A Stream X-Machine Tool for Modelling and Generating Test Cases for Chronic Diseases Based on State-Counting Approach

Programming and Computer Software - In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents)...     

A simulated annealing algorithm for multi-agent systems: a job-shop scheduling application

In this paper, a parallel implementation of the modular simulated annealing algorithm for classical job-shop scheduling is presented. The implementation is for a multi agent system running on the distributed resource machine, which is a novel, scalable, distributed virtual machine based on Java technology. The problems tackled are well known, difficult benchmarks, widely used to measure the efficiency of metaheuristics with respect to both the quality of the solutions and the central processing unit time. The empirical results obtained show that the method proposed is successful in comparison with a sequential version of modular simulated annealing algorithm and other methods described in the literature.     

Characterization and correlation of crude oils from some wells in the North Western Desert,Egypt

Characterization and correlation of crude oils from some wells in the North Western Desert, based on six crude oil samples, were studied by different analytical techniques, including API gravity, sulfur content, nickel and vanadium, bulk compositions and saturated fraction obtained from gas chromatography have been studied. The results show that the crude oils are normal to medium aromatic oils, with high API gravity and high sulfur content. V, Ni, V/Ni and V/(V + Ni) reflecting oils might be sourced from non-clastic source rocks, possibly carbonates, deposited under anoxic-suboxic conditions. Bulk compositions revealing that the crude oils were derived from marine organic sources. While, the paraffins and naphthenes percent indicates that the oils belong to paraffinic to naphthenic oil types, deposited in slightly anoxic to suboxic conditions and contained marine organic matter. Thermal maturity data showed that the oil samples were generated from mature source rocks. This indicates the studied oil samples are well correlated with each other, where they are similar in their oil type maturation and source depositional environments.     

Inter-plant hydrogen integration with regeneration placement and multi-period consideration

Inter-plant hydrogen integration (IPHI) is getting more attention in recent years, as a result of the increasing demand for hydrogen in refinery processes, such as hydrotreating and hydrocracking. In this work, IPHI with regeneration scheme is analyzed. Indirect integration scheme is adopted, where hydrogen sources from different hydrogen networks are integrated via a centralized purifier, such as pressure swing adsorption (PSA) or membrane separation. The introduced model is able to select the optimum interception unit, which minimizes the total annualized cost. Besides, multi-period consideration is included in the analysis to address the effect of changes in operating conditions of the IPHI network on total hydrogen consumption. Two case studies are presented to demonstrate the applicability and usefulness of the proposed model.     

Time-variant balanced routing strategy for underwater wireless sensor networks

In the past decade, researchers’ interest in Underwater Wireless Sensors Networks has rapidly increased. There are several challenges facing the lifetime of UWSNs due to the harsh characteristics of the underwater environment. Energy efficiency is one of the major challenges in UWSNs due to the limited battery budget of the sensor nodes. In this paper, we aim at tackling the energy sink-hole problem that especially hits nodes close to the sink when they run out of battery power before other sensors in the network. We prove that we can evenly distribute the transmission load among mobile sensor nodes by letting sensor nodes adjust their transmission ranges. In this paper, we suppose that sensor nodes may adjust their transmission power up to three levels. Consequently, we strive for deriving the optimal load weight for each possible transmission power level that leads to fair energy consumption among all underwater sensors while taking into account the underwater sensors mobility. Performance results show that energy sink-hole problem is overcame and hence the network lifetime is maximized.

     

Multidirectional and multiscale edge detection via M-band wavelettransform

In this correspondence, the problem of directional and multiscale edge detection is considered. Orthogonal and linear-phase M-band wavelet transform is used to decompose the image into MxM channels. These channels are then combined such that each combination, which we refer to as decomposition filter, results in zero-crossings at the locations of edges corresponding to different directions and resolutions, and inherently performs regularization against noise. By applying a zero-crossing detector on the outputs of the decomposition filters, edge maps of desired resolution and direction are obtained. In addition, with the application of the Teager's energy operator at the analysis stage, it is possible to obtain a reduction in unwanted zero-crossings. Final edge maps of images are obtained through simple combinations of directional edge maps.     

