• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4742-4770
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• 2019

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.

• The Journal of Information Systems
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• v.30 no.2
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• pp.243-259
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• 2021

Purpose The beginning of innovation and creation, Haenggung-dong, Paldal-gu, Suwon-si: Suwon Hwaseong Fortress, which began in 1794 by King Jeongjo in accordance with the spirit of Beopgochangsin, mobilized the abilities of traditional techniques, new science and technology, and artists New starting point for urban innovation in Suwon: Based on 5G technology possessed by leading companies in the global ICT industry in Hwaseong (Haenggung-dong), a product of cutting-edge evidence, solve various urban problems through public, private, industrial and academic governance, and a new business model It aims to reorganize into the space where this is created. Design/methodology/approach The New 1794 Project is a 2019 demonstration project requested by the Ministry of Land, Infrastructure and Transport for "Suwon Smart City Challenge Project: Haenggung-dong, Paldal-gu, Suwon-si," developed by the Dankook University SW Design Convergence Center, and the main project from 2020 to 2022. The smart city project strategy should be implemented based on partnerships with multiple stakeholders, and the bottom-up approach and the traditional top-down must be able to coexist. Therefore, the smart city solution applied a horizontal governance method. Findings In this study, the definition of the New 1794 Project, which is the key to defining smart cities in relation to all analyzed aspects, was developed.

• ETRI Journal
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• v.46 no.1
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• pp.82-95
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• 2024

As automated essay scoring (AES) has progressed from handcrafted techniques to deep learning, holistic scoring capabilities have merged. However, specific trait assessment remains a challenge because of the limited depth of earlier methods in modeling dual assessments for holistic and multi-trait tasks. To overcome this challenge, we explore providing comprehensive feedback while modeling the interconnections between holistic and trait representations. We introduce the DualBERT-Trans-CNN model, which combines transformer-based representations with a novel dual-scale bidirectional encoder representations from transformers (BERT) encoding approach at the document-level. By explicitly leveraging multi-trait representations in a multi-task learning (MTL) framework, our DualBERT-Trans-CNN emphasizes the interrelation between holistic and trait-based score predictions, aiming for improved accuracy. For validation, we conducted extensive tests on the ASAP++ and TOEFL11 datasets. Against models of the same MTL setting, ours showed a 2.0% increase in its holistic score. Additionally, compared with single-task learning (STL) models, ours demonstrated a 3.6% enhancement in average multi-trait performance on the ASAP++ dataset.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.617-623
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• 2024

Identifying emotions through speech poses a significant challenge due to the complex relationship between language and emotions. Our paper aims to take on this challenge by employing feature engineering to identify emotions in speech through a multimodal classification task involving both speech and text data. We evaluated two classifiers-Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM)-both integrated with a BERT-based pre-trained model. Our assessment covers various performance metrics (accuracy, F-score, precision, and recall) across different experimental setups). The findings highlight the impressive proficiency of two models in accurately discerning emotions from both text and speech data.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.183-188
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• 2012

One of the major challenge for retrieval performance is the word mismatch between user's queries and documents in information retrieval. To solve the word mismatch problem, we propose a retrieval model based on the degree of association of query concept and word translation probabilities in translation-based model. The word translation probabilities are calculated based on the set of a sentence and its succeeding sentence pair. To validate the proposed method, we experimented on TREC AP test collection. The experimental results show that the proposed model achieved significant improvement over the language model and outperformed translation-based language model.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.659-666
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• 2021

With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.632-657
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• 2022

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed WAF model. The classification process of the types of abnormal traffics is postponed to the second stage and carried out using an integrated stacked ensemble model. By this way, clients' requests can be served without time delay, and attack types can be detected with high sensitivity. In addition to the high accuracy of the proposed model, by using the statistical similarity and diversity analyses in the study, high generalization for the ensemble model is achieved. Within the study, a comprehensive, up-to-date, and robust multi-class web anomaly dataset named GAZI-HTTP is created in accordance with the real-world situations. The performance of the proposed WAF model is compared to state-of-the-art deep learning models and previous studies using the benchmark dataset. The proposed two-stage model achieved multi-class detection rates of 97.43% and 94.77% for GAZI-HTTP and ECML-PKDD, respectively.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3088-3101
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• 2023

A pressurized vessel-pipe-safety valve (PVPSV) combination is a commonly used configuration in nuclear power plants, and a good numerical model is essential for the system design, sizing and performance optimization. However, owing to the large-scale and cross-scale features, it is still a challenge to build a system level numerical model with both high accuracy and efficiency. To overcome this, a novel system level modeling method which can synthesize the advantages of various models is proposed in this paper. For system modeling, the analytical approach, the method of characteristics (MOC) and the surrogate model approach are respectively adopted to predict the dynamics of the pressure vessel, the connecting pipe and the safety valve, and different models are connected through data interfaces. With this system model, dynamic simulations were carried out and both the stable and the unstable system responses were obtained. For the model verification purpose, the simulation results were compared with those obtained from experiments and full CFD simulations. A good agreement and a better efficiency were obtained, verifying the ability of the model and the feasibility of the modeling method proposed in this paper.

• STI Policy Review
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• v.1 no.1
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• pp.93-109
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• 2010

Over the last decade, some Korean enterprises have emerged to become global players in their specialized products. How have they achieved such tremendous technological progress in a short period of time? This paper explores that question by examining the characteristics of technological innovation activities at major Korean enterprises. The paper begins with a brief review of the stages of economic growth and science and technology development in Korea. Then, the existing literature, explaining the Korean innovation model, is analyzed in order to establish a new framework for the Korean innovation model. Specifically, Korean firms have experienced three sequential phases, and thus, the Korean model, at the firm level, can be coined as "path-following," "path-revealing," and "path-creating." Then, the stylized facts in the first phase (path-following) and the second phase (path-revealing) are discussed, in the context of empirical evidence from the areas of memory chips, automobiles, shipbuilding, and steel. In terms of technology development, the Korean model has evolved as "collective learning" in the first phase, "collective recombination" of existing knowledge and technology in the second phase, and is assumed as "collective creativity" in the third phase. Ultimately, all three can be classified as "collective creation". Korean firms now face a transition in the modes of technological innovation in order to efficiently implement the third phase. To achieve remarkable progress again, as they did in the past, and to sustain the growth momentum, Korean firms should challenge new dimensions such as creative technological ideas, distinctive technological capabilities, and unique innovation systems -- all of which connote 'uniqueness'. Finally, some lessons from the Korean technological innovation experience are addressed.

• Journal of Society of Preventive Korean Medicine
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• v.12 no.3
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• pp.21-34
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• 2008

Objectives : This paper analysed the alternative methods of calculating conversion factor for oriental medicine in the National Health Insurance and estimated the conversion factor(reimbursing price level) of the oriental medical services, based on health insurance claims data and macro economic data. Methods : Comparing cost accounting method, SGR model, and index model to estimate conversion factor in the national health insurance, six empirical models were derived depending on the scope of revenue considered in financial indicators. Classifications of data and sources used in the analysis were identified as officially released by the government. Results and Conclusion : Cost accounting analysis and SGR model showed a two digit decrease in the physician fee schedule of oriental medical services in the national health insurance, while index model indicated a positive increase in the fee reimbursed. As expected, SGR model measured an overall trend of health expenditures rather than an individual financial status of medical institutions, and index model properly estimated the level of payments to oriental medical doctors. Upon a declining share of health expenditures on oriental medicine, a global budget system fixed to a flat rate of total budget could be an opportunity as well as a challenge.