The air dilution olfactory method to measure complex odors needs to store and carry odor samples from the field sampling until the analysis in laboratories. Until the analysis of sample in the laboratory, odor dilution factor (odor sensitivity) in the sample bag may decrease over time depending on the characteristics of each odor substances. This is one of the limitation for the air dilution olfactory method. Thus, the air dilution device enable to measure without loss in complex odors of samples. Recently, many studies on the performance test of on-site air dilution devices, i.e., field olfactometer, has been conducted to figure out the feasibility of the field olfactometers. In this study, seven odor samples were collected from five odor emission source sites. And comparative analysis with the air dilution olfactory method was carried out to assess the field applicability of the olfactometer. As results, the performance of the field olfactometer used in this study is regared as the affordable method. The dilution factors from between two methods showed the similar values, indicating low values of standard deviations. In order to ensure the accuracy and precision of measurement data using the field olfactometer, methodology minimized variables (that may affect measurement) needs to establish.

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., thermometers, irradiance sensors, and soil moisture sensors) is installed in the APV system. This study aims at introducing a simulation-based decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and simulation-based performance estimation. Particularly, an agent-based simulation (ABS) is used to mimic functions of an APV system so that a data-driven function and digital twin environment are implemented in the proposed system. The ABS model is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the digital twin technology in the field of agriculture.

Iron-based amorphous powder attracts increasing attention because of its excellent soft magnetic properties and low iron loss at high frequencies. The development of an insulating layer on the surface of the amorphous soft magnetic powder is important for minimizing the eddy current loss and enhancing the energy efficiency of highfrequency devices by further increasing the electrical resistivity of the cores. In this study, a hybrid insulating coating layer is investigated to compensate for the limitations of monolithic organic or inorganic coating layers. Fe2O3 nanoparticles are added to the flexible silicon-based epoxy layer to prevent magnetic dilution; in addition TiO2 nanoparticles are added to enhance the mechanical durability of the coating layer. In the hybrid coating layer with optimal composition, the decrease in magnetic permeability and saturation magnetization is suppressed.