Coding Method Research Articles

Phase-only hologram video compression using a deep neural network for up-scaling and restoration.

This paper proposes a coding method for compressing a phase-only hologram video (PoHV), which can be directly displayed in a commercial phase-only spatial light modulator. Recently, there has been active research to use a standard codec as an anchor to develop a new video coding for 3D data such as MPEG point cloud compression. The main merit of this approach is that if a new video codec is developed, the performance of relative coding methods can be increased simultaneously. Furthermore, compatibility is increased by the capability to use various anchor codecs, and the developing time is decreased. This paper uses a currently used video codec as an anchor codec and develops a coding method including progressive scaling and a deep neural network to overcome low temporal correlation between frames of a PoHV. Since it is difficult to temporally predict a correlation between frames of a PoHV, this paper adopts a scaling function and a neural network in the encoding and decoding process, not adding complexity to an anchor itself to predict temporal correlation. The proposed coding method shows an enhanced coding gain of an average of 22%, compared with an anchor in all coding conditions. When observing numerical and optical reconstructions, the result images by the proposed show clearer objects and less juddering than the result by the anchor.

Machine learning (ML) based models for predicting the ultimate strength of rectangular concrete-filled steel tube (CFST) columns under eccentric loading

Concrete-filled steel tubes (CFSTs) are popularly used in structural applications. The accurate prediction of their ultimate strength is a key for the safety of the structure. Extensive studies have been conducted on the strength prediction of CFSTs under concentric loading. However, in real situation CFSTs are usually subjected to eccentric loading. The combined compression and bending will result in more complex failure mechanisms at the ultimate strength. The accuracy of methods in design codes is usually limited due to their simplicity. In this study, three machine learning (ML) methods, namely, Support Vector Regression (SVR), Random Forest Regression (RFR), and Neural Networks (NN), are adopted to develop models to predict the ultimate strength of CFSTs under eccentric loading. A database consisting of information of 403 experimental tests from literature is created and statistically analyzed. The database was then split to a training set which was used to optimize and train the ML models, and a test set which was used to evaluate performance of trained ML models. Compared with the methods in two typical design codes, the ML models achieved notable improvement in prediction accuracy. The parametric study revealed that the trained ML models could generally capture the effect of each primary input feature, which was verified by the relevant experimental test results.

Intra Prediction Method for Depth Video Coding by Block Clustering through Deep Learning

In this paper, we propose an intra-picture prediction method for depth video by a block clustering through a neural network. The proposed method solves a problem that the block that has two or more clusters drops the prediction performance of the intra prediction for depth video. The proposed neural network consists of both a spatial feature prediction network and a clustering network. The spatial feature prediction network utilizes spatial features in vertical and horizontal directions. The network contains a 1D CNN layer and a fully connected layer. The 1D CNN layer extracts the spatial features for a vertical direction and a horizontal direction from a top block and a left block of the reference pixels, respectively. 1D CNN is designed to handle time-series data, but it can also be applied to find the spatial features by regarding a pixel order in a certain direction as a timestamp. The fully connected layer predicts the spatial features of the block to be coded through the extracted features. The clustering network finds clusters from the spatial features which are the outputs of the spatial feature prediction network. The network consists of 4 CNN layers. The first 3 CNN layers combine two spatial features in the vertical and horizontal directions. The last layer outputs the probabilities that pixels belong to the clusters. The pixels of the block are predicted by the representative values of the clusters that are the average of the reference pixels belonging to the clusters. For the intra prediction for various block sizes, the block is scaled to the size of the network input. The prediction result through the proposed network is scaled back to the original size. In network training, the mean square error is used as a loss function between the original block and the predicted block. A penalty for output values far from both ends is introduced to the loss function for clear network clustering. In the simulation results, the bit rate is saved by up to 12.45% under the same distortion condition compared with the latest video coding standard.

