Abstract Patients with disabilities and their health status detection is significant in the intelligent computing. When there is no health support people for the disabled people, a system using accelerometer sensors is able to monitor the conditions. While we use the KNN classifier after raw data pre-processing, we have identified six modes of activities. We are able to draw incredible data... Patients with disabilities and their health status detection is significant in the intelligent computing. When there is no health support people for the disabled people, a system using accelerometer sensors is able to monitor the conditions. While we use the KNN classifier after raw data pre-processing, we have identified six modes of activities. We are able to draw incredible data results which can bring useful data analysis of the observation and detection of the health status of the observed disabled people for a longer time. Read More Read Less

Abstract In the medical field, medical analyses are important to properly diagnose the patient’s case by the doctor, especially if there is a history of several analyses of the same patient which are stored in the patient’s electronic medical record; this can help the doctor to make the right decision. However, the doctor always needs other techniques and methods in order... In the medical field, medical analyses are important to properly diagnose the patient’s case by the doctor, especially if there is a history of several analyses of the same patient which are stored in the patient’s electronic medical record; this can help the doctor to make the right decision. However, the doctor always needs other techniques and methods in order to make the right decision. In this work, a disease identification system is performed from electronic medical records using the k-nearest neighbours classification algorithm, which classifies different types of diseases (six diseases were studied) according to the values of the medical analysis. The experiment results show that the identification rate (classification) is 43.18% using very small sample as reference data, and this obtained result is acceptable and present the proof of the feasibility of the proposed system. Read More Read Less

Abstract In this work, we studied the movement of smart cars using the platoon movement. The smart cars have Adaptive or Advanced cruise control (ACC) system also called Intelligent cruise control (ICC) or Adaptive Intelligent cruise control (AICC) system. The cruise control system makes to follow other vehicles on desired distance and to be organized in platoons. We develop a model... In this work, we studied the movement of smart cars using the platoon movement. The smart cars have Adaptive or Advanced cruise control (ACC) system also called Intelligent cruise control (ICC) or Adaptive Intelligent cruise control (AICC) system. The cruise control system makes to follow other vehicles on desired distance and to be organized in platoons. We develop a model to control and stability of an AGV (Automated Guided Vehicles) string, a car following model is being determined. Initially, we model the first vehicle, with platoon with same features and control, the single vehicle model is copied ten times to form model of platoon (string) with ten vehicles. We applied then the PID controllers to control this string, equal, except the leading vehicle. We deployed the feed forward control and feedback control approach for control of vehicle with nonlinear dynamics combination. We design the platoon ov vehicles Matlab/ Simulink models for experimental analysis. Read More Read Less