Query: An evaluation of dynamic adaptive streaming over HTTP in vehicular environments

Relevant passages:
An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP <=SEP=> Adaptive (video) streaming over HTTP is gradually being adopted, as it offers significant advantages in terms of both user-perceived quality and resource utilization for content and network service providers. In this paper, we focus on the rate-adaptation mechanisms of adaptive streaming and experimentally evaluate two major commercial players (Smooth Streaming, Netflix) and one open source player (OSMF). Our experiments cover three important operating conditions. First, how does an adaptive video player react to either persistent or short-term changes in the underlying network available bandwidth. Can the player quickly converge to the maximum sustainable bitrate? Second, what happens when two adaptive video players compete for available bandwidth in the bottleneck link? Can they share the resources in a stable and fair manner? And third, how does adaptive streaming perform with live content? Is the player able to sustain a short playback delay? We identify major differences between the three players, and significant inefficiencies in each of them.

Dynamic adaptive streaming over HTTP dataset <=SEP=> The delivery of audio-visual content over the Hypertext Transfer Protocol (HTTP) got lot of attention in recent years and with dynamic adaptive streaming over HTTP (DASH) a standard is now available. Many papers cover this topic and present their research results, but unfortunately all of them use their own private dataset which -- in most cases -- is not publicly available. Hence, it is difficult to compare, e.g., adaptation algorithms in an objective way due to the lack of a common dataset which shall be used as basis for such experiments. In this paper, we present our DASH dataset including our DASHEncoder, an open source DASH content generation tool. We also provide basic evaluations of the different segment lengths, the influence of HTTP server settings, and, in this context, we show some of the advantages as well as problems of shorter segment lengths.

Dynamic adaptive streaming over HTTP -: standards and design principles <=SEP=> In this paper, we provide some insight and background into the Dynamic Adaptive Streaming over HTTP (DASH) specifications as available from 3GPP and in draft version also from MPEG. Specifically, the 3GPP version provides a normative description of a Media Presentation, the formats of a Segment, and the delivery protocol. In addition, it adds an informative description on how a DASH Client may use the provided information to establish a streaming service for the user. The solution supports different service types (e.g., On-Demand, Live, Time-Shift Viewing), different features (e.g., adaptive bitrate switching, multiple language support, ad insertion, trick modes, DRM) and different deployment options. Design principles and examples are provided.

Dynamic Adaptive Streaming over HTTP – Design Principles and Standards <=SEP=> In this paper, we provide some insight and background into the Dynamic Adaptive Streaming over HTTP (DASH) specifications as available from 3GPP and in draft version also from MPEG. Specifically, the 3GPP version provides a normative description of a Media Presentation, the formats of a Segment, and the delivery protocol. In addition, it adds an informative description on how a DASH Client may use the provided information to establish a streaming service for the user. The solution supports different service types (e.g., On-Demand, Live, Time-Shift Viewing), different features (e.g., adaptive bitrate switching, multiple language support, ad insertion, trick modes, DRM) and different deployment options. Design principles and some forward-looking considerations are provided.

Dummynet: a simple approach to the evaluation of network protocols <=SEP=> Network protocols are usually tested in operational networks or in simulated environments. With the former approach it is not easy to set and control the various operational parameters such as bandwidth, delays, queue sizes. Simulators are easier to control, but they are often only an approximate model of the desired setting, especially for what regards the various traffic generators (both producers and consumers) and their interaction with the protocol itself.In this paper we show how a simple, yet flexible and accurate network simulator - dummynet - can be built with minimal modifications to an existing protocol stack, allowing experiments to be run on a standalone system. dummynet works by intercepting communications of the protocol layer under test and simulating the effects of finite queues, bandwidth limitations and communication delays. It runs in a fully operational system, hence allowing the use of real traffic generators and protocol implementations, while solving the problem of simulating unusual environments. With our tool, doing experiments with network protocols is as simple as running the desired set of applications on a workstation.A FreeBSD implementation of dummynet, targeted to TCP, is available from the author. This implementation is highly portable and compatible with other BSD-derived systems, and takes less than 300 lines of kernel code.

Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks <=SEP=> In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks. The extrapolation scheme is a classical approach for accelerating stochastic gradient descent for convex optimization, but it does not work well for nonconvex optimization typically. Alternatively, we propose an interpolation scheme to accelerate nonconvex optimization and call the method Interpolatron. We explain motivation behind Interpolatron and conduct a thorough empirical analysis. Empirical results on DNNs of great depths (e.g., 98-layer ResNet and 200-layer ResNet) on CIFAR-10 and ImageNet show that Interpolatron can converge much faster than the stateof-the-art methods such as the SGD with momentum and Adam. Furthermore, Anderson’s acceleration, in which mixing coefficients are computed by least-squares estimation, can also be used to improve the performance. Both Interpolatron and Anderson’s acceleration are easy to implement and tune. We also show that Interpolatron has linear convergence rate under certain regularity assumptions.

How Does He Saw Me ? A Recommendation Engine for Picking Heroes in Dota 2 <=SEP=> In this paper, we present a hero recommendation engine for the popular computer game Dota 2. We detail previous efforts at hero recommendation, building on these to provide a more complete exploration of machine learning algorithms applied to this problem. In addition to discussing the details behind the machine learning algorithms we use, we also provide insight into our method of data collection and feature selection. In doing so, the outcome of our efforts is two-fold. First, we provide the first public survey of machine learning algorithms applied to Dota 2–in the process gaining further insight into the algorithms we explore. Second, we provide a tool that we believe will be useful for both the casual and competitive sides of Dota 2’s 6 million unique player base.

Simultaneous penile-vaginal intercourse orgasm is associated with satisfaction (sexual, life, partnership, and mental health). <=SEP=> INTRODUCTION
Previous multivariate research found that satisfaction was associated positively with frequency of specifically penile-vaginal intercourse (PVI; as opposed to other sexual activities) as well as with vaginal orgasm. The contribution to satisfaction of simultaneous orgasm produced by PVI merited direct examination in a large representative sample.


AIMS
To examine the associations of aspects of satisfaction (sexual, life, own mental health, partner relationship) with consistency of simultaneous orgasm produced by PVI (as well as with PVI frequency and vaginal orgasm consistency).


METHODS
A representative sample of Czechs (N = 1,570) aged 35-65 years completed a survey on aspects of satisfaction, PVI frequency, vaginal orgasm consistency, and consistency of simultaneous orgasm produced by PVI (the latter being a specially timed version of vaginal orgasm for women).


MAIN OUTCOME MEASURES
Analysis of variance of satisfaction components (LiSat scale items) from age and the sexual behaviors.


RESULTS
For both sexes, all aspects of satisfaction were associated with simultaneous PVI orgasm consistency and with PVI frequency (except female life satisfaction). All aspects of satisfaction were also associated with vaginal orgasm consistency. Multivariate analyses indicated that PVI frequency and simultaneous orgasm consistency make independent contributions to the aspects of satisfaction for both sexes.


CONCLUSIONS
For both sexes, PVI frequency and simultaneous orgasm produced by PVI (as well as vaginal orgasm for women) are associated with greater life, sexual, partnership, and mental health satisfaction. Greater support for these specific aspects of sexual activity is warranted.

Note-Taking and Secondary Students with Learning Disabilities : Challenges and Solutions <=SEP=> As more secondary students with learning disabilities (LD) enroll in advanced content-area classes and are expected to pass state exams, they are faced with the challenge of mastering difficult concepts and abstract vocabulary while learning content. Once in these classes, students must learn from lectures that move at a quick pace, record accurate and complete notes, and then demonstrate their mastery of the content on tests. This article provides an overview of the challenges faced by students with LD in content-area classes and discusses the problems that students have learning from lectures and recording notes. Further, the article discusses theory and research related to note-taking and presents note-taking interventions that teachers can use to help students improve their note-taking skills, and ultimately, improve their achievement in these classes.

