Video Communication Applications Research Articles

Implementing Distance Learning during COVID-19 in Morocco: Pedagogical Gains, Challenges, and Leaners’ Attitudes

Due to the outbreak of the COVID-19 pandemic, teachers and students in Morocco and elsewhere were forced to move from face-to-face instruction to distance learning. Consequently, a plethora of online platforms, including Google Classroom, Google Meet, Microsoft Teams, WhatsApp, and video communication applications, were used as instructional tools. In light of this, the current study investigates the pedagogical gains of implementing distance learning via Microsoft Teams during the COVID-19 pandemic and the challenges participants encountered. It also probes English as a Foreign Language (EFL) learners’ attitudes toward the effectiveness of this mode of instruction. The study population was 28 secondary school students who taught English courses distantly for eight weeks. A post-questionnaire was used to collect quantitative data. The findings revealed that most participants identified two pedagogical benefits: the ability to learn at home and flexible learning time. As for the challenges, most participants admitted having no or poor network signal, no connectivity in their devices, technical problems related to Microsoft Teams, reduced interaction with their teachers and peers, and poor learning. Besides, the analysis of the 5-point Likert scale survey indicated that while participants were somehow motivated to attend distance learning English courses, they expressed discomfort, they considered face-to-face learning to be more effective than distance learning, and thus they were unsatisfied with the experience and had no intentions of future use. As a result, the study participants displayed negative attitudes toward the implementation of distance learning

Online Learning, Offline Performance: Evidence from Moroccan High School Students during the COVID-19 Pandemic

The outbreak of COVID-19 has made a substantial positive impact in educational settings, urging teachers to use innovative online ways of teaching and making numerous online platforms, including Microsoft Teams, Google Meet, Google Classroom, video communication applications, and many other tools accessible for students. However, the online learning setting has spawned a variety of challenges for both learners and teachers, ranging from technical problems to poor training. As a matter of fact, learners, educators, and practitioners have different attitudes toward the effectiveness of online learning. Considering this, this study investigates the impact of implementing online learning on students' grammar performance in Morocco. It does so by assessing the control and experimental groups' performance during five-week experimentation. The study population was 11th-grade secondary school students in Tazizaoute High School, El Kbab, Khenifra, Benni-Mellal-Khenifra Region. The participants were randomly and equally assigned to the control group (N=30), taught through face-to-face learning, and the experimental group (N=30), taught using online learning via Microsoft Teams. To collect quantitative data, grammar pre- and post-tests were employed to measure the grammar performance in both groups before and after the treatment. Both descriptive and inferential statistics (Independent T-Test) using SPSS-26 were used to analyse the data. The findings revealed a statistically significant difference between the two groups favouring the control group.

Even symmetric chaotic and skewed maps as a technique in video encryption

The massive growth and use of digital multimedia through computer networks, including video and images, have increased the demand for protecting this digital data. To secure digital video, video encryption is frequently utilized. In this paper, a brand-new video scrambling technique based on two chaotic linearly symmetric maps and one chaotic tent map that has been twisted is suggested. The permutation procedure moves every frame pixel's position using a P-box created by permuting a linearly symmetric chaotic sequence. The diffusion technique employs both linearly symmetric chaos maps and distorted tent maps to create key streams. The keystream closely resembles simple frames because the pixels in the permuted frame indicate which of the two even symmetric chaos maps is replicated each time for the following byte. The information entropy, histogram, neighboring pixel correlation and sensitivity analysis, number of pixels changing regions (NPCR), and unified mean change intensity are used to thoroughly evaluate the recommended method's capacity to improve performance and security (UACI). Comparatively to other methods, the suggested algorithm is resistant to clipping, salt and pepper noise, speckle noise rotation assaults, and clipping. This positive outcome indicates that the plan can be successfully implemented for secure video communication applications.

Decision Making Near End of Life: A Qualitative Exploration of the Lived Experiences of Jordanian Healthcare Providers.

