• The Journal of Information Systems
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• v.15 no.4
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• pp.171-188
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• 2006

Information technology and the Internet have had a dramatic effect on education method and individual life. Universities and companies we making large investments in e-Learning applications but are hard to pressed to evaluate the success of their e-Learning systems. e-Learning can be seen as not only one of Internet based information systems which can provide education services but also one of teaching-teaming methods which can implement self-directed teaming. This paper tests the updated model of information system success proposed by Delone and McLean using a field study of a e-Learning. The five dimensions - information quality, system quality, service quality, user satisfaction, net benefit - of the updated model are parsimonious framework for organizing the e-learning success metrics identified in the literature. Questionaires are collected from 107 students who are enrolling a e-learning class using online survey. The model is tested using SPSS and LISREL. The results show that information quality and service quality are significant predictors of user satisfaction with the e-Learning system but system quality is not. Also user satisfaction is found to be a strong predictor of the learning performance. This strong association between user satisfaction and teaming performance suggests that user satisfaction may serve as a valid surrogate for teaming performance. Empirical testing of the updated DeLone & McLean model should therefore be extended to cover a wider variety of systems.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.19-26
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• 2018

One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

• Journal of the Korean Mathematical Society
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• v.60 no.1
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• pp.115-141
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• 2023

We study a class of left-invariant pseudo-Riemannian Sasaki metrics on solvable Lie groups, which can be characterized by the property that the zero level set of the moment map relative to the action of some one-parameter subgroup {exp tX} is a normal nilpotent subgroup commuting with {exp tX}, and X is not lightlike. We characterize this geometry in terms of the Sasaki reduction and its pseudo-Kähler quotient under the action generated by the Reeb vector field. We classify pseudo-Riemannian Sasaki solvmanifolds of this type in dimension 5 and those of dimension 7 whose Kähler reduction in the above sense is abelian.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3693-3711
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• 2020

e-Governance is a medium to offer various services to citizens through a web portal, that exists in many countries nowadays. The existing e-Governance technology is a vast, centrally managed database and a set of applications that connect to it via web interfaces. Despite the modernisation of services, it remains with the lack of transparency. Thus, the existing infrastructure of e-Governance paves the way for corrupt practises by the bureaucrats. e-Governance needs a powerful underlying technology which doesn't provide any way to allow tampering of the record and which in turn eliminates corruption. In this paper, we took land registration as a use-case for building e-Governance by keeping Blockchain as an underlying technology, to put off the corrupt practices and to bring transparency. Once transactions in land registration added to the Blockchain, it is immutable as it is cryptographically secured. Besides, the blockchain technology is secured as the ledger is distributed over the network. If a hacker wants to modify the ledger, he needs to hack every node in the blockchain network. Hyperledger Fabric, a permissioned Blockchain adopted for implementation and Hyperledger Caliper for performance analysis with these evaluation metrics such as throughput, latency and execution time.

• Korean Journal of Ecology and Environment
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• v.46 no.2
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• pp.145-153
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• 2013

It is a global trend that the water management policy is shifting from a water quality-oriented assessment to the aquatic ecosystem-based assessment. The majority of aquatic ecosystem assessment systems were developed solely based on physicochemical factors (e.g., water quality and bed structure) and a limited number of organisms (e.g., plankton and benthic organisms). Only a few systems use plants for a health assessment, although plants are sensitive indicators reflecting long-term disturbances and alterations in water regimes. The development of an assessment system is underway to evaluate and manage lakes as ecosystem units in the Korean Ministry of Environment. We reviewed the existing multivariate health assessment methods of other leading countries, and discussed their applicability to Korean lakes. The application of multivariate assessment methods is costly and time consuming, in addition to the correlation problem among variables. However, a single variable is not available at this moment, and the multivariate method is an appropriate system due to its multidimensional evaluation and cumulative data generation. We, therefore, discussed multivariate assessment methods in three steps: selecting metrics, scoring metrics and assessing indices. In the step of selecting metrics, the best available metrics are species-related variables, such as composition and abundance, as well as richness and diversity. Indicator species, such as sensitive species, are the most frequently used in other countries, but their system of classification in Korea is not yet complete. In terms of scoring metrics, the lack of reference lakes with little anthropogenic impact make this step difficult, and therefore, the use of relative scores among the investigated lakes is a suitable alternative. Overall, in spite of several limitations, the development of a plant-based multivariate assessment method in Korea is possible using mostly field research data. Later, it could be improved based on qualitative metrics on plant species, and with the emergence of further survey data.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.3
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• pp.169-181
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• 2011