Finding and Fixing Vehicle NVH Problems with Transfer Path Analysis <=SEP=> This article discusses the use of experimental transfer path analysis (TPA) to find optimized solutions to NVH problems remaining late in vehicle development stages. After a short review of established TPA methods, four practical case histories are discussed to illustrate how TPA, FE models and practical experiments can supplement each other efficiently for finding optimum and attribute-balanced solutions to complex NVH issues late in the development process. Experimental transfer path analysis (TPA) is a fairly well established technique, 1,2 for estimating and ranking individual low-frequency noise or vibration contributions via the different structural transmission paths from point-coupled power-train or wheel suspensions to the vehicle body. TPA is also used to analyze the transmission paths into vibration-isolated truck or tractor cabs etc. TPA can also be used at higher frequencies (above 150-200 Hz) in road vehicles, although it may be reasonable to introduce a somewhat different formulation based on the response statistics of multimodal vibro-acoustic systems with strong modal overlap. 3 When NVH problems still remain close to start of production (SOP), experimental TPA is often a favored technique to investigate further possibilities to fine-tune the rubber components of the engine or wheel suspension with respect to NVH. The aim is to further improve NVH with minimal negative impact on other vehicle attributes, such as ride comfort, handling , drivability, durability, etc. The only design parameters that can directly be changed in a " what if? " study based purely on experimental TPA, are the dynamic properties of rubber elements connecting the source and the receiving structure. Also, any reduction of transfer path contributions to noise or vibration in that case will be a result of reducing some of the dynamic stiffness' for the connecting elements. To take any other design changes into account, additional measurements are normally necessary. Each degree of freedom (DOF) acting at interface points between a vibration source system and a receiving, passive vibro-acoustic system is a transfer path in TPA. TPA can also be performed analytically, using FE models or specialized system analysis software. 4 The experimental TPA method involves: 1) An indirect measurement procedure for estimating operating force components acting at the coupled DOFs. 2) The direct or reciprocal measurement of all transfer frequency response functions (FRFs) between response in points of interest (e.g. at the drivers ear) and points where these forces act. The FRFs are measured with the receiving subsystem disconnected at all …

gHull: A GPU algorithm for 3D convex hull <=SEP=> A novel algorithm is presented to compute the convex hull of a point set in ℝ3 using the graphics processing unit (GPU). By exploiting the relationship between the Voronoi diagram and the convex hull, the algorithm derives the approximation of the convex hull from the former. The other extreme vertices of the convex hull are then found by using a two-round checking in the digital and the continuous space successively. The algorithm does not need explicit locking or any other concurrency control mechanism, thus it can maximize the parallelism available on the modern GPU.
 The implementation using the CUDA programming model on NVIDIA GPUs is exact and efficient. The experiments show that it is up to an order of magnitude faster than other sequential convex hull implementations running on the CPU for inputs of millions of points. The works demonstrate that the GPU can be used to solve nontrivial computational geometry problems with significant performance benefit.

The evolutionary impact of invasive species. <=SEP=> Since the Age of Exploration began, there has been a drastic breaching of biogeographic barriers that previously had isolated the continental biotas for millions of years. We explore the nature of these recent biotic exchanges and their consequences on evolutionary processes. The direct evidence of evolutionary consequences of the biotic rearrangements is of variable quality, but the results of trajectories are becoming clear as the number of studies increases. There are examples of invasive species altering the evolutionary pathway of native species by competitive exclusion, niche displacement, hybridization, introgression, predation, and ultimately extinction. Invaders themselves evolve in response to their interactions with natives, as well as in response to the new abiotic environment. Flexibility in behavior, and mutualistic interactions, can aid in the success of invaders in their new environment.

