• Nuclear Engineering and Technology
• /
• v.53 no.8
• /
• pp.2445-2453
• /
• 2021

Since the nuclear data forms a vital component in reactor physics computations, the nuclear community needs processing codes as tools for translating the Evaluated Nuclear Data Files (ENDF) to simulate nuclear-related problems such as an ACE format that is used for MCNP. Errors, inaccuracies or discrepancies in library processing may lead to a calculation that disagrees with the experimentally measured benchmark. This paper provides an overview of the processing and preparation of ENDF/B-VIII.0 incident neutron data with NECP-Atlas and NJOY codes for implementation in the MCNP code. The resulting libraries are statistically inter-compared and tested by conducting benchmark calculations, as the mutualcomparison is a source of strong feedback for further improvements in processing procedures. The database of the benchmark experiments is based on a selection taken from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP handbook) and those proposed by Russell D. Mosteller. In general, there is quite good agreement between the NECP-Atlas1.2 and NJOY21^(1.0.0.json) results with no substantial differences, if the correct input parameters are used.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.4
• /
• pp.111-117
• /
• 2022

Many studies have been conducted on software fault prediction models for decades, and the models using machine learning techniques showed the best performance. Deep learning techniques have become the most popular in the field of machine learning, but few studies have used them as classifiers for fault prediction models. Some studies have used deep learning to obtain semantic information from the model input source code or syntactic data. In this paper, we produced several models by changing the model structure and hyperparameters using MLP with three or more hidden layers. As a result of the model evaluation experiment, the MLP-based deep learning models showed similar performance to the existing models in terms of Accuracy, but significantly better in AUC. It also outperformed another deep learning model, the CNN model.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1860-1873
• /
• 2022

Nuclear thermal-hydraulic system analysis codes have been developed to comprehensively model nuclear reactor systems to evaluate the safety of a nuclear reactor system. For analyzing complex systems with finite computational resources, system codes usually solve simplified fluid equations for coarsely discretized control volumes with one-dimensional assumptions and replace source terms in the governing equations with constitutive relations. Wall boiling heat transfer models are regarded as essential models in nuclear safety evaluation among many constitutive relations. The wall boiling heat transfer models of two widely used nuclear system codes, RELAP5 and TRACE, are analyzed in this study. It is first described how wall heat transfer models are composed in the two codes. By utilizing the same method described in Part 1 paper, heat fluxes from the two codes are compared under the same thermal-hydraulic conditions. The significant factors for the differences are identified as well as at which conditions the non-negligible difference occurs. Steady-state simulations with both codes are also conducted to confirm how the difference in wall heat transfer models impacts the simulation results.

• Ocean and Polar Research
• /
• v.45 no.2
• /
• pp.33-42
• /
• 2023

Dissolved oxygen (DO) is a crucial parameter for assessing environmental conditions in aquatic ecosystems. However, commercial in situ dataloggers for oxygen optodes can be relatively expensive and limited in their specifications. In this paper, we present a novel design for a DO datalogger system based on the control boards family with RP2040 MCU chipset. Our design includes two types of dataloggers: a simple logging system and a programmable system for sampling rates via magnetic switches underwater for divers. We provide detailed descriptions of the system, including the MicroPython source code and drawings to aid in construction. We also discuss the various applications of our DO datalogger system in monitoring dissolved oxygen concentration in coastal waters and assessing the benthic metabolism of aquatic ecosystems. Our DO datalogger system provides an affordable and flexible option for researchers to accurately monitor DO concentrations in aquatic environments, and thereby improve our understanding of these complex ecosystems.

• International Journal of Computer Science & Network Security
• /
• v.23 no.3
• /
• pp.169-176
• /
• 2023

The vehicular ad hoc network (VANET) is currently an important approach to improve personal safety and driving comfort. ANEL is a MAC-based authentication scheme that offers all the advantages of MAC-based authentication schemes and overcomes all their limitations at the same time. In addition, the given scheme, ANEL, can achieve the security objectives such as authentication, privacy preservation, non-repudiation, etc. In addition, our scheme provides effective bio-password login, system key update, bio-password update, and other security services. Additionally, in the proposed scheme, the Trusted Authority (TA) can disclose the source driver and vehicle of each malicious message. The heavy traffic congestion increases the number of messages transmitted, some of which need to be secretly transmitted between vehicles. Therefore, ANEL requires lightweight mechanisms to overcome security challenges. To ensure security in our ANEL scheme we can use cryptographic techniques such as elliptic curve technique, session key technique, shared key technique and message authentication code technique. This article proposes a new efficient and light authentication scheme (ANEL) which consists in the protection of texts transmitted between vehicles in order not to allow a third party to know the context of the information. A detail of the mapping from text passing to elliptic curve cryptography (ECC) to the inverse mapping operation is covered in detail. Finally, an example of application of the proposed steps with an illustration

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1466-1488
• /
• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.

