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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Internet Computing and Services
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Korean Society for Internet Information
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Volume & Issues
Volume 10, Issue 6 - Dec 2009
Volume 10, Issue 5 - Oct 2009
Volume 10, Issue 4 - Aug 2009
Volume 10, Issue 3 - Jun 2009
Volume 10, Issue 2 - Apr 2009
Volume 10, Issue 1 - Feb 2009
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An Analysis and Design of Efficient Community Routing Policy for Global Research Network
Jang, Hyun-Hee ; Park, Jae-Bok ; Koh, Kwang-Shin ; Kim, Seung-Hae ; Cho, Gi-Hwan ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 1~12
A routing policy based on BGP community routing permits to select a specific route for particular network by making use of user-defined routing policies. Especially, community based routing policy is recently getting a great concern to enhance overall performance in the global research networks which are generally inter-connected large number of different characterized networks. In this paper, we analyze the community routing which has been applied in existing global research networks in the network performance point of view, and catch hold of problems caused by the routing performance in a new global research network. Then, we suggest an effective community routing policy model along with an interconnection architecture of research networks, in order to make correct some wrong routings and resolve an asymmetric routing problem, for a new global research network. Our work is expected to be utilized as an enabling base technology to improve the network performance of future global research networks as well as commercial networks.
Implementation of 6LoWPAN Testbed: Location Tracking Service Based on Google Map
Kim, Kye-Won ; Seo, Jae-Wan ; Hwang, Dae-Joon ; Choo, Hyun-Seung ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 13~26
Wireless Sensor Networks (WSNs) is one of the key technologies that make it possible to provide u-service in a ubiquitous society, however, it has disadvantages such as difficulty of managing sensor nodes and weaknesses of stability or mobility in large-scale WSNs. In order to solve these problems, 6LoWPAN that integrates with WSNs and IP networks has been studied widely. In this paper, we propose a Location Tracking Service Based on Google Map (LTSGM) system using 6LoWPAN. Since LTSGM system provides visual location information of sensor nodes through Google Map, it is possible to makes it easier than ever to manage sensor nodes in large-scale WSNs. Moreover, LTSGM can be used for various services such as applications for disaster or crime because it can trace the location of mobile nodes. Implementation of LTSGM system will be a test platform for 6LoWPAN.
Improvement of colored thread algorithm for network reachability test
Kim, Han-Kyoung ; Lee, Kwang-Hui ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 27~32
Colored thread algorithm, suggested to be used for the label switching network, needs to be modified for the packet switching network. In this paper, it is recommended to add a merged state, besides the 3 states - null, colored and transparent - which are resulted from the behaviors of extend, rewind, stall, withdraw and merge events. The original colored thread algorithm is designed to generate a new thread and extend it to the downstream direction with unknown hop count when the thread has revisited the node that was visited. It also suggested rewinding the thread to the downstream direction by the source node, instead of rewinding it upstream direction by the revisited node. If a node received multiple threads which had a same forward equivalent class, then it checks first whether the hop counts are ascending or not. If it is in ascending order, then threads are merged. Otherwise the later thread is stalled until the former thread's color is to be changed to transparent or it is removed. This idea removes the effort of generating a new thread with unknown hop count.
Design of DAB/DAB+ Dual-mode Audio Receiver
Kang, Min-Goo ; Lee, Jin-Woo ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 33~39
In this paper, the Window based dual-mode audio receiver of DAB and DAB+(Digital Audio Broadcasting Plus) is designed, and audio performance of it is analyzed. DAB+ can be composed of DAB and AAC(Advanced Audio Coding) for more effective audio services in the limited channel bandwidth. In the result of thesis, the Window based receiver can simultaneously be decoded for DAB/DAB+ dual-mode audio.
On Generating Backbone Based on Energy and Connectivity for WSNs
Shin, In-Young ; Kim, Moon-Seong ; Choo, Hyun-Seung ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 41~47
Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.
A Comparison of Performance between STMP/MST and Existing Spatio-Temporal Moving Pattern Mining Methods
Lee, Yon-Sik ; Kim, Eun-A ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 49~63
The performance of spatio-temporal moving pattern mining depends on how to analyze and process the huge set of spatio-temporal data due to the nature of it. The several method was presented in order to solve the problems in which existing spatio-temporal moving pattern mining methods[1-10] have, such as increasing execution time and required memory size during the pattern mining, but they did not solve properly yet. Thus, we proposed the STMP/MST method as a preceding research in order to extract effectively sequential and/or periodical frequent occurrence moving patterns from the huge set of spatio-temporal moving data. The proposed method reduces patterns mining execution time, using the moving sequence tree based on hash tree. And also, to minimize the required memory space, it generalizes detailed historical data including spatio-temporal attributes into the real world scopes of space and time by using spatio-temporal concept hierarchy. In this paper, in order to verify the effectiveness of the STMP/MST method, we compared and analyzed performance with existing spatio-temporal moving pattern mining methods based on the quantity of mining data and minimum support factor.
