Assessment of the energy and exergy utilization efficiencies in the Turkish agricultural sector

This study deals with evaluating the energy and exergy utilization efficiencies in the Turkish agricultural sector over a 12‐year period from 1990 to 2001. In the energy and exergy analyses, two main energy sources, namely fuels and electricity, are taken into consideration, while the sectoral energy and exergy efficiencies are compared for this period. These main energy sources include diesel for tractors and other vehicles, and electricity for pumps. Overall energy utilization efficiencies are obtained to vary between 29.1 and 41.1%, while overall exergy utilization efficiencies are found to range from 27.9 to 37.4% in the analysed years, respectively. It may be concluded that the present technique proposed here may be used as a useful tool in analysing and evaluating the energy and exergy utilization efficiencies, identifying energy efficiency and/or energy conservation opportunities and dictating the energy strategies of countries. Copyright © 2005 John Wiley & Sons, Ltd.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

Aeroelastic tailoring using lamination parameters

The aim of the present work is to passively reduce the induced drag of the rear wing of a Formula One car at high velocity through aeroelastic tailoring. The angle-of-attack of the rear wing is fixed and is determined by the required downforce needed to get around a turn. As a result, at higher velocity, the amount of downforce and related induced drag increases. The maximum speed on a straight part is thus reduced due to the increase in induced drag. A fibre reinforced composite torsion box with extension-shear coupled upper and lower skins is used leading to bending-torsion coupling. Three-dimensional static aeroelastic analysis is performed loosely coupling the Finite Element code Nastran and the Computational Fluid Dynamics panel code VSAERO using ModelCenter. A wing representative of Formula One rear wings is optimised for minimum induced drag using a response surface methodology. Results indicate that a substantial induced drag reduction is achievable while maintaining the desired downforce during low speed turns.     

Vic-dioximes: A new class of sensitive materials for chemical gas sensing

Vic-dioximes, a class of organic chemical compounds, are proposed and characterized for the first time as sensitive materials for volatile organic compound sensing with sorption based chemical gas sensors. Their peculiar sensing properties described in this work originate in the oxime functional group which is a powerful H bond donor interacting strongly but reversibly with H bond acceptors. These specific interactions result in a high preferential enrichment of analyte molecules with H bonding acceptor capabilities in the sensitive material. Accordingly, sensitivity and selectivity for these compounds of vic-dioxime based sensors are high. The advantageous sensing properties are demonstrated in this work with quartz crystal microbalance sensors using 11 selected volatile organic compounds and a set of vic-dioximes varied in their substituents. Vic-dioximes with short alkylthiol substituents were found highly sensitive to such H bond acceptors as organic amines, alcohols, and esters with partition coefficients up to 26,000. At the same time they showed low affinity for aromatic compounds and chlorocarbons. Vic-dioximes are considered powerful sensing materials and interesting for practical use in chemical gas sensor arrays.     

Routing table updating by using intelligent agents

In a network, one of the important problems is making an efficient routing decision. Many studies have been carried out on making a decision and several routing algorithms have been developed. In a network environment, every node has a routing table and these routing tables are used for making routing decisions. Nowadays, intelligent agents are used to make routing decisions. Intelligent agents have been inspired by social insects such as ants. One of the intelligent agent types is self a cloning ant. In this study, a self cloning ant colony approach is used. Self cloning ants are a new synthetic ant type. This ant assesses the situation and multiplies through cloning or destroying itself. It is done by making a routing decision and finding the optimal path. This study explains routing table updating by using the self cloning ant colony approach. In a real net, this approach has been used and routing tables have been created and updated for every node.     

Is cheating a human function? The roles of presence,state hostility,and enjoyment in an unfair video game

In sports and board games, when an opponent cheats, the other players typically greet it with disdain, anger, and disengagement. However, work has yet to fully address the role of the computer cheating in video games. In this study, participants played either a cheating or a non-cheating version of a modified open-source tower-defense game. Results indicate that when a computer competitor cheats, players perceive the opponent as being more human. Cheating also increases player aggravation and presence, but does not affect enjoyment of the experience. Additionally, players that firmly believed that their opponent was controlled by the computer exhibited significantly less state hostility compared to players that were less certain of the nature of their competitor. Game designers can integrate subtle levels of cheating into computer opponents without any real negative responses from the players. The results indicate that minor levels of cheating might also increase player engagement with video games.     

An experimental study for the effect of different clearances on burr, smooth-sheared and blanking force on aluminium sheet metal

In this study, an experimental study was carried out to examine the effect of different clearances on smooth-sheared depth, burr height and blanking force. Aluminium sheet metals with 0.8, 1, and 1.5 mm thicknesses were used in the experiments. These experiments were carried out in circular blanking dies to 6, 8, 10, and 12 mm diameters. Six different clearances (0.009, 0.064, 0.12, 0.175, 0.231 and 0.287 mm) were used for every material and diameter. The results of the experiment show that burr, smooth-sheared and punch force is strongly related to the clearance value. The results are in agreement with the results of previous theoretical and experimental work in the literature.     

PET纤维纺丝中采用纳米微粒添加剂的相关问题

在许多市场和用途中采用尺寸更小的微粒材料的趋势正明显增长。在纤维纺丝中加入整个范围的添加剂（包含纳米微粒）开发具有特殊性能纺织品时存在着一些争论。纤维纺丝中的主要问题是开发低含量的添加剂。     

On disconjugacy and stability criteria for discrete Hamiltonian systems

By making use of new Lyapunov type inequalities, we establish disconjugacy and stability criteria for discrete Hamiltonian systems. The stability criteria are given when the system is periodic.     

Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks

In wind energy conversion systems, one of the operational problems is the changeability and discontinuity of wind. In most cases, wind speed can fluctuate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. Pitch control is the most efficient and popular power control method, especially for variable-speed wind turbines. It is a useful method for power regulation above the rated wind speed. This paper proposes an artificial neural network-based pitch angle controller for wind turbines. In the simulations, a variable-speed wind turbine is modeled, and its operation is observed by using two types of artificial neural network controllers. These are multi-layer perceptrons with back propagation learning algorithm and radial basis function network. It is shown that the power output was successfully regulated during high wind speed, and as a result overloading or outage of the wind turbine was prevented.