• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2704-2710
• /
• 2024

Nuclear archaeology research provides scientific methods to reconstruct the operating histories of fissile material production facilities to account for past fissile material production. While it has typically focused on analyzing material in permanent reactor structures, spent fuel or high-level waste also hold information about the reactor operation. In this computational study, we explore a Bayesian inference framework for reconstructing the operational history from measurements of isotope ratios from a sample of nuclear waste. We investigate two different inference models. The first model discriminates between three potential reactors of origin (Magnox, PWR, and PHWR) while simultaneously reconstructing the fuel burnup, time since irradiation, initial enrichment, and average power density. The second model reconstructs the fuel burnup and time since irradiation of two batches of waste in a mixed sample. Each of the models is applied to a set of simulated test data, and the performance is evaluated by comparing the highest posterior density regions to the corresponding parameter values of the test dataset. Both models perform well on the simulated test cases, which highlights the potential of the Bayesian inference framework and opens up avenues for further investigation.

• Journal of Intelligence and Information Systems
• /
• v.15 no.1
• /
• pp.87-102
• /
• 2009

With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.

• Journal of KIISE
• /
• v.41 no.9
• /
• pp.674-685
• /
• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of The Korean Association For Science Education
• /
• v.25 no.5
• /
• pp.610-623
• /
• 2005

This was a theoretical study of which the goal was to provide a foundation for developing and implementing earth science inquiry activities based on abduction as a scientific inquiry method. Through a review of relevant literature, the study examined the nature of earth science in terms of the goals of earth science inquiry and the characteristics of what is investigated in earth science. It also explored the forms and meanings of abduction, thinking strategies used in the abductive inference, and the abductive inquiry model. Abduction is the process of inferring certain rules (e.g., scientific facts, principles, laws) and providing explanatory statements or hypotheses in order to explain some phenomena. This method was found to be well-suited to the earth science inquiry which studies the causes and processes of natural phenomena in the earth and space environment. Abduction has the nature of ampliative, selective, evaluative, and creative inference, and several thinking strategies, including reconstruction of data, heuristic generalization, analogy, existential, conceptual combination, and elimination strategies, are employed for inferring rules and suggesting hypotheses. This study found the abductive inquiry model to be adaptable to earth science classrooms, and it is therefore suggested that earth science instructions should be based on the abductive method and that research work concerning the abductive inquiry in the classroom should follow.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1243-1244
• /
• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.5
• /
• pp.827-846
• /
• 2023

Recently, various information technologies such as network communication and sensors have begun to be integrated into weapon systems that were previously operated in stand-alone. This helps the operators of the weapon system to make quick and accurate decisions, thereby allowing for effective operation of the weapon system. However, as the involvement of the cyber domain in weapon systems increases, it is expected that the potential for damage from cyber attacks will also increase. To develop a secure weapon system, it is necessary to implement built-in security, which helps considering security from the requirement stage of the software development process. The U.S. Department of Defense is implementing the Risk Management Framework Assessment and Authorization (RMF A&A) process, along with the introduction of the concept of cybersecurity, for the evaluation and acquisition of weapon systems. Similarly, South Korea is also continuously making efforts to implement the Korea Risk Management Framework (K-RMF). However, so far, there are no cases where K-RMF has been applied from the development stage, and most of the data and documents related to the U.S. RMF A&A are not disclosed for confidentiality reasons. In this study, we propose the method for inferring the composition of the K-RMF based on systematic threat analysis method and the publicly released documents and data related to RMF. Furthermore, we demonstrate the effectiveness of our inferring method by applying it to the naval battleship system.

