Global warming potential of the sulfur–iodine process using life cycle assessment methodology

A life cycle assessment (LCA) of one proposed method of hydrogen production – thermochemical water-splitting using the sulfur–iodine cycle couple with a very high-temperature nuclear reactor – is presented in this paper. Thermochemical water-splitting theoretically offers a higher overall efficiency than high-temperature electrolysis of water because heat from the nuclear reactor is provided directly to the hydrogen generation process, instead of using the intermediate step of generating electricity. The primary heat source for the S–I cycle is an advanced nuclear reactor operating at temperatures corresponding to those required by the sulfur–iodine process. This LCA examines the environmental impact of the combined advanced nuclear and hydrogen generation plants and focuses on quantifying the emissions of carbon dioxide per kilogram of hydrogen produced. The results are presented in terms of global warming potential (GWP). The GWP of the system is 2500 g carbon dioxide-equivalent (CO₂-eq) per kilogram of hydrogen produced. The GWP of this process is approximately one-sixth of that for hydrogen production by steam reforming of natural gas, and is comparable to producing hydrogen from wind- or hydro-electric conventional electrolysis.     

Intelligent and Efficient Strategy for Unstructured Environment Sensing Using Mobile Robot Agents

In field environments it is not usually possible to provide robots in advance with valid geometric models of its task and environment. The robot or robot teams need to create these models by scanning the environment with its sensors. Here, an information-based iterative algorithm to plan the robot's visual exploration strategy is proposed to enable it to most efficiently build 3D models of its environment and task. The method assumes mobile robot (or vehicle) with vision sensors mounted at a manipulator end-effector (eye-in-hand system). This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This is achieved by utilizing a metric derived from Shannon's information theory to determine optimal sensing poses for the agent(s) mapping a highly unstructured environment. This map is then distributed among the agents using an information-based relevant data reduction scheme. This method is particularly well suited to unstructured environments, where sensor uncertainty is significant. Issues addressed include model-based multiple sensor data fusion, and uncertainty and vehicle suspension motion compensation. Simulation results show the effectiveness of this algorithm.     

A HYBRID INTELLIGENT MODEL BASED ON EVOLUTIONARY FUZZY CLUSTERING AND SYNDICATE NEURAL NETWORKS

In this article, a new hybrid intelligent model comprising a cluster allocation and adaptation component is developed for solving classification and pattern recognition problems. Its computation ability has been verified through various benchmark problems and biometric applications. The proposed model consists of two components: cluster distribution and adaptation. In the first module, mean patterns are distributed into the number of clusters based on the evolutionary fuzzy clustering, which is the basis for network structure selection in next module. In the second module, training and subsequent generalization is performed by the syndicate neural networks (SNN). The number of SNNs required in the second module will be same as the number of clusters. Whereas each network contains as many output neurons as the maximum number of members assigned to each cluster. The proposed novel fusion of evolutionary fuzzy clustering with a neural network yields superior performance in classification and pattern recognition problems. Performance evaluation has been carried out over a wide spectrum of benchmark problems and real-life biometric recognition problems with noise and occlusion. Experimental results demonstrate the efficacy of the methodology over existing ones.     

Trajectory control of a PUMA robot arm by inversion and servocompensation

Based on invertibility and functional reproducibility, an approach to the control of the PUMA arm with six rotational degrees of freedom is presented. The control system has two important features: (i) the ability for fast, precise trajectory tracking; and (ii) robustness to uncertainty in the system, such as variable payload, inertia, etc. The control law derived using invertibility gives decoupled, independently controlled responses in each joint angle using torquers. For robustness, a first-order servocompensator is designed for each decoupled inner loop driven by the joint angle error. For smooth joint angle responses, a command generator is constructed that produces the reference trajectories to be tracked. Simulation results are presented to show that rapid, accurate trajectory following is achieved in the closed-loop system in spite of large payload uncertainty.     

The estimation of atmospheric corrections to one-channel (11 μ m) data from the AVHRR; simulation using AVHRR/ 2

It has been established that the sea-surface brightness temperatures Tb₄ in the 11 μ m channel and T_b4in the 12 μ m channel of the Advanced Very High Resolution Radiometer (AVHRR/ 2) are linearly related to a good degree of accuracy, i.e. T_b5= α+ β T_b4 Using AVHRR/ 2 data for various dates and from different parts of the world's oceans, the parameters a and 0 have been determined. The above relation may then be used for simulating T_b5 for those cases for which only Tb4 is available (e.g. for the AVHRR on TIROS-N, NOAA-6, NOAA-8, etc.). The brightness temperature TM and pseudo-brightness temperature T_b5 then enable one to use the split-window technique for estimating atmospherically-corrected sea-surface temperatures (SSTs) from the 11μ m channel data alone. Such an atmospheric correction technique should be a possibility because the 11μ m channel of the AVHRR on the various satellites in question are almost identical

This technique has been used with two split-window algorithms for correcting the data from the 11μ m channel of the AVHRR instrument on the TIROS-N satellite obtained off south-western Portugal. One of the algorithms gives ‘ skin’ temperatures and the other algorithm gives bulk temperatures. The resulting SSTs for twelve dates from 15 June 1979 to 14 June 1980 have been compared with sea-surface (skin) temperatures which were obtained with airborne radiometer data obtained on the same dates.     

Hybrid NSCT domain multiple watermarking for medical images

Multimedia Tools and Applications - Medical image watermarking is a challenging area of research. High bandwidth, secure transmission of patient’s data among hospitals and hiding capacity are...