Park, Hyun-Kyu;Lee, Wan-Gon;Jagvaral, Batselem;Park, Young-Tack
Journal of KIISE
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v.43
no.1
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pp.87-95
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2016
Recently, due to the development of the Internet and electronic devices, there has been an enormous increase in the amount of available knowledge and information. As this growth has proceeded, studies on large-scale ontological reasoning have been actively carried out. In general, a machine learning program or knowledge engineer measures and provides a degree of confidence for each triple in a large ontology. Yet, the collected ontology data contains specific uncertainty and reasoning such data can cause vagueness in reasoning results. In order to solve the uncertainty issue, we propose an RDFS reasoning approach that utilizes confidence values indicating degrees of uncertainty in the collected data. Unlike conventional reasoning approaches that have not taken into account data uncertainty, by using the in-memory based cluster computing framework Spark, our approach computes confidence values in the data inferred through RDFS-based reasoning by applying methods for uncertainty estimating. As a result, the computed confidence values represent the uncertainty in the inferred data. To evaluate our approach, ontology reasoning was carried out over the LUBM standard benchmark data set with addition arbitrary confidence values to ontology triples. Experimental results indicated that the proposed system is capable of running over the largest data set LUBM3000 in 1179 seconds inferring 350K triples.
Li, Z.R.;Li, Z.C.;Dong, Z.F.;Huang, T.;Lu, Y.G.;Rong, J.L.;Wu, H.
Nuclear Engineering and Technology
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v.53
no.9
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pp.3068-3084
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2021
Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to experimentally assess the damage and vibrations of NPP buildings subjected to aircraft crash. In present Part I, two shots of reduce-scaled model test of aircraft impacting on NPP building were carried out. Firstly, the 1:15 aircraft model (weighs 135 kg) and RC NPP model (weighs about 70 t) are designed and prepared. Then, based on the large rocket sled loading test platform, the aircraft models were accelerated to impact perpendicularly on the two sides of NPP model, i.e., containment and auxiliary buildings, with a velocity of about 170 m/s. The strain-time histories of rebars within the impact area and acceleration-time histories of each floor of NPP model are derived from the pre-arranged twenty-one strain gauges and twenty tri-axial accelerometers, and the whole impact processes were recorded by three high-speed cameras. The local penetration and perforation failure modes occurred respectively in the collision scenarios of containment and auxiliary buildings, and some suggestions for the NPP design are given. The maximum acceleration in the 1:15 scaled tests is 1785.73 g, and thus the corresponding maximum resultant acceleration in a prototype impact might be about 119 g, which poses a potential threat to the nuclear equipment. Furthermore, it was found that the nonlinear decrease of vibrations along the height was well reflected by the variations of both the maximum resultant vibrations and Cumulative Absolute Velocity (CAV). The present experimental work on the damage and dynamic responses of NPP structure under aircraft impact is firstly presented, which could provide a benchmark basis for further safety assessments of prototype NPP structure as well as inner systems and components against aircraft crash.
Maul is a rural community with common culture and self-government system and generally consists of tens of houses living together in Korea. Maul is different from a village in the West. Maul archive is a community archive of a maul. It is not only the space to record the life of residents, history and culture of a maul but also the space to realize democracy by the participation of maul residents and to satisfy the cultural life of current residents. Nowadays, it is very important to establish maul archives to connect mauls and to communicate with the outside world, to reinforce the orignal form in maul culture and revive the alienated maul culture. To establish the maul archives, it is necessary to draw the recognition and continuous interest of the central and local government and scientifical study of scholars. The first step to found maul archives is to organize a committee. Then the committee will benchmark the preceding practices, collect, record and manage the maul archives. The maul archives is recommended to be housed in an existent traditional house with some remodeling for spaces of display and education, preservation and management. I believe that the maul archive is culturally meaningful for the resident. They will enjoy and develop their lives better, connected to outside world. The co-operation of the scholar, the resident, and the government will foster the maul archive to a success.
Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.
In recent years, the world's free trade system has been severely damaged by a series of protectionist measures in the United States and anti-globalization practices such as Brexit. Against this background, RCEP, the world's largest trade agreement, was officially signed on November 15, 2021. The RCEP provided a good working basis for the establishment of a Korea, China, and Japan free trade zone. First, this paper describes the current status of Korea-China-Japan trade cooperation and the current status of the trilateral telecommunication industry. Second, this paper simulates the changes in the overall economy of China, Japan, and Korea when tariffs are reduced to 0%, 5%, and 10%, respectively, after the establishment of a free trade zone using the 8th edition GTAP database. Then, using the simulated data changes and using the 2019 data as a benchmark, we calculated the changes in the RCA index for the three countries' telecommunications industries for the three tax rates. In the end, it is concluded that the economies of the three countries will grow to different levels in many ways when the Korea, China, and Japan free trade zone is established. Japan's telecommunications industry will not be significantly affected, Korea will grow significantly with higher tax rates and China will grow significantly with lower tax rates.
