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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Electronics and Telecommunications Research Institute
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Volume & Issues
Volume 32, Issue 6 - Dec 2010
Volume 32, Issue 5 - Oct 2010
Volume 32, Issue 4 - Aug 2010
Volume 32, Issue 3 - Jun 2010
Volume 32, Issue 2 - Apr 2010
Volume 32, Issue 1 - Feb 2010
Selecting the target year
OPRoS: A New Component-Based Robot Software Platform
Jang, Choul-Soo ; Lee, Seung-Ik ; Jung, Seung-Woog ; Song, Byoung-Youl ; Kim, Rock-Won ; Kim, Sung-Hoon ; Lee, Cheol-Hoon ;
ETRI Journal, volume 32, issue 5, 2010, Pages 646~656
DOI : 10.4218/etrij.10.1510.0138
A component is a reusable and replaceable software module accessed through its interface. Component-based development is expected to shorten the development period, reduce maintenance costs, and improve program reusability and the interoperability of components. This paper proposes a new robot software component platform in order to support the entire process of robot software development. It consists of specifications of a component model, component authoring tool, component composer, and component execution engine. To show its feasibility, this paper presents the analysis results of the component's communication overhead, a comparison with other robotic software platforms, and applications in commercial robots.
Hardware-Aware Rate Monotonic Scheduling Algorithm for Embedded Multimedia Systems
Park, Jae-Beom ; Yoo, Joon-Hyuk ;
ETRI Journal, volume 32, issue 5, 2010, Pages 657~664
DOI : 10.4218/etrij.10.1510.0027
Many embedded multimedia systems employ special hardware blocks to co-process with the main processor. Even though an efficient handling of such hardware blocks is critical on the overall performance of real-time multimedia systems, traditional real-time scheduling techniques cannot afford to guarantee a high quality of multimedia playbacks with neither delay nor jerking. This paper presents a hardware-aware rate monotonic scheduling (HA-RMS) algorithm to manage hardware tasks efficiently and handle special hardware blocks in the embedded multimedia system. The HA-RMS prioritizes the hardware tasks over software tasks not only to increase the hardware utilization of the system but also to reduce the output jitter of multimedia applications, which results in reducing the overall response time.
Content Protective Multi-Agent Platform for MsMu Service and Pattern-Based Content Management
Uhm, Yoon-Sik ; Hwang, Zi-On ; Lee, Min-Soo ; Nah, Jae-Hoon ; Song, Hwang-Jun ; Park, Se-Hyun ;
ETRI Journal, volume 32, issue 5, 2010, Pages 665~675
DOI : 10.4218/etrij.10.1510.0143
Recent research on mobile Internet protocol television and digital right management (DRM) interconnections has focused on multimedia technologies designed to enhance content scalability and adaptive content distribution. However, due to the architectural and scalable limitations, recent systems are not flexible and securable with respect to their adaptive content distribution and protective policy management. Therefore, we propose a content protective multi-agent platform that provides secure multimedia services, correlation management, pattern-based management, and multi-source multi-use (MsMu)-based services. Our architecture, supported by DRM, lets us create a rich set of MsMu-based content protection and seamless multimedia services through the extension of one source multi-use (OsMu)-based content services. We have verified our platform, which provides scalable and securable services with a 17% lower service response time by using a testbed.
A Novel Approach for Mining High-Utility Sequential Patterns in Sequence Databases
Ahmed, Chowdhury Farhan ; Tanbeer, Syed Khairuzzaman ; Jeong, Byeong-Soo ;
ETRI Journal, volume 32, issue 5, 2010, Pages 676~686
DOI : 10.4218/etrij.10.1510.0066
Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real-world scenarios. In this paper, we propose a novel framework for mining high-utility sequential patterns for more real-life applicable information extraction from sequence databases with non-binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high-utility sequential patterns, we propose two new algorithms: UtilityLevel is a high-utility sequential pattern mining with a level-wise candidate generation approach, and UtilitySpan is a high-utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high-utility sequential patterns.
