In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). The results showed that the method performed well in all simulation scenarios with respect to different sample sizes.
There is a growing need for up-to-date data for rapid decision making in the modern digital age. Recently, the need for high-resolution topographic maps is highly demanding by most mapping clients. With the maturing automatic structure from mobile and multi-view stereoscopy software, small organizations and individuals now have the ability to make their own surveys based on mobile mapping devices. This study looks at how feasible using low-cost Unmanned Aerial Vehicle (UAV) as a mobile mapping device for photogrammetric topographical surveys. It is showing the impact of different UAV flight settings and parameters on the accuracy of mapping products. An automatic scenario for photogra
The aim of this study was to investigate the effect of operating variables on, the percentage of removed sludge (PSR) obtained during re-refining of 15W-40 Al-Durra spent lubricant by solvent extraction-flocculation treatment method. Binary solvents were used such as, Heavy Naphtha (H.N.): MEK (N:MEK), H.N. : n-Butanol (N:n-But), and H.N. : Iso-Butanol (N:Iso:But). The studied variables were mixing speed (300-900, rpm), mixing time (15-60, min), and operating temperature (2540, oC). This study showed that the studied operating variables have effects where, increasing the mixing time up to 45 min for H.N.: MEK, H.N.: n-Butanol and 30 min for H.N.: Iso-Butanol increased the PSR, after that percentage was decreased; increasing t
... Show MoreBackground: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c
... Show MoreGe-Au infrared photoconductive detection was prepared from germanium single crystal which were doped with different gold concentration using thermal evaporation. The spectral resonsivity (Rλ), spectral detectivity (D*) were determined as function of wavelength, also the resistance, conductivity in dark and with illumination to infrared radiation, the gain and relative photo response have been measured with different gold concentration. Remarkable improvements in the photoresponse gain were observed for the highest resistance specimen at the expense of spectral detectivity values.
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.
Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef
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