Pollution Control Programs of Large-Scale Livestock and Poultry Farms in the Dianchi Lake Basin

With the enlarging scale and intensifying production of livestock and poultry breeding, the environment pollution becomes increasingly prominent in the Dianchi Lake Basin since 1990s. According to the survey of ＂The First National Census of Pollution Sources＂, occurrence and discharge of pollutants in large-scale livestock and poultry farms in this region were first understood. The pollution characteristics of large-scale live- stock and poultry breeding were also analyzed deeply. On this basis, the significance of pollution control programs for environment protection was investigated from aspects of pollution control policy, technology management and publicity.

Safety control program for complex system based on behavior science

To control complex system's safety effectively,safety control program was supported based on the principles of behavioral science that shapes organizational be- havior,and organizational behavior produced individual behavior.The program can be structured into a model that consists of three modules including individual behavior rectifi- cation,organization behavior diagnosis and model of safety culture.The research result not only reveals the deep cause of complex system accidents but also provides structural descriptions with the accidents cause.

Evaluation of a Voluntary Control Program for the Detection of Bovine Leukemia Virus Antibodies Based on Agar Gel Immunodiffusion Test in Dairy Farms in Costa Rica

Cattle from 20 dairy farms were serologically tested over a five-year period using agar gel immunodiffusion test (AGIDT) as part of a voluntary Bovine Leukemia Virus (BLV) control program. After five years of removing infected animals from the herds based on BLV-AGIDT serological status, blood samples from 332 cattle in these farms were collected and analyzed side by side by AGIDT and enzyme-linked immunosorbent assay (ELISA) to detect antibodies against BLV. AGIDT detected 29.2% (97) and 16.0% (53) of the animals as positive and weak positive respectively, whereas ELISA detected 58.2% (193) cattle as positive. The prevalence of BLV-antibodies determined with AGIDT in the dairy farms oscillated between 0% and 86%, whereas prevalence determined by ELISA ranged between 28% and 100% in the same farms. Although both techniques showed similarly results in farms with high BLV-prevalence, ELISA detected a larger proportion of BLV-positive, especially in farms with low or no BLV-prevalence based on AGIDT, leading to wrong assumptions in terms of farm level control efforts. Our results strongly suggest that AGIDT alone is inadequate to implement BLV control programs and ELISA is a more adequate test for BLV surveillance and control programs.

Development, Delivery and Evaluation of a Safety Training Program on Demolition for Blight Reduction

The main objective of the work presented in this paper was to develop a customized safety training program that can be incorporated into the demolition projects undertaken as part of blight reduction efforts in urban centers. A subsidiary objective was to devise and implement a safety program evaluation methodology, and gain insights on the relationships between knowledge acquisition through training and trainee demographics. Salient aspects of blight elimination efforts, as well as the main facets of building demolition practices and requirements, were reviewed. Information on various related safety and health hazards was studied in depth with a focus on demolition operations dealing with blighted properties. A unique safety hazard awareness training program was created for demolition workers, contractors and inspectors based on this research. In addition to devising a curriculum of relevant training topics along with traditional and online delivery systems to be employed, effectiveness evaluation instruments were formulated. Based on the limited data collected from the trainees it was concluded that the program was well-received by them and provided effective learning. It was also found that no statistically significant associations existed between the knowledge gain of the trainees, and either their experience level or union status, after taking this training.

Improving tuberculosis case detection in underdeveloped multi-ethnic regions with high disease burden:a case study of integrated control program in China

