• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.83-105
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• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.381-394
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• 2022

Recently, due to the personalization and customization of data, Internet-based services have increased requirements for real-time processing, such as real-time AI inference and data analysis, which must be handled immediately according to the user's situation or requirement. Real-time tasks have a set deadline from the start of each task to the return of the results, and the guarantee of the deadline is directly linked to the quality of the services. However, traditional container systems are limited in operating real-time tasks because they do not provide the ability to allocate and manage deadlines for tasks executed in containers. In addition, tasks such as AI inference and data analysis basically utilize graphical processing units (GPU), which typically have performance impacts on each other because performance isolation is not provided between containers. And the resource usage of the node alone cannot determine the deadline guarantee rate of each container or whether to deploy a new real-time container. In this paper, we propose a monitoring technique for tracking and managing the execution status of deadlines and real-time GPU tasks in containers to support real-time processing of GPU tasks running on containers, and a node list management technique for container placement on appropriate nodes to ensure deadlines. Furthermore, we demonstrate from experiments that the proposed technique has a very small impact on the system.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.321-334
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• 2021

A fixed reflectivity-rainfall relationship approach, such as the Marshall-Palmer relationship, for an entire year and different seasons, can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian inference framework. A calibrated spatially structured pattern in the parameters exists, particularly for the wet season and parameter for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields. In contrast, the radar rainfall fields obtained from the existing Marshall-Palmer relationship show a systematic underestimation. In the event of high impact weather, it is expected that the value of national radar resources can be improved by establishing an active watershed-level hydrological analysis system.

• The Korean Journal of Archival Studies
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• no.19
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• pp.57-102
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• 2009

Recently, distribution of record via web and coefficient of utilization are increase. so, Archival information service using website becomes essential part of record center. The main point of archival information service by website is making record information retrieval easy. It has need of matching user's request and representation of record resources correctly to making archival information retrieval easy. Archivist and record manager have used various information representation tools from taxonomy to recent thesaurus, still, the accuracy of information retrieval has not solved. This study constructed record retrieval system based on Topic Map by modeling record resources which focusing on description metadata of the records to improve this problem. The target user of the system is general web users and its range is limited to the president related sources in the National Archives Portal Service. The procedure is as follows; 1) Design an ontology model for archival information service based on topic map which focusing on description metadata of the records. 2) Buildpractical record retrieval system with topic map that received information source list, which extracted from the National Archives Portal Service, by editor. 3) Check and assess features of record retrieval system based on topic map through user interface. Through the practice, relevance navigation to other record sources by semantic inference of description metadata is confirmed. And also, records could be built up as knowledge with result of scattered archival sources.

• Environmental and Resource Economics Review
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• v.20 no.3
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• pp.419-457
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• 2011

This study aims at understanding the characteristics of global economic models, which are widely used for climate change policy analysis. A literature review study was conducted in order to derive general features of top-down models such as CGE and bottom-up/hybrid models such as GTEM. Furthermore, a structural analysis was carried out by applying parameter and structural components from other models to a particular model to observe the potential differences in outcomes. Literature review shows that bottom-up or hybrid models generally have higher level of reduction potentials than top-down models in the long run. This contradicts the conclusion presented by IPCC, and raises the need for more rigorous investigation through structural analysis. Structural analysis of EPPA model indicates that the structural component of the energy sector in a particular model is the most influential factor in predicting baseline emissions and reduction potentials. This includes the structure among energy, capital, and labor inputs, and the substitution elasticities within the energy bundle. Technology bundle can establish the conclusions from literature review, and change in Armington elasticities do not significantly affect the outcome in aggregate.

• Korean Journal of Plant Resources
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• v.20 no.2
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• pp.193-200
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• 2007

Pollen grains of seven taxa on the family Pyrolaceae, known to be distributed in Korea (Pyrola dahurica(Andreses) Kom., P. incarnata (DC.) Fisch. ex Kom., P. japonica Klenze ex Alefeld, P. minor L., P. renifolia Max., Orthilia secunda (L.) House, Chimaphila japonica Miq.), were examined by the light and the scanning electron microscope in order to evaluate their taxonomic significances. The pollen units of genus Pyrola, Orthilia, Chimaphila were tetrad, monad, polyad respectively. This characteristics was good character for delimiting the genus, and Orthilia secunda (L.) House was more proper scientific name than Pyrola secunda L. based upon this character. Pollen size, tricolporate length, surface sculpturing pattern were different slightly among the treated taxa, and surface sculpturing patterns of Pyrola dahurica, P. incarnate, P. renifolia, Chimaphiza japonica were different from previous reports. Evolutionary trends of pollen grains in Pyrolaceae were inferred from the pollen units and aperture shapes.

