基于差分星座轨迹图的多任务802.11b/g信号识别方法

针对802.11b/g无线信号的调制方式识别和辐射源个体识别问题,提出了一种基于差分星座轨迹图的多任务卷积神经网络识别方法。将调制识别和辐射源个体识别看作两个相互关联的学习任务,通过共享参数的深度网络提取差分星座轨迹图的特征,并由结构不同的两个分支网络进行分类识别,同时对这两个任务进行联合优化训练并相互促进学习。实验中使用6个不同的路由器进行验证,结果表明相比于单任务模型的识别方法,多任务模型所用的训练时长和模型所占内存均比两个单任务模型之和少,同时对辐射源个体、调制方式的识别率分别平均提高了1.17%和3%。     

Blocking in Wavelength-Routed Optical Networks With Heterogeneous Traffic

In this paper, we present a new analytical model that can give an accurate estimation of the blocking probabilities in wavelength-routed optical networks with heterogeneous traffic. By heterogeneous, we mean that each session offered to the network has its own traffic intensity and burstiness. In such cases, the blocking probability of a session is determined by the busy-wavelength distributions of the links seen at the arrival points of its calls. Thus, we first present two single-link models to estimate the arrival-point busy-wavelength distribution of a link with heterogeneous traffic: the full-population (FP) model and the reduced-population (RP) model. Both models are based on the BPP/M/W/W model, where the first two moments of an arbitrary session are matched by those of a birth–death process whose arrival rate linearly varies with the average number of busy wavelengths occupied by its own calls. We show that different sessions have different arrival-point busy-wavelength distributions depending on the burstiness of their traffic, i.e., a bursty session observes the link more congested than a smooth session. Next, we provide two extensions of the single-link models, the FP-full-load link-correlation model and the RP-reduced-load link-correlation model, to estimate the blocking probabilities of optical networks with heterogeneous traffic and sparse wavelength conversion. Both models employ the existing link-correlation models to take into account the occupied-wavelength-index correlation between two adjacent links. By comparing the results from the models with simulation results, we demonstrate that both models well approximate the blocking probabilities of individual sessions, as well as the network-wide blocking probability, for a wide range of traffic intensity, burstiness, and heterogeneity.     

Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration

In this paper, we show how the concept of statistical deformation models (SDMs) can be used for the construction of average models of the anatomy and their variability. SDMs are built by performing a statistical analysis of the deformations required to map anatomical features in one subject into the corresponding features in another subject. The concept of SDMs is similar to statistical shape models (SSMs) which capture statistical information about shapes across a population, but offers several advantages over SSMs. First, SDMs can be constructed directly from images such as three-dimensional (3-D) magnetic resonance (MR) or computer tomography volumes without the need for segmentation which is usually a prerequisite for the construction of SSMs. Instead, a nonrigid registration algorithm based on free-form deformations and normalized mutual information is used to compute the deformations required to establish dense correspondences between the reference subject and the subjects in the population class under investigation. Second, SDMs allow the construction of an atlas of the average anatomy as well as its variability across a population of subjects. Finally, SDMs take the 3-D nature of the underlying anatomy into account by analysing dense 3-D deformation fields rather than only information about the surface shape of anatomical structures. We show results for the construction of anatomical models of the brain from the MR images of 25 different subjects. The correspondences obtained by the nonrigid registration are evaluated using anatomical landmark locations and show an average error of 1.40 mm at these anatomical landmark positions. We also demonstrate that SDMs can be constructed so as to minimize the bias toward the chosen reference subject.     

Dimensioning of the LTE access network

This paper proposes efficient analytical models to dimension the necessary transport bandwidths for the Long Term Evolution (LTE) access network satisfying the QoS targets required by different services. In this paper, we consider two major traffic types: elastic traffic and real time traffic. For each type of traffic, individual dimensioning models are proposed for both the S1 interface and the X2 interface. For elastic traffic the dimensioning models are based on the Processor Sharing models; while for real time traffic the dimensioning models are based on the fundamental queuing models. For validating these analytical dimensioning models, a developed LTE system simulation model is used. Extensive simulations are performed for various traffic and network scenarios. The analytical results derived from the proposed dimensioning models are compared with the simulation results. The presented results demonstrate that the proposed analytical models can appropriately estimate the required performances for different service classes and priorities. Hence they are suitable to be used for dimensioning of the LTE access network with different traffic and network conditions.     

