Heavyweight extensions to the UML metamodel to describe the C3 architectural style

UML is widely accepted as the standard for representing the various software artifacts generated by a development process. For this reason, there have been attempts to use this language to represent the software architecture of systems as well. Unfortunately, these attempts have ended in the same representations (boxes and lines) already criticized by the software architecture community.In this work we propose an extension to the UML metamodel that is able to represent the syntactics and semantics of the C3 architectural style. This style is derived from C2. The modifications to define C3 are described in section 4. This proposal is innovative regarding UML extensions for software architectures, since previous proposals where based on light extensions to the UML meta-model, while we propose a heavyweight extension of the metamodel. On the other hand, this proposal is less ambitious than previous proposals, since we do not want to represent in UML any architectural style, but only one: C3.

Subjective quality assessment of an adaptive video streaming model

With the recent increased popularity and high usage of HTTP Adaptive Streaming (HAS) techniques, various studies have been carried out in this area which generally focused on the technical enhancement of HAS technology and applications. However, a lack of common HAS standard led to multiple proprietary approaches which have been developed by major Internet companies. In the emerging MPEG-DASH standard the packagings of the video content and HTTP syntax have been standardized; but all the details of the adaptation behavior are left to the client implementation. Nevertheless, to design an adaptation algorithm which optimizes the viewing experience of the enduser, the multimedia service providers need to know about the Quality of Experience (QoE) of different adaptation schemes. Taking this into account, the objective of this experiment was to study the QoE of a HAS-based video broadcast model. The experiment has been carried out through a subjective study of the end user response to various possible clients’ behavior for changing the video quality taking different QoE-influence factors into account. The experimental conclusions have made a good insight into the QoE of different adaptation schemes which can be exploited by HAS clients for designing the adaptation algorithms.

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

Quality of experience and HTTP adaptive streaming: a review of subjective studies

HTTP adaptive streaming technology has become widely spread in multimedia services because of its ability to provide adaptation to characteristics of various viewing devices and dynamic network conditions. There are various studies targeting the optimization of adaptation strategy. However, in order to provide an optimal viewing experience to the end-user, it is crucial to get knowledge about the Quality of Experience (QoE) of different adaptation schemes. This paper overviews the state of the art concerning subjective evaluation of adaptive streaming QoE and highlights the challenges and open research questions related to QoE assessment.

Crowdsourcing based subjective quality assessment of adaptive video streaming

In order to cater for user's quality of experience (QoE) requirements, HTTP adaptive streaming (HAS) based solutions of video services have become popular recently. User QoE feedback can be instrumental in improving the capabilities of such services. Perceptual quality experiments that involve humans are considered to be the most valid method of the assessment of QoE. Besides lab-based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This paper presents insights into a study that investigates perceptual preferences of various adaptive video streaming scenarios through crowdsourcing based subjective quality assessment.

Subjective quality study of adaptive streaming of monoscopic and stereoscopic video

Nowadays, HTTP adaptive streaming (HAS) has become a reliable distribution technology offering significant advantages in terms of both user perceived Quality of Experience (QoE) and resource utilization for content and network service providers. By trading-off the video quality, HAS is able to adapt to the available bandwidth and display requirements so that it can deliver the video content to a variety of devices over the Internet. However, until now there is not enough knowledge of how the adaptation techniques affect the end user's visual experience. Therefore, this paper presents a comparative analysis of different bitrate adaptation strategies in adaptive streaming of monoscopic and stereoscopic video. This has been done through a subjective experiment of testing the end-user response to the video quality variations, considering the visual comfort issue. The experimental outcomes have made a good insight into the factors that can influence on the QoE of different adaptation strategies.

Effect of content characteristics on quality of experience of adaptive streaming

The growing popularity of adaptive streaming-based video delivery nowadays has raised the interest about the user's perception when experiencing quality adaptation. The impact of the video content characteristics on user's perceptual quality has already become evident. The aim of this study is to investigate the influence of this factor on the quality of experience of adaptive streaming scenarios. Our results show that the perceptual quality of adaptation strategies applied on videos with high spatial and low temporal amount of activity is significantly lower compared to the other content types.

