• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1446-1465
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• 2022

Diversified SaaS applications allow users more choices to use, according to their own preferences. However, the diversification of SaaS applications also makes it impossible for users to choose the best one. Furthermore, users can't take advantage of the functionality between SaaS applications. In this paper, we propose a platform that provides an SaaS mashup service, by extracting interoperable service functions from SaaS-based applications that independent vendors deploy and supporting a customized service recommendation function through log data binding in the cloud environment. The proposed SaaS mashup service platform consists of a SaaS aggregation framework and a log data binding framework. Each framework was concreted by using Apache Kafka and rule matrix-based recommendation techniques. We present the theoretical basis of implementing the high-performance message-processing function using Kafka. The SaaS mashup service platform, which provides a new type of mashup service by linking SaaS functions based on the above technology described, allows users to combine the required service functions freely and access the results of a rich service-utilization experience, using the SaaS mashup function. The platform developed through SaaS mashup service technology research will enable various flexible SaaS services, expected to contribute to the development of the smart-contents industry and the open market.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.17-37
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• 1987

The purpose of this study is to establish more rational and practical planning theory for amusement park. It analyze and consider the fluctuation of people who come and use the Tong-Ch'on amusement park. The results drawn from this reserch work are as follows; 1. The main visitors of the Tong-Ch'on amusement park are students in their twenties and thirties, and people whose incomes are below 300,000 Won a month. The purpose of visit is for a rest rather than for amusement and user prefer summer, while the user is so rare in wintertime. Those phenomena observed are somewhat different from the real purpose of a amusement park which is on purpose to make profits by offering entertainments to the users. So planner should pay attention to the three points. They are varieties, seasonable diversification and fantastic character of facilties, in the amusement park. 2. The access time of the Tong-Ch'on amusement park was 41 minutes, the use frequency was 4 times a year and resident time was 164 minutes. The relationship of the three factors are as follows; log Y(F) =1.7832-0.0277(A.T) R$^2$=0.75 Y(R. F)=31.8885+3.3217(A.T) R$^2$=0.53 Y(R. T)=224.8959-87.8309 1og(F) R$^2$=0.38 F;Use frequency(time/year) A.T;Access Time(minute) R.T;Resident Time(minute) 3. In the choice of space, there were much differences according to tole user's age, job, degree of education, companion type and purpose of use. 4. There are considerable correlation between use fluctuation and some factors. The factors are season(summer, winter) as a time, temperature, cloud amount, duration of sunshine, weather(rainy-day) as a climate and a day of the week(weekday, holiday) as a social system. The important variables are temperature, cloud amount, duration of sunshine and a day of the week(weekday, holiday) to estimate the user of amusementpark. 5. 1 can reduce the following two types of regression models. 1) log$\sub$e/ Y1 = 6.9114 + 0.l135 TEM + 0.00002 SUN -0.4068W1 + 0.4316 W3 (R$^2$= 0.94) 2) log$\sub$e/ Y2 = 7.2069 + 0.l177 TEM - 0.0990 CLO + 0.4880 W3 (R$^2$=0.95) Y; Number of User TEM; Temperature CLO; Amount of cloud SUN; Duration of Sunshine W1; Weekday W3; Holiday Those model is in order to estimate the user for management of Tong-Ch'on amusement park and use on the computation of facility sloe for reconstruction. Besides the amusement park, city park and outdoor recreation area could estimate of user through this method. But, I am not sure about the regression models because I did not apply the regression models to the other amusement park, city Park or outdoor recreation area. Therefore, I think that this problem needs to be studied on in the future.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.357-371
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• 2007

For the time-to-failure data with competing risks, cumulative incidence functions (CIFs) are commonly estimated using nonparametric methods. If the cases of events due to the cause of primary interest are infrequent relative to other cause of failure, nonparametric methods may result in rather imprecise estimates for CIF. In such cases, Bryant et al. (2004) suggested to model the cause-specific hazard of primary interest parametrically, while accounting for the other modes of failure using nonparametric estimator. We represented the semiparametric cumulative incidence estimator and extended to the model of Weibull and log-normal distribution. We also conducted simulations to access the performance of the semiparametric cumulative incidence estimators and to investigate the impact of model misspecification in log-normal cause-specific hazard model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.737-743
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• 2017

The intelligent life-log system proposed in this paper is intended to identify and record a myriad of everyday life information as to the occurrence of various events based on when, where, with whom, what and how, that is, a wide variety of contextual information involving person, scene, ages, emotion, relation, state, location, moving route, etc. with a unique tag on each piece of such information and to allow users to get a quick and easy access to such information. Context awareness generates and classifies information on a tag unit basis using the auto-tagging technology and biometrics recognition technology and builds a situation information database. In this paper, we developed an active modeling method and an application that recognizes expressionless and smile expressions using lip lines to automatically record emotion information.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.507-514
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• 2006

