• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.3
• /
• pp.197-209
• /
• 2020

Signboards are installed in different types and sizes depending on the shop characteristics. However, the local government is having difficulty managing signboards with frequent opening and closing of stores and insufficient management personnel. In this study, a methodology was proposed to standardize and efficiently manage signboard information. To this end, the signboard display method of the enforcement ordinance related to outdoor advertising was analyzed to define the attribute elements of standard signboard data. In addition, physical information of signboards was obtained through signboard recognition technology, which is a prior study, and attribute elements of signboard standard data were defined through information that can be read with the naked eye, building integration information of the Ministry of the Interior and Safety, and street name address. In order to standardize the signboard information by spatial characteristics, data product specifications and metadata were defined according to the national spatial information standard. Lastly, standard data for signboards were produced in XML (Extensible Markup Language) format for compatibility, and XSD (XML Schema Definition) was defined for XML integrity so that data validity could be verified. Through this, a standard data model for the informatization of signboards was designed.

• Journal of Practical Engineering Education
• /
• v.8 no.1
• /
• pp.63-68
• /
• 2016

As job mismatch intensifies in the employment market, the work based learning has emerged as a solution to this social problem. The so called Korean dual education system is expected to raise jobseekers equipped with knowledge and skills demanded by industry. This study intends to recommend an effective operational model for contracted education programs at higher institutions in order to support soft landing of Korean dual education system. Students of contracted education programs are adults graduated from vocational high schools and working for companies during weekdays. In consideration of the difficulties experienced by employee students, more flexible operation of academic affairs is required. To address these challenges, the recommended contracted education model includes such beneficial features as S-OJT courses, standard curriculum based on National Competency Standard, recognition of prior learning, flipped classroom, and tutoring system. In the last part, several directions for implementing the new contracted education model are discussed.

• Journal of Korea Technology Innovation Society
• /
• v.12 no.1
• /
• pp.137-164
• /
• 2009

As a means to address the modes of developing institutional evaluation system aimed at improving performances of GRIs, this study looked into the influential relations where institutional evaluation system has an impact on receptivity of evaluation outcomes and performances of institutes optimize their performances. After making analysis, it was confirmed that the National Research Council for Economics, Humanities and Social Sciences' institutional evaluation system for GRIs had a positive (+) influence on performances of research institutes, and receptivity of evaluation outcomes is related to performances of research institutes. In addition, it was also confirmed that institutes with high performances, in general, have high level of receptivity of evaluation outcomes along with positive recognition of institutional evaluation system. However, weaknesses of the Council's institutional evaluation system for GRIs resulted in low level of receptivity amongst GRIs, and thus there is limitation on the government and the Council in the active utilization of evaluation outcomes. Finally, it addressed the limitations and areas for improvement in relation to research outcomes.

• Smart Media Journal
• /
• v.8 no.4
• /
• pp.33-37
• /
• 2019

Because the ECG signals are time-series data acquired as time elapses, it is important to obtain comparative data the same in size as the enrolled data every time. This paper suggests a network model of GAN (Generative Adversarial Networks) based on an auxiliary classifier to generate synthetic ECG signals which may address the different data size issues. The Cosine similarity and Cross-correlation are used to examine the similarity of synthetic ECG signals. The analysis shows that the Average Cosine similarity was 0.991 and the Average Euclidean distance similarity based on cross-correlation was 0.25: such results indicate that data size difference issue can be resolved while the generated synthetic ECG signals, similar to real ECG signals, can create synthetic data even when the registered data are not the same as the comparative data in size.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.4
• /
• pp.73-93
• /
• 2019

This study empirically analyzed the recognition and current status of university libraries related to the legal deposit of thesis and dissertation and investigated the ways to activate legal deposit to National Assembly Library. As a result, most universities conduct legal deposit of thesis and dissertation. However, most librarians face difficulties resulted from the duplication of deposits to many institutions. In the case that the deposits are not made, the main reasons are the university library's policies, duplication and inefficiency of the deposit procedures, and the limitation of obtaining copyright agreements. In order to address these limitations and to maximize the social and informational values of thesis and dissertation, this research proposed approaches to legal deposit of thesis and dissertation, including strengthening digital deposit system through the establishment of independent legal deposit law, preparing the effective ways of preservation. constructing an integrated deposit system, and developing professional collection of thesis and dissertation which can consolidate National Assembly Library.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.2
• /
• pp.179-186
• /
• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.146-151
• /
• 2021