Subjective QoE Analysis of HTTP Adaptive Streaming Applications

Actualmente la optimization de la calidad de experiencia (Quality of Experience- QoE) de HTTP Adaptive Streaming (HAS) de video recibe una atención creciente. Este incremento de interés proviene fundamentalmente de las carencias de las soluciones actuales HAS, que, al no ser QoE-driven, no incluyen la percepción de la calidad de los usuarios finales como una parte integral de la lógica de adaptación. Por lo tanto, la obtención de información de referencia fiable en QoE en HAS presenta retos importantes, ya que las metodologías de evaluación subjetiva de la calidad de vídeo propuestas en las normas actuales no son adecuadas para tratar con la variación temporal de la calidad que es consustancial de HAS. Esta tesis investiga la influencia de la adaptación dinámica en la calidad de la transmisión de vídeo considerando métodos de evaluación subjetiva. Tras un estudio exhaustivo del estado del arte en la evaluación subjetiva de QoE en HAS, se han resaltado los retos asociados y las líneas de investigación abiertas. Como resultado, se han seleccionado dos líneas principales de investigación: el análisis del impacto en la QoE de los parámetros de las técnicas de adaptación y la investigación de las metodologías de prueba subjetiva adecuada para evaluación de QoE en HAS. Se han llevado a cabo un conjunto de experimentos de laboratorio para investigar las cuestiones planteadas mediante la utilización de diferentes metodologáas para pruebas subjetivas. El análisis estadístico muestra que no son robustas todas las suposiciones y reivindicaciones de las referencias analizadas, en particular en lo que respecta al impacto en la QoE de la frecuencia de las variaciones de calidad, de las adaptaciones suaves o abruptas y de las oscilaciones de calidad. Por otra parte, nuestros resultados confirman la influencia de otros parámetros, como la longitud de los segmentos de vídeo y la amplitud de las oscilaciones de calidad. Los resultados también muestran que tomar en consideración las características objetivas de los contenidos puede ser beneficioso para la mejora de la QoE en HAS. Además, todos los resultados han sido validados mediante extensos análisis experimentales que han incluido estudio tanto en otros laboratorios como en crowdsourcing Por último, sobre los aspectos metodológicos de las pruebas subjetivas de QoE, se ha realizado la comparación entre los resultados experimentales obtenidos a partir de un método estandarizado basado en estímulos cortos (ACR) y un método semi continuo (desarrollado para la evaluación de secuencias prolongadas de vídeo). A pesar de algunas diferencias, el resultado de los análisis estadísticos no muestra ningún efecto significativo de la metodología de prueba. Asimismo, aunque se percibe la influencia de la presencia de audio en la evaluación de degradaciones del vídeo, no se han encontrado efectos estadísticamente significativos de dicha presencia. A partir de la ausencia de influencia del método de prueba y de la presencia de audio, se ha realizado un análisis adicional sobre el impacto de realizar comparaciones estadísticas múltiples en niveles estadísticos de importancia que aumentan la probabilidad de los errores de tipo-I (falsos positivos). Nuestros resultados muestran que, para obtener un efectos sólido en el análisis estadístico de los resultados subjetivos, es necesario aumentar el número de sujetos de las pruebas claramente por encima de los tamaños de muestras propuestos por las normas y recomendaciones actuales. ABSTRACT Optimizing the Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) is receiving increasing attention nowadays. The growth of interest is mainly caused by the fact that current HAS solutions are not QoE-driven, i.e. end-user quality perception is not integral part of the adaptation logic. However, obtaining the necessary reliable ground truths on HAS QoE faces substantial challenges, since the subjective video quality assessment methodologies as proposed by current standards are not well-suited for dealing with the time-varying quality properties that are characteristic for HAS. This thesis investigates the influence of dynamic quality adaptation on the QoE of streaming video by means of subjective evaluation approaches. Based on a comprehensive survey of related work on subjective HAS QoE assessment, the related challenges and open research questions are highlighted and discussed. As a result, two main research directions are selected for further investigation: analysis of the QoE impact of different technical adaptation parameters, and investigation of testing methodologies suitable for HAS QoE evaluation. In order to investigate related research issues and questions, a set of laboratory experiments have been conducted using different subjective testing methodologies. Our statistical analysis demonstrates that not all assumptions and claims reported in the literature are robust, particularly as regards the QoE impact of switching frequency, smooth vs. abrupt switching, and quality oscillation. On the other hand, our results confirm the influence of some other parameters such as chunk length and switching amplitude on perceived quality. We also show that taking the objective characteristics of the content into account can be beneficial to improve the adaptation viewing experience. In addition, all aforementioned findings are validated by means of an extensive cross-experimental analysis that involves external laboratory and crowdsourcing studies. Finally, to address the methodological aspects of subjective QoE testing, a comparison between the experimental results obtained from a (short stimuli-based) ACR standardized method and a semi-continuous method (developed for assessment of long video sequences) has been performed. In spite of observation of some differences, the result of statistical analysis does not show any significant effect of testing methodology. Similarly, although the influence of audio presence on evaluation of video-related degradations is perceived, no statistically significant effect of audio presence could be found. Motivating by this finding (no effect of testing method and audio presence), a subsequent analysis has been performed investigating the impact of performing multiple statistical comparisons on statistical levels of significance which increase the likelihood of Type-I errors (false positives). Our results show that in order to obtain a strong effect from the statistical analysis of the subjective results, it is necessary to increase the number of test subjects well beyond the sample sizes proposed by current quality assessment standards and recommendations.

