• Journal of Technologic Dentistry
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• v.46 no.2
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• pp.21-27
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• 2024

Purpose: This study aimed to analyze the stress distribution and deformation in implant abutments made from titanium (Ti-6Al-4V), zirconia, and polyetheretherketone (PEEK), including their screws and fixtures, under various loading conditions using finite element analysis (FEA). Methods: Three-dimensional models of the mandible with implant abutments were created using Siemens NX software (NX10.0.0.24, Siemens). FEA was conducted using Abaqus to simulate occlusal loads and assess stress distribution and deformation. Material properties such as Young's modulus and Poisson's ratio were assigned to each component based on literature and experimental data. Results: The FEA results revealed distinct stress distribution patterns among the materials. Titanium alloy abutments exhibited the highest stress resistance and the most uniform stress distribution, making them highly suitable for long-term stability. Zirconia abutments showed strong mechanical properties with higher stress concentration, indicating potential vulnerability to fracture despite their aesthetic advantages. PEEK abutments demonstrated the least stress resistance and higher deformation compared to other abutment materials, but offered superior shock absorption, though they posed a higher risk of mechanical failure under high load conditions. Conclusion: The study emphasizes the importance of selecting appropriate materials for dental implants. Titanium offers durability and uniform stress distribution, making it highly suitable for long-term stability. Zirconia provides aesthetic benefits but has a higher risk of fracture compared to titanium. PEEK excels in shock absorption but has a higher risk of mechanical failure compared to both titanium and zirconia. These insights can guide improved implant designs and material choices for various clinical needs.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4367-4381
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• 2023

Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called "Digital I&C PSA - Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)", which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017-2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.57-64
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• 2024

The introduction of Smart Factories has transformed manufacturing towards more objective and efficient line management. However, most companies are not effectively utilizing the vast amount of sensor data collected every second. This study aims to use this data to predict product quality and manage production processes efficiently. Due to security issues, specific sensor data could not be verified, so semiconductor process-related training data from the "SAMSUNG SDS Brightics AI" site was used. Data preprocessing, including removing missing values, outliers, scaling, and feature elimination, was crucial for optimal sensor data. Oversampling was used to balance the imbalanced training dataset. The SVM (rbf) model achieved high performance (Accuracy: 97.07%, GM: 96.61%), surpassing the MLP model implemented by "SAMSUNG SDS Brightics AI". This research can be applied to various topics, such as predicting component lifecycles and process conditions.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.39-46
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• 2024

An API gateway is a high-availability component that provides a single entry point for API clients outside the cloud to connect with services inside the cloud. It has a high risk of creating bottlenecks and requires redeployment when services change. The Java language, in which several API gateways are implemented, announced technologies called GraalVM Native Image and Virtual Thread to overcome problems with deployment and operational performance. Applying these technologies to Java applications requires changes to the source code and deployment procedures. In this study, the performance of the API gateway was measured and analyzed when it operated based on GraalVM Native Image and Java Virtual Machine(JVM) and between Virtual Thread and Reactive thread processing methods. In this study, evaluation indicators were selected to evaluate deployment performance and operational performance, and the performance of the evaluation indicators was measured and evaluated in four environments.

• Fisheries and Aquatic Sciences
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• v.27 no.8
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• pp.501-514
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• 2024

Fishes are found in different lentic and lotic aquatic ecosystems. Determining the composition of fish communities is a crucial component of water quality evaluations and conservation strategies in flowing rivers. The present study is carried out to investigate fish species diversity, richness, and abundance in two second-order streams: Gereb Tsedo (GTS) and Elala in the Tekeze sub-basin. We collected fish with backpack electrofishing during August and December 2013 and March 2014. Fish species richness and the total number of species per stream and per microhabitat were calculated for each stream. Species diversity for each site was calculated using the Shannon index of diversity using the standard formula H' = -Σpi ln (pi). Diversity data among habitats and streams were compared using one-way analysis of variance (ANOVA) and Tukey post hoc comparisons, using the statistical software package STATISTICA 11. A total of 6,554 specimens representing four species: Garra blanfordii, Grra ignestii, Garra dembecha and Garra aethiopica, were caught. They are all indigenous riverine fish species of the family Cyprinidae. Fish abundance was significantly higher in GTS than Elala stream (t-test, t = 1.444, df = 3, p < 0.05). Across the two streams, the overall relative fish abundance was higher in pools, with 53%, followed by runs and riffles with 35% and 12%, respectively. Garra blanfordii was dominant in pools while G. aethiopica was the least dominant. Stream and habitat types were likely the more important driving factors behind the observed patterns of diversity, although the impact of other, not evaluated variables cannot be excluded. Most likely, the observed patterns do not represent a signature of fish dispersal limitation given that almost all species were widely distributed across the study area.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4412-4422
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• 2024

