• Journal of the Economic Geographical Society of Korea
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• v.22 no.3
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• pp.258-273
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• 2019

Bilbao, Spain, made a mark as a example of the regional revitalization by culture and tourism. Korean Government have a perspective that culture and tourism could be an alternative to the regional crisis of manufacturing in 2018. The main purpose of this study is to analyze the locational specificity and the revival strategies for the regional development of Bilbao in a structural context. This could provide implications to the regional crisis of Korea. The main results are summarized as follows. Firstly, the local government of Bilbao has taken an active role, using not only its political and financial autonomy but also its locational advantage as an important nodal region of transnational trade networks in Europe. Secondly, Bilbao was able to sustain its regional revitalization initiatives for a long period by facilitating public-private partnership system. Finally, despite the effectiveness of the mega project and place marketing, low job security and the polarization of the service sector have emerged as a problem at the same time. Still, the deindustrialization of Bilbao could be possible due to the various services including knowledge-based services and financial services as well as culture and tourism.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.149-157
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• 2019

Recent research has been actively carried out on systems that want to optimize resource utilization by analyzing the intended behavior and pattern of behavior of objects (users, consumers). A service system that applies information about an object's location or behavior must include a location trigger processing system for tracking an object's real-time location. In this paper, we analyze design problems for the implementation of a context-awareness based location trigger system, and present system models based on analysis details. For this purpose, this paper introduces the concept of location trigger for intelligent location tracking techniques about moving situations of objects, and suggests a mobile agent system with active rules that can perform monitoring and appropriate actions based on sensing information and location context information, and uses them to design and implement the location trigger system for context-awareness based location services. The proposed system is verified by implementing location trigger processing scenarios and trigger service and action service protocols. In addition, through experiments on mobile agents with active rules, it is suggested that the proposed system can optimize the role and function of the application system by using rules appropriate to the service characteristics and that it is scalable and effective for location-based service systems. This paper is a preliminary study for the establishment of an optimization system for utilizing resources (equipment, power, manpower, etc.) through the active characteristics of systems such as real-time remote autonomous control and exception handling over consumption patterns and behavior changes of power users. The proposed system can be used in system configurations that induce optimization of resource utilization through intelligent warning and action based on location of objects, and can be effectively applied to the development of various location service systems.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.105-111
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• 2019

Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.79-90
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• 2021

Landscape composition and structure are important factors determining biological diversity including pests and natural enemires in agricultural ecosystem. This study was conducted to indentify effect of landscape composition on occurrence of lepidopteran pest population in Geochang, Gyoungdnam. For this, orchard characteristics and management practices were surveyed in 80 conventional apple orchards in Geochang, Korea, along with the monitoring of pest population densities. The landscape features of each surveyed orchard also obtained by extracting information from the public-service map. Grapholita molesta was the most dominat and damaging pest followed by Phyllonorycter ringoniella and Carposina sasakii in trap catches. Adoxophyes paraorana occurrences were low. Farmers spray insecticides and fungicides ap. 12.4 times per year respectively while acaricides were sprayed 2.4 times. Major landscape features such as surrounding apple orchard or paddy field did not influence the pest populations but presence of plum, peach, wild peach, graph, and even abandoned orchards significantly resulted in higher pest population mostly on G. molesta. C. sasakii population was higher in orchards with grape, peach, and P. ringoniella with peach, grape, abandoned orchards and jujube. Results highlight the need of landscape management not only for the rural amenity but also for increasing functional diversity of agroecosystem as well as reducing pest population.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.949-955
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• 2020

In this Study, Social Network Analysis of IoT related patents in South Korea, China, and Japan was conducted from the viewpoint of patent informatics. To this end, 2,526 patents filed by PCT until December 2019 were investigated up to the subclass level of the IPC code. As a result, in the case of South Korea, representative IPC codes are in the order of G06Q, H04L, G06F, H04W, and the highest frequency of interconnection is H04L→H04W, H04W→H04L, H04W→H04B. In China, the representative IPC codes are in the order of H04L, H04W, G05B, G06Q. South Korea has strong technological convergence centered on the G06Q, while China has strong convergence centered around H04L and H04W. Moreover, in China, H04L and H04W have more diverse combinations than in South Korea in Section A, B, G, and H. In the future, it is necessary to study the diversity of technology convergence of H04L and H04W in China.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.297-304
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• 2021

This study aims not only to access the visual thought-oriented approach that has been implemented in established art therapy and education but also to integrate language education and therapeutic approach to support the development of school-age children. Thus, text mining technique was applied to search for areas where different areas of language and art can be integrated. This research was conducted in accordance with the procedure of basic research, preliminary DB construction, text screening, DB pre-processing and confirmation, stop-words removing, text mining analysis and the deduction about the convergent areas. These results demonstrated that this study draws convergence areas related to regional, communication, and learning functions, areas related to problem solving and sensory organs, areas related to art and intelligence, areas related to information and communication, areas related to home and disability, topics, conceptualization, peer-related areas, integration, reorganization, attitudes. In conclusion, this study is meaningful in that it established a framework for designing an activity-centered convergence program of art and language in the future and attempted a holistic approach to support child development.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.541-549
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• 2020

This study conducts differential analysis on the financial positions of Korean shipping companies before and after the bankruptcy of the H carrier, looking specifically at their financial ratios, profit and loss patterns, and other factors related to their financial operation. Firstly, it was discovered that major measures of financial health, such as average assets per carrier, were not affected by the bankruptcy of the H carrier. However, despite this, most carriers experienced large changes in profits and losses, with total sales and shipping revenues averaging 424.5 billion won and 381.7 billion won respectively before the bankruptcy, but falling by half to 252.1 billion won and 234.6 billion won after the bankruptcy. Additionally, charter revenues and expenses also dropped by more than half. EBIT/sales and pre-tax revenue margins were also heavily affected after the bankruptcy, with both figures averaging 8% and 3% respectively before the bankruptcy, but falling into the negative range at -2% and -8% post-bankruptcy, resulting in significant deterioration in operational profitability. The study concludes that there is an urgent need to establish a global sales network, improve cost structures, and consistently secure stable cargo in order to increase Korean carriers' profitability. Of all financial measures, liquidity and total asset efficiency were identified as the most severely-impacted by the H carrier bankruptcy, thereby requiring the most pressing policy addressing.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.