Various application systems are developed using RFID as a part of ubiquitous computing, and it is expected that RFID chip will become wide-spread for the distribution industry especially. Efficient and efact intelligent-type of warehouse management system is essential for small-to-medium-sized enterprises in the situation having a trouble in the viewpoint of expense and manpower. In this paper, we implement small-scale warehouse management system using log-based context awareness technology. This system is implemented to be controlled on web, configuring clients to control RFID readers and building up DBMS system in a server. Especially, it grasps user's intention of storing or delivering based on toE data for the history of user's access to the system and it reports user's irregular pattern of warehouse use and serves predictive information of the control of goods in stock. As a result, the proposed system can contribute to enhance efficiency and correctness of small-scale warehouse management.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.6
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• pp.463-475
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• 2009

Flash memory is suitable for real time systems because of its consistent performance for random access, low power consumption and shock resistance. However, flash memory needs blocking time to perform a garbage collection to reclaim invalidated pages. Moreover, the worst-case garbage collection time is significantly longer than the best-case garbage collection time. In this paper, we propose a FTL (Flash Translation Layer) mapping scheme called KAST (K-Associative Sector Translation). In the KAST scheme, user can control the maximum association of the log block to limit the worst-case garbage collection time. Performance evaluation using simulation shows that not only KAST completes the garbage collection within the specified time but also provides about 10~15% better average performance than existing FTL schemes.

• International Journal of Knowledge Content Development & Technology
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• v.4 no.1
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• pp.23-37
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• 2014

The Trust and Authority in Scholarly Communications in the Light of the Digital Transition research project1) was a study which investigated the behaviours and attitudes of academic researchers as producers and consumers of scholarly information resources in respect to how they determine authority and trustworthiness. The research questions for the study arose out of CIBER's studies of the virtual scholar. This paper focuses on elements of this study, mainly an analysis of a scholarly publisher's usage logs, which was undertaken at the start of the project in order to build an evidence base, which would help calibrate the main methodological tools used by the project: interviews and questionnaire. The specific purpose of the log study was to identify and assess the digital usage behaviours that potentially raise trustworthiness and authority questions. Results from the self-report part of the study were additionally used to explain the logs. The main findings were that: 1) logs provide a good indicator of use and information seeking behaviour, albeit in respect to just a part of the information seeking journey; 2) the 'lite' form of information seeking behaviour observed in the logs is a sign of users trying to make their mind up in the face of a tsunami of information as to what is relevant and to be trusted; 3) Google and Google Scholar are the discovery platforms of choice for academic researchers, which partly points to the fact that they are influenced in what they use and read by ease of access; 4) usage is not a suitable proxy for quality. The paper also provides contextual data from CIBER's previous studies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.593-600
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• 2018

Owing to the advancement of Internet and smart devices, access to various media such as social media became easy; thus, a large amount of big data is being produced. Particularly, the companies that provide various Internet services are analyzing the big data by using the MapReduce-based big data analysis techniques to investigate the customer preferences and patterns and strengthen the security. However, with MapReduce, when the big data is analyzed by defining the number of reducer objects generated in the reduce stage as one, the processing rate of big data analysis decreases. Therefore, in this paper, a MapReduce-based split big data analysis method is proposed to improve the log analysis processing rate. The proposed method separates the reducer partitioning stage and the analysis result combining stage and improves the big data processing rate by decreasing the bottleneck phenomenon by generating the number of reducer objects dynamically.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.101-114
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• 2011

As it seems like critical information leakages have been increasing due to industrial espionage and malicious internal users, the importance of introducing audit and log security technology is growing every now and then. In this paper, we suggest the session logging system for the company's internal control to meet the SOX legislation level, by monitoring and analyzing users behaviors connecting to the business-critical Operating System. The system proposed in this paper aims to monitor the user's illegal activities in the Operating System, and to present the clear evidence of purpose of those activities by detailed logs. For this purpose, we modified Operating System by adding multiple services suggested in this paper. These services utilize interfaces provided by the existing Operating System and add functions to control access and get logs. The system saves and manages session logs of users or administrators connected to the server with centralized log storage. And the system supports session log searching and lookup features required by SOX legislation for the company's internal controls with the level of computer forensics and logging technology.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.847-854
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• 2001

The Web continues to grow fast rate in both a large aclae volume of traffic and the size and complexity of Web sites. Along with growth, the complexity of tasks such as Web site design Web server design and of navigating simply through a Web site have increased. An important input to these design tasks is the analysis of how a web site is being used. The is paper proposes a Page logging System(PLS) identifying reliably user sessions required in Web mining system PLS consists of Page Logger acquiring all the page accesses of the user Log processor producing user session from these data, and statements to incorporate a call to page logger applet. Proposed PLS abbreviates several preprocessing tasks which spends a log of time and efforts that must be performed in Web mining systems. In particular, it simplifies the complexity of transaction identification phase through acquiring directly the amount of time a user stays on a page. Also PLS solves local cache hits and proxy IPs that create problems with identifying user sessions from Web sever log.