Ensemble Characteristics of the Human Visual Evoked Response: Periodic and Random Stimulation

Most investigations of visual evoked potentials monitored at the human scalp have utilized the average of a series of responses recorded from a single subject in a specific population to define components of the visual evoked response (VER). While this technique provides a fairly consistent estimate of an individual's average VER, it is not uncommon to obtain quite dissimilar averages from different subjects under identical experimental conditions. This contrast in the VER estimates across a population has hindered the interpretation of the effects of stimulus parameters on the VER and frustrated the attempt to use this average for clinical diagnosis.     

IMPACT OF BUSY LINES AND MOBILITY ON CALL BLOCKING IN A PCS NETWORK

Several analytical models have been proposed to study the blocking probability for personal communications service networks or mobile phone networks. These models cannot accurately predict the blocking probability because they do not capture two important features. First, they do not capture the busy-line effect. Even if a cell has free channels, incoming and outgoing calls must be dropped when the destination portable is already in a conversation. Second, they do not capture the mobility of individual portables. In these models, mobility is addressed by net hand-off traffic to a cell, which results in traffic with a smaller variance to a cell compared with the true situation. We propose a new analytic model which addresses both the busy-line effect and individual portable mobility. Furthermore, our model can be used to derive the portable population distribution in a cell. The model is validated against the simulation experiments. We indicate that the previously proposed models approximate a special case of our model where the number of portables in a cell is 40 times larger than the number of channels.     

Measurements of Signal Components in Single Visualy Evoked Brain Potentials

A two step procedure is described for measuring the characteristics of visual evoked brain potentials. First, the recorded waveforms are processed by a filter designed to minimize the mean square error produced by the ongoing EEG. This filter is different for each subject and is based on certain statistical properties of the measured data. Second, the filtered potentials are searched automatically by a computer to determine the existence and location of the individual components in the responses. By aligning the corresponding components in different waveforms and averaging over the waveform segment in the immediate vicinity of the peak, a latency corrected average is obtained that provides a new representation of the response waveform.     

Uncertainty in the output of artificial neural networks

Analysis of the performance of artificial neural networks (ANNs) is usually based on aggregate results on a population of cases. In this paper, we analyze ANN output corresponding to the individual case. We show variability in the outputs of multiple ANNs that are trained and "optimized" from a common set of training cases. We predict this variability from a theoretical standpoint on the basis that multiple ANNs can be optimized to achieve similar overall performance on a population of cases, but produce different outputs for the same individual case because the ANNs use different weights. We use simulations to show that the average standard deviation in the ANN output can be two orders of magnitude higher than the standard deviation in the ANN overall performance measured by the Az value. We further show this variability using an example in mammography where the ANNs are used to classify clustered microcalcifications as malignant or benign based on image features extracted from mammograms. This variability in the ANN output is generally not recognized because a trained individual ANN becomes a deterministic model. Recognition of this variability and the deterministic view of the ANN present a fundamental contradiction. The implication of this variability to the classification task warrants additional study.     

Random Set Framework for Context-Based Classification With Hyperspectral Imagery

In remotely sensed hyperspectral imagery, many samples are collected on a given flight and many variable factors contribute to the distribution of samples. Various factors transform spectral responses causing them to appear differently in different contexts. We develop a method that infers context via spectra population distribution analysis. In this manner, feature space orientations of sets of spectral signatures are characterized using random set models. The models allow for the characterization of complex and irregular patterns in a feature space. The developed random set framework for context-based classification applies context-specific classifiers in an ensemblelike manner, and aggregates their decisions based on their contextual relevance to the spectra under test. Results indicate that the proposed method improves classification accuracy over similar classifiers, which make no use of contextual information, and performs well when compared to similar context-based approaches.     