Frequently Occurred Information Extraction from a Collection of Labeled Trees
Paik, Ju-Ryon ; Nam, Jung-Hyun ; Ahn, Sung-Joon ; Kim, Ung-Mo ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 65~78
The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.
Optimal Moving Pattern Mining using Frequency of Sequence and Weights
Lee, Yon-Sik ; Park, Sung-Sook ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 79~93
For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F). Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods(
, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.
Design and Application of Multi Concept Keyword Model based on Web-using Information
Yoon, Tae-Bok ; Lee, Seung-Hoon ; Yoon, Kwang-Ho ; Lee, Jee-Hyong ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 95~105
There are various studies to provide useful information for users on huge data of web-sites. Web usage mining among them is a method to extract meaningful patterns based on web users' log data. Most of existing patterns of web usage mining, however, had not considered users' diverse inclination but created general models. Web users' keywords can have various meaning upon their tendency and background knowledge. This study is for generating Multi Concept Keyword Model (MCK-Model) by analyzing web usage information on users' keywords of interest. MCK-Model can supply web page network for various inclination based on users' keywords of interest. Also, MCK-Model can be used to recommend the most proper web pages and it has been confirmed that the suggested method is useful enough.
Detection of Arrhythmia Using Heart Rate Variability and A Fuzzy Neural Network
Jang, Hyoung-Jong ; Lim, Joon-Shik ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 107~116
This paper presents an approach to detect arrhythmia using heart rate variability and a fuzzy neural network. The proposed algorithm diagnoses arrhythmia using 32 RR-intervals that are 25 seconds on average. We extract six statistical values from the 32 RR-intervals, which are used to input data of the fuzzy neural network. This paper uses the neural network with weighted fuzzy membership functions(NEWFM) to diagnose arrhythmia. The NEWFM used in this algorithm classifies normal and arrhythmia. The performances by Tsipouras using the 48 records of the MIT-BIH arrhythmia database was below 80% of SE(sensitivity) and SP(specificity) in both. The detection algorithm of arrhythmia shows 88.75% of SE, 82.28% of SP, and 86.31% of accuracy.
Implementation of Network-based Robot System to Guide a way
Kim, Hyung-Sun ; Lee, Jun-Yeon ; Lim, Jae-Hyun ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 117~125
Early in 21st century, researches about intelligent service robot that provide various services for a human out of the industrial robot only has simple pattern repetition. It concentrates in the research regarding the URC(Ubiquitous Robotic Companion) robot which connects the network in the intelligent service. This paper proposes the robot system based on network to guide a way. The robot has made by lego brick and used ultrasonic sensor, rotation sensor and RFID tag to recognize external environment. Also, it includes a PDA to process the data between robot and server. The network server transmits information to robot controller by bluetooth and it controls the course movement and evasion of the robot. In this research, the robot system based on network to guide a way is easy to expand service and is able to process a data in real time due to data processing in the server as a part of intelligent robot. And it can reduce the cost to build a robot thank to use cheaper sensor equipment.
Extracting Input Features and Fuzzy Rules for Classifying Epilepsy Based on NEWFM
Lee, Sang-Hong ; Lim, Joon-S. ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 127~133
This paper presents an approach to classify normal and epilepsy from electroencephalogram(EEG) using a neural network with weighted fuzzy membership functions(NEWFM). To extract input features used in NEWFM, wavelet transform is used in the first step. In the second step, the frequency distribution of signal and the amount of changes in frequency distribution are used for extracting twenty-four numbers of input features from coefficients and approximations produced by wavelet transform in the previous step. NEWFM classifies normal and epilepsy using twenty four numbers of input features, and then the accuracy rate is 98%.
The Examination of the Variables related to the Students' e-learning Participation that Have an Effect on Learning Achievement in e-learning Environment of Cyber University
Kang, Min-Seok ; Kim, Jin-Il ; Park, Inn-Woo ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 135~143
The purpose of this study is to examine the variables related to the students' e-learning participation that have an effect on learning achievement in e-learning environment of cyber universities. Based on the related research, the followings are derive. First, students' attendance and participation in discussion showed higher correlation with the learning achievement than other participation variables. However, the total studying time in online classes showed lower correlation with the learning achievement. Second, the variables that have an effect on the learning achievement were in the order of students' attendance, participation in discussion, access frequency to online classes, learning progress and number of data uploads. Third, by the learners' background, the difference among the variables that have an effect on learning achievement were found. Based on the results above, this study suggests considerations about participation variables to enhance the learning achievement in cyber universities.
