• Archives of design research
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• v.13 no.4
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• pp.67-76
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• 2000

Websites support various user activities in a wide range of contents domain and so they require different approach to extract principal design problems. In the point of media perspective on websites, this paper figures out the relationship between designer, user and website and discusses design factors of usability. It aims for the basic framework for interface design. In the media perspective website is an information entity mediating user and designer. Information entity is composed of various design factors relating to user, designer, website and others. It intends that user and information entity are accommodative to each other and have common conceptual model. To do so it is necessary for achieving usability objectives such as effectiveness, efficiency and satisfaction based on the understanding user goal, cognitive and affective characteristics. In the point of usability we examine design factors and features that are appropriate for users cognitive and affective function according to information entity model that constitutes contents, organization and representation level.

• Journal of Information Management
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• v.41 no.2
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• pp.31-46
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• 2010

Now named-entity recognition(NER) as a part of information extraction has been used in the fields of information retrieval as well as question-answering systems. Unlike words, named-entities(NEs) are generated and changed steadily in documents on the Web, newspapers, and so on. The NE generation causes an unknown word problem and makes many application systems with NER difficult. In order to alleviate this problem, this paper proposes a new feature generation method for machine learning-based NER. In general features in machine learning-based NER are related with words, but entities in named-entity dictionaries are related to phrases. So the entities are not able to be directly used as features of the NER systems. This paper proposes an encoding scheme as a feature generation method which converts phrase entities into features of word units. Futhermore, due to this scheme, entities with semantic information in WordNet can be converted into features of the NER systems. Through our experiments we have shown that the performance is increased by about 6% of F1 score and the errors is reduced by about 38%.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.575-588
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• 2012

Exploiting unlabeled text data with a relatively small labeled corpus has been an active and challenging research topic in text mining, due to the recent growth of the amount of biomedical literature. Biomedical named-entity recognition is an essential prerequisite task before effective text mining of biomedical literature can begin. This paper proposes an Active Co-Training (ACT) algorithm for biomedical named-entity recognition. ACT is a semi-supervised learning method in which two classifiers based on two different feature sets iteratively learn from informative examples that have been queried from the unlabeled data. We design a new classification problem to measure the informativeness of an example in unlabeled data. In this classification problem, the examples are classified based on a joint view of a feature set to be informative/non-informative to both classifiers. To form the training data for the classification problem, we adopt a query-by-committee method. Therefore, in the ACT, both classifiers are considered to be one committee, which is used on the labeled data to give the informativeness label to each example. The ACT method outperforms the traditional co-training algorithm in terms of f-measure as well as the number of training iterations performed to build a good classification model. The proposed method tends to efficiently exploit a large amount of unlabeled data by selecting a small number of examples having not only useful information but also a comprehensive pattern.

• The Korean Journal of Archival Studies
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• no.68
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• pp.107-150
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• 2021

Representation of an entity starts with recognition of its existence, and recording is mutually circular in that it acts as a means to enable the recognition of the existence. No record is left on an unrecognized entity, record is distorted if any, and the distorted reproduction represents the entity, reinforcing its invisibility. Spivak describes those who cannot speak on their own and cannot be represented as subaltern. This paper examines public record, the media and research records of female restaurant workers, identifies the subaltern characteristics and limitations of their records, and suggests the points to be considered and specific roles required for recording the subalterns. If it is possible to increase the possibility of representation by completely recording a person as an entity that contains the times and society, the accountability of the record to provide an account will extend beyond institutions to the times and society, and individuals and community will be established as political subjects.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.2
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• pp.75-81
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• 2019

In order to research the pathological entity of Jueyin disease in ${\ll}Shanghanlun{\gg}$, some sharing concept of three-yin-three-yang used in ${\ll}Neijing{\gg}$ and ${\ll}Shanghanlun{\gg}$ were investigated first, and then the meaning of jueyin and jueyin disease were analyzed. In cold damage disease, time-space factor is important because the pathological change is rapid and the symptoms along path are similar, therefore three-yin-three-yang having complex meaning of time and space can be used as an appropriate pathological concept. So to speak, it is able to be interpreted as various modes like variations of yin-yang, qi-blood, change of pulse condition, theories of opening, closing, pivot or exuberance and debilitation of form and qi manifested in the six districts of the human body following disease process. Jueyin is between front taiyin and rear shaoyin, and it's attribution is inherent in qi stagnation and yin exuberance in relative to the location of flank and liver. Putting together above descriptions, pathological entity of jueyin disease is that the symptoms mingled with cold and stagnant heat competing each other when a subject having qi stagnation in flank with cold in extremities and lower abdomen in particular is seized with cold influenza.

