A novel consistent quality driven for JEM based distributed video coding

© 2019 by the authors. Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) andWyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality

Real-Time Network Slicing with Uncertain Demand: A Deep Learning Approach

© 2019 IEEE. Practical and efficient network slicing often faces real-time dynamics of network resources and uncertain customer demands. This work provides an optimal and fast resource slicing solution under such dynamics by leveraging the latest advances in deep learning. Specifically, we first introduce a novel system model which allows the network provider to effectively allocate its combinatorial resources, i.e., spectrum, computing, and storage, to various classes of users. To allocate resources to users while taking into account the dynamic demands of users and resources constraints of the network provider, we employ a semi-Markov decision process framework. To obtain the optimal resource allocation policy for the network provider without requiring environment parameters, e.g., uncertain service time and resource demands, a Q-learning algorithm is adopted. Although this algorithm can maximize the revenue of the network provider, its convergence to the optimal policy is particularly slow, especially for problems with large state/action spaces. To overcome this challenge, we propose a novel approach using an advanced deep Q-learning technique, called deep dueling that can achieve the optimal policy at few thousand times faster than that of the conventional Q-learning algorithm. Simulation results show that our proposed framework can improve the long-term average return of the network provider up to 40% compared with other current approaches

Genetic diversity on the tropical rare wood species of Dalbergia in Vietnam revealed by inter-simple sequence repeat (ISSR) markers

Genetic diversities of three rare hardwood species of Dalbergia (D. assamica, D. nigrescens and D. tonkinensis) were evaluated for conservation based on inter-simple sequence repeat (ISSR) markers. A total of 47 ISSR primers were used for the analysis, but only 31 ISSR primers were successfully amplified for 25 samples from each species. There were 166 fragments across the 75 samples produced, in which 153 were polymorphic with an average of 4.94 polymorphic fragments per primer. The number of amplified fragments ranged from 1 (ISSR13, ISSR54 and ISSR59) to 11 (ISSR14) and their size varied from 200 to 1700 bp. The similarity coefficient ranged from 67.0 to 98.9% in D. assamica; from 71.2 to 98.5% in D. nigrescens and from 68.5 to 95.2% in D. tonkinensis. The estimated value of molecular diversity parameters within species such as the effective number of alleles, Shannon's information index, intralocus gene diversity and Nei’s gene diversity were low among the individuals of the different Dalbergia species (1.227, 0.195, 0.662 and 0.146, respectively in D. assamica; 1.135, 0.111, 0.425 and 0.109, respectively in D. nigrescens; 1.198, 0.166, 0.526 and 0.123, respectively in D. tonkinensis). The analysis of molecular variance (AMOVA) of ISSR data indicated that the greater proportion of total genetic variation existed among species rather than within species. The correlation between genetic and geographic distance was also found in the three Dalbergia species.Key words: Dalbergia, endemic species, genetic similarity, ISSR markers

Elemental and mineralogical composition of metal-bearing neutralisation sludges, and zinc speciation – A review

Zinc (Zn) in sludges from neutralisation of acidic emissions is a potential environmental pollutant and an element of interest for recovery. Findings regarding the elemental and mineralogical composition of such wastes were aggregated from the literature and examined together for a better understanding of management options, with a focus on Zn. Zn concentrations ranged from 0.006-22% in 46 acid mine drainage sludges, 0.009%-43% in 72 metal-finishing sludges, 0.024%-11.5% in 32 pyrometallurgical sludges, and 1.71-55.7% in 14 Zn production sludges. The main mineralogical characterization technique was X-ray diffraction, which found the dominant minerals to be calcite, gypsum, quartz, and iron oxides, but could not identify considerable proportions of amorphous phases. More than 60 mineral phases were observed. Crystalline Zn compounds identified included oxides, hydroxides, sulfates, sulfides, and metallic Zn; spinel, olivine and carbonate dominated in pyrometallurgical sludges. Zn may also be present in crystalline phases of low concentration, solid solution, and/or amorphous phases, which could be identified and characterised in more detail using other techniques. Overall, it is concluded that Zn occurs in high concentrations and includes phases that have high potential environmental mobility. Zn recovery seems feasible and would also enable harmless disposal of the residual

Why should i comply? Sellers' accounts for (non-)compliance with legal age limits for alcohol sales

