Multimedia Files Research Articles

Enhanced Dual-Layer Video Steganographic Approach: Enhancing Security and Imperceptibility

In a digital age where the role of digital information is continually expanding, the imperative to ensure secure communication and data protection has intensified. Steganography, a field that conceals sensitive information within apparently innocuous carriers like multimedia files, holds promise for achieving this goal. Recent times have seen a growing interest in video-based steganography, driven by the proliferation of videos online. However, a review has unveiled a noteworthy gap in efforts to increase the safety of video steganography employing the popular Least Significant Bit (LSB) process. LSB steganography is at risk to exploits that could jeopardize the confidentiality of the concealed message. In this research, we present a video steganographic solution achieved through the integration of advanced encryption algorithms and a dual approach involving randomized frame selection using the Fisher-Yates method and pixel selection utilizing the 8-directional technique. Additionally, we have devised an upgraded imperceptible video steganographic approach in the spatial domain, capitalizing on an XOR-based LSB substitution embedding approach. The outcomes underscore the effectiveness of our proposed methodology, revealing significant imperceptibility when compared to recent solutions, thereby reinforcing data security against unauthorized access. This comprehensive solution holds wide-ranging applications across various domains, providing heightened security and confidentiality for sensitive information. Notable applications include secure communications within intelligence agencies, safeguarding patient data in medical sciences, ensuring privacy in video surveillance, fortifying video transmission against errors and data breaches, securing business communications, preventing data leakage, and enhancing rights management for digital content.

Designing File Storage and Sharing System

Background: Files stored on a network are anticipated to be exchanged securely and efficiently. An internet-based file management platform that enables users to securely create, save, organize, collaborate, and share files. Sharing is a recently developed service idea that is frequently sought after by researchers and students. The suggested work offers many forms of data files, including documents and multimedia files. File storage has been a widely used storage method for many years. Materials and Methods: The proposed method used to build the website is Visual Studio 2015 with SQL server Database to provide file storage with different data type storage and it provides a service as an IT repository file storage system to help student and teachers to communicate with each other in academic way for publishing files in easy and in a flexible manner. Results: The proposed system results showed that the website can provide file upload with supported files are ".doc", ".docx", ".pptx", ".pdf", ".zip", ".rar", ".mp4", ".flv", ".avi", ".PDF", ".DOCX" and ".DOC". Results showed that the system uploaded file size 5M, 10 and 25 M smoothly. Conclusion: The work provides a flexible way to store and sharing files for different fields and we use it for education purposes. The results showed that the proposed system is very flexible in the process of uploading various files at a very high speed, due to the ease of uploading files to the server and accessing them by various students in the college.

A robust audio steganography technique based on image encryption using different chaotic maps

The development of innovative methods for concealing critical data in multimedia files has exploded in information security in recent years. Cryptography and steganography cannot be used alone to protect data; rather, they can be combined and used in a single system. Audio steganography is among the most important information security techniques. It involves the concealment of information within audio signals to achieve covert communication. This paper introduces a comprehensive technique that integrates chaos Henon, Baker, and Arnold maps for image encryption with audio steganography to create a robust and secure audio steganography technique. First, the target image is encrypted using chaotic maps. Then, it is embeded within the high frequencies of the cover audio signal based on the Inverse Short Time Fourier Transform (ISTFT) to be transmitted to the destination through the channel. By integrating both encryption and concealment techniques, the cover audio signal quality can be preserved. Moreover, the hidden image security and robustness are improved, making the technique resistant to many types of attacks. The simulation results confirm that the suggested technique is robust in the presence of attacks. It achieves a distinct perceptual quality with an appreciated peak signal-to-noise ratio (PSNR) of 91.2 dB and a Mean Square Error (MSE) of 7.5 × 10–10. The randomness of the resulting encrypted image has successfully passed the National Institute of Standards and Technology (NIST) statistical test suite.