• Carbon letters
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• v.15 no.1
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• pp.25-31
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• 2014

A microstructure analysis is carried out to optimize the process parameters of a randomly oriented discrete length hybrid carbon fiber reinforced carbon matrix composite. The composite is fabricated by moulding of a slurry into a preform, followed by hot-pressing and carbonization. Heating rates of 0.1, 0.2, 0.3, 0.5, 1, and $3.3^{\circ}C/min$ and pressures of 5, 10, 15, and 20 MPa are applied during hot-pressing. Matrix precursor to reinforcement weight ratios of 70:30, 50:50, and 30:70 are also considered. A microstructure analysis of the carbon/carbon compacts is performed for each variant. Higher heating rates give bloated compacts whereas low heating rates give bloating-free, fine microstructure compacts. The compacts fabricated at higher pressure have displayed side oozing of molten pitch and discrete length carbon fibers. The microstructure of the compacts fabricated at low pressure shows a lack of densification. The compacts with low matrix precursor to reinforcement weight ratios have insufficient bonding agent to bind the reinforcement whereas the higher matrix precursor to reinforcement weight ratio results in a plaster-like structure. Based on the microstructure analysis, a heating rate of $0.2^{\circ}C/min$, pressure of 15 MPa, and a matrix precursor to reinforcement ratio of 50:50 are found to be optimum w.r.t attaining bloating-free densification and processing time.

• Journal of Information Management
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• v.40 no.4
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• pp.1-22
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• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.

• Journal of Climate Change Research
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• v.8 no.1
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• pp.1-10
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• 2017

Over the past centuries, industrialization in developed and developing countries has had a negative impact on global warming, releasing $CO_2$ emissions into the Earth's atmosphere. In recent years, the transportation sector, which emits one-third of total $CO_2$ emissions in the United States, has adapted by implementing a climate change action plan to reduce $CO_2$ emissions. Having an environmental policy might be an essential factor in mitigating the man-made global warming threats to protect public health and the coexistent needs of current and future generations; however, to my best knowledge, no research has been conducted in such a context with appropriate statistical validation process to evaluate the effects of climate change policy on $CO_2$ emission reduction in recent years in the U.S. transportation. The empirical findings using an entity fixed-effects model with valid statistical tests show the positive effects of climate change policy on $CO_2$ emission reduction in a state. With all the 49 states joining the climate change action plans, the U.S. transportation sector is expected to reduce its $CO_2$ emissions by 20.2 MMT per year, and for the next 10 years, the cumulated $CO_2$ emission reduction is projected to reach 202.3 MMT, which is almost equivalent to the $CO_2$ emissions from the transportation sector produced in 2012 by California, the largest $CO_2$ emission state in the nation.

• Journal of Gastric Cancer
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• v.19 no.2
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• pp.148-156
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• 2019

Esophagogastric junction (EGJ) cancer is a solid tumor entity with rapidly increasing incidence in the Western countries. Given the high proportion of advanced cancers in the West, treatment strategies routinely employed include surgery and chemotherapy perioperatively, and chemoradiation in neoadjuvant settings. Neoadjuvant chemoradiation and perioperative chemotherapy are mostly performed in esophageal cancer that extends to the EGJ and gastric as well as EGJ cancers, respectively. Recent trials have tried to combine both strategies in a perioperative context, which might have beneficial outcomes, especially in patients with EGJ cancer. However, it is difficult to recruit patients for trials, exclusively for EGJ cancers; therefore, the results have to be carefully reviewed before establishing a standard protocol. Trastuzumab was the first drug for targeted therapy that was positively evaluated for this tumor entity, and there are several ongoing trials investigating more targeted drugs in order to customize effective therapies based on tissue characteristics. The current study reviews the multimodal treatment concept for EGJ cancers in the West and summarizes the latest reports.

• Asia pacific journal of information systems
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• v.28 no.2
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• pp.75-92
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• 2018

Conceptual modeling is well suited as a subject that constitutes the "core" of the Information Systems (IS) discipline and has grown in response to IS development. Several modeling grammars and methods have been studied extensively in the IS discipline. Previous studies, however, present deficiencies in research methods and even put forward contradictory results about the ternary relationship in conceptual modeling. For instance, some studies contend that the semantics of a binary relationship are better for novices, but others argue that a ternary relationship is better than three binary relationships when the association among three entity types clearly exists. The objective of this research is to acquire complete and accurate understanding of the ternary relationship, specifically to understand practitioners' modeling performance when utilizing either a ternary or binary relationship. To the best of our knowledge, no previous work clearly compares real-world modeler performance differences between binary and ternary representations. By investigating practitioners' understanding of ternary relationship and identifying practitioners' cognition, this research can broaden the perspective on conceptual modeling.