Recently, all over the world mechanism of cloud computing is widely acceptable and used by most of the enterprise businesses in order increase their productivity. However there are still some concerns about the security provided by the cloud environment are raises. Thus in this our research project, we are discussing over the cloud computing paradigm evolvement for the large business applications like CRM as well as introducing the new framework for the secure cloud computing using the method of IT auditing. In this case our approach is basically directed towards the establishment of the cloud computing framework for the CRM applications with the use of checklists by following the data flow of the CRM application and its lifecycle. Those checklists are prepared on the basis of models of cloud computing such as deployment models and services models. With this project our main concern is to present the cloud computing implications through the large database enterprise CRM application and achieving the desired level of security with design and implementation of IT auditing technique. We claim that with this our proposed methods for the CRM applications, we will providing the security, regulations, compliance of such cloud computing environments.
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L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.
The tracking and steady state performances of both controllers have been assessed fo
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he dairy industry is one of the industrial activities classified within the food industries in all phases of the dairy industry, which leads to an increase in the amount of wastewater discharged from this industry. The study was conducted in the Abu Ghraib dairy factory, classified as one of the central factories in Iraq, located in the west of Baghdad governorate, with a design capacity of 22,815 tons of dairy products. The characteristics of the liquid waste generated from the factory were determined for the following parameters biological oxygen demand (BOD5), Chemical oxygen demand (COD), total suspended solids (TSS), pH, nitrate, phosphate, chloride, and sulfate with an average value of (1079, 1945, 323, 9.2, 24, 2
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Stripping is one of the major distresses within asphalt concrete pavements caused due to penetration of water within the interface of asphalt-aggregate matrix. In this work, one grade of asphalt cement (40-50) was mixed with variable percentages of three types of additives (fly ash, fumed silica, and phosphogypsum) to obtained an modified asphalt cement to resist the effect of stripping phenomena .The specimens have been tested for physical properties according to AASHTO. The surface free energy has been measured by using two methods namely, the wilhelmy technique and the Sessile drop method according to NCHRP-104
procedures. Samples of asphalt concrete using different asphalt cement and modified asphalt cement percentages(4.1,4.6 an
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Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti
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Crop coefficient for cherries was evaluated by measure the water consumption in Michigan State to find its variation with time as the plant growth. Crop coefficients value (Kc) for cherries were predicated by Michigan State University (MSU) and also by Food and Agriculture Organization (FAO) according to consume of water through the season. In this paper crop coefficients for cherries are modified accordingly to the actual measurements of soil moisture content. Actual evapotranspiration (consumptive use) were measured by the soil moisture readings using Time Domain Reflectometers (TDR), and compared with the actual potential evapotranspiration that calculated by using modified Penman-Monteith equation which depends on metrological statio
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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