Earticle

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method. comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

본 연구는 기술경영 연구 분야의 국내외 대표 학술지에 게재된 연구들을 토대로 연구 설계와 연구 방법론의 현황과 새로운 연구 분류체계를 제시하는데 그 목적이 있다. 본 연구의 목적을 달성하기 위하여 기술혁신학회지를 비롯한 기술경영 연구 분야의 국내 대표 학술지 2개와 상위 11개 국제 학술지에 2006년부터 2012년까지 수록된 696편의 연구 논문을 수집한 후 내용분석(contents analysis)을 실시하였다. 분석 결과, 정성적 개념 연구, 정성적 실증 연구, 정량적 개념 연구, 정량적 실증 연구 등의 연구 설계 내에 총 8가지의 상세 연구방법론을 분류하였으며, 다음과 같이 국내외 연구자 및 학술지, 국내 대표 학술지 간 특징을 바탕으로 기술경영 연구 분야의 동향을 확인하였다. 첫째, 국내외 기술경영 연구자 및 학술지 간 연구 설계와 연구 방법론의 추세는 실증 연구 설계에 편중된 유사한 동향을 보이고 있는 반면, 해외 연구에서 이론 연구 설계의 비율은 국내 연구보다 높게 나타났다. 둘째, 기술혁신학회지에는 정성적 실증 연구 설계와 기록 연구 방법이 더 많이 발표된 것에 반해, 기술혁신연구에는 정량적 실증 연구 설계와 개념 연구 설계의 비율이 높았다. 본 연구결과는 기술경영 연구 분야에서 연구 설계와 연구 방법론에 대한 동향과 새로운 연구 분류체계를 제시함으로써 구체적이고 체계적인 연구 접근법에 대한 방향성을 제공할 뿐만 아니라 후속 연구자들이 연구 목적에 적합한 연구 설계와 연구 방법론을 선택하는데 도움을 줄 수 있을 것으로 기대된다.

This paper proposes the newly developed a classification scheme for Management of Technology (MOT) research, by analyzing research papers published in major academic journals of MOT. To refine our proposed classification, we conducted a contents analysis after collecting 696 papers published in 11 major international journals and 2 representative domestic journals including Journal of Korean Technology Innovation Society, from 2006 to 2012. Our findings show that this classification scheme is composed of total 8 methodologies within each research design such as conceptual qualitative, empirical qualitative, conceptual quantitative, and conceptual quantitative researches. In addition, we provide research reviews based on characteristics between 1) domestic and foreign researchers, 2) domestic and international journals, and 3) different major domestic journals as follows. Firstly, the underlying trends of research design and methodologies in MOT research are concentrated in empirical studies regardless of the origin of researchers and journals. However, the proportion of theoretical discussion in the international journals is higher than that of theoretical discussion in the domestic journals. Secondly, there are many more empirical qualitative researches and archival researches written in the Journal of Korean Technology Innovation Society, whereas the proportion of empirical quantitative research and conceptual research published in the Journal of Technology Innovation is higher than that. From the results, this paper will contribute to choosing research designs and methodologies more suitable to research purpose for future MOT researchers and provide the direction for concrete systematic approach on research designs and methodologies.

In a SoC (system-on-chip) design, a design complexity is a big bottleneck. In order to overcome the design complexity, platform based design method is widely adopted for designers. Most complex SoCs need a heterogeneous design development environment for hardware and software co-design. In this paper, we discuss about some kinds of verification approaches with platform based design methodology at various abstraction levels of SoC design. We separate the verification process to two steps according to the different levels of verification. We employ a flexible SoC design environment to support simultaneous hardware and software development. We demonstrate the verification strategy of a target SoC design, IEEE 802.11a WLAN SoC.