Analysis of Break in Presence During Game Play Using a Linear Mixed Model
Chung, Jae-Yong ; Yoon, Hwan-Jin ; Gardne, Henry J. ;
ETRI Journal, volume 32, issue 5, 2010, Pages 687~694
DOI : 10.4218/etrij.10.1510.0054
Breaks in presence (BIP) are those moments during virtual environment (VE) exposure in which participants become aware of their real world setting and their sense of presence in the VE becomes disrupted. In this study, we investigate participants' experience when they encounter technical anomalies during game play. We induced four technical anomalies and compared the BIP responses of a navigation mode game to that of a combat mode game. In our analysis, we applied a linear mixed model (LMM) and compared the results with those of a conventional regression model. Results indicate that participants felt varied levels of impact and recovery when experiencing the various technical anomalies. The impact of BIPs was clearly affected by the game mode, whereas recovery appears to be independent of game mode. The results obtained using the LMM did not differ significantly from those obtained using the general regression model; however, it was shown that treatment effects could be improved by consideration of random effects in the regression model.
Virtual Reality Content-Based Training for Spray Painting Tasks in the Shipbuilding Industry
Lee, Gun-A. ; Yang, Ung-Yeon ; Son, Wook-Ho ; Kim, Yong-Wan ; Jo, Dong-Sik ; Kim, Ki-Hong ; Choi, Jin-Sung ;
ETRI Journal, volume 32, issue 5, 2010, Pages 695~703
DOI : 10.4218/etrij.10.1510.0105
Training is one of the representative application fields of virtual reality technology where users can have virtual experience in a training task and working environment. Widely used in the medical and military fields, virtual-reality-based training systems are also useful in industrial fields, such as the aerospace industry, since they show superiority over real training environments in terms of accessibility, safety, and cost. The shipbuilding industry is known as a labor-intensive industry that demands a lot of skilled workers. In particular, painting jobs in the shipbuilding industry require a continuous supplement of human resources since many workers leave due to the poor working environment. In this paper, the authors present a virtual-reality-based training system for spray painting tasks in the shipbuilding industry. The design issues and implementation details of the training system are described, and also its advantages and shortcomings are discussed based on use cases in actual work fields.
A Robust Mutual Authentication Protocol for Wireless Sensor Networks
Chen, Tien-Ho ; Shih, Wei-Kuan ;
ETRI Journal, volume 32, issue 5, 2010, Pages 704~712
DOI : 10.4218/etrij.10.1510.0134
Authentication is an important service in wireless sensor networks (WSNs) for an unattended environment. Recently, Das proposed a hash-based authentication protocol for WSNs, which provides more security against the masquerade, stolen-verifier, replay, and guessing attacks and avoids the threat which comes with having many logged-in users with the same login-id. In this paper, we point out one security weakness of Das' protocol in mutual authentication for WSN's preservation between users, gateway-node, and sensor nodes. To remedy the problem, this paper provides a secrecy improvement over Das' protocol to ensure that a legal user can exercise a WSN in an insecure environment. Furthermore, by presenting the comparisons of security, computation and communication costs, and performances with the related protocols, the proposed protocol is shown to be suitable for higher security WSNs.
Wearable Personal Network Based on Fabric Serial Bus Using Electrically Conductive Yarn
Lee, Hyung-Sun ; Park, Choong-Bum ; Noh, Kyoung-Ju ; SunWoo, John ; Choi, Hoon ; Cho, Il-Yeon ;
ETRI Journal, volume 32, issue 5, 2010, Pages 713~721
DOI : 10.4218/etrij.10.1510.0084
E-textile technology has earned a great deal of interest in many fields; however, existing wearable network protocols are not optimized for use with conductive yarn. In this paper, some of the basic properties of conductive textiles and requirements on wearable personal area networks (PANs) are reviewed. Then, we present a wearable personal network (WPN), which is a four-layered wearable PAN using bus topology. We have designed the WPN to be a lightweight protocol to work with a variety of microcontrollers. The profile layer is provided to make the application development process easy. The data link layer exchanges frames in a master-slave manner in either the reliable or best-effort mode. The lower part of the data link layer and the physical layer of WPN are made of a fabric serial-bus interface which is capable of measuring bus signal properties and adapting to medium variation. After a formal verification of operation and performances of WPN, we implemented WPN communication modules (WCMs) on small flexible printed circuit boards. In order to demonstrate the behavior of our WPN on a textile, we designed a WPN tutorial shirt prototype using implemented WCMs and conductive yarn.