Background:In the underdeveloped multi-ethnic regions of China,high tuberculosis(TB)burden and regional inequity in access to healthcare service increase the challenge of achieving the End TB goals.Among all the provinces,the highest TB burden is reported in Xinjiang,where ethnic minorities and older people have suffered most.However,current case-finding strategy is inadequate given the complex social determinants and suboptimal case detection rates.Thus,we developed an integrated TB control program to improve case detection and conducted a pilot in Xinjiang from 2014 to 2015.In this case study,we summarized the activities and key findings.We also shared the experiences and challenges of implementing interventions and provided recommendations to inform the TB control program in the future.Case presentation:The pilot interventions were implemented in one selected town in Yining based on local TB control programs.By applying tailor-made educational materials,outreach TB educational activities were conducted in diverse ways.In 22 Masjids,the trained imams promoted TB education to the Muslims,covering 20,440 persontimes in 88 delivered preaching sessions.In seven schools,1944 students were educated by the teachers and contributed to educating 6929 family members.In the village communities,13,073 residents participated in household education and screening.Among them,12,292 people aged under 65 years were investigated for suspicious pulmonary TB symptoms,where six TB patients were diagnosed out of 89 TB suspects;781 older people were mobilized for screening directly by chest X-ray,where 10 patients were diagnosed out of 692 participants.Supportive healthcare system,multi-sectoral cooperation and multi-channel financing mechanism were the successful experiences of implementation.The interventions were proved to be more effective than the previous performance:the number of TB suspects consulting doctors and patients detected increased by 50%and 26%,respectively.The potential challenges,implications and recommendations should been taken into account for further program improvement.Conclusions:In underdeveloped multi-ethnic regions with high TB burden,improving case detection is necessary and the interventions can be feasible and effective within a supportive system.More intensive educational and training approaches,a high index of TB suspicion and prioritization of older people in screening are recommended.To sustain and scale up the program,the impacts,cost-effectiveness,feasibility and acceptability of interventions warrant further research and evaluation in each specific context.

Optimization of Numerical Control Program and Machining Simulation Based on VERICUT

In the machining process of large-scale complex curved surface,workers will encounter problems such as empty stroke of tool,collision interference,and overcut or undercut of the workpieces.This paper presents a method for generating the optimized tool path,compiling and checking the numerical control(NC)program.Taking the bogie frame as an example,the tool paths of all machining surface are optimized by the dynamic programming algorithm,Creo software is utilized to compile the optimized computerized numerical control(CNC)machining program,and VERICUT software is employed to simulate the machining process,optimize the amount of cutting and inspect the machining quality.The method saves the machining time,guarantees the correctness of NC program,and the overall machining efficiency is improved.The method lays a good theoretical and practical foundation for integration of the similar platform.

Soil organic carbon dynamics in Xilingol grassland of northern China induced by the Beijing-Tianjin Sand Source Control Program

To mitigate impacts of sandstorms on northern China, the Chinese government launched the Beijing- Tianjin Sand Source Control Program （BTSSCP） in 2000. The associated practices （i.e., cultivation, enclosure, and aerial seeding） were expected to greatly enhance grassland carbon sequestration. However, the BTSSCP-induced soil organic carbon （SOC） dynamics remain elusive at a regional level. Using the Xilingol League in Inner Mongolia for a case study, we examined the impacts from 2000 to 2006 of the BTSSCP on SOC stocks using the IPCC carbon budget inventory method. Results indicated that over all practices SOC storage increased by 1.7%, but there were large differences between practices. SOC increased most rapidly at the rate of 0.3 Mg C.ha-1 ＂yr-1 under cultivation, but decreased signifi- cantly under aerial seeding with moderate or heavy grazing （0.3 vs.0.6 Mg C-ha-I .yr-1）. SOC increases varied slightly for grassland types, ranging from 0.10 Mg C-ha-1 .yr-a for temperate desert steppe to 0.16 Mg C.ha-l.yr-1 for temperate meadow steppe and lowland meadow. The overall economic benefits of the SOC sink were estimated to be 4.0 million CNY. Aerial seeding with no grazing was found to be the most cost-effective practice. Finally, we indicated that at least 55.5 years （shortest for cultivation） were needed for the grasslands to reach their potential carbon stocks. Our findings highlight the importance and effectiveness of BTSSCP in promoting terrestrial carbon sequestration which may help mitigate climate change, and further stress the need for more attention to the effective- ness of specific practices.

Program structures and synchronization schemes in numerical coordinate controllers of three-wire welding

In the three-wire welding system, a welding process consists of the operations of four devices, namely three welding machines and one bogie. The operations need to be synchronized by a numerical coordinate controller （ NCC ）. In this paper, we will discuss a tnsk-job-procedure cubic program structure. Under this structure, the devices are synchronized and isolated at the same time. This cubic program structure can also be used as a reference for other multi-device or multi-unit manufacturing processes.

