Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

The purpose of this study was to identify the effects of Pilates and Tai Chi as physical therapy interventions for pain and dysfunction in chronic lumbago patients. A total of 31 females who were at least 20 years old and diagnosed with chronic lumbago were divided into a Pilates group(PG) (n=10), Tai Chi group(TCG)(n=11), and conservative group(CG)(n=10), to measure their pain and dysfunction before and after a six week intervention. With regard to the changes in the lumbago consciousness scale before and after the six-week intervention, all three groups showed statistical significance(p<.05). The intergroup differences were significant between the PG and CG and between the TCG and CG. All three groups also showed statistical significance(p<.05) in the Oswestry Disability Index before and after the six-week intervention. Again, the intergroup differences were significant between the PG and CG and between the TCG and CG. Based on these results, the application of Pilates and Tai Chi with conservative treatment may be effective in reducing pain and improving dysfunction in chronic lumbago patients.

A 40-year-old G1 P0 L0 A1 woman was referred to our clinic with 6-year history of infertility. Before visiting the clinic, she had 3 cycles of In-Vitro Fertilization (IVF) procedures (2 cycles of Controlled Ovarian Stimulation-IVF and 1 cycle of frozen-thawed Embryo Transfer (ET)) at other clinic. She had medical history of abortion at early gestation following FET (frozen-thawed-ET). The patient had complete type of septate uterus, double cervix and longitudinal vaginal septum. Vaginal septotomy was done first and 1 month later, hysteroscopic septoplasty was followed using ballooning filled with dye. After septoplasty, we inserted ballooning and left for several days to compress septal endometrium on the septectomy area. All procedures were done in the ambulatory operating room without laparoscopy or admission. 3 months later, she had in vitro fertilization-embryo transfer (IVF-ET) and FET procedures in our clinic. She had successful pregnancy and now is at 22 weeks of gestation. New ambulatory septoplasty using dye-filled ballooning is easy, safe and minimally invasive surgery for treatment of complete septate uterus.