National Academy Foundation

The global freshwater demand production is steadily growing due to demographic expansion and industrial expansion. The utilization of desalination technology is experiencing a rise in order to fulfill this growing demand. SSs, a type of desalination technology, possess the advantages of low maintenance and affordability. Nevertheless, their productivity is constrained. This paper aims to offer an extensive examination of different classifications of SS. This includes an analysis of designs that are both passive and active, as well as both single- and multiple-effect variations.Additionally, the paper will explore various enhancements aimed at increasing productivity, such as the implementation of reflectors, mechanisms for storing heat, fins, collectors, and techniques for improving thermal and fluid transport. The inclusion of greenhouse and photovoltaic-thermal SS is additionally encompassed within the scope of this study. The capabilities of PCM in improving performance are highly encouraging, suggesting the need for future research in these and related domains to promote wider adoption of SS technology.

Concept design and optimization for a high-temperature superconducting (HTS) rotor of a 100-kW generator is studied in this paper. The rotor has eight HTS magnets constructed by air-cored racetrack coils. The HTS magnets with a unique circular cross-sectional shape can produce a gap field over 2.0 T. The present design is based on a new graphical method developed to estimate the maximum operating current of an HTS magnet that takes both I c -B characteristics and angular dependence into consideration. The optimized stepped shape design saved more than 8% of the HTS material compared with the rectangular one without sacrificing the gap field.

This article summarizes 27 years of observations on the growth status of Scots pine artificial stands established after treating seeds with para-aminobenzoic acid (concentration range: 3.7–18.2 mM) one time. A long-term stimulating effect of PABA on the height growth (up to 47%) and diameter (up to 42%) of artificial stands is discovered. By the age of 27 years, self-pruning of the artificial stands increased by 18%. Possible mechanisms of long-term PABA physiological effect are now being discussed.

The congestion control of TCP Vegas is more stable and brilliant than other TCP versions such as Westwood Plus because of the congestion control before collision in Ad Hoc networks with frequent topology changes. Nevertheless, Vegas has less competitive ability when its data flow coexists with other protocols'. In addition, it cannot make full advantage of available bandwidth to transmit packets. The research aims to propose an improved TCP Vegas, ICATCP, which has three enhanced aspects in congestion avoidance phases. I. The lower layers' parameters will be considered in throughput model to improve the accuracy of theoretical throughput. II. Forward throughput prediction mechanism with revision based on Grey Prediction is used to promote the online cwnd control. III. The optimal exploring mechanism based on Q-Learning is applied to search the more reasonable changing size of congestion window. The simulation results show that the ICATCP has higher throughput, lower delay, more fair allocation of bandwidth than Vegas and Westwood Plus in multi-hops Ad Hoc scenarios.

Notice of Violation of IEEE Publication Principles<br><br>"Comparative Study Among Different Neural Net Learning Algorithms Applied to Rainfall Predication"<br>by Smita Kulkarni and Milind Mushrif <br>in the Proceedings of the International Conference on Electronic Systems, Signal Processing and Computing Technologies" January 2014, pp. 209-216<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:<br><br>"Comparative Study Amoung Different Neural Net Learning Algorithms Applied to Rainfall Time Series"<br>by Surajit Chattopadhyay and Goutami Chattopadhyay<br>in Meteorological Applications, 15, Wiley Interscience, April 2008, pp. 273-280<br><br> <br/> The present article reports studies to identify a non-linear methodology to forecast the time series of average summer-monsoon rainfall over India. Three advanced backpropagation neural network learning rules namely, momentum learning, conjugate gradient descent (CGD) learning, and Levenberg -- Marquardt (LM) learning, and a statistical methodology in the form of asymptotic regression are implemented for this purpose. Monsoon rainfall data pertaining to the years from 1871 to 1999 are explored. After a thorough skill comparison using statistical procedures the study reports the potential of CGD as a learning algorithm for the backpropagation neural network to predict the said time series.

Current pulses flowing along a metallic target obliquely irradiated by Z pinch-generated X-rays are measured. The leading interaction mechanism shows a strong dependence on incident X-ray intensity in addition to photon energy. Photoelectric effect expected to explain the observed current is not vital in the case of intense irradiation used in our experiments. The measured results are attributed to Compton current and thermocurrent on the same level. Simple analytical modeling of radiation demonstrates that obliquely incident X-ray-metal interaction is an effective method for generating directional electromagnetic pulse with its energy and intensity being of interest for practical purposes.

Cloud computing is a new trend of computer science and technology. Cloud computing may become a major tool for researchers to access processors and storage. Cloud computing brings both opportunities and challenges to high performance computing (HPC). Infinite on-demand computing resource can make HPC much more convenient and common than ever before. However, the virtualization paradigm which has been widely used in the cloud computing systems will decrease the running efficiency of the physic machine. We described some difficulties to implement high performance computing of finite element analysis in the cloud computing systems, and gave some candidate solutions in this article.