• Journal of KIISE:Databases
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• v.30 no.4
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• pp.408-419
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• 2003

Data warehouses are usually dedicated to the processing of quires issued by decision support system(DSS). The response time of DSS queries is typically several orders of magnitude higher than the one of OLTP queries. Since DSS queries are often submitted interactively, techniques for reducing their response time are important. The caching of query results is one such technique particularly well suited to the DSS environment. In this paper, we present a cache manager for such an environment. Specifically, we define a canonical form of query. The cache manager looks up a query based on the exact query match or using a suggested query split process if the query is found is non-canonical form or in canonical form, respectively. It dynamically maintains the cache content by employing a profit function which reflects in an integrated manner the query execution cost, the size of query result, the reference rate, the maintenance cost of each result due to updates of their base tables, and the frequency of such updates. We performed the experimental evaluation and it positively shows the performance benefit of our cache manager.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4682-4705
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• 2020

The Unmanned Aerial Vehicles (UAV) networks consisting of low-cost UAVs are very vulnerable to smart jammers that can choose their jamming policies based on the ongoing communication policies accordingly. In this article, we propose a novel cloud and edge-aided mobile communication scheme for low-cost UAV network against smart jamming. The challenge of this problem is to design a communication scheme that not only meets the requirements of defending against smart jamming attack, but also can be deployed on low-cost UAV platforms. In addition, related studies neglect the problem of decision-making algorithm failure caused by intermittent ground-to-air communication. In this scheme, we use the policy network deployed on the cloud and edge servers to generate an emergency policy tables, and regularly update the generated policy table to the UAVs to solve the decision-making problem when communications are interrupted. In the operation of this communication scheme, UAVs need to offload massive computing tasks to the cloud or the edge servers. In order to prevent these computing tasks from being offloaded to a single computing resource, we deployed a lightweight game algorithm to ensure that the three types of computing resources, namely local, edge and cloud, can maximize their effectiveness. The simulation results show that our communication scheme has only a small decrease in the SINR of UAVs network in the case of momentary communication interruption, and the SINR performance of our algorithm is higher than that of the original Q-learning algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1693-1713
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• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.160-163
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• 2000

Due to the complexities of the real-world system, a water resource management program has to deal with various types of data. It appears that management personnel who has to use the program usually suffers from the technical burdens of handling large amount of data and understanding the optimization theory when they try to interpret the results. By combining the capabilities of database technology and modeling technique with optimization procedure we can develop a reliable decision supporting tool for multi-reservoir operation planning, which yields operating schedule for each dam in a river basin. We introduce two special data handling methodology for the real world application. First, by treating dams, hydro-electric power generating facilities and demand sites as separate database tables, the proposed data handling scheme can be applied to general water resource system in Korea. Second, by assigning variable names using predetermined key words, we can save searching time for identifying the moaning of the variables, so that we can quickly save the results of the optimization run to the database.

• Steel and Composite Structures
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• v.7 no.1
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• pp.53-70
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• 2007

This paper presents a analysis of the problem of optimal design of the beams with two I-type cross section shapes. These types of beams are simply supported and subject to pure bending. The strength and stability conditions were formulated and analytically solved in the form of mathematical equations. Both global and selected types of local stability forms were taken into account. The optimization problem was defined as bicriteria. The cross section area of the beam is the first objective function, while the deflection of the beam is the second. The geometric parameters of cross section were selected as the design variables. The set of constraints includes global and local stability conditions, the strength condition, and technological and constructional requirements in the form of geometric relations. The optimization problem was formulated and solved with the help of the Pareto concept of optimality. During the numerical calculations a set of optimal compromise solutions was generated. The numerical procedures include discrete and continuous sets of the design variables. Results of numerical analysis are presented in the form of tables, cross section outlines and diagrams. Results are discussed at the end of the work. These results may be useful for designers in optimal designing of thin-walled beams, increasing information required in the decision-making procedure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.194-199
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• 2003

Data are an expression of the language or numerical values that show some features. And the information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns or make a decision. Today, knowledge extraction and application of that are broadly accomplished for the easy comprehension and the performance improvement of systems in the several industrial fields. The knowledge extraction can be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge is drawn by rules with data mining techniques. Clustering (CL), input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for the knowledge expression based upon rules. In this paper, the various approaches of the knowledge extraction are surveyed and categorized by methodologies and applied industrial fields. Also, the trend and examples of each approaches are shown in the tables and graphes using the categories such as CL, ISP, NF, NN, EM, and so on.

