• Annual Conference on Human and Language Technology
• /
• 2023.10a
• /
• pp.415-418
• /
• 2023

테이블 데이터는 일반적으로 헤더와 데이터로 구성되며, 헤더는 데이터의 구조와 내용을 이해하는데 중요한 역할을 한다. 하지만 웹 스크래핑 등을 통해 얻은 데이터와 같이 다양한 상황에서 헤더 정보가 누락될 수 있다. 수동으로 헤더를 생성하는 것은 시간이 많이 걸리고 비효율적이기 때문에, 본 논문에서는 자동으로 헤더를 생성하는 태스크를 정의하고 이를 해결하기 위한 모델을 제안한다. 이 모델은 BART를 기반으로 각 열을 구성하는 텍스트와 열 간의 관계를 분석하여 헤더 텍스트를 생성한다. 이 과정을 통해 테이블 데이터의 구성요소 간의 관계에 대해 이해하고, 테이블 데이터의 헤더를 생성하여 다양한 애플리케이션에서의 활용할 수 있다. 실험을 통해 그 성능을 평가한 결과, 테이블 구조 정보를 종합적으로 활용하는 것이 더 높은 성능을 보임을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.60.2-60
• /
• 2001

In this paper, manufacturing system and Internet are combined and NC milling machine engraves image and text on nameplate. Image and text are input through Internet. And NC tool path is obtained by thinning algorithm and NC part program is generated. Thinning algorithm detects center lines from image and text by using connectivity and tool path is obtained along the center line. Actually experiments are performed and thinning algorithm and G-code generation module are verified.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.13 no.5
• /
• pp.124-130
• /
• 2017

Character encoding is the method used to represent characters or symbols on a computer, and there are many encoding detection software tools. For the widely used encoding detection software"uchardet", the accuracy of encoding detection of unmodified normal text document is 91.39%, but the accuracy of language detection is only 32.09%. Also, if a text document is encrypted by substitution, the accuracy of encoding detection is 3.55% and the accuracy of language detection is 0.06%. Therefore, in this paper, we propose encoding and language detection of text document using the deep learning algorithm called LSTM(Long Short-Term Memory). The results of LSTM are better than encoding detection software"uchardet". The accuracy of encoding detection of normal text document using the LSTM is 99.89% and the accuracy of language detection is 99.92%. Also, if a text document is encrypted by substitution, the accuracy of encoding detection is 99.26%, the accuracy of language detection is 99.77%.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2000.10a
• /
• pp.121-127
• /
• 2000

No Abstract.See Full-text

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.5
• /
• pp.80-86
• /
• 2010

This paper presents automated music story video generation technique as one of entertainment features that is equipped in multimedia system of the vehicle. The automated music story video generation is a system that automatically creates stories to accompany musics with photos stored in user's mobile phone by connecting user's mobile phone with multimedia systems in vehicles. Users watch the generated music story video at the same time. while they hear the music according to mood. The performance of the automated music story video generation is measured by accuracies of music classification, photo classification, and text-keyword extraction, and results of user's MOS-test.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.3
• /
• pp.847-852
• /
• 2010

Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.6
• /
• pp.1778-1799
• /
• 2022

Automatic text summarization is a procedure that packs enormous content into a more limited book that incorporates significant data. Malayalam is one of the toughest languages utilized in certain areas of India, most normally in Kerala and in Lakshadweep. Natural language processing in the Malayalam language is relatively low due to the complexity of the language as well as the scarcity of available resources. In this paper, a way is proposed to deal with the text summarization process in Malayalam documents by training a model based on the Support Vector Machine classification algorithm. Different features of the text are taken into account for training the machine so that the system can output the most important data from the input text. The classifier can classify the most important, important, average, and least significant sentences into separate classes and based on this, the machine will be able to create a summary of the input document. The user can select a compression ratio so that the system will output that much fraction of the summary. The model performance is measured by using different genres of Malayalam documents as well as documents from the same domain. The model is evaluated by considering content evaluation measures precision, recall, F score, and relative utility. Obtained precision and recall value shows that the model is trustable and found to be more relevant compared to the other summarizers.

