This study describes how fuzzy logic control FLC can be applied to sonars of mobile robot. The fuzzy logic approach has effects on the navigation of mobile robots in a partially known environment that are used in different industrial and society applications. The fuzzy logic provides a mechanism for combining sensor data from all sonar sensors which present different information. The FLC approach is achieved by means of Fuzzy Decision Making method type of fuzzy logic controller. The proposed controller is responsible for the obstacle avoidance of the mobile robot while traveling through a map from a home point to a goal point. The FLC is built as a subprogram based on the intelligent architecture (IA). The software program uses the Advanced Robotics Interface for Applications (ARIA), it is programmed with C++ package ( Visual C++.Net ), and Networking software is used for setup Wireless TCP/IP Ethernet-to-Serial connection between robot and PC. The results show that the developed mobile robot travels successfully from one location to another and reaches its goal after avoiding all obstacles that are located in its way. The platform mobile robot is a Pioneer 3 DX that is equipped with Sonar sensors.
The research aims to focus on the human rights guarantees as they are subjected to continuous violations due to changes, wars and conflicts between nations and people, especially in the Arab world and the third world due to political, social, economic and environmental conditions and the failure of democratic tracks under the current reality.
Keyword: Human rights, Reality, Ambition.
يركز على دراسة ماهية حقوق الانسان وسياق تطورها ضمن اجيالها الثلاث ذات العلاقة بالجيل الاول الذي يختص بمناقشة الحقوق المدنية والجيل الثاني المتلازم مع توصيف الحقوق الاقتصادية والاجتماعية والجيل الثالث يطلق علية الجيل الجديد( حقوق التضامن)، فضلا عن تحديد الاساليب والاليات الداعمة لترقية وحماية حقوق الانسان وحرياته الاساسية
حقوق الانسان في الدستور الامريكي
The Concept of the Constitution and the most Important of Human Rights
The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s
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