• Journal of Distribution Science
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• v.12 no.6
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• pp.15-20
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• 2014

Purpose - In general, researchers try to abide by the code of research ethics, but many of them are not fully aware of plagiarism, unintentionally committing the research misconduct when they write a research paper. This research aims to introduce researchers a clear and easy guideline at a conference, which helps researchers avoid accidental plagiarism by addressing the issue. This research is expected to contribute building a climate and encouraging creative research among scholars. Research design, data, methodology & Results - Plagiarism is considered a sort of research misconduct along with fabrication and falsification. It is defined as an improper usage of another author's ideas, language, process, or results without giving appropriate credit. Plagiarism has nothing to do with examining the truth or accessing value of research data, process, or results. Plagiarism is determined based on whether a research corresponds to widely-used research ethics, containing proper citations. Within academia, plagiarism goes beyond the legal boundary, encompassing any kind of intentional wrongful appropriation of a research, which was created by another researchers. In summary, the definition of plagiarism is to steal other people's creative idea, research model, hypotheses, methods, definition, variables, images, tables and graphs, and use them without reasonable attribution to their true sources. There are various types of plagiarism. Some people assort plagiarism into idea plagiarism, text plagiarism, mosaic plagiarism, and idea distortion. Others view that plagiarism includes uncredited usage of another person's work without appropriate citations, self-plagiarism (using a part of a researcher's own previous research without proper citations), duplicate publication (publishing a researcher's own previous work with a different title), unethical citation (using quoted parts of another person's research without proper citations as if the parts are being cited by the current author). When an author wants to cite a part that was previously drawn from another source the author is supposed to reveal that the part is re-cited. If it is hard to state all the sources the author is allowed to mention the original source only. Today, various disciplines are developing their own measures to address these plagiarism issues, especially duplicate publications, by requiring researchers to clearly reveal true sources when they refer to any other research. Conclusions - Research misconducts including plagiarism have broad and unclear boundaries which allow ambiguous definitions and diverse interpretations. It seems difficult for researchers to have clear understandings of ways to avoid plagiarism and how to cite other's works properly. However, if guidelines are developed to detect and avoid plagiarism considering characteristics of each discipline (For example, social science and natural sciences might be able to have different standards on plagiarism.) and shared among researchers they will likely have a consensus and understanding regarding the issue. Particularly, since duplicate publications has frequently appeared more than plagiarism, academic institutions will need to provide pre-warning and screening in evaluation processes in order to reduce mistakes of researchers and to prevent duplicate publications. What is critical for researchers is to clearly reveal the true sources based on the common citation rules and to only borrow necessary amounts of others' research.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.478-485
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• 2013

"GukMinSoHakDokBon", published in 1895, is the first national textbook designated by the Education Institute. Ten of the 41 chapters consist of scientific contents. In this thesis, some the contents are reviewed in detail and studied to see what significance it has in view of science education. The scientific contents described in "GukMinSoHakDokBon" include Plants Change, Clock, Camels, Wind, Hive, Respiration, Crocodiles, Nature of Animals, and Chemical Elements. For that kind of diversity, it was told that "GukMinSoHakDokBon" was not considered for normal students, and there were many ambiguities due to in sufficient explanations. Some of the contents were even technically wrong. So it has been noted that the scientific contents of "GukMinSoHakDokBon" have more significance in providing new information at that time but not in understanding newly-organized scientific knowledge. However, it is obvious that the early science education in Korea is composed of the methods of reading "GukMinSoHakDokBon". This is a common figure, which can be found in "Willson's Reader", the elementary reading textbook in the U.S. in the 1860's or "小學讀本" by the Ministry of Education in Japan. One thing remarkable is "GukMinSoHakDokBon" induced students' interests through the use of storytelling method for introducing some unfamiliar scientific knowledge. There is no doubt that "GukMinSoHakDokBon" has a very positive role in increasing students interest and intelligence. These advantages are being actively applied in the present model of storytelling education these days. Therefore, "GukMinSoHakDokBon" can be regarded as both a language textbook and an early figure in science education, and it can be also considered that "GukMinSoHakDokBon" has a significance not only in approaching scientific substances theoretically but in using storytelling methods to deliver unfamiliar and strange knowledges to students.