Background\ud Availability is an important predictor of early and excessive alcohol consumption by adolescents. Many countries have implemented age limits to prevent underage purchases of alcohol. However, shop-floor compliance with these age limits appears to be problematic. This study addresses the issue of non-compliance with age limits. Which measures do vendors take to avoid underage alcohol sales, and what do they report as important reasons to comply or not with age limits for alcohol sales? \ud \ud Methods\ud Open-ended telephone interviews were conducted with store managers selling alcohol (N = 106). Prior to the interviews, all outlets were visited by an underage mystery shopper in order to measure compliance with the legal age limits on alcohol sales. The interview results are compared against actual compliance rates. \ud \ud Results\ud Several measures have been taken to prevent underage sales, but the compliance level is low. Furthermore, open coding resulted in 19 themes, representing both valid and invalid arguments, that vendors mentioned as relevant to their decisions of whether to comply with the law. Compliance with age limits is dependent on the knowledge of the rules and the ability and motivation to follow the rules. The ability aspect in particular seems to be problematic, but in many cases, the motivation to actively comply with the age limits is lacking. \ud \ud Conclusions\ud To enhance compliance, it is important to raise the awareness of the importance of age limits and to connect possible violations of the regulations to negative consequences\u

Age and sex influence marmot antipredator behavior during periods of heightened risk

Animals adjust their antipredator behavior according to environmental variation in risk, and to account for their ability to respond to threats. Intrinsic factors that influence an animal’s ability to respond to predators (e.g., age, body condition) should explain variation in antipredator behavior. For example, a juvenile might allocate more time to vigilance than an adult because mortality as a result of predation is often high for this age class; however, the relationship between age/vulnerability and antipredator behavior is not always clear or as predicted. We explored the influence of intrinsic factors on yellow-bellied marmot (Marmota flaviventris) antipredator behavior using data pooled from 4 years of experiments. We hypothesized that inherently vulnerable animals (e.g., young, males, and individuals in poor condition) would exhibit more antipredator behavior prior to and immediately following conspecific alarm calls. As expected, males and yearlings suppressed foraging more than females and adults following alarm call playbacks. In contrast to predictions, animals in better condition respond more than animals in below average condition. Interestingly, these intrinsic properties did not influence baseline time budgets; animals of all ages, sexes, and condition levels devoted comparable amounts of time to foraging prior to alarm calls. Our results support the hypothesis that inherent differences in vulnerability influence antipredator behavior; furthermore, it appears that a crucial, but poorly acknowledged, interaction exists between risk and state-dependence. Elevated risk may be required to reveal the workings of state-dependent behavior, and studies of antipredator behavior in a single context may draw incomplete conclusions about age- or sex-specific strategies

The transition between stochastic and deterministic behavior in an excitable gene circuit

We explore the connection between a stochastic simulation model and an ordinary differential equations (ODEs) model of the dynamics of an excitable gene circuit that exhibits noise-induced oscillations. Near a bifurcation point in the ODE model, the stochastic simulation model yields behavior dramatically different from that predicted by the ODE model. We analyze how that behavior depends on the gene copy number and find very slow convergence to the large number limit near the bifurcation point. The implications for understanding the dynamics of gene circuits and other birth-death dynamical systems with small numbers of constituents are discussed.Comment: PLoS ONE: Research Article, published 11 Apr 201

Colored extrinsic fluctuations and stochastic gene expression

Stochasticity is both exploited and controlled by cells. Although the intrinsic stochasticity inherent in biochemistry is relatively well understood, cellular variation, or ‘noise', is predominantly generated by interactions of the system of interest with other stochastic systems in the cell or its environment. Such extrinsic fluctuations are nonspecific, affecting many system components, and have a substantial lifetime, comparable to the cell cycle (they are ‘colored'). Here, we extend the standard stochastic simulation algorithm to include extrinsic fluctuations. We show that these fluctuations affect mean protein numbers and intrinsic noise, can speed up typical network response times, and can explain trends in high-throughput measurements of variation. If extrinsic fluctuations in two components of the network are correlated, they may combine constructively (amplifying each other) or destructively (attenuating each other). Consequently, we predict that incoherent feedforward loops attenuate stochasticity, while coherent feedforwards amplify it. Our results demonstrate that both the timescales of extrinsic fluctuations and their nonspecificity substantially affect the function and performance of biochemical networks