• Journal of The Korean Association For Science Education
• /
• v.27 no.1
• /
• pp.50-58
• /
• 2007

In this study, students' thoughts were searched according to the types of experiments related to the "law of definite proportions" in 9th grade science textbooks. The most common four types of experiments in textbooks were selected and analyzed for this study. It was found that the experiments needed various preconceptions and complex inferring process by students. But most of the students could not catch the concept understanding desired from the experiments. They just perceived simple observation from their senses. These phenomena were common regardless of types of experiments. These means that the level of preconceptions and inferring process for the interpretation of the experimental data did not match with students' level of thoughts. The goals of the experiments in science textbooks are to increase students' inquiry ability, and to acquire science concepts by themselves from the experiment results. But if the contents of experiments are not suitable to students' understanding level, the educational effects of the performance of these experiments were not positive. Therefore, these experiments need contents revisions for students to acquire the concept related to the "law of definite proportions" by themselves.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.13 no.2
• /
• pp.147-162
• /
• 2011

The performance-art costume is a tool for expression that can dynamically display the intention of a production. The purpose of this study is to examine the whole costume for performance arts targeting musical works, to which were added such elements as music, dance, and drama, among performance arts in several genres. This study aims to consider how the symbol contained in the costume was intended to be expressed by inferring a change in performance costume and character as the stage costume. Accordingly, the following research problems were established in this study. First, Which role does the costume play in performance art? Second, into which types can the performance-art costume be classified depending on the kind of performance art? Third, what is the expressive method for the performance-art costume? To examine the types of performance-art costume, the acting costume, the singing costume, the dancing costume and the rhythmic performance costume were considered. As a result, the performance costume can be seen to have been designed through the effect of a change in color by lighting, through the differentiation of character caused by excessive decoration, through the differentiation in material for free movement, and through symbolic expression.

• Corrosion Science and Technology
• /
• v.5 no.4
• /
• pp.141-148
• /
• 2006

The chemical composition and the semiconducting properties of the passive films formed on Alloy 690 in various film formation conditions were investigated by XPS, photocurrent measurement, and Mott-Schottky analysis. The XPS and photocurrent spectra showed that the passive films formed on Alloy 690 in pH 8.5 buffer solution at ambient temperature, in air at $400^{\circ}C$, and in PWR condition comprise $Cr_2O_3$, $Cr(OH)_3$, ${\gamma}-Fe_2O_3$, NiO, and $Ni(OH)_2$. The thermally grown oxide in air and the passive film formed at high potential (0.3 $V_{SCE}$) in pH 8.5 buffer solution were highly Cr-enriched, whereas the films formed in PWR condition and that formed at low potential (-0.3 $V_{SCE}$) in pH 8.5 buffer solution showed relatively high Ni content and low Cr content. The Mott-Schottky plots exhibited n-type semiconductivity, inferring that the semiconducting properties of the passive films formed on Alloy 690 in various film formation conditions are dominated by Cr-substituted ${\gamma}-Fe_2O_3$. The donor density, i.e., concentration of oxygen vacancy, was measured to be $1.2{\times}10^{21}{\sim}4.6{\times}10^{21}cm^{-3}$ and lowered with increase in the Cr content in the passive film.

• IEIE Transactions on Smart Processing and Computing
• /
• v.2 no.6
• /
• pp.357-366
• /
• 2013

Spectrum sensing, as a fundamental functionality of Cognitive Radio (CR), enables Secondary Users (SUs) to monitor the spectrum and detect spectrum holes that could be used. Recently, the security issues of Cognitive Radio Networks (CRNs) have attracted increasing research attention. As one of the attacks against CRNs, a Primary User Emulation (PUE) attack compromises the spectrum sensing of CR, where an attacker monopolizes the spectrum holes by impersonating the Primary User (PU) to prevent SUs from accessing the idle frequency bands. Energy detection is often used to sense the spectrum in CRNs, but the presence of PUE attack has not been considered. This study examined the effect of PUE attack on the performance of energy detection-based spectrum sensing technique. In the proposed protocol, the stationary helper nodes (HNs) are deployed in multiple stages and distributed over the coverage area of the PUs to deliver spectrum status information to the next stage of HNs and to SUs. On the other hand, the first stage of HNs is also responsible for inferring the existence of the PU based on the energy detection technique. In addition, this system provides the detection threshold under the constraints imposed on the probabilities of a miss detection and false alarm.