An Adaptive Channel Quality Metric for Ultra-Narrowband Systems

Proper channel selection is essential to exploit the benefits of multi-channel systems by distributing conflicting transmissions across non-interfering channels. Critical to channel selection is the channel quality metric. We propose a busy time ratio (BTR) metric that captures channel contention and user traffic load under a variety of network dynamics. We also propose a distributed collaborative sensing scheme to reduce sensing overhead and energy consumptions. The proposed algorithms can be implemented using conventional 802.11 hardware with single radio interface. The proposed metric can be integrated with routing and channel selection. Experimental results show that the proposed scheme significantly outperforms the existing channel selection methods.

The performance of MIMO systems can be improved or optimized if channel state information (CSI) is known at the transmitter. In such systems, the transmitter adapts to the channel based on some channel metric(s). The design and performance of the adaptive scheme depends on the time-varying nature of the metric(s). Some previous work in this area [P.J. Smith et al., May 2005] includes a derivation of level crossing rates (LCR) and average fade durations (AFD) for channel eigenvalues. In this paper, we extend this work to study the temporal behavior of three channel metrics. In particular, we derive the approximate LCR and AFD for the eigenvalue sum, eigenvalue range and simultaneous eigen mode outages. The analysis has been verified through simulations.

Multichannel communication has great potential in environments with unknown interference patterns. However, existing link quality metrics and models are generally established and verified under a single-channel scenario, which does not consider the impacts of radio interference and channel change. Therefore, it is hard to directly judge whether these metrics and models are still valid under a multichannel scenario. This paper empirically analyzes the applicability of popular link quality metrics and models in multiple channels with different interference levels. Results show that the link quality estimation (LQE) capability of traditional metrics will be affected by the interference level of the channel, which makes the conclusions obtained under a single-channel scenario no longer valid. Meanwhile, traditional LQE models are basically not adaptive to radio interference and channel change. They are only valid for channels with similar interference under which they are modeled. If these models are directly used under a multichannel scenario, the link quality will be overestimated inevitably. In other words, traditional LQE metrics and models cannot be directly used in the multichannel scenario. It is necessary to deeply analyze the statistical characteristics of popular link quality metrics in multiple typical channels and design channel and interference adaptive metrics and models to support effective multichannel communication.

Channel quality and utilization metric for interference estimation in Wireless Mesh Networks

The purpose of this article is to review clinical computed tomography (CT) lung screening program elements essential to safely and effectively manage the millions of Americans at high risk for lung cancer expected to enroll in lung cancer screening programs over the next 3 to 5 years. To optimize the potential net benefit of CT lung screening and facilitate medical audits benchmarked to national quality standards, radiologists should interpret these examinations using a validated structured reporting system such as Lung-RADS. Patient and physician educational outreach should be enacted to support an informed and shared decision-making process without creating barriers to screening access. Programs must integrate smoking cessation interventions to maximize the clinical efficacy and cost-effectiveness of screening. At an institutional level, budgets should account for the necessary expense of hiring and/or training qualified support staff and equipping them with information technology resources adequate to enroll and track patients accurately over decades of future screening evaluation. At a national level, planning should begin on ways to accommodate the upcoming increased demand for physician services in fields critical to the success of CT lung screening such as diagnostic radiology and thoracic surgery. Institutions with programs that follow these specifications will be well equipped to meet the significant oncoming demand for CT lung screening services and bestow clinical benefits on their patients equal to or beyond what was observed in the National Lung Screening Trial.

Visual quality assessment plays a crucial role in many vision-related signal processing applications. In the literature, more efforts have been spent on spatial visual quality measure. Although a large number of video quality metrics have been proposed, the methods to use temporal information for quality assessment are less diversified. In this paper, we propose a novel method to measure the temporal impairments. The proposed method can be incorporated into any image quality metric to extend it into a video quality metric. Moreover, it is easy to apply the proposed method in video coding system to incorporate with MSE for rate-distortion optimization.

New challenges have been brought out along with the emerging of 3D-related technologies, such as virtual reality, augmented reality (AR), and mixed reality. Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, and so on, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced-, and no-reference models.