Journal of the Korea Society of Computer and Information
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v.28
no.5
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pp.163-170
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2023
As the development of the 4th industrial revolution in the maritime industry has accelerated, the technical development and progress of maritime autonomous surface ship(MASS), and the development of international regulations have been accelerated. In particular, the IMO Maritime Safety Committee(MSC) has established a road-map for the development of the non-mandatory goal-based MASS instrument(MASS Code) and started developing a non-mandatory MASS Code at MSC 105th meeting. Many countries are actively participating in the Correspondence Group on the development of MASS Code, and the development of detailed requirements for MASS functions in the MASS Code is underway. Especially, the concept of "Mode of Operation" for MASS functions was mentioned in the Correspondence Group for the first time, and it is expected that discussions on these modes will be conducted from the IMO MASS JWG meeting to held in April 2023. The concept of "Mode of Operation" will be useful in explaining MASS and MASS functions and will be discussed continually for the development of MASS Code. This paper reviews the contents of the IMCA M 220 document, which provides guidelines on operating modes, to conduct research on the benchmark for setting the operating modes of MASS.
Korean general trading companies had started their business to benchmark and to adopt the successful new business models of the Japanese ones. Nevertheless, the strategic gaps between Korean and Japanese GTCs, Sogo-Shosha, still exist, including financial profitability and managerial competencies. In this regard, it is academically and practically required to find out the differences between Korean and Japanese GTCs. This study overviews the previous researches and the business cases to understand the features of GTCs and to get recent and meaningful factors which are related with the rebirth of Sogo-Shosha. Thereafter, in-depth interviews with industry experts and scholars and subsequent investigations were also conducted to suggest meaningful implications for both academicians and practitioners with the found factors. This study suggests four fundamental differences between the Korean and Japanese GTCs: ① the origin and growth path, ② business ownership, governance strategies and contracts management, ③ availabilities of investment portfolio and risk management, ④ business operation system and organizational culture. This study suggests meaningful implications for Korean GTCs to apply the experiences and lessons learned from Japanese Sogo-Shosha into their own business.
KSII Transactions on Internet and Information Systems (TIIS)
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v.17
no.7
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pp.1951-1975
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2023
Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.
Exploration of asteroids' internal structure is essential for understanding their evolutional history. It also provides a fundamental information about the history of coalescence and collision of the solar system. Among several models of the internal structures, the rubble-pile model, confirmed by the near-Earth asteroid (25143) Itokawa by Hayabusa mission [1], is now widely regarded as the most common to asteroids with size ranging from 200 m to 10 km [2]. On the contrary, monolithic and core-mantle structures are also possible for small asteroids [3]. It is, however, still challenging to look through the interior of a target object using remote-sensing devices. In this presentation, we introduce our ongoing research conducted at Seoul National and propose an idea to infer the internal structure of Apophis using available instruments. Itokawa's research provides an important benchmark for Apophis exploration because both asteroids have similar size and composition [4][5]. We have conducted research on Itokawa's evolution in terms of collision and space weathering. Space weathering is the surface alteration process caused by solar wind implantation and micrometeorite bombardment [6]. Meanwhile, resurfacing via a collision acts as a counter-process of space weathering by exposing fresh materials under the matured layer and lower the overall degree of space weathering. Therefore, the balance of these two processes determine the space weathering degrees of the asteroid. We focus on the impact evidence on the boulder surface and found that space weathering progresses in only 100-10,000 years and modifies the surface optical properties (Jin & Ishiguro, KAS 2020 Fall Meeting). It is important to note that the timescale is significantly shorter than the Itokawa's age, suggesting that the asteroid can be totally processed by space weathering. Accordingly, our result triggers a further discussion about why Itokawa indicates a moderately fresh spectrum (Sq-type denotes less matured than S-type). For example, Itokawa's smooth terrains show a weaker degree of space weathering than other S-type asteroids [7]. We conjecture that the global seismic shaking caused by collisions with >1 mm-sized interplanetary dust particles induces granular convection, which hinders the progression of space weathering [8]. Note that the efficiency of seismic wave propagation is strongly dependent on the internal structure of the asteroid. Finally, we consider possible approaches to investigate Apophis's internal structure. The first idea is studying the space weathering age, as conducted for Itokawa. If Apophis indicates a younger age, the internal structure would have more voids [9]. In addition, the 2029 close encounter with Earth provides a rare natural opportunity to witness the contrast between before and after the event. If the asteroid exhibits a slight change in shape and space weathering degree, one can determine the physical structure of the internal materials (e.g., rubble-pile monolithic, thick or thin regolith layer, the cohesion of the materials). We will also consider a possible science using a seismometer.
KIPS Transactions on Software and Data Engineering
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v.12
no.11
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pp.481-492
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2023
This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.
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