• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.12
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• pp.1098-1125
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• 2000

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 1998 and 1999 has been done. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environment. The conclusions are as follows. 1) A review of the recent studies on fluid flow, turbomachinery and pipe-network shows that many experimental investigations are conducted in applications of impingement jets. Researches on turbulent flows, pipe flows, pipe-networks are focused on analyses of practical systems and prediction of system performance. The results of noise reduction in the turbomachinery are also reported. 2) A review of the recent studies on heat transfer analysis and heat exchanger shows that there were many papers on the channel flow with the application to the design of heat exchanger in the heat transfer analysis. Various experimental and numerical papers on heat exchanger were also published, however, there were few papers available for the analysis of whole system including heat exchanger. 3) A review of the recent studies on heat pump system have focused on the multi-type system and the heat pump cycle to utilize treated sewage as the heat source. The defrosting and the frosting behaviors in the fin-tube heat exchanger is experimentally examined by several authors. Several papers on the ice storage cooling system are presented to show the dynamic simulation program and optimal operation conditions. The study on the micro heat pipes for the cooling of high power electronic components is carried out to examine the characteristics of heat and mass transfer processed. In addition to these, new type of separate thermosyphon is studied experimentally. 4) The recent studies on refrigeration/air conditioning system have focused on the system performance and efficiency for new alternative refrigerants. New systems operating with natural refrigerants are drawing lots of attention. In addition to these, evaporation and condensation heat transfer characteristics of traditional and new refrigerants are investigated for plain tubes and also for microfin tubes. Capillary tubes and orifice are main topics of research as expansion devices and studies on thermophysical properties of new refrigerants and refrigerant/oil mixtures are widely carried out. 5) A review of the recent studies on absorption cooling system shows that numerous experimental and analytical studies on the improvement of absorber performance have been presented. Dynamic analysis of compressor have been performed to understand its vibration characteristics. However research works on tow-phase flow and heat transfer, which could be encountered in the refrigeration system and various phase-change heat exchanger, were seemed to be insufficient. 6) A review of recent studies on duct system shows that the methods for circuit analysis, and flow balancing have been presented. Researches on ventilation are focused on the measurement of ventilation efficiency, and variation of ventilation efficiency with ventilation methods by numerous experimental and numerical studies. Furthermore, many studies have been conducted in real building in order to estimate indoor thermal environments. Many research works to get some information for cooling tower design have been performed but are insufficient. 7) A review on the recent studies on architectural thermal environment and building mechanical systems design shows that thermal comfort analysis is sitting environment, thermal performance analysis of Korean traditional building structures., and evaluation of building environmental load have been performed. However research works to improve the performance of mechanical system design and construction technology were seemed to be insufficient.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.19-28
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• 2012

After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.121-137
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• 2022

The purpose of this study is to present the necessary success factors and strategies for high-tech social ventures and stakeholders in the related ecosystem by empirically identifying factors that affect their sustainable performance. Based on prior research, the dimensions of three performance factors were presented: core technology competency, core business competency, and social mission orientation. Then, such sub-dimensions such as technology innovation orientation, R&D capability, business model, customer orientation, social network, and social mission pursuit were derived. For empirical analysis, a survey was conducted on domestic high-tech social ventures, and the significance of the hypothesis was tested through PLS-structural equation analysis of the collected 243 valid data. As a result, it was found that the technology innovation orientation was embedded as an abstract organizational and cultural characteristic in the high-tech social venture, which is a research sample, and thus did not significantly affect the dependent variable. In other words, aiming for the latest cutting-edge technology alone cannot affect performance, and it is a result of proving the need for substantial influencing factors that can strengthen it. On the other hand, the business model had a significant effect only on social performance, which is presumed to be the limitation of measurement tools developed for social enterprises, and the results of additional multi-group analysis to determine the cause also supported the basis for this estimation. Excluding the previous two performance factors, R&D competency, customer orientation, social network, and social mission pursuit were all found to have a significant positive (+) effect on social and economic performance. This study laid a foundation for related research by identifying high-tech social ventures emerging in the ecosystem of a social economy and expanded empirical research models related to the performance of existing social enterprises and social ventures. However, in the research method or process, there were limitations such as factor derivation or verification for balance of dual performance, subjective measurement method, and sample representativeness. It is expected that more in-depth follow-up studies will continue by supplementing future limitations and designing improved research models.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.2
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• pp.83-95
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• 2016

