Classification of Indonesian adult forensic gender using cephalometric radiography with VGG16 and VGG19: a Preliminary research.

BACKGROUND: The use of cephalometric pictures in dental radiology is widely acknowledged as a dependable technique for determining the gender of an individual. The Visual Geometry Group 16 (VGG16) and Visual Geometry Group 19 (VGG19) algorithms have been proven to be effective in image classification. OBJECTIVES: To acknowledge the importance of comprehending the complex procedures associated with the generation and adjustment of inputs in order to obtain precise outcomes using the VGG16 and VGG19 algorithms. MATERIAL AND METHOD: The current work utilised a dataset including 274 cephalometric radiographic pictures of adult Indonesians' oral health records to construct a gender classification model using the VGG16 and VGG19 architectures using Python. RESULT: The VGG16 model has a gender identification accuracy of 93% for females and 73% for males, resulting in an average accuracy of 89% across both genders. In the context of gender identification, the VGG19 model has been found to achieve an accuracy of 0.95% for females and 0.80% for men, resulting in an overall accuracy of 0.93% when considering both genders. CONCLUSION: The application of VGG16 and VGG19 models has played a significant role in identifying gender based on the study of cephalometric radiography. This application has demonstrated the exceptional effectiveness of both models in accurately predicting the gender of Indonesian adults.

Design and Application of Near Infrared LED and Solenoid Magnetic Field Instrument to Inactivate Pathogenic Bacteria.

PURPOSE: This study aims to evaluate the efficiency of infrared LEDs with a magnetic solenoid field in lowering the quantity of gram-positive Staphylococcus aureus and gram-negative Escherichia coli bacteria, as well as the best exposure period and energy dose for inactivating these bacteria. METHOD: Research has been performed on a photodynamic therapy technique called photodynamic inactivation (PDI), which combines infrared LED light with a wavelength range of 951-952 nm and a solenoid magnetic field with a strength of 0-6 mT. The two, taken together, can potentially harm the target structure biologically. Infrared LED light and an AC-generated solenoid magnetic field are both applied to bacteria to measure the reduction in viability. Three different treatments infrared LED, solenoid magnetic field, and an amalgam of infrared LED and solenoid magnetic field, were used in this study. A factorial statistical ANOVA analysis was utilized in this investigation. RESULTS: The maximum bacterial production was produced by irradiating a surface for 60 min at a dosage of 0.593 J/cm2, according to the data. The combined use of infrared LEDs and a magnetic field solenoid resulted in the highest percentage of fatalities for Staphylococcus aureus, which was 94.43 s. The highest percentage of inactivation for Escherichia coli occurred in the combination treatment of infrared LEDs and a magnetic field solenoid, namely, 72.47 ± 5.06%. In contrast, S. aureus occurred in the combined treatment of infrared LEDs and a magnetic field solenoid, 94.43 ± 6.63 percent. CONCLUSION: Staphylococcus aureus and Escherichia coli germs are inactivated using infrared illumination and the best solenoid magnetic fields. This is evidenced by the rise in the proportion of bacteria that died in treatment group III, which used a magnetic solenoid field and infrared LEDs to deliver a dosage of 0.593 J/cm2 over 60 min. According to the research findings, the magnetic field of the solenoid and the infrared LED field significantly impact the gram-positive bacteria S. aureus and the gram-negative bacteria E. coli.

Modified Gray-Level Haralick Texture Features for Early Detection of Diabetes Mellitus and High Cholesterol with Iris Image.

Iris has specific advantages, which can record all organ conditions, body construction, and psychological disorders. Traces related to the intensity or deviation of organs caused by the disease are recorded systematically and patterned on the iris and its surroundings. The pattern that appears on the iris can be recognized by using image processing techniques. Based on the pattern in the iris image, this paper aims to provide an alternative noninvasive method for the early detection of DM and HC. In this paper, we perform detection based on iris images for two diseases, DM and HC simultaneously, by developing the invariant Haralick feature on quantized images with 256, 128, 64, 32, and 16 gray levels. The feature extraction process does early detection based on iris images. Researchers and scientists have introduced many methods, one of which is the feature extraction of the gray-level co-occurrence matrix (GLCM). Early detection based on the iris is done using the volumetric GLCM development, namely, 3D-GLCM. Based on 3D-GLCM, which is formed at a distance of d = 1 and in the direction of 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°, it is used to calculate Haralick features and develop Haralick features which are invariant to the number of quantization gray levels. The test results show that the invariant feature with a gray level of 256 has the best identification performance. In dataset I, the accuracy value is 97.92, precision is 96.88, and recall is 95.83, while in dataset II, the accuracy value is 95.83, precision is 89.69, and recall is 91.67. The identification of DM and HC trained on invariant features showed higher accuracy than the original features.

The efficacy of photodynamic inactivation with laser diode on Staphylococcus aureus biofilm with various ages of biofilm.

Biofilms are able to cause microorganisms to be 80% more resistant to antibiotics. The extracelullar polymeric substance (EPS) in biofilm functions to protect bacteria, making it difficult for antibiotics to penetrate the biofilm layer. This study aims to determine the effectiveness of photodynamic inactivation with blue diode laser to reduce Staphylococcus aureus biofilm at various ages of biofilms. The light source is a 403 nm blue diode laser with an energy power of about 27.65±0.01 mW. The study was designed with two groups: Group C was the untreated control group with variations in age of biofilms (0; 6; 11; 17; 24; 32; 40 and 48) hours; Group T was a laser treatment group with variations in age of biofilm and energy density (4.23; 8.46; 12.70; 16.93 and 21.16) J/cm2. Biofilm reduction measurement method using ELISA test was performed to calculate OD595 value. The statistical analysis results of variance showed that there was an influence of biofilm age and irradiation energy density of laser on biofilm reduction. Optical density analysis showed the most optimum biofilm reduction happened when biofilm age is perfectly constructed (about 17 hours) and with 91% reduction. The longer biofilm age lived among those biofilms, the greater the reduction. The results of the Scanning Microscope Electron and fluorescent microscope measurement showed destruction site of the EPS biofilm and bacterial cell death. So, the activated photodynamic with 403 nm laser diode is effective to reduce the Staphylococcus aureus biofilm in the maturation phase.