• International journal of advanced smart convergence
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• 제10권1호
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.403-411
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• 2021

This study discusses the influence of economic factors on the clothing exports from China and 15 South and Southeast Asian countries to the United States. A basic gravity trade model with three predictors, including the GDP value produced by exporting and importing countries and their geographical distance was established to explain the bilateral trade patterns. The conventional approach of multiple regression and the novel approach of Artificial Neural Networks (ANNs) were developed based on the value of clothing exports from 2012 to 2018 and applied to the trade pattern prediction of 2019. The results showed that ANNs can achieve a more accurate prediction in bilateral trade patterns than the commonly-used econometric analysis of the basic gravity trade model. Future studies can examine the predictive power of ANNs on an extended gravity model of trade that includes explanatory variables in social and environmental areas, such as policy, initiative, agreement, and infrastructure for trade facilitation, which are crucial for policymaking and managerial consideration. More research should be conducted for the examination of the balance between developing countries' economic growth and their social and environmental sustainability and for the application of more advanced machine-learning algorithms of global trade flow examination.

• Journal of Communications and Networks
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• 제13권2호
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• pp.175-186
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• 2011

The proliferation of advanced technologies has been altering our lifestyle and social interactions-the next frontier is the digital home. Although the future of smart homes is promising, many technical challenges must be addressed to achieve convenience and security. In this paper, we delineate the unique combination of security challenges specifically for access control and consider the challenges of how to simply and securely assign access control policies to visitors for home devices and resources. We present a set of intuitive access control policies and suggest four access control settings based on our in-person interview results. Furthermore, we propose the automated Clairvoyant access right assignment (CARA) mechanism that utilizes home owners' social relationship to automatically deduce to which class a visitor belongs. The combination of CARA and the suggested mapping provides a promising first step for home policy assignment such that nonexpert home owners can let visitors use their home network with confidence. We anticipate that future research can build on our proposed mechanisms to provide confidence to non-expert home owners for letting visitors use their home network.

• 한국산학기술학회논문지
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• 제15권4호
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• pp.2393-2398
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• 2014

LTE-Advanced 망을 형성하는 리소스 및 망의 형상(대역, 에러율 등)들이 가변적으로 변하기 때문에 기존 음성서비스에 적용된 절차적이고, 인위적이고, 정적인 제어방식으로는 제어가 불가능하다고 판단하고 있다. 본 연구에서는 정책제어를 기반으로 서비스 연속성을 효과적으로 지원하기 위한 QoS 관리 체계를 제안하고자 한다. 가입자 단말기는 자신의 현재 상태 및 주변 기지국 정보를 수집하고, 기지국은 내부 및 인접한 기지국 모니터링으로 수집된 정보를 통하여, 관련 제어데이터를 공유하고 이를 종합 분석하여 서비스 연속성을 자체적으로 조절/제어하는 방법을 제시한다.

• 대한지리학회지
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• 제29권2호
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• pp.117-136
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• 1994

오늘날 첨단산업의 발전과 더불어 산업의 공간구조 변화가 지역적인 차원은 물론 국제적인 차원에서 일어나고 있으며 신산업지구의 등장은 그 좋은 예라고 볼 수 있다. 신산 업지구는 소기업 중심의 유연적 전문화에 의해서만 형성되는 것이 아니라 생산체계, 생산의 네트워크, 뿌리내림(embeddedness), 기업의 규모 등 4가지 요인과 관련하여 다양한 형태로 형성발전하는 역동성을 가지고 있다. 신산업지구는 기본적으로 네트워크의 유형에 따라 4개 의 기본유형과 5개의 혼합형으로 구분될 수 있는데, 이들은 위의 4가지 요인 외에도 기업간 권한의 계층성, 협력과 경쟁, 제도적 요인, 매몰비용(sunk costs) 등에 의해서 그 특성이 구 분되며 사례를 확인할 수 있다. 9개의 유형은 모두 첨단산업과 관련지을 수 있으나, 첨단산 업의 발전과 더불어 혼합형 산업지구가 형성발전될 가능성이 더 크다. 과거의 산업지구는 역사적 우연성에 의해서 형성되는 경우가 흔하였지만 오늘날 첨단산업과 관련한 산업지구는 정책과 전략이 그 형성과 발전에 중요하다. 따라서 제도적 지원체계의 마련, 매몰비용의 절 감, 국제화에 대한 대응 등의 여러 가지 전략이 추진되어야 신산업지구의 형성과 역동적인 발전이 가능하다.

