TCVQ-SVM algorithm for narrowband spectrum sensing

Spectrum sensing is viewed as the basic and crucial technology for cognitive radio. To improve the accuracy of spectrum sensing in low signal to noise ratio (SNR), this paper presents an efficient TCVQ-SVM method based on machine learning for narrowband spectrum sensing. Firstly, trace of covariance matrix and variance of quadratic covariance matrix (TCVQ) is extracted as feature vectors and combined as training samples of spectrum sensing. Then, the classification model can be achieved by training samples based on support vector machine (SVM), which can avoid setting threshold and adjusting classification hyperplane by its self-learning ability. Lastly, the result of spectrum sensing can be obtained. By utilizing trace and variance as input features of SVM, the algorithm can make full use of the eigenvalue difference and structure characteristic of the received signal, and at the same time, achieve good performance in low SNR. Theoretical analysis reveals that the proposed method has low computational complexity. Simulation results and experiments on the hardware platform illustrate that the proposed algorithm is effective and robust.     

Deep learning-based energy-efficient relay precoder design in MIMO-CRNs

This paper investigates the problem of energy efficient relay precoder design in multiple-input multiple-output cognitive relay networks (MIMO-CRNs). This is a non-convex fractional programming problem, which is traditionally solved using computationally expensive optimization methods. In this paper, we propose a deep learning (DL) based approach to compute an approximate solution. Specifically, a deep neural network (DNN) is employed and trained using offline computed optimal solution. The proposed scheme consists of an offline data generation phase, an offline training phase, and an online deployment phase. The numerical results show that the proposed DNN provides comparable performance at significantly lower computational complexity as compared to the conventional optimization-based algorithm that makes the proposed approach suitable for real-time implementation.     

纺织品中4-氨基偶氮苯的测定能力验证分析

“P00012-2011-T07纺织品中禁用偶氮染料的测定(测试项目:4-氨基偶氮苯)”能力验证严格按照能力验证计划运作要求实施,并采用稳健统计法对测试结果进行统计,测试样品指定值为54.8 mg/kg,标准化四分位距(NIQR)为6.8941 mg/kg.共有12个省市、自治区的61家实验室参加本次能力验证,采用Z比分数对各实验室结果进行评价,结果满意率为86.9％.     

A Model for Studying Display Methods of Statistical Graphics

Abstract

A method of statistical graphics consists of two parts: a selection of statistical information to be displayed and a selection of a visual display method to encode the information. Some display methods lead to efficient, accurate visual decoding of encoded information, and others lead to inefficient, inaccurate decoding. It is only through rigorous studies of visual decoding that informed judgments can be made about how to choose display methods. A model has been developed to provide a framework for the study of visual decoding. The model consists of three parts: (1) a two-way classification of information on displays—quantitative-scale, quantitative-physical, categorical-scale, and categorical-physical; (2) a division of the visual processing of graphical displays into pattern perception and table look-up; (3) a specification of visual operations that are employed to carry out pattern perception and table look-up. Display methods are assessed by studying the visual operations to which they lead. Studies use the theory and experimental technique of various areas of vision research including psychophysics, cognitive psychology, and computational vision. This process is illustrated by studies of three display methods: visual reference grids for graphs with juxtaposed panels and common scales, encoding a categorical variable on a scatterplot by the type of plotting symbol, and choosing the aspect ratio of a factor-response graph.     

Using the Relative Entropy of Linguistic Complexity to Assess L2 Language Proficiency Development

This study applies relative entropy in naturalistic large-scale corpus to calculate the difference among L2 (second language) learners at different levels. We chose lemma, token, POS-trigram, conjunction to represent lexicon and grammar to detect the patterns of language proficiency development among different L2 groups using relative entropy. The results show that information distribution discrimination regarding lexical and grammatical differences continues to increase from L2 learners at a lower level to those at a higher level. This result is consistent with the assumption that in the course of second language acquisition, L2 learners develop towards a more complex and diverse use of language. Meanwhile, this study uses the statistics method of time series to process the data on L2 differences yielded by traditional frequency-based methods processing the same L2 corpus to compare with the results of relative entropy. However, the results from the traditional methods rarely show regularity. As compared to the algorithms in traditional approaches, relative entropy performs much better in detecting L2 proficiency development. In this sense, we have developed an effective and practical algorithm for stably detecting and predicting the developments in L2 learners’ language proficiency.     