Optimization of indoor thermal environment based on sensor networks and multimedia assisted physics teaching

Multimedia technology combines various media elements such as text, images, sound, and video, making classroom teaching more vivid, intuitive, and interesting. This article introduces a multimedia courseware assisted physics teaching application based on sensor networks and deep learning technology. This application has two functional modules: user user end and cluster control end. On the user end, obtain user commands through the virtual machine end and share the original multimedia files using the CIFS protocol. The user command is redirected to the user end, and then the corresponding command is executed on the user end to directly transmit and play the original multimedia file. At the same time, the user end will also provide data feedback and recording for subsequent data analysis and evaluation. At the cluster control end, based on the information collected by the sensor network, an adaptive linear regression algorithm is used to predict the reference value. By analyzing and processing the collected information, the cluster control end can reasonably arrange the playback content of multimedia courseware to meet the learning needs of students. This multimedia courseware assisted physics teaching application based on sensor networks and deep learning technology provides new help and support for physics teaching.

A Mellin transform based video steganography with improved resistance to deep learning steganalysis for next generation networks

In the era of 5 G network advancements, the potential for extremely robust, less-latency, and huge-capacity communication opens up new perspective for multimedia. Steganography enables embedding of sensitive data within multimedia files, making it unreadable to unauthorized third parties. Notably, when using videos as cover, the capacity for data embedding is substantially increased. Recent developments in steganography have largely revolved around modified versions of transform domain techniques. Due to this repetitiveness, it becomes easier for steganalytic tools in detecting concealed data. Addressing this issue, our paper introduces an innovative data embedding approach MARVIS based on the Mellin transform. The superiority of the proposed approach is exhibited using the metrics, MSE, PSNR, and SSIM. MARVIS has achieved PSNR of 50–60 dB and SSIM of 0.9998 for embedding 4 bits of secret data, outperforming other methods that achieve 40 dB for 1 bit. By quadrupling stego capacity, we can embed more secret data per pixel without compromising the integrity of the cover object.•MARVIS utilizes phase modulation for data embedding, offering advantages beyond traditional frequency domain techniques which use frequency domain for data embedding.•The effectiveness of the proposed data embedding approach is validated through Y-Net, a deep learning-based steganalysis tool.

Method for generating multimedia files for the tasks of facial biometrics and its applications

Method for generating multimedia files for the tasks of facial biometrics and its applications

Crisis Response in Nursing Education: An Integrative Review of Nursing Program Adaptation to COVID-19.

This integrative review sought to systematically examine and synthesize published research on crisis response to identify ways in which undergraduate nursing education programs in various countries adapted to the coronavirus disease 2019 (COVID-19) pandemic. A computerized search of CINAHL, Science Direct, and Web of Science databases was performed. The literature search, review, and data extraction process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format of identification, screening, eligibility, and inclusion. Digital learning technology platforms were used in undergraduate nursing education in various ways to adapt to the teaching and learning challenges of the COVID-19 pandemic. Teaching and learning methodologies identified included online lectures and webinars; interactive virtual learning experiences, such as videos, presentations, quizzes, games, and other web-based interactive forms of multimedia files and textual content; and virtual simulations for nursing skills and tele-health experience. [J Nurs Educ. 2024;63(7):445-451.].

Leveraging Linear Network Error Correction for steganographic network codes

Steganography is an ingenious method employed to conceal data within an unassuming, non-secret file or message, thereby evading detection. The concealed information is later extracted at its intended destination. Many legitimate applications of steganography exist, ranging from hiding watermarks or trademarks covertly within multimedia or other content files, to embedding sensitive information securely. In this paper, we introduce Steganographic schemes employing Linear Network Error Correction Codes (LNECCs). Initially, we emphasize the enhanced throughput achieved through the integration of steganography into joint channel-network codes, then we demonstrate the feasibility of leveraging LNECCs and their corresponding error patterns to formulate distortion-free steganographic schemes. Specifically, for a given LNECC in relation to a terminal and a resolvable error pattern, with the precondition that the minimum cut between them is positive, we delineate the corresponding distortion-free steganographic protocols. Moreover, we conduct a thorough analysis of our scheme and fortify it against potent steganalysis attacks. Finally, we propose a prospective solution for cases involving erroneous retrievals.

