Minimum energy transmission scheduling subject to deadline constraints

We consider the problem of transmission scheduling of data over a wireless fading channel with hard deadline constraints. Our system consists of N users, each with a fixed amount of data that must be served by a common deadline. Given that, for each user, the channel fade state determines the throughput per unit of energy expended, our objective is to minimize the overall expected energy consumption while satisfying the deadline constraint. We consider both a linear and a strictly convex rate-power curve and obtain optimal solutions, based on dynamic programming (DP), and tractable approximate heuristics in both cases. For the special non-fading channel case with convex rate-power curve, an optimal solution is obtained based on the Shortest Path formulation. In the case of a linear rate-power curve, our DP solution has a nice “threshold” form; while for the convex rate-power curve we are able to obtain a heuristic algorithm with comparable performance with that of the optimal scheduling scheme. Alessandro Tarello received his M.Sc. and Ph.D. degrees in Electrical and Communication Engineering from Politecnico di Torino, Torino, Italy, in 2002 and 2006 respectively. He currently holds a Postdoctoral position at Politecnico di Torino. He visited the Laboratory for Information and Decision Systems at MIT, Cambridge, MA, USA, in 2004 and 2005. During Summer 2005 he also visited the Jet Propulsion Laboratory, Pasadena, CA, USA. He received the best student paper award at the Third International Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks (WiOPT’05). His research interests are in the fields of stochastic and fluid models for performance evaluation of packet networks and optimization techniques for wireless and ad-hoc networks. Jun Sun received his B.S. degree in Computer Engineering from University of Florida in 1997 and his M.S. in Electrical Engineering from Massachusetts Institute of Technology in 2002. He is currently a Ph.D. student in the Laboratory for Information and Decision Systems at MIT. His research interest is on communication networks with emphasis on satellite and wireless networks. Murtaza Zafer received his B.Tech degree in Electrical Engineering from the Indian Institute of Technology (IIT), Madras, India, in 2001 and his M.S. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT), MA, USA, in 2003. Currently, he is pursuing his doctoral studies at the Laboratory for Information and Decision Systems (LIDS) in the department of Electrical Engineering and Computer Science at MIT. He spent the summer of 2004 at the Mathematical Sciences Research center, Bell Laboratories and the summer of 2003 at Qualcomm, Inc. His research interests lie in queueing theory, information theory, control and optimization theory and its applications to wireless communication networks. He is the co-recipient of the best Student Paper award at WiOpt, 2005. He also received the Siemens (India) and Philips (India) award for academic excellence. Eytan Modiano received his B.S. degree in Electrical Engineering and Computer Science from the University of Connecticut at Storrs in 1986 and his M.S. and PhD degrees, both in Electrical Engineering, from the University of Maryland, College Park, MD, in 1989 and 1992 respectively. He was a Naval Research Laboratory Fellow between 1987 and 1992 and a National Research Council Post Doctoral Fellow during 1992–1993. Between 1993 and 1999 he was with MIT Lincoln Laboratory where he was the project leader for MIT Lincoln Laboratory’s Next Generation Internet (NGI) project. Since 1999 he has been on the faculty at MIT; where he is presently an Associate Professor. His research is on communication networks and protocols with emphasis on satellite, wireless, and optical networks. He is currently an Associate Editor for Communication Networks for IEEE Transactions on Information Theory and for The International Journal of Satellite Communications. He had served as a guest editor for IEEE JSAC special issue on WDM network architectures; the Computer Networks Journal special issue on Broadband Internet Access; the Journal of Communications and Networks special issue on Wireless Ad-Hoc Networks; and for IEEE Journal of Lightwave Technology special issue on Optical Networks. He is the Technical Program co-chair for Wiopt 2006, IEEE Infocom 2007, and ACM MobiHoc 2007.     

