• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.135-142
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• 2022

Despite global medical advancements, many patients are misdiagnosed, and more people are dying as a result. We must now develop techniques that provide the most accurate diagnosis of heart disease based on recorded data. To help immediate and accurate diagnose of heart disease, several data mining methods are accustomed to anticipating the disease. A large amount of clinical information offered data mining strategies to uncover the hidden pattern. This paper presents, comparison between different classification techniques, we applied on the same dataset to see what is the best. In the end, we found that the Random Forest algorithm had the best results.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.213-220
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• 2024

Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.30-45
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• 2024

This study introduces an effective method for predicting individual local tax delinquencies using prevalent machine learning and deep learning algorithms. The evaluation of credit risk holds great significance in the financial realm, impacting both companies and individuals. While credit risk prediction has been explored using statistical and machine learning techniques, their application to tax arrears prediction remains underexplored. We forecast individual local tax defaults in Republic of Korea using machine and deep learning algorithms, including convolutional neural networks (CNN), long short-term memory (LSTM), and sequence-to-sequence (seq2seq). Our model incorporates diverse credit and public information like loan history, delinquency records, credit card usage, and public taxation data, offering richer insights than prior studies. The results highlight the superior predictive accuracy of the CNN model. Anticipating local tax arrears more effectively could lead to efficient allocation of administrative resources. By leveraging advanced machine learning, this research offers a promising avenue for refining tax collection strategies and resource management.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.728-744
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• 2024

The presence of hydrogen absorbed by zirconium-based cladding materials during reactor operation can trigger degradation mechanisms and endanger the rod integrity. Ensuring the durability of the rods in extended time-frames like dry storage requires anticipating hydrogen behavior using numerical modeling. In this context, the present paper describes a hydrogen post-processing tool for Falcon - HYPE, a PSI's in-house tool able to calculate hydrogen uptake, transport, thermochemistry, reorientation of hydrides and hydrogen-related failure criteria. The tool extracts all necessary data from a Falcon output file; therefore, it can be considered loosely coupled to Falcon. HYPE has been successfully validated against experimental data and applied to reactor operation and interim storage scenarios to present its capabilities.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.81-86
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• 2024

Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

• Journal of Educational Research in Mathematics
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• v.27 no.3
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• pp.511-536
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• 2017

The present study aims to investigate ways in which pre-service secondary mathematics teachers anticipate 1) students' responses to specific mathematical tasks which are chosen or devised by the participating pre-service teachers as requiring students' higher cognitive demand and, 2) their roles as math teachers to scaffold students' mathematical thinking. To achieve the goal, we had our pre-service teachers to engage in an adapted version of Spangler & Hallman-Thrasher(2014)'s Task Dialogue writing activity whose focus was to develop pre-service elementary teachers' ability to orchestrate mathematical discussion. 14 pre-service teachers who were junior at the time enrolled in the Mathematics Teaching Method Course were subjects of the current study. In-depth analysis of both Task Dialogues which pre-service secondary mathematics teachers wrote and audiotapes of the group discussions while they wrote the dialogues suggests the following results: First, the pre-service secondary teachers anticipated how students would approach a task based on their own teaching experiences. Second, they were challenged not only to anticipate more than one correct students' responses but to generate questions for the predicted correct-responses to bring forth students' divergent thinking. Finally, although they were aware that students' knowledge should be the crucial element guiding their decision-making process in teaching, they tended to lower the cognitive demands of tasks by providing students with too much guidance which brought forth the use of procedural knowledge. The study contributes to the field as it provides insights as to what to attend in designing teacher education course whose goal is to provide a foundation for developing pre-service teachers' ability to effectively orchestrate mathematical discussion.

