• Journal of the Korean Geophysical Society
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• v.9 no.2
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• pp.99-103
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• 2006

3D object recognition independent of translation and rotation using an ultrasonic sensor array, invariant moment vectors and SOFM(Self Organizing Feature Map) neural networks is presented. Using invariant moment vectors of the acquired 16×8 pixel data of square, rectangular, cylindric and regular triangular blocks, 3D objects could be classified by SOFM neural networks. Invariant moment vectors are constant independent of translation and rotation. The recognition rates for the training and testing data were 95.91% and 92.13%, respectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.73-82
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• 1996

In this paper, an efficient algorithm for recognizing and positioning occuluded objects in a two-dimensional plane is presented. Model objects and unknown input image are approximated by polygonal boundaries, which are compactly represented by shape functions of the polygons. The input image is partitioned into measningful segments whose end points are at the locations of possible occlusion - i.e. at concave vertices. Each segment is matched against known model objects by calculating a matching measure, which is defined as the minimum euclidean distance between the shape functions. An O(mm(n+m) algorithm for computing the measure is presentd, where n and m are the number of veritces for a model and an unknown object, respectively. Match results from aprtial segments are combined based on mutual compatibility, then are verified using distance transformation and translation vector to produce the final recognition. The proposed algorithm is invariant under translation and rotation of objects, which has been shown by experimental results.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.1-19
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• 2000

With rapid economic development, the emphasis of the public health movement in Korea has shifted towards addressing the burden of chronic disease. With this shift in direction comes a greater focus on health behaviour and the need for planning models to assist in lifestyle modification programs. The Health Belief Model (HBM), which originated in the US, has generated more research than any other theoretical approach to describe and predict the health behaviour of individuals. In recent years it has been applied in many different cultures and modifications have been suggested to accommodate different cultures. Given the centrality of language and culture, any attempts to use models of health behaviour developed in a different culture, must be studied and tested for local applicability. The paper reviews the applicability and suitability of the HBM in Korea, in the context of the Korean language and culture. The HBM has been used in Korea for almost three decades. The predictability of the HBM has varied in Korean studies as in other cultures. Overall, this literature review indicates that the HBM has been found applicable in predicting health and illness behaviours by Korean people. However if the HBM is used in a Korean context, the acquisition of health knowledge is an important consideration. Most new knowledge in the health sciences is originally published in English and less frequently in another foreign language. Most health knowledge in Korea is acquired through the media or from health professionals and its acquisition often involves translation from the original. The selection of articles for translation and the accuracy of translation into language acceptable in the Korean culture become important determinants of health knowledge. As such translation becomes an important part of the context of the HBM. In this paper modifications to the HBM are suggested to accommodate the issues of language and knowledge in Korea.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.535-543
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• 2002

In this paper, we propose a new gaze detection method using 2-D facial images captured by a camera on top of the monitor. We consider only the facial rotation and translation and not the eyes' movements. The proposed method computes the gaze point caused by the facial rotation and the amount of the facial translation respectively, and by combining these two the final gaze point on a monitor screen can be obtained. We detected the gaze point caused by the facial rotation by using a neural network(a multi-layered perceptron) whose inputs are the 2-D geometric changes of the facial features' points and estimated the amount of the facial translation by image processing algorithms in real time. Experimental results show that the gaze point detection accuracy between the computed positions and the real ones is about 2.11 inches in RMS error when the distance between the user and a 19-inch monitor is about 50~70cm. The processing time is about 0.7 second with a Pentium PC(233MHz) and 320${\times}$240 pixel-size images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2798-2805
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• 1997

The paper studies the Quality of Service(QoS) concept in Broadband Integrated Services Digital Network (B-ISDN). Guaranteeing the QoS requirements indistributed multimedia systems and networks is fundamentally an end-to-end issus, that is, from application to application. An important issue in the QoS translation between the application-level QoS and network-level QoS is that the translation depends not only on the translation between system resources and network resources, but also on the translation between thelayered protocol and the access procedures. In this paepr, we propose a methodology for translating the AAL(ATM Adaptation Layer) QoS parameters into the ATM layer QoS parameters in end-systems. The QoS parameters in the ATM layer and AAL are defined, and we concentrate on the translation from the AAL to the ATM layer, because the AAL must be designed to be service dependent and specific. As an example, we concentrate on the constant bit rate(CBR) guaranteed real-time service using AAL1 protocol.