• The KIPS Transactions:PartB
• /
• v.10B no.5
• /
• pp.485-490
• /
• 2003

In this paper, we propose the possibility of introducing chaotic sequences into digital watermarking systems as potential substitutes to commonly used pseudo noise sequences. Chaotic sequences have several good properties including the availability of a great number of them, the ease of their generation, as well as their sensitive dependence on their initial conditions. And the quantization does not destroy the good property. So this paper proposes a method that transforms Hangul text to chaotic sequence. And we presents how the Hangul text is expressed by an implied data and the implied data is regenerated into the original text. In this paper, we use this implied Hangul text for watermarking.

• Plant Biotechnology Reports
• /
• v.2 no.2
• /
• pp.113-122
• /
• 2008

Nitric oxide (NO) affects the growth and development of plants and also affects plant responses to various stresses. Because NO induces root differentiation, we examined whether or not it is involved in increased ROS generation. Treatments with sodium nitroprusside (SNP), an NO donor, 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (PTIO), a specific NO scavenger, and $N{\omega}-nitro-{\text\tiny{L}}-arginine$ methyl ester hydrochloride (${\text\tiny{L}}-NAME$), an NO synthase (NOS) inhibitor, revealed that NO is involved in the adventitious root growth of mountain ginseng. Supply of an NO donor, SNP, activates NADPH oxidase activity, resulting in increased generation of $O_2{^{{\cdot}-}}$, which subsequently induces growth of adventitious roots. Moreover, treatment with diphenyliodonium chloride (DPI), an NADPH oxidase inhibitor, individually or with SNP, inhibited root growth, NADPH oxidase activity, and $O_2{^{{\cdot}-}}$ anion generation. Supply of the NO donor, SNP, did not induce any notable isoforms of enzymes; it did, however, increase the activity of pre-existing bands of NADPH oxidase, superoxide dismutase, catalase, peroxidase, ascorbate peroxidase, and glutathione reductase. Enhanced activity of antioxidant enzymes induced by SNP supply seems to be responsible for a low level of $H_2O_2$ in the adventitious roots of mountain ginseng. It was therefore concluded that NO-induced generation of $O_2{^{{\cdot}-}}$ by NADPH oxidase seems to have a role in adventitious root growth of mountain ginseng. The possible mechanism of NO involvement in $O_2{^{{\cdot}-}}$ generation through NADPH oxidase and subsequent root growth is discussed.

• Journal of Information Technology Services
• /
• v.22 no.3
• /
• pp.101-118
• /
• 2023

The 'MZ generation' is accustomed to expressing their thoughts and opinions online. As a result, the role of social media in understanding the opinions and public sentiment of the MZ generation has become increasingly important. In particular, the role of social media in understanding the opinions of young people in political contexts such as policies and elections is becoming more significant. Traditionally, in such political situations, various institutions conduct opinion surveys to grasp the opinions of the people. However, existing opinion surveys have many errors and limitations in understanding the specific opinions of the entire population since they are conducted on arbitrary individuals through survey techniques. Online communities are representative social media that share the opinions of the public on specific issues such as politics, economics, and culture. Therefore, online communities are widely used as a means to supplement the limitations of traditional opinion polls. In particular, the MZ generation is familiar with online platforms, and their political support has significant influence on election results and policy decisions. With this regard, this study analyzed the relationship between the sentiment reflected in online community text data by age group on major candidates and public opinion survey support rates during the Korean presidential election for those in their 20s. The analysis showed that negative sentiments reflected in online communities by the MZ generation have a negative correlation with public opinion survey support rates. This study contributes to theory and practice by revealing a significant association between social media and public opinion polls.