• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.101-112
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• 2005

Recently, one of the most challenging Problems is to compose web services dynamically, that is, on demand. In particular, when a functionality that cannot be directly realized by existing services is required, existing services may be combined together to fulfill the request. This paper is to implement the dynamic composition of web services using existing workflow technologies. Workflow systems play a major role in E-businesses. However, due to the composition of web services using workflows differs from the design of traditional workflow systems, two problems need to be solved. (1) how to efficiently discover web services and (2) how to facilitate the interoperability of heterogeneous web services. In this paper, we present a matching algorithm for web service discovery and propose an approach based on the use of ontologies to facilitate the integration of web services. Finally, we have built a prototype system to illustrate how to the dynamic composition of web services are achieved.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.63-73
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• 2020

The Ministry of Land, Infrastructure and Transport carried out a pilot project for data maintenance in 2011 to ensure the accuracy of cadastral records nationwide, and now trying to reduce the errors such as omission of the cadastral book, inconsistency of land category between cadastral account book and cadastral map, etc. and the boundary between the map boundary, scale, and administrative areas. In this study, we looked at the currents status and problems of the cadastral research, improving the cadastral map, which has been promoted by the government and the cadastral office. In order to revitalize the cadastral map data maintenance project, it is necessary to re-establish the plan for each step for challenging the limitation of current data maintenance, and the master plan for promotion system, and develop manuals to maintain consistency and secure accuracy of cadastral map maintenance, such as "Coverage and Maintenance Guidelines for Cadastral Maps", and secure the national budget for error correction in cadastral map led by government.

• Communications of Mathematical Education
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• v.23 no.4
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• pp.1043-1058
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• 2009

This study concerns with the effects of group projects performed by the students in college math classes. The study result shows that 61% of the students get more self-confidence and interest in mathematics through working projects. In addition, the result reveals that one of the essential factors for successful college mathematics class is to provide a strong motivation for learning to students. For effective teaching through group projects, this paper suggests that 1) the number of students in the class be 20 or less, 2) the projects group be consisted of two members, 3) the instructor should select proper problems to students' level from extra-textbooks, 4) the problems should be interesting, positive and challenging, 5) each group should take only one problem, 6) the groups be provided with enough references and materials, 7) each student in the group be cared to feel importance and necessity of mathematics and cooperative work, 8) the students should work with math joyfully, 9) the instructor remind the students that we live with mathematics in real life, 10) 2-month be a necessary and appropriate term in working projects.

• Journal of Hospice and Palliative Care
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• v.24 no.2
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• pp.130-134
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• 2021

In the era of coronavirus disease 2019 (COVID-19), social distancing and strict visitation policies at hospitals have made it difficult for medical staff to provide high-quality end-of-life (EOL) care to dying patients and their families. There are various issues related to EOL care, including psychological problems of patients and their families, difficulties in EOL decision-making, the complicated grief of the bereaved family, moral distress, and exhaustion of medical staff. In relation to these issues, we aimed to discuss practical considerations in providing high-quality EOL care in the COVID-19 pandemic. First, medical staff should discuss advance care planning as early as possible and use the parallel planning strategy. Second, medical staff should play a role in facilitating patient-family communication. Third, medical staff should actively and proactively evaluate and alleviate dying patients' symptoms using non-verbal communication. Lastly, medical staff should provide care for family members of the dying patient, who may be particularly vulnerable to post-bereavement problems in the COVID-19 era. Establishing a system of screening high-risk individuals for complicated grief and connecting them to bereavement support services might be considered. Despite the challenging and limited environment, providing EOL care is essential for patients to die with dignity in peace and for the remaining family to return to life after the loved one's death. Efforts considering the practical issues faced by all medical staff and healthcare institutions caring for dying patients should be made.

• Journal of KIBIM
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• v.10 no.4
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• pp.22-31
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• 2020

Shop drawing tasks conducted after finishing coordinated or engineering design have great influences on the quality and cost of a project. However, despite the development of commercial BIM applications, shop drawings have mainly produced manually in certain engineering fields. Incorrect shop drawings with human errors have occurred various problems such as cost overrun, time delay and reworks. An automated shop drawing publishing from BIM is expected to resolve these problems. Despite attempts for automate shop drawing production, the field of mechanical, electrical and plumbing (MEP) is yet regarded challenging due to complexity of components and connection. In this research, we develop a process for automated producing 3D MEP shop drawings in BIM environment as following steps: to analyze conventional MEP shop drawing process, to identify detailed process that can be automated, to classify existing MEP objects and assign codes usable in BIM, and to develop an application. The validation of automated process is conducted against 10 clean room projects in which MEP is more complex and its cost is higher than other projects in terms of productivity and workers' satisfaction. Results show that the number of manpower for shop drawing is reduced by 30%, and the working time is shortened by 31%. Personal opinions of involved practitioners is interpreted as positive as the average rate of agrement on practicability, easy-to-use and necessary retouch tasks is around 66%.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.73-82
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• 2022

