Employment Status of the Graduates of De La Salle Lipa’s Certificate in Medical Transcription Program: A Tracer Survey and an Assessment

De La Salle Lipa has been offering the Certificate in Medical Transcription since June 2006. It is a 1- year certificate program that blends online transcription, facility- based instruction, and on the job training. The Department\u27s Vision- Mission is to be the leading provider of qualified medical transcriptionists both in local and global healthcare industry. It also aims to produce medical transcriptionists with Lasallian values who are efficient in converting dictated medical records into electronic data. This tracer study looked into the different aspects of the graduates past and present activities, more particularly in the aspects of education, training and employment. Utilizing a customized questionnaire in gathering vital information for the study, 22 graduates belonging to four batches from AY 2006- 2010 were surveyed. The study revealed that majority of the graduates are young adults falling on the age bracket 20-30 years old; are single and are female and have attended 1 or 2 years of college and are shiftees from different degree courses. Graduates consider listening skills, competence in Human Anatomy, and transcription practice as most useful in their job. MT graduates are highly employable, mostly are hired as medical transcriptionists, some are call center agents and MT trainer. Strengths that were cited include on-line training, effective and efficient course delivery, the mentors and the school facilities. The non- USAge of foot pedals and the length and duration of the training are the perceived weaknesses. Recommendations on intensifying the marketing strategy for the program and for some modifications in the course flow and design are put forward

Population dynamic of ring nematode in peach orchard managed with castor bean cake and millet crop.

Edição dos Proceedings do 6th International Congress of Nematology, Cape Town, South Africa, May 2014

Practical Guidelines for Tuning Model-Based Predictive Controllers for Refrigeration Compressor Test Rigs

This paper presents a practical methodology for tuning the parameters of a model predictive control technique for controlling the suction and discharge pressures of refrigeration compressor in test rigs. Typically, in this type of rig, the compressor under test is subjected to similar conditions as the ones found in refrigeration systems, such as refrigerators and freezers. Even though in industrial practice it is common to find proportional-integral (PI) controllers in such rigs, they are multivariable processes with partial coupling between the variables of interest. Model-based predictive control (MPC) is a control technique which uses an explicit process model to predict the future behavior of the system over a horizon, and then calculates a sequence of control actions so that the future outputs of the process track future references. Thus, since MPC is inherently a multivariable control technique, it can be used, for example, to mitigate the coupling between suction and discharge pressures, thus improving the performance of the control of the compressor operating condition and, therefore, the overall test performance. The study presented in this paper is based on a specific test rig used in industry, but the ideas are presented in a general way so that they can be used as general guidelines for tuning MPC for refrigeration compressor test rigs. The rig considered for this paper has two outputs, which are the pressures at the inlet and outlet of the compressor under test, and two manipulated variables, which are two valve openings. The paper begins by showing how to identify the dynamic models that describe the behavior of the compressor pressures and also how to use them to define an expression that relates the static gains of the models identified with the parameters of the predictive controller, with respect to closed loop-performance specifications of the test. In this study, the model predictive control technique known as generalized predictive control was used and, in addition to the tuning methodology, an analysis of the effects of the controller parameters on the closed-loop results is presented. Finally, the performance of the predictive controller tuned according to the proposed methodology is compared to the results obtained by two independent PI controllers, showing the improvement of the responses for both reference tracking and disturbance rejection. The obtained results are promising and show that the proposed methodology can be used as a starting point for the tuning of predictive controllers applied in test rigs. In addition, it is shown that the use of advanced control techniques, such as model-based predictive control, can contribute to increasing the productivity and operational efficiency of compressor tests

Practical Nonlinear Model Predictive Control with Hammerstein Model Applied to a Test Rig of Refrigeration Compressors

This paper discusses the implementation and presents the results of a suboptimal nonlinear model predictive controller used to control the suction and discharge pressures of compressors under test in a rig. The objective of this rig is to emulate operational conditions to which refrigeration compressors can be subjected when applied in a refrigeration system, such as household refrigerators and freezers, and allow quick measurements of some of the compressor characteristics under those conditions. There is a coupling between suction and discharge pressures and the behavior of such variables is nonlinear with respect to the valve openings, thus the plant to be controlled can be characterized as multivariable and nonlinear. Even though in industry it is common to use linear controllers to control nonlinear plants, the use of nonlinear controllers can bring advantages in terms of performance and robustness. The controller implemented in this paper is the practical nonlinear model predictive control algorithm, which is a general framework that can be used for the implementation of nonlinear model predictive controllers considering almost any class of nonlinear model. Even though model predictive control is harder to be implemented than classical controllers, such as PID, it poses the process control problem in the time domain, so the concepts involved are intuitive and at the same time the tuning is relatively easy, even for the multivariable case. In addition, model predictive control allows constraints, such as valve opening limitations and pressure limits, to be handled during the design phase. This paper considers a specific nonlinear model architecture, the nonlinear Hammerstein model, which is composed of a static nonlinear element in series with a linear dynamic part. Since this model is conceptually simple and presents good results in most of the practical situations, it is widely used in practice when a nonlinear model is desired. The dynamics of the real test rig were identified using this nonlinear model structure and the identification results are discussed. The practical nonlinear model predictive controller was implemented in the real test rig, being tested in a variety of operating conditions. The results of the controller are compared with the ones obtained with a classical PID controller. The modeling approach presented good results and the results obtained in this study show that it is possible to use nonlinear model predictive control algorithms in refrigeration test rigs, and that this use can contribute to increasing the productivity and operational efficiency of compressor tests