• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.281-286
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• 2023

Diagnosing reading disorders involves complex procedures to evaluate complex cognitive processes. For an accurate diagnosis, a series of tests and evaluations by human experts are required. In this study, we propose a quantitative tool to diagnose reading disorders based on natural reading behaviors using minimal human input. The eye movements of the third- and fourth-grade students were recorded while they read a text at their own pace. Seven machine learning models were used to evaluate the gaze patterns of the words in the presented text and classify the students as normal or having a reading disorder. The accuracy of the machine learning-based diagnosis was measured using the diagnosis by human experts as the ground truth. The highest accuracy of 0.8 was achieved by the support vector machine and random forest classifiers. This result demonstrated that machine learning-based automated diagnosis could substitute for the traditional diagnosis of reading disorders and enable large-scale screening for students at an early age.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.113-130
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• 2004

Most multimedia data contain text to emphasize the meaning of the data, to present additional explanations about the situation, or to translate different languages. But, the left makes it difficult to reuse the images, and distorts not only the original images but also their meanings. Accordingly, this paper proposes a support vector machines (SVMs) and spatiotemporal restoration-based approach for automatic text detection and removal in video sequences. Given two consecutive frames, first, text regions in the current frame are detected by an SVM-based texture classifier Second, two stages are performed for the restoration of the regions occluded by the detected text regions: temporal restoration in consecutive frames and spatial restoration in the current frame. Utilizing text motion and background difference, an input video sequence is classified and a different temporal restoration scheme is applied to the sequence. Such a combination of temporal restoration and spatial restoration shows great potential for automatic detection and removal of objects of interest in various kinds of video sequences, and is applicable to many applications such as translation of captions and replacement of indirect advertisements in videos.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Journal of Information Management
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• v.35 no.4
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• pp.1-16
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• 2004

In this paper, we outline the user interface problems that the text messaging users face to provide empirical basis for developing better improved mobile text messaging system. Our initial hypothesis was that the majority of the problems that the text messaging users face, namely, 1) difficulty in correctly understanding the intent of the incoming messages and 2) problem with frequently mis-addressing the recipient of the outgoing messages, can be accounted for by the poor usability of the text messaging user interface. Our analysis is based on the text message-based communication diaries, which were recorded for one week by each and every one of 75 college students, and survey taken from the same subjects. The data was collected in 2004. The students listed various difficulties including the limited message length, obscure input method, lack of mean to express emotional content, lack of receipt confirmation, lack of auto save feature when preparing messages to send, and lack of means to permanently save messages. Some of these problems were also identified in the previous studies. However, we were able to gather additional problems that the users face and also elicit potential solutions to remedy the problems. From these findings and analysis, we attempted to provide ways to improve the text messaging user interface.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.76-90
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• 1994

In this paper, an efficient algorithm is proposed which recognizes the mixed document consisting of the printed Korean/alphanumeric texts and graphic images. In the preprocessing step an input document is aligned if necessary by rotating it. We obtain the rotation angle using the Hough transform and align the input document horizontally. Then we separate graphic image parts from text parts by considering chain codes of connected components. We further separate each character using vertical and horizontal projections. In the recognition step Korean and alphanumeric characters are classified and each of them is recognized hierarchically using several features. In summary an efficient recognition algorithm for mixed documents is proposed and its performance is demonstrated via computer simulations.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.99-104
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• 2013

With diversity of mobile services (e.g., messenger, and social network service) on smartphone, the demand of text input using a soft keyboard is increasing. However, studies on subjective and physiological responses of users for various touch locations are lacking. The present study investigated the ergonomic effects according to touch locations of a soft keyboard on smartphone. The experiment of the present study measured perceived discomfort using Borg's CR-10 scale and electromyography (EMG) on forearm (abductor pollicis longus, and extensor digitorum communis) and thumb (abductor pollicis brevis, and first dorsal interossei) muscles. Perceived discomfort was significantly varied from 0.7 (extremely weak discomfort) to 2.5 (weak discomfort) depending on touch locations. %MVC according to touch locations was only significant at abductor pollicis brevis which varied from 10% to 23%. The experimental results of the present study can be utilized in the ergonomic design of a soft keyboard.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.153-158
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• 2015

Nowadays, automatic keyphrase extraction is considered to be an important task. Most of the previous studies focused only on selecting keyphrases within the body of input documents. These studies overlooked latent keyphrases that did not appear in documents. In addition, a small number of studies on latent keyphrase extraction methods had some structural limitations. Although latent keyphrases do not appear in documents, they can still undertake an important role in text mining because they link meaningful concepts or contents of documents and can be utilized in short articles such as social network service, which rarely have explicit keyphrases. In this paper, we propose a new approach that selects qualified latent keyphrases from input documents and overcomes some structural limitations by using deep belief networks in a supervised manner. The main idea of this approach is to capture the intrinsic representations of documents and extract eligible latent keyphrases by using them. Our experimental results showed that latent keyphrases were successfully extracted using our proposed method.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.165-168
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• 2000

A hardware architecture to implement the SEED block cipher algorithm into one chip is described. Each functional unit is designed with VHDL hardware description language and synthesis tools. The designed hardware receives a 128-bit block of plain text input and a 128-bit key, and generates a 128-bit cipher block after 16-round operations after 8 clocks. The encryption time is within 20 nsec.

• Korean Management Science Review
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• v.12 no.1
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• pp.125-138
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• 1995

This paper is to develop an integrated environment software on MS-DOS for linear programming. For the purpose, First, the linear programming integrated environment software satisfying both the educational purpose and the professional purpose was designed and constructed on MS-DOS. Second, the text editor with big capacity was developed. The arithmetic form analyser was also developed and connected to the test editor so that users can input data in the arithmetic form. As a result, users can learn and perform linear programming in the linear programming integrated environment software.

• ETRI Journal
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• v.28 no.2
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• pp.250-252
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• 2006

In this letter, a discrete state, discrete time chaotic pseudo random number generator (CPRNG) is presented for stream ciphering of text, audio, or image data. The CPRNG is treated as a finite state machine, and its state is modulated according to the input bit sequence of the signal to be encrypted. The modulated state sequence obtained can be transmitted as a spread spectrum or encrypted data.