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High-efficiency video coding (HEVC) is the latest video coding standard that has better coding efficiency than the H.264/advanced video coding (AVC) standard. The purpose of this paper is to design and develop an effective block search mechanism for the video compression-HEVC standard such that the developed compression standard is applied for the communication applications.

In the proposed method, an rate-distortion (RD) trade-off, named regressive RD trade-off is used based on the conditional autoregressive value at risk (CaViar) model. The motion estimation (ME) is based on the new block search mechanism, which is developed with the modification in the Ordered Tree-based Hex-Octagon (OrTHO)-search algorithm along with the chronological Salp swarm algorithm (SSA) based on deep recurrent neural network (deepRNN) for optimally deciding the shape of search, search length of the tree and dimension. The chronological SSA is developed by integrating the chronological concept in SSA, which is used for training the deep RNN for ME.

The competing methods used for the comparative analysis of the proposed OrTHO-search based RD + chronological-salp swarm algorithm (RD + C-SSA) based deep RNN are support vector machine (SVM), fast encoding framework, wavefront-based high parallel (WHP) and OrTHO-search based RD method. The proposed video compression method obtained a maximum peak signal-to-noise ratio (PSNR) of 42.9180 dB and a maximum structural similarity index measure (SSIM) of 0.9827.

In this research, an effective block search mechanism was developed with the modification in the OrTHO-search algorithm along with the chronological SSA based on deepRNN for the video compression-HEVC standard.

With the advent of technology, a huge amount of data is being transmitted and received through the internet. Large bandwidth and storage are required for the exchange of data and storage, respectively. Hence, compression of the data which is to be transmitted over the channel is unavoidable. The main purpose of the proposed system is to use the bandwidth effectively. The videos are compressed at the transmitter’s end and reconstructed at the receiver’s end. Compression techniques even help for smaller storage requirements.

The paper proposes a novel compression technique for three-dimensional (3D) videos using a zig-zag 3D discrete cosine transform. The method operates a 3D discrete cosine transform on the videos, followed by a zig-zag scanning process. Finally, to convert the data into a single bit stream for transmission, a run-length encoding technique is used. The videos are reconstructed by using the inverse 3D discrete cosine transform, inverse zig-zag scanning (quantization) and inverse run length coding techniques. The proposed method is simple and reduces the complexity of the convolutional techniques.

Coding reduction, code word reduction, peak signal to noise ratio (PSNR), mean square error, compression percent and compression ratio values are calculated, and the dominance of the proposed method over the convolutional methods is seen.

With zig-zag quantization and run length encoding using 3D discrete cosine transform for 3D video compression, gives compression up to 90% with a PSNR of 41.98 dB. The proposed method can be used in multimedia applications where bandwidth, storage and data expenses are the major issues.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

This paper aims first to describe the most prevalent teachers’ and students’ behaviors in synchronous online classes in emergency remote teaching; second, to discern behavior profiles and third, to investigate what features explain the observed behaviors.

An adapted COPUS observation protocol was employed to observe 292 online classes from 146 higher education teachers.

The most prevalent behaviors were: Presenting for teachers and Receiving for students, followed by Teachers Guiding and Students Talking to Class. Furthermore, cluster analysis showed two groups: Traditional and Interactive. The variables that better explained belonging to the Interactive lecture group were disciplinary area – social sciences and humanities –and teaching in technical institutions.

In a context where higher education institutions intend to project the lessons learned into post-pandemic learning experiences, this study provides observational evidence to realize the full potential expected from online and blended teaching and learning.

Despite the prevalence of synchronous online lectures during COVID-19, there is a paucity of observational studies on the actual behaviors that occurred in this context. Most research has been based on surveys and interviews. This study addresses this gap.

Over the past decade, architecture, construction and engineering (ACE) industries have been evolving from traditional practices into more current, interdisciplinary and technology integrated methods. Intricate digital tools and mobile computing such as computational design, simulation and immersive technologies, have been extensively used for different purposes in this field. Immersive technologies such as augmented reality (AR) and virtual reality (VR) have proven to be very advantageous while the research is in its infancy in the field. Therefore, this study aims to develop an immersive pedagogical framework that can create a more engaging teaching and learning environment and enhance students' skill in the ACE field.

This study developed a BIM-enabled VR-based pedagogical framework for the design studio teaching in architectural courses, using a qualitative approach. A case study method was then used to test and validate this developed framework. Architectural Master Design Studio B, at Queensland University of Technology (QUT) was selected as the case study, with South Bank Corporation (SBC) as the industry partner and stakeholder of this project.

The practicality and efficiency of this framework was confirmed through increased students' and stakeholders' engagement. Some of the additional outcomes of this digitally enhanced pedagogical framework are as follows: enhanced students' engagement, active participation, collective knowledge construction and increased creativity and motivation.

