The priority of requirement is important because the priority is a critical activity of release plan especially in software development which has an open market customer. Also, it is important for stakeholders to select a method and aspects to prioritize requirements. The selection is based on the organizational experience of a priority process, the process model of the product, goals and a type of products, and dependencies between requirements. But, the current researches considered only static dependency between requirements and did not suggest a systematic priority process. In addition, the current researches only suggest limited aspects to prioritize requirements, such as cost and value. Therefore, this paper proposes an adjustable priority process based on a priority model to select a method and aspects for the suitable priority for product and organization. Especially, this paper enhances the completeness of a release plan by a definition of static and dynamic dependency types between requirements. This paper suggests a priority model, which considers the dependencies between requirement and various viewpoint of software development. Based on the priority model, the paper suggests a systematic priority process to promote reasonable decisions to the priority and release plan of requirement.
Journal of Korean Society of Coastal and Ocean Engineers
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v.8
no.2
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pp.123-136
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1996
A three-dimensional Galerkin-FEM model which can handle the temporal and spatial variation of density is presented. The hydrostatic approximation is used and density effects are included by means of conservation equation of heat and the equation of state. The finite difference grids are used in the horizontal plane and a set of linear-shape functions is used for the vertical expansion. The similarity transform is introduced to solve resultant matrix equations. The proposed model was first applied to the density-driven circulation in an idealized basin in the presence of the heat exchange between the air and the sea. The advection terms in the momentum equation were ignored, while the convection terms were retained in the heat equation. Coefficients of the vertical eddy viscosity and diffusivity were fixed to be constant. Calculation in a non-rotating idealized basin shows that the difference in heat capacity with depth gives rise to the horizontal gradient of temperature. Consequently, there is a steady new in the upper layer in the direction of increasing depth with compensatory counter flow .in the lower layer. With Coriolis force, geostrophic flow was predominant due to the balance between the pressure gradient and the Coriolis force. As a test in region of irregular topography, the model is applied to the Yellow Sea. Although the resultant flow was very complex, the character of the flow Showed to be geostrophic on the whole.
This paper presents the design of service model, transport channel, and service signaling for the Terrestrial DMB Automatic Emergency Alert Service (AEAS) Standard. The paper begins with the analysis of technical backgrounds related to the design topics. Next, the raper presents the design of service model for the AEAS. Since, unlike the regular T-DMB services, the AEAS is event-driven and common to all services, some problems have been identified to design a service model conforming to the T-DMB standard. So, the paper proposes a new concept, called the common service, and the AEAS is modeled using the common service. Next, in order to decide the transport channel for the alert information, the paper proposes to divide the alert information into the message which contains code/text-based essential information, and the supplemental multimedia information. Then, the paper tries to find the most efficient transport channels. Emergency Warning Service (EWS) which uses FIG 5/2 is selected for the delivery of the message. The paper proposes no constraints on delivery of supplemental information except that it shall use the MSC. Finally, it proposes the service signaling for the common service and transport channel. Due to the problems of conventional signaling using the MCI, it proposes a new signaling method. The paper will contribute as a guideline to the development for emergency alert service standards fur other broadcasting media.
Kim, Yong-Jin;Nam, Ki-Chan;Song, Jae-Ki;Koo, Chul-Mo
Asia pacific journal of information systems
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v.17
no.3
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pp.131-146
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2007
Recently, the role of IT service providers has been enlarged from managing a single function or system to reconstructing entire information management processes in new ways to contribute to shareholder value across the enterprise. This movement toward extensive and complex outsourcing agreements has been driven by the assumption that outsourcing information technology functions is a reliable approach to maximizing resource productivity. Hiring external IT service providers to manage part or all of its information-related services helps a firm focus on its core business and provides better services to its clients, thus obtaining sustainable competitive advantage. This practice of focusing on the strategic aspect of outsourcing is referred to as strategic sourcing where the focus is capability sourcing, not procurement. Given the importance of the strategic outsourcing, however, to our knowledge, there is little empirical research on the relationship between the strategic outsourcing orientation and outsourcing performance. Moreover, there is little research on the factor that makes the strategic outsourcing effective. This study is designed to investigate the relationship between strategic IT outsourcing orientation and IT outsourcing performance and the process through which strategic IT outsourcing orientation influences outsourcing performance, Based on the framework of strategic orientation-performance and core competence based management, this study first identifies core competency orientation as a proper strategic orientation pertinent to IT outsourcing and IT outsourcing process management capability as the mediator to affect IT outsourcing performance. The proposed research model is then tested with a sample of 200 firms. The findings of this study may contribute to the literature in two ways. First, it draws on the strategic orientation - performance framework in developing its research model so that it can provide a new perspective to the well studied phenomena. This perspective allows practitioners and researchers to look at outsourcing from an angle that emphasizes the strategic decision making to outsource its IT functions. Second, by separating the concept of strategic orientation and outsourcing process management capability, this study provides practices with insight into how the strategic orientation can work effectively to achieve an expected result. In addition, the current study provides a basis for future studies that examine the factors affecting IT outsourcing performance with more controllable factors such as IT outsourcing process management capability rather than external hard-to-control factors including trust and relationship management. This study investigates the major factors that determine IT outsourcing success. Based on strategic orientation and core competency theories, we develop the proposed research model to investigate the relationship between core competency orientation and IT outsourcing performance and the mediating role of IT outsourcing process management capability on IT outsourcing performance. The model consists of two independent variables (core-competency-orientation and IT outsourcing process management capability), and two dependent variables (outsourced task complexity and IT outsourcing performance). Comprehensive data collection was conducted through an outsourcing association. The survey data were analyzed using a structural analysis method. IT outsourcing process management capability was found to mediate the effect of core competency orientation on both outsourced task complexity and IT outsourcing performance. Further analysis and findings are discussed.