Effect of a Combined Exercise and Cognitive Activity Intervention on Cognitive Function in Community-dwelling Older Adults: A Pilot Randomized Controlled Trial

Objective: The purpose of this study is to investigate the effect of an intervention combining exercise and cognitive activity on cognitive function in healthy older adults. Methods: This pilot randomized controlled trial recruited 33 eligible, healthy communitydwelling older adults (mean age, 77.1 years old; women, 51.5%), who were divided into intervention and waitlist control groups. The intervention group was engaged weekly in a group activity comprising exercise and discussions of homework, which included reading aloud, simple arithmetic, and simple activities, like spotting differences, for cognitive stimulation. They were also required to complete cognitive activity homework twice a week. The waitlist control group received no intervention. The main outcomes were cognitive function assessed using the Mini-Mental State Examination, delayed recall score on the Logical Memory IIA of the Wechsler Memory Scale Revised, Trail Making Test, and digit symbol substitution test. Results: According to the results, Mini-Mental State Examination scores were maintained in the intervention group but declined in the control group [Mean change in outcomes in control group (95% confidence interval): -1.68 (-2.89 to -0.48)]. Additional mean change in outcomes in intervention group were found [1.68 (0.02 to 3.35)]. Conclusions: Interventions combining exercise and cognitive activity can be helpful for preserving cognitive function in healthy older adults.     

Indoor cognitive radio operation within the broadcast TV protection contour

Although the broadcast television (TV) spectrum is currently open for unlicensed operation in the USA, a considerably large geographic area still remains excluded from the unlicensed operation due to potential interference to the licensed users. However, it might be possible to reuse primary spectrum within the protection contour if the frequency reuse occurs inside a building that shields radio signals and reduces interference to the primary system. Interference to outdoor licensed users from the indoor operations can be minimized if the unlicensed users adjust their transmit power according to their locations in the building. This paper presents an analysis and effectiveness evaluation of a novel cognitive radio (CR) system which enables CRs to access the licensed spectrum inside a building in the area within the protection contour. The system utilizes an indoor sensor network for (i) interference sensing, (ii) CR transmit power control, to limit the interference to the outdoor primary receiving antennas. Power control model of the indoor system has been developed to estimate safe transmit power for the indoor users. Two cases have been considered; single-user single-sensor (single indoor user and single sensor), and multi-user multi-sensor. Based on the power control model, a power control algorithm has been developed and its effectiveness is assessed through simulations. The algorithm is effective in realistic propagation scenarios, e.g. when internal partition walls and multipath fading are present. The outage probabilities in these propagation scenarios are found and the procedure of determining the transmit powers for CRs is presented.     

Power allocation for cognitive underlay networks with spectrum band selection

In this paper, we study the cooperative communication of a cognitive underlay network by utilizing the diversity of multiple spectrum bands. In particular, we assume that the transmission power of the secondary user (SU) is subject to different joint constraints, such as peak interference power of the multiple primary users (PUs), peak transmission power of the SU, outage tolerate interference, and outage probability threshold. Accordingly, two power allocation schemes are considered on the basis of the minimum interference channel from the SU to the PU and the channel state information of the primary user link. Furthermore, the SU can select one of the three transmission modes following the channel state conditions, namely as cellular, device-to-device, or switching mode, to transmit the signal to the secondary user receiver. Given this setting, two power allocation schemes over a spectrum band selection strategy are derived. In addition, closed-form expressions for the outage probability of three modes are also obtained to evaluate the performance of the secondary network. Most importantly, a closed-form expression for the peak interference power level of the PU, which is considered as one of the most important parameters to control the SU’s transmission power, is derived by investigating the relation of two considered power allocation schemes in the practise. Finally, numerical examples show that the outage performance of secondary network in the switching mode outperforms the one of the cellular and device-to-device (D2D) mode for all considered power allocation schemes.