• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.493-503
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• 2018

The present study is a conceptual replication of O'Grady, Lee, and Choo's (2003) earlier study designed to investigate two hypotheses (linear distance hypothesis vs. structural distance hypothesis) in relation to L2 Korean learners' processing of Korean subject and object relative clauses (RCs) in a scholarly attempt to explicate Keenan and Comrie's (1977) Noun Phrase Accessibility Hierarchy (NPAH). In addition, the current study is intended to explore any potential role of working memory capacity (WMC) in the processing of Korean subject and/or object RCs. Chinese-speaking learners of Korean taking a language course offered at a local university in Korea participated in this experimental study. Among those recruited, only 23 learners completed the experimental tasks appropriately according to the specific instructions provided on each task, and thus, subsequent statistical analyses were conducted on their data. Fifteen Korean NSs were also recruited for the control group. Two experimental tasks were administerd to the participants: one picture selection task containing the same test items used in O'Grady et al.'s study to measure their processing of subject-object RCs and an operation span (OSPAN) task to measure their WMC. Somewhat differently from O'Grady et al.'s findings, the participating Chinese learners of Korean performed significantly better on object RCs than on subject RCs, seemingly lending support to the linear distance hypothesis. Further analyses, however, suggested that the results in favor of, or relative ease of processing, object relative clauses were due, most likely, to the learners' excessive use of the canonical sentence strategy, which also led to nonsignificant correlations between WMC and learner performance on the picture selection task.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.734-739
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• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. For the control of the mobile robot, an absolute position sensor is necessary. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and that is propagated to getting the pose of a mobile robot. With the experiments in the corridor, the proposed active calibration scheme is verified experimentally.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.592-601
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• 2013

Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.

• Physical Therapy Rehabilitation Science
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• v.1 no.1
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• pp.1-5
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• 2012

Objective: Dual-task walking deficits impact functional daily life, which often requires walking while performing simultaneous tasks such as talking, thinking or carrying an object. This study is to find out the latest trend of dual-task training's influence on ambulatory abilities of a stroke patient. Design: Systematic review of randomized controlled trials. Methods: This literature review was conducted in Pubmed and Sciencedirect with the follwing key words:stroke, cerebro-vascular accident, hemiplegia, gait, rehabilitation, exercise. 7 studies were chosen in findings by search tool. 3 studies were case study, 3 studies were cross sectional observational study and 1 study was randomized controlled trial. Results: It was found that stroke patients have difficulties in doing 2 motor tasks simultaneously and when they do 2 tasks, one is done in a naturally preferred activity areas. Moreover, when simply applying dual-tasks, the walking speed decreased. Meanwhile, when applying them through training, the speed increased. This showed the improvement of effective task-implementation abilities after dual-task training using task-integration models. Conclusions: In the beginning of the 2000s, dual-tasks were implemented by simply combining walking and cognition or exercise task, and the results of this study suggest that subjects with stroke have difficulty performing dual task. However, the latest trend is to let patients do the dual-task training by combining it with virtual reality. Therefore, dual task training could be performed in a safe in the environment such as virtual reality or augment reality.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.174-182
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• 2002

The object-oriented design methods and their CASE tools are widely used in practice by many real-time software developers. However, object-oriented CASE tools require an additional step of identifying tasks from a given design model. Unfortunately, it is difficult to automate this step for a couple of reasons: (1) there are inherent discrepancies between objects and tasks; and (2) it is hard to derive tasks while maximizing real-time schedulability since this problem makes a non-trivial optimization problem. As a result, in practical object-oriented CASE tools, task identification is usually performed in an ad-hoc manner using hints provided by human designers. In this paper, we present a systematic, schedulability-aware approach that can help mapping real-time object-oriented models to multi-threaded implementations. In our approach, a task contains a group of mutually exclusive transactions that may possess different periods and deadline. For this new task model, we provide a new schedulability analysis algorithm. We also show how the run-time system is implemented and how executable code is generated in our frame work. We have performed a case study. It shows the difficulty of task derivation problem and the utility of the automated synthesis of implementations as well as the Inappropriateness of the single-threaded implementations.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1178-1178
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• 1999

A spatial join has the property that its execution time exponentially increases in proportion to the number of spatial objects. Recently, there have been many attempts for improving the performance of the spatial join by using parallel processing schemes, In the case of executing parallel spatial join using the parallel machine with shared disk architecture, the disk bottleneck of parallel processing of spatial join worsens in comparison with sequential spatial join. This paper presents the algorithms of task creation and assignment to reduce the disk bottleneck caused by accessing the shared disk at the same time, and to minimize message passing between processors, This paper proposes object caching which is a higher level of abstraction than page caching, and uses it to do creation and assignment of tasks according to temporal and spatial localities for minimizing disk access time. The object caching shows the performance improvement of 50%. The task creation and assignment using localities gives the gain of 30% and 20%. Overall performance evaluation of the proposed algorithms shows 7.2 times speed up than those of sequential execution of spatial joins.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.309-321
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• 2013

In current complex nature of management with task-structures, a method to reach the enterprise's informationalization success is not common. To satisfy these various requirement, improving the usability of information technology (IT) is a key factor which defining the level of organizational requirement first. Imposing an IT-solution which has excess service of the organization's previous task-environment, procedure and scope is not effective to SME-level unit, which unit could not have a formal organization structure and task structure. SME level informationalization will be success if each function realizes easier on the task-employee's viewpoint. Achieving this objective, a solution provider or department must reflect their work characteristics of nature which has least level of work performing resistance. It is most useful system for SME level unit, if a provider develops single programs which based on task activities, and each program can configure network-linking.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.32.5-32
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• 2001

There has been many teleoperation systems handling the micro object. However, the stability problem for these systems has not been mentioned yet. Historically, Lawrence[1] proposed the Transparency-Optimized Architecture and passivity theorem for stability analysis of bilateral teleoperation. He claimed that unless the task(or environment) impedance contains significance inertial behavior, Passivity condition for Transparency-optimized architecture is not satisfied. In this paper we propose one method which satisfies passivity condition for the micro-teleoperation system handling a insignificant inertial object and is based on the structure of Lawrence and Hashtrudi-Zaad[2] and velocity-force scaling.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• The Magazine of the IEIE
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• v.39 no.2
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• pp.45-54
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• 2012

Object detection is a fundamental task for many high-level computer vision applications such as image retrieval, scene understanding, activity recognition, visual surveillance and many others. Although object detection is one of the most popular problems in computer vision and various algorithms have been proposed thus far, it is also notoriously difficult, mainly due to lack of proper models for object representation, that handle large variations of object structure and appearance. In this article, we review a branch of object detection algorithms based on Support Vector Machines (SVMs), a well-known max-margin technique to minimize classification error. We introduce a few variations of SVMs-Structural SVMs and Latent SVMs-and discuss their applications to object detection and localization.