A CSP based Learner Tailoring Question Recommendation Process using Item Response Theory
Jeong, Hwa-Young ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 145~152
Applications such as study guides and adaptive tutoring must rely on a fine grained student model to tailor their interaction with the user. They are useful for Computer Adaptive Testing (CAT), for example, where the test items can be administered in order to maximize the information. I study how to design learner tailoring question process for recommendation. And this process can be applied the CAT and I use the formal language such as CSP in each process development for efficient process design. I use the item difficulty of item response theory for question recommendation process and learner can choice the difficulty step for learning change to control the difficulty of question in next learning. Finally, this method displayed the structural difference to compare between existent and this process.
Extended Use Case Modeling for Service-Oriented Computing
Cho, Jun-Soo ; Chong, Ki-Won ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 153~163
It is necessary to identify the use cases of the supplier systems in order to define new service using their functions. Current use case modeling techniques, however, do not represent the external use cases clearly, because the external system is represented only by an actor. This ambiguity of the modeling technique declines the comprehensiveness of the model, and does not limit the scope of the target system explicitly. In this paper, we propose the extended use case modeling technique for service-oriented computing. This modeling technique enables the definition of external use cases and components. They are used to limit the boundary of the target system, and the relationship between them are modeled by the realization of external use cases. The proposed technique uses UML stereotype extension mechanism. so the compatibility with current use case modeling technique is preserved.
Interactive Shape Analysis of the Hippocampus in a Virtual Environment
Kim, Jeong-Sik ; Choi, Soo-Mi ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 165~181
This paper presents an effective representation scheme for the shape analysis of the hippocampal structure and a stereoscopic-haptic environment to enhance sense of realism. The parametric model and the 3D skeleton represent various types of hippocampal shapes and they are stored in the Octree data structure. So they can be used for the interactive shape analysis. And the 3D skeleton-based pose normalization allows us to align a position and an orientation of the 3D hippocampal models constructed from multimodal medical imaging data. We also have trained Support Vector Machine (SVM) for classifying between the normal controls and epileptic patients. Results suggest that the presented representation scheme provides various level of shape representation and the SVM can be a useful classifier in analyzing the shape differences between two groups. A stereoscopic-haptic virtual environment combining an auto-stereoscopic display with a force-feedback (or haptic) device takes an advantage of 3D applications for medicine because it improves space and depth perception.
Active Shape Model-based Objectionable Image Detection
Jang, Seok-Woo ; Joo, Seong-Il ; Kim, Gye-Young ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 183~194
In this paper, we propose a new method for detecting objectionable images with an active shape model. Our method first learns the shape of breast lines through principle component analysis and alignment as well as the distribution of intensity values of corresponding landmarks, and then extracts breast lines with the learned shape and intensity distribution. To accurately select the initial position of active shape model, we obtain parameters on scale, rotation, and translation. After positioning the initial location of active shape model using scale and rotation information, iterative searches are performed. We can identify adult images by calculating the average of the distance between each landmark and a candidate breast line. The experiment results show that the proposed method can detect adult images effectively by comparing various results.
Framework for Improving Mobile Embedded Software Process
Shin, Seung-Woo ; Kim, Haeng-Kon ; Kim, Soung-Won ;
Journal of Internet Computing and Services, volume 10, issue 5, 2009, Pages 195~209
The embedded software has been become more important than the hardware in mobile systems in ubiquitous society. The improvement models such as CMMI(Capability Maturity Model Integration) and SPICE(Software Process Improvement and Capability dEtermination) are used to improve the quality of software in general systems. Software process improvement is also necessary for mobile embedded software development to improve its quality. It is not easy to apply the general software improvement model to the mobile embedded software development due to the high cost effectiveness and heavy process. On the other hand, XP has the characteristics on focused communications with customers and iteration development. It is specially suitable for mobile embedded software development as depending on customer's frequent requirement changes and hardware attributes. In this paper, we propose a framework for development small process improvement based XP(eXtreme Programming)'s practice in order to accomplish CMMI level 2 or 3 in mobile embedded software development at the small organizations. We design and implement the Mobile Embedded Software Process Improvement System(MESPIS) to support process improvement. We also suggest the evaluation method for the mobile embedded software development process improvement framework with CMMI coverage check by comparing other process improvement model. In the future, we need to apply this proposed framework to real project for practical effectiveness and the real cases quantitative. It also include the enhance the functionality of MESPIS.