Social networking communities (SNCs) are media designed to facilitate social interaction using highly accessible and scalable publishing techniques. SNCs can constitute individuals' their own profiles in the online environment and share texts, images and photos in a variety ways. In other words, one of the other motivators is knowledge sharing. Various sites, such as Facebook, Orkut, MySpace, and Hi5 are categorized as SNCs. SNCs have become increasingly popular in recent years among youths, especially students, who use them to build social networks. This study examines whether this usage of SNCs inculcates a sense of community among their members. Several studies have examined the role of a sense of community through increased usage in the context of virtual communities. Although this result may be true of virtual communities, this paper contends that the opposite relationship prevails in the case of SNCs because members interact to build networks and are not obliged to interact. The results reveal that maintaining long-term interactions in the SNCs is helpful in building a sense of community in SNCs. Although short-term usage may not boost the development of a sense of community in SNCs, it does matter if the premise is for a long-term commitment to SNCs. Implications for theory and practice are discussed.
Purpose: The purpose of this study was to investigate the adverse effects of sensorimotor function at the shoulder joint according to long-term cane usage in stroke patients without apraxic behavior, in terms of the presence of shoulder joint pain, accuracy of tracking task, proprioceptive joint position sense, and nine-hole pegboard. Methods: Nineteen stroke patients with long-term cane usage (cane usage group) and nineteen stroke patients without cane usage (non-cane usage group) were recruited. All subjects were tested in pain presence, a tracking task for visuomotor function, joint reposition, and nine-hole pegboard in the shoulder joint regarding the non-affected side. Results: In the accuracy index for tracking task and the nine-hole pegboard test, significant differences were observed between the cane usage group and the non-cane usage group. However, although a higher emergence of shoulder pain and a lower accuracy for joint reposition sense were detected in the cane usage group in comparison to the non-cane usage group, there were no significant differences between the two groups. Conclusion: Our findings suggest that long-term cane usage could induce to decrease in delicate movement and coordination in the non-affected upper arm in stroke patients. In addition, they could experience high frequency of shoulder pain and poor joint reposition sense. Therefore, careful evaluation and observation will be required concerning stroke patients with long-term cane usage.
This research intends to observe the effects of social capital regarding fashion social enterprises on the community sense of participating consumers, and verify the relationship of the effects that such social capital and community sense have on sustainability formation variable(shared values, suitability of values, behavioral flow, cognitive belief and long-term relationship orientation) of social enterprises. For such analysis, a sample of 400 consumers with experience of purchasing products of fashion social enterprises more than once was utilized, and path analysis was conducted utilizing AMOS 20.0. As a result of this research, first, information sharing, social participation among the characteristic factors of social enterprises' social capital had a meaningful impact on shared values, and self-pursuit and significance meaningfully affected the suitability of values. Second, mutual influence, sense of belonging, satisfaction of needs and emotional bond among the characteristic factors of community sense between social enterprises and consumers meaningfully affected shared values, whereas mutual influence, sense of belonging and emotional bond substantially influenced suitability of values. Third, shared values and suitability of values affected the relationship between behavioral flow and cognitive trust, and behavioral flow and cognitive trust both had meaningful impact on long-term relationship orientation.
Journal of the Korean Society of Clothing and Textiles
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v.42
no.4
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pp.639-656
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2018
The term fashion sense is used in everyday conversations by consumers to refer to the ability of people who dress well in attractive ways or to refer to the competencies or expertise of fashion professionals. Despite the frequent use of the term, its concept has rarely been explored systematically. In this study, we performed in-depth interviews with 14 fashion experts to clarify the concept of fashion sense. The core elements of fashion sense were explored based on the interview results. As a result, twelve core elements were identified that included visual ability, aesthetic experience, aesthetic recognition ability, intuition, self-consciousness, self-efficacy, fashion experience, involvement in fashion, creativity, innate sense, environmental support, and development due to education. In addition to these twelve core elements, 42 supplementary elements were identified. This study is to help initiate an academic discussion of the concept of fashion sense as a competency that fashion experts should develop. The findings of this study can provide practical and educational implications for the fashion industry and academia.