Memory modeling for system synthesis

We present our methodology for developing models of on-chip SRAM memory organizations. The models were created to enable the quick evaluation of energy, area, and performance of different memory configurations considered during synthesis. The models are defined in terms of parameters, such as size and mode of operation, which are known at synthesis time. Our methodology does not require knowledge of the underlying memory circuitry and provides models with average percentage errors within 8%. We examine the importance of the different parameters in the models to reduce the time required to develop the models. We found that only ten different memories from a large span of possible memory sizes are needed to obtain reasonably accurate models, with average errors within 15%. In this paper, we present our modeling methodology, discuss the important aspects in developing the models, and examine the parameters necessary in creating accurate models quickly and easily     

Investigating the nonlinear dynamics of cellular motion in theinner ear using the short-time Fourier and continuous wavelet transforms

The short-time Fourier transform (STFT) and the continuous wavelet transform (CWT) are used to analyze the time course of cellular motion in the inner ear. The velocity responses of individual outer hair cells and Hensen's cells to sinusoidal and amplitude modulated (AM) acoustical signals applied at the ear canal display characteristics typical of nonlinear systems, including the generation of harmonic and half-harmonic components. The STFT proves to be valuable for following the time course of the frequency components generated using sinusoidal and ARM input signals. The CWT is also useful for analyzing these signals; however, it is generally not as effective as the STFT when octave-band-based CWT's are used. For the transient response, the spectrogram (which is the squared magnitude of the STFT) and the octave-band-based scalogram (which is the squared magnitude of the CWT) prove equally valuable, and the authors have used both to study the responses of these cells to step-onset tones of different frequencies. Such analyses reveal information about the preferred vibration frequencies of cells in the inner ear and are useful for deciding among alternative mathematical models of nonlinear cellular dynamics. A modified Duffing oscillator model yields results that bear some similarity to the data     

Dependence of the Occupational Exposure to Mobile Phone Base Stations on the Properties of the Antenna and the Human Body

This study assesses human exposure in the close vicinity of mobile phone base station antennas by finite-difference time-domain simulations. The peak spatial average specific absorption rate (SAR) and the whole-body average SAR are analyzed in three different anatomical models (55–101 kg) with respect to the basic restrictions for occupational exposure. The models are at distances between 0.5 and 4 m from various antenna types operating at frequencies ranging from 450  to 2140 MHz. The validity of the simulations is confirmed by an analysis of the impact of the mesh resolution on local and whole-body average SAR and by experimental validation of the numerical models. The results demonstrate that the whole-body absorption generally determines the maximum permissible antenna output power for collinear array antennas. Local exposure depends on various effects that fluctuate strongly among individuals. In particular for short antennas, the peak spatial average SAR can be more restrictive than the whole-body absorption because they may only expose a fraction of the body. Therefore, compliance must be demonstrated for both quantities.      

Induced electric currents in models of man and rodents from 60 Hzmagnetic fields

Induced electric currents in models of man, rat and mouse from 60 Hz magnetic fields are computed using the impedance method. The models all have realistic shapes, and in the case of rodents, a homogeneous average tissue conductivity is assumed. The model of man is analyzed for two cases, a homogeneous average tissue conductivity and a heterogeneous model, both consisting of 1.3 cm cubical tissue cells whose conductivities are representative of the tissue within the cube. The results for various models and species, as well as different orientations of the magnetic field, are compared. The data presented are useful as the first step in dosimetry for 60 Hz magnetic fields, and for interspecies scaling of biological interactions related to the tissue induced electric currents     

基于竞争指数的模拟退火排序选择算子

 提出基于竞争指数的模拟退火排序选择算子.竞争指数是对个体的适应度和编码差异度进行综合评估后产生的一种个体质量评价指标,代表了个体的绝对价值.依据竞争指数对群体及其后代个体进行排序,个体在队列中的位置代表了它的相对重要性.应用模拟退火过程产生个体在队列中的排序位置参数,作为个体相对价值的量化指标.将个体绝对价值和相对价值量化指标的加权平均数作为其生存的概率,这种选择方式可有效控制群体迭代过程的选择压力,保持群体结构的合理.通过对典型函数的优化实验表明,该算子在显著改善进化算法抗早熟能力的同时,可有效提高算法的搜索效率.     

Language,modality, and mobile media use experiences: Social responses to smartphone cues in a task-oriented context

With people’s growing use of virtual agents and voice assistants on smartphones, researchers have pointed out that mobile phones are not only acting as intermediaries that connect users from different places, but also communication terminals that present different combinations of social cues. This study applies the Computers are Social Actors paradigm in human-phone interaction and postulates that compared to non-anthropomorphic language and text cues, anthropomorphic language and vocal cues will have more effects on users’ social responses to smartphones. This study also explores the role of individual differences in users’ social responses to smartphones. Based on a lab experiment using a between-subjects factorial design, the study suggests that although anthropomorphic language and voice-based information did not have main effects on users’ social responses, people’s mobile media usage and intensive phone use interacted with these cues in their social responses to the smartphones. In addition, this study implies that it is the combination of social cues, individual differences, and communication contexts that contributes to people’s social reactions to the smartphones. The findings of the study can inform user interface design and precipitate further discussion about the ethical issues in human-phone interaction.     

