A hybrid chaotic map for communication security applications

Recently, the synchronization between two matching chaotic systems to provide confident communication has gained a lot of interest. Continuously, there is a necessity to produce a novel dynamical system to be used in synchronization to implement a strong security system. In this paper, a hybrid chaotic system is suggested and verified for the potential use of secure communication through chaos synchronization. The Lyapunov exponent (LE) and zero‐one (0‐1) tests have been used to verify the performance of the suggested hybrid chaotic system, while National Institute of Standard and Technology (NIST) tests have been applied to verify the randomness properties. And the synchronization has been achieved between master and slave systems by using nonlinear control laws. The simulation outcomes demonstration that the hybrid system has chaotic performance and outstanding randomness characteristic. The statistical results gained for LE test was 0.8822, and for frequency test (FT) was 0.2028, while for the run test (RT) was 0.1924. Accordingly, the suggested hybrid system can be used to evolve functional synchronization algorithms and encryption for image, video, and voice secure communication applications.     

Low Complexity High-Performance Precoding Algorithms for mm-Wave MU-MIMO Communication System

Wireless Personal Communications - In this paper, linear precoding (LP) algorithm has been studied to improve the bit error rate (BER) performance of large scale multiple input multiple output...     

氮化硼纳米片吸附Cd(II)的动力学和热力学研究

本工作对Cd(II)在多孔六方氮化硼(p-BN)上的吸附行为和机理进行了系统而全面的研究, 考察了溶液pH、吸附剂用量、接触时间和温度等条件对于Cd(II)吸附的影响, 并采用不同手段表征了吸附前后p-BN的化学组成、形态和表面官能团的变化, 进而研究其吸附机理。研究结果显示, 在pH 7.0和313 K条件下, Cd(II)的最大吸附容量可达到184 mg·g ^-1, 其动力学数据与拟二级模型和颗粒内扩散模型吻合, 表明吸附主要受化学吸附控制, 限速步骤主要是分子扩散。Cd(II)在p-BN上的吸附是一个自发和吸热过程, 吸附等温线分别符合Freundlich和Langmuir模型, 说明Cd(II)通过多层和单层吸附而吸附在非均相表面上。XPS的光谱结果显示, p-BN吸附剂具有大量的B-N, B-O等结构用作键合位点, 有利于从废水中吸收Cd(II)。这些结果表明, p-BN有希望作为吸附材料用于清除水体中的Cd(II)。     

Context-Aware Collaborative Filtering Framework for Rating Prediction Based on Novel Similarity Estimation

Recommender systems are rapidly transforming the digital world into intelligent information hubs. The valuable context information associated with the users’ prior transactions has played a vital role in determining the user preferences for items or rating prediction. It has been a hot research topic in collaborative filtering-based recommender systems for the last two decades. This paper presents a novel Context Based Rating Prediction (CBRP) model with a unique similarity scoring estimation method. The proposed algorithm computes a context score for each candidate user to construct a similarity pool for the given subject user-item pair and intuitively choose the highly influential users to forecast the item ratings. The context scoring strategy has an inherent capability to incorporate multiple conditional factors to filter down the most relevant recommendations. Compared with traditional similarity estimation methods, CBRP makes it possible for the full use of neighboring collaborators’ choice on various conditions. We conduct experiments on three publicly available datasets to evaluate our proposed method with random user-item pairs and got considerable improvement in prediction accuracy over the standard evaluation measures. Also, we evaluate prediction accuracy for every user-item pair in the system and the results show that our proposed framework has outperformed existing methods.     

Solar energy harvesting and a water droplet cleaning of micropost arrays surfaces

Solar energy harvesting in dusty environments initiates many challenges for sustainable operation of photovoltaic panels. Environmental dust reduces photovoltaic device performance and requires regular cleaning of active surfaces. Self-cleaning of surfaces by water droplets offers advantages in terms of reduced cost and sustainable operation. The present study investigates dust removal from hydrophobic and optically transparent micropost arrays surfaces in relation to solar energy applications. The micropost arrays are replicated using polydimethylsiloxane (PDMS) casting on textured silicon wafers. The replicated micropost arrays result in hydrophobic surface with contact angle of about 147.6° ± 5° and the hysteresis of 16° ± 2°. In relation to self-cleaning, water droplet behavior on the inclined replicated micropost arrays is simulated and droplet movement is examined experimentally. The optical transmittance of micropost arrays is tested in outdoor dusty environments. It is found that droplet slides on the inclined micropost surface and expanding droplet size enhances the sliding velocity. Alkaline dust compounds dissolve in droplet while increasing pH from 4.35 to 7.94 and surface tension from 0.072 to 0.120 N/m. This alters droplet pinning and lowers the sliding velocity from 0.2 to 0.15 m/s. Optical transmittance of the samples was tested in outdoor dusty environments improve considerably by sliding water droplet cleaning on daily bases (transmittance reduces only 3% or less as reference to surface being kept indoor environments). Hence, introducing micropost arrays on photovoltaic panel protective cover surface can provide self-cleaning effect, via droplet rolling, while slightly reducing optical transmittance of cover glass (approximately 2.5%-3%) in outdoor environments.     