The results have proven that the developed technology-enhanced and digitally enabled teaching pedagogy and framework can be successfully implemented into architectural design studios. This can bridge the existing gap between the technological advancements in ACE industry and higher education teaching and learning methods and outcomes. It is also expected that such innovative pedagogies will future-proof students' skill set as the future generation of architects and built environment workers. A major limitation of this framework is accessibility to the required hardware such as HMD, controllers, high-capacity computers and so on. Although the required software is widely accessible, particularly through universities licencing, the required hardware is yet to be readily and widely available and accessible.

The result of this study can be implemented in the architectural design studios and other ACE related classrooms in higher educations. This can bridge the existing gap between the technological advancements in ACE industry, and higher education teaching and learning methods and outcomes. It is also expected that such innovative pedagogies will future-proof students' skill set.

Such technology-enhanced teaching methods have proven to enhance students' engagement, active participation, collective knowledge construction and increased creativity and motivation.

Despite the advancement of digital technologies in ACE industry, the application of such technologies and tools in higher education context are not yet completely explored and still scarce. Besides, there is still a significant gap in the body of knowledge about developing teaching methods and established pedagogies that embrace the usage of such technologies in the design and architecture curricula.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

This paper aims to investigate public library staff engagement and perceptions of video games and video game services.

Quantitative and qualitative data on staff video game experiences, perceptions and confidence were collected through an online questionnaire.

The results indicate an overall positive perception of video games in public libraries, with 87% of the respondents supporting video games in public libraries. Video game players appear to think more positively about video games and have more general knowledge about them than non-players. They also appeared to be more confident in delivering related services and were more likely to be running gaming-related events. It was concluded that staff attitudes towards video games are not a barrier to their inclusion in public libraries, as found in previous research.

Encouraging staff engagement with video games may improve their knowledge and confidence in delivering video game services, although further research is required to confirm this. There is a potentially underserved population of those aged 46–84 years, nearly half of whom play video games. Evaluation of this potentially underserved population is an interesting topic for future research.

To the best of the authors’ knowledge, this was the first survey of public library staff views towards video games in Aotearoa New Zealand, and it updates previous research in light of developments in gaming, gaming technology and the increased focus on public libraries as providers of digital technology and sites of community engagement.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

The purpose of this study was to explore potential witnesses' memories for a day that was experienced an unremarkable. There may be instances in an investigation in which all leads have been exhausted, and investigators use a broad appeal for witnesses who may have witnessed something important. Investigators can benefit from knowing the types of information that may be recalled in such circumstances, as well as identifying specific methods that are effective in eliciting useful information.

The present study explored how the delay to recall and recall method influenced the recollection of a seemingly unremarkable day that later became important. Participants were asked to recall an experienced event that occurred either recently (a few weeks prior) or in the distant past (a year prior). Participants recalled via either a written method, in-person individual-spoken or collaborative-spoken interviews.

Results suggest an independent benefit for individual-spoken in-person recall (compared to written or collaborative-spoken recall) and recall undertaken closely after an event (compared to delayed recall). Both individual-spoken interviews as well as more recent recollection resulted in a greater number of overall details recalled. The authors further examined the types of details recalled that might be important to progressing an investigation (e.g. other witnesses and records).

The present work provides important implications for interviewing witnesses about a seemingly unremarkable event that later became important.

360-degree video is recorded with omnidirectional or multi-camera systems that capture all directions at the same time in a spherical view. With immersive technologies gaining momentum and reducing educational cost, it has attracted the interest of the academic community. However, little is known about using 360-degree video in teacher education. The purpose of this study is to conduct a systematic scoping review through a systematic process based on 15 included studies to determine the characteristics, impacts, strengths and weaknesses of the 360-degree video applied to teacher education.

This study combines scoping and systematic review based on the PRISMA paradigm.

This paper explores that 360-degree videos are applicable to teacher education, specifically with their positive effects on pre-service teachers’ immersion, noticing, reflection and interpersonal competence. However, as for learners’ reactions, physical discomfort is reported, like motion sickness.

First, some recently published studies on the subjects were partially accessible, which precluded the authors from adding their findings to this study. Second, the sample of articles is constrained to the search and selection strategies described in the methods section, which increases the possibility that pertinent research may be omitted. Furthermore, this study’s summary of the selected research may be inadequate. Third, only English-language publications were included in this study. Future researchers can expand on this topic by gathering additional relevant empirical data from publications in other languages.

Practically, findings in this study reveal the positive effects of 360-degree video in teacher education. The results may help researchers and preservice teachers better understand 360-degree video and use it more frequently in teaching. Instructional video technologies have been found to have a nearly medium effect on learning effectiveness in educational practice from a broader perspective.

The findings in this study can shed light on future educational technology research on instructional video technologies and technology-enhanced teacher education.