Deep Reinforcement Learning with Importance Weighted A3C for QoE enhancement in Video Delivery Services

Adaptive bitrate (ABR) algorithms are used to adapt the video bitrate based on the network conditions to improve the overall video quality of experience (QoE). Recently, reinforcement learning (RL) and asynchronous advantage actor-critic (A3C) methods have been used to generate adaptive bit rate algorithms and they have been shown to improve the overall QoE as compared to fixed rule ABR algorithms. However, a common issue in the A3C methods is the lag between behaviour policy and target policy. As a result, the behaviour and the target policies are no longer synchronized which results in suboptimal updates. In this work, we present ALISA: An Actor-Learner Architecture with Importance Sampling for efficient learning in ABR algorithms. ALISA incorporates importance sampling weights to give more weightage to relevant experience to address the lag issues with the existing A3C methods. We present the design and implementation of ALISA, and compare its performance to state-of-the-art video rate adaptation algorithms including vanilla A3C implemented in the Pensieve framework and other fixed-rule schedulers like BB, BOLA, and RB. Our results show that ALISA improves average QoE by up to 25%-48% higher average QoE than Pensieve, and even more when compared to fixed-rule schedulers.Comment: Number of pages: 10, Number of figures: 9, Conference name: 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM

Data-Centric Energy Efficient Adaptive Sampling Techniques for Wireless Pollution Sensor Networks

PhDAir pollution is one of the gravest problems being faced by modern world, and urban traffic emissions are the single major source of air pollution. This work is founded on collaboration with environmental scientists who need fine grained data to enable better understanding of pollutant distribution in urban street canyons. “Wireless sensor networks” can be used to deploy a significant number of sensors within a space as small as a single street canyon and capture simultaneous readings both in the time and space domain. Sensor energy management becomes the most critical constraints of such a solution, because of the energy hungry gas sensors. Hence, the main research objective addressed in this thesis is to propose novel temporal and spatial adaptive sampling techniques for wireless pollution sensor nodes that take into account the pollution data characteristics, and enable the sensor nodes to sample, only when, an important event happens to collect accurate statistics in as efficient a manner as possible. The major contributions of this thesis can be summarised as: 1) Better understanding of underlying pollution data characteristics (based on real datasets collected during pollution trials in Cyprus and India) using techniques from time series analysis and more advanced methods from multi-fractal analysis and nonlinear dynamical systems. 2)Proposal of novel adaptive temporal sampling algorithm called Exponential Double Smoothing based Adaptive Sampling (EDSAS) that exploits the presence of slowly decaying autocorrelations and local linear trends. The algorithm uses a time series prediction method based upon exponential double smoothing for irregularly sampled data. This algorithm has been compared against a random walk based stochastic scheduler called e-Sense and found to give better sampling performance. EDSAS has been extended to the spatial domain by incorporating distributed hierarchical agglomerative clustering mechanism. 3)Proposal of a novel spatial sampling algorithm called Nearest Neighbour based Adaptive Spatial Sampling (NNASS) that exploits the non-linear dynamics existing in pollution data to compute predictability measures to adapt the sampling intervals for the sensor nodes. NNASS has been compared against another spatial sampling algorithm called ASAP and found to give comparable or better sampling performance

Histopathological Spectrum of various gastroduodenal lesions in North India and prevalence of Helicobacter pylori infection in these lesions: a prospective study

