• Journal of The Korean Association of Information Education
• /
• v.7 no.3
• /
• pp.263-274
• /
• 2003

Web based instruction (WBI) has been widely used thesedays because the web has various advantages for instruction. However, most of current WBI systems do not support various requirements from students. It is because of the lack of research for structural instruction method. This paper presents a new method of WBI and designs an instruction model to support various requirements from students by implementing dynamic WBI system using JSP to solve current WBI problems. The developed WBI system uses multimedia based instructions. The implemented system focused on the practical instruction by providing the functions of listening, homework, and test on web site. For the similar effects as in the classroom, it supports functions of electronic white board and multimedia data which is consisted of high-quality sound and video data with high degree of compression. Furthermore, the system supports that instructors can design a test using three kinds of basic forms, a multiple-choice test, brief-answer test, essay test, and evaluate the tests easily. It also supports easy management for homework, lecture registration, and many school affairs.

• Journal of Internet Computing and Services
• /
• v.17 no.5
• /
• pp.89-95
• /
• 2016

In a software testing domain, test case prioritization techniques improve the performance of regression testing, and arrange test cases in such a way that maximum available faults be detected in a shorter time. User-sessions and cookies are unique features of web applications that are useful in regression testing because they have precious information about the application state before and after making changes to software code. This approach is in fact a user-session based technique. The user session will collect from the database on the server side, and test cases are released by the small change configuration of a user session data. The main challenges are the effectiveness of Average Percentage Fault Detection rate (APFD) and time constraint in the existing techniques, so in this paper developed an intelligent framework which has three new techniques use to manage and put test cases in group by applying useful criteria for test case prioritization in web application regression testing. In dynamic weighting approach the hybrid criteria which set the initial weight to each criterion determines optimal weight of combination criteria by evolutionary algorithms. The weight of each criterion is based on the effectiveness of finding faults in the application. In this research the priority is given to test cases that are performed based on most common http requests in pages, the length of http request chains, and the dependency of http requests. To verify the new technique some fault has been seeded in subject application, then applying the prioritization criteria on test cases for comparing the effectiveness of APFD rate with existing techniques.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.9
• /
• pp.435-444
• /
• 2007

Caching web pages is an important part of web infrastructures. The effects of caching service are even more pronounced for wireless infrastructures due to their limited bandwidth. Medium to large-scale infrastructures deploy a cluster of servers to solve the scalability problem and hot spot problem inherent in caching. In this paper we present scheduling scheme based on cache utilization in a wireless internet proxy server cluster environment. The proposed method uses cache utilization for distributing evenly client requests to a cluster of cache servers and solving hot spot problem. We have implemented our approach and performed various experiments using publicly available traces. Experimental results on a cluster of 16 cache servers demonstrate that the proposed hashing method gives 45% to 114% Performance improvement over other widely used methods while addressing the hot spot problem.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.3
• /
• pp.443-454
• /
• 2020

The JavaScript engine is a module that receives JavaScript code as input and processes it, among many functions that are loaded into web browsers and display web pages. Many fuzzing test studies have been conducted as vulnerabilities in JavaScript engines could threaten the system security of end-users running JavaScript through browsers. Some of them have increased fuzzing efficiency by guiding test coverage in JavaScript engines, but no coverage guided fuzzing of optimized, dynamically generated machine code was attempted. Optimized JavaScript codes are difficult to perform sufficient iterative testing through fuzzing due to the function of runtime guards to free the code in the event of exceptional control flow. To solve these problems, this paper proposes a method of performing fuzzing tests on optimized machine code by avoiding deoptimization. In addition, we propose a method to measure the coverage of runtime-guards by the dynamic binary instrumentation and to guide increment of runtime-guard coverage. In our experiment, our method has outperformed the existing method at two measures: runtime coverage and iteration by time.