• Cartoon and Animation Studies
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• s.36
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• pp.375-391
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• 2014

Animation movie is a non-photorealistic animated art that consists of formative language forming a frame based on a story and cuts describing frames that form the cuts. Therefore, in expressing an image, artistic expression methods and devices for a formative space are should be provided in a frame while cuts have the images between frames faithfully. Short animation movie is produced by various image experiments with unique image expressions rather than narration for expressing subjective discourse of a writer. Therefore, image style that forms unique images and various image directions are important factors. This study compared the experimental image directions of and , both of which showed a production method of film manipulation. First, while uses pixilation that produces images obtained from live images through painting and many optical disclosure process on a cell mat, was made with diverse collage techniques such as tearing, cutting, pasting, and folding hundreds of scenes from action movies. Second, expresses non-causal relationship of characters by their repetitive behaviors and circulatory image structure through a fixed camera angle, resisting typical scene transition. On the other hand, has an advancing structure that progresses antagonistic relationship of characters through diverse camera angles and scene transition of unique images. Third, in terms of editing, uses a long-take short cut technique in which the whole image consists of one short cut, though it seems to be many scenes with the appearance of various characters. On the other hand, maximizes visual fun and commitment by image reconstruction with hundreds of various short cuts. That is, both works have common features of an experimental work that shows expansion of animated image expressions through film manipulation that is different form general animation productions. On top of that, delivers routine life of diverse human beings without clear narration through image of conceptualized spaces. expresses it in a new image space through image reconstruction with collage technique and speedy progress, setting a binary opposition structure.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Cross-Cultural Studies
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• v.41
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• pp.351-379
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• 2015

In the Andes regions of Latin America continents, groups of diverse native tribes are intensively distributed.Among these tribes, the Aymara compose the most representative group of natives along with the Quechua. Especially, the Aymara who are concentrated on the border areas of Peru and Bolivia centered on Lake Titicaca have pursued common identity forming the same cultural area although they belong to different nations. In the meantime, the Aymara have maintained a sense of fellowship while emphasizing historicity and specialty, which are differentiated with groups of other natives based on a language constituting identity of the tribe. However, recently, focused on Puno State as the center of the border areas of both countries, the tribe's conflicts come to the surface. After being divided by the artificial boundary line, which was formed in the course of building modern countries after the independence, natives of Latin America started to emphasize differences simultaneously with cultural similarity in the frame of cooperation and competition. Together with the historical contexts, lately, focused on the border areas of Peru and Bolivia, as the same tribe came to be bound by the frameworks of different nations respectively, a new tribal conflict is being developed. Though the Aymara unite emphasizing cultural and historical specialty and recognizing them as one tribe, when they conflict with each other over inner interest, a tendency to form the identity of differentiation and distinction appeared even in the inside of the tribe. Usually, disorder between tribes seems to be originated from intertribal strife, which coexists in one region. In case of the Aymara of Peru and Bolivia, centered on Puno State where both countries maintain the border, an aspect that the fellowship of the tribe, which was established through old history changes into conflict structures by realistic conditions comes out. In understanding this point, this study analyzed the historical origin of the conflict of the Aymara and the deepened cause of the tribal disorder.

• 한국노년학
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• v.36 no.4
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• pp.1037-1058
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• 2016

This study aims to investigate the female caregivers'experiences of aggression by nursing home residents, and to identify the policy strategies for violence prevention referred by the female caregivers. A total of 121 female caregivers with more than 6 months of working experiences had participated in this study. Of these, 56.2% had experienced verbal aggression, 51.2% physical aggression, and 27.3% sexual aggression, which reveals that client violence toward caregivers in nursing homes was at an alarming level. Although, physical and verbal violences were mostly caused unintentionally, about a half of the sexual aggression were caused deliberately. Aggression occurred the most when caregivers were providing the following services: changing the diapers or clothes, giving a bath, and serving meals. It was found that 'hitting' was the most common form of physical aggression and it was 'swearing' and 'touching or physical contacting' in the case of verbal and sexual aggression, respectively. Though there was a difference depending on the type of aggression, the most frequent reactions against client violence were to start a conversation or calm down the nursing home residents, and to leave the scene or ignore the incident. This means that the caregivers are coping very passively through resolving the aggressions by themselves, or overlooking the situation. The most frequently recommended strategy to prevent resident aggression was to provide educational programs on violence prevention to nursing home residents and caregivers(42.7%). Compared to the previous studies, this study indicates some differentiated strategies to prevent violence in nursing homes, which include hiring male caregivers, assuring directors to pay closer attention toward caregivers, using refined language between caregivers and residents, and keeping caregivers to wear appropriate clothes. Based on the study results, some policy recommendations on the prevention of client violence in nursing homes were suggested.

