Abstract This research paper is based on you only look once (YOLO) object detection algorithm that detects and recognizes Indian license plates on conventional environments. Traffic control and management has been rising problems in urban conditions and several attempts have been already made to mitigate it using different methods. The safety as well as smooth flow of traffic is very important. Currently... This research paper is based on you only look once (YOLO) object detection algorithm that detects and recognizes Indian license plates on conventional environments. Traffic control and management has been rising problems in urban conditions and several attempts have been already made to mitigate it using different methods. The safety as well as smooth flow of traffic is very important. Currently such a problem lacks an elegant solution. By using state-of-the-art object detection technique combined with the configured convolutional neural network (CNN) built using Tensor flow core open source libraries, real-time detection and recognition has been achieved. Although license plate detection as well as recognition had been widely adopted by enormous number of countries around the world for surveillance purposes it remains as a significant challenge in India, where the size of the number plates on Indian vehicles are not fixed and the CCTV used are not of high resolution. This paper tries to solve this problem by using a version of YOLOv2 (improved version of YOLO). The results of this achieved acceptable real time detection up to mean average of 9.8 FPS when running in Nvidia GT 940M graphics card. Read More Read Less

Abstract This study had chose the half water gypsum board and diatomite as the main raw material, and added lime and mullite fiber preparation of ordinary gypsum board; and chose the capric acid and dodecanoic acid as phrase change materials, then mixed both based on a certain mass weight ratio, then chose plaster board carrier, and made phase change energy-storing gypsum... This study had chose the half water gypsum board and diatomite as the main raw material, and added lime and mullite fiber preparation of ordinary gypsum board; and chose the capric acid and dodecanoic acid as phrase change materials, then mixed both based on a certain mass weight ratio, then chose plaster board carrier, and made phase change energy-storing gypsum board by impregnation method; Finally, this study analyzed and discussed the quality of the relationship between prepared phase change energy-storing gypsum board and the dipping time, the content of phase change material in phase change energy-storing gypsum board, the durability and water-absorption performance of phase change energy-storing gypsum board, etc. Read More Read Less

Abstract Data management and analysis for risk assessment of rare and complex diseases such as Neuroblastoma require efficient management of multidisciplinary data. Recent advances in genomic testing are revealing new publicly available data whose storage and analysis with clinical and genomic data is becoming a big challenge. The use of Conceptual Modeling (CM) techniques helps to define and structure the Neuroblastoma domain,... Data management and analysis for risk assessment of rare and complex diseases such as Neuroblastoma require efficient management of multidisciplinary data. Recent advances in genomic testing are revealing new publicly available data whose storage and analysis with clinical and genomic data is becoming a big challenge. The use of Conceptual Modeling (CM) techniques helps to define and structure the Neuroblastoma domain, which serves as a basis to determine the information required for diagnosing the disease. It is important to highlight that a Genomic Information System (GeIS) based on a conceptual model allows improving the adaptation of new requirements of the domain, and greatly simplifies the integration and management of heterogeneous and homogeneous data. The main objectives of this work are: i) to present a Conceptual Model of Neuroblastoma (CMN), which defines all elements involved in the clinical and genomic domain. ii) to apply the SILE method, in order to obtain all (clinically) relevant variations associated with Neuroblastoma from genomic data sources. The developed GeIS is intended to make the correct exploitation of the validated data set to provide an early and efficient risk assessment for patients with Neuroblastoma. Read More Read Less