Time division access feasibility study modulation and synchronization considerations

Time division access system for satellite communications, and figure of merit for effects of bit and frequency synchronizatio

Corporate Law: What Is the Impact of New ALI Proposals on Shareholder Litigation

When the American Law Institute\u27s Corporate Governance Project meets this month, one of the most hotly debated agenda items is likely to be its new rules governing shareholder litigation, which are now up for final approval. The proposed change means that corporate boards will now have to prove in court that a decision to dismiss a shareholder claim alleging self-dealing was in the corporation\u27s best interest. In addition, the requirement for a formal demand on the board by shareholders will be uniform, rather than subject to excuse, as it is under Delaware law and in the majority of states. Drafters of the proposal say it will allow courts necessary scrutiny of self-dealing; critics charge it will tie up corporate boards in needless litigation. Debating the issue are the project\u27s reporter, John C. Coffee, a Columbia University law professor, and Michael P Dooley, a University of Virginia law professor. Coffee says the proposals strike a balance between oversight and efficient operation, while Dooley contends that the new rules will drive up the settlement value of shareholder suits

Enhanced retinal image registration accuracy using expectation maximisation and variable bin-sized mutual information

While retinal images (RI) assist in the diagnosis of various eye conditions and diseases such as glaucoma and diabetic retinopathy, their innate features including low contrast homogeneous and nonuniformly illuminated regions, present a particular challenge for retinal image registration (RIR). Recently, the hybrid similarity measure, Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) has been proposed for RIR. This paper investigates incorporating various fixed and adaptive bin size selection strategies to estimate the probability distribution in the mutual information (MI) stage of EMPCA-MI, and analyses their corresponding effect upon RIR performance. Experimental results using a clinical mono-modal RI dataset confirms that adaptive bin size selection consistently provides both lower RIR errors and superior robustness compared to the empirically determined fixed bin sizes

A new cross-layer dynamic spectrum access architecture for TV White Space cognitive radio applications

As evermore applications and services are developed for wireless devices, the dramatic growth in user data traffic has led to the legacy channels becoming congested with the corresponding imperative of requiring more spectra. This has motivated both regulatory bodies and commercial companies to investigate strategies to increase the efficiency of the existing spectrum. With the emergence of cognitive radio technology, and the transference of TV channels from analogue to digital platforms, a unique opportunity to exploit spectrum by mobile digital service providers has emerged, commonly referred to as TV White Space (TVWS). One of the challenges in utilising TVWS spectrum is reliable primary user (PU) detection which is essential as any unlicensed secondary user has no knowledge of the PU and thereby can generate interference. This paper addresses the issue of PU detection by introducing a new dynamic spectrum access algorithm that exploits the unique properties of how digital TV (DTV) frequencies are deployed. A fuzzy logic inference model based on an enhanced detection algorithm (EDA) is used to resolve the inherent uncertain nature of DTV signals. Simulation results confirm EDA significantly improves the detection probability of a TVWS channel compared to existing PU detection techniques, while providing consistently low false positive detections. The paper also analyses the impact of the hidden node problem on EDA by modelling representative buildings and proposes a novel solution

Improving distributed video coding side information by intelligently combining macro-blocks from multiple algorithms

The performance of distributed video coding (DVC) greatly relies on the quality of Side information (SI). This paper investigates a novel way of producing SI by intelligently combining macroblocks (MB) produced by two SI generation algorithms, namely higher-order piecewise temporal trajectory interpolation (HOPTTI) and adaptive overlapped block motion compensation (AOBMC). The two algorithms address the problem differently. HOPTTI attempts to improve the motion estimation using higher order trajectory interpolation while AOMBC addresses the blocking and overlapping problem caused by inaccurate block matching. By judiciously selecting when to incorporate AOBMC with HOPTTI, it would give a peak signal-to-noise ratio (PSNR) improvement in SI quality. Two switching mechanisms, which exploit the spatial-temporal correlation at the macro-block level, have been investigated and the RST-based intelligent mode switching (IMS) algorithm is found to produce enhanced SI quality. Experimental results show that the basic mode switching algorithm gives a PSNR improvement of up to 1.8dB in SI quality compared to using only HOPTTI. The more intelligent RST-based switching provides a further PSNR enhancement of up to 1.1dB for certain test sequences