Touchpad for Force and Location Sensing
Kim, Dong-Ki ; Kim, Jong-Ho ; Kwon, Hyun-Joon ; Kwon, Young-Ha ;
ETRI Journal, volume 32, issue 5, 2010, Pages 722~728
DOI : 10.4218/etrij.10.1510.0073
This paper presents the design and fabrication model of a touchpad based on a contact-resistance-type force sensor. The touchpad works as a touch input device, which can sense contact location and contact force simultaneously. The touchpad is 40 mm wide and 40 mm long. The touchpad is fabricated by using a simple screen printing technique. The contact location is evaluated by the calibration setup, which has a load cell and three-axis stages. The location error is approximately 4 mm with respect to x-axis and y-axis directions. The force response of the fabricated touchpad is obtained at three points by loading and unloading of the probe. The touchpad can detect loads from 0 N to 2 N. The touchpad shows a hysteresis error rate of about 11% and uniformity error rate of about 3%.
A Novel Character Segmentation Method for Text Images Captured by Cameras
Lue, Hsin-Te ; Wen, Ming-Gang ; Cheng, Hsu-Yung ; Fan, Kuo-Chin ; Lin, Chih-Wei ; Yu, Chih-Chang ;
ETRI Journal, volume 32, issue 5, 2010, Pages 729~739
DOI : 10.4218/etrij.10.1510.0086
Due to the rapid development of mobile devices equipped with cameras, instant translation of any text seen in any context is possible. Mobile devices can serve as a translation tool by recognizing the texts presented in the captured scenes. Images captured by cameras will embed more external or unwanted effects which need not to be considered in traditional optical character recognition (OCR). In this paper, we segment a text image captured by mobile devices into individual single characters to facilitate OCR kernel processing. Before proceeding with character segmentation, text detection and text line construction need to be performed in advance. A novel character segmentation method which integrates touched character filters is employed on text images captured by cameras. In addition, periphery features are extracted from the segmented images of touched characters and fed as inputs to support vector machines to calculate the confident values. In our experiment, the accuracy rate of the proposed character segmentation system is 94.90%, which demonstrates the effectiveness of the proposed method.
Noun Sense Identification of Korean Nominal Compounds Based on Sentential Form Recovery
Yang, Seong-Il ; Seo, Young-Ae ; Kim, Young-Kil ; Ra, Dong-Yul ;
ETRI Journal, volume 32, issue 5, 2010, Pages 740~749
DOI : 10.4218/etrij.10.1510.0083
In a machine translation system, word sense disambiguation has an essential role in the proper translation of words when the target word can be translated differently depending on the context. Previous research on sense identification has mostly focused on adjacent words as context information. Therefore, in the case of nominal compounds, sense tagging of unit nouns mainly depended on other nouns surrounding the target word. In this paper, we present a practical method for the sense tagging of Korean unit nouns in a nominal compound. To overcome the weakness of traditional methods regarding the data sparseness problem, the proposed method adopts complement-predicate relation knowledge that was constructed for machine translation systems. Our method is based on a sentential form recovery technique, which recognizes grammatical relationships between unit nouns. This technique makes use of the characteristics of Korean predicative nouns. To show that our method is effective on text in general domains, the experiments were performed on a test set randomly extracted from article titles in various newspaper sections.
Clausius Normalized Field-Based Stereo Matching for Uncalibrated Image Sequences
Koh, Eun-Jin ; Lee, Jae-Yeon ; Park, Jun-Seok ;
ETRI Journal, volume 32, issue 5, 2010, Pages 750~760
DOI : 10.4218/etrij.10.1510.0067
We propose a homology between thermodynamic systems and images for the treatment of time-varying imagery. A physical system colder than its surroundings absorbs heat from the surroundings. Furthermore, the absorbed heat increases the entropy of the system, which is closely related to its disorder as given by the definition of Clausius and Boltzmann. Because pixels of an image are viewed as a state of lattice-like molecules in a thermodynamic system, the task of reckoning the entropy variations of pixels is similar to estimating their degrees of disorder. We apply this homology to the uncalibrated stereo matching problem. The absence of calibrations alleviates user efforts to install stereo cameras and enables users to freely modify the composition of the cameras. The proposed method is also robust to differences in brightness, white balancing, and even focusing between stereo image pairs. These peculiarities enable users to estimate the depths of interesting objects in practical applications without much effort in order to set and maintain a stereo vision setup. Users can consequently utilize two webcams as a stereo camera.