The effect of anthropometric variations on acoustical flow estimation: proposing a novel approach for flow estimation without the need for individual calibration

Tracheal sound average power is directly related to the breathing flow rate and recently it has attracted considerable attention for acoustical flow estimation. However, the flow-sound relationship is highly variable among people and it also changes for the same person at different flow rates. Hence, a robust model capable of estimating flow from tracheal sounds at different flow rates in a large group of individuals does not exist. In this paper, a model is proposed to estimate respiratory flow from tracheal sounds. The proposed model eliminates the dependence of the previous methods on calibrating the model for every individual and at different flow rates. To validate the model, it was applied to the respiratory sound and flow data of 93 healthy individuals. We investigated the statistical correlation between the model parameters and anthropometric features of the subjects. The results have shown that gender, height, and smoking are the most significant factors that affect the model parameters. Hence, we grouped nonsmoker subjects into four groups based on their gender and height. The average of model parameters in each group was defined as the group-calibrated model parameters. These models were applied to estimate flow from data of subjects within the same group and in the other groups. The results show that flow estimation error based on the group-calibrated model is less than 10%. The low estimation errors confirm the possibility of defining a general flow estimation model for subjects with similar anthropometric features with no need for calibrating the model parameters for every individual. This technique simplifies the acoustical flow estimation in general applications including sleep studies and patients' screening in health care facilities.     

Analytical models for the series resistance of selective emitters in silicon solar cells including the effect of busbars

A theoretical analysis of the power loss and series resistance of the front side emitter in silicon solar cells is presented. Existing 1D models (infinitely long finger) and 2D models (including the effect of busbars) of emitter series resistance contribution are extended to the case of selective emitters. The general case of different current densities for both emitters in the selective emitter scheme is considered in these extensions. The resulting models depend on the individual sheet resistances and current densities in both emitters and the device's overall grid geometry. The models are corroborated by finite element simulation of the potential in the emitter. An excellent agreement is found between the analytical models, and the simulations for a wide range of sheet resistances typically encountered in silicon solar cells. Grid simulations using the 2D model are applied to solar cells with selective emitters, where the width of the low‐resistive emitter was varied. The simulations demonstrate that the 2D model can explain the absolute change in fill factor observed in these cells. Copyright © 2013 John Wiley & Sons, Ltd.     

The entropy of ordered sequences and order statistics

The entropy of a sequence of random variables under order restrictions is examined. A theorem that shows the amount of entropy reduction when the sequence is ordered is presented. Upper and lower bounds to the entropy reduction and conditions under which they are achieved are derived. Some interesting properties of the entropy of the individual order statistics are also presented. It is shown that the difference between the average entropy of the individual order statistics and the entropy of a member of the original independent identically distributed (IID) population is a constant, regardless of the original distribution. Finally, the entropies of the individual order statistics are found to be symmetric about the median when the probability density function (PDF) of the original IID sequence is symmetric about its mean     

Measurements of the RF Power Absorption in Spheroidal Human and Animal Phantoms Exposed to the Near Field of a Dipole Source

Experimental results for the average specific absorption rate (SAR) in scaled spheroidal phantoms of human and animal models exposed to near-field radiation are presented. Prolate spheroidal phantoms filled with saline solution simulating muscle tissue were used to measure average SAR values in different models. To control the exposure conditions, simple sources of known radiation characteristics, namely, short electric dipoles, were used. The accuracy of the experimental procedure was evaluated by making several average SAR measuremens at large distances (0.6 ?) from the dipole. The results obtained are found to be in good agreement with those available in the Radiofrequency Radiation Dosimetry Handbook [2]. Near-field SAR measurements for different models are presented as a function of the distance from the source. It is shown that even for the complex radiation fields in the near zone of the source, the average SAR below the resonance frequency can be explained in tenns of the magnitude and direction of the incident fields in the same way that the plane wave absorption characteristics are explained.