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A new multi-model predictive control (MMPC) algorithm was proposed and applied in an intelligent vehicle lateral tracking control system in this paper, which is better to adapt the intelligent vehicle lateral tracking control under complex multi-conditions. First, the Gustafson–Kessel algorithm was used for the cluster analysis based on the vehicle test data to obtain the clustering center and train the sample data of each typical steering condition. Then, a multi-model structure was constructed by least squares support vector machines, and the sub-models of each category were taken as the prediction model for the application of MPC. Hence, the objective function of multi-objective optimization can be established and the multi-objective optimization problem was solved by the non-dominated sorted genetic algorithm-II algorithm to obtain the optimal control quantity. Finally, the MMPC-based intelligent vehicle lateral tracking control system was used to control the vehicle lateral tracking under three steering conditions, including straight line, normal right turn, and U-turn, through a simulation study in the MATLAB/Simulink environment. By comparing the vehicle trajectory, steering wheel angle, lateral deviation, and lateral angle, the performance of the proposed control method was verified. The experimental analysis results show that the proposed method can track the steering wheel angle of the vehicle reference trajectory under various working conditions. The vehicle lateral deviation value can be controlled in the range of (−1.0 m, 0.5 m). The high-precision lateral tracking control ensures that the yaw rate of the vehicle can track the yaw velocity under the reference driving track and guarantees the driving stability of intelligent vehicles. [ABSTRACT FROM AUTHOR]

Objectives The objectives of this study were to evaluate the effects of medication education and behavioral intervention on Chinese patients with epilepsy and to compare the difference between them. Methods A total of 109 patients with epilepsy who did not to take their antiepileptic drugs (AEDs) more than once were randomly assigned to two intervention groups: the medication education group (group I) and the medication education with behavioral intervention group (group II). Group I was initially provided with medication education in the form of oral education and written materials, and this education was reinforced by monthly calls from the pharmacist over the next six months. The behavioral intervention provided to group II consisted of a modified medication schedule which was based on cue–dose training therapy. The outcomes that were evaluated both in the beginning and in the end of the study included adherence, which was measured using the four-item Morisky Medication Adherence Scale (MMAS-4), the number of seizures, knowledge of AEDs, and the number of patients who missed a dose of their AEDs. Differences within and between the groups were analyzed. Results After intervention, the adherence and knowledge of AEDs increased greatly in all patients, and the number of patients who had seizures or missed AEDs decreased. However, no significant differences were observed between groups I and II. The observed changes were (group I vs group II, p value) increased adherence: 62.3% vs 64.3%, 0.827; increased knowledge of AEDs: 88.7% vs 80.4%, 0.231; and improved seizure control: 64.2% vs 64.3%, 0.988. In addition, the percentage of patients who forgot to take their AEDs decreased to 45.0% from more than 70%, and 44.9% of these patients took the missed AEDs as soon as they remembered. Discussion These findings clearly demonstrate that medication education and reinforced telephone calls from pharmacists can help to increase adherence to AEDs, the knowledge of patients regarding AEDs, and seizure control. However, the inclusion of a behavioral strategy that was easy to administer and use in this program did not lead to any significant effects on improving adherence. The results indicate that pharmacists can play an important role in improving the effects of medication regimens, but further research is required to identify strategies for improving adherence to behavioral theory. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: The objectives of this study were: (1) to evaluate self-reported adherence in adult patients with epilepsy in China who had missed taking their antiepileptic drugs (AEDs) at least once and (2) to determine why patients were not adherent to their medication to employ interventions targeted at barriers to adherence. Methods: A questionnaire was used to collect the patients'' demographic data, disease information, and reasons for why the patients did not take their AEDs. Adherence was also included as measured using a four-item Morisky questionnaire (Morisky-4 questionnaire). Results: Of the 131 patients, 4.6%, 70.2%, and 25.2% showed high, medium, and low adherence, respectively. The reasons for nonadherence included forgetfulness (54.2%), being seizure-free for a period (48.9%), and fear of adverse drug effects (27.5%). Conclusions: Medium adherence was the predominant nonadherence pattern, and forgetfulness, being seizure-free for a period, and fear of adverse effects were the primary reasons for nonadherence to AEDs. To overcome barriers to nonadherence, it is essential to use tools that are sensitive to reasons for nonadherence. [Copyright &y& Elsevier]

Automotive Open System Architecture (AUTOSAR), as an open, standardized framework for automotive electronic software development, has gradually become the standard followed by major automotive manufacturers and automotive electronic device suppliers. The electronic software system problem improves the development efficiency and portability of the system by reducing the development cost of automotive electronic software while ensuring the quality of products and services, which is beneficial for subsequent upgrades and updates of the system. In order to improve the reliability of the software component deployment algorithm based on AUTOSAR architecture, we proposed the TDCA algorithm. During the execution of the algorithm, communication volume and communication degree are introduced to improve the accuracy of the deployment plan by optimizing the bus load and ECU balancing. Algorithm comparison experiments show that comparing heuristic and linear optimization algorithms, the TDCA algorithm proposed in this paper has significant advantages in reducing bus load and ECU utilization. The algorithm can reduce the communication between cores and balance ECU load according to the constraints of AUTOSAR architecture. [ABSTRACT FROM AUTHOR]

For the different degrees of danger caused by different driving habits, a lane departure warning algorithm based on probability statistics of driving habits is proposed in this paper. According to the different driving habits of different drivers, the early warning mechanism can be adaptively adjusted through the method of probability statistics to make lane departure warning more targeted and accurate. Firstly, each frame of image is preprocessed, including gray treatment, edge detection and binarization. Then, Canny operator is used to detect the edge, and Hough transform is applied to detect the lines. And the lane median line equation for the detection and identification of lane also can be calculated. After that, the image coordinate system is transformed into the world coordinate system by means of the formula and matrix of coordinate conversion. According to the theory of Kalman filter, the statistics of lateral acceleration and lateral velocity are updated continuously, and the position of the vehicle in the next moment is predicted by the state transition equation and the forecast equation. From the results of experiments and the comparison with exhaustive algorithms, the advantages of using Kalman filter to predict the location of vehicles and the improved time-to-lane-crossing combined with probabilistic statistics to warning are illustrated clearly. [ABSTRACT FROM AUTHOR]

We undertook this survey about the use of clarithromycin in the Ear, Nose, and Throat (ENT) Outpatient Department of Fudan University Hospital to understand its utilization patterns and rational use. A survey of prescriptions given to outpatients was carried out, and detailed information of the patients, including age, sex, diagnosis, combined medication, and other information, was recorded in Excel spreadsheets. The rationale for each prescription was evaluated retrospectively. Based on our analysis, 82.5% of the clarithromycin prescriptions were for the treatment of rhinosinusitis. It was found that the parameters for the diagnosis of this condition were surprisingly broad and should have been more specific. In addition, the clarithromycin dosage regimen varied in clinical practice. For chronic rhinosinusitis, the duration of treatment was between 8 and 16 days, which was not sufficient. Moreover, clarithromycin was prescribed along with considerable numbers of pharmacotherapeutic anti-allergic drugs. Our survey indicated that improvements in the quality of clarithromycin prescriptions in otolaryngology outpatients should be made. Furthermore, the importance of medical education to patients should be emphasized. In addition, the interaction between clarithromycin and other anti-allergic drugs requires further investigation. [ABSTRACT FROM AUTHOR]