• Journal of Korean Classical Literature and Education
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• no.39
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• pp.221-246
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• 2018

In this text, the author examines the aspects and characteristics of the three forms that were created and enjoyed when the upper-class nobles of Japan "combined(混淆)" waka(和歌) and Chinese poetry(漢詩) between the 10th and 17th centuries. The three forms are the "Collection of Japanese and Chinese poems for singing"(和漢朗詠), "A collection of Japanese and Chinese poems" (詩歌合), and the "Renku renga"(聯句連歌). "Collection of Japanese and Chinese poems for singing" appeared in the 10th century, "A collection of Japanese and Chinese poems" appeared in the 12th century, "Renku renga" appeared in the 14th century, and all three continued to influence the history of Japanese literature after that time. As the combination of literary Japanese and Chinese progressed, the gap between waka and Chinese poetry decreased until they finally combined to create a single work. That is, waka and Chinese poetry converged in one place in multiple ways: as a work that was appropriate to be recited("Collection of Japanese and Chinese poems for singing"), facing each other work against work in a competition("A collection of Japanese and Chinese poems"), and, in the end, they reached the point where they were interchangeable as lines making up long poems(長詩)("Renku renga"). The combination of literary Japanese and Chinese can be said to be the Japanese version of the common movement in East Asian literary history during the Middle Ages to make songs from one's own language flawless in Chinese poetry. Meanwhile, by examining the status changes that appeared as Chinese poetry paralleled, fought with, replaced, and combined with waka, we can find clues to explain the attitudes of the Japanese people on Chinese poetry during the period when the three forms existed, as well as the characteristics of Japanese Chinese poetry that appeared in response to that. The preferences not of "myself" but of the "audience," content and expressions that revere the period rather than the inner self of the poet, and the fact that it is a means for enjoyable pleasure rather than having the original characteristics of lyrical poetry for self-expression are all characteristics of Chinese poetry in Japan during the early and late Middle Ages period. These characteristics can be said to be the current that flows in the underbelly of the history of Chinese literature in Japan. This author believes that the key to discussing the history of Chinese literature in Japan during the Middle Ages period from the perspective of East Asian literary history can be found here.

• Cross-Cultural Studies
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• v.25
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• pp.695-721
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• 2011

The purpose of this study is to provide the case study of expression education using story-telling about their cultures from which they came to the women who get interracial married and study korean cultures with the pride of their homeland. This research is also for the diverse members of korean society to deeply understand interracial married women, get higher understanding cultural diversities. And it is expected that these women could learn and study more korean cultures, too. In this study, process-based instruction method is used in the first step and second step such as brainstorming, questioning, discussing, investigating, teacher's asking in order to create some ideas about their home countries. Suggesting an example answer by teacher and free-writing are also involved. As the core of the process-based writing activity, the second step is focused on revising and correcting. Through reviewing their own writing task, feedback from teacher, interviewing from the difficulty of writing after this activity to cultural and linguistic backgrounds, they could appreciate their errors or mistakes in writing are natural and this affects their learning abilities positively. In third step which is focused on speaking activities, teacher provides feedback to learners after checking their common errors or habits in speaking. Meanwhile, by evaluating the role of the appraiser, It is helpful for the learners to have self-esteem of their own. When interviewing after fourth step's activities, the teacher compliments each learner's improvement while pointing out some errors. Afterward, We can see they show more positiveness to learn and understand korean cultures and set their identities. And they indicate interests and concerns each other's cultures by story-telling. It means they identify the popularity and interaction which the story-telling contains. Also, they confirm the participation in story-telling by expressing their willingness to revise their stories. After the activities in fifth step, there have been relatively positive changes in establishing identity and cultivating a sense of pride of learner's homeland cultures. Furthermore, we could find the strong will to be a story-teller about their homeland cultures. On this research, the effectiveness of expression education case study using story-telling about local cultures of interracial married women's homeland has been examined centrally focused on popularity, interaction, and participation. Afterward, interracial married women could not only cultivate the understanding about korean cultures but also establish their identity, improve their korean language skills through this education case study. Finally, the studies of the education programs to train interracial married women as story-tellers for their homeland local cultures are expected.