Discussions related to a patient's prognosis and interventions near end of life are challenging and stressful for healthcare providers. Many reported experiencing emotional distress and discomfort during the decision-making process. The aim of this study was to describe the lived experience of nurses and physicians who participate in decision making near the end of a patient's life. A descriptive, phenomenological approach was used with a purposive sample of 7 nurses and 6 physicians from 2 palliative and end-of-life care institutions in Jordan. Data derived from focus group discussions conducted online via the ZOOM video communication application, and analysis followed Colaizzi's qualitative methodology. Three major themes emerged from the healthcare providers' experiences. Initially, the participants described how they "strive toward optimal decision-making near end of life," "the overwhelming experience of decision making near end of life," and finally, their struggle in sharing details about the end of life when patients ask and whether to tell or not to tell them as "the time for hard talk." The healthcare providers' experiences revealed several issues of decision making near a patient's end of life, such as a lack of appropriate training and administrative support, emotional distress, fear of legal liability, and the burden of a hard talk with patients. These findings necessitate institutional support of setting appropriate policies and guidelines, staff counseling, and healthcare provider support. Institutions providing palliative and end-of-life care can use this study's findings to support their staff by setting appropriate practice guidelines and providing staff training and counseling.

Fighting a Battle Alone: Experiences of COVID-19 Survivors of Mandatory Isolation

This study determined the experiences of the COVID-19 survivors during their mandatory isolation. Descriptive phenomenology is the research design used in the study. Snowball sampling was utilized to determine the 24 participants of the study. The data was gathered through an online semi-structured interview conducted via Google Meet and Zoom, two video communication applications. Thematic analysis was utilized to develop themes based on the responses from the COVID-19 survivors who served as participants. The study generated four themes with twelve sub-themes. The study revealed that mental health impacts how the participants perceive, feel, behave, and perform, as well as how they plan, handle stress, and interact with others. The participants' mental health has been compromised because of the mandatory isolation, and they expressed a wide range of psychological emotions, including stress, fear, anxiety, and loneliness, that may impact their mental health. Daily communication and entertainment, an optimistic mindset, and praying regularly are the coping mechanisms identified in the study. Coping mechanisms were developed to determine the activities made by the participants to mitigate the impact of mandatory isolation on their mental health. Furthermore, the study also recommends that future researchers must explore the mental health of a larger group of isolated individuals.

A hybrid chaotic map for communication security applications

SummaryRecently, the synchronization between two matching chaotic systems to provide confident communication has gained a lot of interest. Continuously, there is a necessity to produce a novel dynamical system to be used in synchronization to implement a strong security system. In this paper, a hybrid chaotic system is suggested and verified for the potential use of secure communication through chaos synchronization. The Lyapunov exponent (LE) and zero‐one (0‐1) tests have been used to verify the performance of the suggested hybrid chaotic system, while National Institute of Standard and Technology (NIST) tests have been applied to verify the randomness properties. And the synchronization has been achieved between master and slave systems by using nonlinear control laws. The simulation outcomes demonstration that the hybrid system has chaotic performance and outstanding randomness characteristic. The statistical results gained for LE test was 0.8822, and for frequency test (FT) was 0.2028, while for the run test (RT) was 0.1924. Accordingly, the suggested hybrid system can be used to evolve functional synchronization algorithms and encryption for image, video, and voice secure communication applications.

Design of Low-Power Non-Binary LDPC Decoder Exploiting DRAM Refresh Rate Over-Scaling

This brief presents a low-power non-binary low density parity-check decoder design exploiting domain specific information for high-throughput wireless video communication applications. The proposed technique can dynamically scale the refresh rate of DRAM according to channel conditions as well as decoding states, hence to greatly reduce the DRAM power as well as the decoder power with lower refresh overhead. Evaluation results show that the proposed technique can achieve significant decoder power saving than conventional techniques.

Highly Accurate Image Reconstruction for Multimodal Noise Suppression Using Semisupervised Learning on Big Data

Impulse noise corruption in digital images frequently occurs because of errors generated by noisy sensors or communication channels, such as faulty memory locations in devices, malfunctioning pixels within a camera, or bit errors in transmission. Although recently developed big data streaming enhances the viability of video communication, visual distortions in images caused by impulse noise corruption can negatively affect video communication applications. In addition, ${{sparsity}}$ , ${{density}}$ , and ${{multimodality}}$ in large volumes of noisy images have often been ignored in recent studies, whereas these issues have become important because of the increasing viability of video communication services. To effectively eliminate the visual effects generated by the impulse noise from the corrupted images, this study proposes a novel model that uses a devised cost function involving semisupervised learning based on a large amount of corrupted image data with a few labeled training samples. The proposed model qualitatively and quantitatively outperforms the existing state-of-the-art image reconstruction models in terms of the denoising effect.