Recent developments in the fields of communications, smart transportation systems and computer systems have significantly expanded the potential for intelligent solutions in the domains of traffic safety, convenience and efficiency. The utilization of Artificial Intelligence (AI) is presently prevalent across diverse sectors of application due to its significant capacity to augment conventional data-driven methodologies. In the domain of Vehicular Ad hoc NETworks (VANETs), data is regularly gathered from several sources. The collected data serves multiple goals, such as facilitating efficient routing, enhancing driver awareness, forecasting mobility patterns to prevent potential risks, and ultimately enhancing passenger comfort, safety and overall road experience. Internet of thing (IoT) can be a good solution fro many issues that of VANETs. In order to make a complete system of VANETs communications are very essential like 5G and 6G. This study provides a detailed examination of AI, IoT and 5G/6G methodologies currently being investigated by multiple research endeavors in the field of VANETs. The merits and demerits of the AI-based methodologies suggested for the VANET domain have been analyzed with the using of IoT and 5G/6G. In conclusion, forthcoming research prospects in the field of VANETs are ascertained.

Three-dimensional integrated circuits (3D ICs), starting with memory cubes, have entered the mainstream recently. The benefits many predicted in the past are indeed delivered, including higher memory bandwidth, smaller form factor, and lower energy. However, 3D ICs have yet to find their deployment in aerospace applications. In this paper we first present key design tools and methodologies for high performance, low power, and reliable 3D ICs that mainly target terrestrial applications. Next, we discuss research needs to extend their capabilities to ensure reliable operations under the harsh space environments. We first present a design methodology that performs fine-grained partitioning of functional modules in 3D ICs for power reduction. Next, we discuss our multi-physics reliability analysis tool that identifies thermal and mechanical reliability trouble spots in the given 3D IC layouts. Our tools will help aerospace electronics designers to improve the reliability of these 3D IC components while not degrading their energy benefits.

Until today, success in germline cells and tissue cryopreservation is limited mainly due to the poor understanding of the complex physiological processes can lead to cell damage during cryopreservation. Germline cells, from both male and female, have unique ability to differentiate into one or more cell lines and thus it becomes a crucial point to store them in subzero temperature with the minimal damage of their functional properties and maximum recovery of unchanged and viable cells when thawed. In the past three decades, a vast research has been performed using various different animal models which in fact have led to development of new methodologies and optimization of older one. However, successful use of animal model has provided the opportunity in research with human germline cells and tissues preservation, but not in all the cases. Therefore, the use of new cryo-protective chemicals and modified protocols have been often found in different groups of researchers based on the types, physical structures, utility and animal species of the specimens to be cryopreserved. This review discusses about the basics of different types of cryopreservation methodologies and commonly used optimized protocols and cryoprotectants for germline cells and tissues preservation.

Accurate determination of rainfall thresholds is essential for effective landslide prediction and early warning. This study compares two methodologies for analysing landslide-triggering rainfall thresholds in South Korea: one using data from the single nearest station selected through recent site verification, and the other based on averaged rainfall data from multiple nearby observation stations. I–D and E–D curves were derived using quantile regression with consistent rainfall event thresholds, and predictive performance was evaluated using ROCbased classification accuracy (AUC). The single observation station approach exhibited considerable variability, whereas the average-based method produced more stable and consistent threshold estimates. The comparison identifies the strengths and limitations of each approach depending on the availability and distribution of observational infrastructure, providing insights into effective data utilization strategies for landslide early warning systems

Often most of the modern human people are suffering from a long time of working or studying on the stationary pose. Subsequently, the health of our life is highly threatened to be exacerbated by chronic orthopedic diseases. In order to solve this social problem, we suggest pose detection that can have the people who have deleterious postures be notified. By using nowadays advanced computer vision techniques, in this paper we suggest the posture recognition module to enhance our quality of life. While most posture recognition recognizes only one person's posture, we made our pipeline to perform posture recognition for multiple people through images obtained through a single camera. One of the big problems in measuring people's postures is that it is necessary to distinguish the various body structures and postures of people. For this, posture images and labeling of various people are required. We created pose images of people of various body types through images of a small number of people through skeleton-based coordinates augmentation. We made a posture classifier using various models and observed the improvement of augmentation performance for each model. Through this, we found that the postures of various people can be measured using a relatively small data set. In particular, for deep-learning models that require a lot of data, generalization performance was greatly improved.

