• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.1
• /
• pp.37.1-37.1
• /
• 2019

The faint quasars with M1450 > -24 mag are known to hold the key to the determination of the ultraviolet emissivity for the cosmic reionization. But only a few have been identified so far because of the limitations on the survey data. Here we present the first results of the z ~ 5 faint quasar survey with the Infrared Medium-deep Survey (IMS), which covers ${\sim}100deg^2$ areas in J band to the depths of $J_{AB}$ ~ 23 mag. To improve selection methods, the medium-band follow-up imaging has been carried out using the SED camera for QUasars in Early uNiverse (SQUEAN) on the Otto Struve 2.1 m Telescope. The optical spectra of the candidates were obtained with 8 m class telescopes. We newly discovered 10 quasars with -25 < $M_{1450}$ < -23 at z ~ 5, among which three have been missed in a previous survey using the same optical data over the same area, implying the necessity for improvements in high-redshift faint quasar selection. We derived photometric redshifts from the medium-band data and found that they have high accuracies of ${\langle}{\mid}{\Delta}z{\mid}/(1+z){\rangle}=0.016$. The medium-band-based approach allows us to rule out many of the interlopers that contaminate ${\geq}20%$ of the broadband-selected quasar candidates. These results suggest that the medium-band-based approach is a powerful way to identify z ~ 5 quasars and measure their redshifts at high accuracy (1%-2%). It is also a cost-effective way to understand the contribution of quasars to the cosmic reionization history.

• Journal of Animal Science and Technology
• /
• v.66 no.1
• /
• pp.31-56
• /
• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Korean Journal of Environmental Agriculture
• /
• v.15 no.1
• /
• pp.91-104
• /
• 1996

The viability loss or death of weed seeds buried in soil can be induced by infrared irradiation which has good penetration in moist soil. By using this principle of pre-emergence soil-treatment, the study was carried out to obtain basic information needed to develop the effective weed control method for the production of less polluted agricultural products. An apparatus for irradiating infrared was constructed by using ceramic material with high emissivity. The LPG was used as fuel for producing infrared by heating ceramic material. The soil heated in this study was loam with four levels of moisture contents (0.6, 5.7, 10.7, 15.1 % wb). The temperature distribution was measured at various soil depths when soil with different moisture content was irradiated with infrared for three different times (30, 60, 90 sec). The soil depths with duration time of minimum 3 minutes over $80^{\circ}C$, temperature inducing viability loss of weed seeds, were investigated. When the moisture content of soil was 0.6 and 5.7 % wb, the soil depths which can induce viability loss of weed seeds was greatly increased with increasing irradiation time. However, any depths of soil tested in this study was not reached to the temperature of $80^{\circ}C$ when 30 seconds of irradiation time was applied on soil with moisture content of 10.7 or 15.1 % wb. Generally, the soil depth needed for viability loss of weed seeds was decreased with increasing moisture content of soil. Also, longer irradiation time was required to induce viability loss of weed seeds with increasing moisture content of soil.