Han Hyun Chul;Cho Chang Soo;Suh Jung Hee;Lee Doo Sung
Geophysics and Geophysical Exploration
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v.1
no.1
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pp.49-56
/
1998
Seismic tomography has been widely used as high resolution subsurface imaging techniques in engineering applications. Although most of the techniques have been using travel time inversion, waveform method is being driven forward owing to the progress of computational environments. Although full-waveform inversion method has been known as the best method in terms of model resolving power without high-frequency restriction and weak scattering approximation, it has practical disadvantage that it is apt to get stuck in local minimum if the initial guess is far from the actual model and it consumes so much time to calculate. In this study, 2-D full-waveform inversion algorithm in acoustic medium is developed, which uses result of traveltime tomography as initial model. From the application on synthetic data, it is proved that this approach can efficiently reduce the problem of conventional approaches: our algorithm shows much faster convergence rate and improvement of model resolution. Result of application on physical modeling data also shows much improvement. It is expected that this algorithm can be applicable to real data.
With the recent establishment of a ubiquitous-based medical and healthcare environment, the medical information system for obtaining situation information from various sensors is increasing. In the medical information system environment based on context-awareness, the patient situation can be determined as normal or emergency using situational information. In addition, medical staff can easily access patient information after simple user authentication using ID and Password through applications on smart devices. However, these services of authentication and patient information access are staff-oriented systems and do not fully consider the ubiquitous-based healthcare information system environment. In this paper, we present a authentication service model based context-awareness system for providing situational information-driven authentication services to users who access medical information, and implemented proposed system. The authentication service model based context-awareness system is a service that recognizes patient situations through sensors and the authentication and authorization of medical staff proceed differently according to patient situations. It was implemented using wearables, biometric data measurement modules, camera sensors, etc. to configure various situational information measurement environments. If the patient situation was emergency situation, the medical information server sent an emergency message to the smart device of the medical staff, and the medical staff that received the emergency message tried to authenticate using the application of the smart device to access the patient information. Once all authentication was completed, medical staff will be given access to high-level medical information and can even checked patient medical information that could not be seen under normal situation. The authentication service model based context-awareness system not only fully considered the ubiquitous medical information system environment, but also enhanced patient-centered systematic security and access transparency.
Rasheed, Adnan;Lee, Jong Won;Kim, Hyeon Tae;Lee, Hyun Woo
Journal of Bio-Environment Control
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v.28
no.3
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pp.225-233
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2019
In the summer season, natural ventilation is commonly used to reduce the inside air temperature of greenhouse when it rises above the optimal level. The greenhouse shape, vent design, and position play a critical role in the effectiveness of natural ventilation. In this study, computational fluid dynamics (CFD) was employed to investigate the effect of different roof vent designs along with side vents on the buoyancy-driven natural ventilation. The boussinesq hypothesis was used to simulate the buoyancy effect to the whole computational domain. RNG K-epsilon turbulence model was utilized, and a discrete originates (DO) radiation model was used with solar ray tracing to simulate the effect of solar radiation. The CFD model was validated using the experimentally obtained greenhouse internal temperature, and the experimental and computed results agreed well. Furthermore, this model was adopted to compare the internal greenhouse air temperature and ventilation rate for seven different roof vent designs. The results revealed that the inside-to-outside air temperature differences of the greenhouse varied from 3.2 to $9.6^{\circ}C$ depending on the different studied roof vent types. Moreover, the ventilation rate was within the range from 0.33 to $0.49min^{-1}$. Our findings show that the conical type roof ventilation has minimum inside-to-outside air temperature difference of $3.2^{\circ}C$ and a maximum ventilation rate of $0.49min^{-1}$.
Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.
A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.1
/
pp.415-423
/
2021
Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.
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