ICDAR 2013 Chinese Handwriting Recognition Competition <=SEP=> This paper describes the Chinese handwriting recognition competition held at the 12th International Conference on Document Analysis and Recognition (ICDAR 2013). This third competition in the series again used the CASIA-HWDB/OLHWDB databases as the training set, and all the submitted systems were evaluated on closed datasets to report character-level correct rates. This year, 10 groups submitted 27 systems for five tasks: classification on extracted features, online/offline isolated character recognition, online/offline handwritten text recognition. The best results (correct rates) are 93.89% for classification on extracted features, 94.77% for offline character recognition, 97.39% for online character recognition, 88.76% for offline text recognition, and 95.03% for online text recognition, respectively. In addition to the test results, we also provide short descriptions of the recognition methods and brief discussions on the results.

Fusion of Stereo Vision for Pedestrian Recognition using Convolutional Neural Networks <=SEP=> Pedestrian detection is a highly debated issue in the scientific community due to its outstanding importance for a large number of applications, especially in the fields of automotive safety, robotics and surveillance. In spite of the widely varying methods developed in recent years, pedestrian detection is still an open challenge whose accuracy and robustness has to be improved. Therefore, in this paper, we focus on improving the classification component in the pedestrian detection task on the Daimler stereo vision data set by adopting two approaches: 1) by combining three image modalities (intensity, depth and flow) to feed a unique convolutional neural network (CNN) and 2) by fusing the results of three independent CNNs.

International Accounting Standards and Accounting Quality <=SEP=> We compare characteristics of accounting amounts for firms that apply International Accounting Standards (IAS) to a matched sample of firms that do not to investigate whether applying IAS is associated with higher accounting quality and lower equity cost of capital. We find that firms applying IAS evidence less earnings management, more timely loss recognition, and more value relevance of accounting amounts than do those applying domestic GAAP. Firms applying IAS have higher variance of the change in net income, a higher ratio of the variances of the change in net income and change in cash flows, a significantly less negative correlation between accruals and cash flows, and a lower frequency of small positive net income. They have a significantly higher frequency of large negative net income and generally higher value relevance of accounting amounts. Differences between firms applying IAS and those applying domestic GAAP in the period before IAS firms adopt IAS do not explain the differences in accounting quality. Firms applying IAS generally exhibit higher accounting quality than when they previously applied domestic GAAP. The increase in accounting quality for IAS firms is generally greater than that for firms applying domestic GAAP throughout the sample period. We also find weak evidence suggesting that application of IAS is associated with a lower equity cost of capital. Overall, our results suggest improvement in accounting quality associated with applying IAS.

As Cool as a Cucumber: Towards a Corpus of Contemporary Similes in Serbian <=SEP=> Similes are natural language expressions used to compare unlikely things, where the comparison is not taken literally. They are often used in everyday communication and are an important part of cultural heritage. Having an up-to-date corpus of similes is challenging, as they are constantly coined and/or adapted to the contemporary times. In this paper we present a methodology for semi-automated collection of similes from the world wide web using text mining techniques. We expanded an existing corpus of traditional similes (containing 333 similes) by collecting 446 additional expressions. We, also, explore how crowdsourcing can be used to extract and curate new similes.

Network-Based Intrusion Detection Using Unsupervised Adaptive Resonance Theory ( ART ) <=SEP=> This paper introduces the Unsupervised Neural Net based Intrusion Detector (UNNID) system, which detects network-based intrusions and attacks using unsupervised neural networks. The system has facilities for training, testing, and tunning of unsupervised nets to be used in intrusion detection. Using the system, we tested two types of unsupervised Adaptive Resonance Theory (ART) nets (ART-1 and ART-2). Based on the results, such nets can efficiently classify network traffic into normal and intrusive. The system uses a hybrid of misuse and anomaly detection approaches, so is capable of detecting known attack types as well as new attack types as anomalies.

