• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.1
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• pp.25-33
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• 2020

Multipath routing protocols with unmanned aerial vehicles have been proposed to improve reliability in tactical ad hoc networks. Most of existing studies tend to establish the paths with multiple metrics. However, these approaches suffer from link loss and congestion problems according to the network condition because they apply same metric for both ground and air path or employ the simple weight value to combine multiple metrics. To overcome this limitation, in this study, we propose new routing metrics for path over unmanned aerial vehicles and use the multi-criteria decision making (MCDM) method to determine the weight factors between multiple metrics. For the case studies, we extend the ad-hoc on-demand distance vector protocol and propose a strategy for modifying the route discovery and route recovery procedure. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in tactical ad hoc networks.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.97-118
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• 1996

Information systems quality engineering is one of the most problematic areas in practice and research, and needs cooperative efforts between practice and theory [Glass, 1996]. A model for evaluating the quality of system development process and ensuing success is proposed based on information processing theory of project unit design. A nomological net among a set of quality variables is identified from prior research in the areas of organization science, software engineering, and management information systems. More specifically, system development success was modelled as a function of project complexity, system development modelling environment, user participation, project unit structure, resource availability, and the level of iterative nature of development methodology. Based on the model developed from the information processing theory of project unit design in organization science. appropriate quality metrics for each variable in the proposed model are matched. In this way, a framework of relevant systems development and success quality metrics for controlling systems development processes and ensuing success is proposed. The causal relationships among the constructs in the proposed model are proposed as future empirical research for academicians and as managerial tools for quality managers. The framework and propositions help quality manager to select more parsimonious quality metrics for controlling information systems development processes and project success in an integrated way. Also this model can be utilized for evaluating software quality assurance programmes, which are developed and marketed by many vendors.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1131-1141
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• 2004

Cohesion refers to the degree of the relatedness of the elements in a module, and it is widely accepted that the module of higher cohesion is easier to understand, maintain, and reuse. Recently, several cohesion metrics have been proposed to measure the cohesiveness of classes in an object-oriented program. However, the existing cohesion metrics do not consider the characteristics of dependent instance variables that are commonly used in a class and, thus, do not properly reflect the cohesiveness of the class. This paper presents an approach for improving the cohesion metrics by considering the characteristics of the dependent instance variables in an object-oriented program. To demonstrate the importance of the dependent instance variables, a case study has been conducted on a class library.

• Journal of Internet Computing and Services
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• v.3 no.4
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• pp.71-82
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• 2002

Recently. component-based software development is getting accepted in industry as a new effective software development paradigm, Since an introduction of component-based software engineering(CBSE) at later 90's, the CBSD research has focused largely on component modeling, methodology, architecture and platform, However. as the number of components available on the market increases, it becomes more important to make metrics to measure the various characteristics of components. In this paper. we propose metrics for measuring the complexity, customizability, and resuability of software components, Complexity of metrics can be used to evaluate the complexity of components Customizability is used to measure how efficiently and widely the components can be customized for specific requirements organization, Resuability can be used to measure the degree of features that is reused in building applications.

• Clinical and Experimental Reproductive Medicine
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• v.41 no.4
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• pp.147-150
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• 2014

Objective: Clinical and Experimental Reproductive Medicine (CERM) converted its language to English only beginning with the first issue of 2011. From that point in time, one of the goals of the journal has been to become a truly international journal. This paper aims to identify the position of CERM in its scholarly journal network based on the journal's metrics. Methods: The journal's metrics, including citations, countries of author affiliation, and countries of citing authors, Hirsch index, and proportion of funded articles, were gathered from Web of Science and analyzed. Results: The two-year impact factor of 2013 was calculated at 0.971 excluding self-citation, which corresponds to a Journal Citation Reports ranking of 85.9% in the category of obstetrics and gynecology. In 2012, 2013, and 2014, the total citations were 17, 68, and 85, respectively. Authors from nine countries contributed to CERM. Researchers from 25 countries cited CERM in their articles. The Hirsch index was six. Out of 88 original articles, 35 studies received funds (39.8%). Conclusion: Based on the journal metrics, changing the journal language to English was found to be successful in promoting CERM to international journal status.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.618-641
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• 2003

Various quality models using quality factor, quality criteria and metrics have been proposed in order to evaluate quality of software products. However, a customized quality model which is specific to the characteristics of software component is required. In this paper, we propose external quality prediction techniques enable us to predict what external quality the final software product will have by using metrics as with internal attributes of software in development. We also propose a model not only for measuring quality by using metrics but also for applying internal attributes of ISO 9126 into artifacts of software component development.

• Journal of the Korea Computer Industry Society
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• v.2 no.3
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• pp.377-388
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• 2001

Software metrics provide effective methods for characterizing software. Metrics have traditionally been composed through the definition of an equation, but this approach restricted within a full understanding of every interrelationships among the parameters. This paper use fuzzy logic system that is capable of uniformly approximating any nonlinear function and applying cognitive psychology theory. First of all, we extract multiple regression equation from the factors of 12 software complexity metrics collected from Java programs. We apply cognitive psychology theory in program volume factor, and then measure program volume complexity to execute fuzzy learning. This approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics.

• Journal of the Ergonomics Society of Korea
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• v.34 no.3
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• pp.235-245
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• 2015

Objective: The purpose of this study is to develop visual complexity metrics based on theoretical bases. Background: With the development of IT technologies, drivers process a large amount of information caused by automotive human-machine interface (HMI), such as a cluster, a head-up display, and a center-fascia. In other words, these systems are becoming more complex and dynamic than traditional driving systems. Especially, these changes can lead to the increase of visual demands. Thus, a concept and tool is required to evaluate the complicated systems. Method: We reviewed prior studies in order to analyze the visual complexity. Based on complexity studies and human perceptual characteristics, the dimensions characterizing the visual complexity were determined and defined. Results: Based on a framework and complexity dimensions, a set of metrics for quantifying the visual complexity was developed. Conclusion: We suggest metrics in terms of perceived visual complexity that can evaluate the in-vehicle displays. Application: This study can provide the theoretical bases in order to evaluate complicated systems. In addition, it can quantitatively measure the visual complexity of In-vehicle information system and be helpful to design in terms of preventing risks, such as human error and distraction.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.470-477
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• 2012

Climate related policies have been considered due to increase of energy and fossil fuel consumption. Therefore, research has been done to reduce $CO_2$ and to implement green construction. This paper proposes green construction performance metrics for transportation facilities based on previous literature review and survey. The metrics are composed with economic, social, and environment parts and number of metrics are 14, 10, and 12 respectively. The survey was performed to evaluate relevance, clarity, timeliness, comparable, and obtainable of the proposed metrics. Then implementation strategy is also proposed for effective use.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.174-179
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• 2005

In automotive engineering, the brand sound is one of the important advantage strategy in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In paper, booming sound and rumbling sound, which are professional words used by NVH engineers are used for the design of brand sound. We employed sound metrics which are the subjective parameter used in psychoacoustics. According to most research results, the relationship between subjective evaluations and sound metrics has nonlinear characteristics and is very complex. In order to link these subjective evaluations to sound metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes is used for 46 passenger cars, which are samples of famous cars in the world. Also the preference in car sounds is evaluated by the trained NVH engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two -dimensional sound index and preference index are very useful fur the development of brand sound in passenger cars.