Novel PID-Fuzzy Video Rate Controller for High-Delay Applications of the HEVC Standard

The new High Efficiency Video Coding (HEVC) standard is targeted for high-resolution video contents that are suitable for many high-delay video communications applications, such as video streaming. A few-rate control algorithms (RCAs) have been proposed for the HEVC in the literature. Almost all state-of-the-art RCAs proposed for the HEVC are optimized for constant bit rate low-delay applications. In order to reach a higher visual quality in high-delay applications, such as video streaming, a proportional integral derivative (PID)-fuzzy RCA with the buffering constraint is proposed for the HEVC in this paper. The proposed RCA is designed to minimize fluctuations of quantization parameter (QP) while the buffering constraints are fully obeyed. Unlike conventional fuzzy-PID algorithms that use a PID controller for control and a fuzzy system for tuning the PID parameters, the proposed algorithm uses a fuzzy controller with proportional, integral, and derivative inputs. A base QP is calculated for each group of picture (GOP) by the PID-fuzzy controller and determined QP offsets are added to the base QP to obtain the QP of frames at different temporal layers in the GOP. Experimental results indicate that high rate-distortion performance, fulfilled buffering constraint, and the high visual quality of compressed video are gained simultaneously by the proposed algorithm with low computational complexity.

Low Complexity HEVC INTRA Coding for High-Quality Mobile Video Communication

INTRA video coding is essential for high quality mobile video communication and industrial video applications since it enhances video quality, prevents error propagation, and facilitates random access. The latest high-efficiency video coding (HEVC) standard has adopted flexible quad-tree-based block structure and complex angular INTRA prediction to improve the coding efficiency. However, these technologies increase the coding complexity significantly, which consumes large hardware resources, computing time and power cost, and is an obstacle for real-time video applications. To reduce the coding complexity and save power cost, we propose a fast INTRA coding unit (CU) depth decision method based on statistical modeling and correlation analyses. First, we analyze the spatial CU depth correlation with different textures and present effective strategies to predict the most probable depth range based on the spatial correlation among CUs. Since the spatial correlation may fail for image boundary and transitional areas between textural and smooth areas, we then present a statistical model-based CU decision approach in which adaptive early termination thresholds are determined and updated based on the rate-distortion (RD) cost distribution, video content, and quantization parameters (QPs). Experimental results show that the proposed method can reduce the complexity by about 56.76% and 55.61% on average for various sequences and configurations; meanwhile, the RD degradation is negligible.

Video quality assessment using content-weighted spatial and temporal pooling method

Video quality assessment plays an important role in video processing and communication applications. We propose a full reference video quality metric by combining a content-weighted spatial pooling strategy with a temporal pooling strategy. All pixels in a frame are classified into edge, texture, and smooth regions, and their structural similarity image index (SSIM) maps are divided into increasing and saturated regions by the curve of their SSIM values, then a content weight method is applied to increasing regions to get the score of an image frame. Finally, a temporal pooling method is used to get the overall video quality. Experimental results on the LIVE and IVP video quality databases show our proposed method works well in matching subjective scores.

Delay-Rate-Distortion Model for Real-Time Video Communication

With the increased use of smart phones and mobile tablets, video encoding and streaming over wireless networks become a big concern. Real-time video service requires low end-to-end delay, which mainly consists of video encoding delay, queuing delay, and transmission delay. Previous works either assume video encoding delay to be constant or infinite and neglect it from end-to-end delay. However, encoding time has an effective impact on encoding rate ( $R$ ) and distortion ( $D$ ). Hence, the optimal R-D performance based on the assumption of infinite encoding time is neither accurate nor realistic. To achieve the optimal end-to-end performance under low delay constraint, we extend the traditional R-D model to a novel delay-rate-distortion (d-R-D) model, which quantifies the relationship among source coding time, rate, and distortion for IPPPP coding mode in H.264/Advanced Video Coding (AVC). On the other hand, a delay insensitive video communication application can afford hierarchical bidirectional prediction mode that introduces extra encoding delay than IPPPP mode in H.264/AVC, as it achieves higher encoding efficiency when delay is not a top priority. However, coding efficiency does not always increase with delay, and delay is not unlimited as well. How to maximize coding efficiency in hierarchical B mode with limited encoding time constraint is not a well-addressed problem. With the proposed d-R-D model, we can mathematically formulate this problem and provide a practical solution for the first time.