The needs of power spectral density in fatigue life prediction of heavy vehicle leaf spring

This study characterized the properties of random strain loading data for using power spectral density (PSD) in frequency domain of a heavy vehicle leaf sp     

Reducing seismic vibrations of typical steel buildings using new multi-level yielding pipe damper

Multi-level Pipe Damper (MPD) recently proposed by the authors is a passive control device to reduce the seismic vibration. In this research, seismic response of steel structures equipped with MPD is studied. To evaluate the effects of the proposed damper, typical 5, 10 and 15-story steel buildings are modeled and their seismic responses under seven earthquake excitations are investigated using dynamic nonlinear time-history analyses by SAP2000 program. Results show the effectiveness of MPD to altering the seismic response of the structures such that maximum displacement reduced by average of 54, 52, and 19% and maximum roof acceleration decreased by average of 16, 14, and 11% compared to those of the bare frames for the 5, 10 and 15-story buildings respectively. Moreover, using MPD decreases the structural and nonstructural damages noticeably by limiting the inter story drifts because of the secondary hardening branch of force-displacement by average of 53, 54, and 11% for the 5, 10 and 15-story buildings respectively proving the effectiveness of the proposed damper as a retrofitting technique for structures at high seismic risk areas.     

Structural damage prognosis of three-dimensional large structural systems

A novel procedure for the health assessment of large three-dimensional (3D) structures with several significant attractive features and improved implementation potential is proposed. Structures are represented by 3D finite elements and a substructure concept is used so that acceleration time histories can be measured only at small part(s) of the structure. Just by measuring relatively few noise-contaminated responses in the substructure, the health of the whole structure can be assessed by the system identification (SI) concept by tracking the stiffness parameter of all the elements using a significantly improved unscented Kalman filter (UKF) algorithm. Since measuring excitation time histories can be very problematic and expensive, the UKF algorithm is integrated with 3D iterative least-squares with unknown input algorithm. UKF fails to identify large structures due to convergence-related issues. The authors used short duration responses and multiple global iterations with weight factor and objective function instead of one long duration response generally used in UKF. For the preselected excitation, short duration eliminates multiple sources of excitation beyond the control of inspector. The weight factor helps accurately locate the defect spot. With informative examples, it is documented that the proposed method is superior to various other forms of Kalman filter-based algorithms.     

Effect of copper slag as a fine aggregate on the properties of cement mortars and concrete

An experimental investigation was conducted to study the effect of using copper slag as a fine aggregate on the properties of cement mortars and concrete. Various mortar and concrete mixtures were prepared with different proportions of copper slag ranging from 0% (for the control mixture) to 100% as fine aggregates replacement. Cement mortar mixtures were evaluated for compressive strength, whereas concrete mixtures were evaluated for workability, density, compressive strength, tensile strength, flexural strength and durability. The results obtained for cement mortars revealed that all mixtures with different copper slag proportions yielded comparable or higher compressive strength than that of the control mixture. Also, there was more than 70% improvement in the compressive strength of mortars with 50% copper slag substitution in comparison with the control mixture. The results obtained for concrete indicated that there is a slight increase in density of nearly 5% as copper slag content increases, whereas the workability increased significantly as copper slag percentage increased compared with the control mixture. A substitution of up to 40–50% copper slag as a sand replacement yielded comparable strength to that of the control mixture. However, addition of more copper slag resulted in strength reduction due to the increase in the free water content in the mix. Also, the results demonstrated that surface water absorption decreased as copper slag content increases up to 50% replacement. Beyond that, the absorption rate increased rapidly and the percentage volume of the permeable voids was comparable to the control mixture. Therefore, it is recommended that up to 40–50% (by weight of sand) of copper slag can be used as a replacement for fine aggregates in order to obtain a concrete with good strength and durability requirements.     

Modeling of some properties of the crushed tile concretes exposed to elevated temperatures

In this study, artificial neural network (ANN) and fuzzy logic (FL) models have been developed for predicting the compressive strength (f_c) and dynamic modulus of elasticity (E_d) of the crushed tile concretes (CTC) exposed to elevated temperatures. Some relationships are established between chosen inputs and outputs by developing and testing a multi-layered feed forward ANN and FL trained with the back-propagation algorithm. First of these relationships is established between the outputs as f_c of CTC after being exposed to elevated temperatures and the inputs as exposed temperature (T), crushed tile aggregate (CT) and crushed stone II (CSII) contents of concrete. The second one is the relationship between E_d of concretes and the same inputs. In this aim, concrete specimens are produced by CT replacing 16–31.5 mm coarse aggregate at the ratios of 0%, 10%, 25%, 50%, 75% and 100%. Concrete specimens are exposed to 20, 150, 300, 400, 600, 900 and 1200 °C high temperatures corresponding TS EN 1363-1 after an initial 28 day curing period. After heating, the specimens are slowly air-cooled to the room temperature and then E_d and f_c of concretes were determined. Experimental results are also predicted by constructing models in ANN and FL methods. In the models, the training and testing results have shown that ANN and FL methods have strong potential for predicting the f_c and E_d of crushed tile concretes exposed to elevated temperatures.