Discrete modeling of sand–tire mixture considering grain-scale deformability

Mixing sand or soil with small pieces of tire is common practice in civil engineering applications. Although the properties of the soil are changed, it is environmentally friendly and sometimes economical. Nevertheless, the mechanical behavior of such mixtures is still not fully understood and more numerical investigations are required. This paper presents a novel approach for the modeling of sand–tire mixtures based on the discrete element method. The sand grains are represented by rigid agglomerates whereas the tire grains are represented by deformable agglomerates. The approach considers both grain shape and deformability. The micromechanical parameters of the contact law are calibrated based on experimental results from the literature. The effects of tire content and confining pressure on the stress–strain response are investigated in detail by performing numerical triaxial compression tests. The main results indicate that both strength and stiffness of the samples decrease with increasing tire content. A tire contact of 40% is identified as the boundary between rubber-like and sand-like behavior.     

Classification of Electroencephalogram Signals Using LSTM and SVM Based on Fast Walsh-Hadamard Transform

Classification of electroencephalogram (EEG) signals for humans can be achieved via artificial intelligence (AI) techniques. Especially, the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions. From this perspective, an automated AI technique with a digital processing method can be used to improve these signals. This paper proposes two classifiers: long short-term memory (LSTM) and support vector machine (SVM) for the classification of seizure and non-seizure EEG signals. These classifiers are applied to a public dataset, namely the University of Bonn, which consists of 2 classes –seizure and non-seizure. In addition, a fast Walsh-Hadamard Transform (FWHT) technique is implemented to analyze the EEG signals within the recurrence space of the brain. Thus, Hadamard coefficients of the EEG signals are obtained via the FWHT. Moreover, the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings. Also, a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers. The LSTM classifier provides the best performance, with a testing accuracy of 99.00%. The training and testing loss rates for the LSTM are 0.0029 and 0.0602, respectively, while the weighted average precision, recall, and F1-score for the LSTM are 99.00%. The results of the SVM classifier in terms of accuracy, sensitivity, and specificity reached 91%, 93.52%, and 91.3%, respectively. The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s, respectively. The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals. Eventually, the proposed classifiers provide high classification accuracy compared to previously published classifiers.     

Efficient utilization of elliptic curve cryptosystem for hierarchical access control

The elliptic curve cryptosystem (ECC) has recently received significant attention by researchers due to its high performance, low computational cost, and small key size. In this paper, an efficient key management and derivation scheme based on ECC is proposed to solve dynamic access problems in a user hierarchy. Compared to previous ECC based works, the proposed method does not require constructing interpolate polynomials, therefore, the computational complexity of key generation and key derivation is significantly reduced. At the same time, time complexity of adding/deleting security classes, modifying their relationships, and changing of secret keys is decreased in the proposed method.     

Nonlinear ceramics for tunable microwave devices

The research on materials and systems for tunable microwave devices has gained attraction within the last years. The radio frequency characterization and the component design of tunable microwave components based on dielectric ceramics especially barium-strontium-titanate (BST) are presented in this second part, whereas the basic material properties are discussed in detail in the first part. After a short introduction to the processing technology used for the fabrication of tunable components based on a BST thick film, the relations between microwave properties and material properties as well as the microstructure are presented in detail. The design process for tunable microwave components based on BST thick films is described. Especially the considerations related to micro- and macrostructure and their connection are highlighted. The paper closes with two different application examples: a reconfigurable array antenna for satellite communication and varactors for high power applications.     

A memetic algorithm for minimizing the total weighted completion time on a single machine under step-deterioration

In this paper, we consider minimizing total weighted completion time criteria on a single machine. Jobs processing times are step function of its starting time and all jobs have a common due date. First, we present some new lemmas and dominance properties for this NP-hard problem, and then a memetic algorithm using these properties is developed. We compare the solutions of the memetic algorithm with optimal solutions obtained from complete enumeration. The results show that the average percentage error of the proposed algorithm from optimal solutions is about 2% and as the variance of processing time increase, the percentage errors decrease.     

Building extraction from high-resolution satellite images in urban areas: recent methods and strategies against significant challenges

Building extraction from high-resolution satellite images (HRSI) in urban areas is an intricate problem. Recent studies proposed different methods during 2005–2015. However, in HRSI, they have not investigated the effects of challenges altogether. This paper studies the effects of non-building features which are the main drawbacks in building extraction. To overcome each challenge, it reviews recent strategies between 2005 and 2015. The pros and cons of each strategy are discussed, and proper strategies are combined to generate hybrid methods. Lower cost and fewer strategies are efficient attributes to recognize the best hybrid methods. Hybrid methods can be useful for different case studies in the future.     

