• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.651-658
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• 2021

In this paper, we propose methods for character recognition and classification for table items through deep learning. First, table areas are detected in a document image through CNN. After that, table areas are separated by separators such as vertical lines. The text in document is recognized through a neural network combined with CNN and RNN. To correct errors in the character recognition, multiple candidates for the recognized result are provided for a sentence which has low recognition accuracy.

• Annual Conference of KIPS
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• 2013.05a
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• pp.435-437
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• 2013

본 논문은 육상 기지국(상용 기지국)과 해안 기지국(UC-2), 해상 이동형 기지국(UE-2-N, 예: 선박)과의 무선 통신 라우팅 정보 산출을 위한 ad-hoc 통신과 관련한 것이다. 육상 기지국(상용기지국)과 해안 기지국(UE-2)과의 연결 경로, 해안 기지국(UE-2)와 해상 이동형 기지국(UE-3-N)과의 연결 경로를 확보하기 위하여 각각의 기지국(UE-2/UE-3-N)들의 출력 정보와 위치정보(벡터 값으로 표현)를 이용한 최적 라우팅 정보 산출 확대 관리 방법에 관한 것이다.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.113-117
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• 2021

The data gathering delay and the network lifetime are important indicators to measure the service quality of wireless sensor and actuator networks (WSANs). This study proposes a dynamically cluster head (CH) selection strategy and automatic scheduling scheme of collectors for prolonging the network lifetime and shorting data gathering delay in WSAN. First the monitoring region is equally divided into several subregions and each subregion dynamically selects a sensor node as CH. These can balance the energy consumption of sensor node thereby prolonging the network lifetime. Then a task allocation method based on genetic algorithm is proposed to uniformly assign tasks to actuators. Finally the trajectory of each actuator is optimized by ant colony optimization algorithm. Simulations are conducted to evaluate the effectiveness of the proposed method and the results show that the method performs better to extend network lifetime while also reducing data delay.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.695-702
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• 2022

In this paper, we propose the method of a table structure recognition in various table types for document processing automation. A table with items surrounded by ruled lines are analyzed by detecting horizontal and vertical lines for recognizing the table structure. In case of a table with items separated by spaces, the table structure are recognized by analyzing the arrangement of row items. After recognizing the table structure, the areas of the table items are input into OCR engine and the character recognition result output to a text file in a structured format such as CSV or JSON. In simulation results, the average accuracy of table item recognition is about 94%.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.258-269
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• 2022

In these days, innovative functions are required to unmanned parcel delivery lockers. As non-face-to-face transactions become the center due to the recent COVID-19 pandemic, many problem occurs in society such as theft crimes and lack of loading space. Therefore, New concept storage device is developed in korea. It has the functions that minimizes empty spaces by using the internal transport device to enable efficient space loading and refrigerate goods such as foods. In order to systematically approach the system design of the unmanned parcel delivery lockers which is the new function is applied, We applied model-based system engineering to improve the development efficiency and use a system modeling language to express the system. We conducted interworking research of CAD data including system modeling and design data. it is expected that this method will increase the effective development efficiency such as maintenance traceability and reduction of development period and cost.

• ETRI Journal
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• v.45 no.2
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• pp.329-337
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• 2023

For safe last-mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time-series data in a complementary fashion to minimize errors. A long short-term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.559-567
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• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.143-165
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• 2020

The rapid growth of economic transactions generated by live streaming broadcasts ("LSB") has created opportunities for retailers to increase sales. However, little is known about what impact LSB celebrities have on customers and what causes LSB celebrities to become famous. This study aimed to fill this gap by studying the economics of LSBs. This study was conducted through a para-social relationship and attractiveness theory framework. Consequently, social and task attraction were assumed to be the antecedents of the para-social relationship that induced purchase intention. This study examined the impact of relationship rewards, self-disclosure, affective interactivity, informative interactivity, and the amount of information provided on purchase intentions through LSB. Celebrities can use the results of this study to enhance their appeal to fans and promote customers' purchase on e-commerce. This study contributed to the IS field by investigate the impact of para-social relationship on the online shopping context.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.87-93
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• 2016

In the current information-based society, information and communication technology(ICT) is very important for an individual, a society, and a nation. Especially, for a nation, ICT-related industries are forming an important part of a nation's economy. Also, unlike other industries, ICT-related industries do not require various infrastructures, and have an advantage of being developed with a few talented persons in a short period of time. In this sense, identification and education of gifted children in IT become an essential task of a nation's future. In the past, selection of the gifted children was based on paper tests. However, paper tests incurred various side effects such as private education. Since 2013, observation-recommendation system instead of paper tests has been fully adopted. The purpose of this paper is to analyze the validity of observation-recommendation admission system of the gifted children in IT. For this research purpose, the gifted children in gifted science education center attached in a university at Seoul become the focus of the samples. Their entrance score ranking and graduation record raking are compared for analysis of validity of admission system. After statistical analysis, there is a meaningful correlation between entrance score ranking and graduation record ranking for the gifted children in IT. It means that the higher entrance score ranking, the higher graduation record ranking. The analysis results are expected to be valuable baseline data for deciding usefulness of observation-recommendation admission system.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.99-107
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• 2015

In this era of smart convergent environment wherein all industries are converged on ICT infrastructure and industries and cultures come together, the information and communication construction business is becoming more important. For the information and communication construction business to continue growing, it is very important to ensure that technical manpower is stably supplied. To date, however, there has been no theoretically methodical analysis of manpower supply and demand in the information and communications construction business. The need for the analysis of manpower supply and demand has become even more important after the government announced the road map for the development of construction business in December 2014 to seek measures to strengthen the human resources capacity based on the mid- to long-term manpower supply and demand analysis. As such, this study developed the manpower supply and demand forecast model for the information and communications construction business and presented the result of manpower supply and demand analysis. The analysis suggested that an overdemand situation would arise since the number of graduates of technical colleges decreased beginning 2007 because of fewer students entering technical colleges and due to the restructuring and reform of departments. In conclusion, it cited the need for the reeducation of existing manpower, continuous upgrading of professional development in the information and communications construction business, and provision of various policy incentives.