A review of gas engine driven heat pumps (GEHPs) for residential and industrial applications

This study reviews gas engine-driven heat pump (GEHP) systems for residential and industrial applications in terms of energetic and exergetic aspects for the first time to the best of the authors’ knowledge. These systems are novel heat pump systems (one of today's promising new technologies). Although the first investigations had been performed at late 1970s, the first merchandized GEHP was produced and introduced in the market in 1985. Gradually, it has become widespread all over the world for various purposes. Main application of GEHPs are for space and water heating/cooling purposes. However, they can be integrated to industrial applications, especially to drying processes.In this study, historical development of GEHP systems was briefly given first. Next, the operation of these systems was described, while studies conducted on them were reviewed and presented in tabulated forms. GEHPs were then modeled for performance evaluation purposes by using energy and exergy analysis methods. Finally, an illustrative example was given, while the results obtained were discussed. In addition, a new project on integration of GEHP systems to food drying processes in Turkey initiated by the authors was introduced. It is expected that this comprehensive study will be very beneficial to everyone involved or interested in the energetic and exergetic design, simulation, analysis and performance of assessment of GEHP systems.     

Improvements in microstructural,mechanical, and biocompatibility properties of nano-sized hydroxyapatites doped with yttrium and fluoride

Hydroxyapatite was doped with Y³⁺ (2.5, 5 and 7.5 mol%) and F⁻ (2.5 mol%) ions (2.5YFHA, 5YFHA, 7.5YFHA, respectively) to compare its structural and mechanical properties and cellular response with pure-hydroxyapatite. No second phases were observed by X-ray diffraction spectra of 2.5YFHA. Doped hydroxyapatites had F⁻ bonds in addition to OH⁻ bonds. Hydroxyapatites sintered at 900 and 1100 °C were in nano-size. 7.5YFHA sintered at 1300 °C had the highest microhardness value. 2.5YFHA sintered at 1100 °C had the highest fracture toughness value. MTT viability assays showed high cell attachments on 2.5YFHA. Cell proliferation on 2.5YFHA and 5YFHA sintered at 1100 and 1300 °C was comparable with the control after 5-day culture. The highest ALP production and calcium deposition were observed on all hydroxyapatites sintered at 1100 °C. 2.5YFHA sintered at 1100 °C can be an alternative for hydroxyapatite in orthopedic applications.     

Synthesis, Characterization and Crystal Structure of a Novel Three-Dimensional Supramolecular Framework Containing Ni···π Interaction Heteronuclear Complex: {[Cu(4(5)-Meim)4][Ni(CN)4] · H2O}n

The heteronuclear complex, {[Cu(4(5)-Meim)₄][Ni(CN)₄] · H₂O}_n (1), (4(5)-Meim = 4(5)-methylimidazole) was synthesized and characterized by FT-IR spectroscopy, single crystal X-ray diffraction, thermal analysis and elemental analysis. The Cu(II) ion has a distorted square planar geometry, extended to (4 + 2) weak coordination by two nitrogen atoms of the cyano group. The coordination sphere around the Ni(II) ion should be described as a 4 + 2 geometry with the four cyano groups and the axial coordination site is located at the imidazole ring though a weak Ni···π interaction. The coordination bond is much stronger than the Ni···π interactions and it is expected that the formation of the coordination bond will affect more significantly the position of the absorption bands associated with the vibrations of the ligand. In addition, the out-of-plane modes of 4(5)-Meim are shifted to higher frequencies relative to free ligand. We propose that these shifts are indicative of the weak CH∙∙∙π and Ni∙∙∙π interactions, according to the crystallographic and spectroscopic data.     

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.     

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.     

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.     

Ternary encoding based feature extraction for binary text classification

A novel framework for termset based feature extraction is proposed for binary text classification. The proposed approach is based on the encoding of the terms within a termset. The ternary codes ‘+1’ and ‘?1’ are used to represent the class that the term supports, whereas ‘0’ denotes no support to any of the classes. Four different encoding schemes are proposed where the term weights and the term occurrence probabilities in the positive and negative documents are used to define the ternary code of a given term. The ternary patterns are utilized to define novel features by splitting them into positive and negative codes where each code is treated as a different feature extractor. Use of the derived features individually and together with bag of words representation are both investigated. The histograms of the resultant features are also employed to study the improvements that can be achieved using a small number of additional features to augment bag of words representation. Experiments conducted on four benchmark datasets with different characteristics have shown that the proposed feature extraction framework provides significant improvements compared to the bag of words representation.     

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.