• 한국도서관정보학회지
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• 제45권2호
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• pp.73-92
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• 2014

학교도서관 헌장은 학교도서관이 나아가야 할 방향과 기본적으로 지켜야 할 방침이나 규범을 열거한 규칙이나 법칙이다. IFLA/UNESCO, IASL, 일본의 학교도서관 헌장을 비교하고 분석해 본 결과 IFLA/UNESCO 학교도서관 헌장은 학교도서관의 임무, 예산 확보와 네트워크, 목적, 직원, 운영 및 관리, 선언의 구현 등으로 구성되어 있는데, 예산 확보와 네트워크를 강조하고 있다. IASL 학교도서관 선언은 학교도서관의 기능, 자료, 시설, 인적자원, 정보활용능력, 정부 및 공공단체의 지원 등을 구성요소로 하고 있는데, 정보활용능력 육성을 강조하고 있다. 일본의 학교도서관 헌장은 학교도서관의 이념, 기능, 직원, 자료, 시설, 운영 등을 구성요소로 하고 있는데, 학교도서관의 이념을 강조하고 있다. IFLA/UNESCO, IASL, 일본의 학교도서관 헌장을 비교하고 분석한 결과를 토대로 우리나라의 학교도서관 헌장은 선진국의 구성요소를 수용하되 학교도서관의 교육적 역할을 강조하여 교육 영역을 별도의 항목으로 하고 학교도서관의 임무, 시설, 인적자원, 교육, 예산, 운영 및 관리, 헌장 구현을 위한 정부의 책임 등을 구성요소로 하는 것이 바람직하겠다.

• Asian Journal of Innovation and Policy
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• 제8권1호
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• pp.1-30
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• 2019

The advent of digitalisation has transformed economies into more integrated, but increasingly complex systems. This new trend has brought dynamic changes in the manufacturing sector through advanced ICT infrastructure, smart factories, digitally-controlled logistics, and skilled ICT-labour. The impacts of the digital economy on manufacturing could be best illustrated through "Industry 4.0." With this wave of technological advancement, countries aim to establish an industrial ecosystem where every manufacturing process and function is connected and interacts through digital networks. Industry 4.0 presents opportunities for Emerging Asia, as the region has emerged as a fast-growing manufacturing hub and particularly a production base for ICT goods. However, growing production capacity, increased exports, and increases in FDI in the field of ICT goods manufacturing have so far contributed little to the development and diffusion of ICT. A huge gap exists in the ICT uptake amongst countries and between small and large firms. This paper highlights the level of Industry 4.0 readiness of Emerging Asia and key factors that determine its enhancement.

• KDI Journal of Economic Policy
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• 제14권2호
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• pp.77-108
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• 1992

흔히 우리의 취약한 기술력은 GNP에 대한 R&D 투자비중이 낮은 것으로 대변되고 있고, 기술개발투자의 확대가 기술력 향상과 동일시되고 있다. 그러나 산업발전단계(産業發展段階)에 따라 개발대상(開發對象) 기술(技術)의 구성(構成)이 달라지므로 선진국에 비해 R&D 비중이 낮다고 하여 반드시 기술개발 노력이 부진한 것은 아니다. 한국(韓國)은 기술개발에 투입할 경제여력이나 그것을 담당할 수 있는 고급 인력의 공급측면에서 선진국에 비해 절대적 열세에 처해 있는만큼, 연구개발투자(硏究開發投資)의 절대 수준도 중요하나 기술개발(技術開發)의 성과(成果)를 극대화하기 위한 기술의 획득(獲得) 및 습득과정(習得過程)의 효율화(效率化)에 최선을 다해야 할 것이다. 산업경쟁력(産業競爭力) 향상을 위한 기술개발정책(技術開發政策)의 기본방향(基本方向)은 국내산업의 기술발전단계와 연구개발의 국내기반에 입각하여 기술개발투자(技術開發投資)의 효율화(效率化)를 위한 국제화(國際化) 전략(戰略)의 전개, 기업중심의 연구개발(硏究開發) 네트워크의 고도화, 공공연구기관의 정예화(精銳化) 및 대학의 연구활성화(硏究活性化)를 유도해 나가는 것으로 요약된다.

• 방사선산업학회지
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• 제17권1호
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• pp.19-32
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• 2023

The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.