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Explore the best ranked sports medicine colleges and universities. Read what they are saying on the web, including Facebook, Twitter, and YouTube. The Sports Medicine Core Curriculum Lecture Series. This comprehensive lecture series includes the most common and the most serious medical illness and injuries. MSc in Sports Medicine, Exercise & Health. Sports Medicine, Exercise & Health MSc. The MSc in Sports Medicine, Exercise and. Health, based at the Institute of Sport Exercise and Health (ISEH), is designed to give students a broad understanding of sports medicine. The MSc is also available via distance learning for students who wish to study at home - from anywhere in the UK or the world. Sports Medicine PhD Programs. Learn how to become a sports medicine doctor! Explore the education requirements and important career information such as salary and job outlook. Individuals searching for schools that offer sports medicine found the articles, information, and resources on this page helpful. It will introduce the key areas relating to sports and exercise medicine. This will prepare you for. NHS musculoskeletal clinics and community. Graduates of the programme will gain a deeper understanding. This will. prepare them for potential work in many areas from elite sports medicine. NHS sports and musculoskeletal clinics and exercise medicine. Studentship. Key Information. Tuition Fees (2. 01. UK/EU. . Fees for flexible, modular study are charged pro- rata to the appropriate full- time Master's fee taken in an academic session. The tuition fee schedule for 2. UCL Current Students website. Applicants should have a minimum of one year post- graduation clinical experience relating to their primary degree. English Language Requirements. If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency. The English language level for this programme is: Good. Further information can be found on our English language requirements page. International students. Country- specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website. International applicants can find out the equivalent qualification for their country by selecting from the list below. Select your country. Select a country. Afghanistan. Albania. Algeria. Argentina. Armenia. Australia. Austria. Azerbaijan. Bahrain. Bangladesh. Barbados. Belarus. Belgium. Belize. Bolivia. Bosnia and Herzegovina. Botswana. Brazil. Brunei. Bulgaria. Cambodia. Cameroon. Canada. Caribbean / West Indies. Chile. China. Colombia. Congo (DR)Costa Rica. Croatia. Cuba. Cyprus (Greek Cypriot and Turkish Cypriot communities)Czech Republic. Denmark. Dominican Republic. Ecuador. Egypt. El Salvador. Eritrea. Estonia. Ethiopia. Finland. France. Georgia. Germany. Ghana. Greece. Guatemala. Guyana. Honduras. Honduras. Hong Kong. Hungary. Iceland. India. Indonesia. Iran. Iraq. Ireland. Israel. Italy. Ivory Coast. Jamaica. Japan. Jordan. Kazakhstan. Kenya. Kuwait. Kyrgyzstan. Latvia. Lebanon. Lesotho. Liberia. Libya. Lithuania. Luxembourg. Macau. Macedonia. Madagascar. Malawi. Malaysia. Malta. Mauritius. Mexico. Moldova. Mongolia. Montenegro. Morocco. Myanmar (Burma)Namibia. Nepal. Netherlands. New Zealand. Nicaragua. Nigeria. Norway. Oman. Pakistan. Panama. Papua New Guinea. Paraguay. Peru. Philippines. Poland. Portugal. Qatar. Romania. Russia. Rwanda. Saudi Arabia. Senegal. Serbia Sierra Leone. Singapore. Slovakia. Slovenia. South Africa. South Korea. Spain. Sri Lanka. Sudan. Sweden. Switzerland. Syria. Taiwan. Tajikistan. Tanzania. Thailand. Trinidad & Tobago. Tunisia. Turkey (including Turkish sector of Cyprus)Turkmenistan. Uganda. Ukraine. United Arab Emirates (UAE)United States of America. Uruguay. Uzbekistan. Venezuela. Vietnam. Zambia. Zimbabwe. International equivalencies. Graduates of the programme will gain a deeper understanding and valuable insights into the key areas of sports injury prevention and management, health and physical activity, and will be able to prescribe exercise safely for a range of medical conditions. This will prepare them for potential work in many areas from elite sports medicine to NHS sports and musculoskeletal clinics and exercise medicine services. Top career destinations for this programme. Osteopath, Self Employed. Paediatrician, NHS. Team Doctor, Football Club. Lead Physiotherapist, England u. Basketball. (2. 01. Team Doctor, Semi Professional Rugby Club. Employability. A Master's level degree in Sports Medicine, Exercise & Health from UCL will open many doors in the sports and exercise medicine world, from sports injury clinics to developing exercise medicine programmes for the prevention and treatment of chronic disease, and working with sports teams. UCL's MSc in Sports Medicine, Exercise & Health is led by local experts with active involvement in NHS and elite sports and exercise medicine settings. A distinct feature of the programme is the wide variety and large number of distinguished external guest speakers, all experts in their own fields locally, nationally and internationally. Students have unrivalled access to our guest speakers for career advice and potential opportunities. Temperature Controllers & PID Controllers. As the name implies, a temperature controller is an instrument used to control temperatures, mainly without extensive operator involvement. A controller in a temperature control system will accept a temperature sensor such as a thermocouple or. RTD as input and compare the actual temperature to