Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

An introduction to heat transfer

Solar Engineering Of Thermal Processes

Exergy assessment and energy integration of a novel solar-driven liquid carbon dioxide and liquefied natural gas cogeneration system using liquid air cold energy recovery

We report the photoacoustic (PA) response in the terahertz (THz) range by employing a detection process actuated with a silicon cantilever pressure sensor and a carbon-based radiation absorber. The detection relies on the mechanical response of the cantilever, when the volume of the carrier gas inside the PA cell expands with the heat produced by the radiation absorber. The detector interferometrically monitors the movement of the cantilever sensor to generate the PA signal. We selected the absorber material with the highest THz responsivity for detailed studies at 1.4 THz (214 µm wavelength). The observed responsivities of two different radiation absorbers are nearly the same at 1.4 THz and agree within 10% with responsivity values at 0.633 µm wavelength. The results demonstrate the potential of covering with a single PA detector a broad spectral range with approximately constant responsivity, large dynamic range, and high damage threshold.

Terahertz radiation detection with a cantilever-based photoacoustic sensor.

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

The strict complementary slackness condition (SCSC) is an important concept in the duality theory of linear programming (LP). The current study aims at extending this concept to the framework of linear fractional programming (LFP). First, we define this concept in this framework and demonstrate the existence of a strict complementary solution - a pair of primal and dual optimal solutions satisfying the SCSC. Second, we show that the problem of finding such a solution reduces to that of identifying a relative interior point of a polyhedron. More recently, Mehdiloozad et al. (2016) have addressed the latter problem by proposing an LP problem. Using their proposed LP problem, we finally develop two procedures for finding a strict complementary solution.

The strict complementary slackness condition in linear fractional programming

In this paper we shall consider the Symmetrical Hierarchical Network (SHN) and show that SHN possesses poor properties of survivability. There are several methods for raising the survivability of SHN. Here we consider the effectiveness of radial reserve to raise the survivability of SHN taking account of destruction of the main radial edges, and radial reserve.

Mohammad Hossein Ahmadi

Papers

Exergy assessment and energy integration of a novel solar-driven liquid carbon dioxide and liquefied natural gas cogeneration system using liquid air cold energy recovery

Terahertz radiation detection with a cantilever-based photoacoustic sensor.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

The strict complementary slackness condition in linear fractional programming

The Survivability of Symmetrical Hierarchical Networks with Radial Reserve