• Food Science of Animal Resources
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• v.32 no.2
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• pp.133-141
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• 2012

This study was carried out to investigate the effects of substitution of fermented king oyster mushroom (P. eryngii) by-products diet on pork meat quality characteristics, during the storage. A mixture of 40% king oyster mushroom by-products, 28% soybean meal and 20% corn was fermented for 10 d, and the basal diet was then substituted by the fermented diet mixture of up to 20, 50 and 80%, respectively. A total of 96 pigs were fed experimental diet (8 pigs per pen ${\times}$ 4 diets ${\times}$ 3 replication), and eight longissiumus (LD) per treatment were collected, when each swine reached to 110 kg of body weight. The Warner-Bratzler shear forces and cooking loss were significantly lowered in the treatments, while crude protein content and water holding capacity significantly (p<0.05) increased in the treatments than in the control group. The volatile basic nitrogen (VBN), at 1 d of storage, was lower in the treatments, while texture profiles and sensory evaluation did not differ between the control and the treatments (p>0.05). The pH, thiobarbituric acid reactive substances (TBARS), VBN and meat color in all treatments were increased as storage increased. Fermented king oyster mushroom by-products diet effects on lightness (CIE $L^*$), yellowness (CIE $b^*$) and chroma were determined, when LD muscles in T2 and T3 treatments were higher (p<0.05), up to 7 d (p<0.05). Therefore, the results indicate that the substitution of the fermented king oyster mushroom by-products diet to swine diet influenced the quality of the meat and it may be an economically valuable ingredient.

• Current Optics and Photonics
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• v.3 no.5
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• pp.429-437
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• 2019

Temperature adaptability is an important metric for evaluating the performance of an optical system. The temperature characteristics of the optical system are closely related to the material and shape of its lens. In this paper, we establish a mathematical model relating the temperature characteristics to the shape and material of the lens. Then a novel assembly structure that can solve the lens constraint and positioning problem is proposed. From those basics, the correctness of the theoretical model and the effectiveness of the assembly structure are verified through simulated analysis of the imaging quality of the optical system, whose operating temperature range is $-60{\sim}100^{\circ}C$.

• Proceedings of the Korean Ceranic Society Conference
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• 2003.10a
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• pp.22-22
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• 2003

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.256.1-256.1
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• 2007

• 축산식품과학과 산업
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• v.9 no.2
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• pp.36-45
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• 2020

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.197-198
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• 2018

• Proceedings of the Korean Vacuum Society Conference
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• 2009.02a
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• pp.246.2-246.2
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• 2009

• Proceedings of the Korean Vacuum Society Conference
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• 2009.02a
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• pp.113.2-113.2
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• 2009

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.106-107
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• 2007

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.225-234
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• 2023

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.