the desired control temperature, or setpoint. It will then provide an output to a control element. The controller is usually just one part of a temperature control system, and the whole system should be analyzed and considered in selecting the proper controller. Depending upon the system to be controlled, the operator will be able to use one type or another to control the process. The output from the device is either on or off, with no middle state. An on- off controller will switch the output only when the temperature crosses the setpoint. For heating control, the output is on when the temperature is below the setpoint, and off above setpoint. Since the temperature crosses the setpoint to change the output state, the process temperature will be cycling continually, going from below setpoint to above, and back below. In cases where this cycling occurs rapidly, and to prevent damage to contactors and valves, an on- off differential, or . This differential requires that the temperature exceed setpoint by a certain amount before the output will turn off or on again. On- off differential prevents the output from . On- off control is usually used where a precise control is not necessary, in systems which cannot handle having the energy turned on and off frequently, where the mass of the system is so great that temperatures change extremely slowly, or for a temperature alarm. PID CONTROLLER DESIGN FOR CONTROLLING DC MOTOR SPEED USING MATLAB APPLICATION MOHAMED FARID BIN MOHAMED FARUQ This thesis is submitted as partial fulfillment of the. 1 Tutorial 7 - PID Control System (JEE344 Applied Control Engineering) Aim Workbook Learning System for Automation and Communications 171 149 Process Control System Control of temperature, flow and filling level. PID Control Theory 221 While PID controllers are applicable to many control problems, and often perform satisfactorily without any improvements or even tuning, they. Uncorrected proofs book 2007/8 page 1 Chapter 6 PID Controller Design PID (proportional integral derivative) control is one of the earlier control strategies PID Controller Tuning: A Short Tutorial. This tutorial is in PDF format with navigational control. How does the PID parameters a Instrumentation & Control Process Control Fundamentals. Control loops in the process control industry work in the same way, requiring three tasks to occur. Introduction to PID Control. Controller: Provides the excitation for the plant; Designed to control the overall system behavior The three-term controller. One special type of on- off control used for alarm is a limit controller. This controller uses a latching relay, which must be manually reset, and is used to shut down a process when a certain temperature is reached. A proportional controller decreases the average power supplied to the heater as the temperature approaches setpoint. This has the effect of slowing down the heater so that it will not overshoot the setpoint, but will approach the setpoint and maintain a stable temperature. This proportioning action can be accomplished by turning the output on and off for short time intervals. The proportioning action occurs within a . Outside this band, the controller functions as an on- off unit, with the output either fully on (below the band) or fully off (above the band). However, within the band, the output is turned on and off in the ratio of the measurement difference from the setpoint. Control System The basic idea behind a PID controller is to read a sensor, then compute the desired actuator output by calculating proportional, integral, and.At the setpoint (the midpoint of the proportional band), the output on: off ratio is 1: 1; that is, the on- time and off- time are equal. If the temperature is below setpoint, the output will be on longer; if the temperature is too high, the output will be off longer. This controller combines proportional control with two additional adjustments, which helps the unit automatically compensate for changes in the system. These adjustments, integral and derivative, are expressed in time- based units; they are also referred to by their reciprocals, RESET and RATE, respectively. The proportional, integral and derivative terms must be individually adjusted or . It provides the most accurate and stable control of the three controller types, and is best used in systems which have a relatively small mass, those which react quickly to changes in the energy added to the process. It is recommended in systems where the load changes often and the controller is expected to compensate automatically due to frequent changes in setpoint, the amount of energy available, or the mass to be controlled. These are known as autotune controllers. In order to provide interchangeability between temperature controllers, most temperature controllers are designed to standard DIN sizes. The most common DIN sizes are shown below. The following items should be considered when selecting a controller. Type of input sensor (thermocouple, RTD) and. Type of output required (electromechanical. SSR, analog output)Control algorithm needed (on/off, proportional. PID)Number and type of outputs (heat, cool, alarm. PID for Dummies - Control Solutions. Anatomy Of A Feedback Control System. Here is the classic block diagram of a process under PID Control. What’s going on this diagram? The Setpoint (SP) is the value that we want the process to be. For example, the temperature control system in our house may have a SP of 2. This means that“we