• Nuclear Engineering and Technology
• /
• v.55 no.10
• /
• pp.3591-3598
• /
• 2023

Photoneutron background spectroscopy observations at linac are essential for directing accelerator shielding and subtracting background signals. Therefore, we constructed a Bonner Sphere Spectrometer (BSS) system based on an array of BF₃ gas proportional counter tubes. Initially, the response of the BSS system was simulated using the MCNP5 code. Next, the response of the system was calibrated by using neutrons with energies of 2.86 MeV and 14.84 MeV. Then, the system was employed to measure the spectrum of the ²⁴¹Am-Be neutron source, and the results were unfolded by using the Gravel and EM algorithms. Using the validated system, the undesirable neutron spectrum of the 120 MeV electron linac was finally measured and acquired. In addition, it is demonstrated that the equivalent undesirable neutron dose at a distance of 3.2 m from the linac is 19.7 mSv/h. The results measured by the above methods could provide guidance for linac-related research.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.314-316
• /
• 2023

최근 수많은 오픈소스로 공개되면서, 대부분의 소프트웨어가 오픈소스를 활용하여 구현되고 있다. 하지만, 오픈소스에 적용되어 있는 라이선스 간의 충돌 문제가 발생하면서, 라이선스 위반 문제가 지속적으로 발생하고 있다. 이러한 문제를 사전에 방지하기 위해 소스코드 분석이 필수적이지만, 다양한 기능이 실행되는 소스코드 특성 상 소스코드만 봤을 경우 직관적으로 분석이 어렵다는 문제점이 있다. 최근 소스코드의 효과적인 분석을 도와주는 다양한 도구들이 개발되었고, 그 중 한 가지 방법은 소스코드를 그래프로 변환하여 시각적인 편의성을 제공하는 방법이다. 그래프로 변환된 소스코드는 해당 시점에는 분석이 가능하지만, 분석이 필요할 때마다 변환을 해야 하는 문제점이 존재한다. 따라서 소스코드를 변환한 그래프 데이터를 저장하는 방법이 요구되었는데, 그래프 데이터베이스의 경우 특정 파일 형식만 지원하기 때문에 그래프 데이터 저장에 어려움이 존재한다. 본 제안방식에서는 소스코드를 변환한 그래프 데이터를 그래프 데이터베이스에 효과적으로 저장하고, 분석이 요구될 때마다 데이터베이스 상에서 즉각적으로 분석이 가능한 방법을 제안한다.

• Journal of Aerospace System Engineering
• /
• v.18 no.2
• /
• pp.79-86
• /
• 2024

We have developed software for the SMFD that utilizes a range of graphic design tools. These tools enable us to effortlessly create graphic elements by defining their attributes, such as position and motion. Subsequently, we can convert these designs into source code and execute the resulting software on the target system, leveraging the graphic engines provided by the tools. However, when it comes to developing the displaying software for the SMFD using multiple graphic design tools on a single system, we face various challenges. In this paper, we will delve into these challenges and propose solutions for developing the displaying software for SMFD based on heterogeneous display design tools.

• International Journal of Advanced Culture Technology
• /
• v.12 no.2
• /
• pp.161-166
• /
• 2024

As globalization has accelerated, the use of English loanwords is increasing in South Korea. In this paper, we have analyzed news stories from four Korean quality newspapers-Chosun Ilbo, Dong-A Ilbo, KyungHyang Sinmun, and Chung-Ang Ilbo to investigate the usage of English loanwords in news texts. Thirty-eight news stories on life, politics, business and IT were collected from the four newspapers and then analyzed based on the five types of loanwords-Direct, Mixed Code Combination, Clipping and Neologism and Double Notation, partly following Lee's and Rudiger's classification. As a result, the followings were revealed: first, the use of the category Direct was overwhelming the others with 90%, indicating that English loanwords were not translated from its source language and introduced into Korean directly with little modification; second, the use of English loanwords was significantly higher in the sections of business and IT than in other sectors, implying that English loanwords function in a similar way as a lingua franca does within those fields. Furthermore, the linguistic trends can provide a basic guide for translators to make an informed decision between the use of English loanwords and its translated Korean version in English-into Korean translation.