Disguised-Face Discriminator for Embedded Systems
Yun, Woo-Han ; Kim, Do-Hyung ; Yoon, Ho-Sub ; Lee, Jae-Yeon ;
ETRI Journal, volume 32, issue 5, 2010, Pages 761~765
DOI : 10.4218/etrij.10.1510.0139
In this paper, we introduce an improved adaptive boosting (AdaBoost) classifier and its application, a disguised-face discriminator that discriminates between bare and disguised faces. The proposed classifier is based on an AdaBoost learning algorithm and regression technique. In the process, the lookup table of AdaBoost learning is utilized. The proposed method is verified on the captured images under several real environments. Experimental results and analysis show the proposed method has a higher and faster performance than other well-known methods.
Asymmetric Semi-Supervised Boosting Scheme for Interactive Image Retrieval
Wu, Jun ; Lu, Ming-Yu ;
ETRI Journal, volume 32, issue 5, 2010, Pages 766~773
DOI : 10.4218/etrij.10.1510.0016
Support vector machine (SVM) active learning plays a key role in the interactive content-based image retrieval (CBIR) community. However, the regular SVM active learning is challenged by what we call "the small example problem" and "the asymmetric distribution problem." This paper attempts to integrate the merits of semi-supervised learning, ensemble learning, and active learning into the interactive CBIR. Concretely, unlabeled images are exploited to facilitate boosting by helping augment the diversity among base SVM classifiers, and then the learned ensemble model is used to identify the most informative images for active learning. In particular, a bias-weighting mechanism is developed to guide the ensemble model to pay more attention on positive images than negative images. Experiments on 5000 Corel images show that the proposed method yields better retrieval performance by an amount of 0.16 in mean average precision compared to regular SVM active learning, which is more effective than some existing improved variants of SVM active learning.
Efficient Image Chaotic Encryption Algorithm with No Propagation Error
Awad, Abir ; Awad, Dounia ;
ETRI Journal, volume 32, issue 5, 2010, Pages 774~783
DOI : 10.4218/etrij.10.1510.0063
Many chaos-based encryption methods have been presented and discussed in the last two decades, but very few of them are suitable to secure transmission on noisy channels or respect the standard of the National Institute of Standards and Technology (NIST). This paper tackles the problem and presents a novel chaos-based cryptosystem for secure transmitted images. The proposed cryptosystem overcomes the drawbacks of existing chaotic algorithms such as the Socek, Xiang, Yang, and Wong methods. It takes advantage of the increasingly complex behavior of perturbed chaotic signals. The perturbing orbit technique improves the dynamic statistical properties of generated chaotic sequences, permits the proposed algorithm reaching higher performance, and avoids the problem of error propagation. Finally, many standard tools, such as NIST tests, are used to quantify the security level of the proposed cryptosystem, and experimental results prove that the suggested cryptosystem has a high security level, lower correlation coefficients, and improved entropy.
Robust Facial Expression Recognition Based on Local Directional Pattern
Jabid, Taskeed ; Kabir, Md. Hasanul ; Chae, Oksam ;
ETRI Journal, volume 32, issue 5, 2010, Pages 784~794
DOI : 10.4218/etrij.10.1510.0132
Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.
A New Distance Measure for a Variable-Sized Acoustic Model Based on MDL Technique
Cho, Hoon-Young ; Kim, Sang-Hun ;
ETRI Journal, volume 32, issue 5, 2010, Pages 795~800
DOI : 10.4218/etrij.10.1510.0062
Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.
Statistical Model-Based Noise Reduction Approach for Car Interior Applications to Speech Recognition
Lee, Sung-Joo ; Kang, Byung-Ok ; Jung, Ho-Young ; Lee, Yun-Keun ; Kim, Hyung-Soon ;
ETRI Journal, volume 32, issue 5, 2010, Pages 801~809
DOI : 10.4218/etrij.10.1510.0024
This paper presents a statistical model-based noise suppression approach for voice recognition in a car environment. In order to alleviate the spectral whitening and signal distortion problem in the traditional decision-directed Wiener filter, we combine a decision-directed method with an original spectrum reconstruction method and develop a new two-stage noise reduction filter estimation scheme. When a tradeoff between the performance and computational efficiency under resource-constrained automotive devices is considered, ETSI standard advance distributed speech recognition font-end (ETSI-AFE) can be an effective solution, and ETSI-AFE is also based on the decision-directed Wiener filter. Thus, a series of voice recognition and computational complexity tests are conducted by comparing the proposed approach with ETSI-AFE. The experimental results show that the proposed approach is superior to the conventional method in terms of speech recognition accuracy, while the computational cost and frame latency are significantly reduced.