The Information Systems Identity Crisis: Focusing on High-Visibility and High-Impact Research <=SEP=> This paper presents an alternative view of the Information Systems identity crisis described recently by Benbasat and Zmud (2003). We agree with many of their observations, but we are concerned with their prescription for IS research. We critique their discussion of errors of inclusion and exclusion in IS research and highlight the potential misinterpretations that are possible from a literal Ron Weber was the accepting senior editor for this paper. Iris Vessey and Rudy Hirschheim served as reviewers. reading of their comments. Our conclusion is that following Benbasat and Zmud’s nomological net will result in a micro focus for IS research. The results of such a focus are potentially dangerous for the field. They could result in the elimination of IS from many academic programs. We present an alternative set of heuristics that can be used to assess what lies within the domain of IS scholarship. We argue that the IS community has a powerful story to tell about the transformational impact of information technology. We believe that a significant portion of our research should be macro studies of the impact of IT. It is important for academic colleagues, deans, and managers to understand the transformational power of the technology. As IS researchers with deep knowledge of the underlying artifact, we are best positioned to do such research.

Electronic model of human brain using verilog <=SEP=> Computers are man-made machines which work according to the given set of inputs and perform some operation on the input to generate a new set of outputs. They can be programmed to perform huge and complex task yet they lack imagination and ability to understand things. On the hand human brain is a machine which can learn new tasks by process of acquiring knowledge and understanding through thought, experience and the senses. To make computer work or think like human, human brain modeling of machine is necessary. We need to know how human brain works. The basic component of human brain is neuron, which make us think and do smart things. Brains have billions of neurons and they communicate with each other using electrical impulse. These impulses are responsible for making brain think and to have a consciousness. This paper proposes such a model of a part of the brain.

Object-Oriented Bayesian Networks <=SEP=> Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applications. However, when faced with a large complex domain, the task of modeling using Bayesian networks begins to resemble the task of programming using logical circuits. In this paper, we describe an object-oriented Bayesian network (OOBN) language, which allows complex domains to be described in terms of inter-related objects. We use a Bayesian network fragment to describe the probabilistic relations between the attributes of an object. These attributes can themselves be objects, providing a natural framework for encoding part-of hierarchies. Classes are used to provide a reusable probabilistic model which can be applied to multiple similar objects. Classes also support inheritance of model fragments from a class to a subclass, allowing the common aspects of related classes to be defined only once. Our language has clear declarative semantics: an OOBN can be interpreted as a stochastic functional program, so that it uniquely specifies a probabilistic model. We provide an inference algorithm for OOBNs, and show that much of the structural information encoded by an OOBN—particularly the encapsulation of variables within an object and the reuse of model fragments in different contexts—can also be used to speed up the inference process.

Entrapment of the sciatic nerve at the linea aspera: A case report and literature review <=SEP=> BACKGROUND
Nontraumatic, non-neoplastic sciatic nerve entrapment at the level of the thigh is extremely rare. In its course, in proximity of the linea aspera, the nerve is exposed to unexpected neuropathic syndromes associated with bone disorders.


CASE DESCRIPTION
A 67-year-old woman presented with a painful, neuropathic syndrome of the sciatic nerve, not resulting from any trauma and persisting for approximately 2 years. Imaging studies of the thigh showed a delimited zone of hyperostosis in the proximal third of the femoral diaphysis. The symptoms dramatically resolved after the patient underwent neurolysis of the tract of the nerve adjoining to the linea aspera. At the clinical checkup 2 years later, the patient remained free of pain.


CONCLUSION
The diagnosis of sciatic nerve entrapment at the linea aspera may present considerable difficulties. The clinical history and physical examination sometimes motivate the exploration and neurolysis of the nerve at this site.

