Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

Autorías: Ghassan Adeeb Abdulhasan, Rasha Raed Hamid Hameed, Hussein Jabber Abood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

The experiment was conducted to evaluate and performance comparison for moldboard and disk plows in central of Iraq in 2011. Three factor were used in this study included Two types of plows included moldboard and disk plows which represented main plot , three forward speeds of the tillage was second factor included 1.85, 3.75 and 5.62 km / h which represented sup plot , and three levels of soil moisture was third factor included 21 , 18 and 14 % to determined data actual plow depth , Practical productivity, Volume of disturbed soil, Field efficiency , Slippage percentage in silt clay loam soil with depth 22 cm were studied in the experiment Split – split plot design under randomized complete block design with three replications using

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Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

Introduction and Aims: Job burnout such as occupational hazards that have been considered in recent years. This research aimed to investigate the relationship between religious beliefs and job burnout among nurses working in hospitals in Gonabad city in 2017. Materials and Methods: This study is cross-sectional and correlational study. The sample consisted of 100 nurses in Gonabad city who were selected using stratified randomized method. Using the Maslach job burnout and Alport religious beliefs Inventories, data were collected and were analyzed with SPSS version 16 and Pearson, Spearman and independent sample T tests were analyzed. Significant level was considered less than 0.05. Results: Average job burnout in nurses working in hospit