In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-deriva

       Laboratory experiments were carried  out in Technical college AL- Mussiab / Babylon during 2005  to study bioactivity of different concentration from ( aqueous , alcohol and hexane) extracts of bee venom collected from different workers of bees against some bacterial types that cause European Foul – brood Melissococcus plutom , Bacillus alvei and B. letrosporus which had been isolated from infected arched with disease . Two diffusion methods (digging and paper discs) were followed for the extraction of the venom . Results showed that digging diffusion method was more efficient for  test of bacterial inhibition which led to increase the activity of bee venom extract with general a

This research includes the study of the harsh environment areas in which engineers and workers operate in drilling oil wells, and their own characteristics in terms of nature and the climate and other surrounding factors, that negatively large amount affect on all the staff, present in comparison with other lands, so the study showed the preparations administrative and methodology that must be taken to confront the problems that may arise or for the purpose of avoiding. One of these things should be addressed is the process of adaptation of the staff live in the remote desert land and under difficult living conditions. The study also demonstrated all kinds of diseases and ill health which afflict the staff due to climatic conditions that

Among the available chaotic modulation schemes, differential chaos shift keying (DSCK) offers the perfect noise performance. The power consumption of DCSK is high since it sends chaotic signal in both of 1 and 0 transmission, so it does not represent the optimal choice for some applications like indoor wireless sensing where power consumption is a critical issue. In this paper a novel noncoherent chaotic communication scheme called differential chaos on-off keying (DCOOK) is proposed as a solution of this problem. With the proposed scheme, the DCOOK signal have a structure similar to chaos on-off keying (COOK) scheme with improved performance in noisy and multipath channels by introducing the concept of differential coherency used in DCS

The influx of Arab Qahtani and Nizari tribes continued to the countries of Baluchistan and the Levant in pre-Islamic times until the Levant became open to the Arab-Islamic tide during the first century AH. The Islamic Orient until the early Islamic Arab Army reached the western borders of China. What we will see in the folds of the search.

 Parties as active units in this process in order to work must have access to sources of funding in order to maintain their political presence in society and participate in the process of electoral competition, To win the election, bolstering the huge role that money has played in influencing the principle of equality among contestants in the elections. Those who own money will have a greater chance of winning the elections while less competitive opportunities for others who do not own the money or what they own does not give them the competitive ability to win elections. From this point of view, controlling political finance through legal regulation and institutional, media and popular monitoring has become an important requirement

In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

The piled raft is a geotechnical composite construction consisting of three elements: piles, raft and soil.
In the design of piled rafts, the load shared between the piles and the raft, and the piles are used up to a
load level that can be of the same order of magnitude as the bearing capacity of a comparable single
pile or even greater. Therefore, the piled raft foundation allows reduction of settlements in a very
economic way as compared to traditional foundation concepts.
This paper presents experimental study to investigate the behavior of piled raft system in sandy
soil. A small scale “prototype” model was tested in a sand box with load applied to the system through
a compression machine. The settlement was

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima