Development of low-cost feed for culture of giant freshwater prawn (Macrobrachium rosenbergii de Man) in ponds

An experiment was conducted for 105 days in 12 earthen mini ponds of each 30m² size. Five different experimental diets containing 32% protein were formulated and prepared using fishmeal, shrimp meal, soybean meal, mustard oil cake, sesame meal, wheat bran and rice bran. A commercial shrimp diet (SABINCO starter-III) was assigned to treatment six and considered as the control. Prawns were stocked at the rate of 2.5 fry/m² and feed twice daily at the rate of 10% at the beginning and reduced to 8% for the last two months. The results of the experiment showed that prawn fed diets 1, 2, and 6 (control) showed significantly (P<0.05) highest weight gain among the dietary groups, while prawn fed diet 5 showed significantly lowest weight gain. The FCR values of diets ranged between 3.06 to 4.85. Prawns fed diet 1 and 6 showed significantly higher SGR, survival (%) and production among the dietary groups. The survival (%) of the prawns ranged between 46.6 to 66.6% and the production ranged between 304.5 to 563.3 kg/ha/105 days. The result of the study showed that diet containing 30% fishmeal, 5% shrimp meal, 5% soybean meal, 10% mustard oil cake, 10% sesame meal, 20% wheat bran, 18% rice bran, 1% oyster shell and 1% vitamin premix may be recommended for monoculture of M. rosenbergii.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models. © 2010 Nagengast et al.

Development of low cost feed using local ingredients for culture of freshwater prawn, Macrobrachium rosenbergii in ponds

Two experiments were conducted to formulate and evaluate test diets using locally available ingredients to find out suitable diets for mono and polyculture of Macrobrachium rosenbergii in ponds. The first experiment was conducted from 1 July 2003 to 29 September 2003 in 12 experimental ponds each measuring 30 square meters behind the Fisheries Faculty Building, BAU campus, Mymensingh. Three experimental diets containing 30% protein were formulated using fish meal, meat and bone meal, mustard oilcake, sesame meal and rice bran and assigned to treatments 1, 2 and 3, respectively. A special shrimp feed (Starter-II) from Saudi-Bangla Fish Feed Ltd. was assigned to treatment 4 (Control). Each treatment had three replications. Juveniles of M. rosenbergii (2.90±0.81g) were stocked at the rate of 4/square meter. Prawns were fed three times daily at the rate of 15% of their body weight at the beginning, which was gradually reduced to 10% and 5% for the last two months. There was no significant (P>0.05) difference between the weight gains of prawns fed diets 1 and 4 (control), but they were significantly (P<0.05) higher than those of diets 2 and 3. The FCR values of diets ranged between 2.61 to 3.36 with diets 1 and 4 showing significantly (P<0.05) lower FCR values. The survival rate of prawns ranged between 68 to 78% with prawns fed diets 1 and 4 showing significantly higher survival rate. The production of prawn ranged from 921 to 1,428 kg/ha/90 days and diet 1 gave the highest production. Treatment 1 gave the highest net profit ofTk. 161,980/ha/90 days. The second experiment was conducted from December, 2003 to April, 2004 to see the growth of over wintered M. rosenbergii juveniles in polyculture with indigenous major carps (catla and rohu) in ponds using formulated diets. Three isoenergetic experimental diets formulated using fish meal, meat and bone meal, mustard oil cake, rice bran, wheat bran and molasses, and a shrimp feed 'Golda special feed' from Saudi-Bangla Fish Feed Ltd. were assigned to treatments 1, 2, 3 and 4 (control), respectively, each treatment had two replications. Eight experimental ponds each measuring 80 square meters in the Field Laboratory Complex of the Faculty of Fisheries, BAU campus, Mymensingh were used. The mean initial weights of M. rosenbergii, catla and rohu were 1.60±0.01, 30.0±0.09 and 25.0±0.08 g, respectively. A total of 160 fish and prawn (20,000/ha) were stocked in each pond at the ratio of 2:1:1 (prawn: catla: rohu). Fish were fed at the rate of 3-5% of their body weight. Prawns fed diet 1, 2 and 4 showed higher weight gains compared to diet 3. The weight gain of catla was significantly higher in T1 while in case of rohu was higher in T1 and T4, respectively. There were no significant differences (P>0.05) in the survival rate of fish as obtained from different treatments. The overall total fish production ranged from 2196 to 2679 kg/ha/5 months. The highest production and the highest profit (Tk. 56,531/ha/5 months) was obtained from T1 and the lowest (Tk. 24,932/ha/5 months) from T4.

Surface excavation with model predictive control

This paper describes the application of variable-horizon model predictive control to trajectory generation in surface excavation. A nonlinear dynamic model of a surface mining machine digging in oil sand is developed as a test platform. This model is then stabilised with an inner-loop controller before being linearised to generate a prediction model. The linear model is used to design a predictive controller for trajectory generation. A variable horizon formulation is augmented with extra terms in the cost function to allow more control over digging, whilst still preserving the guarantee of finite-time completion. Simulations show the generation of realistic trajectories, motivating new applications of variable horizon MPC for autonomy that go beyond the realm of vehicle path planning. ©2010 IEEE.