Leveraging Peer Centrality in the Designof Socially-Informed Peer-to-Peer Systems <=SEP=> Social applications mine user social graphs to improve performance in search, provide recommendations, allow resource sharing and increase data privacy. When such applications are implemented on a peer-to-peer (P2P) architecture, the social graph is distributed on the P2P system: the traversal of the social graph translates into a socially-informed routing in the peer-to-peer layer. In this work we introduce the model of a projection graph that is the result of decentralizing a social graph onto a peer-to-peer network. We focus on three social network metrics: degree, node betweenness and edge betweenness centrality and analytically formulate the relation between metrics in the social graph and in the projection graph. We demonstrate with an application scenario on real social networks the usability of the projection graph properties in designing social search applications and unstructured P2P overlays that exhibit improved performance and reduced overhead over baseline scenarios.

The Coherent Heart Heart – Brain Interactions , Psychophysiological Coherence , and the Emergence of System-Wide Order <=SEP=> This article presents theory and research on the scientific study of emotion that emphasizes the importance of coherence as an optimal psychophysiological state. A dynamic systems view of the interrelations between psychological, cognitive and emotional systems and neural communication networks in the human organism provides a foundation for the view presented. These communication networks are examined from an information processing perspective and reveal a fundamental order in heart-brain interactions and a harmonious synchronization of physiological systems associated with positive emotions. The concept of coherence is drawn on to understand optimal functioning which is naturally reflected in the heart’s rhythmic patterns. Research is presented identifying various psychophysiological states linked to these patterns, with neurocardiological coherence emerging as having significant impacts on well being. These include psychophysiological as well as improved cognitive performance. From this, the central role of the heart is explored in terms of biochemical, biophysical and energetic interactions. Appendices provide further details and research on; psychophysiological functioning, reference previous research in this area, details on research linking coherence with optimal cognitive performance, heart brain synchronization and the energetic signature of the various psychophysiological modes.

Study of Hand Gesture Recognition Technologies and Applications for Human Vehicle Interaction <=SEP=> This paper describes the primary and secondary driving task together with Human Machine Interface (HMI) trends and issues which are driving automotive user interface designers to consider hand gesture recognition as a realistic alternative for user controls. A number of hand gesture recognition technologies and applications for Human Vehicle Interaction (HVI) are also discussed including a summary of current automotive hand gesture recognition research.

1.5MVA grid-connected interleaved inverters using coupled inductors for wind power generation system <=SEP=> In this paper, grid-connected interleaved voltage source inverters for PMSG wind power generation system with coupled inductors is introduced. In parallel operation, the undesirable circulating current flows between inverters. There are some differences in circulating currents according to source configuration. It is mathematically analyzed and simulated for the verification of analysis. In case of interleaved inverters, the uncontrollable circulating current in switching frequency level flows between inverter modules regardless of source configuration such as common or separated if filter inductance which is placed between inverters is significantly low. In order to suppress high frequency circulating current, the coupled inductors are employed in each phase. A case of 1.5MVA grid-connected interleaved inverters using coupled inductors prototype for the PMSG wind power generation Back To Back converters in parallel are introduced and experimentally verified the proposed topology.

Machine Learning Strategies for Time Series Forecasting <=SEP=> The increasing availability of large amounts of historical data and the need of performing accurate forecasting of future behavior in several scientific and applied domains demands the definition of robust and efficient techniques able to infer from observations the stochastic dependency between past and future. The forecasting domain has been influenced, from the 1960s on, by linear statistical methods such as ARIMA models. More recently, machine learning models have drawn attention and have established themselves as serious contenders to classical statistical models in the forecasting community. This chapter presents an overview of machine learning techniques in time series forecasting by focusing on three aspects: the formalization of one-step forecasting problems as supervised learning tasks, the discussion of local learning techniques as an effective tool for dealing with temporal data and the role of the forecasting strategy when we move from one-step to multiple-step forecasting.