want the heating and cooling process in our house to achieve a steady temperature of as close to 2. It doesn’t have to do anything, it will set its output to zero. However, if there is a disparity between the SP and the PV we have an error and corrective action is needed. In our house this will either be cooling or heating depending on whether the PV is higher or lower than the SP respectively. Let’s imagine the temperature PV in our house is higher than the SP. The air- con is switched on and the temperature drops. The sensor picks up the lower temperature, feeds that back to the controller, the controller sees that the “temperature error” is not as great because the PV (temperature) has dropped and the air con is turned down a little. This process is repeated until the house has cooled down to 2. Sounds dead simple eh? Understanding the controller. Unfortunately, in the real world we need a controller that is a bit more complicated than the one described above, if we want top performance form our loops. We are the driver, and therefore the controller of the process of changing the car’s position. Here’s the Block Diagram we used before, with the labels changed to represent the car- on- windy- freeway control loop. Notice how important closing the feedback loop is. If we removed the feedback loop we would be in “open loop control”, and would have to control the car’s position with our eyes closed! Thankfully we are under “Closed loop control” - using our eyes for position feedback. As we saw in the house- temperature example the controller takes the both the PV and SP signals, which it then puts through a black box to calculate a controller output. That controller output is sent to an actuator which moves to actually control the process. We are interested here in what the black box actually does, which is that it applies 1, 2 or 3 calculations to the SP and Measured PV signals. The PV is subtracted from the SP to create the Error. The error is simply multiplied by one, two or all of the calculated P, I and D actions (depending which ones are turned on). That’s all there is to it. Integrals without the Math. Is it any wonder that so many people run scared from the concept of integrals and integration, when this is a typical definition? What the!?!? If you understood that you are a smarter person than me. Here’s a plain English definition: The integral of a signal is the sum of all the instantaneous values that the signal has been, from whenever you started counting until you stop counting. So if you are to plot your signal on a trend and your signal is sampled every second, and let’s say you are measuring temperature. If you were to superimpose the integral of the signal over the first 5 seconds . It is the sum of the 5 temperature values over the time period that you are interested in. In numerical terms it is the sum of the areas of each of the blue rectangles: (1. When we have real world systems, we actually get an approximation to the area under the curve, which as you can see from the diagram gets better, the faster we sample. The tricky thing about Integral Action is that it will really screw up your process unless you know exactly how much Integral action to apply. A good PID Tuning technique will calculate exactly how much Integral to apply for your specific process - but how is the Integral Action adjusted in the first place? Adjusting the Integral Action. The way to adjust how much Integral Action you have is by adjusting a term called “minutes per repeat”. Not a very intuitive name is it? So where does this strange name come from? It is a measure of how long it will take for the Integral Action to match the Proportional Action. In other words, if the output of the proportional box on the diagram above is 2. Integral box to get to 2. And the important point to note is that the “bigger” integral action, the quicker it will get this 2. That is, it will take fewer minutes to get there, so the “minutes per repeat” value will be smaller. In other words the smaller the “minutes per repeat” is the bigger the integral action. To make things a bit more intuitive, a lot of controllers use an alternative unit of “repeats per minute” which is obviously the inverse of “minutes per repeat”. The nice thing about “repeats per minute” is that the bigger it is - the bigger the resulting Integral action is. That is the reason that PI controllers are the most prevalent. They do the job well enough and keep things simple. But engineers being engineers are always looking to tweak performance. They do this in a PID loop by adding the final ingredient: Derivative Action. So adding derivative action can allow you to have bigger P and I gains and still keep the loop stable, giving you a faster response and better loop performance. If you think about it, Derivative action improves the controller action because it predicts what is yet to happen by projecting the current rate of change into the future. This means that it is not using the current measured value, but a future measured value. The units used for derivative action describe how far into the future you want to look. If derivative action is 2. The big problem with D control is that if you have noise on your signal (which looks like a bunch of spikes with steep sides) this confuses the hell out of the algorithm. It looks at the slope of the noise- spike and thinks: “Holy crap! This process is changing quickly, lets pile on the D Action!!!”And your control output jumps all over the place, messing up your control. Of course you can try and filter the noise out, but my advice is that, unless PI control is really slow, don’t worry about switching D on. Early Warning System for West Nile Virus Risk Areas, California, USA - Volume 1. Number 8. Through press releases and various types of media campaigns at state and local levels, citizens were encouraged to use the hotline (1- 8. WNV- BIRD) and website (www. Information regarding location, date found, and species was collected for each dead bird reported to the hotline; multiple dead birds included in a single report were treated as multiple reports. Hotline staff screened and entered these data into an Access database (Microsoft Corporation, Redlands, WA, USA); data were subsequently geocoded by using Arc. Map version 9. 