Subjective and objective quality assessment of videos in error-prone network environments

Compression and transmission are two fundamental stages involved in wireless video communications, each of which may cause degradation of the quality of experience (QoE) of end users by producing compression artifacts and packet loss artifacts, respectively. They have their own unique perceptual influences. To provide insight for designing QoE-aware content delivery applications, this paper studies subjective and objective quality of videos containing both types of artifacts. First, subjective quality assessment is conducted, from which interaction between the two types of artifacts during quality perception is investigated. Second, using the subjective data, the performance of the state-of-the-art objective quality metrics is evaluated, with the aim of examining suitability of the existing metrics for their use in error-prone video communication applications. Finally, the developed data set is made publicly available for the community.

A Novel Image Encryption Scheme Based on Multi-orbit Hybrid of Discrete Dynamical System

A multi-orbit hybrid image encryption scheme based on discrete chaotic dynamical systems is proposed. One generalized Arnold map is adopted to generate three orbits for three initial conditions. Another chaotic dynamical system, tent map, is applied to generate one pseudo-random sequence to determine the hybrid orbit points from which one of the three orbits of generalized Arnold map. The hybrid orbit sequence is then utilized to shuffle the pixels' positions of plain-image so as to get one permuted image. To enhance the encryption security, two rounds of pixel gray values' diffusion is employed as well. The proposed encryption scheme is simple and easy to manipulate. The security and performance of the proposed image encryption have been analyzed, including histograms, correlation coefficients, information entropy, key sensitivity analysis, key space analysis, differential analysis, etc. All the experimental results suggest that the proposed image encryption scheme is robust and secure and can be used for secure image and video communication applications. Index Terms—Chaotic dynamical system, generalized Arnold map, tent map, shuffling, diffusion

A Chaos-based Pseudorandom Permutation and Bilateral Diffusion Scheme for Image Encryption

A great many chaos-based image encryption schemes have been proposed in the past decades. Most of them use the permutation-diffusion architecture in pixel level, which has been proved insecure enough as they are not dependent on plain-images and so cannot resist chosen/known plain-image attack usually. In this paper, we propose a novel image encryption scheme comprising of one permutation process and one diffusion process. In the permutation process, the image sized M N  is expanded to one sized 2 M N  by dividing the plainimage into two parts: one consisting of the higher 4bits and one consisting of the lower 4bits. The permutation operations are done row-by-row and column-by-column to increase the speed of permutation process. The chaotic cat map is utilized to generate chaotic sequences, which are quantized to shuffle the expanded image. The chaotic sequence for permutation process is dependent on plainimage and cipher keys, resulting in good key sensitivity and plain-image sensitivity. To achieve more avalanche effect and larger key space, a chaotic Bernoulli shift map based bilateral (i.e., horizontal and vertical) diffusion function is applied as well. The security and performance of the proposed image encryption have been analyzed, including histograms, correlation coefficients, information entropy, key sensitivity analysis, key space analysis, differential analysis, encryption rate analysis etc. All the experimental results suggest that the proposed image encryption scheme is robust and secure and can be used for secure image and video communication applications.

An Image Encryption Scheme Based on Generalized Arnold Map and Chinese Remainder Theorem

A novel image encryption scheme comprising of one permutation process and one diffusion process is proposed. In the permutation process, the image sized is expanded to one sized by dividing the plain-image into two parts: one consisting of the higher 4bits and one consisting of the lower 4bits. The permutation operations are done row-by-row and column-by-column to increase the speed. The chaotic generalized Arnold map is utilized to generate chaotic sequence, which is quantized to shuffle the expanded image. The chaotic sequence for permutation process is dependent on plain-image and cipher keys, resulting in good key sensitivity and plain-image sensitivity. To achieve more avalanche effect and larger key space, Chinese Remainder Theorem is applied to diffuse the shuffled image. The key sensitivity and key space of the proposed image encryption have been analyzed as well. The experimental results suggest that the proposed image encryption scheme can be used for secure image and video communication applications.

