• Journal of KIISE:Databases
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• v.31 no.4
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• pp.373-383
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• 2004

There have been an emerging interests in the importance of database tuning techniques under modem database environments in which very large-scale data should be managed. In Particular. database performance parameters should be tuned to reflect system loads appropriately. This paper presents two parameter tuning strategies, namely throughput-based and response-time-based, which tune each performance parameter accordingly. The proposed techniques are applied to two commercial database systems in the TPC-W benchmark to see the effectiveness of those methods. The results show that they can help improve system performance considerably.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.11a
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• pp.67-67
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• 2007

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.183-190
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• 2006

Database workloads may show different resource usages for database applications. Database administrators can enhance the DBMS performances through resource management that reflects workload characteristics. We provide a method that can identify tunable resources from analyzing the relationship between performance indicators and resources. First, we select which performance indicators increase or decrease by expanding resources using a correlation coefficient and a significance level test. Next, we identify resources that can affect the DBMS Performances by using increasing or decreasing performance indicators. We evaluated our method in the TPC-C and TPC-W environments.

• Korean Journal of Food Science and Technology
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• v.36 no.1
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• pp.174-182
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• 2004

Hygienic standards for pizza specialty restaurant located in Seoul during summer, 2000 were established based on HACCP concept by measuring temperature, time, pH, $A_{w}$ and microbiological assessments of pizza, and evaluation of hygienic conditions of kitchens and workers. Kitchen and worker conditions were average 1.2 and 1.0 (3 point Sly's scale), respectively, Microbial contaminations occurred at $5-60^{\circ}C$, pH above 5.0, and $A_{w}$ (0.93-0.98). Microbial assessments for pizza processing revealed $1.5{\times}10^{2}-3.9{\times}10^{8}\;CFU/g$ of TPC and $0.5{\times}10^{1}-1.6{\times}10^{7}\;CFU/g$ of coliforms, exceeding standards ($TPC\;10^{6}\;CFU/g\;and\;coliform\;10^{3}\;CFU/g$) established by Solberg et al., although significantly decreased after baking. S. aureus was not discovered, but Salmonella was found in onions. Tools and containers such as pizza cutting knife, topping container, serving bowl, pizza plate, working board, and dough kneading board contained $6.2{\times}10^{2}-1.1{\times}10^{9}\;CFU/g$ of TPC, $2.0{\times}10^{1}-6.2{\times}10^{3}\;CFU/g$ of coliforms. Workers' hands contained $3.1{\times}10^{4}\;CFU/g$ of TPC and S. aureus as compared to safety standards of Harrigan and McCance (500 and 10 CFU/g of TPC and coliforms per $100cm^{2}$). CCPs (critical control points) were determined as receiving, topping, and baking according to CCP decision tree analysis. Results suggest purchase of quality materials, careful monitoring of time and temperature, hygienic use of tools and utensils, and sanitary practicer by workers are recommended as control points for safe pizza production.

• Food Science and Preservation
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• v.24 no.7
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• pp.949-956
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• 2017

This study attempted to find optimum extract range of active ingredient for barley sprouts (Hordeum vulgare L.). Extracts from Hordeum vulgare L. were made by microwave extraction method and total polyphenol content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity (DPPH) were measured with extract of Hordeum vulgare L.. Response surface methodology (RSM) was applied to a extraction process, and central composite design (CCD) was also used for this process to examine the optimum condition. Independent variables ($X_n$) are concentration of ethanol ($X_1$: 0, 25, 50, 75, 100%), microwave power ($X_2$: 60, 120, 180, 240, 300 W), extraction time ($X_3$: 4, 8, 12, 16, 20 min). Dependent variables ($Y_n$) are TPC ($Y_1$), TFC ($Y_2$), DPPH radical scavenging ($Y_3$). It is formed by sixteen conditions to extract. The $R^2$ value of dependent variables is ranged from 0.90 to 0.97 (p<0.05). Experiments values within the optimal range (40% of ethanol concentration, 120 W of microwave power, 18 min of extraction time) were 3.74 mg GAE/g (TPC), 3.00 mg RE/g (TFC), 35.43% (DPPH), respectively. Under the optimized conditions, predicted value showed no significant difference comparing with the experimental values.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.84-90
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• 2010

DBMS is used for a range of applications from data warehousing through on-line transaction processing. As a result of this demand, DBMS has continued to grow in terms of its size. This growth invokes the most important issue of manually tuning the performance of DBMS. The DBMS tuning should be adaptive to the type of the workload put upon it. But, identifying workloads in mixed database applications might be quite difficult. Therefore, a method is necessary for identifying workloads in the mixed database environment. In this paper, we propose a SVM workload classifier to automatically identify a DBMS workload. Database workloads are collected in TPC-C and TPC-W benchmark while changing the resource parameters. Parameters for SVM workload classifier, C and kernel parameter, were chosen experimentally. The experiments revealed that the accuracy of the proposed SVM workload classifier is about 9% higher than that of Decision tree, Naive Bayes, Multilayer perceptron and K-NN classifier.

• Korean Chemical Engineering Research
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• v.56 no.1
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• pp.66-72
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• 2018

Corn stover is known as a good candidate for a functional food ingredient when the main lignocellulosic material, lignin, is used as bioactive materials as form of polyphenolic compounds. The purpose of this study was to determine the microwave extraction conditions under which total phenolic compounds (TPC) and flavonoid contents of corn stover were maximized. Microwave-assisted extracts using sulfuric acid ranging from 0 to 1.0 mol with extraction time between 40 and 240 sec were conducted by using response surface methodology (RSM). Microwave power showed significant effects (p<0.05) and the concentrations of TPC and flavonoids increased with increased level of microwave power and extraction time. The optimum conditions for corn stover extraction were determined as 698.6 W, 240 sec, and 0 mol sulfuric acid, and the predicted value of TPC and flavonoid is 82.4 mg GAE/g DM and 18.1 mg/g DM, respectively. Microwave extraction was evaluated as an economic process with low energy consumption, short extraction and high extraction yield of bioactive including TPC and flavonoids compared to conventional extractions.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.747-754
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• 2004

Database administrators should be aware of performance characteristics of database systems in order to manage database system effectively. The usages of system resources in database systems could be quite different under database workloads. The objective of this paper is to identify and analyze performance characteristics of database systems in different workloads, which could help database tuners tune database systems Under the TPC-C and TPC-W workloads, which represent typical workloads of online transaction processing and electronic commerce respectively, we investigated usage types of resource that are determined by fourteen performance indicator, and are behaved in response to changes of four tuning parameters (data buffer, private memory, I/O process, shared memory). Eight out of the fourteen performance indicators cleary show the performance differences under the workloads. Changes of data buffer parameter give a influences to database system. The tuning parameter that affects the system performance significantly is the database buffer size in the both workloads.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1041-1048
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• 2004

Database logs contain various information on database operations, but they are used to recover database systems from failures generally. This paper proposes a log analysis tool that provides useful information for database tuning. This tool provides users with information on work-load organization, database schemas, and resources usages of queries. This paper describes the tool in views of its architecture, functions, implementation, and verification. The tool is verified by running the TPC-W benchmark, and representative analysis results are also presented.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.271-282
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• 2008

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method, comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.