Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Regional variation in tolvaptan prescribing across England: national data and retrospective evaluation from an expert centre

Background Tolvaptan, a vasopressin V2 receptor antagonist, was approved in 2015 by the UK National Institute for Health and Care Excellence for use in patients with autosomal dominant polycystic kidney disease (ADPKD) and rapid disease progression. Simultaneous guidance was issued by the UK Kidney Association (UKKA) to facilitate national implementation. Methods Data on tolvaptan prescribing in England was obtained through the National Health Service (NHS) Digital, a national survey of all 77 adult kidney units, and the implementation of UKKA guidance was evaluated at an expert PKD centre. Results A regional variation of up to 4-fold for tolvaptan prescribing in England was found. Despite most kidney units following UKKA guidance, centre-based estimates of eligible or treated patient numbers were highly variable. Retrospective evaluation at an expert PKD centre revealed that in a cohort demonstrating rapid estimated glomerular filtration rate (eGFR) decline, 14% would not be eligible for tolvaptan by Mayo imaging classification and more than half (57%) would not be eligible by Predicting Renal Outcome in Polycystic Kidney Disease score. The 3-year discontinuation rate was higher than expected (56%), the majority (70%) due to aquaretic symptoms. In patients taking tolvaptan for at least 2 years, 81% showed a reduction in the rate of eGFR decline compared with baseline, with earlier disease associated with positive treatment response. Conclusion Real-world data have revealed a much higher regional variation in tolvaptan prescribing for ADPKD in England than expected. We propose further investigation into the factors responsible for this variation

Biallelic inheritance of hypomorphic PKD1 variants is highly prevalent in very early onset polycystic kidney disease

Purpose To investigate the prevalence of biallelic PKD1 and PKD2 variants underlying very early onset (VEO) polycystic kidney disease (PKD) in a large international pediatric cohort referred for clinical indications over a 10-year period (2010–2020). Methods All samples were tested by Sanger sequencing and multiplex ligation-dependent probe amplification (MLPA) of PKD1 and PKD2 genes and/or a next-generation sequencing panel of 15 additional cystic genes including PKHD1 and HNF1B. Two patients underwent exome or genome sequencing. Results Likely causative PKD1 or PKD2 variants were detected in 30 infants with PKD-VEO, 16 of whom presented in utero. Twenty-one of 30 (70%) had two variants with biallelic in trans inheritance confirmed in 16/21, 1 infant had biallelic PKD2 variants, and 2 infants had digenic PKD1/PKD2 variants. There was no known family history of ADPKD in 13 families (43%) and a de novo pathogenic variant was confirmed in 6 families (23%). Conclusion We report a high prevalence of hypomorphic PKD1 variants and likely biallelic disease in infants presenting with PKD-VEO with major implications for reproductive counseling. The diagnostic interpretation and reporting of these variants however remains challenging using current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) and Association of Clinical Genetic Science (ACGS) variant classification guidelines in PKD-VEO and other diseases affected by similar variants with incomplete penetrance

Barriers and facilitators to the implementation of guidelines in rare diseases: a systematic review

Background Rare diseases present a challenge to guideline implementation due to a low prevalence in the general population and the unfamiliarity of healthcare professionals. Existing literature in more common diseases references barriers and facilitators to guideline implementation. This systematic review aims to identify these barriers and facilitators in rare diseases from existing literature. Methods A multi-stage strategy included searching MEDLINE PubMed, EMBASE Ovid, Web of Science and Cochrane library from the earliest date available to April 2021, Orphanet journal hand-search, a pearl-growing strategy from a primary source and reference/citation search was performed. The Integrated Checklist of Determinants of Practice which comprises of twelve checklists and taxonomies, informed by 57 potential determinants was selected as a screening tool to identify determinants that warrant further in-depth investigation to inform design of future implementation strategies. Results Forty-four studies were included, most of which were conducted in the United States (54.5%). There were 168 barriers across 36 determinants (37 studies) and 52 facilitators across 22 determinants (22 studies). Fifteen diseases were included across eight WHO ICD-11 disease categories. Together individual health professional factors and guideline factors formed the majority of the reported determinants (59.5% of barriers and 53.8% of facilitators). Overall, the three most reported individual barriers were the awareness/familiarity with the recommendation, domain knowledge and feasibility. The three most reported individual facilitators were awareness/familiarity with the recommendation, agreement with the recommendation and ability to readily access the guidelines. Resource barriers to implementation included technology costs, ancillary staff costs and more cost-effective alternatives. There was a paucity of studies reporting influential people, patient advocacy groups or opinion leaders, or organisational factors influencing implementation. Conclusions Key barriers and facilitators to the implementation of clinical practice guidelines in the setting of rare diseases were at the individual health professional and guideline level. Influential people and organisational factors were relatively under-reported and warrant exploration, as does increasing the ability to access the guidelines as a potential intervention

Performance analysis of video encoders for wireless video sensor networks

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video encoding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video encoders based on emerging video encoding paradigms such as distributed video coding (DVC) and distributed compressive video sensing (DCVS) for WVSN. The main objective of this work is to provide an insight about the computational complexity and energy consumption of these video encoders, and the quality of reconstruction from the encoded frames. Based on the findings, this paper also provides some guidelines for the selection of appropriate video encoders for a given WVSN application

Distributed compressive video sensing: A review of the state-of-the-art architectures

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications. In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS). The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures

A review of the state-of-the-art distributed compressive video sensing architectures

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications. In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS). The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures

RSS ranging based Wi-Fi localization for unknown path loss exponent

Localization of mobile phones is important to location-based mobile services, but achieving good location estimation of mobile phones is difficult especially in environment whose path loss exponent is unknown. In this paper, we present a Wi-Fi localization solution specifically designed for dense WLANs with unknown path loss exponent. In order to leverage between the computational cost and localization accuracy, our solution establishes a neighbor selection scheme based on the Voronoi diagram to identify a subset of Access Points (APs) to participate in localization. It considers the identified subset of APs and a mobile phone to be located as a mass-spring system. Provided with information of known coordinates of APs, the solution estimates the path loss exponent of the physical environment, infers inter-distances between APs and the mobile phone from Wi-Fi signals received, and implements spring relaxation algorithm to approximate the geographical location of the mobile phone, where this location estimation is fed back to refine the estimated exponent iteratively. Extensive simulation results confirm that our solution is able to provide location estimation with an attractive average accuracy of below 2 m in a typical Wi-Fi setup

Applying spring-relaxation technique in cellular network localization

This paper presents a simple solution suitable for the mandatory localization function for E-911 services specified by FCC. Our solution introduces zero-length spring technique to compute the estimated location based on received signal strength (RSS). The introduced zero-length spring concept permits a less detailed path loss model to use without significant impact to the location estimation. We show the stability of our algorithm by illustrating the convergence of the estimated locations computed by the algorithm. We then demonstrate with simulation the accuracy of the estimation with various settings, and compare this accuracy with two candidate localization techniques