The object of this paper is to evaluate the fission product inventories and radiological doses in a non- LOCA event, based on the U.S. NRC’s regulatory methodologies recommended by the TID-14844 and the RG 1.195. For choosing a non-LOCA event, one fuel assembly was assumed to be melted by a channel blockage accident. The Hanul nuclear power reactor unit 6 and the CE 16×16 fuel assembly were selected as the computational models. The burnup cross section library for depletion calculations was produced using the TRITON module in the SCALE6.1 computer code system. Based on the recently licensed values for fuel enrichment and burnup, the source term calculation was performed using the ORIGEN-ARP module. The fission product inventories released into the environment were obtained with the assumptions of the TID-14844 and the RG 1.195. With two kinds of source terms, the radiological doses of public in normal environment reflecting realistic circumstances were evaluated by applying the average condition of meteorology, inhalation rate, and shielding factor. The statistical analysis was first carried out using consecutive three year-meteorological data measured at the Hanul site. The annual-averaged atmospheric dispersion factors were evaluated at the shortest representative distance of 1,000 m, where the residents are actually able to live from the reactor core, according to the methodology recommended by the RG 1.111. The Korean characteristic-inhalation rate and shielding factor of a building were considered for a series of dose calculations.

The precise characterization of critical current, Ic is fundamental for the design and stable operation of large-scale high-temperature superconducting (HTS) applications, such as fusion magnets and power cables. However, unlike low-temperature superconductors (LTS), HTS materials exhibit complex voltage-current characteristics governed by thermal fluctuations and flux creep, leading to significant measurement uncertainties. This paper provides a comprehensive review of the international standards for Ic measurement, specifically the IEC 61788 series, with a particular focus on the transition from Nb-based conductors to REBCO coated conductors (IEC 61788-26). The theoretical background of the E-J power law model is analyzed and various definition criteria of critical current are evaluated to highlight the engineering implications of criterion dependency. Furthermore, key technical requirements for reproducible data, such as atmospheric pressure correction and current transfer length, are discussed in detail. Finally, this paper addresses the engineering gap between standardized short-sample tests and actual magnet performance, examining critical issues including screening currents, self-field effects, and mechanical stress in large-scale systems.

본 연구는 인공지능 네트워크 시스템의 개발을 위해 존재하는 방법론들이 어떠한 것이 있는지를 연구하고자 한다. 인공지능 네트워크 개발에 대해 현재 발표된 것과 방법론을 명확히 하기위한 관점들을 측정하였으며 그것은 이러한 네트워크 개발에 이용되었다. 광범위한 이러한 방법론들을 어떻게 범주화하고, 만약 이런 방법론들이 인공지능 네트워크 개발에 대한 일반적, 근본적이고 포괄적인 방법론으로 증명할 수 있는지, 그리고 이런 방법론들이 기존 시스템 개발 방법론들과 어떻게 다른지 본 연구를 통해 시험했다.

We examined current publications on artificial neural network development with a view to identifying the methodologies that are being used to develop these networks, how extensive these methodologies are, the categorization of these methodologies, if these methodologies demonstrate a common underlying and generic (standard) methodology for the development of artificial neural networks, and how closely these methodologies (and the underlying genetic methodology, if established) relate to the conventional systems development methodologies.

