• Wind and Structures
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• v.38 no.4
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• pp.231-244
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• 2024

As wind farms expand into low wind speed areas, an increasing number are being established in mountainous regions. To fully utilize wind energy resources, it is essential to understand the details of mountain flow fields. Reconstructing the wind speed field in complex terrain is crucial for planning, designing, operation of wind farms, which impacts the wind farm's profits throughout its life cycle. Currently, wind speed reconstruction is primarily achieved through physical and machine learning methods. However, physical methods often require significant computational costs. Therefore, we propose a Full Convolutional Neural Network (FCNN)-based reconstruction method for mountain wind velocity fields to evaluate wind resources more accurately and efficiently. This method establishes the mapping relation between terrain, wind angle, height, and corresponding velocity fields of three velocity components within a specific terrain range. Guided by this mapping relation, wind velocity fields of three components at different terrains, wind angles, and heights can be generated. The effectiveness of this method was demonstrated by reconstructing the wind speed field of complex terrain in Beijing.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.471-479
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• 2024

Recent advancements in cloud computing have significantly increased its importance across various sectors. As sensors, devices, and customer demands have become more diverse, workloads have become increasingly variable and difficult to predict. Cloud providers, connected to multiple physical servers to support a range of applications, often over-provision resources to handle peak workloads. This approach results in inconsistent services, imbalanced energy usage, waste, and potential violations of service level agreements. In this paper, we propose a novel engine equipped with a scheduler based on the Hot-Threshold concept, aimed at optimizing resource usage and improving energy efficiency in cloud environments. We developed this engine to employ both proactive and reactive methods. The proactive method leverages workload estimate-based provisioning, while the reactive Hot-Cold Scheduler consists of a Predictor, Solver, and Processor, which together suggest an intelligent migration flow. We demonstrate that our approach effectively addresses existing challenges in terms of cost and energy consumption. By intelligently managing resources based on past user statistics, we provide significant improvements in both energy efficiency and service consistency.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• Nutrition Research and Practice
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• v.17 no.2
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• pp.371-385
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• 2023

BACKGROUND/OBJECTIVES: Soy isoflavone (SIF) and soy lecithin (SL) have beneficial effects on many chronic diseases, including neurodegenerative diseases. Regretfully, there is little evidence to show the combined effects of these soy extractives on the impairment of cognition and abnormal cerebral blood flow (CBF). This study examined the optimal combination dose of SIF + SL to provide evidence for improving CBF and protecting cerebrovascular endothelial cells. MATERIALS/METHODS: In vivo study, SIF50 + SL40, SIF50 + SL80 and SIF50 + SL160 groups were obtained. Morris water maze, laser speckle contrast imaging (LSCI), and hematoxylin-eosin staining were used to detect learning and memory impairment, CBF, and damage to the cerebrovascular tissue in rat. The 8-hydroxy-2'-deoxyguanosine (8-OHdG) and the oxidized glutathione (GSSG) were detected. The anti-oxidative damage index of superoxide dismutase (SOD) and glutathione (GSH) in the serum of an animal model was also tested. In vitro study, an immortalized mouse brain endothelial cell line (bEND.3 cells) was used to confirm the cerebrovascular endothelial cell protection of SIF + SL. In this study, 50 µM of Gen were used, while the 25, 50, or 100 µM of SL for different incubation times were selected first. The intracellular levels of 8-OHdG, SOD, GSH, and GSSG were also detected in the cells. RESULTS: In vivo study, SIF + SL could increase the target crossing times significantly and shorten the total swimming distance of rats. The CBF in the rats of the SIF50 + SL40 group and SIF50 + SL160 group was enhanced. Pathological changes, such as attenuation of the endothelium in cerebral vessels were much less in the SIF50 + SL40 group and SIF50 + SL160 group. The 8-OHdG was reduced in the SIF50 + SL40 group. The GSSG showed a significant decrease in all SIF + SL pretreatment groups, but the GSH showed an opposite result. SOD was upregulated by SIF + SL pretreatment. Different combinations of Genistein (Gen)+SL, the secondary proof of health benefits found in vivo study, showed they have effective anti-oxidation and less side reaction on protecting cerebrovascular endothelial cell. SIF50 + SL40 in rats experiment and Gen50 + SL25 in cell test were the optimum joint doses on alleviating cognitive impairment and regulating CBF through protecting cerebrovascular tissue by its antioxidant activity. CONCLUSIONS: SIF+SL could significantly prevent cognitive defect induced by β-Amyloid through regulating CBF. This kind of effect might be attributed to its antioxidant activity on protecting cerebral vessels.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Journal of Ginseng Research
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• v.44 no.3
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• pp.442-452
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• 2020

