The incidence of multiple ovulations in Dutch warmblood mares

In the period 1994-1996 1030 oestruses of Dutch Warmblood mares were evaluated on the incidence of multiple ovulations diagnosed by rectal palpation. Ultrasonography was not used. All follicles > 25 mm were noted. The examination was repeated every 48 hours. The incidence of multiple follicle development was 7.3%. In a group of 50 ultrasonographically diagnosed twin-pregnant mares only 14 (28%) had been detected by rectal palpation as a multiple ovulation. This suggests an incidence of multiple ovulations in Dutch Warmblood mares of 7.3 x 1/28 x 100 = 26%. Restrictions of rectal palpation are discussed. Ultrasonography is essential for the diagnosis of multiple ovulations. The importance of a good twin-prevention programme is emphasized.     

A mean blood velocity statistic for the Doppler signal from anarrow ultrasound beam

An easily calculable statistic proportional to the instantaneous spatial mean blood velocity through a vessel cross section is derived from Doppler power spectral estimates for the case where the Doppler beam is assumed to be of negligible thickness compared to the vessel diameter. This is an alternative statistic to that derived where uniform insonation is assumed, an assumption thought to be poorer in many real cases. The main requirement is that the velocity profile is monotonic increasing from the vessel wall to the vessel center. Errors in each statistic are compared for a variety of true beam dimensions, using a variety of velocity profiles, and the new statistic is shown to incur less error for Gaussian beam response profiles with a standard deviation less than 0.4 of the vessel radius, or for rectangular response profiles with a width less than 0.65 of the vessel diameter. If an estimate can be made of the true beam dimensions and vessel diameter, a weighted sum of the two statistics can give a more accurate estimate of mean velocity. The case of a beam displaced from the center of the vessel is also considered, and errors are found to be less than 4% for a displacement of 20% of the vessel radius     

A Distributed Message-passing Approach for Clustering Cognitive Radio Networks

Forming collaborative wireless network clusters in dynamically changing environments is essential for cognitive radios to achieve such desired objectives as interference resilience and low communications overhead. In this paper, a novel approach to form efficient node clusters in an ad hoc cognitive radio network (CRN) is introduced based on the affinity propagation (AP) message-passing technique. With this approach, nodes exchange messages containing local network information with their direct neighbours until a high quality set of clusterheads and an efficient cluster structure emerges. The groupings are based on measures of similarity between the network nodes, which are selected based on application requirements. As an initial application, we show how the AP technique can be used to distributively determine cluster assignments and elect a small number of clusterheads that cover a CRN. Such an objective is commonly used to reduce communication overhead in key network functions such as resource management and routing table maintenance. To demonstrate the merits of the proposed approach, the clustering efficiency of the AP technique is evaluated on randomly generated open spectrum access scenarios. The simulation results demonstrate that the proposed approach provides a smaller number of clusters than a standard technique based on approximating the minimum dominating sets of the corresponding ad hoc network graphs.     

Iterative tree search detection for MIMO wireless systems

This paper presents a reduced-complexity soft-input soft-output detection scheme, called iterative tree search detection, for multiple-input multiple-output wireless communication systems employing turbo processing at the receiver. In this scheme, a reduced search space is selected with the aid of the M-algorithm, and QAM signal constellations with block partitionable labels are used in order to make the detection complexity per bit almost independent of the modulation order, as well as asymptotically linear in the number of transmit antennas. Results from computer simulations are presented which demonstrate the capability of the scheme to approach optimal performance at considerably reduced complexity.     

The Side Transformation Pattern: Making Transforms Modular and Re-usable

The basic principles of meta-modelling are now well established for individual models. Activities such as the MOF QVT [QVT-Merge Group, “Revised submission for MOF 2.0 Query/Views/Transformations RFP (ad/2002-04-10)”, OMG Document ad/04-04-01, URL: http://www.omg.org/docs/ad/04-04-01.pdf] are now extending these principles to transformation between models. However, meta-model incompatibilities between transformations reduce opportunities for effective re-use, hindering wide scale adoption. We introduce a pattern, the Side Transformation Pattern, that arises naturally as transformations are made re-usable, and present a series of examples that show how its use can bring clarity and robustness to complex transformation problems.     

Frame synchronization using distributed sequences

Frame synchronization is traditionally achieved by inserting a given sequence periodically into the data stream. Here, a new method of synchronization is introduced in which the synchronization sequence is not contiguous, but is interleaved with the data symbols. The properties of these distributed sequences are investigated, and requirements are specified for detectability of these sequences when inserted in random data. Methods for constructing and searching for good sequences are presented. It is demonstrated that this new method reduces the probability of false synchronization over traditional methods in the presence of additive white Gaussian noise     

Observation-Based Time-Varying MIMO Channel Model

This paper presents a method to model and simulate time-varying narrowband multiple-input–multiple-out (MIMO) channels based on observations from measured data. The data were obtained in a vehicular urban environment, with a fixed transmitter array and a mobile receiver array. The measured channel response matrices were decomposed to isolate the coupling from the transmitter eigenbasis to the received eigenbasis, as in the Weichselberger model. These complex coupling elements have been characterized and seen to comprise directional components that may be Ricean or Rayleigh fading. The Rayleigh fading directional components can be well modeled using the von Mises probability density function, which is parameterized for the time-varying model using the measured data. The model has been validated by comparing the mutual information and eigenstructure autocorrelation characteristics of its output with those of the measured data. The statistical nature of the model means that different realizations can be generated, each representative of the originating data.      

On Achievable Data Rates and Optimal Power Allocation in Fading Channels with Imperfect Channel State Information

Achievable rates of wireless communication systems with pilot-based channel estimation are investigated for the case of time-selective fading. Novel analytical expressions for the maximum achievable rates of such systems are derived in terms of the system signal-to-noise ratio (SNR), fading rate and estimation scheme deployed. The frame size is optimized jointly based on the SNR and the fading rate. The maximum rate achieving coding scheme is suggested and shown to be a modified version of the classical water-filling algorithm that accounts for imperfect channel state information (CSI) at the transmitter. The impact of the estimation scheme and the angular spread of the received signal on the quality of estimation and achievable rates is evaluated. A number of numerical simulations are provided to illustrate the dependence of the optimal block length and achievable rates on SNR, fading rate, estimation scheme and angular spread of the channel.

Efficient Adaptive SVD Algorithm for MIMO Applications

Many multiple-input multiple-output (MIMO) applications require the computation of some or all of the nonzero singular values and the corresponding left and right singular vectors of a time-varying channel response matrix. An adaptive algorithm is derived to achieve this goal, based on a first-order perturbation, which updates a full or partial singular value decomposition (SVD) using input and noisy output vectors. The updates can be computed recursively, resulting in a highly efficient algorithm that has lower complexity than the earlier least-mean-square (LMS)-based algorithm and achieves better performance at low signal-to-noise ratio (SNR). The performance is demonstrated using measured MIMO channel data obtained in an urban microcellular environment.     

Mean blood velocity measurement with a narrow ultrasound beam and an asymmetric velocity profile

Previous discussions of the measurement of spatial mean blood velocity using Doppler ultrasound with a narrow beam have required the velocity profile in the cross section to be symmetric about the vessel axis. A type of asymmetry is put forward which incurs no error in mean velocity measurement when the beam is directed through the point of maximum velocity. Assuming correct alignment of the beam, errors due to profile asymmetry are, therefore, related to the degree of departure of the asymmetry from this acceptable form.