Applying state space grids methods to characterize counsellor-client interactions in a physical activity behavioural intervention for adults with disabilities

BackgroundPhysical activity (PA) counselling research has mainly focused on identifying which behaviour change techniques (BCTs) are delivered by a counsellor. Less is known about how BCTs are received by clients. State Space Grids (SSGs) is a dynamic system method that can be used to study counsellor-client interactions by examining frequencies, durations and sequences of BCT delivery and receipt. In this methods paper, we show how SSG methods can be pragmatically used to characterize counsellor-client interactions during a PA behavioural support intervention for adults with disabilities. MethodsMethods were demonstrated through a secondary analysis of data from adults with spinal cord injury (age: 45.79 ± 13.63; females: n = 5; males: n = 9) who received PA counselling. Transcripts of 30 audio-recorded counselling sessions (total duration: ∼8.3 h) were double-coded for BCT delivery and receipt statements using a reliable coding method (>84% agreement) and analyzed in two different ways using SSGs methods. ResultsApplying the SSG analyses to our data demonstrated that frequencies, durations, and sequences of BCT delivery and receipt varied largely within and between dyads. Across all sessions, the counsellor and client spent on average 32–34% of their time on talking about BCTs related to goals and planning, ∼29% of their time talking about other BCTs (e.g., self-belief, support strategies), and the remaining 27–29% of their time talking about other topics (not BCT-specific). ConclusionThis paper showed how dynamic system methods can be pragmatically used to characterize counsellor-client interactions and illustrate the variability of how BCTs are delivered by a counsellor and received by clients in a PA behavioural support intervention. We demonstrated that SSGs methods can facilitate the examination of frequencies, durations and sequences of BCT delivery and receipt can help advance our understanding of PA behavioural support for adults with and without disabilities.

COMPARATIVE STUDIES OF METHODS FOR IMPROVING THE CYBER SECURITY OF UNMANNED AERIAL VEHICLES WITH THE BUILT-IN ADS-B SYSTEM

The subject of study in the article is methods for improving the cybersecurity of unmanned aerial vehicles with an integrated ADS-B system. The aim is to analyze and compare methods for improving the cybersecurity of unmanned aerial vehicles with an embedded ADS-B system. Particular scientific tasks: analysis and comparative studies of the main types of cyber threats and methods for improving the cybersecurity of unmanned aerial vehicles with an integrated ADS-B system, the development of an appropriate taxonomy, and the development of proposals for further research. The methods used in the article are the methods of system analysis. The following research results have been obtained: a classification of cyber threats to the security of unmanned aerial vehicles with an integrated ADS-B system has been developed; a taxonomy of ADS-B message modification and injection attacks has been developed; practical UAV security metrics adapted to the presented taxonomy of cyberattacks are defined and researched ; chosen most priority directions research ; - a generalized classification of cryptographic protection methods adapted to solve the problems of improving the security of UAVs with an integrated ADS-B system has been developed; the use of additional means of identification based on steganographic methods of data protection is proposed. Conclusions. An analysis and comparative studies have been carried out, and a generalized classification of methods for improving the cybersecurity of unmanned aerial vehicles with an integrated ADS-B system has been developed. Their advantages and disadvantages are revealed, which made it possible to determine the priority of further research and possible promising ways to solve the tasks.

Psychiatric nurses' experiences after the closure of Life Esidimeni psychiatric care centres.

A national tragedy occurred between October 2015 and June 2016 when psychiatric patients with profound intellectual disabilities were transferred from psychiatric care centres to non-governmental organisations (NGOs). The process of transferring psychiatric patients had severe consequences for psychiatric patients and psychiatric nurses. The study's objective was to explore and describe psychiatric nurses' experiences after the closure of Life Esidimeni psychiatric care centres. A qualitative, exploratory, descriptive and contextual research design was employed. Semi-structured interviews were utilised to collect data. Purposive sampling was utilised to select eight psychiatric nurses to participate in the study. Data were analysed using Tesch's thematic method of coding. The analysis of data revealed the following themes: With the closure of the care centres participants experienced (1) shock, dismay and life interruption; (2) trauma related to the disintegration, of psychiatric patients' lives, their own families and work-life and (3) sense of resilience. From the findings, it is clear that the psychiatric nurses needed support as evidenced by the challenges they experienced. The healthcare professionals in mental health and mental health nursing post-graduate students could conduct further research focusing on the experiences and the impact that the closure of Life Esidimeni psychiatric care centres have on the psychiatric nurses' mental health.Contribution:This study contributes to the body of knowledge in psychiatric nursing by highlighting the impact of hospital closure on psychiatric nurses.