A Secure and Efficient Image Encryption Scheme Based on Tent Map and Permutation-substitution Architecture

A secure image encryption scheme based on 2D skew tent map is proposed for the encryption of color images. The proposed encryption scheme is composed of one permutation process and one substitution process. The 3D color plain-image matrix is converted to 2D image matrix first, then 2D skew tent map is utilized to generate chaotic sequences, which are used for both permutation process and substitution process. The chaotic sequence for permutation process is dependent on plain- image and cipher keys, resulting in good key sensitivity and plaintext sensitivity. The substitution process is first initiated with the initial vectors generated by the cipher keys and 2D skew tent map, then the gray values of row and column pixels of 2D image matrix are mixed with the pseudorandom number sequences via bitxoring operation. Both permutation process and substitution process are executed row-by-row and column-by-column instead of pixel-by-pixel to improve the speed of encryption. The security and performance of the proposed image encryption have been analyzed, including histograms, correlation coefficients, information entropy, key sensitivity analysis, key space analysis, differential analysis, encryption/decryption rate analysis etc. All the experimental results suggest that the proposed image encryption scheme is robust and secure and can be used for secure image and video communication applications. Index Terms—Chaotic system, skew tent map, image encryption, permutation-substitution architecture

Evaluation on Multiple Video Streaming in IEEE 802.11e Multihop Networks

In the last decade, both customers and researchers paid attention to wireless video communications applications because they contain abundant and visual information. However, characteristics of wireless networks such as limited resource and fluctuated link quality degrade video transmission quality. In this paper, multiple video streaming in IEEE 802.11e multihop networks is evaluated under different conditions to find out how to design an adaptive cross-layer video transmission scheme for multi-stream transmission. On one hand, we compare the performances of multipath routing and single path routing. On the other hand, EDCA and its two modifications are evaluated to verify their flexibility. Evaluation results show that the performance of multi-stream video transmission depends on many factors, including data rates and coding structures of video sequences, traffic assignment mechanism, data rates of background data streams, etc.

Full-Reference Video Quality Assessment by Decoupling Detail Losses and Additive Impairments

Video quality assessment plays a fundamental role in video processing and communication applications. In this paper, we study the use of motion information and temporal human visual system (HVS) characteristics for objective video quality assessment. In our previous work, two types of spatial distortions, i.e., detail losses and additive impairments, are decoupled and evaluated separately for spatial quality assessment. The detail losses refer to the loss of useful visual information that will affect the content visibility, and the additive impairments represent the redundant visual information in the test image, such as the blocking or ringing artifacts caused by data compression and so on. In this paper, a novel full-reference video quality metric is developed, which conceptually comprises the following processing steps: 1) decoupling detail losses and additive impairments within each frame for spatial distortion measure; 2) analyzing the video motion and using the HVS characteristics to simulate the human perception of the spatial distortions; and 3) taking into account cognitive human behaviors to integrate frame-level quality scores into sequence-level quality score. Distinguished from most studies in the literature, the proposed method comprehensively investigates the use of motion information in the simulation of HVS processing, e.g., to model the eye movement, to predict the spatio-temporal HVS contrast sensitivity, to implement the temporal masking effect, and so on. Furthermore, we also prove the effectiveness of decoupling detail losses and additive impairments for video quality assessment. The proposed method is tested on two subjective quality video databases, LIVE and IVP, and demonstrates the state-of-the-art performance in matching subjective ratings.

A Chaotic Block Cipher for Real-Time Multimedia

Problem statement: The widespread use of image, audio and video data makes media content protection increasingly necessary and important. We propose a naive approach which treats the multimedia signal to be protected as a text and use proposed encryption design to encrypt the whole data stream. Upon reception, the entire cipher text data stream would be decrypted and playback can be performed at the client end with an initial time delay. Approach: We introduce a block cipher algorithm, which encrypts and decrypts a block size of 512 bits regardless of the file format. In this, a permutation algorithm using a chaotic system is employed to provide the shuffler function. A shuffler operator is defined using the shuffler function. A random key generator generates key sequences and the scheme employs key-dependant transformations based on distance in the shuffling operator. The process of encryption/decryption is governed by the shuffler function, shuffler operator and the pseudorandom key. Results: The basic operation used is logical XOR and so the algorithm has a very high encryption/decryption speed. The execution time shows the proposed scheme is faster than the existing cryptographic schemes. Conclusion: The proposal of the algorithm is to manage the tradeoffs between the speed and security and hence appropriate for real-time image and video communication applications.