Applying quality control in building energy modelling: Comparative simulation of a high performance building

Quality control is considered from the simulator's perspective through comparative simulation of an ultra energy-efficient building with EE4-DOE2.1E and EnergyPlus. The University of Calgary's Leadership in Energy and Environmental Design Platinum Child Development Centre, with a 66% certified energy cost reduction rating, was the case study building. A Natural Resources Canada incentive program required use of EE4 interface with DOE2.1E simulation engine for energy modelling. As DOE2.1E lacks specific features to simulate advanced systems such as radiant cooling in the CDC, an EnergyPlus model was developed to further evaluate these features. The EE4-DOE2.1E model was used for quality control during development of the base EnergyPlus model and simulation results were compared. Advanced energy systems then added to the EnergyPlus model generated small difference in estimated total annual energy use. The comparative simulation process helped identify the main input errors in the draft EnergyPlus model. The comparative use of less complex simulation programs is recommended for quality control when producing more complex models. © 2009 International Building Performance Simulation Association (IBPSA).

Optical tweezing beam control using liquid crystal adaptive optical elements

Liquid crystal (LC) adaptive optical elements are described, which provide an alternative to existing micropositioning technologies in optical tweezing. A full description of this work is given in [1]. An adaptive LC prism supplies tip/tilt to the phase profile of the trapping beam, giving rise to an available steering radius within the x-y plane of 10 μm. Additionally, a modally addressed adaptive LC lens provides defocus, offering a z-focal range for the trapping site of 100 μm. The result is full three-dimensional positional control of trapped particle(s) using a simple and wholly electronic control system. Compared to competing technologies, these devices provide a lower degree of controllability, but have the advantage of simplicity, cost and light efficiency. Furthermore, due to their birefringence, LC elements offer the opportunity of the creation of dual optical traps with controllable depth and separation.

Auto ID based control systems - An overview

This paper will provide a rationale for developing control systems based on the availability of automated identification (Auto ID) information provision. Much of the Auto-ID research has to date focussed on developing the essential infrastructure for dynamically extracting, networking and storing product data. These developments will help to revolutionise the accuracy, quality and timeliness of data acquired by Business Information Systems and should lead to major cost savings and performance improvements as a result. This paper introduces an additional phase of Auto ID research and development in which the nature of control system decisions is reconsidered in the light of the availability of ubiquitous, unique, item-level information. The paper will: (i) Indicate why the availability of ubiquitous, unique, item-level data can enable enhanced and fundamentally different control approaches and highlight potential benefits from control systems incorporating this Auto ID data (ii) Demonstrate what is required to develop control systems based around the availability of Auto ID data. (iii) Outline the research challenges in determining how such systems will be developed.

Optimal control with stochastic PDE constraints and uncertain controls

The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with the control function possibly decomposed into an unknown deterministic component and a known zero-mean stochastic component. The extra freedom provided by the stochastic dimension in defining cost functionals is explored, demonstrating the scope for controlling statistical aspects of the system response. One-shot stochastic finite element methods are used to find approximate solutions to control problems. It is shown that applying the stochastic collocation finite element method to the formulated problem leads to a coupling between stochastic collocation points when a deterministic optimal control is considered or when moments are included in the cost functional, thereby forgoing the primary advantage of the collocation method over the stochastic Galerkin method for the considered problem. The application of the presented methods is demonstrated through a number of numerical examples. The presented framework is sufficiently general to also consider a class of inverse problems, and numerical examples of this type are also presented. © 2011 Elsevier B.V.

A novel vector control approach for Single Phase Brushless Doubly Fed Machine

This paper proposed a novel control scheme for operating the Single Phase Brushless Doubly-Fed Machine (SPB) based on Stator-Flux-Oriented control algorithm. The SPB is a new type of Brushless Doubly-Fed Machine (BDFM) which shows a potential in applications which require adjustable speed such as Wind Power generation and speed adjustable Drive. The SPB can be applied to single-phase power system and the lower cost of the SPB makes the SPB suitable for low-rated power conversion applications. This paper develops the control scheme of the SPB with explicit mathematical analysis and block diagram of the controller. Experimental verification is also given. © 2011 IEEE.