Strategies for parks and open spaces in the 21st century have moved from focusing on specific elements, such as quantitative growth and ecological and recreational aspects, to green infrastructure, which refers to a multi-functional network of open and green spaces offering a range of benefits. In the case of London, green infrastructure is realised as an integral part of urban infrastructure, involving physical and social infrastructure as well as practical spatial planning at the local level within statutory urban planning as part of a continuously developing green infrastructure framework with a theoretical basis. Taking this perspective, the present study looks at alterations to and developments in green infrastructure policies in the London Plan, the green grid framework as detailed in the city's strategic implementation of green infrastructure. Various trends and characteristics of the policies adopted in the London Plan and some implications are deduced, with three main results being identified. The first is a clear division of roles among the national government, Greater London Authority and borough councils, with local plans established under the guidance of the National Planning Policy Framework (NPPF) and the London Plan. Green infrastructure policies in the London Plan have been applied at a high rate in the boroughs' local plans, which leads to another, linked point. Secondly, green infrastructure policies and the green grid as an implementation framework have been consistently extended and developed through consolidating the London Plan, despite the change of government. Finally, in order to achieve the London Plan, the Mayor of London implemented policies by partnership and supporting programmes for London boroughs. Recently, the Seoul Metropolitan Authority introduced a parks and green spaces development policy, but the London case remains a good example; this is because green infrastructure policies in London were not a manifesto pledge but rather have been continuously and consistently advanced regardless of party politics and thus realised as long-term planning.

• Archives of design research
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• v.20 no.3 s.71
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• pp.151-162
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• 2007

How can new media devices and networks provide an effective response to the world's growing sector of cultural and historically-minded travelers? This study emerged from the question of how mobile handsets can change the nature of cultural and historical tourism in ubiquitous city environments. As wireless network and mobile IT have rapidly developed, it becomes possible to deliver cultural and historical information on the site through mobile handset as a tour guidance system. The paper describes the development of a new type of mobile tourism platform for site-specific cultural and historical information. The central objective of the project was to organize this cultural and historical walking tour around the mobile handset and its unique advantages (i.e. portability, multi-media capacity, access to wireless internet, and location-awareness potential) and then integrate the tour with a historical story and role-playing game that would deepen the mobile user's interest in the sites being visited, and enhance his or her overall experience of the area. The project was based on twelve locations that were culturally and historically significant to Korean War era in Busan. After the mobile tour game prototype was developed for this route, it was evaluated at the 10th PIFF (Pusan International Film Festival). After use test, some new strategies for developing mobile "edutainment content" to deliver cultural historical contents of the location were discussed. Combining 'edutainment' with a cultural and historical mobile walking tour brings a new dimension to existing approaches of the tourism and mobile content industry.

• Geotechnical Engineering
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• v.13 no.3
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• pp.101-122
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• 1997

A spiting reinforcement system is composed of a series of radially installed reinforcing spites along the perimeter of the tunnel opening ahead of excavation. The reinforcing spill network is extended into the in-situ soil mass both radially and longitudinally The sailing reinforcement system has been successfully used for the construction of underground openings to reinforce weak rock formations on several occasions. The application of this spiting reinforcement system is currently extended to soft ground tunneling in limited occasions because of lack of reliable analysis and design methods. A method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground is presented. The shape of the potential failure wedge for the case of smile-reinforced shallow tunnel is assumed on the basis of the results of three dimensional finite element analyses. A criterion to differentiate the spill-reinforced shallow tunnel from the smile-reinforced deep tunnel is also formulated, where the tunnel depth, soil type, geometry of the tunnel and reinforcing spites, together with soil arching effects, are considered. To examine the suitability of the proposed method of threedimensional stability analysis in practice, overall stability of the spill-reinforced shallow tunnel at facing is evaluated, and the predicted safety factors are compared with results from twotimensional analyses. Using the proposed method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground, a parametric study is also made to investigate the effects of various design parameters such as tunnel depth, smile length and wadial spill spacing. With slight modifications the analytical method of threeiimensional stability analysis proposed may also be extended for the analysis and design of steel pipe reinforced multi -step grouting technique frequently used as a supplementary reinforcing method in soft ground tunnel construction.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.39-53
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• 2007

Generally, fractured medium can be described with some key parameters, such as hydraulic conductivities or random field of hydraulic conductivities (continuum model), spatial and statistical distribution of permeable fractures (discrete fracture network model). Investigating the practical applicability of the well-known conceptual models for the description of groundwater flow in fractured media, various types of hydraulic tests were applied to studies on the highly fractured media in Geumsan, Korea. Results from single-hole packer test show that the horizontal hydraulic conductivities in the permeable media are between $7.67{\times}10^{-10}{\sim}3.16{\times}10^{-6}$ m/sec, with $7.70{\times}10^{-7}$ m/sec arithmetic mean and $2.16{\times}10^{-7}$ m/sec geometric mean. Total number of test interval is 110 at 8 holes. The number of completely impermeable interval is 9, and the low permeable interval - below $1.0{\times}10^{-8}$ m/sec is 14. In other words, most of test intervals are permeable. The vertical distribution of hydraulic conductivities shows apparently the good correlation with the results of flowmeter test. But the results from the cross-hole test show some different features. The results from the cross-hole test are highly related to the connectivity and/or the binary properties of fractured media; permeable and impermeable. From the viewpoint of the connection, the application of the general stochastic approach with a single continuum model may not be appropriate even in the moderately or highly permeable fractured medium. Then, further studies on the investigation method and the analysis procedures should be required for the reasonable and practical design of the conceptual model, with which the binary properties, including permeable/impermeable features, can be described.