Early detection continues to be the mainstay of breast cancer control as well as the improvement of its treatment. Even so, the absence of cancer symptoms at the onset has early detection quite challenging. Therefore, various researchers continue to focus on cancer as a topic of health to try and make improvements from the perspectives of diagnosis, prevention, and treatment. This research's chief goal is development of a system with deep learning for classification of the breast cancer as non-malignant and malignant using mammogram images. The following two distinct approaches: the first one with the utilization of patches of the Region of Interest (ROI), and the second one with the utilization of the overall images is used. The proposed system is composed of the following two distinct stages: the pre-processing stage and the Convolution Neural Network (CNN) building stage. Of late, the use of meta-heuristic optimization algorithms has accomplished a lot of progress in resolving these problems. Teaching-Learning Based Optimization algorithm (TIBO) meta-heuristic was originally employed for resolving problems of continuous optimization. This work has offered the proposals of novel methods for training the Residual Network (ResNet) as well as the CNN based on the TLBO and the Genetic Algorithm (GA). The classification of breast cancer can be enhanced with direct application of the hybrid TLBO- GA. For this hybrid algorithm, the TLBO, i.e., a core component, will combine the following three distinct operators of the GA: coding, crossover, and mutation. In the TLBO, there is a representation of the optimization solutions as students. On the other hand, the hybrid TLBO-GA will have further division of the students as follows: the top students, the ordinary students, and the poor students. The experiments demonstrated that the proposed hybrid TLBO-GA is more effective than TLBO and GA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Journal of the Korean GEO-environmental Society
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• v.24 no.11
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• pp.5-10
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• 2023

Slag-CB is widely used in various fields that require groundwater control. It is a type of CB where a portion of the cement mixed with CB is replaced with GGBS. In general, Slag-CB has the advantage of long-term improvement in compressive strength, permeability, durability, and chemical resistance as the GGBS replacement ratio increases. However, there are problems such as decreased flexibility and resistance to deformation of the cut-off walls, as well as brittleness upon failure. To address these problems, some quality standards recommend designing Slag-CB with lower strength, which makes it challenging to apply high-strength Slag-CB with a high GGBS replacement ratio in the field.In this study, we aimed to improve the flexibility and resistance to deformation of Slag-CB to prevent brittle failure and improve the field applicability of Slag-CB. To achieve this, we evaluated the compressive behavior of nylon fiber-reinforced Slag-CB and proposed measures for enhancing the flexibility and resistance to deformation of Slag-CB.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.105-114
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• 2024

Recently, with an emphasis on software proficiency, universities are providing software education to all students regardless of their majors. However, non-majors often lack motivation for software education and perceive the unfamiliar learning content as more challenging. To address this issue, tailored software education according to the learners' characteristics is essential. Art students, for instance, with their strong visual comprehension and expressive abilities, can benefit from utilizing visual literacy to enhance the effectiveness of programming education. In this study, we propose decomposing everyday problems into flowcharts and pseudocode to construct procedural and visual images. Using the educational programming language PlayBot, we aim to analyze the effectiveness of teaching by coding to solve problems. Through this approach, students are expected to grasp programming concepts, understand problem-solving processes through computational thinking, and acquire skills to apply programming in their respective fields.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.559-564
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• 2024

Since the era of industrial revolution, the waste volume has continued to grow; waste management has thus become one of the major global environmental challenges facing humanities today. Waste treatment and management issues trigger NIMBY movements, and disputes among states, governments, and social actors over the issues have been accelrating. At the level of states and sub-states, various measures including institutions, laws, regulations, market-oriented methods, consensus and collaborative governance have been introduced to address various problems associated with waste. More recently, science and technology has been applied to the waste treatment and management under the notion of circular economy. However, societal support for addressing waste problems still remains inadequate, calling for new approaches and alternative pathways. In this context, this study examines two cases of urban incineration plants designed by Hudertwasser, Austria-born artist and architect: Spittelau, Austria, and Osaka, Japan. Through these case studies, I demonstrate how creative and innovative culture-technology convergence can shed new light on challenging environmental issues such as an urban waste problem.