Currently, the demand for vehicles from one family is increasing in many countries at home and abroad, reducing the number of people on the vehicle and increasing the number of vehicles on the road. The multi-passenger lane system, which is available to solve the problem of traffic congestion, is being implemented. The system allows police to monitor fast-moving vehicles with their own eyes to crack down on illegal vehicles, which is less accurate and accompanied by the risk of accidents. To address these problems, applying deep learning object recognition techniques using images from road sites will solve the aforementioned problems. Therefore, in this paper, we compare and analyze the performance of existing deep learning models, select a deep learning model that can identify real-time vehicle occupants through video, and propose a vehicle occupancy detection algorithm that complements the object-ident model's problems.

• Journal of Drive and Control
• /
• v.17 no.4
• /
• pp.23-30
• /
• 2020

Driving on irregular and inclined roads using agricultural machinery such as spraying machines or trucks in orchards causes farmer casualties associated with the overturning of agricultural machinery. In addition, the harm to agricultural workers caused by the excessive inhalation of the scattered pesticide frequently occurs during pest control processes. To address these problems, we introduced precision agricultural technology that could selectively spray pesticides only where the fruit is present by recognizing the presence or shape of the fruit in the orchard. In this paper, a 16-channel LIDAR (VLP-16) made of Velodyne was used to identify the shape of fruit trees. Solenoid valves were attached to the end parts of 12 nozzles of the orchard spraying machine for on/off control. The smart spraying machine implemented in this way was mounted on a vehicle capable of autonomous travel and performed selective control depending upon the shape of the fruit trees while traveling in the orchards. This is expected to significantly reduce the amounts of pesticides used in orchards and production costs.

• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.89-104
• /
• 2021

Food delivery service combined with IT technology and HMR (Home Meal Replacement) are rapidly growing due to the COVID-19. Recently, the demand for salads along with HMR has increased among office workers in their 20s and 30s who are interested in health and beauty. Freshcode is a food startup with 6 years of experience that started selling salad products through O2O service. Freshcode applied for a patent for a service that collects orders from nearby areas and delivers them on the same day to a designated delivery address 'FCOSPOT' to save shipping costs. In March 2021, in recognition of the growth potential of the regular delivery service, Freshcode received an investment of 6 billion won in Series A. This study may have practical implications to early-stage startups and scale-up stage startups through a longitudinal case study on the growth of a single company. As for the research method, the lean startup methodology and lean canvas were used in the early stage of startup. In particular, the process of the build-measure and learn feedback-loop, which is the core of lean startup methodology, was applied to each major decision-making step. In the scale-up stage after 5 years, the business model canvas was used to schematize the growth as a food online O2O platform to verify continuous innovation. This case study has three main findings. First, the idea of 'FCOSPOT' was successfully implemented through the Lean Startup methodology. Second, Freshcode demonstrated the scalability of the differentiated business model of shared base delivery O2O. Third, a key factor of success was the digital integrated communication operation strategy that maximizes the experience for the created customers.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.8
• /
• pp.365-370
• /
• 2023

This paper aims to compare the performance of speech data classification into two groups, adult and elderly, based on the acoustic and linguistic characteristics that change due to aging, such as changes in respiratory patterns, phonation, pitch, frequency, and language expression ability. For acoustic features we used attributes related to the frequency, amplitude, and spectrum of speech voices. As for linguistic features, we extracted hidden state vector representations containing contextual information from the transcription of speech utterances using KoBERT, a Korean pre-trained language model that has shown excellent performance in natural language processing tasks. The classification performance of each model trained based on acoustic and linguistic features was evaluated, and the F1 scores of each model for the two classes, adult and elderly, were examined after address the class imbalance problem by down-sampling. The experimental results showed that using linguistic features provided better performance for classifying adult and elderly than using acoustic features, and even when the class proportions were equal, the classification performance for adult was higher than that for elderly.