Lossless Image Steganography Based on Invertible Neural Networks.

Image steganography is a scheme that hides secret information in a cover image without being perceived. Most of the existing steganography methods are more concerned about the visual similarity between the stego image and the cover image, and they ignore the recovery accuracy of secret information. In this paper, the steganography method based on invertible neural networks is proposed, which can generate stego images with high invisibility and security and can achieve lossless recovery for secret information. In addition, this paper introduces a mapping module that can compress information actually embedded to improve the quality of the stego image and its antidetection ability. In order to restore message and prevent loss, the secret information is converted into a binary sequence and then embedded in the cover image through the forward operation of the invertible neural networks. This information will then be recovered from the stego image through the inverse operation of the invertible neural networks. Experimental results show that the proposed method in this paper has achieved competitive results in the visual quality and safety of stego images and achieved 100% accuracy in information extraction.

Analysis of bubble dynamics and thermal destratification induced by gas bubbles in cylindrical liquid storage tanks

• OpenFOAM code is modified to incorporate temperature-dependent transport properties. • A new parameter to estimate the extent of the destratification is introduced. • The destratification index increased by 25.29% as the diameter ratio is increased. • Bubble in square pitch with p/d =4 gives higher effectiveness for thermal destratification. • The destratification index increased by 44.65% as the gravity ratio is increased. Thermal stratification is of great concern for liquid propellant storage tanks of space vehicles. The present study's primary objective is to better understand the bubble dynamics on thermal destratification, quantify the extent of destratification and propose a scheme for destratification. This study investigates the effect of different geometric parameters on the destratification of thermally stratified layers of liquid using the volume of fluid and interface compression method of OpenFOAM CFD code. The OpenFOAM code is modified to incorporate temperature-dependent fluid properties. Different values of bubble diameter, spacing between the bubbles, and arrangement of bubbles in triangular and square fashion with different pitches are considered. The effect of gravitational forces on thermal destratification is also reported. For all these cases, the effectiveness of thermal destratification is quantified in terms of the destratification index ( I d ). The average destratification index ( I davg ) value increased by 25.29% as the ratio of bubble diameter to tank diameter ( d/D ) increased from 0.10 to 0.16. When the pitch to bubble diameter ratio ( p/d ) of triangular and square arrangements is reduced from 8 to 4, the I davg increases by 14.59% and 22.97%, respectively. The average destratification index increased by 44.65% when the g/g e ratio changed from 0.3 to 3. These studies give an overall idea of the sparger design for getting the correct gas flow rate for thermal destratification within the liquid propellant storage tanks.

Leakage-Resilient Secret Sharing With Constant Share Size

In this work, we consider the leakage-resilience of algebraic-geometric (AG for short) codes based ramp secret sharing schemes extending the analysis on the leakage-resilience of linear threshold secret sharing schemes over prime fields that is done by Benhamouda et al. in the effort to construct linear leakage-resilient secret sharing schemes with constant share size. Since there does not exist any explicit efficient construction of AG codes over prime fields with constant field size, we consider constructions over prime fields with the help of concatenation method and constructions of codes over field extensions. Extending the Fourier analysis done by Benhamouda et al., one can show that concatenated algebraic geometric codes over prime fields do produce some nice leakage-resilient secret sharing schemes. One natural and curious question is whether AG codes over extension fields produce better leakage-resilient secret sharing schemes than the construction based on concatenated AG codes. Such construction provides several advantage compared to the construction over prime fields using concatenation method. It is clear that AG codes over extension fields give secret sharing schemes with a smaller reconstruction threshold for a fixed privacy parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> . In this work, it is also confirmed that indeed AG codes over extension fields have stronger leakage-resilience under some reasonable assumptions. Furthermore, we also show that AG codes over extension fields may provide strong multiplicative property which may be used in its application to the study of multiparty computation. In contrast, the same cannot be said for constructions based on concatenated AG codes, even when we are considering multiplication friendly embeddings. These advantages strongly motivate the study of secret sharing schemes from AG codes over extension fields. The current paper has two main contributions: (i) we obtain leakage-resilient secret sharing schemes with constant share sizes and unbounded numbers of players. Some of the schemes constructed without the use of concatenation also possesses strong multiplicative property (ii) via Fourier Analysis, we analyze the leakage-resilience of secret sharing schemes from codes over extension fields. This is of its own theoretical interest independent of its application to secret sharing schemes from algebraic geometric codes over extension fields.

