يهدف المقرر لتعريف الطلاب والطالبات بالاتجاهات المعاصرة والمستجدة في مجال الإدارة التربوية، ونماذج من الإدارة التربوية في بعض دول العالم. وذلك لتوظيف هذه الاتجاهات في تطوير المؤسسات التربوية، وتأهيل الكوادر القيادية التربوية بأحدث الاتجاهات التي تساعدهم على تطوير العمل في مؤسساتهم التربوية.
In this article, we introduce a localization system to reduce the accumulation of errors existing in the dead-reckoning method of mobile robot localization. Dead-reckoning depends on the information that comes from the encoders. Many factors, such as wheel slippage, surface roughness, and mechanical tolerances, affect the accuracy of dead-reckoning. Therefore, an accumulation of errors exists in the dead-reckoning method. In this article, we propose a new localization system to enhance the localization operation of the mobile robots.
The recent emergence of body sensor networks (BSNs) has made it easy to continuously collect and processvarioushealth-orienteddatarelatedtotemporal,spatialandvitalsignmonitoringofapatient.As such, discovering or mining interesting knowledge from the BSN data stream is becoming an important issuetopromoteandassistimportantdecisionmakinginhealthcare.Inthispaper,wefocusonminingthe inherentregularityofdifferentparameterreadingsobtainedfromdifferentbodysensorsrelatedtovital sign data of a patent for the purpose of following up health condition to prevent some kinds of chronic diseases.
Countless applications today are using mobile robots, including autonomous navigation, security patrolling, housework, search-and-rescue operations, material handling, manufacturing, and automated transportation systems. Regardless of the application, a mobile robot must use a robust autonomous navigation system. Autonomous navigation remains one of the primary challenges in the mobile-robot industry; many control algorithms and techniques have been recently developed that aim to overcome this challenge.
20/20 -the expression for normal eyesight (or 6/6 in countries where metric measurements are used). This notation is expressed as a fraction. The numerator (1st number) refers to the distance you were from the test chart, which is usually 20 feet (6 meters). The denominator (2nd number) denotes the distance at which a person with normal eyesight could read the line with the smallest letters that you could correctly read.
