• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.46 no.3
• /
• pp.239-247
• /
• 2010

Species of fish such as striped beakperch, bluefin searobin and konoshiro gizzard shad are commercially very important due to their high demand in the Korean market. When estimating acoustically the abundance of stocks for these species, it is of crucial importance to know the target strength (TS) to the length dependence. In relation to these needs, the TS experiments were conducted on three different species in an acrylic salt water tank using two split-beam echo sounders of 70 and 120 kHz. The TS for these three species under the controlled condition was simultaneously measured with the swimming movement by a DVR system and analyzed as a function of fish length (L) and frequency (or wavelength $\lambda$). The equation of the form TS=a log (L)+b log ($\lambda$)+c was derived for their TS-length dependence. The best fit regression of TS on fork length for striped beakperch was estimated as TS=35.67 log (L, m) -15.67 log ($\lambda$, m) -46.69 ($r^2$=0.78). Furthermore, the best fit regression of TS on fork length for konoshiro gizzard shad was shown to be TS=25.85 log (L, m) -5.85 log ($\lambda$, m) -32.22 ($r^2$=0.51). The averaged TS for 12 bluefin searobins with a mean length of 24.36cm at 70 kHz was analyzed to be -41.55dB. In addition, the averaged tilt angle obtained simultaneously by a DVR system with TS measurements for 27 konoshiro gizzard shads swimming within an acrylic salt water tank was estimated at $-2.7^{\circ}$.

• Journal of Digital Convergence
• /
• v.16 no.11
• /
• pp.335-340
• /
• 2018

Commercialized speech recognition systems that have an accuracy recognition rates are used a learning model from a type of speaker dependent isolated data. However, it has a problem that shows a decrease in the speech recognition performance according to the quantity of data in noise environments. In this paper, we proposed the vector quantization based speech recognition performance improvement using maximum log likelihood in Gaussian distribution. The proposed method is the best learning model configuration method for increasing the accuracy of speech recognition for similar speech using the vector quantization and Maximum Log Likelihood with speech characteristic extraction method. It is used a method of extracting a speech feature based on the hidden markov model. It can improve the accuracy of inaccurate speech model for speech models been produced at the existing system with the use of the proposed system may constitute a robust model for speech recognition. The proposed method shows the improved recognition accuracy in a speech recognition system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.546-548
• /
• 2019

In recent days, vehicle safety technologies for supporting safe vehicle driving attract public attention. This paper proposes multi-log platform based vehicle safety system (MLPVSS) that analyzes multi-log data (i.e., log-data on human, object, and place) and supports vehicle safety. The MLPVSS gathers sensor data and image data on the human, object, and place, and then generates multi-log data that are context-aware data on the human, object, and place. The MLPVSS can detect, predict, and response vehicle dangers. The MLPVSS can contribute to reduce car accidents.

• Journal of the Korean Chemical Society
• /
• v.34 no.6
• /
• pp.582-592
• /
• 1990

Retention behavior of lanthanide-$\alpha$HiBA complexes was studied on the cation exchanger (LC-18 coated with $C_{20}H_{41}SO_4^-$). An equation predicting retention of lanthanides in isocratic or gradient elution with sodium ion and $\alpha$-HiBA concentration was derived from ion exchange equilibria of metal-ligand complex system, respectively. The relations between log k' and log [Na$^+$] /log [$\alpha$-HiBA) showed non-linearity in isocratic elution. In gradient elution a good linearity between log k' vs log R was obtained. The values of slopes (log k / log R) gave good agreements between calculation and experiment. Individual capacity factors ($k'_{Ln}^{3+}, k'_{LnL}^{2+}, k'{LnL2+}) and stability constant (${\beta}_1$, ${\beta}_2$, ${\beta}_3$) of lanthanide-$\alpha$HiBA complexes were calculated by the non-linear least square fittings using the retention equation. The correlation coefficients of lanthanides were shown better than 0.9996 between experiment and calculation.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.6
• /
• pp.1399-1410
• /
• 2015

Gartner is requiring companies to considerably change their survival paradigms insisting that companies need to understand and provide again the upcoming era of data competition. With the revealing of successful business cases through statistic algorithm-based predictive analytics, also, the conversion into preemptive countermeasure through predictive analysis from follow-up action through data analysis in the past is becoming a necessity of leading enterprises. This trend is influencing security analysis and log analysis and in reality, the cases regarding the application of the big data analysis framework to large-scale log analysis and intelligent and long-term security analysis are being reported file by file. But all the functions and techniques required for a big data log analysis system cannot be accommodated in a Hadoop-based big data platform, so independent platform-based big data log analysis products are still being provided to the market. This paper aims to suggest a framework, which is equipped with a real-time and non-real-time predictive analysis engine for these independent big data log analysis systems and can cope with cyber attack preemptively.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.9 no.3
• /
• pp.13-26
• /
• 1999

Widespread use of Internet despite numerous positive aspects resulted in increased number of system intrusions and the need for enhanced security mechanisms is urgent. Systematic collection and analysis of log data are essential in intrusion investigation. Unfortunately existing logs are stored in diverse and incompatible format thus making an automated intrusion investigation practically impossible. We examined the types of log data essential in intrusion investigation and implemented a tool to enable systematic collection and efficient analysis of voluminous log data. Our tool based on RBDMS and SQL provides graphical and user-friendly interface. We describe our experience of using the tool in actual intrusion investigation and explain how our tool can be further enhanced.

• Korean Management Science Review
• /
• v.20 no.2
• /
• pp.1-16
• /
• 2003

Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

• Journal of the Korean Chemical Society
• /
• v.33 no.6
• /
• pp.596-600
• /
• 1989

The simple and mixed ligand complexes of cadmium-oxalate-citrate systems have been studied with differential pulse polarography at 25${\circ}$C, in the solution with constant ionic strength, ${\mu}$= 1.0 ($NaNO_3$) and pH 8.0. Using the graphical methods by DeFord-Hume and Schaap-McMasters, the overall stability constants for the mixed ligand complexes, $\beta_{ij}$, were found to be: $log\beta_{11}$ = 4.91, $log\beta_{12}$ = 4.99, and log $log\beta_{21}$ = 5.18, respectively. Various equilibria involved in the mixed system have also been discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.1
• /
• pp.21-26
• /
• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.29-32
• /
• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the users' access pattern to web site and their following purchasable items and improves their web pare on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning it employs Rough Set, which is a method that searches the association rule and offers most suitable cases by reduces cases. It reasons the web pages by considering the users' access pattern and time by using the web log and reasons the users' purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of users' web pages and displays the inferred goods on users' web pages.