• Journal of The Korean Society of Grassland and Forage Science
• /
• v.40 no.4
• /
• pp.196-202
• /
• 2020

Rye, whole-crop barley and Italian Ryegrass are major winter forage species in Korea, and yield monitoring of winter forage species is important to improve forage productivity by precision management of forage. Forage monitoring using Unmanned Aerial Vehicle (UAV) has offered cost effective and real-time applications for site-specific data collection. To monitor forage crop by multispectral camera with UAV, we tested four types of vegetation index (Normalized Difference Vegetation Index; NDVI, Green Normalized Difference Vegetation Index; GNDVI, Normalized Green Red Difference Index; NGRDI and Normalized Difference Red Edge Index; NDREI). Field measurements were conducted on paddy field at Naju City, Jeollanam-do, Korea between February to April 2019. Aerial photos were obtained by an UAV system and NDVI, GNDVI, NGRDI and NDREI were calculated from aerial photos. About rye, whole-crop barley and Italian Ryegrass, regression analysis showed that the correlation coefficients between dry matter and NDVI were 0.91~0.92, GNDVI were 0.92~0.94, NGRDI were 0.71~0.85 and NDREI were 0.84~0.91. Therefore, GNDVI were the best effective vegetation index to predict dry matter of rye, wholecrop barley and Italian Ryegrass by UAV system.

• Nuclear Engineering and Technology
• /
• v.54 no.7
• /
• pp.2592-2598
• /
• 2022

Research groups in the field of PET instrumentation are studying time-of-flight(TOF) technology to improve the signal-to-noise ratio of PET images. Scintillation light transport and collection plays an important role in improving the coincidence resolving time(CRT) of PET detector based on a pixelated crystal array. Four crystal arrays were designed by the different optical reflection configuration such as external reflectors and surface treatment on the CRT and compared with the light output, energy resolution and CRT. The design proposed in the study was composed of 8 × 8 LYSO crystal array consisted of 3 × 3 × 15 mm³ pixels. The entrance side was roughened while the other five surfaces were polished. Four sides of all crystal pixels were wrapped with ESR-film, and the entrance surface was covered by Teflon-tape. The design provided an excellent timing resolution of 210 ps and improved the CRT by 16% compared to the conventional method using a polishing treatment and ESR-film. This study provided a method for improving the light output and CRT of a pixelated scintillation crystal-based brain TOF PET detector. The proposed configuration might be an attractive detector design for TOF brain PET requiring fast timing performance with high cost-effectiveness.

• Journal of KIBIM
• /
• v.12 no.4
• /
• pp.61-69
• /
• 2022

Earthmoving operations account for approximately 25% of construction cost, generally executed prior to the construction of buildings and structures with heavy equipment. For the successful completion of earthwork projects, it is crucial to constantly monitor earthwork equipment (e.g., trucks), estimate productivity, and optimize the construction process and equipment on a construction site. Traditional methods however require time-consuming and painstaking tasks for the manual observations of the ongoing field operations. This study proposed the use of a GPS sensor embedded in a smartphone for the tracking and visualization of equipment locations, which are in turn used for the estimation and simulation of cycle times and production rates of ongoing earthwork. This approach is implemented into a digital platform enabling real-time data collection and simulation, particularly in a 2D (e.g., maps) or 3D (e.g., point clouds) virtual environment where the spatial and temporal flows of trucks are visualized. In the case study, the digital platform is applied for an earthmoving operation at the site development work of commercial factories. The results demonstrate that the production rates of various equipment usage scenarios (e.g., the different numbers of trucks) can be estimated through simulation, and then, the optimal number of tucks for the equipment fleet can be determined, thus supporting the practical potential of real-time sensing and simulation for onsite equipment management.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1105-1112
• /
• 2022

Field data monitoring systems such as renewable energy generation and smart farm integrated control are developing from PC and server to mobile first, and various wireless communication and application services have emerged with the development of IoT technology. Low-power wide-area networks are services optimized for low-power, low-capacity, and low-speed data transmission, and data collected in the field is transmitted to designated storage servers or cloud-based data platforms, enabling data monitoring. In this paper, we implement an IoT repeater that collects field data with a single device and transmits it to a wireless carrier cloud data flat using a low-power wide-area network, and a monitoring app using it. Using this, the system configuration is simpler, the cost of deployment and operation is lower, and effective data accumulation is possible.