Texture-Aware Spherical Rotation for High Efficiency Omnidirectional Intra Video Coding

To adapt to the existing video coding standards, omnidirectional videos are usually projected from Three-Dimensional (3D) sphere to Two-Dimensional (2D) plane. However, this projection will cause geometrical stretching distortion and boundary discontinuity, which may degrade coding efficiency. In this paper, we present a Spherical Rotation based Omnidirectional Video Coding (SROVC) method, which exploits the textural properties of omnidirectional videos with spherical rotation. Firstly, SROVC framework is presented and Full-traversal Spherical Rotation (FSR) is developed to derive the optimal rotation angle with frame-level Rate Distortion Optimization (RDO). Secondly, to achieve comparable coding gains and lower computational complexity when compared with FSR, a Texture-aware Spherical Rotation (TSR) method is proposed to predict the rotation angle. Finally, to further reduce complexity and maintain coding efficiency, a Group-oriented TSR (G-TSR) approach is presented, in which the group length is statistically determined. Extensive experiments demonstrate that the proposed TSR and G-TSR schemes can achieve bit rate reductions up to 4.38%, 0.94% and 0.89% on average for CubeMap Projection (CMP) based high efficiency omnidirectional video coding. Additionally, the TSR scheme achieves bit rate saving from 0.91% to 1.19% on average under three more CMP-based projection formats, and 1.89% for joint rotation of X, Y, and Z axes.

Teamwork in faculty members' research activities: Difficulties and solutions

The aim of this study was to analyze difficulties and solutions of teamwork in faculty members' research activities. This applied research used qualitative method as the research strategy. The data collection tool was semi-structured interview. For this study, four comprehensive universities in Tehran including University of Tehran, Shahid Beheshti University, Kharazmi University and Tarbiat Modares University were selected. In each university, one faculty was randomly selected for every 20 faculties. Then, within each faculty, all departments were considered. Finally, among the departments, faculty members were purposefully selected and considered as participants in the research (45 faculty members up to theoretical saturation). Open coding and theme analysis methods used to analyze data. To ensure the validity of the research, while trying to control the bias and prejudice of the researcher, some participants reviewed the extracted categories. Also, one of the colleagues was asked to review the findings. To calculate the reliability, test-retest reliability method and agreement for two raters method were used. The results showed that there was a difference between the natures of disciplines for teamwork. There was not any difference between universities regarding team-work implementation. In addition, to choose an activity to do the work as a team, the nature of that work is decisive and among the research activities listed in Article 3 of the Regulation, no order and priority can be considered for the implementation of teamwork. Finally, teamwork difficulties can be divided into five categories: related to individual, related to the team and team factors, within the organization and within the university, related to the higher education system, and general context and national factors.

КОНЦЕПЦІЯ ЗНИЖЕННЯ ІНФОРМАЦІЙНОЇ ІНТЕНСИВНОСТІ ТРАНСФОРМАНТ ІНФОРМАТИВНИХ СЕГМЕНТІВ ЗОБРАЖЕННЯ

The article is devoted to the problem of providing users with the necessary qualitative indicators of remote video service provision. The imbalance between the reliability of the received video image and time delays in the process of delivering such an image via wireless communication channels is substantiated. For this purpose, the article proposes to use an integrated method of technological solutions, which is connected with the technological processes of reducing the bit intensity of the video stream. It is justified that reducing the intensity of the video stream is achieved by eliminating the amount of redundancy of various types (statistical, psychovisual, structural-statistical, structural) in the segment. Technological stages of the developed method of coding transforms of informative image segments are provided. It is justified that each stage of the created method, during processing, is responsible for eliminating various types of video segment redundancy.

