• Wind and Structures
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• v.34 no.1
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• pp.29-42
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• 2022

Following the BARC initiative, wind tunnel measurements have been performed on a 5:1 rectangular cylinder. Pressure distribution has been measured in several sections, checking the two-dimensionality of the flow around the model. Mean values compare well with previous data. These measurements have been processed using the standard Proper Orthogonal Decomposition (POD) and the snapshot POD to obtain phase-resolved cycles. This decomposition has been used to analyze the characteristics of the flow around the cylinder, in particular, the behavior of the recirculation bubble in the upper/lower surfaces. The effect of the angle of attack, the turbulence intensity and the Reynolds number has been studied. First and second modes extracted from POD have been found to be related to the reattachment of the flow in the upper surface. Increasing the angle of attack is related to a delay in the reattachment position, while an increase in turbulence intensity makes the reattachment point to move towards the windward face.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.486-503
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• 2023

Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.249-255
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• 2023

This study aims to empirically confirm the effect and impact of community care design research centered on domestic space and environment on health promotion, diagnosis treatment, disease management, rehabilitation, and mitigation through the year of publication and perspective. To this end, based on 1,227 space and environment design studies from 2,144 community care design research data conducted for about 20 years from 2002 to 2022, when care services began in earnest through the long-term care system for the elderly, SPSS 26.0 was used to create a 'Multi-layer Perceptron' artificial neural network structure model was predicted and neural network analysis was performed. Research Results First, as a result of checking studies in each field of health care by year, there is a significant difference with the number of studies related to health promotion being the highest. Second, the five perspectives are region, time, dimension, function, and content perspective. As a result of inputting these variables as independent variables and analyzing their importance in the artificial neural network, the function perspective had the most influence, followed by the region > content > dimension > time perspective.

• The Journal of Industrial Distribution & Business
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• v.14 no.1
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• pp.67-74
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• 2023

Purpose: This study aims to investigate how the online review usefulness affect consumers' shopping behavior in non-face-to-face shopping, which is now very common format of shopping environment after COVID-19 pandemic. Factors influencing online reviews were determined as quantity of review, agreement of review and characteristic of review based on research by existing researchers. Research design, data, and methodology: Customers in their teens to 60s who had experience of checking online reviews and purchasing products were surveyed using a Google questionnaire form from January 15, 2022 to February 19, 2022. To verify the validity and reliability of the research model, confirmatory factor analysis and discriminant validity analysis were conducted. In addition, the causal relationship between factors was verified through path analysis. Results: As a result, quantity of review and agreement of review had a statistically significant effect on review usefulness. However, characteristic of review did not have a statistically significant influence on review usefulness. And review usefulness had a statistically significant effect on attitude and purchase intention. Conclusions: This study investigated the factors affecting usefulness of online reviews and empirically analyzed the effects of online reviews on consumer attitudes and purchase intentions providing practical and theoretical implications for corporate online review management.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.794-807
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• 2022

Although registration of dogs is mandatory according to the revision of the Animal Protection Act, the registration rate is low due to the inconvenience of the current registration method. In this paper, a performance improvement study was conducted on the dog face recognition technology, which is being reviewed as a new registration method. Through deep learning learning, an embedding vector for facial recognition of a dog was created and a method for identifying each dog individual was experimented. We built a dog image dataset for deep learning learning and experimented with InceptionNet and ResNet-50 as backbone networks. It was learned by the triplet loss method, and the experiments were divided into face verification and face recognition. In the ResNet-50-based model, it was possible to obtain the best facial verification performance of 93.46%, and in the face recognition test, the highest performance of 91.44% was obtained in rank-5, respectively. The experimental methods and results presented in this paper can be used in various fields, such as checking whether a dog is registered or not, and checking an object at a dog access facility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2323-2329
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• 2013

Web-services employ an XML to represent data and an XML parser is needed to use data. The DOM(Document Object Model) is widely used to parse an XML, but it is not suitable for any systems with limited resources because it requires a preprocessing to create the DOM and additional memory space. In this paper, we propose the StreXTree(Streaming XML Tree) with failure transitions and without any preprocessing tasks in order to improve the system performance. Compared to other works, our StreXTree parser achieves 2.39x and 3.02x improvement in system performance in Search and RBStreX, respectively. In addition, our StreXTree parser supports Well-Formed checking to verify the syntax and structure of XML.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3666-3672
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• 2010

This study dealt with the controller design of the cooling system for controlling the inside temperature of the LCD panel console(the rest console') using as an outdoor billboard. The cooling performance of the LCD console that had been developed by the preceding research, was insufficient in the performance of the controller. In order to improve the performance of the system, in this study defined the structure and the design condition of the system first, after measured the parameters having influence on the dynamic characteristics, and developed the mathematical model for the analysis of the system. Finally planned a controlling scheme of the system and simulated the controller for the performance checking, compared the performance of this system controller with the preceding one. The purpose of this study is the presentation of the more improving method for the system control.

• Journal of Pharmaceutical Investigation
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• v.22 no.4
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• pp.289-300
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• 1992

The counter-transport phenomena in the hepatic transport of 1-anilino-8-naphthalene sulfonate (ANS) were kinetically investigated by analyzing the plasma disappearance-time profiles and the transport into the isolated hepatocytes. In vivo "counter transport phenomena" were simulated based on the perfusion model which incorporated the carrier-mediated transport and the saturable intracellular binding. The condition that the mobility of carrier-ligand complex is greater than that of free carrier is not essential for the occurrence of counter-transport phenomenon. To examine the inhibitory effects on the initial uptake of a ligand by the liver, it is necessary to judge whether the true counter-transport mechanism (trans-stimulation) is working or not. The initial plasma disappearance curves of ANS were then kinetically analyzed based on a two-compartment model, in which the ligand is eliminated only from the peripheral compartment (liver compartment). No effects on the initial plasma disappearance rates of ANS were observed after preloading of bromophenol blue (BPB) or rose bengal (RB) in the liver. Inhibitory effect of BPB or RB on the initial uptake (or efflux) rates of ANS by the isolated hepatocytes were not observed, suggesting that the true counter transport mechanism is not working. In conclusion, checking the preloading effects of transstimulation on the initial uptake of a ligand by the liver could be a useful criterion for carrier cycling and common use of the same carrier between two ligands. However, one cannot exclude those possibilities even if the preloading effects cannot be observed.