Cognitive Radio and TV White Space (TVWS) Applications

As more user applications emerge for wireless devices, the corresponding amount of traffic is rapidly expanding, with the corollary that ever-greater spectrum capacity is required. Service providers are experiencing deployment blockages due to insufficient bandwidth being available to accommodate such devices. TV White Space (TVWS) represents an opportunity to supplement existing licensed spectrum by exploiting unlicensed resources. TVWS spectrum has materialised from the unused TV channels in the switchover from analogue to digital platforms. The main obstacles to TVWS adoption are reliable detection of primary users (PU) i.e., TV operators and consumers, allied with specifically, the hidden node problem. This chapter presents a new Generalised Enhanced Detection Algorithm (GEDA) that exploits the unique way Digital Terrestrial TV (DTT) channels are deployed in different geographical areas. GEDA effectively transforms an energy detector into a feature sensor to achieve significant improvements in detection probability of a DTT PU. Furthermore, by framing a novel margin strategy utilising a keep out contour, the hidden node issue is resolved, and a viable secondary user sensing solution formulated. Experimental results for a cognitive radio TVWS model have formalised both the bandwidth and throughput gains secured by TVWS users with this new paradigm

Disocclusion Hole-Filling in DIBR-Synthesized Images using Multi-Scale Template Matching

Transmitting texture and depth images of captured camera view(s) of a 3D scene enables a receiver to synthesize novel virtual viewpoint images via Depth-Image-Based Rendering (DIBR). However, a DIBR-synthesized image often contains disocclusion holes, which are spatial regions in the virtual view image that were occluded by foreground objects in the captured camera view(s). In this paper, we propose to complete these disocclusion holes by exploiting the self-similarity characteristic of natural images via nonlocal template-matching (TM). Specifically, we first define self-similarity as nonlocal recurrences of pixel patches within the same image across different scales--one characterization of self-similarity in a given image is the scale range in which these patch recurrences take place. Then, at encoder we segment an image into multiple depth layers using available per-pixel depth values, and characterize self-similarity in each layer with a scale range; scale ranges for all layers are transmitted as side information to the decoder. At decoder, disocclusion holes are completed via TM on a per-layer basis by searching for similar patches within the designated scale range. Experimental results show that our method improves the quality of rendered images over previous disocclusion hole-filling algorithms by up to 3.9dB in PSNR

Intra- and interobserver reproducibility of pelvic ultrasound for the detection and measurement of endometriotic lesions