Background: Gastroduodenal diseases are perhaps the commonest diseases in adult population worldwide. Helicobacter pylori (H. pylori) represent one of the most common gastroduodenal infections and have been established as the etiologic factor in the development of various gastroduodenal diseases. Spectrum of H. pylori associated gastroduodenal diseases have not been systematically investigated in North India. So this study was carried out to determine the spectrum of gastroduodenal lesions on upper Gastro-Intestinal (GI) endoscopic biopsies and to determine the prevalence of H. pylori in gastric mucosa in these lesions.Methods: Gastroduodenal mucosal biopsies of 100 patients from November 2012 to October 2013 in a tertiary care centre in north India were evaluated by routine histopathological methods and the presence of H. pylori in gastric mucosa in these lesions was determined.  Results: An age range of 17 years to 80 years was observed with maximum cases in the 4th decade and a male to female ratio of 1.86:1. The most frequently observed lesions were chronic gastritis followed by duodenitis, duodenal ulcer and gastric carcinoma. 5% cases showed unremarkable mucosa. H. pylori positivity was seen in 47% cases. 80% cases of duodenal ulcer, 68.75% cases of duodenitis, 50.56% cases of chronic gastritis, 50% cases of gastric ulcer & 40% cases of gastric carcinoma were positive for H. pylori infection.Conclusion: Endoscopic gastroduodenal biopsies help to detect benign and malignant gastroduodenal diseases and to rule out H. pylori infection. Chronic gastritis was the most common gastroduodenal lesion followed by duodenitis, duodenal ulcer and gastric carcinoma. Duodenal ulcer, duodenitis, chronic gastritis and gastric ulcer showed strong positivity for H. pylori highlighting the role of this microorganism in the pathogenesis of these diseases.

Game Theory-Based Authentication Framework to Secure Internet of Vehicles with Blockchain

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV's openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities' areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework's credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the suggested framework achieves greater security and functionality characteristics and provides lower transaction and computation overhead than many of the available solutions so far. However, these solutions never considered the prime concerns of physical cloning and side-channel attacks. However, the framework in this paper is capable of handling them along with all the other security attacks the previous work can handle. Finally, the suggested framework has been subjected to a blockchain implementation to demonstrate its efficacy with duel gaming to achieve authentication in addition to its capability of using lower burdened blockchain at the physical layer, which current blockchain-based authentication models for IoVs do not support

"The fruits of independence": Satyajit Ray, Indian nationhood and the spectre of empire

Challenging the longstanding consensus that Satyajit Ray's work is largely free of ideological concerns and notable only for its humanistic richness, this article shows with reference to representations of British colonialism and Indian nationhood that Ray's films and stories are marked deeply and consistently by a distinctively Bengali variety of liberalism. Drawn from an ongoing biographical project, it commences with an overview of the nationalist milieu in which Ray grew up and emphasizes the preoccupation with colonialism and nationalism that marked his earliest unfilmed scripts. It then shows with case studies of Kanchanjangha (1962), Charulata (1964), First Class Kamra (First-Class Compartment, 1981), Pratidwandi (The Adversary, 1970), Shatranj ke Khilari (The Chess Players, 1977), Agantuk (The Stranger, 1991) and Robertsoner Ruby (Robertson's Ruby, 1992) how Ray's mature work continued to combine a strongly anti-colonial viewpoint with a shifting perspective on Indian nationhood and an unequivocal commitment to cultural cosmopolitanism. Analysing how Ray articulated his ideological positions through the quintessentially liberal device of complexly staged debates that were apparently free, but in fact closed by the scenarist/director on ideologically specific notes, this article concludes that Ray's reputation as an all-forgiving, ‘everybody-has-his-reasons’ humanist is based on simplistic or even tendentious readings of his work

Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al

The Kuramoto model in complex networks

181 pages, 48 figures. In Press, Accepted Manuscript, Physics Reports 2015 Acknowledgments We are indebted with B. Sonnenschein, E. R. dos Santos, P. Schultz, C. Grabow, M. Ha and C. Choi for insightful and helpful discussions. T.P. acknowledges FAPESP (No. 2012/22160-7 and No. 2015/02486-3) and IRTG 1740. P.J. thanks founding from the China Scholarship Council (CSC). F.A.R. acknowledges CNPq (Grant No. 305940/2010-4) and FAPESP (Grants No. 2011/50761-2 and No. 2013/26416-9) for financial support. J.K. would like to acknowledge IRTG 1740 (DFG and FAPESP).Peer reviewedPreprin