• Korean Journal of Social Welfare Studies
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• no.36
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• pp.203-225
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• 2008

The purpose of this study is to examine how much the external locus of control, social support, self-esteem, and adoption decision making process influence to teen parents' grief and find out the differences depending on meeting the baby, breast-feeding, anticipating the meeting the baby, ceremony for separation, and exposing their grief by themself or to others. Data was analysed with multiple regression and t-test. With the result of multiple regression analysis, the higher external locus of control, pressure of birthfather, regrets for adoption decision are, the higher grief is, and the lower support of friends and self-esteem are, the higher grief is. And It is estimated high grief statically among the group of breast-feeding, anticipating the baby, no ceremony for separation. But the group exposing their grief by self or to others felt low grief. On the basis of the results, we will find out the meaningful contents for intervention. The staffs of birthmother shelter and social worker don't overlooking the relationship between birthmother and birthfather and enforce the internal locus of control, self-esteem. Above all we will intervene about exploring the adoption decision making and facilitate the exposure of feeling related to surrendered baby(guilt, anxiety, sadness, shame, fear).

• Asian Oncology Nursing
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• v.6 no.2
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• pp.121-132
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• 2006

Purpose: The purpose of this study was to describe the lived experience of the patients with cancer participating in a clinical trial for the development of a new drug. Method: This study was based on a phenomenological approach. The eight patients participating in a clinical trial were selected as the participations of this study. The data were obtained through in-depth interviews from the participants and were analyzed using the Giorgi method. Results: Essential experiences of the patients with cancer under a clinical trial consisted of anticipating recovery of physical health and a social role, passing the strict criteria of a clinical trial, diminishing economic burden, satisfaction with special treatment receiving, social contribution, concerns about side effects and withdrawal from the clinical trial, conflicts as a participant, pain, limited administration of other treatments, regret for giving up other treatments, strict compliance with instructions, prevention of side effects and maintaining desirable life-style. Integrated units of meaning of these components were hope, good luck, a sense of satisfaction, fear, distress, and the will of self-control. Conclusion: The most essential meaning of the cancer patients participating in a clinical trial was hope. Hope was found to be a primary factor reinforcing the will of self-management. The results of this study can be of great help to the research nurses to understand the lived experience of the patients with cancer and to plan an effective nursing intervention for the patients.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.159-169
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• 2012

One of critical issues in the housing area is what strategies should be adopted for revitalizing contemporary communities in housing complex. It is expected that those strategies could encourage neighbourship and recover the existing community spaces. Based on the assumption that contemporary communities might have different characteristics from those of the traditional communities and spaces, this research aims to explore the possibility of new communities in a current context. With the development of the information communication technologies (ICT) and hardware systems, the environment would be capable of anticipating people's needs and then provide them with customization options to tailor the environment to their requirements. By incorporating the 'smart' paradigm, this paper introduces the concept of a smart community and space with the potential of mobile Augmented Reality(AR) as alternative strategies for activating the communities. The residents believe that existing common spaces need to be extendable and augmented by combining new technologies. The smart communities and spaces are expected to extend people's interaction to virtual world in aj real context, further combined with social network, it enables sustainable relationships among residents, contributina to a new type of community.

• Korean Journal of Applied Biomechanics
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• v.24 no.1
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• pp.1-9
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• 2014

The purpose of this study was to investigate the muscle mechanical properties of the pelvic axial pre-rotational movement for the Jireugi in the Taekwondo Juchumseogi stance. Eleven elite Taekwondo Poomsae athletes participated. Each participant performed 5 right hand Jireugi in Juchumseogi stance as fast and strong as possible while their motion was recorded by a 3D motion analysis system and the ground reaction forces by two force plates. The power and work of the muscular group surrounding the waist were analyzed to verify the effect of the stretch-shortening cycle (SSC) theory. The cause of the greater power seems to be the application of the SSC by the muscles surrounding the waist during the preparation phase of the pre-rotation group. For the none pre-rotation group, they only used the concentric contraction of the muscles surrounding the waist. Because the pre-rotation group used the SSC theory, they had the effect of shortening of the range of movement, creating a fast and more powerful rotation, thus anticipating the increase the magnitude of impact.