• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.635-638
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• 2014

As ICT-convergence deploying projects in horticulture sector has been promoted, the concerning technology development and market has recently been enlarged. In particular, the domestic and overseas products for a variety of horticulture complex environmental control equipments has been produced and sold, but it can be seen that there is no the compatibility among the products and is differences in performance. There is the need to provide a standard of the specifications and installation criteria for domestic products in order to promote ICT convergence deploying projects in the horticulture field and provide convenience to the consumers through the compatibility among products under this circumstances. In this paper, we suggest the standardization items which our country can lead and the directions for future standardization by analyzing the introducing situation and the trend of Technology and standardization for complex environmental control system in domestic horticulture field.

• Journal of Platform Technology
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• v.11 no.5
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• pp.16-22
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• 2023

There is a growing interest in facial age estimation because many applications require age estimation techniques from facial images. In order to estimate the exact age of a face, a technique for extracting aging features from a face image and classifying the age according to the extracted features is required. Recently, the performance of various CNN-based deep learning models has been greatly improved in the image recognition field, and various CNN-based deep learning models are being used to improve performance in the field of facial age estimation. In this paper, age estimation performance was compared by learning facial features based on various CNN-based models such as AlexNet, VGG-16, VGG-19, ResNet-18, ResNet-34, ResNet-50, ResNet-101, ResNet-152. As a result of experiment, it was confirmed that the performance of the facial age estimation models using ResNet-34 was the best.

• Journal of Platform Technology
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• v.11 no.4
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• pp.50-61
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• 2023

The advancement of various big data technologies has had a tremendous impact on many industries. Diverse big data research studies have been conducted to process and analyze massive data quickly. Under these circumstances, new emerging technologies such as high-capacity persistent memory (PMEM) and Compute Express Link (CXL) have lately attracted significant attention. However, little investigation into a big data "search" platform has been made. Moreover, most big data software platforms have been still optimized for traditional DRAM-based computing systems. This paper first evaluates the basic performance of Intel Optane PMEM, and then investigates both indexing and searching performance of Elasticsearch, a widely-known enterprise big data search platform, on the PMEM-based computing system to explore its effectiveness and possibility. Extensive and comprehensive experiments shows that the proposed Optane PMEM-based Elasticsearch achieves indexing and searching performance improvement by an average of 1.45 times and 3.2 times respectively compared to DRAM-based system. Consequently, this paper demonstrates the high I/O, high-capacity, and nonvolatile PMEM-based computing systems are very promising for big data search platforms.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.3
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• pp.49-54
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• 2020

To attach a stretchable/flexible electrode to something or something to on electrode, conductive adhesives must be stretchable/flexible to suit the properties of the electrode. In particular, conductive adhesive require durability and heat resistance, and unlike conventional adhesives, they should also have conductivity. To this end, Epoxy, which has good strength and adhesion, was selected as an adhesive, and a plasticizer and a reinforcement were mixed instead of a two-liquid material consisting of a conventional theme and a hardener, and a four-liquid material was used to give stretchability/flexibility to high molecules. The conductive filler was selected as silver, a material with low resistance, and for high conductivity, three shapes of Ag particles were used to increase packing density. Conductivity was compared with these developed conductive adhesives and two epoxy-based conductive adhesives being sold in practice, and about 10 times better conductivity results were obtained than products being actually sold. In addition, conductivity, mechanical properties, adhesion and strength were evaluated according to the presence of plasticizers and reinforcement agent. There was also no problem with 60% tensile after 5 minutes of curing at 120℃, and pencil hardness was excellently measured at 6H. As a result of checking the adhesion of electrodes through 3M tape test, all of them showed excellent results regardless of the mixing ratio of binders. After attaching the Cu sheet on top of the electrode through conductive adhesive, the contact resistance was checked and showed excellent performance with 0.3 Ω.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.67-85
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• 2015

This study investigates the relationships among SMEs' innovation capacity, standardization education activities, and performances. Employing about 900 SMEs in the ICT and electronics electricity industries, this study used regression analysis and examined the effects of standardization education activities on performance and the moderating effect of innovation capacity. The results indicate that standardization education activities positively affect SMEs' production and quality improvement and R&D activity improvement. The results also show that R&D investment ratio moderates the relationship between standardization education and production and quality improvement. This study provides practical insight into why firm managers should pay attention to standardization education and innvation capacity to improve firm performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.578-578
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• 2016

In the past decade, many countries developed varies promising theories, methodologies and technologies for water resources management, such as Smart Water in Korea, eWater in Australia, Intelligent Water in Untied States, and Internet of Water in China. It is no exaggeration to say that Smart Water Management(SWM) will have a major role to play in addressing the global water challenges in the background of climate change, population growth and rapid urbanization. As a result, we can see major shifts taking place in the structure of the water industry, with a need for new approaches, skills, and water management policies. All these point towards a brighter future for the smart water sector and a new water paradigm, with applications and potential throughout the water cycle. However, each countries have their technology and industry standard system which may swift similar innovation and technology into different channels. In that sense, developing a common performance index and standard docking adapter for assessing Smart Water Management Initiatives(SWMI) is crucial for drawing a linkage of SWMI and SWMs to a way to implement advanced technology across Asia and Pacific. The performance index and standard docking adapter will facilitate quantitative and qualitative effects of utilized SWM techniques.

• International Journal of Contents
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• v.10 no.2
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• pp.1-8
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• 2014

This paper discusses designing an interdisciplinary learning environment to promote learning of the liberal arts for advanced music students in order to expand the boundaries of their education experience beyond the technical mastery of their musical instruments. The paper discusses the utilization of salient features of information, communications, and technology and the use of instructional theory to promote the understanding of how individual pieces of music can be connected to knowledge of the context in which they were created to support the understanding of the relationship between experience in the world and musical composition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3083-3098
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• 2023

As demands for efficient and echo-friendly production of marine products increase, smart aquaculture based on information and communication technology (ICT) has become a promising trend. The smart aquaculture is expected to control fundamental farm environment variables including water temperature and dissolved oxygen (DO) levels with less human intervention. A recirculating aquaculture system (RAS) is required for the smart aquaculture which utilizes a purification tank to reuse water drained from the water tank while blocking the external environment. Elaborate water treatment should be considered to properly operate RAS. However, analyzing the water treatment performance is a challenging issue because fish farm circumstance continuously changes and recursively affects water fluidity. To handle this issue, we introduce computational fluid dynamics (CFD) aided water treatment analysis including water fluidity and the solid particles removal efficiency. We adopt RAS parameters widely used in the real aquaculture field to better reflect the real situation. The simulation results provide several indicators for users to check performance metrics when planning to select appropriate RAS without actually using it which costs a lot to operate.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.