Advanced Driver Assistance System Based on IoT V2V and V2I for Vision Enabled Lane Changing with Futuristic Drivability.

In conventional modern vehicles, the Internet of Things-based automotive embedded systems are used to collect various data from real-time sensors and store it in the cloud platform to perform visualization and analytics. The proposed work is to implement computer vision-aided vehicle intercommunication V2V (vehicle-to-vehicle) implemented using the Internet of Things for an autonomous vehicle. Computer vision-based driver assistance supports the vehicle to perform efficiently in critical transitions such as lane change or collision avoidance during the autonomous driving mode.

Review of Semantic Segmentation of Medical Images Using Modified Architectures of UNET.

In biomedical image analysis, information about the location and appearance of tumors and lesions is indispensable to aid doctors in treating and identifying the severity of diseases. Therefore, it is essential to segment the tumors and lesions. MRI, CT, PET, ultrasound, and X-ray are the different imaging systems to obtain this information.

Anterior Cruciate Ligament Tear Detection Based on Deep Convolutional Neural Network.

Anterior cruciate ligament (ACL) tear is very common in football players, volleyball players, sprinters, runners, etc. It occurs frequently due to extra stretching and sudden movement and causes extreme pain to the patient. Various computer vision-based techniques have been employed for ACL tear detection, but the performance of most of these systems is challenging because of the complex structure of knee ligaments.

Complex Mullerian Malformation: A Rare Case of Hypoplastic Noncavitated Uterus in the Middle with Two Rudimentary Horns on Either Side.

Mullerian anomalies which cause infertility in women were described by different classification systems. We report a rare case of uterine anomaly in a 16-year-old patient presented with primary amenorrhea. Her diagnostic laparoscopy findings revealed two uterine rudimentary horns on either side of the upper pelvis with a hypoplastic noncavitated central uterus.

Preparation and Thermo-Physical Properties of Fe2O3-Propylene Glycol Nanofluids.

Iron oxide (Fe2O3) nanoparticles were prepared from ferric chloride and ferrous sulphate by precipitation reaction. Fe2O3-propylene glycol nanofluid was prepared by dispersing Fe2O3 nanoparticles in propylene glycol through stirred bead milling, shear homogenization and probe ultrasonication. The nanofluid was characterized through measurement of viscosity, particle size distribution and thermal conductivity.

Influence of nanoparticle concentration on thermo-physical properties of CuO-propylene glycol nanofluids.

Experiments were performed on the preparation and characterization of CuO-propylene glycol nanofluids. The influence of nanoparticle concentration and temperature on nanofluid viscosity reveals existence of a range of nanoparticle concentration and temperature in which the viscosity of nanofluid is lower than that of propylene glycol, possibly due to interactions between nanoparticles and propylene glycol. A temperature-independent, thermal conductivity enhancement of 38% was obtained for nanoparticle concentration of 1.