Factors Predicting Organizational Commitment among Nurses in State Hospitals, Malaysia

Introduction: With an increase in national nursing shortage, organizational commitment is extremely important for retention of nurses. This predictive study determines the level of organizational commitment and the predictive ability of perceived organizational support, components of job satisfaction, including pay, task requirement, organizational policies, autonomy, interaction and professional status as well as years of experience on organizational commitment. Method: Data were collected from 416 nurses in four state hospitals in Malaysia, using self-administered questionnaires. The hospitals were selected from each region in Peninsular Malaysia and samples were selected by a random sampling method. Questionnaires, including demographic data, Organizational Commitment Questionnaires, Survey of Perceived Organizational Support, and Index Work Satisfaction were distributed by researcher and research assistants. Stepwise multiple regression technique was used to analyze the data. Results: The results discovered that (1) nearly half of the subjects (48.07%) reported high level of organizational commitment. (2) Professional status, autonomy, interaction, task requirement and years of experience could predict the organizational commitment (ß = 0.52, 0.17, p < 0.01); ß= 0.13, 0.11, 0.09, p < 0.05 respectively). Overall, all predictors explained 33% of variability in the organizational commitment among nurses in state hospitals. Conclusions: This study found that nurses in state hospitals were highly committed to their organizations. Results of this study provide information for nurse administrators to consider and maintain these factors in nursing practice to foster a high level of organizational commitment among Malaysian nurses.

Optimal Path Planning Satisfying Complex Task Requirement in Uncertain Environment

SummaryRobots often need to accomplish some complex tasks such as surveillance, response and obstacle avoidance. In this paper, a dynamic search method is proposed to generate optimal robot trajectories satisfying complex task requirement in uncertain environment. The LTL-A* algorithm is presented to generate a global optimal path and the A* algorithm is provided to modify the global optimal path. The task is specified by a linear temporal logic (LTL) formula, and a weighted transition system according to the known information in uncertain environment is modeled to describe the robot motion. Subsequently, a product automaton is constructed by combining the transition system with the task requirement. Based on the product automaton, the LTL-A* algorithm is proposed to generate a global optimal path. The local path planning based on the A* algorithm is employed to deal with the environment change during the process of tracking the global optimal path for the robot. The results of the simulation and experiments show that the proposed method can not only meet the complex task requirement in uncertain environment but also improve the search efficiency.

Research on Simulation and Performance Optimization of Mach 4 Civil Aircraft Propulsion Concept

Supersonic civil aircraft is of a promising area in the development of future civil transport, and aircraft propulsion system is one of the key issues which determine the success of the aircraft. To get a good conceptual design and performance investigation of the supersonic civil aircraft engine, in this article, a fast, versatile as well as trust-worthy numerical simulation platform was established to analyze the Mach 4 turbine-based combined cycle (TBCC) engine concept so as to be applied to the supersonic civil aircraft. First, a quick and accurate task requirement analysis module was newly established to analyze the mission requirement of the Mach 4 supersonic civil aircraft. Second, the TBCC engine performance simulation model was briefly presented and the number of engines on the supersonic civil aircraft was analyzed, considering single engine inoperative. Third, the Stone model and the DLR method were investigated to estimate the engine jet noise and the NOx emission of the Mach 4 supersonic civil aircraft. Finally, a multiobjective optimization tool made up of a response surface method and a genetic algorithm was developed to optimize the design parameters and the control law of the TBCC engine, in order to make the Mach 4 supersonic civil aircraft engine with better performance, lower noise, and lower emissions. The uniqueness of the developed analysis tool lies in that it affords a numerical simulation platform capable of investigating the task requirement analysis module of the supersonic civil aircraft, engine jet noise prediction model, and the NOx emission prediction model, as well as a multiobjective performance optimization tool, which is beneficial for the conceptual design and performance research of Mach 4 supersonic civil aircraft’s propulsion system.

Primacy and Recency Effects in Immediate Free Recall of Sequences of Spatial Positions

This study evaluated the serial position curve based on free recall of spatial position sequences. To evaluate the memory processes underlying spatial recall, some manipulations were introduced by varying the length of spatial sequences (Exp. 1) and modifying the presentation rate of individual positions (Exp. 2). A primacy effect emerged for all sequence lengths, while a recency effect was evident only in the longer sequences. Moreover, slowing the presentation rate increased the magnitude of the primacy effect and abolished the recency effect. The main novelty of the present results is represented by the finding that better recall of early items in a sequence of spatial positions does not depend on the task requirement of an ordered recall but it can also be observed in a free recall paradigm.

Mood and Flexibility in Categorization: A Conceptual Replication

The present study tested the hypothesis that positive mood facilitates cognitive flexibility in categorization, i.e., positive mood enhances the ability to categorize flexibly at broad and narrow levels contingent on task requirement. The study was a conceptual replication of the 1990 work by Murray, Sujan, Hirt, and Sujan. Unlike the original study, it was carried out on the WWW with some modifications in the procedure. Participants were 29 women and 132 men whose average age was 29 yr. They were put into a positive, negative, or neutral mood using the Velten technique. Mood was measured with standard mood scales. Subjects then listed similarities or differences between two entertainment TV shows. Contrary to the prediction, participants in a positive mood did not list a higher number, more diverse, or more unusual similarities and differences between the shows, and they were not faster than participants with neutral or negative moods. It is concluded that the influence of mood on cognitive flexibility needs to be reconsidered In research, temporal aspects of categorization performance as well as a wider range of mood valences should be taken into account.