• Fisheries and Aquatic Sciences
• /
• v.25 no.11
• /
• pp.537-548
• /
• 2022

Apparent digestibility coefficients (ADCs) of dry matter, crude protein, crude lipid, nitrogen-free extract, energy and essential amino acids in animal-based feed ingredients were determined for olive flounder (Paralichthys olivaceus). A reference diet (RF) was formulated to contain 1.0% chromic oxide (Cr₂O₃) as an inert indicator. Nine test diets were formulated to contain RF and one of the feed ingredients (pollock meal [PM], jack mackerel meal [JMM], anchovy meal [AM], cod meal [CM], sardine meal [SM], sand eel meal [SEM], tuna meal [TM], meat meal [MM] and squid liver meal [SLM]) at a 7:3 ratio in each diet designated as PM, JMM, AM, CM, SM, SEM, TM, MM and SLM, respectively. Olive flounder, averaging 150 ± 8.0 g, were stocked at a density of 25 fish per tank in 400-L fiberglass tanks attached with fecal collection columns. Feces were collected from triplicate groups of fish one time a day for four weeks. Dry matter and crude protein ADCs of CM and SEM were significantly higher than the other tested ingredients. Lipid ADCs of JMM, CM and SEM were significantly higher than the other test ingredients. Energy ADCs of CM and SEM were significantly higher than that of the other tested ingredients. The availability of amino acids in CM was generally higher than the other animal protein sources. PM exhibited the lowest amino acid availability among the treatments. Interestingly, MM exhibited significantly higher nutrient digestibility than several marine-based ingredients. However, CM and SEM are seeming to be highly digestible and effective to use in olive flounder diet compared to the other tested ingredients. Overall, the results of this study provide information about the bioavailability of nutrients and energy in animal feedstuffs to apply when formulating cost-effective practical feeds for olive flounder.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.334-334
• /
• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Journal of Practical Engineering Education
• /
• v.14 no.3
• /
• pp.565-572
• /
• 2022

Card sorting is a useful data collection method for understanding users' perceptions of relationships between items. In general, card sorting is an intuitive and cost-effective technique that is very useful for user research and evaluation. In this study, the core competencies of each field were used as competency cards used in the next stage of card sorting for course development, and the clustering results were derived by applying the K-means algorithm to cluster the results. As a result of card sorting, competency clustering for core competencies for each occupation in each field was verified based on Participant-Centric Analysis (PCA). For the number of core competency cards for each occupation, the number of participants who agreed appropriately for clustering and the degree of card similarity were derived compared to the number of sorting participants.

• Korea Trade Review
• /
• v.47 no.4
• /
• pp.69-88
• /
• 2022

Recently, International commerce has continuously expanded with the development of logistics technology. However, the cost of international logistics is rising rapidly. The Korea International Trade Association (2021) proposes that the use of international commercial terms in Incoterms® could be an effective way against logistics costs. The purpose of this study is to verify the effect on the flexible operation of international commercial terms. For the detection of variables and data collection for empirical analysis based on previous studies and in-depth interviews. The questionnaires were distributed after pilot-study to a random sample of companies based on the list of members such as the Korea International Trade Association, the Korea Trade-Investment Promotion Agency, and the Global Small and Medium Business Association. A total of 800 questionnaires were distributed, and 166 were used for empirical analysis. The results of this study are as follows. First, mutual cooperation and Flexibly using of international commercial terms has a positive (+) effect on logistics efficiency. This is in line with the study of Yang (2021) and Stojanović et al. (2021) that logistics by using international commercial terms will increase the efficiency of logistics. Second, use of international commercial terms based on mutual understanding mediates the relationship between the logistics environment of the other country and the logistics efficiency. As in the study of Vidrova (2020), it is important to operate on international commercial terms mutually.

• Information Systems Review
• /
• v.22 no.1
• /
• pp.113-124
• /
• 2020

In the operation of farms, it is very important to evaluate the quality of harvested crops and to classify defective products. However, farmers have difficulty coping with the cost and time required for quality assessment due to insufficient capital and manpower. This study thus aims to detect defects by analyzing the epidermis of fruit using deep learning algorithm. We developed a model that can analyze the epidermis by applying YOLOv3 algorithm based on Region Convolutional Neural Network to video images of peach. A total of four classes were selected and trained. Through 97,600 epochs, a high performance detection model was obtained. The crop failure detection model proposed in this study can be used to automate the process of data collection, quality evaluation through analyzed data, and defect detection. In particular, we have developed an analytical model for peach, which is the most vulnerable to external wounds among crops, so it is expected to be applicable to other crops in farming.

• Asia pacific journal of information systems
• /
• v.30 no.3
• /
• pp.568-589
• /
• 2020

Recently, Social media has become a concern for businesses, including Small and Medium Enterprises (SMEs). SMEs began to adopt social media to support their performance. To benefit from the application of social media, SMEs must implement the right strategy. This study aims to analyze the factors that influence the use of social media in SMEs. Furthermore, alignment between social media functionalities and strategies and their effect on SME's performance are investigated. A case study is conducted in Gymi, a garment SMEs in East Java, Indonesia. The data collection includes interviews with the owner of SMEs, observations, and document analysis. Data analysis is performed by pattern matching, which matches the patterns from the literature with data from the case study. The results of this study show that cost-effectiveness, interactivity, and compatibility are factors that influence the use of social media in Gymi. The social media used by Gymi are Instagram, Facebook, YouTube, WhatsApp, and LINE. However, the main social media used to support Gymi's functions is Instagram. Gymi has a relatively good social media strategy as it has defined a specific goal, target audience, and channel selection for social media (Instagram). It also has specific resources and policies to handle social media. Gymi monitors and evaluates their social media content activities. These strategies are aligned with the Instagram feature used to support Gymi's function, particularly marketing, sales, customer service, and to some extent, internal operation. The alignment contributes to Gymi's performance measured by the increase in reputation (number of Instagram followers) and sales.