Energy and exergy analyses of an integrated SOFC and coal gasification system

This paper examines an integrated gasification and solid oxide fuel cell (SOFC) system with a gas turbine and steam cycle that uses heat recovery of the gas turbine exhaust. Energy and exergy analyses are performed with two different types of coal. For the two different cases, the energy efficiency of the overall system is 38.1% and 36.7%, while the exergy efficiency is 27% and 23.2%, respectively. The effects of changing the reference temperature on the exergy destruction and exergy efficiency of different components are also reported. A parametric study on the effects of changing the pressure ratio on the component performance is presented.     

Guest Editor's Introduction: Special Section on Power-Aware Parallel and Distributed Computing (PAPADS)

The ten papers in this special section focus on power-aware parallel and distributed computing (PAPADS).     

Durability of PEM fuel cell cathode in the presence of Fe and Al

The contamination effects of Fe³⁺ and Al³⁺ on the performance of polymer electrolyte membrane fuel cells were investigated by continuously injecting Fe³⁺ or Al³⁺ salt solution into the air stream of an operating fuel cell. Both metal ions individually caused significant cell performance degradation at a level of only 5 ppm mol in air. In addition, elevated temperature accelerated fuel cell performance degradation in the presence of Fe³⁺. Moreover, the presence of Fe³⁺ in an operating fuel cell resulted in the cell's sudden death, due to the formation of membrane pinholes that may have been promoted by the enhanced production of peroxy radicals catalyzed by Fe species. Half-cell tests in liquid electrolyte revealed that the presence of Al³⁺ in the electrolyte changed the kinetics and mechanisms of the oxygen reduction reaction by reducing the kinetic current densities and the electron transfer number.     

A methodology for measuring interface fracture properties of composite materials

A methodology is presented for measuring interface fracture properties of composite materials. A bimaterial Brazilian disk specimen with a crack along the interface is employed. The specimen is analyzed by means of the finite element method and a conservative integral to determine stress intensity factors as a function of loading angle and crack length. A weight function is employed to determine the effect of residual curing stresses on the stress intensity factors. These are combined to determine the critical interface energy release rate _ic as a function of stress intensity phase angle for tests carried out on a glass/epoxy material pair.     

A 2 GHz Phase-Locked Loop Frequency Synthesizer with On-Chip VCO

This paper discusses the implementation of the building blocks for a 2 GHz phase-locked loop frequency synthesizer in a standard 0.5 m BiCMOS process. These blocks include a low-power optimized dual modulus prescaler which is able to operate with input frequencies up to 2.7 GHz, a phase detector with extremely constant gain throughout the input phase difference range, a chargepump with a rail-to-rail output, and an on-chip voltage-controlled oscillator.     

Machine Learning Approaches to Detect DoS and Their Effect on WSNs Lifetime

Energy and security remain the main two challenges in Wireless Sensor Networks (WSNs). Therefore, protecting these WSN networks from Denial of Service (DoS) and Distributed DoS (DDoS) is one of the WSN networks security tasks. Traditional packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of attacks. This paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life time. We examined the performance metrics of different machine learning classification categories such as K-Nearest Neighbour (KNN), Logistic Regression (LR), Support Vector Machine (SVM), Gboost, Decision Tree (DT), Naïve Bayes, Long Short Term Memory (LSTM), and Multi-Layer Perceptron (MLP) on a WSN-dataset in different sizes. The test results proved that the statistical and logical classification categories performed the best on numeric statistical datasets, and the Gboost algorithm showed the best performance compared to different algorithms on average of all performance metrics. The performance metrics used in these validations were accuracy, F1-score, False Positive Ratio (FPR), False Negative Ratio (FNR), and the training execution time. Moreover, the test results showed the Gboost algorithm got 99.6%, 98.8%, 0.4% 0.13% in accuracy, F1-score, FPR, and FNR, respectively. At training execution time, it obtained 1.41 s for the average of all training time execution datasets. In addition, this paper demonstrated that for the numeric statistical data type, the best results are in the size of the dataset ranging from 3000 to 6000 records and the percentage between categories is not less than 50% for each category with the other categories. Furthermore, this paper investigated the effect of Gboost on the WSN lifetime, which resulted in a 32% reduction compared to other Gboost-free scenarios.     

Application of the standard coupled-mode formalism to the analysis of holey photonic crystals

Presented below is a new, Standard Coupled-mode Theory (CMT) based approach for analysis of optical characteristics of holey photonic crystals (i.e., photonic devices, built on periodicity of holes in dielectric media). This class of devices encompasses the majority of photonic crystal fibres and several kinds of modern thresholdless lasers. Naturally, holey photonic crystals were considered as a sequence of holes, surrounded by dielectric media. This model made it impossible to utilise CMT for analysing their characteristics. The underlying idea of our approach is a different physical model, considering holey photonic devices as a sequence of coupled dielectric spots (waveguides), surrounded by air. This model can be combined with the Standard Coupled-mode formalism. The latter combination allows fast (on a timescale of several minutes to tens of minutes) and accurate analysis of holey photonic devices. Moreover, it gives a deeper insight into the behaviour of EM fields in holey photonic crystals.     

Ant colony optimization algorithm to solve for the transportation problem of cross-docking network

This paper addresses the transportation problem of cross-docking network where the loads are transferred from origins (suppliers) to destinations (retailers) through cross-docking facilities, without storing them in a distribution center (DC). We work on minimizing the transportation cost in a network by loading trucks in the supplier locations and then route them either directly to the customers or indirectly to cross-docking facilities so the loads can be consolidated. For generating a truck operating plan in this type of distribution network, the problem was formulated using an integer programming (IP) model and solved using a novel ant colony optimization (ACO) algorithm. We solved several numerical examples for verification and demonstrative purposes and found that our proposed approach finds solutions that significantly reduce the shipping cost in the network of cross-docks and considerably outperform Branch-and-Bound algorithm especially for large problems.     

A computer-aided ECG diagnostic tool

Jordan lacks companies that provide local medical facilities with products that are of help in daily performed medical procedures. Because of this, the country imports most of these expensive products. Consequently, a local interest in producing such products has emerged and resulted in serious research efforts in this area. The main goal of this paper is to provide local (the north of Jordan) clinics with a computer-aided electrocardiogram (ECG) diagnostic tool in an attempt to reduce time and work demands for busy physicians especially in areas where only one general medicine doctor is employed and a bulk of cases are to be diagnosed. The tool was designed to help in detecting heart defects such as arrhythmias and heart blocks using ECG signal analysis depending on the time-domain representation, the frequency-domain spectrum, and the relationship between them. The application studied here represents a state of the art ECG diagnostic tool that was designed, implemented, and tested in Jordan to serve wide spectrum of population who are from poor families. The results of applying the tool on randomly selected representative sample showed about 99% matching with those results obtained at specialized medical facilities. Costs, ease of interface, and accuracy indicated the usefulness of the tool and its use as an assisting diagnostic tool.