Quality of experience of adaptive video streaming: investigation in service parameters and subjective quality assessment methodology

The usage of HTTP adaptive streaming (HAS) has become widely spread in multimedia services. Because it allows the service providers to improve the network resource utilization and user׳s Quality of Experience (QoE). Using this technology, the video playback interruption is reduced since the network and server status in addition to capability of user device, all are taken into account by HAS client to adapt the quality to the current condition. Adaptation can be done using different strategies. In order to provide optimal QoE, the perceptual impact of adaptation strategies from point of view of the user should be studied. However, the time-varying video quality due to the adaptation which usually takes place in a long interval introduces a new type of impairment making the subjective evaluation of adaptive streaming system challenging. The contribution of this paper is two-fold: first, it investigates the testing methodology to evaluate HAS QoE by comparing the subjective experimental outcomes obtained from ACR standardized method and a semi-continuous method developed to evaluate the long sequences. In addition, influence of using audiovisual stimuli to evaluate the video-related impairment is inquired. Second, impact of some of the adaptation technical factors including the quality switching amplitude and chunk size in combination with high range of commercial content type is investigated. The results of this study provide a good insight toward achieving appropriate testing method to evaluate HAS QoE, in addition to designing switching strategies with optimal visual quality.

Streaming potential measurements in αβγ-rat epithelial Na+ channel in planar lipid bilayers

Streaming potentials across cloned epithelial Na+ channels (ENaC) incorporated into planar lipid bilayers were measured. We found that the establishment of an osmotic pressure gradient (Δπ) across a channel-containing membrane mimicked the activation effects of a hydrostatic pressure differential (ΔP) on αβγ-rENaC, although with a quantitative difference in the magnitude of the driving forces. Moreover, the imposition of a Δπ negates channel activation by ΔP when the Δπ was directed against ΔP. A streaming potential of 2.0 ± 0.7 mV was measured across αβγ-rat ENaC (rENaC)-containing bilayers at 100 mM symmetrical [Na+] in the presence of a 2 Osmol/kg sucrose gradient. Assuming single file movement of ions and water within the conduction pathway, we conclude that between two and three water molecules are translocated together with a single Na+ ion. A minimal effective pore diameter of 3 Å that could accommodate two water molecules even in single file is in contrast with the 2-Å diameter predicted from the selectivity properties of αβγ-rENaC. The fact that activation of αβγ-rENaC by ΔP can be reproduced by the imposition of Δπ suggests that water movement through the channel is also an important determinant of channel activity.

Synaptic Vesicles Form by Budding from Tubular Extensions of Sorting Endosomes in PC12 Cells

The putative role of sorting early endosomes (EEs) in synaptic-like microvesicle (SLMV) formation in the neuroendocrine PC12 cell line was investigated by quantitative immunoelectron microscopy. By BSA-gold internalization kinetics, four distinct endosomal subcompartments were distinguished: primary endocytic vesicles, EEs, late endosomes, and lysosomes. As in other cells, EEs consisted of vacuolar and tubulovesicular subdomains. The SLMV marker proteins synaptophysin and vesicle-associated membrane protein 2 (VAMP-2) localized to both the EE vacuoles and associated tubulovesicles. Quantitative analysis showed that the transferrin receptor and SLMV proteins colocalized to a significantly higher degree in primary endocytic vesicles then in EE-associated tubulovesicles. By incubating PC12 cells expressing T antigen-tagged VAMP (VAMP-TAg) with antibodies against the luminal TAg, the recycling pathway of SLMV proteins was directly visualized. At 15°C, internalized VAMP-TAg accumulated in the vacuolar domain of EEs. Upon rewarming to 37°C, the labeling shifted to the tubular part of EEs and to newly formed SLMVs. Our data delineate a pathway in which SLMV proteins together with transferrin receptor are delivered to EEs, where they are sorted into SLMVs and recycling vesicles, respectively.