Although the concept of "common sense" is often taken for granted, judging whether behavior or knowledge is common sense requires a complex series of mental processes. Additionally, different perceptions of common sense can lead to social conflicts. Thus, it is important to understand how we perceive common sense and make relevant judgments. The present study investigated the dynamics of neural representations underlying judgments of what common sense is. During functional magnetic resonance imaging, participants indicated the extent to which they thought that a given sentence corresponded to common sense under the given perspective. We incorporated two different decision contexts involving different cultural perspectives to account for social variability of the judgments, an important feature of common sense judgments apart from logical true/false judgments. Our findings demonstrated that common sense versus non-common sense perceptions involve the amygdala and a brain network for episodic memory recollection, including the hippocampus, angular gyrus, posterior cingulate cortex, and ventromedial prefrontal cortex, suggesting integrated affective, mnemonic, and social functioning in common sense processing. Furthermore, functional connectivity multivariate pattern analysis revealed that interactivity among the amygdala, angular gyrus, and parahippocampal cortex reflected representational features of common sense perception and not those of non-common sense perception. Our study demonstrated that the social memory network is exclusively involved in processing common sense and not non-common sense. These results suggest that intergroup exclusion and misunderstanding can be reduced by experiencing and encoding long-term social memories about behavioral norms and knowledge that act as common sense of the outgroup.
Enteral nutritional support has been used via tube feeding for dysphagic stroke patients. We performed long and short term trials to evaluate the effects of commercial enteral nutritional supports on nutrition and health in stroke patients (mRS = 3~5) and quality of life in their caregivers. For a long term study, we recruited chronic (${\geq}$ 1 yrs) stroke patients (n = 6) and administered them 6 cans/day (1,200 kcal) of the commercial enteral formula N for 6 months according to IRB-approved protocol. We collected peripheral blood at 0, 2, 4 and 6 months. For a short term study, we recruited acute (${\leq}$ 3 months) stroke patients (n = 12) and randomly administered them two different commercial enteral formulas, N or J, for 2 weeks. We collected their blood at 0, 4, 7 and 14 day of the administration. Blood samples were analyzed to quantify 19 health and nutritional biomarkers and an oxidative stress biomarker, malondialdehyde (MDA). In order to evaluate quality of life, we also obtained the sense of competence questionnaire (SCQ) from all caregivers at 'before' and 'after trials'. As results, the enteral formula, N, improved hemoglobin and hematocrit levels in the long term trial and maintained most of biomarkers within normal ranges. The SCQ levels of caregivers were improved in the long term treatment (P < 0.05). In a case of the short term study, both of enteral formulas were helpful to maintain nutritional status of the patients. In addition, MDA levels were decreased in the acute patients following formula consumption (0.05 < P < 0.1). Most of health and nutrition outcomes were not different, even though there is a big difference in price of the two products. Thus, we evaluate the formula N has equal nutritional efficacy compared to the formula J. In addition, long term use of enteral formula N can be useful to health and nutrition of stroke patients, and the quality of life for their caregivers.
As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.
In this paper, a new fusion architecture consisting of a host filter and a do-correlated compression filter is proposed based on propagated measurement fusion. In the proposed architecture, the host filter estimates the system states in long-term sense based on the measurements from the beginning to the current time. The de-correlated compression filter assists the host filter by providing fusion results in short-term sense based on the measurements within a block of time. The proposed de-correlated compression filter alleviates computational burden of the host filter by reducing the maximum amount of instantaneous computation, and provides an efficient environment for real-time fault detection and estimation.
International Journal of Fuzzy Logic and Intelligent Systems
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v.11
no.4
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pp.238-246
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2011
This paper proposes a new semantic representation and its associated similarity measure. The representation expresses textual context observed in a context of a certain term as a network where nodes are terms and edges are the number of cooccurrences between connected terms. To compare terms represented in networks, a graph kernel is adopted as a similarity measure. The proposed representation has two notable merits compared with previous semantic representations. First, it can process polysemous words in a better way than a vector representation. A network of a polysemous term is regarded as a combination of sub-networks that represent senses and the appropriate sub-network is identified by context before compared by the kernel. Second, the representation permits not only words but also senses or contexts to be represented directly from corresponding set of terms. The validity of the representation and its similarity measure is evaluated with two tasks: synonym test and unsupervised word sense disambiguation. The method performed well and could compete with the state-of-the-art unsupervised methods.
The Journal of the Convergence on Culture Technology
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v.4
no.1
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pp.153-163
/
2018
The purpose of this study was to investigate nurses' ethical dilemma and professionalism in long-term care hospitals. Participants in this study were 210 nurses working in 14 long-term care hospitals. Data analysis was done using SPSS / WIN 24.0 program. As a result of this study, the ethical dilemma of the nurse was moderate. The highest sub-area was 'nurse-patient relationship' and 'respect of life and human rights' was the lowest sub-area. The professionalism of the subjects was moderate, and the score of 'sense of mission' area was the lowest. Nursing ethics guidelines should be developed that reflect the ethical dilemma of nurses in long-term care hospitals, and will provide the right values for the ethical dilemma that nurses face in their workplace. When planning the nurses' professionalism education, it is necessary to have a strategy to enhance the sense of mission by emphasizing beliefs and values about nursing care.
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