Preliminary, open-label, pilot study of add-on oral Δ9-tetrahydrocannabinol in chronic post-traumatic stress disorder. <=SEP=> BACKGROUND AND OBJECTIVES
Many patients with post-traumatic stress disorder (PTSD) achieve but partial remission with current treatments. Patients with unremitted PTSD show high rates of substance abuse. Marijuana is often used as compassion add-on therapy for treatment-resistant PTSD. This open-label study evaluates the tolerance and safety of orally absorbable Δ(9)-tetrahydrocannabinol (THC) for chronic PTSD.


METHODS
Ten outpatients with chronic PTSD, on stable medication, received 5 mg of Δ(9)-THC twice a day as add-on treatment.


RESULTS
There were mild adverse effects in three patients, none of which led to treatment discontinuation. The intervention caused a statistically significant improvement in global symptom severity, sleep quality, frequency of nightmares, and PTSD hyperarousal symptoms.


CONCLUSIONS
Orally absorbable Δ(9)-THC was safe and well tolerated by patients with chronic PTSD.

Subjective Evaluation of Latency and Packet Loss in a Cloud-Based Game <=SEP=> On-demand multimedia services are more popular than ever and continue to grow. Consumers can now stream music, movies, television, and video games at the push of a button. Such services typically require a minimum connection speed to support streaming. However, transient network effects such as packet loss and delay variation can play a crucial role in determining the user quality of experience (QoE) in streaming multimedia systems. This paper will seek to establish the subjective impact of negative network effects on the user experience of a popular cloud-based on-demand video game service.

Privacy preservation and public auditing for cloud data using ASS in Multi-cloud <=SEP=> Cloud computing is the new business paradigm introduced in the IT market in the current decade providing the customers with the option to pay for the amount of service utilized. The use of cloud computing has increased rapidly in many organizations. Ensuring security of data in a cloud is a major factor in the cloud computing environment, as users often store fragile information in cloud storage. Public auditing on shared data stored in the cloud is done by exploiting Aggregate Signature Scheme. With this mechanism, the identity of the signer of various blocks of shared data is kept private from public verifiers, who are able to verify efficiently the integrity of shared data without retrieving the entire file. However traceability is a major issue. A Multi-clouds Database Model (MCDB) which is based on Multi-clouds service providers instead of using single cloud service provider such as in Amazon cloud service is used to implement traceability. Also, dealing with single cloud providers is predicted to become less popular with customers due to risks of service availability failure and the possibility of malicious insiders in the single cloud. A movement towards multi-clouds is highly efficient and this system would also check for the data's which are attacked by malicious users, with short time and cost requirement.

Event-Driven Semantic Concept Discovery by Exploiting Weakly Tagged Internet Images <=SEP=> Analysis and detection of complex events in videos require a semantic representation of the video content. Existing video semantic representation methods typically require users to pre-define an exhaustive concept lexicon and manually annotate the presence of the concepts in each video, which is infeasible for real-world video event detection problems. In this paper, we propose an automatic semantic concept discovery scheme by exploiting Internet images and their associated tags. Given a target event and its textual descriptions, we crawl a collection of images and their associated tags by performing text based image search using the noun and verb pairs extracted from the event textual descriptions. The system first identifies the candidate concepts for an event by measuring whether a tag is a meaningful word and visually detectable. Then a concept visual model is built for each candidate concept using a SVM classifier with probabilistic output. Finally, the concept models are applied to generate concept based video representations. We use the TRECVID Multimedia Event Detection (MED) 2013 as our video test set and crawl 400K Flickr images to automatically discover 2, 000 visual concepts. We show significant performance gains of the proposed concept discovery method over different video event detection tasks including supervised event modeling over concept space and semantic based zero-shot retrieval without training examples. Importantly, we show the proposed method of automatic concept discovery outperforms other well-known concept library construction approaches such as Classemes and ImageNet by a large margin (228%) in zero-shot event retrieval. Finally, subjective evaluation by humans also confirms clear superiority of the proposed method in discovering concepts for event representation.