• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.101-108
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• 2023

Decision Support Systems (DSS) is an Information Systems (IS) application that aids in decision-making processes for many business concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model and for the purpose of the study we have compared the CRM between patients and hospital management.

• Advances in Computational Design
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• v.8 no.4
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• pp.327-351
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• 2023

This article explores how multi-objective optimization techniques can be used to design cost-effective and structurally optimal spatial steel structures, highlighting that optimizing performance can be as important as minimizing costs in real-world engineering problems. The study includes the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor concerning the first global buckling mode of the structure, and weight minimization as the objectives. Additionally, it outlines a systematic approach to selecting the best design by employing four different evolutionary algorithms based on differential evolution and a multi-criteria decision-making methodology. The paper's contribution lies in its comprehensive consideration of multiple conflicting objectives and its novel approach to simultaneous consideration of bracing system, column orientation, and commercial profiles as design variables.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Management & Information Systems Review
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• v.37 no.4
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• pp.195-217
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• 2018

Inaction inertia effect refers to the phenomenon wherein people who missed attractive opportunities in the past do not take any action when they are given the opportunity to receive discounts (sale). The main objective of this study was to find out how such inaction inertia effect influenced the expected regret from the action, expected regret from inaction, and purchase intention depending on the two types of consumption purposes-for pleasure and for practical use. As the personal disposition of each consumer differs from one another, it was expected that habitual purchase behavior and maximization behavior would influence the inaction inertia. An experiment was thus conducted by using a scenario to satisfy the objective of this study. Results showed that in the case of consumers whose consumption purpose was for pleasure, those who habitually purchased the same brand showed a higher level of expected regret from the action and expected regret from inaction. In the case of maximization behavior, no differences were found in the expected regret from the action between practical consumption purpose and pleasurable consumption purpose. On the other hand, differences were found in the level of expected regret from inaction, which is the case wherein consumers who missed their first opportunity to receive discounts (sale) did not make any purchase on their second opportunity for discounts (sale). Thus, inaction inertia was shown in accordance with habitual purchase behavior in the case of consumption purpose for pleasure, but it was not clearly shown in the case of consumption for practical use. This is because there is a relatively low level of justification on consumption, in the case of consumption for practical use. On the other hand, it was found that consumers with maximization behavior felt a stronger sense of regret in the case of their expected regret for inaction in consumption for practical use than in consumption for pleasure. Also, with regard to purchase intention, it turned out that only consumers with pleasurable consumption purpose had purchase intentions. Through these study results, it would be necessary to consider the consumption purpose behind the purchase of products or services, with regard to inaction inertia, depending on personal dispositions. In accordance with these study results, several theoretical and practical implications were discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11A
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• pp.878-891
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• 2011

We consider the throughput-maximization problem for both the up- and downlink in a wireless network with interference channels. For this purpose, we design an iterative and distributive uplink algorithm based on Lagrangian relaxation. Using the uplink power prices and network duality, we achieve throughput-maximization in the dual downlink that has a symmetric channel and an equal power budget compared to the uplink. The network duality we prove here is a generalized version of previous research [10], [11]. Computational tests show that the performance of the up- and downlink throughput for our algorithms is close to the optimal value for the channel orthogonality factor, ${\theta}{\in}$(0.5, 1]. On the other hand, when the channels are slightly orthogonal (${\theta}{\in}$(0, 0.5]), we observe some throughput degradation in the downlink. We have extended our analysis to the real downlink that has a nonsymmetric channel and an unequal power budget compared to the uplink. It is shown that the modified duality-based approach is thoroughly applied to the real downlink. Considering the complexity of the algorithms in [6] and [18], we conclude that these results are quite encouraging in terms of both performance and practical applicability of the generalized duality theorem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.436-446
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• 2018

The purpose of this study is to examine the priorities of innovation activities, business performance, and maximization factors of SMEs. Support programs for each government department are operated by various industries. Various supports, including subsidies, grants, marketing, planning, and education, are provided to each company. Therefore, this study aims to analyze and identify the priorities of innovation activities that have a positive effect on business performance. The efficacy of the proposed model and the psychometric properties of structure were analyzed using the analytic hierarchy process (AHP). The hierarchical structure of corporate innovation activities are composed of 'R&D' and 'government support', and 'Inside R&D, Outsourcing R &D, Consortium R&D'. As a result of analyzing companies that received more than one type of R&D government support, it can be seen that 'government support' (72.1%) is more important than 'research and development' (27.8%). In addition, this study found key sub-factors loadings including Assistant Support (30.1%), Tax Support (22.7%), Funding Support (18.8%), Inside R&D (10.8%), Outsourcing R&D (10.3%), and Consortium R&D (7.2%). Analysis results suggest that the priorities of detailed innovation activities of R&D and government support affect product innovation and process innovation, which in turn, influence business performance and maximization of SMEs. This implies that SMEs who want to participate in the government support project will be helpful in setting the direction of innovation activities. This study also suggests the importance of strategic priorities among the decision elements for CEOs.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.537-542
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• 2017

Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Asia Marketing Journal
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• v.14 no.3
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• pp.49-68
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• 2012

When a channel is vertically separated, there can be inefficiencies, double marginalization. Channel coordination to amend this inefficiency has been an important issue in marketing and economics. Channel coordination deals with maximization of joint profit and achieving proper profit sharing among participants. In this paper, a manufacturer and heterogeneous multiple retailers with exclusive territory are assumed, and channel coordination with two-part tariff is considered. When multiple heterogeneous retailers are assumed, profit sharing can be an issue even though the tariffs based on marginal cost can maximize joint profit. In case of multiple heterogeneous retailers, the manufacturer earns the same profit (fixed fee) from each retailer. This means that a large retailer occupies all the gaps of channel profit between small and large markets. Then, the manufacturer, which generally plays the role of Stackelberg leader, will consider increasing fixed price or marginal price to earn more profit from large retailer. Those reactions can sacrifice maximization of joint profit by making small retailer withdraw or by changing the sales quantities. In this paper, to maximize joint profit and achieve proper profit sharing, two kinds of optional tariffs are considered. The first is an optional two-part tariff based on marginal cost and the second is an optional modified two-part tariff in which marginal prices are higher than the manufacturer's marginal cost. In both types of optional tariffs, maximization of joint profit in each market can be achieved. Moreover, optional tariffs alleviate the problem of profit sharing. Optional tariffs can provide a manufacturer more profit from a large retailer when profit from a small retailer is given. However, the analysis shows that the maximum share of manufacturer from a large retailer is restricted by the condition for self-selection. In case of optional two-part tariffs based on marginal cost, if the gap between demands is large, the maximum share of the manufacturer is sufficient to achieve proper profit sharing. If the gap between demands is not sufficiently large, the manufacturer cannot earn sufficient share from increased profit. An optional modified two-part tariff where marginal price is more than marginal cost of manufacturer is considered because of this scenario. The marginal price above the marginal cost may additionally control the distribution of the increased profit. However, the analysis shows that a manufacturer's maximum profit from a large retailer with given profit from a small retailer is the same as or lower than the maximum profit when optional two-part tariffs based on marginal cost are applied. Therefore, it can be concluded that the optional modified tariffs do not have additional contribution to profit sharing relative to the tariffs based on marginal cost. Although this paper does not cover all kinds of optional tariffs that are different from tariffs based on marginal cost, it shows the advantage of optional tariffs based on marginal cost and has important theoretical implications. The result of this paper also gives guide for channel coordination. Optional two-part tariff based on marginal cost can increase efficiency in channel coordination.