• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.175-184
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• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• Journal of Information Technology Applications and Management
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• v.21 no.1
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• pp.17-34
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• 2014

As the numbers of Internet users have grown dramatically in recent years due to increased use of mobile devices, businesses using internet are also expanding rapidly. Internet marketing has the advantage of expanding business without any constraint of time and space using the global network which connects tens of thousands of world's computers and mobile devices. In a way of utilizing internet marketing, the present study examines the applicability of Customer Relationship Management (CRM) to the domestic professional baseball industry in Korea. The study focuses on the issue of whether the intangible value of customer satisfaction can create higher profits. We combine both inductive and conductive methods for this study. First, we carry out a random survey of baseball spectators and find that customers are willing to pay more when their satisfaction level is improved. Next, we recognize satisfaction factors that are considered as important by customers through literature survey. Then we use Decision Tree to find which satisfaction factors are most important to each clustered customer group. Finally we estimate how much they would pay more when the most important satisfaction factor improves by each customer group. Therefore, this study demonstrates that CRM implementation to one-to-one internet marketing can improve the profitability of baseball industry. The major contribution of the present study is to show that the introduction of CRM can be used as a profit-generating strategy in various industries for future internet marketing.

• Journal of the Microelectronics and Packaging Society
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• v.7 no.1
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• pp.13-18
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• 2000

Low temperature co-fired ceramics on metal (LTCC-M) is efficient for embedding passive components with good tolerance in a module due to the dimensional stability in x and y directions by the constraint of metal core during the firing. In addition, the radiation noise can be reduced by metal core. In this paper, embedded passive components were introduced and a power amplifier module (PAM) fabricated by using the passive components was explained. The embedded passive components in test patters showed the tolerance of 10~20% and the good repeatability in tolerance of embedded passives was maintained in module fabrication. The shortened traces in multi chip modules (MCMs) make the signal delay time decreased and the embedded passives simplify the packaging processes owing to the less solder points, which enhance the electrical performance and increase the reliability of the modules. The LTCC-M technology is one of the promising candidates for RF application and is expected to expand its applications to power and high performance devices.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.549-561
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• 2007

Vision-based scene understanding is to infer and interpret the context of a scene based on the evidences by analyzing the images. A probabilistic approach using Bayesian networks is actively researched, which is favorable for modeling and inferencing cause-and-effects. However, it is difficult to gather meaningful evidences sufficiently and design the model by human because the real situations are dynamic and uncertain. In this paper, we propose a learning method of Bayesian network that reduces the computational complexity and enhances the accuracy by searching an efficient BN structure in spite of insufficient evidences and training data. This method represents the domain knowledge as ontology and builds an efficient hierarchical BN structure under constraint rules that come from the ontology. To evaluate the proposed method, we have collected 90 images in nine types of circumstances. The result of experiments indicates that the proposed method shows good performance in the uncertain environment in spite of few evidences and it takes less time to learn.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.323-338
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• 2003

The main memory database systems (MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. Recently, it has been increased needs that have the fast data processing as well as the efficient modeling of application requiring for a complicated structure, and conformity to applications that need the strict dta consistency. In MMDBMS, because all the data is located in the main memory, it can support the usable expression methods of data satisfying their needs without performance overhead. The method has the operation to manipulate the data and the constraint such as referential integrity in more detail. The data model consists of this methods is an essential component to decide the expression power of DBMS. In this paper, we discuss about various requests to provide the communication services and propose the data model that support it. The mainly discussed issues are 1) definition of the relationship between tables using the pointer, 2) navigation of the data using the relationship, 3) support of the referential integrity for pointer, 4) support of the uniform processing time for the join, 5) support of the object-oriented concepts, and 6) sharing of an index on multi-tables. We discuss the pointer-based data model that designed to include these issues to efficiently support complication environments.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.10-20
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• 2007

For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.882-891
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• 2010

Many automated dynamic test data generation technique have been proposed. The techniques evaluate fitness of test data through executing instrumented Software Under Test (SUT) and then generate new test data based on evaluated fitness values and optimization algorithms. Previous researches and experiments have been showed that these techniques generate effective test data. However, optimization algorithms in these techniques incur much time to generate test data, which results in huge test case generation cost. In this paper, we propose a technique for reducing the time of evaluating a fitness of test data among steps of dynamic test data generation methods. We introduce the concept of Fitness Evaluation Program (FEP), derived from a path constraint of SUT. We suggest a test data generation method based on FEP and implement a test generation tool, named ConGA. We also apply ConGA to generate test cases for C programs, and evaluate efficiency of the FEP-based test case generation technique. The experiments show that the proposed technique reduces 20% of test data generation time on average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.169-176
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• 2018

In this paper, we consider duty-cycled wireless sensor networks (WSNs) in which sensor nodes are periodically dormant in order to reduce energy consumption. In such networks, as the duty cycle interval increases, the energy consumption decreases. However, a higher duty cycle interval leads to the increase in the end-to-end (E2E) delay. Many applications of WSNs are delay-sensitive and require packets to be delivered from the sensr nodes to the sink with delay requirements. Most of existing studies focus on only reducing the E2E delay, rather than considering the delay bound requirement, which makes hard to achieve the balanced performance between E2E delay and energy consumption. A few study that considered delay bound requirement require time synchronization between neighboring nodes or a specific distribution of deployed nodes. In order to address limitations of existing works, we propose a duty-cycle scheduling algorithm that aims to achieve low energy consumption, while satisfying the delay requirements. To that end, we first estimate the probability distribution for the E2E delay. Then, by using the obtained distribution we determine the maximal duty cycle interval that still satisfies the delay constraint. Simulation results show that the proposed design can satisfy the given delay bound requirements while achieving low energy consumption.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.668-680
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• 2006

Web services on the Internet are not always reliable in terms of service availability and performance. Dynamic service coordination capability of a system or an application invoking Web services is essential to cope with such unreliable situations. In dynamic service coordination, if a Web service does not respond within a specific time constraint, it is replaced with another Web service at run time for reliable invocation of Web services. In this paper, we develop an exception based dynamic service coordination framework for Web services. In the framework, all necessary information for dynamic service coordination is explicitly specified and summarized as a set of attributes. Then classes and workflows, supporting dynamic service coordination and invoking Web services, are automatically created based on these attributes. Developers of Web services client programs can make the invocations of Web services reliable by calling the methods of the classes. Some performance loss has been observed in the indirect invocation of a Web service. However, when we consider the flexibility and reliability gained from the method, the performance loss would be acceptable in many cases.