System performance analysis of cooperative multihop relaying network applying approximation to dual‐hop relaying network

In this paper, the closed‐form expressions for outage probability, channel capacity, and average symbol error probability are derived for amplify‐and‐forward multihop relay network. Based on approximation of multihop relay by dual‐hop relay systems, the analytical expressions are obtained for the case when maximal ratio combining technique is employed at each relay while destination node uses selection combining technique. The impact of system and channel parameters on the system performances is investigated, and numerical results are graphically presented. The derived analytical expressions are verified by numerical simulation.     

Electric field–temperature phase diagram of sodium bismuth titanate-based relaxor ferroelectrics

The electric field–temperature phase diagrams of three bismuth sodium titanate-based relaxor ferroelectrics are reported, namely 0.94(Na_1/2Bi_1/2TiO₃)–0.06(BaTiO₃), 0.80(Na_1/2Bi_1/2TiO₃)–0.20(K_1/2Bi_1/2TiO₃) and 0.75(Na_1/2Bi_1/2TiO₃)–0.25(SrTiO₃). Relaxor behavior is demonstrated by temperature-dependent dielectric permittivity measurements in the unpoled and poled states, as well as by the field-induced phase transition into a ferroelectric phase from the relaxor phase. From temperature-dependent thermometry measurements, we identified the threshold electric field to induce the ferroelectric phase and obtained the released latent heat of the phase transition. We determined the nonergodic and ergodic relaxor phase temperature range based on the absence or presence of reversibility of the relaxor to ferroelectric transition. For all three compositions, the electric field–temperature phase diagram was constructed and a critical point was identified. The constructed electric field–temperature phase diagrams are useful to find optimum operational ranges of ferroelectrics and relaxors for electromechanical and electrocaloric applications.     

SN-38 loading capacity of hydrophobic polymer blend nanoparticles: formulation,optimization and efficacy evaluation

One of the most important problems in nanoencapsulation of extremely hydrophobic drugs is poor drug loading due to rapid drug crystallization outside the polymer core. The effort to use nanoprecipitation, as a simple one-step procedure with good reproducibility and FDA approved polymers like Poly(lactic-co-glycolic acid) (PLGA) and Polycaprolactone (PCL), will only potentiate this issue. Considering that drug loading is one of the key defining characteristics, in this study we attempted to examine whether the nanoparticle (NP) core composed of two hydrophobic polymers will provide increased drug loading for 7-Ethyl-10-hydroxy-camptothecin (SN-38), relative to NPs prepared using individual polymers. D-optimal design was applied to optimize PLGA/PCL ratio in the polymer blend and the mode of addition of the amphiphilic copolymer Lutrol^®F127 in order to maximize SN-38 loading and obtain NPs with acceptable size for passive tumor targeting. Drug/polymer and polymer/polymer interaction analysis pointed to high degree of compatibility and miscibility among both hydrophobic polymers, providing core configuration with higher drug loading capacity. Toxicity studies outlined the biocompatibility of the blank NPs. Increased in vitro efficacy of drug-loaded NPs compared to the free drug was confirmed by growth inhibition studies using SW-480 cell line. Additionally, the optimized NP formulation showed very promising blood circulation profile with elimination half-time of 7.4?h.     

Spiking Neural Networks: Background,Recent Development and the NeuCube Architecture

Neural Processing Letters - This paper reviews recent developments in the still-off-the-mainstream information and data processing area of spiking neural networks (SNN)—the third generation...     

Image coding algorithm based on Hadamard transform and simple vector quantization

Transform coding is commonly used in image processing algorithms to provide high compression ratios, often at the expense of processing time and simplicity of the system. We have recently proposed a pixel value prediction scheme in order to exploit adjacent pixel correlation, providing a low-complexity model for image coding. However, the proposed model was unable to reach high compression ratios retaining high quality of reconstructed image at the same time. In this paper we propose a new segmentation algorithm which further utilizes adjacent pixel correlation, provides higher compression ratios and it is based on application of Hadamard transform coding. Additional compression is provided by using vector quantization for a low number of quantization levels and by simplifying generalized Lloyd’s algorithm where the special attention is paid to determination of optimal partitions for vector quantization, making a fixed quantizer. The proposed method is quite simple and experimental results show that it ensures better or similar rate-distortion ratio for very low bit-rates, comparing to the other similar methods that are based on wavelet or curvelet transform coding and support or core vector machine application. Furthermore, the proposed method requires very low processing time since the proposed quantizers are fixed, much less than the required time for the aforementioned methods that we compare with as well as much less than the time required for fractal image coding. In the end, the appropriate discussion is provided comparing the results with a scheme based on linear prediction and dual-mode quantization.