STUDY QUESTION: What is the interobserver and intraobserver reproducibility of pelvic ultrasound for the detection of endometriotic lesions? SUMMARY ANSWER: Pelvic ultrasound is highly reproducible for the detection of pelvic endometriotic lesions. WHAT IS KNOWN ALREADY: Transvaginal ultrasound (TVS) has been widely adopted as the first-line assessment for the diagnosis and assessment of pelvic endometriosis. Severity of endometriosis as assessed by ultrasound has been shown to have good concordance with laparoscopy (kappa 0.79). The reproducibility of TVS for assessment of ovarian mobility and pouch of Douglas obliteration using the 'sliding sign' has already been described in the literature. However, there is no available data in the literature to demonstrate the intraobserver repeatability of measurements for endometriotic cysts and nodules. STUDY DESIGN SIZE DURATION: This was a prospective observational cross-sectional study conducted over a period of 12 months. We included 50 consecutive women who were all examined by two operators (A and B) during their clinic attendance. PARTICIPANTS/MATERIALS SETTING METHODS: The study was carried out in a specialist endometriosis centre. We included all consecutive women who had ultrasound scans performed independently by two experienced operators during the same visit to the clinic. The outcomes of interest were the inter- and intraobserver reproducibility for the detection of endometriotic lesions. We also assessed repeatability of the measurements of lesion size. MAIN RESULTS AND THE ROLE OF CHANCE: There was a good level of agreement between operator A and operator B in detecting the presence of pelvic endometriotic lesions (k = 0.72). There was a very good level of agreement between operators in identifying endometriotic cysts (k = 0.88) and a good level of agreement in identifying endometriotic nodules (k = 0.61). The inter- and intraobserver repeatability of measuring endometriotic cysts was excellent (intra-class correlation (ICC) ≥ 0.98). There was good interobserver measurement repeatability for bowel nodules (ICC 0.88), but the results for nodules in the posterior compartment were poor (ICC 0.41). The intraobserver repeatability for nodule size measurements was good for both operators (ICC ≥0.86). LIMITATIONS REASONS FOR CAUTION: Within this cohort, there was insufficient data to perform a separate analysis for nodule size in the anterior compartment. All examinations were performed within a specialised unit with a high prevalence of deep endometriosis. Our findings may not apply to operators without intensive ultrasound training in the diagnosis of pelvic endometriosis. WIDER IMPLICATIONS OF THE FINDINGS: These findings are important because ultrasound has been widely accepted as the first-line investigation for the diagnosis of pelvic endometriosis, which often determines the need for future investigations and treatment. The detection and measurement of bowel nodules is essential for anticipation of surgical risk and planning surgical excision. STUDY FUNDING/COMPETING INTERESTS: The authors have no conflict of interest. No funding was obtained for this work

Multimodal retinal image registration using a fast principal component analysis hybrid-based similarity measure

Multimodal retinal images (RI) are extensively used for analysing various eye diseases and conditions such as myopia and diabetic retinopathy. The incorporation of either two or more RI modalities provides complementary structure information in the presence of non-uniform illumination and low-contrast homogeneous regions. It also presents significant challenges for retinal image registration (RIR). This paper investigates how the Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) algorithm can effectively achieve multimodal RIR. This iterative hybrid-based similarity measure combines spatial features with mutual information to provide enhanced registration without recourse to either segmentation or feature extraction. Experimental results for clinical multimodal RI datasets comprising colour fundus and scanning laser ophthalmoscope images confirm EMPCA-MI is able to consistently afford superior numerical and qualitative registration performance compared with existing RIR techniques, such as the bifurcation structures method

Impact of Brown Midrib Trait on the Decomposition Rate of Sorghum-Sudangrass Residue in Pastures

Sorghum-sudangrass (Sorghum bicolor var. bicolor x bicolor var. sudanense) can provide high quality summer grazing. Some varieties possess the brown midrib (BMR) trait which results in reduced lignin resulting in higher digestibility and animal performance. If microbes in the rumen can digest BMR sorghum-sudangrass more completely, then soil macro/micro flora and fauna may do so as well. This could result in nutrients being returned to the soil faster from plants containing the BMR trait. The objective of this study was to determine the decomposition rate of BMR and non-BMR sorghumsudangrass. The experimental design was a random complete with four replications. Sorghum-sudangrass with and without the BMR trait was placed in litter decomposition bags as whole plants or divided into leaves and stems. A composite sample was taken when bags were loaded to determine initial dry matter. Loaded bags were then placed on the soil surface in a pasture and collected at 1, 2, 3, 4, 6, 8, 10, 12, 14, or 16 weeks after placement. Upon collection plant material was dried for 3-days at 55°C in a forced air oven. Dry weights at each collection date were subtracted from the initial dry weight to determine total DM loss. The BMR trait did not impact dry matter loss in the leaves. Stems possessing the BMR trait lost dry matter at a greater rate resulting in dry matter losses at 14 weeks of 78 and 68% and 59 and 47% for the BMR and non-BMR varieties in trials 1 and 2, respectively. Whole plants showed limited differences in dry matter loss at 14 weeks after placement