The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator has superior performance compared with other estimators.
Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented
... Show MoreThis work represents development and implementation a programmable model for evaluating pumping technique and spectroscopic properties of solid state laser, as well as designing and constructing a suitable software program to simulate this techniques . A study of a new approach for Diode Pumped Solid State Laser systems (DPSSL), to build the optimum path technology and to manufacture a new solid state laser gain medium. From this model the threshold input power, output power optimum transmission, slop efficiency and available power were predicted. different systems configuration of diode pumped solid state laser for side pumping, end pump method using different shape type (rod,slab,disk) three main parameters are (energy transfer efficie
... Show MoreIn the current study, haemoglobin analytes dissolved in a special buffer (KH2PO4(1M), K2HPO4(1M)) with pH of 7.4 were used to record absorption spectra measurements with a range of concentrations from (10-8 to 10-9) M and an absorption peak of 440nm using Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS) which is considered a simple, low cost, and robust setup. The principle work of this technique depends on the multiple reflections between the light source, which is represented by the Light Emitting Diode 3 W, and the detector, which is represented by the Avantes spectrophotomer. The optical cavity includes two high reflectivity ≥99% dielectric mirrors (dia
... Show MoreAs the bit rate of fiber optic transmission systems is increased to more than , the system will suffer from an important random phenomena, which is called polarization mode dispersion. This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. So that, time jittering leads to interference between neighboring pulses. On the other hand, increasing bit period will prevent the possibility of sending high rates. In this paper, an accurate mathematical analysis to increase the rates of transmission, which contain all physical random variables that contribute to determine the transmission rates, is presen
... Show MoreThe convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
... Show MoreWastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost
... Show MoreIn the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res
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