• The KIPS Transactions:PartA
• /
• v.9A no.4
• /
• pp.603-614
• /
• 2002

Delivery efficiency of e-learning media can be influenced by authoring processes. Generally, a moving picture recorded by video camera can be delivered to student by multimedia streaming service, using media server technology. A e-learning media authored by lecture authoring tool is played in a student application by download-based delivery system. Recently, some animation know-how are applied to author e-learning media by hand-operation. In this paper, we suggest a client-based streaming service for the e-leaning media consists of media files and integration data The lecture of e-learning media nay be divided into some time-based small blocks. Each blocks can be located distributed site. The student system gather those blocks by download-scheduling. This is a valid method for QoS guarantee streaming services. In addition to our study, lecturers can author composite e-learning media includes media files and dynamic web pages simply, The distributed e-learning media files of our study is managed by multi-author and updated rapidly.

• Journal of KIISE:Software and Applications
• /
• v.28 no.2
• /
• pp.179-191
• /
• 2001

Comparison shopping is a merchant brokering process that finds the best price for the desired product from several Web-based online stores. To get a scalable comparison shopper, we need an agent that automatically constructs a simple information extraction procedure, called a wrapper, for each semi-structured store. Automatic construction of wrappers for HTML-based Web stores is difficult because HTML only defines how information is to be displayed, not what it means, and different stores employ different ways of manipulating customer queries and different presentation formats for displaying product descriptions. Wrapper induction has been suggested as a promising strategy for overcoming this heterogeneity. However, previous scalable comparison-shoppers such as ShopBot rely on a strong bias in the product descriptions, and as a result, many stores that do not confirm to this bias were unable to be recognized. This paper proposes a more scalable comparison-shopping agent named MORPHEUS. MORPHEUS presents a simple but robust inductive learning algorithm that antomatically constructs wrappers. The main idea of the proposed algorithm is to recognize the position and the structure of a product description unit by finding the most frequent pattern from the sequence of logical line information in output HTML pages. MORPHEUS successfully constructs correct wtappers for most stores by weakening a bias assumed in previous systems. It also tolerates some noises that might be present in production descriptions such as missing attributes. MORPHEUS generates the wrappers rapidly by excluding the pre-processing phase of removing redundant fragments in a page such as a header, a tailer, and advertisements. Eventually, MORPHEUS provides a framework from which a customized comparison-shopping agent can be organized for a user by facilitating the dynamic addition of new stores.

• The KIPS Transactions:PartC
• /
• v.17C no.1
• /
• pp.27-36
• /
• 2010

In Web registration pages and online polling applications, CAPTCHA(Completely Automated Public Turing Test To Tell Computers and Human Apart) is used for distinguishing human users from automated programs. Text-based CAPTCHAs have been widely used in many popular Web sites in which distorted text is used. However, because the advanced optical character recognition techniques can recognize the distorted texts, the reliability becomes low. Image-based CAPTCHAs have been proposed to improve the reliability of the text-based CAPTCHAs. However, these systems also are known as having some drawbacks. First, some image-based CAPTCHA systems with small number of image files in their image dictionary is not so reliable since attacker can recognize images by repeated executions of machine learning programs. Second, users may feel uncomfortable since they have to try CAPTCHA tests repeatedly when they fail to input a correct keyword. Third, some image-base CAPTCHAs require high communication cost since they should send several image files for one CAPTCHA. To solve these problems of image-based CAPTCHA, this paper proposes a new CAPTCHA based on both image and text. In this system, an image and keywords are integrated into one CAPTCHA image to give user a hint for the answer keyword. The proposed CAPTCHA can help users to input easily the answer keyword with the hint in the fused image. Also, the proposed system can reduce the communication costs since it uses only a fused image file for one CAPTCHA. To improve the reliability of the image-text fusion CAPTCHA, we also propose a dynamic building method of large image dictionary from gathering huge amount of images from theinternet with filtering phase for preserving the correctness of CAPTCHA images. In this paper, we proved that the proposed image-text fusion CAPTCHA provides users more convenience and high reliability than the image-based CAPTCHA through experiments.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.57-71
• /
• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.