The CFETR multipurpose overload robot (CMOR) is a critical component of the fusion reactor remote handling system. To accurately calculate and visualize the structural deformation and stress characteristics of the CMOR motion process, this paper first establishes a CMOR kinematic model to analyze the unfolding and working process in the vacuum chamber. Then, the dynamic model of CMOR is established using the Lagrangian method, and the rigid-flexible coupling modeling of CMOR links and joints is achieved using the finite element method and the linear spring damping equivalent model. The co-simulation results of the CMOR rigid-flexible coupled model show that when the end load is 2000 kg, the extreme value of the end-effector position error is more than 0.12 m, and the maximum stress value is 1.85 × 10⁸ Pa. To utilize the stress-strain data of CMOR, this paper designs a CMOR morphology prediction control system based on Unity software. Implanting CMOR finite element analysis data into the Unity environment, researchers can monitor the stress strain generated by different motion trajectories of the CMOR robotic arm in the control system. It provides a platform for subsequent research on CMOR error compensation and extreme operation warnings.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.509-520
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• 2007

In this paper, we propose a real-time sensor node platform that guarantees the real-time scheduling of periodic and aperiodic tasks through a multitask-based software decomposition technique. Since existing sensor networking operation systems available in literature are not capable of supporting the real-time scheduling of periodic and aperiodic tasks, the preemption of aperiodic task with high priority can block periodic tasks, and so periodic tasks are likely to miss their deadlines. This paper presents a comprehensive evaluation of how to structure periodic or aperiodic task decomposition in real-time sensor-networking platforms as regard to guaranteeing the deadlines of all the periodic tasks and aiming to providing aperiodic tasks with average good response time. A case study based on real system experiments is conducted to illustrate the application and efficiency of the multitask-based dynamic component execution environment in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. It shows that our periodic and aperiodic task decomposition technique yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.

• Analytical Science and Technology
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• v.29 no.1
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• pp.1-9
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• 2016

It is believed that traditional Korean medicines can be managed more scientifically through the development of logical criteria to verify their region of cultivation, and that this could contribute to the advancement of the traditional herbal medicine industry. This study attempted to determine such criteria for Sansuyu. The volatile compounds were obtained from 20 samples of domestic Corni fructus (Sansuyu) and 45 samples of Chinese Sansuyu by steam distillation. The metabolites were identified in the NIST Mass Spectral Library via the obtained gas chromatography/mass spectrometer (GC/MS) data of 53 training samples. Data binning at 0.2 min intervals was performed to normalize the number of variables used in the statistical analysis. Multivariate statistical analyses, such as principle component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed using the SIMCA-P software package. Significant variables with a variable importance in the projection (VIP) score higher than 1.0 were obtained from OPLS-DA, and variables that resulted in a p-value of less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Finally, among the 11 variables extracted, 1-ethylbutyl-hydroperoxide (9.089 min), nonadecane (20.170 min), butylated hydroxytoluene (25.319 min), 5β,7βH,10α-eudesm-11-en-1α-ol (25.921 min), 7,9-bis(2-methyl-2-propanyl)-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione (34.257 min), and 2-decyldodecyl-benzene (54.717 min) were selected as markers to indicate the origin of Sansuyu. The statistical model developed was suitable for the determination of the geographical origin of Sansuyu. The cultivation areas of four Korean and eight Chinese Sansuyu samples were predicted via the established OPLS-DA model, and it was confirmed that 11 of the 12 samples were accurately classified.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.255-266
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• 2004

In the Web-based information systems, separating the business process logic from the data and presentation logic brings about a wide range of advantages. However, this separation is not easily achieved; even the data logic may be not separated from the presentation layer. So, it requires to define an model for business processes, and then to map the model into the user's dynamic interface using the logic separating strategy. This paper presents a stylesheet method to recognize the process by extending XSLT (Extensible Stylesheet Language Transformations), in order to achieve the logic separation. To do this, it provides an specification of the business process, and a scheme that extracts business model factors and their interactions using a Petri-net notation to show the business model into the process point of view. This is an attempt to separate users' interaction from the business process, that is, dynamic components of interaction Web document from the process structure of Web applications. Our architecture consist mainly of an XSLT controller that is extended by a process control component. The XSLT controller is responsible for receiving the user requests and searching the relevant templet rule related to different user requests one by one. Separation of concerns facilities the development of service-oriented Web sites by making if modular. As a result, the development of service-oriented Web sites would be very easy, and can be changed without affecting the other modules, by virtue of the modularization concept. So, it is easy to develop and maintain the Web applications in independent manner.