Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods show that extrapolated density measurement used an average for the real density. The gradient of an extrapolated method is much better in shallow depth into the vertical stress calculations. The Miller density method had an excellent fit with the real density in deep depth. It has been crucial to calculate vertical stress for the past 40 years because calculating pore pressure and geomechanical building models have employed vertical stress as input. The strongest predictor of vertical stress may have been bulk density. According to these results, the miller and extrapolated techniques may be the best two methods for determining vertical stress. Still, the gradient of an extrapolated method is much more excellent in shallow depth than the miller method. Extrapolated density approach may produce satisfactory results for vertical stress, while miller values are lower than those obtained by extrapolating. This may be due to the poor gradient of this method at shallow depths. Gardner's approach incorrectly displays minimum values of about 4000 psi at great depths. While other methods provide numbers that are similar because these methods use constant bulk density values that start at the surface and continue to the desired depth, this is incorrect.
dictates the need to study the cultural aspects of the context and the consequent relations between the person and the objective environment surrounding him, as the philosophical understanding of the role of culture has led to the emergence of new theoretical interpretations of design that are organically linked with the development of society, especially that the development of the human environment philosophically and culturally is linked to the philosophical perception of its role in Culture as a precondition for new theoretical interpretations of design.
From the above, this problem can be studied by defining the following question (What are the implications of the cultural context in graphic design)?
The research included
Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro
... Show MoreJava is a high-level , third generation programming language were introduced Javaoptics Open Source Physics (OSP) as a new simulation for design one of the most important interference optical coating called antireflection coating. It is recent developments in deign thin-film coatings. (OSP) shows multiple beam interferences from a parallel dielectric thin film and the evolution of reflection factors. It is simple to use and efficiently also can serve educational purposes. The obtained results have been compared with needle method
Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi
... Show MoreMulti-walled carbon nanotubes from cheap tubs company MWCNT-CP were purified by alcohol \ H2O2 \ separation funnel which is simple, easy and scalable techniques. The steps of purification were characterized by X-ray diffraction, Raman spectroscopy, scanning electron microscopy SEM with energy dispersive of X-ray spectroscopy EDX and surface area measurements. The technique was succeeded to remove most the trace element from MWCNT-CP which causing increase the surface area. The ratios of impurities were reduced to less 0.6% after treatment by three steps with losing less than 5% from MWCNT-CP.
This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem. The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show More