Hop-timing estimation for FH signals using a coarsely channelizedreceiver

This paper addresses new hop-timing (epoch) estimation schemes which employ a coarsely channelized preprocessor in order to suppress the frequency and phase dependence in random frequency-hopping (FH) signals. Coarse channelization implies a bank of filters, covering the total spread bandwidth of the FH signal, whose number is much smaller than the size of the candidate hop frequency set. Linear and nonlinear combinations of preprocessor outputs are explored and compared. It is found that post-processing, rather than the size of the filter bank alone, is the determining factor on estimation performance. Performance evaluation is presented via both extensive computer simulations and analytical lower bounds. Comparisons with existing optimal and suboptimal systems are also provided     

Disclosing the Role of Defect-Engineered Metal–Organic Frameworks in Mixed Matrix Membranes for Efficient CO2 Separation: A Joint Experimental-Computational Exploration

Incorporation of defects in metal–organic frameworks (MOFs) offers new opportunities for manipulating their microporosity and functionalities. The so-called “defect engineering” has great potential to tailor the mass transport properties in MOF/polymer mixed matrix membranes (MMMs) for challenging separation applications, for example, CO₂ capture. This study first investigates the impact of MOF defects on the membrane properties of the resultant MOF/polymer MMMs for CO₂ separation. Highly porous defect-engineered UiO-66 nanoparticles are successfully synthesized and incorporated into a CO₂-philic crosslinked poly(ethylene glycol) diacrylate (PEGDA) matrix. A thorough joint experimental/simulation characterization reveals that defect-engineered UiO-66/PEGDA MMMs exhibit nearly identical filler–matrix interfacial properties regardless of the defect concentrations of their parental UiO-66 filler. In addition, non-equilibrium molecular dynamics simulations in tandem with gas transport studies disclose that the defects in MOFs provide the MMMs with ultrafast transport pathways mainly governed by diffusivity selectivity. Ultimately, MMMs containing the most defective UiO-66 show the most enhanced CO₂/N₂ separation performance—CO₂ permeability = 470 Barrer (four times higher than pure PEGDA) and maintains CO₂/N₂ selectivity = 41—which overcomes the trade-off limitation in pure polymers. The results emphasize that defect engineering in MOFs would mark a new milestone for the future development of optimized MMMs.     

A MC-CDMA Mobile Communication System Employing Pre-Rake and Transmit Diversity

In this paper, a multi-carrier code division multiple access (MC-CDMA) downlink mobile communication system employing pre-rake and dual transmit diversity is proposed. It combines high spectral efficiency with an immunity to channel dispersion and fading. It also ensures small size, cost and power consumption of the terminal. Theoretical and simulation results for the system under consideration are obtained. Depicted results show appreciable improvements of the proposed system over those previously known.Emad K. Al-Hussaini received his B.Sc degree in Electrical Communication Engineering from Ain-Shams University, Cairo, Egypt, in 1964 and his M.Sc and Ph.D. degrees from Cairo University, Giza, Egypt, in 1974 and 1977, respectively. From 1964 to 1970, he was with the General Egyptian Aeroorganization. Since 1970, he has been with the Department of Electronics and Communications, Faculty of Engineering, Cairo University, and is currently professor there. He was a research fellow at Imperial College, London, UK, and at the Moore School of Electrical Engineering, University of Pennsylvania, Philadelphia, PA, USA, in the academic years 1976/1977 and 1981/1982, respectively. In 1990, he received the Egyptian national encouragement award for outstanding engineering research. He has written several papers for technical international journals and conferences. His research interests include signal processing, fading channel communication, modulation, and cellular mobile radio systems. Dr Al-Hussaini is a senior member of IEEE. He is listed in Marquis Whos Who in the World and in the IBC (International Biographical Center, Cambridge) for outstanding people of the 20th century.Hebat-Allah M.Mourad received her B.Sc, M.Sc and Ph.D degrees in Electrical Communication Engineering from Cairo University, Egypt, in 1983, 1987 and 1994 respectively. Since 1983 she has been with the Electronics and Communications Department, Faculty of Engineering Cairo University and is currently associate professor there. Her research interests include mobile communications, satellite communications and optical fiber communications.Fatma A. Newagy received her B.Sc and M.Sc degrees in electrical communication engineering from Cairo University, Egypt in 1998 and 2002 respectively. Since 1999, she has been a research assistant with the Department of Electronics and Communications, Faculty of Engineering, Cairo University. She is pursuing her Ph.D. there. Her research interests include mobile communications and modulation techniques for spread spectrum and wireless communications.     

A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks

Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high‐profile organizations and can potentially have high economic and time costs. In this paper, several machine learning methods including ensemble models and autoencoder‐based deep learning classifiers are compared and tuned using Bayesian optimization. The autoencoder framework enables to extract new features by mapping the original input to a new space. The methods are trained and tested both for binary and multi‐class classification on Digiturk and Labris datasets, which were introduced recently for detecting various types of DDoS attacks. The best performing methods are found to be ensembles though deep learning classifiers achieved comparable level of accuracy.