1,857 research outputs found
Temporal video transcoding from H.264/AVC-to-SVC for digital TV broadcasting
Mobile digital TV environments demand flexible video compression like scalable video coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. This paper proposes two techniques to convert an H.264/AVC bitstream in Baseline (P-pictures based) and Main Profile (B-pictures based) without scalability to a scalable bitstream with temporal scalability as part of a framework for low-complexity video adaptation for digital TV broadcasting. Our approaches are based on accelerating the interprediction, focusing on reducing the coding complexity of mode decision and motion estimation tasks of the encoder stage by using information available after the H. 264/AVC decoding stage. The results show that when our techniques are applied, the complexity is reduced by 98 % while maintaining coding efficiency
PHP46 Design and Operational Challenges With Time and Motion (T&M) Studies Run Alongside Clinical Trials
Detectable HIV Viral Load in Kenya: Data from a Population-Based Survey.
IntroductionAt the individual level, there is clear evidence that Human Immunodeficiency Virus (HIV) transmission can be substantially reduced by lowering viral load. However there are few data describing population-level HIV viremia especially in high-burden settings with substantial under-diagnosis of HIV infection. The 2nd Kenya AIDS Indicator Survey (KAIS 2012) provided a unique opportunity to evaluate the impact of antiretroviral therapy (ART) coverage on viremia and to examine the risks for failure to suppress viral replication. We report population-level HIV viral load suppression using data from KAIS 2012.MethodsBetween October 2012 to February 2013, KAIS 2012 surveyed household members, administered questionnaires and drew serum samples to test for HIV and, for those found to be infected with HIV, plasma viral load (PVL) was measured. Our principal outcome was unsuppressed HIV viremia, defined as a PVL ≥ 550 copies/mL. The exposure variables included current treatment with ART, prior history of an HIV diagnosis, and engagement in HIV care. All point estimates were adjusted to account for the KAIS 2012 cluster sampling design and survey non-response.ResultsOverall, 61·2% (95% CI: 56·4-66·1) of HIV-infected Kenyans aged 15-64 years had not achieved virological suppression. The base10 median (interquartile range [IQR]) and mean (95% CI) VL was 4,633 copies/mL (0-51,596) and 81,750 copies/mL (59,366-104,134), respectively. Among 266 persons taking ART, 26.1% (95% CI: 20.0-32.1) had detectable viremia. Non-ART use, younger age, and lack of awareness of HIV status were independently associated with significantly higher odds of detectable viral load. In multivariate analysis for the sub-sample of patients on ART, detectable viremia was independently associated with younger age and sub-optimal adherence to ART.DiscussionThis report adds to the limited data of nationally-representative surveys to report population- level virological suppression. We established heterogeneity across the ten administrative and HIV programmatic regions on levels of detectable viral load. Timely initiation of ART and retention in care are crucial for the elimination of transmission of HIV through sex, needle and syringe use or from mother to child. Further refinement of geospatial mapping of populations with highest risk of transmission is necessary
Weakly supervised deep learning for the detection of domain generation algorithms
Domain generation algorithms (DGAs) have become commonplace in malware that seeks to establish command and control communication between an infected machine and the botmaster. DGAs dynamically and consistently generate large volumes of malicious domain names, only a few of which are registered by the botmaster, within a short time window around their generation time, and subsequently resolved when the malware on the infected machine tries to access them. Deep neural networks that can classify domain names as benign or malicious are of great interest in the real-time defense against DGAs. In contrast with traditional machine learning models, deep networks do not rely on human engineered features. Instead, they can learn features automatically from data, provided that they are supplied with sufficiently large amounts of suitable training data. Obtaining cleanly labeled ground truth data is difficult and time consuming. Heuristically labeled data could potentially provide a source of training data for weakly supervised training of DGA detectors. We propose a set of heuristics for automatically labeling domain names monitored in real traffic, and then train and evaluate classifiers with the proposed heuristically labeled dataset. We show through experiments on a dataset with 50 million domain names that such heuristically labeled data is very useful in practice to improve the predictive accuracy of deep learning-based DGA classifiers, and that these deep neural networks significantly outperform a random forest classifier with human engineered features
