A novel optimization-based bandwidth-aware minimum power multicast routing algorithm in green wireless networks

Multicast routing in wireless networks that possess the wireless multicast advantage could significantly reduce the power and energy consumption. However, this kind of multicast routing that only addresses the transmission radius coverage might not be able to meet the bandwidth requirement of the users. As a result, additional transmissions are required to incur more energy consumption and carbon dioxide emissions that make existing algorithms not applicable to bandwidth constrained applications. In this paper, for the first time, we address the bandwidth aware minimum power multicast routing problem in wireless networks where the objective function is to minimize the total power consumption subject to the users?? bandwidth requirements. This problem is a challenging cross-layer design problem that requires seamless and sophisticated integrated design in the network layer (multicast routing) and physical layer (bandwidth-aware wireless transmission and power control). We first formulate this problem as a mixed integer linear programming problem and then propose a Lagrangian relaxation based algorithm to solve this problem. Numerical results demonstrate that the proposed approach is a sound green networking algorithm that outperforms the existing power efficient multicast routing approaches under all tested cases, especially in large bandwidth request, fine radius granularity, large group size and sparse network.     

Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach

Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation of early activity based duration estimation in software project management. The goal of the optimization is to reduce linguistic terms complexity and improve estimation accuracy of the fuzzy rule set while at the same time maintaining a similar degree of interpretability. The optimized numbers of linguistic terms in fuzzy rules by 27.76% using simplistic binary encoding mechanism managed to improve accuracy by 14.29% and reduce optimization execution time by 6.95% without compromising on interpretability in addition to promote improvement of knowledge base in fuzzy rule based systems.     

Convolutional neural networks for classification of music-listening EEG: comparing 1D convolutional kernels with 2D kernels and cerebral laterality of musical influence

Neural Computing and Applications - This paper highlights the ability of convolutional neural networks (CNNs) at classifying EEG data listening to different kinds of music without the requirement...     

Projecting CLPR constraints

The presentation of constraints in a usable form is an essential aspect of Constraint Logic Programming (CLP) systems. It is needed both in the output of constraints, as well as in the production of an internal representation of constraints for meta-level manipulation. Typically, only a small subset \(\tilde x\) of the variables in constraints is of interest, and so an informal statement of the problem at hand is: given a conjunction \(c(\tilde x,\tilde y)\) of constraints, express the projection \(\exists \tilde y c(\tilde x,\tilde y)\) ofc onto \(\tilde x\) in the simplest form. In this paper, we consider the constraints of the CLP(R) system and describe the essential features of its projection module. One main part focuses on the well-known problem of projection inlinear arithmetic constraints. We start with a classical algorithm and augment it with a procedure for eliminating redundant constraints generated by the algorithm. A second part discusses projection of the other object-level constraints: equations over trees and nonlinear equations. The final part deals with producing a manipulable form of the constraints, which complicates the projection problem.     

Parametric Sequence Alignment with Constraints

Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences. We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints. Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment. The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score. The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise. This reduces the number of inequalities significantly and strengthens the constraint representation with equalities. We present some preliminary results using parametric alignment on some general alignment queries.     

MMU GASPFA: A COTS multimodal biometric database

This paper describes the baseline corpus of a new multimodal biometric database, the MMU GASPFA (Gait–Speech–Face) database. The corpus in GASPFA is acquired using commercial off the shelf (COTS) equipment including digital video cameras, digital voice recorder, digital camera, Kinect camera and accelerometer equipped smart phones. The corpus consists of frontal face images from the digital camera, speech utterances recorded using the digital voice recorder, gait videos with their associated data recorded using both the digital video cameras and Kinect camera simultaneously as well as accelerometer readings from the smart phones. A total of 82 participants had their biometric data recorded. MMU GASPFA is able to support both multimodal biometric authentication as well as gait action recognition. This paper describes the acquisition setup and protocols used in MMU GASPFA, as well as the content of the corpus. Baseline results from a subset of the participants are presented for validation purposes.     