• Cross-Cultural Studies
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• v.45
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• pp.55-83
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• 2016

To provide a set of data with which instructors may boost the sagging demand for Anglo-American poetry classes, this thesis classifies the kinds of difficulties the students face in reading English poems. Asses to the classification is an analysis on the causes of the difficulties at different levels of the reading process, from the linguistic to the cultural. Arnoldian insight argues that poetry is the best of all forms of writing. Without an ample exposure to poetry, average English majors would barely sharpen the skills that they use to deal with other kinds of writing. To help ease the continuing need for a workable teaching model in English poetry reading classes, this thesis suggests focusing on the kinds of wrong translations produced by the students. According to the theory of cultural translation, any translation, even the wrong kind, is already a product of a very complicated process of interpretation that involves many cultural factors. With the analysis of these factors discovered in Korean college English reading classes, this thesis tries to explain the mechanisms through which wrong translations are produced, since these inevitably lead to wrong interpretations of given poetic texts.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.206-212
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• 2021

Society is developing more and more, and communication methods are developing in many ways. However, developed communication is a way for the non-disabled and has no effect on the deaf. Therefore, in this paper, a CNN-based sign language translation program is designed and implemented to help deaf people communicate. Sign language translation programs translate sign language images entered through WebCam according to meaning based on data. The sign language translation program uses 24,000 pieces of Korean vowel data produced directly and conducts U-Net segmentation to train effective classification models. In the implemented sign language translation program, 'ㅋ' showed the best performance among all sign language data with 97% accuracy and 99% F1-Score, while 'ㅣ' showed the highest performance among vowel data with 94% accuracy and 95.5% F1-Score.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.140-147
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• 2024

In the Republic of Korea, people with hearing impairments are the second-largest demographic within the registered disability community, following those with physical disabilities. Despite this demographic significance, research on sign language translation technology is limited due to several reasons including the limited market size and the lack of adequately annotated datasets. Despite the difficulties, a few researchers continue to improve the performacne of sign language translation technologies by employing the recent advance of deep learning, for example, the transformer architecture, as the transformer-based models have demonstrated noteworthy performance in tasks such as action recognition and video classification. This study focuses on enhancing the recognition performance of sign language translation by combining transformers with 3D-CNN. Through experimental evaluations using the PHOENIX-Wether-2014T dataset [1], we show that the proposed model exhibits comparable performance to existing models in terms of Floating Point Operations Per Second (FLOPs).

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.4
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• pp.87-94
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• 1994

The aim of the work descrihed in this paper is to study a characteristics of an unsaturated soil for the different matric suctions. To this end, a series of suction controlled isotropic and triaxial compression tests is conducted on silty sands. Matric suction is controlled by the axis translation technique using high air entry ceramic disk. Total volume change, air and water volume changes are measured by the device made for the experiment. The specimens are compacted using a half of Proctor compaction energy and with the water contents of 5% drier than the optimum moisture contents. Isotropic compression and triaxial compression tests are conducted on the specimen at each equilibrium state of matric suction. From test results, volume changes and deviator stresses are analyzed at each state and their relationships are formulated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.255-262
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• 1998

This paper presents a translation, rotation and scale invariant methodology for the recognition of closed planar shape images using the bispectrum of a contour sequence and the learning vector quantization(LVQ) neural classifier. The contour sequences obtained from the closed planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The higher order spectra based on third order cumulants is applied to tihs contour sample to extract fifteen bispectral feature vectors for each planar image. There feature vector, which are invariant to shape translation, rotation and scale transformation, can be used to represent two0dimensional planar images and are fed into a neural network classifier. The LVQ architecture is chosen as a neural classifier because the network is easy and fast to train, the structure is relatively simple. The experimental recognition processes with eight different hapes of aircraft images are presented to illustrate the high performance of this proposed method even the target images are significantly corrupted by noise.