Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

The importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab

The present study is to investigate the possibility of using wastes in the form of scrap iron (ZVI) and/ or aluminum ZVAI for the detention and immobilization of the chromium ions in simulated wastewater. Different batch equilibrium parameters such as contact time (0-250) min, sorbent dose (2-8 g ZVI/100 mL and 0.2-1 g ZVAI/100 mL), initial pH (3-6), initial pollutant concentration of 50 mg/L, and speed of agitation (0-250) rpm were investigated. Maximum contaminant removal efficiency corresponding to (96 %) at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed were obtained.

The best isotherm model for the batch single Cr(III) uptake by ZVI

Abstract: Background: Optical biosensors offer excellent properties and methods for detecting bacteria when compared to traditional analytical techniques.  It allows direct detection of many biological and chemical materials.  Bacteria are found in the human body naturally non-pathogenic and pathologically, as they are found in other living organisms.  One of these bacteria is Escherichia coli (E. coli) which are found in the human body in its natural and pathogenic form. E.coli bacteria cause many diseases, including Stomach, intestines, urinary system infections, and others. The aim of this study: is sensing and differentiation between normal flora and pathogenic E.coli. Material and method:

This paper reports test results and describes a numerical investigation of the effectiveness of using carbon fibre reinforced polymer (CFRP) fabrics for strengthening concrete cylinders that have been undamaged and damaged due to heating under preload. The purpose of this research was to investigate whether there is any difference in the performance of CFRP-wrapped cylinders if the wrapping is done under preload, and those for which neither heating, cooling nor wrapping was done under preload. The cylinders were exposed to 30% of maximum load at ambient temperature during heating and cooling before being wrapped under preload. Of 18 Ø 100 × 200 mm identical cylinders, 6 were left as control samples without heating, 12 were exposed t

To assess the biochemical, mechanical and structural characteristics of retained dentin after applying three novel bromelain‑contained chemomechanical caries removal (CMCR) formulations in comparison to the conventional excavation methods (hand and rotary) and a commercial papain‑contained gel (Brix 3000). Seventy‑two extracted permanent molars with natural occlusal carious lesions (score > 4 following the International Caries Detection and Assessment System (ICDAS‑II)) were randomly allocated into six groups (n = 12) according to the excavation methods: hand excavation, rotary excavation, Brix 3000, bromelain‑contained gel (F1), bromelain‑chloramine‑T (F2), and bromelain chlorhexidine gel (F3). The superficial and deepe

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca