• The Journal of Information Systems
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• v.29 no.2
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• pp.1-26
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• 2020

Purpose This study empirically investigates the impact of information technology(IT) investments on the financial and non-financial performance of a manufacturing firm. We examined the interaction effects of IT investments and strategic applications levels of information systems(IS). This study also demonstrated the three-way interaction effects of IT investments, levels of IS strategic applications, and perceived environmental uncertainty(PEU). Design/methodology/approach For this study, empirical data were collected from 98 manufacturing firms with the structured questionnaires. The data were analyzed with multiple regression models, and partial derivatives were utilized to identify the directions of the impact. Findings From the empirical results, it was found that when both the levels of IS strategic applications and the degrees of IT investments are high, the ratios of the costs of goods sold to total sales(RCGS) and the labor costs to total sales(RLCS) are decreased, as it were, the performance of a firm is improved. However, it was observed that when the levels of strategic IS are low, the high degrees of IT investments do not contribute to the improvement of a performance. The results showed that when the levels of strategic IS are high, the high degrees of IT investments incur the high RSAE not low RSAE. When PEU is considered, the empirical results showed that under the low degrees of PEU, the IT investments under high levels of strategic IS applications (strategic IT investments) improve the performance, as it were, low RCGS, and high degrees of perceived financial and non-financial performance. However, under high PEU, it was observed that high degrees of strategic IT investments do not increase the performance. When PEU is high, the strategic IT investments reduce RSAE, and under low PEU, RSAE is increased.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.1-8
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• 2019

Modern computers provide tremendous computing capability and a large memory system. Hybrid memories consist of next generation memory devices and are adopted in high performance systems. However, the increased complexity of the microprocessor makes it difficult to operate the system effectively. In this paper, we propose a simple data migration method called Bandwidth-aware Data Migration (BDM) to efficiently use memory systems for high performance processors with hybrid memory. BDM monitors the status of applications running on the system using hardware performance monitoring tools and migrates the appropriate pages of selected applications to High Bandwidth Memory (HBM). BDM selects applications whose bandwidth usages are high and also evenly distributed among the threads. Experimental results show that BDM improves execution time by an average of 20% over baseline execution.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.491-502
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• 2014

In this paper we present some research results on computing intensive applications using modern high performance architectures and from the perspective of high computational needs. Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there are applications based on simulations, aiming to maximize system resources for processing large computations for simulation. In this research work, we consider an application that simulates scheduling and resource allocation in a Grid computing system using Genetic Algorithms. In such application, a rather large number of simulations is needed to extract meaningful statistical results about the behavior of the simulation results. We study the performance of Oracle Grid Engine for such application running in a Cluster of high computing capacities. Several scenarios were generated to measure the response time and queuing time under different workloads and number of nodes in the cluster.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1421-1444
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• 2012

Mobile devices such as Android devices are emerging as a convenient client computing device with mobility and context-sensing capability. However, the computing power and hardware resource of the devices are limited due to their small form-factor. Consequently, large-scaled applications could not be deployed on these devices. Nonetheless, if the large-scaled applications are deployed and executed on the devices, high performance of the applications cannot be guaranteed. To remedy the limitation in terms of performance, it is inevitable to let some heavy-weight functionality executed on the server side and let a client application invoke the functionality in the server. To realize this kind of mobile applications, we adopt well-defined architecture design principles; being thin-client, being layered with Model-View-Controller (MVC), and being balanced between client side and server side. By adopting the principles, we propose a unique, ideal and practical architecture for mobile applications, called balanced MVC architecture. By considering the principles, key design considerations of realizing balanced MVC architecture lie in functionality partitioning. Hence, we define key criteria of determining the degree of performance. And, we define a method to design a balanced MVC architecture which embodies functionality partitioning for high performance, and a simulation-based evaluation method of balanced MVC architectures.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.287-293
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• 2011

As chip multiprocessors have been widely adopted in embedded systems, achieving both high performance and low power consumptions of parallel applications becomes challenging. In order to meet these requirements, it is crucial for developers to analyze the performance and energy consumption of parallel applications. In this paper, we propose a tool for profiling and optimizing the performance and energy consumption of OpenMP applications (energy PROfiler and analyzer for OpenMP: ePRO-OMP). The main advantage of ePRO-OMP is that it can analyze both the performance and energy consumption of each parallel region of an OpenMP application, which can help developers find the bottleneck of parallel applications in detail.

• Advances in materials Research
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• v.1 no.1
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• pp.37-49
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• 2012

In this paper, we present modeling and characterization of CNT-based TSVs to be used in high-frequency RF applications. We have developed an integrated model of CNT-based TSVs by incorporating the quantum confinement effects of CNTs with the kinetic inductance phenomenon at high frequencies. Substrate parasitics have been appropriately modeled as a monolithic microwave capacitor with the resonant line technique using a two-polynomial equation. Different parametric variations in the model have been outlined as case studies. Furthermore, electrical performance and signal integrity analysis on different cases have been used to determine the optimized configuration for CNT-based TSVs for high frequency RF applications.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.137-146
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• 2006

Shared Memory Multiprocessor (SMP) systems adopting Chip-level MultiThreading (CMT) technology are becoming mainstream servers in commercial applications and High Performance Computining (HPC) applications as well. OpenMP has become the standard paradigm to parallelize applications for SMP mostly because of its ease of use. As the demand for more computing power in HPC applications is growing rapidly, obtaining high performance and scalability for these applications parallelized using OpenMP API's will become more important. In this paper, we study the performance and scalability of HPC applications parallelized using OpenMP, SPEC OMPL (standard OpenMP benchmark suite), on the Sun Fire E25K server which adopts CMT technology. We also study the effect of CMT on SPEC OMPL.

• Composites Research
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• v.19 no.1
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• pp.43-48
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• 2006

High performance fiber reinforced cement composites have better performances than traditional cement based materials, therefore, have been expected as new construction applications such as the materials for construction & bridge structure, repair and rehabilitation applications, anti-collapse applications, anti-noise applications etc. However, they have lots of the problems such as material design, fabrication method and structural analysis. Also, the most serious problems of High performance fiber reinforced cement composites have been expensive initial cost, lack of long-term exposure data. As a result, it is needed that the efforts for lowering the initial cost and accumulation of long-term exposure. There has been hardly assessment results of life cycle cost for HPFRCC in construction field, but some papers showed that total life cycle cost could be profitable if the initial cost could be reduced.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

• International Journal of Concrete Structures and Materials
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• v.10 no.2
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• pp.125-142
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• 2016

An overall review of the structural behaviors of ultra-high-performance fiber-reinforced concrete (UHPFRC) elements subjected to various loading conditions needs to be conducted to prevent duplicate research and to promote its practical applications. Thus, in this study, the behavior of various UHPFRC structures under different loading conditions, such as flexure, shear, torsion, and high-rate loads (impacts and blasts), were synthetically reviewed. In addition, the bond performance between UHPFRC and reinforcements, which is fundamental information for the structural performance of reinforced concrete structures, was investigated. The most widely used international recommendations for structural design with UHPFRC throughout the world (AFGC-SETRA and JSCE) were specifically introduced in terms of material models and flexural and shear design. Lastly, examples of practical applications of UHPFRC for both architectural and civil structures were examined.