Three-Stage Framework for Unsupervised Acoustic Modeling Using Untranscribed Spoken Content
Zgank, Andrej ;
ETRI Journal, volume 32, issue 5, 2010, Pages 810~818
DOI : 10.4218/etrij.10.1510.0092
This paper presents a new framework for integrating untranscribed spoken content into the acoustic training of an automatic speech recognition system. Untranscribed spoken content plays a very important role for under-resourced languages because the production of manually transcribed speech databases still represents a very expensive and time-consuming task. We proposed two new methods as part of the training framework. The first method focuses on combining initial acoustic models using a data-driven metric. The second method proposes an improved acoustic training procedure based on unsupervised transcriptions, in which word endings were modified by broad phonetic classes. The training framework was applied to baseline acoustic models using untranscribed spoken content from parliamentary debates. We include three types of acoustic models in the evaluation: baseline, reference content, and framework content models. The best overall result of 18.02% word error rate was achieved with the third type. This result demonstrates statistically significant improvement over the baseline and reference acoustic models.
A Multichannel TDMA MAC Protocol to Reduce End-to-End Delay in Wireless Mesh Networks
Trung, Tran Minh ; Mo, Jeong-Hoon ;
ETRI Journal, volume 32, issue 5, 2010, Pages 819~822
DOI : 10.4218/etrij.10.0210.0102
Supporting QoS over multihop wireless mesh networks is difficult because end-to-end delay increases quickly with the increasing number of hops. This paper introduces a novel multichannel time-division multiple-access media access control (McTMAC) protocol that can help to efficiently reduce delay over multihop networks. Performance evaluation results demonstrate that McTMAC outperforms existing alternative protocols. The max-delay can be reduced by as much as 60% by using McTMAC.
Handover Ranging Power Adjustment Using Uplink Channel Information in IEEE 802.16e/m
Kim, Ji-Su ; Kim, Jae-Hyun ;
ETRI Journal, volume 32, issue 5, 2010, Pages 823~826
DOI : 10.4218/etrij.10.0210.0161
This letter proposes a handover ranging power adjustment scheme to improve handover performance. Incorrect ranging power can degrade handover performance due to the increased handover latency; therefore, the proposed scheme exploits the uplink channel information to adjust the uplink handover ranging power. Simulation results demonstrate that the proposed scheme reduces call outage probability by 33% compared to that of the conventional scheme. It also improves the number of users who satisfy the system requirements for handover interruption time.
Design of 24 GHz Radar with Subspace-Based Digital Beam Forming for ACC Stop-and-Go System
Jeong, Seong-Hee ; Oh, Jun-Nam ; Lee, Kwae-Hi ;
ETRI Journal, volume 32, issue 5, 2010, Pages 827~830
DOI : 10.4218/etrij.10.0210.0107
For an adaptive cruise control (ACC) stop-and-go system in automotive applications, three radar sensors are needed because two 24 GHz short range radars are used for object detection in an adjacent lane, and one 77 GHz long-range radar is used for object detection in the center lane. In this letter, we propose a single sensor-based 24 GHz radar with a detection capability of up to 150 m and
for an ACC stop-and-go system. The developed radar is highly integrated with a high gain patch antenna, four channel receivers with GaAs RF ICs, and back-end processing board with subspace based digital beam forming algorithm.
Joint Channel Coding Based on Principal Component Analysis
Hyun, Dong-Il ; Lee, Dong-Geum ; Park, Young-Cheol ; Youn, Dae-Hee ; Seo, Jeong-Il ;
ETRI Journal, volume 32, issue 5, 2010, Pages 831~834
DOI : 10.4218/etrij.10.0210.0124
This paper proposes a new joint channel coding algorithm based on principal component analysis. A conventional joint channel coder using passive downmixing undergoes a reduction of both the primary-to-ambient energy ratio (PAR) of the downmix signal and the panning gain ratio of the primary source. The proposed system preserves the PAR of the downmix signal by using active downmixing which reflects spatial characteristic. The proposed system also improves the accuracy of the panning gain ratio estimation. Computer simulations and subjective listening tests verify the performance of the proposed system.