Joint optimal fair cooperative spectrum sensing and transmission in cognitive radio

Since the sensing power consumption of cooperative spectrum sensing (CSS) will decrease the throughput of secondary users (SU) in cognitive radio (CR), a joint optimal model of fair CSS and transmission is proposed in this paper, which can compensate the sensing overhead of cooperative SUs. The model uses the periodic listen-before-transmission method, where each SU is assigned a portion of channel bandwidth, when the primary user (PU) is estimated to be free by the coordinator. Then, a joint optimization problem of local sensing time, number of cooperative SUs, transmission bandwidth and power is formulated, which can compensate the sensing overhead of cooperative SUs appropriately through choosing suitable compensating parameter. The proposed optimization problem can be solved by the Polyblock algorithm. Simulation results show that compared with the traditional model, the total system throughput of the fairness cooperation model decreases slightly, but the total throughput of the cooperative SUs improves obviously.     

Thermal measurements using ultrasonic acoustical pyrometry

Reflections from geometric discontinuities can be used with ultrasonic energy to predict the temperature of an interface where classical temperature measurement techniques are impractical because of physical access limitations or harsh environmental conditions. Additionally, these same ultrasonic measurements can be used with inversion methods commonly applied to ill-posed heat transfer problems to increase the accuracy of the measurement of surface temperature or heat flux at the surface of interest. Both methods for determining surface temperature are presented, along with a comparison of results both from a verification example and using data gathered in a field test of the methods. The results obtained with these two methods are shown to be in good agreement with an empirical relationship used in the design of large caliber guns.     

Dynamic analysis and regulation of the flexible pipe conveying fluid with a hard-magnetic soft segment

Applied Mathematics and Mechanics - The recently developed hard-magnetic soft (HMS) materials can play a significant role in the actuation and control of medical devices, soft robots, flexible...     

一种快速发现考试作弊信号的方法

简要介绍了基于压缩感知理论,对重构随机出现的考试作弊信号进行了仿真实验,理论实验表明,基于压缩感知理论的信号重构算法可以快速有效的发现随机出现的作弊信号,为后续的阻断工作奠定了基础。     

一种用于电气设备状态监测的新式FBG传感器北大核心CSCD

为了监测绕组变压器的静态应力场和发生短路等故障时的动态应力变化,设计了一种用于电气设备状态监测的新式FBG传感器。该传感器由聚醚醚酮材料封装的FBG构成,通过内部圆锥形空腔结构实现将轴向应力集中于FBG敏感位置。通过仿真对不同压力强度下传感器结构的应力场部分及形变趋势进行了计算与分析,论证了设计的合理性。实验分别对静态载荷和动态冲击进行测试,结果显示,在静态压载测试中,当100 N相似文献   

Biological applications of amide and amino acid containing synthetic macrocycles

ABSTRACT

Amino acid derived macrocycles with elaborate well-defined stereochemistry are a unique class of compounds that have been isolated from natural sources. Macrocycles like cyclosporine, octreotide, and valinomycin have been used in multiple applications, like drugs or ion sensors. Chemists have long been fascinated by the unique molecular recognition capabilities of these macrocycles and tried to design synthetic analogs with similar functions. This article is focused on reviewing current research on amide and amino acid containing macrocycles that have been developed in research laboratories for biological recognition, specifically for anion sensing, ion transport, carbohydrate sensing, and peptide sensing.     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

A Noise-Aware Real-Time Processing Approach for Electroencephalogram Signal Classification

Electroencephalogram (EEG) signal processing has emerged as a critical problem for biometric applications due to its real-time requirement. While compressive sensing is an efficient method for signal compression, its application in EEG signal processing is limited due to its noise unawareness during transmission and time-consuming reconstruction procedure. In this paper, we propose a noise-aware sparse Bayesian learning approach with block structure (NA-BSBL) to achieve higher efficiency on data compression, reconstruction and classification. By applying novel structure for parameter and introducing the Mahalanobis Distance, our approach achieves an almost 20% reconstruction performance lift and 10% accuracy lift under noise condition. For further application of reconstructed EEG signal, we extract both the spatial and frequency domain features for classification. Experimental results show that the proposed approach can achieve 94% classification accuracy with 16% speed up compared with the conventional approach.     

Hexanuclear 3d − 4f metal–organic cages assembled from a carboxylic acid‐functionalized tris‐triazamacrocycle for highly selective fluorescent sensing of picric acid

Two Ln^III ions are sandwiched by dinuclear Co^II building blocks derived from a tris‐triazamacrocyclic ligand bearing pendant carboxylic acid functionality, 1,3,5‐tris((4,7‐bis(2‐carboxyethyl)‐1,4,7‐triazacyclonon‐1‐yl)methyl)‐benzene (H₆L), giving rising to two nanoscale heterometallic metal–organic cages formulated as [Co₄Ln₂(LH_2.5)₂(H₂O)₄]·(ClO₄)₆·NO₃·nH₂O [Ln = Dy, n = 12 ( 1 ); Ln = Yb, n = 9 ( 2 )], whose internal cavity accommodates a guest NO₃^? anion. Their hexanuclear cage‐like architectures are maintained both in solution and solid states as confirmed by mass spectrum as well as X‐ray diffraction experiments. These two cages display ligand‐based fluorescence emissions and therefore both were chosen to be operated as fluorescent chemosensors for the detection of nitroaromatic compounds. Attractively, these metal–organic cages allow highly selective and sensitive detection of picric acid (PA) over other nitroaromatics in solution and suspension, and the fluorescence resonance energy transfer (FRET) between the cage probes and PA is mainly responsible for the remarkable detection efficiency.     

A novel multi-focus image fusion method based on distributed compressed sensing

Multi-focus image fusion aims to produce an all-in-focus image by merging multiple partially focused images of the same scene. The main work is identifying the focused region and then composing all the focused regions. In this paper, a novel efficient multi-focus image fusion method based on distributed compressed sensing (DCS) is proposed. Firstly, the low-frequency and high-frequency images are obtained by comparing the variance of the source images, which are further utilized to get the low-frequency and high-frequency dictionaries. Secondly, DCS using joint sparsity model-1 (JSM-1) is applied to reconstruct the precise high-frequency images. Thirdly, the decision map is obtained based on all the high-frequency images and then improved by the morphological processing. Finally, the focused pixels are chosen from the source images through the decision map. Experimental results indicate that the proposed DCS-based method can be competitive with or even outperform some state-of-the-art methods in terms of both visual and quantitative metric evaluations.