Mass rearing of Aphidius gifuensis (Hymenoptera : Aphidiidae) for biological control of Myzus persicae (Homoptera : Aphididae)

The green peach aphid, Myzus persicae, is a major pest of tobacco, Nicotiana tabacum, in Yunnan province, China, where its control still depends on the use of insecticides. In recent years, the local government and farmers have sought to improve the biological control of this tobacco pest. In this paper, we present methods for mass rearing Aphidius gifuensis, a dominant endoparasitoid of M. persicae on tobacco plants in this region. The tobacco cultivar K326 (N. tabacum) was used as the host plant and M. persicae as the host insect. In the greenhouse, we collected tobacco seedlings for about 35 days (i.e., until the six-true-leaf stage), transferred them to 7.5-cm diameter pots, and kept these plants in the greenhouse for another 18 days. These pots were then transferred to an insectary-greenhouse, where the tobacco seedlings were inoculated with five to seven wingless adult M. persicae per pot. After 3 days, the infested seedlings were moved to a second greenhouse to allow the aphid population to increase, and after an additional 4 +/- 1 days when 182 +/- 4.25 aphid adults and nymphs were produced per pot, they were inoculated with A. gifuensis. With this rearing system, we were able to produce 256 +/- 8.8 aphid mummies per pot, with an emergence rate of 95.6 +/- 2.45%; 69% were females. The daily cost of parasite production (recurring costs only) was US$ 0.06 per 1000 aphid mummies. With this technique, we released 109 800 parasitoids in 1998, 196 000 in 1999, 780 000 in 2000, and 5 600 000 in 2001 during a 2-month period each year This production method is discussed with respect to countrywide usage in biological control and integrated control of M. persicae.

Automated 3D Vision Tracking for Project Control Support

On-site tracking in open construction sites is often difficult because of the large amounts of items that are present and need to be tracked. Additionally, the amounts of occlusions/obstructions present create a highly complex tracking environment. Existing tracking methods are based mainly on Radio Frequency technologies, including Global Positioning Systems (GPS), Radio Frequency Identification (RFID), Bluetooth and Wireless Fidelity (Wi-Fi, Ultra-Wideband, etc). These methods require considerable amounts of pre-processing time since they need to manually deploy tags and keep record of the items they are placed on. In construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. This paper presents a novel method for open site tracking with construction cameras based on machine vision. According to this method, video feed is collected from on site video cameras, and the user selects the entity he wishes to track. The entity is tracked in each video using 2D vision tracking. Epipolar geometry is then used to calculate the depth of the marked area to provide the 3D location of the entity. This method addresses the limitations of radio frequency methods by being unobtrusive and using inexpensive, and easy to deploy equipment. The method has been implemented in a C++ prototype and preliminary results indicate its effectiveness

Predictive control of a Boeing 747 aircraft using an FPGA

New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.

Performance evaluation of multiplexed model predictive control for a large airliner in nominal and contingency scenarios

Model predictive control allows systematic handling of physical and operational constraints through the use of constrained optimisation. It has also been shown to successfully exploit plant redundancy to maintain a level of control in scenarios when faults are present. Unfortunately, the computational complexity of each individual iteration of the algorithm to solve the optimisation problem scales cubically with the number of plant inputs, so the computational demands are high for large MIMO plants. Multiplexed MPC only calculates changes in a subset of the plant inputs at each sampling instant, thus reducing the complexity of the optimisation. This paper demonstrates the application of multiplexed model predictive control to a large transport airliner in a nominal and a contingency scenario. The performance is compared to that obtained with a conventional synchronous model predictive controller, designed using an equivalent cost function. © 2012 AACC American Automatic Control Council).

Sensor data scheduling for linear quadratic Gaussian control with full state feedback

Networked control systems (NCSs) have attracted much attention in the past decade due to their many advantages and growing number of applications. Different than classic control systems, resources in NCSs, such as network bandwidth and communication energy, are often limited, which degrade the closed-loop system performance and may even cause the system to become unstable. Seeking a desired trade-off between the closed-loop system performance and the limited resources is thus one heated area of research. In this paper, we analyze the trade-off between the sensor-to-controller communication rate and the closed-loop system performance indexed by the conventional LQG control cost. We present and compare several sensor data schedules, and demonstrate that two event-based sensor data schedules provide better trade-off than an optimal offline schedule. Simulation examples are provided to illustrate the theories developed in the paper. © 2012 AACC American Automatic Control Council).

Generating Options for Active Risk Control (GO-ARC): introducing a novel technique.

BACKGROUND: After investing significant amounts of time and money in conducting formal risk assessments, such as root cause analysis (RCA) or failure mode and effects analysis (FMEA), healthcare workers are left to their own devices in generating high-quality risk control options. They often experience difficulty in doing so, and tend toward an overreliance on administrative controls (the weakest category in the hierarchy of risk controls). This has important implications for patient safety and the cost effectiveness of risk management operations. This paper describes a before and after pilot study of the Generating Options for Active Risk Control (GO-ARC) technique, a novel tool to improve the quality of the risk control options generation process. OUTCOME MEASURES: The quantity, quality (using the three-tiered hierarchy of risk controls), variety, and novelty of risk controls generated. RESULTS: Use of the GO-ARC technique was associated with improvement on all measures. CONCLUSIONS: While this pilot study has some notable limitations, it appears that the GO-ARC technique improved the risk control options generation process. Further research is needed to confirm this finding. It is also important to note that improved risk control options are a necessary, but not sufficient, step toward the implementation of more robust risk controls.