목적: 현재 근파워지구력에 대한 명확한 정의가 없으며, 다양한 스포츠 종목의 경기력 향상에 중요한 요소 임에도 불구하고 프로토콜과 매개변수가 표준화되어 있지 않다. 이에 우리는 근파워지구력에 대한 더 나은 설명을 위한 기존 문헌에 대한 비판적 고찰을 진행하였다. 방법: 1970년부터 2023년까지의 주요 데이터베이스를 활용하 여 관련 또는 연관 키워드 검색을 통한 서술적 고찰을 수행하였다. 결과: 108건의 연구를 검토한 결과, 47가지의 서로 다른 측정 프로토콜이 확인되어 해당 분야의 표준화가 상당히 미흡함을 나타냈다. 근파워지구력은 ATP-PCr, 해당과정, 유산소 에너지 시스템을 활용하여 높은 수준의 파워를 연속적으로 발휘하는 것으로 정의할 수 있었다. 시사점: 반복 스프린트와 고강도 인터벌 트레이닝을 결합한 통합 트레이닝 전략이 가장 효과적인 것으 로 나타났다. 이러한 근거는 표준화된 프로토콜을 개발하고 향후 연구를 제시하는 데 활용될 수 있을 것이다.

There is no clarity around muscular power endurance and protocols and parameters are not standardized even though it is important for sports performance in a number of different sports. A critical review of existing literature was developed for the purpose of establishing a better description of muscular power endurance. methods: A narrative review with related or associated keyword searches was performed using the major databases from 1970-2023. results: Review of 108 studies identified 47 different measurement protocols, indicating substantial lack of standardization in the field. Muscular power endurance could be defined as successively exerting power at a high level utilizing the ATP-PCr, glycolytic and aerobic energy systems. Implications: Integrated training strategies, which combine repeated sprints and high-intensity interval training, have been shown to be the most effective. This evidence could be used when creating standardised protocols and suggesting future research.

Technology acceptance model has demonstrated that technology adoption behavior can be explained by two user belief constructs: perceived usefulness and perceived ease of use. A number of studies have explored how these beliefs develop by utilizing primarily individual-level antecedents. However, because innovation and new techniques bear a direct relation to social concerns, non-individual antecedents may be necessary. Therefore, in this study, social and organizational supports are used to understand how software developers foster beliefs regarding secure coding practices. We compiled data from 83 software developers to evaluate the technology acceptance model. Our findings show that these collective antecedents can effectively explain user belief constructs and the intention to adopt secure coding methodologies. These findings imply that society and organizations offering more concrete support programs will experience smoother deployment of security-enhancing measures.

Nous présentons ici un modèle d’analyse de textes à dimension idéologique visant à indiquer comment la langue véhicule diverses idéologies. Ce modèle s’appuie sur les paramètres dégagés par l’Analyse Critique du Discours (Critical Discourse Analysis) et sur les études traductologiques et a recours également au logiciel WordSmith Tools afin de mettre en regard les deux méthodes et d’en dégager les désavantages et la manière dont elles peuvent se combiner.

전 지구적 기후 위기 심화에 따라 ISO 14044 등 국제 표준에 기반한 일관성 있고 재현 가능한 제품 탄소 발자국(PCF) 산정 체계 구축이 시급한 과제로 부상하였다. 본 연구는 LCA 기반의 국내외 탄소 배출량 산정 규제를 비교 분석하고자 EU 제품 환경 발자국(PEF), GHG Protocol, PAS 2050 및 한국의 환경성적표지(EPD) 제도를 검토하였다. 분석 결과, EU PEF는 구체적인 기능 단위 정의, 정량적 데이터 품질 등급(DQR) 적용, 표준화된 보고 및 검증 체계를 통해 가장 엄격한 요구사항을 제시하는 것으로 나타났다. 반면 타 제도들은 상대적으로 원칙 중심적이거나 개별 프로그램의 자율성에 의존하는 한계를 보였다. 이를 실증하기 위해 수행된 배경 LCI 데이터베이스(DB) 변경 감도 분석에서는 동일 조건임에도 불구하고 최대 90% 이상의 과소평가를 포함한 유의미한 결과 편차가 확인되었다. 이는 컷오프 기준, 영향 범주 선택 및 검증 요건의 차이가 데이터 관리 관행을 통해 분석 결과에 직접 투영됨을 시사한다. 따라서 한국형 EPD 제도의 국제적 정합성 확보를 위해 PEF형 데이터 품질 관리 도입, 검증 절차 강화, 국가 LCI DB의 양적·질적 확충을 제안한다.