In this present paper, a comprehensive drain current model incorporating the effects of channel length modulation has been presented for multi-layered gate material engineered trapezoidal recessed channel (MLGME-TRC) MOSFET and the expression for linearity performance metrics, i.e. higher order transconductance coefficients: $g_{m1}$, $g_{m2}$, $g_{m3}$, and figure-of-merit (FOM) metrics; $V_{IP2}$, $V_{IP3}$, IIP3 and 1-dB compression point, has been obtained. It is shown that, the incorporation of multi-layered architecture on gate material engineered trapezoidal recessed channel (GME-TRC) MOSFET leads to improved linearity performance in comparison to its conventional counterparts trapezoidal recessed channel (TRC) and rectangular recessed channel (RRC) MOSFETs, proving its efficiency for low-noise applications and future ULSI production. The impact of various structural parameters such as variation of work function, substrate doping and source/drain junction depth ($X_j$) or negative junction depth (NJD) have been examined for GME-TRC MOSFET and compared its effectiveness with MLGME-TRC MOSFET. The results obtained from proposed model are verified with simulated and experimental results. A good agreement between the results is obtained, thus validating the model.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.355-364
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• 2005

Previous researches on subsequence matching have been focused on how to make indexes in order to speed up the matching time, and do not take into account the effectiveness issues of subsequence matching methods. This paper considers the effectiveness of subsequence matching methods and proposes two metrics for effectiveness evaluations of subsequence matching algorithms. We have applied the proposed metrics to Korean stock data and five known matching algorithms. The analysis on the empirical data shows that two methods (i.e., the method supporting normalization, and the method supporting scaling and shifting) outperform the others in terms of the effectiveness of subsequence matching.

• Journal of Communications and Networks
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• v.8 no.2
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• pp.241-252
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• 2006

Traditional service-level agreements (SLAs), defined by average delay or packet loss, often camouflage the instantaneous performance perceived by end-users. We define a set of metrics for service availability to quantify the performance of Internet protocol (IP) backbone networks and capture the impact of routing dynamics on packet forwarding. Given a network topology and its link weights, we propose a novel technique to compute the associated service availability by taking into account transient routing dynamics and operational conditions, such as border gateway protocol (BGP) table size and traffic distributions. Even though there are numerous models for characterizing topologies, none of them provide insights on the expected performance perceived by end customers. Our simulations show that the amount of service disruption experienced by similar networks (i.e., with similar intrinsic properties such as average out-degree or network diameter) could be significantly different, making it imperative to use new metrics for characterizing networks. In the second part of the paper, we derive goodness factors based on service availability viewed from three perspectives: Ingress node (from one node to many destinations), link (traffic traversing a link), and network-wide (across all source-destination pairs). We show how goodness factors can be used in various applications and describe our numerical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1717-1732
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• 2015

The widespread use of location-based services (LBSs), which allows untrusted service provider to collect large number of user request records, leads to serious privacy concerns. In response to these issues, a number of LBS privacy protection mechanisms (LPPMs) have been recently proposed. However, the evaluation of these LPPMs usually disregards the background knowledge that the adversary may possess about users' contextual information, which runs the risk of wrongly evaluating users' query privacy. In this paper, we address these issues by proposing a generic formal quantification framework,which comprehensively contemplate the various elements that influence the query privacy of users and explicitly states the knowledge that an adversary might have in the context of query privacy. Moreover, a way to model the adversary's attack on query privacy is proposed, which allows us to show the insufficiency of the existing query privacy metrics, e.g., k-anonymity. Thus we propose two new metrics: entropy anonymity and mutual information anonymity. Lastly, we run a set of experiments on datasets generated by network based generator of moving objects proposed by Thomas Brinkhoff. The results show the effectiveness and efficient of our framework to measure the LPPM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1613-1631
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• 2011

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised that consists of three main components, i.e., stereo attention predictor (SAP), depth variation (DV), and stereo distortion predictor (SDP). Visual attention is modeled based on entropy and inverse contrast to detect regions or objects of interest/attention. Depth variation is fused into the attention probability to account for the amount of changed depth in distorted stereo images. Finally, the stereo distortion predictor is designed by integrating distortion probability, which is based on low-level human visual system (HVS), responses into actual attention probabilities. The results show that regions of attention are detected among the visually significant distortions in the stereo image pair. Drawbacks of human visual sensitivity based picture quality metrics are alleviated by integrating visual attention and depth information. We also show that positive correlation with ground-truth attention and depth maps are increased by up to 0.949 and 0.936 in terms of the Pearson and the Spearman correlation coefficients, respectively.