1 and associated 2. Street. Map USA Plus Alt. Names street dataset (Environmental Systems Research Institute, Inc., Redlands, CA, USA). Early Warning Infectious Disease Surveillance (EWIDS) Guidance. Develop and implement a program to collaborate with states or provinces. Develop or improve infectious disease surveillance in a uniform manner. Pacific-wide simplified syndromic surveillance for early warning of outbreaks. Pacific-wide simplified syndromic surveillance for early warning of. Progress In Infectious Disease Surveillance But Gaps Remain. Progress In Infectious Disease Surveillance But Gaps Remain. United States Mexico Border Health Commission - Early Warning Infectious Disease Surveillance Project. At the USMBHC’s 4th binational meeting in Saltillo, Mexico, U.S. Department of Health and Human Services Former Secretary.WNV became a reportable disease in California in 2. Data were subsequently stripped of personal identifiers, and addresses were geocoded by using a CDPH batch geocoding service that used multiple reference databases (www. Early Warning Infectious Disease Surveillance Project.
Use of human data was approved by the institutional review board at the California Health and Human Services Agency (project no. Procedure. Figure 1. Figure 1. California counties with 2. Dynamic Continuous- Area Space- Time (DYCAST) analysis regions (3. Data were mapped by using Arc. Map version 9. 3. Environmental Systems Research Institute, Inc., Redlands, CA, USA).. Figure 2. Figure 2. Schematic of the Dynamic Continuous- Area Space- Time (DYCAST) procedure, illustrating domains of Knox test (1. The 2. 4- km.. The DYCAST procedure was implemented by using GIS software, Smallworld 3. Magik programming language (General Electric Company, Fairfield, CT, USA). Regions comprising 3. Clustering of dead bird reports was quantified by using a Knox test (1. Figure 2). The 2. The effective flight range of these mosquitoes is also 2. The temporal domain of 2. WNV, which ranges from 5 to 8 days for Culex spp. Candidate values for defining proximity of dead birds in space (0. During model calibration, locations of human cases were compared with DYCAST risk maps generated by using various combinations of candidate values; 0. For this calibration, the daily DYCAST procedure was run retrospectively (once during May 2. May 1 through September 3. Los Angeles, Orange, Riverside, and San Bernardino Counties, which contained 6. The DYCAST procedure was run at the center of every cell for which a minimum of 1. Clustering was evaluated by comparing the observed number of pairs of dead birds that were close in both space and time (based on aforementioned values of proximity), with the expected number of pairs given a random spatiotemporal distribution of these reports (1. The resulting p values were assigned to individual cells, which were considered to indicate high risk for WNV transmission to humans at p< 0. Evaluation. Model evaluation was conducted by analyzing the relationship between the location of human cases and the ability of DYCAST to predict their occurrence in both space and time. Prediction was defined as the identification of a cell as high risk before or on the date of illness onset (1. Sensitivity was calculated as the number of high- risk cells classified as predicted (true positives) divided by the total number of cells in which a human case occurred. Specificity was calculated as the proportion of low- risk cells without cases (true negatives) to the total number of cells without cases. Because agreement between model predictions and cases can occur by chance, a spatiotemporal implementation of the . The Center for Vectorborne Diseases (CVEC) at the University of California Davis provided server infrastructure (Microsoft SQL Server, Microsoft Corporation; Arc. IMS, Environmental Systems Research Institute, Inc.) for data exchange and implementation of interactive online risk maps, in collaboration with CDPH and the Mosquito and Vector Control Association of California. The Center for Advanced Research of Spatial Information calibrated and ran the DYCAST procedure and exported the data to the CVEC map server. During the pilot phase, animations of daily risk from June 1 through June 2. Sacramento Valley region (Sacramento, Placer, and Yolo Counties), the central San Joaquin Valley region (Fresno, Kings, and Tulare Counties), and the greater Los Angeles area. Figure 3. Figure 3. Dynamic Continuous- Area Space- Time (DYCAST) risk maps (top) and timeline (bottom) of West Nile virus epidemic in Sacramento County, California, 2. Within timeline, black bars represent reported human cases within Sacramento County.. Prospective modeling