Demóstenes Zegarra Rodríguez

The impact of video-quality-level switching on user quality of experience in dynamic adaptive streaming over HTTP

Dynamic adaptive streaming over HTTP (DASH) has become a promising solution for video delivery services over the Internet in the last few years. Currently, several video content providers use the DASH solution to improve the users’ quality of experience (QoE) by automatically switching video quality levels (VQLs) according to the network status. However, the frequency of switching events between different VQLs during a video streaming session may disturb the user’s visual attention and therefore affect the user’s QoE. As one of the first attempts to characterize the impact of VQL switching on the user’s QoE, we carried out a series of subjective tests, which show that there is a correlation between the user QoE and the frequency, type, and temporal location of the switching events. We propose a novel parameter named switching degradation factor (SDF) to capture such correlation. A DASH algorithm with SDF parameter is compared with the same algorithm without SDF. The results demonstrate that the SDF parameter significantly improves the user’s QoE, especially when network conditions vary frequently.

Video Quality Assessments on Digital TV and Video Streaming services using Objective Metrics

There is a wide range of telecommunications services that transmit voice, video and data through complex transmission networks and in some cases, the service has not an acceptable quality level for the end user. In this sense the study of methods for assessing video quality and voice have a very important role. This paper presents a classification scheme, based on different criteria, of the methods and metrics that are being studied in recent years. This paper presents how the video quality is affected by degradation in the transmission channel in two kinds of services: Digital TV (ISDB-TB) due the fading in the air interface and video streaming service on an IP network due packet loss. For Digital TV tests was set up a scenario where the digital TV transmitter is connected to an RF channel emulator, where are inserted different fading models and at the end, the videos are saved in a mobile device. The tests of streaming video were performed in an isolated scenario of IP network, which are scheduled several network conditions, resulting in different qualities of video reception. The video quality assessment is performed using objective assessment methods: PSNR, SSIM and VQM. The results show how the losses in the transmission channel affects the quality of end-user experience on both services studied.

Age Groups Classification in Social Network Using Deep Learning

Social networks have a large amount of data available, but often, people do not provide some of their personal data, such as age, gender, and other demographics. Although the sentiment analysis uses such data to develop useful applications in people’s daily lives, there are still failures in this type of analysis, either by the restricted number of words contained in the word dictionaries or because they do not consider the most diverse parameters that can influence the sentiments in a sentence; thus, more reliable results can be obtained, if the users profile information and their writing characteristics are considered. This research suggests that one of the most relevant parameter contained in the user profile is the age group, showing that there are typical behaviors among users of the same age group, specifically, when these users write about the same topic. A detailed analysis with 7000 sentences was performed to determine which characteristics are relevant, such as, the use of punctuation, number of characters, media sharing, topics, among others; and which ones can be disregarded for the age groups classification. Different learning machine algorithms are tested for the classification of the teenager and adult age group, and the deep convolutional neural network had the best performance, reaching a precision of 0.95 in the validation tests. Furthermore, in order to validate the usefulness of the proposed model for classifying age groups, it is implemented into the enhanced sentiment metric (eSM). In the performance validation, subjective tests are performed and the eSM with the proposed model reached a root mean square error and a Pearson correlation coefficient of 0.25 and 0.94, respectively, outperforming the eSM metric, when the age group information is not available.

Recommendation system using sentiment analysis considering the polarity of the adverb

This paper presents a recommendation system based on sentiment analysis of sentences extracted from Social Networks considering an algorithm which depends on the adverb found in the sentence. Furthermore, the recommendation system has a low complexity, therefore the perceived impacts on the analysis of energy consumption on electronic devices is almost negligible.

Monitoring system for potential users with depression using sentiment analysis

This paper presents a monitoring solution for users with potential psychological disturbs, specifically stress. The phrases extracted from Social Networks are filtered by mood and scored using a sentiment-analysis-metric that considers personal characteristics, such as gender and age. The solution informs, to authorized persons, the emotional changes of the users.

Performance assessment of High Efficiency Video Coding - HEVC

The main goal of this paper is to evaluate the performance of the proposed new video coding standard, the High Efficiency Video Coding (HEVC), also known as H.265. This evaluation considers mainly a comparison with the baseline profile of H.264/AVC encoder in terms of: compression efficiency, the video quality achieved by decoding the video signal at the receiver, and the computational complexity of encoding and decoding algorithms. As material test are used different spatial resolutions of video and also videos with different temporal and spatial information parameters. For video quality assessment are used two objective metrics, PSNR and SSIM. Furthermore, a transcoding H.264/HEVC scenario is evaluated considering the cascade method, which is very important for the first service applications that will use HEVC. The results indicate that compressed video file sizes using HEVC is 40-52% in relation with H.264 depending of the video content type without any significant video quality degradation at the receiver.

Voice quality assessment in mobile devices considering different fading models

This paper presents a mechanism to provide a real-time assessment of voice quality on mobile handled devices. This solution considers the voice degradations caused by the radio frequency channel and packet losses on the IP network. Furthermore, the network architecture of the proposed solution is introduced and the application is implemented on the user mobile device.

Real-time evaluation of speech quality in mobile communication services

This paper presents a mechanism to provide a real-time evaluation of speech quality. This solution consists of a voice-quality-server (VQS) based on the ITU-T P.563 algorithm with modifications to treat natural silences of human speech and packet losses on the network. Furthermore, an application is implemented on the user device.

Improving a Video Quality Metric with the Video Content Type parameter

Nowadays, there are several multimedia services, which are carried via IP networks. From these services; the traffic regarding video applications had the greatest growth in the last years. In this context, the study of methods for assessing video quality plays a very important role. In general, video quality metrics are defined from mathematical models, which use as inputs, different network or application layer parameters, and the video quality assessment results from subjective tests. This paper aims to demonstrate that the video quality metric performance can be improved by adding a parameter regarding the video content type. In order to perform video quality assessment tests in a short time period, the so-called crowdsourcing methodology is used. In this methodology remote users assess the video quality. The experimental results show that the Video streaming Quality Metric (VsQM) performance is improved when the video content type is considered (eVsQM). Indeed, the Pearson correlation factors between eVsQM and crowdsourcing results reach 0.94 ¿ 0.98, depending on the video degradation scenario.

Recommendation system based on user profile extracted from an IMS network with emphasis on social network and digital TV

This paper introduces new network architecture capable of providing a flexible and configurable Recommendation System in which network operator, subscribers and content providers could interact to each other by message exchanging. This solution considers multiple inputs provided by the user and context-based information of IP Multimedia Subsystem (IMS) network. It creates a specific subscriber profile based on information from cellular and fixed networks, digital TV and, internet services as social networks or e-mail accounts. Also, for collecting information is used a Cell Broadcast platform which can send messages to a specific geographic location achieving users with high probability of similar preferences. User feedback is collected to evaluate the utility of recommendation messages. As additional features, the Recommendation System uses presence and location information as a decision factor to send or not the recommendation messages.