  • With the advent of flash memory based new storage device (SSD), there is considerable interest within the computer industry in using flash memory based storage devices for many different types of application. The dynamic index structure of large text collections has been a primary issue in the Information Retrieval Applications among them. Previous studies have proven the three approaches to be effective: In- Place, merge-based index structure and a combination of both. The above-mentioned strategies have been researched with the traditional storage device (HDD) which has a constraint on how keep the contiguity of dynamic data. However, in case of the new storage device, we don' have any constraint contiguity problems due to its low access latency time. But, although the new storage device has superiority such as low access latency and improved I/O throughput speeds, it is still not well suited for traditional dynamic index structures because of the poor random write throughput in practical systems. Therefore, using the experimental performance evaluation of various index maintenance schemes on the new storage device, we propose an efficient index structure for new storage device that improves significantly the index maintenance speed without degradation of query performance.

Merged-Packet based Effective Queuing Mechanism for Underwater Networks (결합패킷 활용기반 수중네트워크 전송 큐 관리 기법)

  • Shin, Soo Young;Park, Soo-Hyun;Namgung, Jung Il
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.2
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    • pp.61-67
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    • 2017
  • In this paper, an adaptive MAC technique for various underwater environment with narrow-bandwidth and low transmission speed was proposed. In previously published Underwater Packet Flow Control (UPFC) technique, three transmission types (normal, block and parallel transmission) had been proposed using the number of transmission and transmission time. In addition to the UPFC, the proposed technique is an improved version of UPFC having more effective queuing technique for merge transmission. A mathematical model of the proposed queuing theory was constructed and its increased efficiency per unit transmission number was also verified based on simulations.

SVM-based Utterance Verification Using Various Confidence Measures (다양한 신뢰도 척도를 이용한 SVM 기반 발화검증 연구)

  • Kwon, Suk-Bong;Kim, Hoi-Rin;Kang, Jeom-Ja;Koo, Myong-Wan;Ryu, Chang-Sun
    • MALSORI
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    • no.60
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    • pp.165-180
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    • 2006
  • In this paper, we present several confidence measures (CM) for speech recognition systems to evaluate the reliability of recognition results. We propose heuristic CMs such as mean log-likelihood score, N-best word log-likelihood ratio, likelihood sequence fluctuation and likelihood ratio testing(LRT)-based CMs using several types of anti-models. Furthermore, we propose new algorithms to add weighting terms on phone-level log-likelihood ratio to merge word-level log-likelihood ratios. These weighting terms are computed from the distance between acoustic models and knowledge-based phoneme classifications. LRT-based CMs show better performance than heuristic CMs excessively, and LRT-based CMs using phonetic information show that the relative reduction in equal error rate ranges between $8{\sim}13%$ compared to the baseline LRT-based CMs. We use the support vector machine to fuse several CMs and improve the performance of utterance verification. From our experiments, we know that selection of CMs with low correlation is more effective than CMs with high correlation.

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