Cotton growth and development is influenced by various uncontrollable environmental conditions. Temperature variations in the field can be created by planting at different dates. The objective of the present study was to evaluate the effect of planting dates and thermal temperatures (growing degree days) on yield of 4 genotypes viz. CIM-598, CIM-599, CIM-602, Ali Akbar-703. Plants were subjected to six planting dates during 2013 and 2014 in a trial conducted in randomized complete block design with four replications. Cotton genotypes exhibited significant differences for boll number, boll weight and seed cotton yield while CIM-599 produced the highest seed cotton yield of 2062 kg ha-1 on account of maximum boll number and boll weight. Highest seed cotton yield was recorded in planting dates from April 15 to May 1 whereas early and delayed planting reduced the yield due to less accumulation of heat units. Regression analysis revealed that increase of one unit (15 days) from early to optimum date (March 15 to April 15) increased yield by 93.58 kg ha-1. Delay in planting also decreased the seed cotton yield with the same ratio. Thus it is concluded that cotton must be sown from April 15 to May 1 to have good productivity in this kind of environment.

This paper presents an emergency vehicle priority control system based on connected vehicle technology, called MMITSS priority. Traditional preemption does not consider the effect of the current traffic situation, such as the presence of a freight vehicle in the dilemma zone, on an opposing movement and can have a significant negative impact on the minor movements of vehicles. A mixed integer linear programming model is developed which can consider the priority requests from multiple emergency vehicles and dilemma zone requests from freight vehicles that could be trapped in the dilemma zone. The optimization model provides an optimal schedule that minimizes the total weighted priority request delays and dilemma zone request, as well as some flexibility to adapt to other vehicles in real time. The flexible implementation of the optimal signal timing schedule is designed to improve the mobility of the non-emergency vehicles. The approach has been tested and evaluated using microscopic traffic simulation. The simulation experiments show that the proposed priority control method is able to improve the travel time of the vehicles on the minor street while ensuring safe passage of the freight vehicle at the dilemma zone without significantly delaying the emergency vehicles. The method is implemented at the Maricopa County SMARTDrive ProgramSM test bed in Anthem, Arizona.

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This paper investigates the trajectory tracking problem for a Multi-Input Multi-Output (MIMO) Twin Rotor Aerodynamic System (TRAS) using a hybrid architecture based on an H∞∞∞∞ controller and Iterative Learning Control (ILC). TRAS is a fast, nonlinear coupled system and therefore it is a challenging task to design a control system that ensures the tracking for fast changing trajectories. The controllers proposed in the literature for the TRAS through linear approaches tend to have a large control effort, while the ones designed using the nonlinear approaches track only for smooth input trajectories. Both issues are important from control point of view. In this paper, these issues are addressed by designing a feedback H∞∞∞∞ control that stabilizes the system and a feedforward ILC which reduces the control effort. The H∞∞∞∞ controller achieves the tracking for input trajectories with sharp edges, but the control effort required for tracking is large. With the proposed hybrid approach, tracking is achieved by the H∞∞∞∞ controller whereas the required control effort is reduced in each subsequent iteration by ILC. After a few iterations, accurate tracking at a minimized control effort is achieved. The simulations have been performed using MATLAB software and the controller designed through the proposed approach has been validated on nonlinear model of the system. The results of the proposed technique, compared with the flatness-based and back-stepping control strategies, show that the proposed controller ensures accurate tracking at the reduced control effort.

Growing cotton (Gossypium hirsutum L.) after wheat (Triticum aestivum L.) is an important cropping system in Pakistan. However, numerous tillage practices commonly applied for cotton production are not productive. Conservation tillage may optimize cotton yield and quality if nitrogen (N) is not a limiting factor. Field experiments were conducted on silty clay soil (Hyperthermic, and Typic Torrifluvents) of Dera Ismail Khan, Pakistan to study the impact of tillage techniques (zero (ZT), reduced (RT), and conventional tillage (CT)) and nitrogen, namely 0, 50, 100, 150, and 200 kg ha -1 on cotton yield and quality. Mean values for N revealed that bolls plant -1 , boll weight, seed cotton yield, ginning out turn (GOT), fiber length, strength, and micronaire were highest at 150-200 kg N ha -1 . Averaged over years, tillage × nitrogen revealed that RT had higher bolls plant -1 , boll weight, GOT, fiber length, and strength at 150-200 kg N ha -1 compared to other tillage system. The micronaire revealed that RT had no adverse effect on fiber fineness compared to ZT/ CT. RT had accumulated higher soil organic matter and total soil N compared to CT. RT with 150-200 kg N ha -1 may be a sustainable and environmentally safe strategy to enhance cotton yield and quality.