Approximate Dynamic Programming for Self-Learning Control

This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.

Stability of Nonlinear Systems Using Optimal Fuzzy Controllers and Its Simulation by Java Programming

In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.

Using Automation Controller System and Simulation Program for Testing Closed Circuits of Mini-Sprinkler Irrigation System

The field experiments were conducted at the experimental farm of Faculty of agricultural, southern Illinois University SIUC, USA. The project makes the irrigation automated. With the use of low cost sensors and the simple circuitry makes currently project a low cost product, which can be bought even by a poor farmer. This research work is best suited for places where water is scares and has to be used in limited quantity and this proposal is a model to modernize the agriculture industries at a mass scale with optimum expenditure. In the field of agricultural engineering, use of sensor method of irrigation operation is important and it is well known that closed circuits of Mini-sprinkler irrigation system are very economical and efficient. Closed circuits are considered one of the modifications of Mini-sprinkler irrigation system, and added advantages to Mini-sprinkler irrigation system because it can relieve low operating pressures problem at the end of the lateral lines. In the conventional closed circuits of Mini-sprinkler irrigation system, the farmer has to keep watch on irrigation timetable, which is different for different crops. Using this system, one can save manpower, water to improve production and ultimately profit. The data could be summarized in following: Irrigation methods under study when using lateral length 60 mcould be ranked in the following ascending order according the values of the predicted and measured head losses CM1M-SIS CM2M-SIS.The correlation (Corr.) coefficients were used to compare the predicted and measured head losses along the lateral lines of all the closed circuits designs. Generally, the values of correlation analysis were (>0.90) were obtained with 0% field slope60 mlength (experimental conditions) for all closed circuits.The interaction between irrigation methods: at the start there are significant differences between CM2M-SIS and CM1M-SIS.

Linear Programming for Optimum PID Controller Tuning

This work presents a new methodology based on Linear Programming (LP) to tune Proportional-Integral-Derivative (PID) control parameters. From a specification of a desired output time domain of the plant, a linear optimization system is proposed to adjust the PID controller leading the output signal to stable operation condition with minimum oscillations. The constraint set used in the optimization process is defined by using numerical integration approach. The generated optimization problem is convex and easily solved using an interior point algorithm. Results obtained using familiar plants from literature have shown that the proposed linear programming problem is very effective for tuning PID controllers.

Research on Program-controlled Power Source Based on DDS

Direct Digital Synthesis(DDS)chip was used in the design of program controlled power source in this paper.With the accurate control of Dual DDS chips by Micro Controller Unit(MCU),filter and power amplifier,this power source can generate voltage and current output with variable frequency,amplitude and phase.There are several advantages of this power source such as high power,high accuracy,output stable,light and convenient.

Fuzzy neural network control of underwater vehicles based on desired state programming

Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was presented, which used the technique of fuzzy neural network. The structure of fuzzy neural network was constructed according to the moving characters and the back propagation algorithm was deduced. Simulation experiments were conducted on general detection remotely operated vehicle. The results show that there is a great improvement in response and precision over traditional control, and good robustness to the model’s uncertainty and external disturbance, which has theoretical and practical value.

Optimal Control for a Class of Complex Singular System Based on Adaptive Dynamic Programming

This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.

CONTROLLING ROBOT MANIPULATORS BY DYNAMIC PROGRAMMING

A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.

Control strategy optimization using dynamic programming method for synergic electric system on hybrid electric vehicle

Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.

Bilevel linear programming model of charging for effluent based on price control

For the optimum price problem of charging for effluent, this paper analyzes the optimal Pigovian Tax and the serious information asymmetry problem existing in the application process of optimal Pigovian Tax, which is predominant in theory. Then the bilevel system optimizing decision-making theory is applied to give bilevel linear programming decision-making model of charging for effluent, in which the government (environmental protection agency) acts as the upper level decision-making unit and the polluting enterprises act as the lower level decision-making unit. To some extent, the model avoids the serious information asymmetry between the government and the polluting enterprises on charging for effluent.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.