Backgroud: Sleep deprivation (SD) impairs learning and memory by inhibiting hippocampal functioning at molecular and cellular levels. Abnormal autophagy and apoptosis are closely associated with neurodegeneration in the central nervous system. This study is aimed to explore the alleviative effect and the underlying molecular mechanism of stem-leaf saponins of Panax notoginseng (SLSP) on the abnormal neuronal autophagy and apoptosis in hippocampus of mice with impaired learning and memory induced by SD. Methods: Mouse spatial learning and memory were assessed by Morris water maze test. Neuronal morphological changes were observed by Nissl staining. Autophagosome formation was examined by transmission electron microscopy, immunofluorescent staining, acridine orange staining, and transient transfection of the tf-LC3 plasmid. Apoptotic event was analyzed by flow cytometry after PI/annexin V staining. The expression or activation of autophagy and apoptosis-related proteins were detected by Western blotting assay. Results: SLSP was shown to improve the spatial learning and memory of mice after SD for 48 h, accomanied with restrained excessive autophage and apoptosis, whereas enhanced activation of phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin signaling pathway in hippocampal neurons. Meanwhile, it improved the aberrant autophagy and apoptosis induced by rapamycin and re-activated phosphoinositide 3-kinase/Akt/mammalian target of rapamycin signaling transduction in HT-22 cells, a hippocampal neuronal cell line. Conclusion: SLSP could alleviate cognitive impairment induced by SD, which was achieved probably through suppressing the abnormal autophagy and apoptosis of hippocampal neurons. The findings may contribute to the clinical application of SLSP in the prevention or therapy of neurological disorders associated with SD.

• 대한공업교육학회지
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• v.38 no.1
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• pp.163-194
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• 2013

This study aims at giving examples that can be applied in the real education field, and it develops theme-based integrative education program for Industrial Specialized high school students. It analyzed the models of many scholars about the development of education course, and devised developmental models and procedures of the theme-based integrative education program of engineering specialized high school from those. As a result, it used and reorganized ADDIE model which is the systematic education course development model and the theme-based integrative education development model of Frazee and Rudnitski(1995) as the basic structure, and came to devise theme-based integrative education program of engineering specialized high school while referring to creative engineering design education program development model by Lee Chang-hoon. This study that is theme-based integrative education program for engineering-specialized high school students and is the result of this study has the following characters. First, This theme-based integrative education program that is developed for engineering-specialized high school students can be applied and the initial example that approach the Theme-Based. Second, This Education Program included the Activity project that is "Making Maglev" for the third grade at the engineering-specialized high school and One of the Program's aim is to bring up their attitude that engaged to in the class having the Interest. Third, Theme-based integrative education program for engineering-specialized high school is composed the workbook for the students and the teaching guidance plan for the teachers. Workbook for the students is composed four Units;"Brief about the Maglev","Basic principles about the Maglev","Intensive principles about the Maglev", Activity project about the Maglev". And each unit is made by Learning Purpose, Introducing, Learning Contents(Deepen Learning, Reading Magazines), Assesment etc. Teaching guidance plan for the teachers include that Summary, Purpose, Time Planing & Streaming Map for the class, contents associated Maglev, prerequisite learning, constructure of the education program, flow chart, learning activity, assesment(self-appraiser and peer review).

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.48-63
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• 2024

This study aims to develop a class procedure for the application of classrooms that value context and to conduct science classes using this procedure to examine the effects. Among various contexts related to scientific knowledge, the study develops a teaching procedure for designing classes that focus on the contexts of discovery and real life. After verifying the content validity of the context-based design and the program to which it was applied, a class was conducted, and the responses of the children were checked. The final draft of the lesson design completed after revision and supplementation is as follows: context-based design was presented in four stages, namely, presenting, exploring the context, adapting the context, and organizing (share and synthesizing; PEAS). The goal is to enable people to experience the overall flow of scientific knowledge instead of focusing on the acquisition of fragmentary knowledge by covering a wide range of topics from the social and historical contexts in which scientific knowledge was created to its use in real life. To aid in understanding the newly proposed class procedure and verifying its effectiveness, we developed a program by selecting the "My Fun Exploration," 2. Biology and Environment unit of the second semester of the fifth grade. The result indicated that the elementary science program that applied the context-centered design effectively improved the self-directed learning ability of students. In addition, the effect was especially notable in terms of intrinsic motivation. As the students experienced the contexts of discovery and real life related to scientific knowledge, they developed the desire to actively participate in science learning. As this becomes an essential condition for deriving active learning effects, a virtuous cycle in which meaningful learning can occur has been created. Based on the implications, developing programs that apply context-based design to various areas and contents will be possible.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.453-462
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• 2005

Recently, due to technical improvements of storage devices and networks, the amount of data increase rapidly. In addition, it is required to find the knowledge embedded in a data stream as fast as possible. Huge data in a data stream are created continuously and changed fast. Various algorithms for finding frequent itemsets in a data stream are actively proposed. Current researches do not offer appropriate method to find frequent itemsets in which flow of time is reflected but provide only frequent items using total aggregation values. In this paper we proposes a novel algorithm for finding the relative frequent itemsets according to the time in a data stream. We also propose the method to save frequent items and sub-frequent items in order to take limited memory into account and the method to update time variant frequent items. The performance of the proposed method is analyzed through a series of experiments. The proposed method can search both frequent itemsets and relative frequent itemsets only using the action patterns of the students at each time slot. Thus, our method can enhance the effectiveness of learning and make the best plan for individual learning.