Post-marketing assessment of content and efficacy of preservatives in artemisinin-derived antimalarial dry suspensions for paediatric use
BACKGROUND: Artemisinin-derivative formulations are now widely used to treat falciparum malaria. However, the dry powder suspensions developed for children are few and/or are of poor quality. In addition to the active compound, the presence of a suitable preservative in these medicines is essential. In this study, an evaluation of the preservative content and efficacy in some dry suspensions available on the Kenyan market was performed. METHOD: UV spectrophotometry was used to identify the preservatives in each sample while HPLC-UV was used for quantification. After reconstitution of the powders in water, the dissolution of the preservatives was followed for 7 days. Antimicrobial efficacy of the preservatives was assessed by conducting a preservative efficacy test (PET) following the European pharmacopoeia standards. RESULTS: Four different preservatives were identified namely methylparahydroxybenzoate (MP), propylparahydroxybenzoate (PP), benzoic acid and sorbic acid. MP and PP were identified in Artesiane(® )(artemether 300 mg/100 ml), Alaxin(® )(dihydroartemisinin 160 mg/80 ml) andGvither (® )(artemether 300 mg/100 ml) respectively. Sorbic acid was presentin Artenam(® )(artemether 180 mg/60 ml) while benzoic acid was identified in Santecxin(® )(dihydroartemisinin 160 mg/80 ml) andArtexin(® )(dihydroartemisinin 160 mg/80 ml) respectively. Cotecxin(® )(dihydroartemisinin 160 mg/80 ml) did not contain any of the above preservatives. After reconstitution in water, preservativesin 50%(3/6) of the products did not completely dissolve and the PET results revealed that only Artenam(® )and Gvither(® )met the requirements for antimicrobial efficacy. The other products did not conform. CONCLUSION: These results show that paediatric antimalarial dry powder formulations on the market may contain ineffective or incorrect amounts of preservatives. This is a potential risk to the patient. Studies conducted on the dry powder suspensions should include the analysis of both the active ingredient and the preservative, including the efficacy of the latter
Financial phantasmagoria: corporate image-work in times of crisis
Our purpose in this article is to relate the real movements in the economy during 2008 to the ?image-work? of financial institutions. Over the period January?December 2008 we collected 241 separate advertisements from 61 financial institutions published in the Financial Times. Reading across the ensemble of advertisements for themes and evocative images provides an impression of the financial imaginaries created by these organizations as the global financial crisis unfolded. In using the term ?phantasmagoria? we move beyond its colloquial sense of a set of strange images designed to dazzle towards the more technical connotation used by Ranci�re (2004) who suggested that words and images can offer a trace of an overall determining set-up if they are torn from their obviousness so they become phantasmagoric figures. The key phantasmagoric figure we identify here is that of the financial institution as timeless, immortal and unchanging; a coherent and autonomous entity amongst other actors. This notion of uniqueness belies the commonality of thinking which precipitated the global financial crisis as well as the limited capacity for control of financial institutions in relation to market events. It also functions as a powerful naturalizing force, making it hard to question certain aspects of the recent period of ?capitalism in crisis?
Encryption for high efficiency video coding with video adaptation capabilities
Video encryption techniques enable applications like digital rights management and video scrambling. Applying encryption on the entire video stream can be computationally costly and prevents advanced video modifications by an untrusted middlebox in the network, like splicing, quality monitoring, watermarking, and transcoding. Therefore, encryption techniques are proposed which influence a small amount of the video stream while keeping the video compliant with its compression standard, High Efficiency Video Coding. Encryption while guaranteeing standard compliance can cause degraded compression efficiency, so depending on their bitrate impact, a selection of encrypted syntax elements should be made. Each element also impacts the quality for untrusted decoders differently, so this aspect should also be considered. In this paper, multiple techniques for partial video encryption are investigated, most of them having a low impact on rate-distortion performance and having a broad range in scrambling performance(1)
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