Structural Properties of Networked Control Systems With Bandwidth Limitations and Delays

The structural properties of networked control systems with both bandwidth limitations and delays are investigated. Sufficient conditions are given for controllability (stabilizability) and reconstructibility (detectability). Our results enhance previous works by capturing bandwidth limitations and delays simultaneously. The adopted modeling framework could be readily used in control and estimation methods, including optimal and predictive schemes. It also facilitates the use of scheduling optimization algorithms in conjunction with the control scheme presented.     

A theory of mode of action of azolylalkylquinolines as DNA binding agents using automated flexible ligand docking

Azolylalkylquinolines (AAQs) are a family of quinolines with varying degrees of cytotoxic activity (comparable or moderately superior to adriamycin in some cases) developed in the past decade in our group where their exact mode of action is still unclear. In this study the most probable DNA binding mode of AAQs was investigated employing a novel flexible ligand docking approach by using AutoDock 3.0. Forty-nine AAQs with known experimental inhibitory activity were docked onto d(CGCAAATTTGCG)(2), d(CGATCG)(2) and d(CGCG)(2) oligonucleotides retrieved from the Protein Data Bank (PDB IDs: 102D, 1D12 and 1D32, respectively) as the representatives of the three plausible models of interactions between chemotherapeutic agents and DNA (groove binding, groove binding plus intercalation and bisintercalation, respectively). Good correlation (r(2)=0.64) between calculated binding energies and experimental inhibitory activities was obtained using groove binding plus intercalation model for phenyl-azolylalkylquinoline (PAAQ) series. Our findings show that the most probable mode of action of PAAQs as DNA binding agents is via intercalation of quinolinic moiety between CG base pairs with linker chain and azole moiety binding to the minor groove.     

An Immune-based Genetic Algorithm with Reduced Search Space Coding for Multiprocessor Task Scheduling Problem

Multiprocessor task scheduling is an important problem in parallel applications and distributed systems. In this way, solving the multiprocessor task scheduling problem (MTSP) by heuristic, meta-heuristic, and hybrid algorithms have been proposed in literature. Although the problem has been addressed by many researchers, challenges to improve the convergence speed and the reliability of methods for solving the problem are still continued especially in the case that the communication cost is added to the problem frame work. In this paper, an Immune-based Genetic algorithm (IGA), a meta-heuristic approach, with a new coding scheme is proposed to solve MTSP. It is shown that the proposed coding reduces the search space of MTSP in many practical problems, which effectively influences the convergence speed of the optimization process. In addition to the reduced search space offered by the proposed coding that eventuate in exploring better solutions at a shorter time frame, it guarantees the validity of solutions by using any crossover and mutation operators. Furthermore, to overcome the regeneration phenomena in the proposed GA (generating similar chromosomes) which leads to premature convergence, an affinity based approach inspired from Artificial Immune system is employed which results in better exploration in the searching process. Experimental results showed that the proposed IGA surpasses related works in terms of found makespan (20% improvement in average) while it needs less iterations to find the solutions (90% improvement in average) when it is applied to standard test benches.     

Reduction of Noise from Disc Brake Systems Using Composite Friction Materials Containing Thermoplastic Elastomers (TPEs)

Attempts have been made for the first time to prepare a friction material with the characteristic of thermal sensitive modulus, by the inclusion of thermoplastic elastomers (TPE) as viscoelastic polymeric materials into the formulation in order to the increase the damping behavior of the cured friction material. Styrene–butadiene–styrene (SBS), styrene–ethylene–butylene–styrene (SEBS) and nitrile rubber/polyvinyl chloride (NBR/PVC) blend system were used as TPE materials. In order to evaluate the viscoelastic parameters such as loss factor (tan δ) and storage modulus (E′) for the friction material, dynamic mechanical analyzer (DMA) were used. Natural frequencies and mode shapes of friction material and brake disc were determined by modal analysis. However, NBR/PVC and SEBS were found to be much more effective in damping behavior. The results from this comparative study suggest that the damping characteristics of commercial friction materials can be strongly affected by the TPE ingredients. This investigation also confirmed that the specimens with high TPE content had low noise propensity.