With tightening climate targets, internationally consistent product carbon footprint (PCF) accounting based on ISO 14044 and ISO 14067 is critical. This study compares LCA-based domestic and international regulations, evaluating the EU Product Environmental Footprint (PEF), GHG Protocol, PAS 2050, and the Korea EPD scheme. Analysis reveals that EU PEF sets the strictest requirements through concrete functional units, data quality ratings (DQR), and standardized reporting, while other schemes remain principle-based. A sensitivity analysis varying only the background LCI database under identical conditions shows large deviations, including underestimations up to 90%. These results indicate that differences in cut-off criteria, impact selection, and verification directly influence outcomes via data management practices. For the Korea EPD, priorities include adopting PEF-type quality management, tightening verification, and expanding the national LCI DB for international alignment. Improving the national database is essential for domestic industries to navigate global regulations and ensure environmental claims are recognized without technical discrepancies.

Objective: This study aimed to review the methodologies for evaluation of consumer spray products containing engineered nanomaterials (ENM), particularly focusing on inhalation exposure. Method: Literature on the evaluation methods for aerosolized ENM exposure from consumer spray products were collected through academic web searching. Common methodologies used in the literature, including research reports and academic articles, were also introduced. Results: The number of ENM-containing products have shown a considerable increase over recent years, from 54 in 2005 to 1,827 in 2018. Currently there is still discussion over the existing regulations with regard to product safety. Analysis of both ENM suspensions in the products and their aerosols is important for risk assessment. Comparison between the phases suggests how the size and concentration of particles change during the spray process. To analyze the ENM suspensions, dynamic light scattering, electron microscopy techniques, and inductively coupled plasma with mass spectrometry were used. In the aerosol monitoring, direct-reading instruments have been used to monitor the aerosols and conventional active sampling is used together to supplement the lack of real-time monitoring. There are also some models for estimating inhalation exposure. These models may be used to estimate mass exposure to nanomaterials contained in consumer products. Conclusion: Although there is no standardized method to evaluate ENM exposure from consumer products, many concerns about ENM have emerged. Every potential measure to reduce exposure to ENM from spray product use should be implemented through a precautionary recognition.

인공지능 기술의 발전과 함께 딥러닝 기반의 오디오 딥페이크 기술이 크게 향상되었고, 이를 악용하여 다양한 범죄 활동이 이루어지고 있다. 오디오 딥페이크를 탐지하여 이러한 피해를 예방하기 위해 본 논문은 새로운 컨시스트(CoNSIST) 모델을 제안한다. 이 모델은 그래프 기반의 모델인 AASIST를 기반으로, 세 가지 추가적인 모델링 방법론을 적용하여 오디오 딥페이크 탐지를 한다. 세 가지 추가적인 모델링을 통해 특징 추출을 강화하고, 불필요한 작업을 제거하며, 다양한 정보를 통합하는 것을 목표로 한다. 최종 실험 결과, 컨시스트가 기존 오디오 딥페이크 탐지 모델들보다 더 우수한 성능을 보여 딥페이크의 악용을 방지하기 위해 더 나은 해결책을 제공한다.

Advancements in artificial intelligence(AI) have significantly improved deep learning-based audio deepfake technology, which has been exploited for criminal activities. To detect audio deepfake, we propose CoNSIST, an advanced audio deepfake detection model. CoNSIST builds on AASIST, which a graph-based end-to-end model, by integrating three key components: Squeeze and Excitation, Positional Encoding, and Reformulated HS-GAL. These additions aim to enhance feature extraction, eliminate unnecessary operations, and incorporate diverse information. Our experimental results demonstrate that CoNSIST significantly outperforms existing models in detecting audio deepfakes, offering a more robust solution to combat the misuse of this technology.