began on June 1. July 1 the system was fully implemented and integrated into the CDPH WNV Surveillance Program. This implementation involved running the DYCAST procedure for analysis regions every weekday through November 1, 2. Figure 3) were generated and made available in real time to mosquito control agencies via the CVEC password- protected website, the California Vectorborne Disease Surveillance Gateway (www. These interactive maps were overlaid with county boundaries, streets, and locations of reported and WNV- positive dead birds. Implementation 2. Addresses of where dead birds were found were automatically geocoded in real time by using the Yahoo Maps application programming interface (Yahoo! Inc., Sunnyvale, CA, USA), which allowed hotline staff to validate location data while callers remained on the line; birds not automatically geocoded were omitted from DYCAST analysis. Interactive DYCAST risk maps were made available online to local mosquito control agencies and integrated with dead bird, mosquito, and sentinel chicken surveillance data from May 1 through October 3. May 1 through August 3. March 1 through August 3. Statewide reports of DYCAST activity, including maps and animations of high- risk areas over time, were sent to local agencies on a routine basis. A real- time alert system was also introduced in 2. DYCAST reports and interpretations for counties experiencing rapidly increasing or elevated levels of high- risk areas (8). In December of 2. DBSP were provided by email to 6. DYCAST to assist mosquito larviciding or adulticiding activities each year. For agencies that participated in the 2. DYCAST program, the 2. DYCAST results were used . Rate ratios (RRs) were used to compare annual DYCAST prediction rates of reported human WNV cases between agencies that did and did not use DYCAST to assist each mosquito control activity (2. Results. Figure 4. Figure 4. Percentages of reported human West Nile virus cases within Sacramento County (red line) and remainder of analysis regions (black line) predicted by Dynamic Continuous- Area Space- Time (DYCAST) in 2. During 2. 00. 5, a total of 1. DBSP hotline, > 3 million hits were made to the website, and 1. California (Table 1) (2. DYCAST identified high risk in 9. Relative risk of a WNV case in high- risk cells compared with low- risk cells was 3. Sensitivity and specificity of the DYCAST system were 8. Table 2). Prevalence of cells containing cases was 0. Overall, 2. 89/3. Table 3), with cells identified as high risk before onset of illness by a mean of 3. A total of 2. 52/3. According to the 2. DYCAST results to assist public education or to promote dead bird reporting in 2. DYCAST risk maps were also used to direct WNV surveillance (and ultimately control) efforts as early as the pilot phase, when 2 emerging clusters of high- risk cells were identified around the Arden- Arcade and Citrus Heights regions of Sacramento County on June 2. Figure 3, June 2. These results were immediately shared with the Sacramento- Yolo Mosquito & Vector Control District (SYMVCD), which used the risk maps to deploy mosquito traps within the 2 high- risk clusters on June 2. D. On June 2. 9, SYMVCD collected and detected 4 WNV- positive Cx. Additionally, both human cases from Sacramento County with onset of illness before June 2. DYCAST as high risk, 1. Figure 3, June 2. Within Sacramento County, DYCAST predicted 1. Figure 4). After 2. Table 1); the percentage of successfully geocoded dead bird reports ranged from 9. The statewide DYCAST prediction rates for reported human cases during 2. Responses to the 2. Results indicated that most of the agencies that responded each year used DYCAST to assist larviciding or adulticiding activities (Table 4). DYCAST prediction rates were significantly higher for agencies that answered . Conversely, the prediction rate was significantly lower for agencies answering . However, excluding the most extreme outlier with respect to total number of cases, an agency in Kern County whose jurisdiction included 4. RRs were not significant in 2. Table 4). Discussion. Results from prospective implementation of the DYCAST system in California indicate that the risk model provided accurate and early identification of areas at high risk for WNV transmission to humans during a statewide epidemic in 2. Our findings indicate that DYCAST yielded high levels of sensitivity and specificity for predicting human cases during the 2. WNV case was > 3. Given the low prevalence of cells containing cases (0. DYCAST, and the (> 1 cell) spatial scale of WNV transmission and mosquito control (8), positive predictive value is considered inferior to other metrics such as . Values maintained a moderate strength of chance- adjusted agreement for > 4 weeks before onset of illness, which indicates temporal robustness of model predictions. Figure 5. Figure 5. Analysis of West Nile virus cases, California, USA, 2. Gray region represents area within all analysis regions (black line) and Sacramento County (gray line, for scale) designated by Dynamic Continuous- Area Space- Time.. Cells containing predicted cases were identified as high risk before onset of illness by a mean of 3. Indeed, 2. 52/3. 54 (7. Additionally, because the DYCAST procedure only analyzes dead bird reports, it provided for more timely results than did active systems relying on the collection and testing of bird carcasses. Results from Sacramento County in 2. 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