Accurate objective quality metrics are of great potential benefit to the video industry, as they promise the means to evaluate the performance of acquisition, display, coding and communication systems. Many researchers have focused on developing digital video quality metrics which produce results that accurately emulate subjective responses. However, to be widely applicable a metric must also work over a wide range of quality, and be useful for in-service quality monitoring. We have developed novel spatial-temporal distortion metrics for video sequences. This metric is capable of capturing spatial distortions in video sequences, in addition to temporal artifacts. And it can quantify the spatial distortion and differentiate the type of distortion. Furthermore the metric correlate well with subjective quality measures because perception distortions of human were took account of. Results are presented that demonstrate our perceptual quality metric performs better than existing methods

Sleep quality in patients studied with laboratory-based polysomnography may differ from sleep quality in patients studied at home but remains clinically relevant and important to describe. We assessed objective sleep quality and explored factors associated with poor sleep in patients undergoing laboratory-based polysomnography. We reviewed diagnostic polysomnography studies from a 10-year period at a single sleep center. Total sleep time (TST) and sleep efficiency (SE) were assessed as markers of sleep quality. Poor sleep was defined as TST ≤ 4 hours or SE ≤ 50%. Multivariable analysis was performed to determine associations between objective sleep quality as an outcome and multiple candidate predictors including age, sex, race, body mass index, comorbidities, severity of obstructive sleep apnea, and central nervous system medications. Among 4957 patients (age 53 ± 15 years), average TST and median SE were 5.8 hours and 79%, respectively. There were 556 (11%) and 406 (8%) patients who had poor sleep based on TST and SE, respectively. In multivariable analysis, those who were older (per 10 years: 1.48 [1.34, 1.63]), male (1.38 [1.14,1.68]), and had severe obstructive sleep apnea (1.76 [1.28, 2.43]) were more likely to have short sleep. Antidepressant use was associated with lower odds of short sleep (0.77 [0.59,1.00]). Older age (per 10 years: 1.48 [1.34, 1.62]), male sex (1.34 [1.07,1.68]), and severe obstructive sleep apnea (2.16 [1.47, 3.21]) were associated with higher odds of poor SE. We describe TST and SE from a single sleep center cohort. Multiple demographic characteristics were associated with poor objective sleep in patients during laboratory-based polysomnography. Harrison EI, Roth RH, Lobo JM, et al. Sleep time and efficiency in patients undergoing laboratory-based polysomnography. J Clin Sleep Med. 2021;17(8):1591-1598.

Image quality evaluation is becoming essential in many image processing problems. This paper proposes a new image quality evaluation approach based on decision fusion method of canonical correlation analysis (CCA). By exploring several diverse visual models, we constructed a comprehensive quality metric which can deal with complicated image distortion problem with increasing accuracy and robustness. Validation by comparing the proposed metric against other image quality metrics (IQMs) demonstrates that its fidelity prediction performs better across wide distortion range and types.

Remote photoplethysmography (rPPG) is a recent technique for estimating heart rate by analyzing the pulsatility of skin hue using regular cameras. To determine the quality of the measurement, many existing methods are based on the signal-to-noise ratio (SNR) calculated in the frequency domain. However, the Fast Fourier Transform (FFT) operation is performed with a minimal complexity of O(n log n). Therefore, the use of this quality metric in an unsupervised rPPG framework in which this metric is estimated a large number of times will tend to greatly increase the complexity of the solution. In this paper, we propose a new probabilistic formulation of a cardiac signal quality index, with lower complexity, based on the Bayesian information criterion (BIC) that encapsulates the characteristic shape of the rPPG signal. The results of this study, obtained on a public database, have demonstrated that the proposed probabilistic metric outperforms the regular SNR metric with a lower computation complexity.