• Economic and Environmental Geology
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• v.23 no.4
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• pp.393-409
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• 1990

Synthetic seismograms and deduced characteristic properties of the non-geometrical $S^*$ and $P^*$ waves are presented. These waves are excited on the free surface or an interface between two different media by an inhomogeneous P wave from a point source nearby, and propagate as homogeneous waves in the media. Synthetic seismograms are computed using an extended reflectivity method designed for buried source and receiver. An efficient computational procedure for propagator matrices of layers is devised to reduce the computational time and the RAM memory size in the implementation of the reflectivity method. Radiation patterns are obtained from the particle motions of the four types of the "*" waves, i.e., the $S^*$ wave generated near the free surface, and the reflected $S^*$, transmitted $S^*$ and transmitted $P^*$ waves generated near an interface. Some patterns show polarity changes of displacements and others reveal monotonic or non-monotonic variation of amplitude depending on the velocity structure. The decaying trend of amplitude with increasing epicentral distance are also shown for the head wave type of the "*" waves.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.551-561
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• 2016

The purpose of this study is to investigate both theoretically and empirically the roles of models in abductive reasoning for scientific problem solving. The context of the study is design-based research the goal of which is to develop inquiry learning programs in the domain of earth science, and the current article dealt with an early process of redesigning an abductive inquiry activity in geology. In the theoretical study, an extensive review was conducted with the literature addressing abduction and modeling together as research methods characterizing earth science. The result led to a tentative scheme for modeling-based abductive inference, which represented relationships among evidence, resource models, and explanatory models. This scheme was improved by the empirical study in which experts' reasoning for solving a geological problem was analyzed. The new scheme included the roles of critical evidence, critical resource models, and a scientifically sound explanatory model. Pedagogical implications for the support of student reasoning in modeling-based abductive inquiry in earth science was discussed.

• Transactions on Semiconductor Engineering
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• v.2 no.1
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• pp.17-20
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• 2024

This paper presents a novel lightweight object detection model tailored for low-powered edge devices, addressing the limitations of traditional resource-intensive computer vision models. Our proposed detector, inspired by the Single Shot Detector (SSD), employs a compact yet robust network design. Crucially, it integrates an 'enhancer block' that significantly boosts its efficiency in detecting smaller objects. The model comprises two primary components: the Light_Block for efficient feature extraction using Depth-wise and Pointwise Convolution layers, and the Enhancer_Block for enhanced detection of tiny objects. Trained from scratch on the Udacity Annotated Dataset with image dimensions of 300x480, our model eschews the need for pre-trained classification weights. Weighing only 5.5MB with approximately 0.43M parameters, our detector achieved a mean average precision (mAP) of 27.7% and processed at 140 FPS, outperforming conventional models in both precision and efficiency. This research underscores the potential of lightweight designs in advancing object detection for edge devices without compromising accuracy.

• Communications of Mathematical Education
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• v.38 no.1
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• pp.69-92
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• 2024

This study analyzed students' mathematical noticing in high school sequence classes based on students' two perceptions of sequence. Specifically, mathematical noticing was analyzed in four aspects: center of focus, focusing interaction, task features, and nature of mathematics activities, and the following results were obtained. First of all, the change pattern of central of focus could not be uniquely described by any one component among 'focusing interaction', 'task features', and 'the nature of mathematical activities'. Next, the interactions between the components of mathematical noticing were identified, and the teacher's individual feedback during small group activities influenced the formation of the center of focus. Finally, students showed two different modes of reasoning even within the same classroom, that is, focusing interaction, task features, and nature of mathematics activities that resulted in the same focus. It is hoped that this study will serve as a catalyst for more active research on students' understanding of sequence.