Formulating efficient software solution for digital image processing system

Digital image processing systems are complex, being usually composed of different computer vision libraries. Algorithm implementations cannot be directly used in conjunction with algorithms developed using other computer vision libraries. This paper formulates a software solution by proposing a processor with the capability of handling different types of image processing algorithms, which allow the end users to install new image processing algorithms from any library. This approach has other functionalities like capability to process one or more images, manage multiple processing jobs simultaneously and maintain the manner in which an image was processed for later use. It is a computational efficient and promising technique to handle variety of image processing algorithms. To promote the reusability and adaptation of the package for new types of analysis, a feature of sustainability is established. The framework is integrated and tested on a medical imaging application, and the software is made freely available for the reader. Future work involves introducing the capability to connect to another instance of processing service with better performance. Copyright © 2015 John Wiley & Sons, Ltd.     

Utilization of Heavy Metal Molten Salts in the ARIES-RS Fusion Reactor

ARIES-RS is one of the major magnetic fusion energy reactor designs that uses a blanket having vanadium alloy structure cooled by lithium [1, 2]. It is a deuterium–tritium (DT) fusion driven reactor, having a fusion power of 2170 MW [1, 2]. This study presents the neutronic analysis of the ARIES-RS fusion reactor using heavy metal molten salts in which Li₂BeF₄ as the main constituent was mixed with increased mole fractions of heavy metal salt (ThF₄ or UF₄) starting by 2 mol.% up to 12 mol.%. Neutron transport calculations were carried out with the help of the SCALE 4.3 system by solving the Boltzmann transport equation with the XSDRNPM code in 238 neutron groups and a S ₈–P ₃ approximation. According to the numerical results, tritium self-sufficiency was attained for the coolants, Flibe with 2% UF₄ or ThF₄ and 4% UF₄. In addition, higher energy multiplication values were found for the salt with UF₄ compared to that with ThF₄. Furthermore, significant amount of high quality nuclear fuel was produced to be used in external reactors.     

Modification of PROMETHEUS Reactor as a Fusion Breeder and Fission Product Transmuter

This study presents the analyses of the fissile breeding and long-lived fission product (LLFP) transmutation potentials of PROMETHEUS reactor. For this purpose, a fissile breeding zone (FBZ) fueled with the ceramic uranium mono-carbide (UC) and a LLFP transmutation zone (TZ) containing the ⁹⁹TC and ¹²⁹I and ¹³⁵Cs isotopes are separately placed into the breeder zone of PROMETHEUS-H design. The neutronic calculations are performed by using two different computer codes, the XSDRNPM/SCALE4.4a neutron transport code and the MCNP4B Monte Carlo code. A range of analyses are examined to determine the effects of the FF, the fraction of ⁶Li in lithium (Li) and the theoretical density (TD) of Li₂O in the tritium breeder zone (TBZ) on the neutronic parameters. It is observed that the numerical results obtained from both codes are consistent with each other. It is carried out that the profiles of fission power density (FPD) are flattened individually for each FF (from 3 to 10%). Only, in the cases of FF ≥ 8%, the system is self sufficient from the point of view of tritium generation. The results bring out that the modified PROMETHEUS fusion reactor has capabilities of effective fissile breeding and LLFP transmutation, as well as the energy generation.     

Coupling effects in bending, buckling and free vibration of generally laminated composite beams

A closed form expression to determine the effective flexural modulus of a laminated composite beam is developed and presented in this contribution. This effective flexural modulus is applied to the bending, buckling and free vibration response of generally laminated composite beams with various boundary supports. The expression was developed using the combination of the Euler–Bernoulli beam and classical lamination theory. In addition the results of an extensive finite element analysis are used to validate the analytical model. The comparison of the analytical results, the finite element results and the experimental results showed good correlation. It is also observed that coupling response is an important variable that must be included in the computation of the effective flexural stiffness of generally laminated beam.