     

Preference-based topology optimization for vehicle concept design with concurrent static and crash load cases

In the simulation-based design process of automotive structures, an increasing amount of multi-disciplinary requirements have to be considered. Methods of topology optimization can be used to devise structural concepts early in the design process to obtain the best possible structural layout as starting point for further development steps. Especially relevant for the vehicle design process is the concurrent consideration of static load requirements representing normal operating conditions and energy absorption requirements targeting passive safety in crash events. When the disciplines are considered separately, the heuristic Hybrid Cellular Automaton topology optimization is a suitable method. However, in practical applications, both disciplines are usually addressed sequentially. This complicates the overall process and may reduce the quality of the final optimization result, since optimization objectives may be conflicting. We propose a preference-based Scaled Energy Weighting approach to address the topology optimization of both disciplines concurrently. The main idea is to decouple the user preference from the scaling of the different magnitudes of energies. This enables a multi-objective optimization and ultimately the selection of the desired trade-off solution. We first validate the capability of the method to provide structures optimized for stiffness and energy absorption objectives on beam examples. Finally, the method is applied to optimize a concept structure of an industrial vehicle body, demonstrating its practical feasibility.     

SkaSim – Skalierbare HPC‐Software für molekulare Simulationen in der chemischen Industrie

This article outlines advances in molecular modeling and simulation using massively parallel high‐performance computers (HPC). In the SkaSim project, partners from the HPC community collaborated with users from science and industry. The aim was to optimize the prediction of thermodynamic property data in terms of efficiency, quality and reliability using HPC methods. In this context, various topics were dealt with: atomistic simulation of homogeneous gas bubble formation, surface tension of classical fluids and ionic liquids, multicriteria optimization of molecular models, the development of the molecular simulation codes ls1 mardyn and ms2, atomistic simulation of gas separation processes, molecular membrane structure generators, transport resistors and the evaluation of predictive property data models based on specific mixture types.     

An Example of Human-Centric Sensor Network: Be Responsible Platform

The paper addresses the Be Responsible platform, a representative example of human-centric sensing network which, relying on the Info-Communication and Internet of Things concepts, aims to improve the communication between citizens, on one side, and government authorities, on the other side, with the purpose of resolving various problems encountered in a modern society. A widespread network of human-centric smartphone devices and PCs has been used as a valuable source of data collected and processed in order to trigger adequate actions upon problem resolving. In this way, humans acting as sensor operators and data sources become a powerful factor in improving their society. The Be Responsible platform enables the people to report the irregularities in various aspects of their social life (grey economy, misuse of government vehicles, ecology, traffic), and hence to take active part in resolving them. It also promotes positive and responsible social and institutional behavior, which has to be nurtured in any society seeking progress. The number of submitted reports as well as the money collected from the fine revenues and subsequently invested in projects of social good, undoubtedly prove that what could not be achieved through years of traditional government-led policy approach, was achieved in months of citizen engagement.     

基于剪切波域改进Gamma校正的医学图像增强算法

为了解决医学图像在采集和传输过程中引入噪 声和干扰导致图像质量恶化从而严重影响医学诊断的问题,提出 一种基于剪切波(shearlet)域改进Gamma校正的图像增强方法。首先,通过剪切波变换,把 图像分解成高频 部分和低频部分;其次,用改进的Gamma校正处理剪切波分解后的低频部分以调整图像的整 体对比 度,采用改进的自适应阈值函数对高频部分进行去噪;最后,把剪切波反变换的重构图 像进行模糊对比 增强,以突出图像的细节信息。实验结果表明,本文算法的峰值信噪比(PSNR )、结构相似度(SSIM)和 绝对均值差(MAE)优于其他对比算法,尤其是PSNR的提升更加明显。这些 客观指标说明,本 文算法不仅能有效地抑制噪声,而且能明显改善增强对比度。从主观方面观察,本文算法与 其他算法相比,能获得更好的视觉效果。     

Management of bridges with shallow foundations exposed to local scour

Abstract

The Serbian road network includes a large portion of bridges with shallow foundations vulnerable to local scour as tragically demonstrated during the extreme flooding in May 2014. Currently, the bridge management procedures in Serbia and worldwide do not comprehensively account for a risk of bridge failure due to flooding and fail to provide sufficient information for the decision-making. Thus, a novel methodology for quantitative vulnerability assessment is suggested as a tool to identify the most vulnerable bridges in a network. Herein, the essential task is evaluation of the conditional probability of a bridge failure due to local scour in a flooding event of a certain magnitude. To apply this approach on a network level, there is a dire need to establish precise practice-ready guidelines on an optimal set of information to be used and/or collected in situ, which is discussed on an example of the Serbian bridge database. The vulnerability of a bridge to local scour may be used as a comprehensive indicator of a bridge performance in a flooding event. For a network level, the vulnerability maps with respect to flooding of different magnitudes will give road operators crucial information to apply adequate quality control plans to vulnerable bridges.