A dynamic S-box generation based on a hybrid method of new chaotic system and DNA computing

S-box is one of the most significant structures used to construct encryption that is strong and resistant to attacks in encryption algorithms. The new 4D-hyper chaotic system and deoxyribonucleic acid (DNA) computing are used in this paper to provide a new dynamic S-box generating approach. The 4D generated numbers are processed to generate a hexadecimal number that will encode using the DNA coding method and using addition, subtraction, and exclusive-or operations to produce the final DNA string decoded to make the S-Box. The dynamic form of s-boxes is represented by a minor change in the initial conditions of the proposed chaotic method that will generate dynamic sequences of numbers. The proposed method enhances the security criteria of the block ciphers. The S-box testing criteria were done like strict avalanche, balanced, and bit independence criteria, in addition to differential approximation probability and linearity approximation probability, to test the security of the new S-Box. The results show that the new S-box has good security and is resistant to attacks.

Using Secret Image Block to Secure LSB Data Steganography

Data steganography is one of the most popular methods of data protection, but most introduced methods are not secure. In this paper research a simplified LSB method of data steganography will produced, this method will easily used to hide any message in any covering image, changing the image or/and changing the message will not require any changes in the algorithm. The proposed method will use a complicated key to select a secret block from the covering image to be used to hide the message. The PK will contain 5 components of double data type, thus the PK will provide a huge key space which is capable to resist any hacking attempt, the algorithm of the proposed method will be very sensitive to the PK values, any changes in these values will be considered as a hacking attempt by producing unexpected outputs. The proposed method will be implemented and tested using various messages, various covering images, and various PK; the obtained results will be analyzed applying sensitivity analysis, quality analysis and security analysis to prove the improvements added to LSB method of data steganography.

Method of compression and ensuring the fidelity of video images in infocommunication networks

Subject research in the article is the methods of compressing video images under conditions of ensuring the desired level of their fidelity in the delivery process using infocommunication networks. The goal is to develop methods of encoding video images for increasing the level of their compression in the conditions of ensuring required reliability. Task: to substantiate the approach regarding the structural clusterization of transformed video segments in the conditions of preserving their reliability; to develop a method of structural and statistical coding of transformants in the spectral-cluster space; conduct a comparative evaluation of the effectiveness of various methods of encoding video segments. The methods used: mathematical models for estimating the amount of statistical and structural redundancy in the clustered spectral space of video segments; methods of statistical coding. The following results have been obtained. The potential effectiveness of representing a transformant in clustered space by the number of series of units in binary description of their components has been substantiated. A method of structural-statistical coding in the spectral-cluster space has been created. The basic component of this technological approach is the evaluation of the estimates regarding the potential ability to eliminate various types of redundancy in the current cluster. Here, the amount of redundancy is reduced considering the statistical and structural features of the cluster. The comparative evaluation revealed the advantages of the created method over coding methods in standardized platforms. The advantage is achieved in terms of the peak signal-to-noise ratio by at least 30%. and in terms of a compression ratio by an average of 12 %. Conclusions. The scientific novelty of the obtained results is as follows: for the first time, a method of structural-statistical coding of video segments in spectral space based on their clusterization has been created. The differences of the method lie in the fact that the component of the transformant is simultaneously interpreted as an element of the statistical and combinatorial cluster space; the potential capabilities of eliminating various types of redundancy in the clustered transformant are considered. This provides an increase in the level of compression of video images for a given level of reliability.

Understanding Alcohol Use Discourse and Stigma Patterns in Perinatal Care on Twitter.