• Journal of Korean Public Health Nursing
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• v.18 no.1
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• pp.154-166
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• 2004

The purpose of this study was to design and implementation of database for school health activity. This database system was designed stand-alone application for college school health center without a hospital affiliation and the database system was made of relational database management system, Microsoft access 2000 to be made GUI (Graphic user interface) type design and made up 7 tables: patients. symptoms. departments, income and outgo. medical cures. and medicine. The construction of this database system was patient management. code management. medicine management. and statistics management. The results of the database system were as follows; 1) This database system could be used for college school health center. 2) This database system could be made correct statistic data. 3) This database system could be managed income and outgo. 4) This database system could be changed for the better activity of community health service. 5) This database system could be simply attired administrative system. This database system will be used for students and employees to protect and promote health to measure for health level and quality of health service. In conclusion. this database system can be applied for unit health center to manage the college school health activity and advanced data management can be applied for health profession to do quality improvement. cost containment. management information system. and decision support system.

• Journal of IKEEE
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• v.24 no.4
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• pp.991-997
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• 2020

Reinforcement learning has been applied mainly in sequential decision-making problems. Especially in recent years, reinforcement learning combined with neural networks has brought successful results in previously unsolved fields. However, reinforcement learning using deep neural networks has the disadvantage that it is too complex for immediate use in the field. In this paper, we implemented path planning algorithm for mobile robots using Q-learning, one of the easy-to-learn reinforcement learning algorithms. We used real-time Q-learning to update the Q-table in real-time since the Q-learning method of generating Q-tables in advance has obvious limitations. By adjusting the exploration strategy, we were able to obtain the learning speed required for real-time Q-learning. Finally, we compared the performance of real-time Q-learning and DQN.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.633-638
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• 2009

This study was conducted to develop stem taper equations and stem volume tables for Eucalyptus pellita and Acacia mangium plantations in Kalimantan, Indonesia. To derive a most adequate taper equation for the plantations, three models - Max & Burkhart, Kozak, and Lee models - were applied and their fitness were statistically analyzed by using fitness index, bias, and standard error of bias. The result showed that there is no significant difference between the three models, but the fitness index was slightly higher in the Kozak model. Therefore, the Kozak model was chosen for generating stem taper equations and stem volume tables for the Eucalyptus pellita and Acacia mangium plantations. The resulted stem volume table was compared to the local volume table used in Kalimantan regions, but no significant difference was found in the stem volume estimation. It is expected that the results of this study would provide a good information about the tree growth in abroad plantations and support a reliable decision-making for their management.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.71-84
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• 1999

The purpose of this study is to construct a dynamic traffic analysis model using the existing traffic flow theory in order to develope a dynamic traffic assignment technique. In this study the dynamic traffic analysis model was constructed using Daganzo's CELL TRANSMISSION THEORY which was considered more suitable to dynamic traffic assignment than the other traffic flow theories. We developed newly the diverging split module, the cost update module and the link cost function and defined the maximum waiting time decision function that Daganzo haven't defined certainly at his Papers. The output that resulted from the simulation of the dynamic traffic analysis model with test network I and II was shown at some tables and figures, and the analysis of the bottleneck and the HOV lane theory showed realistic outputs. Especially, the result of traffic assignment using the model doesn't show equilibrium status every time slice but showed that the average travel cost of every path maintains similarly in every time slice. It is considered that this model can be used at the highway operation and the analysis of traffic characteristics at a diverging section and the analysis of the HOV lane effect.