• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.803-804
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• 2023

본 논문은 외국인 근로자의 여권 위변조를 탐지하기 위해 MRZ 코드와 발광 데이터를 활용하는 방법을 제안하고 구현한 것이다. 이 기술은 외국인 근로자의 보호와 국내 안보 강화, 금융 거래의 안전성 향상을 지원하며, 웹 기반 인터페이스를 통해 실시간 판별과 사용자 편의성을 제공한다. 이로써 여권 위변조로 인한 잠재적인 위험을 예방하고 국내 여행 및 비즈니스 환경을 향상시킬 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.27-30
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• 2024

A digital platform government without boundaries between the public and private sectors and between government ministries is impossible without national data management. Logical verification was carried out in this study following the definition of the national data management system's purpose, elements, and mode of implementation. Specifically, it was broken down into three dimensions in an effort to review different aspects: the management subject, the management method, and the designation target of national data. Finally, a description of the national master data management system and organization was given. The direction for the implementation of the digital platform government will be presented by this study.

• Geophysics and Geophysical Exploration
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• v.19 no.3
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• pp.145-152
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• 2016

We used graphics processing units for an efficient time-domain 3D wave propagation modeling. Since graphics processing units are designed for massively parallel processes, we need to optimize the calculation and memory management to fully exploit graphics processing units. We focused on the memory management and examined the performance of programs with respect to the memory management methods. We also tested the effects of memory transfer on the performance of the program by varying the order of finite difference equation and the size of velocity models. The results show that the memory transfer takes a larger portion of the running time than that of the finite difference calculation in programs transferring whole 3D wavefield.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.80-88
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• 2019

Recently, automobile manufacturing companies, which are major customers of them, are requiring IATF 16949 (ISO/TS 16949) certification as a mandatory requirement to secure product quality. In particular, IATF 16949 : 2016, revised in October 2016, was reinforced product traceability requirements for production information management by lot in the production process. Therefore, small and medium-sized precision parts processing companies in the automobile industry are very difficult to survive due to quality and price competition for customers satisfaction. MES (Manufacturing Execution System) is required to solve this problem. However, small and medium sized precision parts processing enterprises are reluctant to introduce the MES which is not suitable for the manufacturing environment of them such as high cost and low utilization. Even if the system is introduced, it is difficult to operate and maintain the system because the lack of computer manpower. In this paper, we propose a method for building a lot tracking system for small and medium precision parts processing companies by reviewing relevant literature and analyzing cases. In addition, by managing the production history for each lot of the final product in the system, we will grasp the effect of reducing the quality failure cost obtained by minimizing the range of defect selection.

• Information Systems Review
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• v.1 no.1
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• pp.75-100
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• 1999

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.499-509
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• 2018

Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.55-61
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• 2005

We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

• ETRI Journal
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• v.44 no.5
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• pp.849-858
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• 2022

Dynamic voltage frequency scaling (DVFS) has been widely adopted for runtime power management of various processing units. In the case of neural processing units (NPUs), power management of neural network applications is required to adjust the frequency and voltage every layer to consider the power behavior and performance of each layer. Unfortunately, DVFS is inappropriate for layer-wise run-time power management of NPUs due to the long latency of voltage scaling compared with each layer execution time. Because the frequency scaling is fast enough to keep up with each layer, we propose a layerwise dynamic frequency scaling (DFS) technique for an NPU. Our proposed DFS exploits the highest frequency under the power limit of an NPU for each layer. To determine the highest allowable frequency, we build a power model to predict the power consumption of an NPU based on a real measurement on the fabricated NPU. Our evaluation results show that our proposed DFS improves frame per second (FPS) by 33% and saves energy by 14% on average, compared with DVFS.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.239-251
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• 2024

Coronavirus disease 2019 (COVID-19) has severely curtailed travelers' willingness to carpool and complicated the psychological processing system of travelers' carpooling decisions. In the post-COVID-19 era, a two-stage decision model under dynamic decision scenarios is constructed by tracking the psychological states of subjects in the face of multi-scenario carpooling decisions. Through a scenario experiment method, this paper investigates how three psychological variables, travelers' psychological distance to COVID-19, anticipated regret, and experienced regret about carpooling decisions, affect their willingness to carpool and re-carpool. The results show that in the initial carpooling decision, travelers' perception gap of anticipated regret positively predicts carpooling willingness and partially mediates between psychological distance to COVID-19 and carpooling willingness; in the re-carpooling decision, travelers' perception gap of anticipated regret mediates in the process of experienced regret influencing re-carpooling willingness; the inhibitory effect of experienced regret on carpooling in the context of COVID-19 is stronger than its facilitative effect on carpooling willingness. This paper tries to offer a fact-based decision-processing system for travelers.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.161-171
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• 1999

Query language has been widely used as a convenient tool to obtain information from a database. However, users demand more intelligent query processing systems that can understand the intent of an imprecise query and provide additional useful information as well as exact answers. This paper introduces a meta-database and presents a query processing mechanism that supports a variety of intelligent queries in a consistent and integrated way. The meta-database extracts data abstraction knowledge from an underlying database on the basis of a multilevel knowledge representation framework KAH. In cooperation with the underlying database, the meta-database supports four types of intelligent queries that provide approximately or conceptually equal answers as well as exact ones.