(1) Background: perinatal alcohol use generates a variety of health risks. Social media platforms discuss fetal alcohol spectrum disorder (FASD) and other widespread outcomes, providing personalized user-generated content about the perceptions and behaviors related to alcohol use during pregnancy. Data collected from Twitter underscores various narrative structures and sentiments in tweets that reflect large-scale discourses and foster societal stigmas; (2) Methods: We extracted alcohol-related tweets from May 2019 to October 2021 using an official Twitter search API based on a set of keywords provided by our clinical team. Our exploratory study utilized thematic content analysis and inductive qualitative coding methods to analyze user content. Iterative line-by-line coding categorized dynamic descriptive themes from a random sample of 500 tweets; (3) Results: qualitative methods from content analysis revealed underlying patterns among inter-user engagements, outlining individual, interpersonal and population-level stigmas about perinatal alcohol use and negative sentiment towards drinking mothers. As a result, the overall silence surrounding personal experiences with alcohol use during pregnancy suggests an unwillingness and sense of reluctancy from pregnant adults to leverage the platform for support and assistance due to societal stigmas; (4) Conclusions: identifying these discursive factors will facilitate more effective public health programs that take into account specific challenges related to social media networks and develop prevention strategies to help Twitter users struggling with perinatal alcohol use.

For the Parent, by the Parent: Creating a Program to Empower Parents of Refugee Background in Canada Using Novel Participatory Approaches.

Families of refugee background have complex, multigenerational mental health and developmental needs that are not accounted for in current programming frameworks in Canada. Providing appropriate support services and educational resources that address the unique concerns of families of refugee background will allow for improved family cohesion and developmental outcomes for children. Parenting programs have been shown to be successful in improving parental stress, parental efficacy, and children's mental health and well-being. This study gathers data about the experiences of caregivers of refugee background in order to develop a novel, multi-dimensional parenting program model using Community-Based Participatory Research (CBPR) principles. This was a qualitative, CBPR study using a formative research framework. In-depth interviews (IDIs) were conducted with caregivers of refugee background and service providers that work closely with this population. Data were recorded, transcribed, and coded using deductive and inductive coding methods by two independent coders. A total of 20 IDIs were conducted (7 caregivers and 13 service providers). The main topics that were identified to be incorporated into the program include: features of child development, how to address resettlement issues, child advocacy, and parenting after resettlement. Participants felt that tackling language barriers, addressing the overlapping responsibilities of caregivers attending the sessions, providing incentives, increasing awareness of the program, and using an anti-racist and anti-oppressive approach was key to the program's success. Participants emphasized the need for trauma-informed mental health supports within the program model. This study describes the key considerations for a novel parenting program for families of refugee background, by engaging them as key stakeholders in the program design process. Future iterations of this project would involve a pilot and evaluation of the program.

079 Applying human phenomics to electronic health records provides a framework for understanding skin-aging related phenotypes

Standard disease classification and defining human phenotypes are incomplete and imprecise because biological mechanisms underpinning human diseases and phenotypes are not yet captured even with different coding systems and methods. Such methods are arbitrary (e.g., hypertension), based on a location or organ (e.g., tumors), or have been used since physicians originally described certain diseases (e.g., Alzheimer’s diseases) over a century ago, which cause confusion and uncertainty in diagnosis, drug discovery and medical care.

CovertSYS: A systematic covert communication approach for providing secure end-to-end conversation via social networks

While encryption can prevent unauthorized access to a secret message, it does not provide undetectability of covert communications over the public network. Implementing a highly latent data exchange, especially with low eavesdropping/discovery probability, is challenging for practical scenarios, such as social and political movements in authoritarian regimes, military operations, and privacy preservation. Moreover, the current literature suffers from a low embedding capacity and monolingual applicability, limiting the amount of hiding secret data within short text messages using state-of-the-art algorithms, e.g., linguistic-based, structural-based, or coverless-based solutions. In this paper, we present a systematic covert communication technique called CovertSYS that enables a multilingual secure end-to-end conversation via messaging or social network platforms. The CovertSYS functions by encrypting a confidential message using a multi-factor authentication scheme and converting the encoded binary data into hidden Unicode symbols to be transmitted under cover of short text messages. We then conduct extensive experiments to confirm the security and validity of the proposed technique against state-of-the-art approaches. Our experimental results show that the CovertSYS provides a superior mean performance of 91.53% by improving the criteria scores: embedding capacity rate of 100%, imperceptibility rate of 76.4%, and distortion robustness rate of 98.2%. Finally, we discuss the practical implications of the proposed technique compared to the existing text steganography methods.

Developing an adaptive DCT-based steganography method using a genetic algorithm

Developing an adaptive DCT-based steganography method using a genetic algorithm