Introduction: Studies show that patients with IBD are at increased risk for pneumococcal disease relative to the general population. This may be linked to the underlying immune response in IBD and the risk is further increased in patients on immunomodulator therapy. The 2017 ACG guidelines for preventative care in IBD and other similar guidelines recommend pneumococcal vaccination in all adult IBD patients. However, data from the few studies that have analyzed pneumococcal vaccination trends in this population suggests that IBD patients are highly under-vaccinated including patients on immunosuppressant therapy. Methods: We conducted a chart review of patients age 18 and older seen by the gastroenterology group at our tertiary care academic center between 1/2010 and 9/2015 with an ICD-9 diagnosis of IBD. An abstraction form was used to document clinical history and health maintenance metrics which included any pneumococcal vaccination. Characteristics were compared between those with and without documented vaccine status using Chi-square or Wilcoxon Rank-Sum tests. Subgroup analysis was also conducted for patients on immunomodulator therapy. Results: A total of 184 patients had documented pneumococcus vaccination status with 29.3% (n=54) having received the vaccine. Crohn's disease was more common in the studied population (n=79) than ulcerative colitis (n=55). Notably, patients on immunomodulator therapy (n=81) were 2.7 times more likely to receive vaccination against pneumococcus than those not taking immunomodulators (40.7% versus 20.4%, odds ratio 2.7, 95% CI 1.4-5.2, p=0.003). Those with more than 1 month of steroid use were also more likely to be vaccinated (p=0.005). Age above 65 (recommended vaccination age for a healthy adult) did not have significant association with vaccination status and vaccination did not vary significantly by other demographic characteristics. Conclusion: Overall pneumococcal vaccination rates were higher than seen in other studies but still far below optimal targets. Our analysis showed patients on immunomodulator and biologic therapy are significantly more likely to have documented pneumococcal vaccination. However the rates are still suboptimal as this quality metric is met for less than half of patients. Overall a large number of patients were missing documentation of vaccination status in the medical record. The findings suggest addressing this preventable cause of mortality can be improved in the routine care and health maintenance of IBD patients.Table: Table. Characteristics of Patients in the Study (n=184) Compared by Pneumococcus Vaccination Status as Documented in Patient Chart

Abstract. The high resolution digital images from Ultracam-D Large Format Digital Camera (LFDC) was used for near automatic DTM generation. In the past, manual method for DTM generation was used which are time consuming and labour intensive. In this study LFDC in synergy with accurate position and orientation system and processes like image matching algorithms, distributed processing and filtering techniques for near automatic DTM generation. Traditionally the DTM accuracy is reported using check points collected from the field which are limited in number, time consuming and costly. This paper discusses the reliability of near automatic DTM generated from Ultracam-D for an operational project covering an area of nearly 600 Sq. Km. using 21,000 check points captured stereoscopically by experienced operators. The reliability of the DTM for the three study areas with different morphology is presented using large number of stereo check points and parameters related to statistical distribution of residuals such as skewness, kurtosis, standard deviation and linear error at 90% confidence interval. The residuals obtained for the three areas follow normal distribution in agreement with the majority of standards on positional accuracy. The quality metrics in terms of reliability were computed for the DTMs generated and the tables and graphs show the potential of Ultracam-D for the generation of semiautomatic DTM process for different terrain types.

A method for deriving an objective video quality metric that emulates the human video quality metric is described. The objective metric comprises a family of measurements that quantify spatial, temporal, luminance, and chrominance distortions, followed by a prediction algorithm. The intent is that the derived metric will work well over a wide range of digital and analog video transmission and storage technologies. After describing the need for these measures, a detailed description of the derivation process and some preliminary results are given. >

In genome-wide association studies, quality control (QC) of genotypes is important to avoid spurious results. It is also important to maintain long-term data integrity, particularly in settings with ongoing genotyping (e.g. estimation of genomic breeding values). Here we discuss SNPQc, a fully automated pipeline to perform QC analyses of Illumina SNP array data. It applies a wide range of common quality metrics with user-defined filtering thresholds to generate a comprehensive QC report and a filtered dataset, including a genomic relationship matrix, ready for further downstream analyses which make it amenable for integration in high-throughput environments. SNPQC also builds a database to store genotypic, phenotypic and quality metrics to ensure data integrity and the option of integrating more samples from subsequent runs. The program is generic across species and array designs, providing a convenient interface between the genotyping laboratory and downstream genome-wide association study or genomic prediction.