Generadores ScalaCheck para property-based testing de programas Spark y Spark Streaming

En los últimos años hemos sido testigos de la expansión del paradigma big data a una velocidad vertiginosa. Los cambios en este campo, nos permiten ampliar las áreas a tratar; lo que a su vez implica una mayor complejidad de los sistemas software asociados a estas tareas, como sucede en sistemas de monitorización o en el Internet de las Cosas (Internet of Things). Asimismo, la necesidad de implementar programas cada vez robustos y eficientes, es decir, que permitan el cómputo de datos a mayor velocidad y de los se obtengan información relevante, ahorrando costes y tiempo, ha propiciado la necesidad cada vez mayor de herramientas que permitan evaluar estos programas. En este contexto, el presente proyecto se centra en extender la herramienta sscheck. Sscheck permite la generación de casos de prueba basados en propiedades de programas escritos en Spark y Spark Streaming. Estos lenguajes forman parte de un mismo marco de código abierto para la computación distribuida en clúster. Dado que las pruebas basadas en propiedades generan datos aleatorios, es difícil reproducir los problemas encontrados en una cierta sesion; por ello, la extensión se centrará en cargar y guardar casos de test en disco mediante el muestreo de datos desde colecciones mayores.

Now Streaming: A Consortial PDA Video Pilot Project

In 2014, eight academic libraries in the state of New York collaborated on a group patron driven acquisition (PDA) pilot program with Kanopy, a video streaming service for libraries. The institutions, despite vast differences in size and profile, each launched Kanopy’s streaming solution on their campuses under a program where they would jointly contribute to and acquire films based on group usage. The pilot ran for seven months and led to some fascinating insights into the differences in demand for film across campuses, the possibility of PDA as a model for library acquisition, and the feasibility of a group approach to acquisition. This paper presents the background to, results of, and reflections on the pilot program from the three unique perspectives of the consortium, the vendor, and one of the libraries involved, providing a holistic view of the success of the pilot and the lessons learned.

Detecting implicit expressions of affect in text using EmotiNet and its extensions

In the past years, an important volume of research in Natural Language Processing has concentrated on the development of automatic systems to deal with affect in text. The different approaches considered dealt mostly with explicit expressions of emotion, at word level. Nevertheless, expressions of emotion are often implicit, inferrable from situations that have an affective meaning. Dealing with this phenomenon requires automatic systems to have “knowledge” on the situation, and the concepts it describes and their interaction, to be able to “judge” it, in the same manner as a person would. This necessity motivated us to develop the EmotiNet knowledge base — a resource for the detection of emotion from text based on commonsense knowledge on concepts, their interaction and their affective consequence. In this article, we briefly present the process undergone to build EmotiNet and subsequently propose methods to extend the knowledge it contains. We further on analyse the performance of implicit affect detection using this resource. We compare the results obtained with EmotiNet to the use of alternative methods for affect detection. Following the evaluations, we conclude that the structure and content of EmotiNet are appropriate to address the automatic treatment of implicitly expressed affect, that the knowledge it contains can be easily extended and that overall, methods employing EmotiNet obtain better results than traditional emotion detection approaches.

A Cloud-based Framework for Security Analysis of Browser Extensions

In today's internet world, web browsers are an integral part of our day-to-day activities. Therefore, web browser security is a serious concern for all of us. Browsers can be breached in different ways. Because of the over privileged access, extensions are responsible for many security issues. Browser vendors try to keep safe extensions in their official extension galleries. However, their security control measures are not always effective and adequate. The distribution of unsafe extensions through different social engineering techniques is also a very common practice. Therefore, before installation, users should thoroughly analyze the security of browser extensions. Extensions are not only available for desktop browsers, but many mobile browsers, for example, Firefox for Android and UC browser for Android, are also furnished with extension features. Mobile devices have various resource constraints in terms of computational capabilities, power, network bandwidth, etc. Hence, conventional extension security analysis techniques cannot be efficiently used by end users to examine mobile browser extension security issues. To overcome the inadequacies of the existing approaches, we propose CLOUBEX, a CLOUd-based security analysis framework for both desktop and mobile Browser EXtensions. This framework uses a client-server architecture model. In this framework, compute-intensive security analysis tasks are generally executed in a high-speed computing server hosted in a cloud environment. CLOUBEX is also enriched with a number of essential features, such as client-side analysis, requirements-driven analysis, high performance, and dynamic decision making. At present, the Firefox extension ecosystem is most susceptible to different security attacks. Hence, the framework is implemented for the security analysis of the Firefox desktop and Firefox for Android mobile browser extensions. A static taint analysis is used to identify malicious information flows in the Firefox extensions. In CLOUBEX, there are three analysis modes. A dynamic decision making algorithm assists us to select the best option based on some important parameters, such as the processing speed of a client device and network connection speed. Using the best analysis mode, performance and power consumption are improved significantly. In the future, this framework can be leveraged for the security analysis of other desktop and mobile browser extensions, too.