• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.89-104
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• 2024

Cloud-based e-learning (CBEL) represents a promising technological frontier. Existing literature has presented a diverse array of findings regarding the determinants that influence the adoption of CBEL. The primary objective of this study is to conduct an exhaustive examination of the available literature, aiming to determine the key predictors of CBEL utilization by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A comprehensive review of 35 articles was undertaken, shedding light on the status of CBEL as an evolving field. Notably, there has been a discernible downturn in related research output during the COVID-19 pandemic, underscoring the temporal dynamics of this subject. It is noteworthy that a significant portion of this research has emanated from the Asian continent. Furthermore, the dominance of the technology acceptance model (TAM) in research frameworks is affirmed by our findings. Through a rigorous thematic analysis, our study identified five overarching themes, each encompassing a diverse range of sub-themes. These themes encompass 1) technological factors, 2) individual factors, 3) organizational factors, 4) environmental factors, and 5) security factors. This categorization provides a structured framework for understanding the multifaceted nature of CBEL adoption determinants. Our study serves as a compass, guiding future research endeavours in this domain. It underscores the imperative for further investigations utilizing diverse theoretical frameworks, contextual settings, research methodologies, and variables. This call for diversity and expansion in research efforts reflects the dynamic nature of CBEL and the evolving landscape of e-learning technologies.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.391-395
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• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.13-27
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• 2014

Agile methodologies have gained recognition as efficient development processes through their quick delivery of software, even under time constraints. However, like other agile methods such as Scrum, Extreme Programming (XP) and The Dynamic Systems Development Method (DSDM), Feature Driven Development (FDD) has been criticized due to the unavailability of security elements in its twelve practices. In order to examine this matter more closely, we conducted a systematic literature review (SLR) and studied literature for the years 2001-2012. Our findings highlight that, in its current form, the FDD model partially supports the development of secure software. However, there is little research on this topic, as detailed information about the usage of secure software is rarely published. Thus, we have been able to conclude that the existing five phases of FDD have not been enough to develop secure software until recently. For this reason, security-based phase and practices in FDD need to be proposed.

• Advances in aircraft and spacecraft science
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• v.5 no.2
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• pp.251-258
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• 2018

This work illustrates the progress of a TAS activity at exploring the challenges and the benefits of the Virtual Shaker Testing (VST) approach. The definition and the validation of new computational methodologies with respect to the state of the art were encouraged throughout this activity. The shaker Finite Element (FE) model in lateral configuration was built for the purpose and it was merged with the SpaceCraft (S/C) FE model, together with the S/C-Shaker adapter. FE matrices were reduced through the Craig-Bampton method. The VST transient analysis was performed in MATLAB(R) numerical computing environment. The closed-loop vibration control is accounted for and the solution is obtained through the fourth-order Runge Kutta method. The use of pre-existing built-in functions was limited by authors with the aim of tracing the impact of all the problems' parameters in the solution. Assumptions and limitations of the proposed methodology are detailed throughout this paper. Some preliminary results pertaining to the current progress of the activity are thus illustrated before the conclusions.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.748-752
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• 2008

Various services are developed from advancement of satellite imagery methodologies and internet infrastructure expansions. However, most of these services still rely upon low-resolution satellite images combined with DEM models. In this paper, we have implemented the raw data processing modules and other modules that transfer and render high-spatial resolution satellite images for efficient streaming services in web environments. By utilizing the Bukhan-mountain data as a pilot study, the paper has proposed the efficient approach to solve graphical problems in real time processing the large geographical area.

• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.257-266
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• 2012

This paper overviews clock design problems related to the circuit reliability in deep submicron design technology. The topics include the clock polarity assignment problem for reducing peak power/ground noise, clock mesh network design problem for tolerating clock delay variation, electromagnetic interference aware clock optimization problem, adjustable delay buffer allocation and assignment problem to support multiple voltage mode designs, and the state encoding problem for reducing peak current in sequential elements. The last topic belongs to finite state machine (FSM) design and is not directly related to the clock design, but it can be viewed that reducing noise at the sequential elements driven by clock signal is contained in the spectrum of reliable circuit design from the clock source down to sequential elements.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.45-48
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• 2003

We can easily buy network system for high performance micro-processor, progress computer architecture is caused of high bandwidth and low delay time. Coupling PC-based commodity technology with distributed computing methodologies provides an important advance in the development of single-user dedicated systems. Lately Network is joined PC or workstation by computers of high performance and low cost. Than it make intensive that Cluster system is resembled supercomputer. Unix, Linux, BSD, NT(Windows series) can use Cluster system OS(operating system). I'm chosen linux gain low cost, high performance and open technical documentation. This paper is benchmark performance of Beowulf clustering by UltraSPARC-1K(64bit-RISC processor). Benchmark tools use MPI(Message Passing Interface) and NetPIPE. Beowulf is a class of experimental parallel workstations developed to evaluate and characterize the design space of this new operating point in price-performance.

• Journal of Mechanical Science and Technology
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• v.18 no.5
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• pp.814-819
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• 2004

The conceptual design of a rotorcraft system involves many different analysis disciplines. The decomposition of such a system into several subsystems can make analysis and design more efficient in terms of the total computation time. Adaptive parallel decomposition makes the structure of the overall design problem suitable to apply the multidisciplinary design optimization methodologies and it can exploit parallel computing. This study proposes a decomposition method which adaptively determines the number and sequence of analyses in each sub-problem corresponding to the available number of processors in parallel. A rotorcraft design problem is solved and as a result, the adaptive parallel decomposition method shows better performance than other previous methods for the selected design problem.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.263-275
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• 2000

Multidisciplinary design optimization(MDO) can yield optimal design considering all the disciplinary requirements concurrently. A method to implement the collaborative optimization(CO) approach, one of the MDO methodologies, is developed using a pre-compiler “EzpreCompiler”, a design optimization library “EzOptimizer”, and a common object request broker architecture(CORBA) in distributed computing environment. The CO approach is applied to a mathematical example to show its applicability and equivalence to standard optimization(SO) formulation. In a realistic engineering problem such as optimal design of a two-member hub frame, optimal design of a speed reducer and initial design of a bulk carrier, the CO yields better results than the SO. Furthermore, the CO allows the distributed processing using the CORBA, which leads to reduction of overall computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2964-2983
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• 2015

As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field.