The Level of Satisfaction with Blended Learning via the Flipped Classroom Approach in the Epidemiology Course Among Nursing Students

Background: The flipped classroom (FC) instructional strategy, as a blended learning approach, encourages students to take an active role in the learning process. Objectives: This study aimed to investigate the level of satisfaction with FC in the epidemiology course among nursing students. Methods: This descriptive-analytical study with a cross-sectional research design was conducted in 2022 at a school of nursing in Tehran, Iran. A total of 109 nursing students enrolled in the second semester of an undergraduate program were recruited via convenience sampling. These students were taught using the FC approach. The lecturer initially prepared teaching materials for each session in the form of multimedia files and uploaded them on the offline NAVID Virtual Education System. Subsequently, a series of questions related to the teaching materials were given to the students to answer in groups of 3 to 4 and discuss. The researcher facilitated the discussion to address any doubts among the students. After completing eight sessions, the Questionnaire for Satisfaction with Flipped Classroom (QSFC), with confirmed validity and reliability, was administered to evaluate the level of satisfaction among the students. Results: The majority of students expressed satisfaction with FC at moderate (48.6%) to high (47.7%) levels. Additionally, most male students (67.3%) reported being highly satisfied with FC, while 46% of female students showed a moderate level of satisfaction. The overall mean satisfaction score with FC was 55.36 ± 12.54, indicating a moderate level of satisfaction. This total score was not significantly correlated with students' age (P = 0.086), but the moderate level of satisfaction among male students was higher than that among females (P = 0.017). Conclusions: The study results suggest that FC, as a type of blended learning, is an appropriate teaching method in nursing education, as it enhances students' satisfaction levels. Improving the quality of virtual education infrastructure and facilities and enhancing teachers' capabilities in utilizing new teaching methods can enhance the quality of education, especially in critical situations.

Using knowledge graphs for audio retrieval: a case study on copyright infringement detection

Identifying cases of intellectual property violation in multimedia files poses significant challenges for the Internet infrastructure, especially when dealing with extensive document collections. Typically, techniques used to tackle such issues can be categorized into either of two groups: proactive and reactive approaches. This article introduces an approach combining both proactive and reactive solutions to remove illegal uploads on a platform while preventing legal uploads or modified versions of audio tracks, such as parodies, remixes or further types of edits. To achieve this, we have developed a rule-based focused crawler specifically designed to detect copyright infringement on audio files coupled with a visualization environment that maps the retrieved data on a knowledge graph to represent information extracted from audio files. Our system automatically scans multimedia files that are uploaded to a public collection when a user submits a search query, performing an audio information retrieval task only on files deemed legal. We present experimental results obtained from tests conducted by performing user queries on a large music collection, a subset of 25,000 songs and audio snippets obtained from the Free Music Archive library. The returned audio tracks have an associated Similarity Score, a metric we use to determine the quality of the adversarial searches executed by the system. We then proceed with discussing the effectiveness and efficiency of different settings of our proposed system.Graphical abstract

Computer Feed based Text Processing Using NLP

The goal of this research project is to create a comprehensive multimedia and text processing framework that can be used in a variety of applications. The objective is to combine a collection of libraries and instruments for the purpose of extracting, analyzing, and modifying textual information obtained from multimedia files, including images, videos, and audio files. The strategy involves applying cutting-edge techniques such as computer vision, audio processing, natural language processing (NLP), optical character recognition (OCR), and computer vision. Important findings include accurate text extraction from multimedia inputs, accurate textual data analysis using natural language processing techniques, and the production of insightful information via sentiment analysis, summarization, and translation. Its main contributions are related to the development of a flexible system that can process a wide range of multimedia inputs and provide useful text processing features. This project provides a foundation for future research and useful applications in the fields of text processing and multimedia.

Digital Image Watermarking

Digital watermarking has become an essential method for encrypting multimedia files by adding undetectable data. In this work, we present a novel approach to digital watermarking that makes use of the Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) methods. By combining these methods, robustness against different types of attacks can be achieved while preserving excellent perceptual quality. Our approach ensures resilience and invisibility by embedding the watermark in the singular values that are obtained from the decomposition of DWT subbands. The outcomes of the experiments show that the suggested strategy is more efficient and effective than the current techniques when it comes to maintaining image quality and being resistant to common image processing threats.

Image Copyright Protection Based on Blockchain Technology Review

On a daily basis, a significant number of individuals distribute several photos and videos that have been marginally modified from the original material produced by copyright owners, such as photographers, graphic designers, and video producers. Individuals that infringe upon the rights of others, lacking the legal authority to access multimedia content, employ various digital image and picture manipulation techniques, it involves converting to gray scale, trimming, rotating, contracting the frame, and adjusting the background speed, to modify said content. Blockchain technology obviates the necessity of an intermediary, hence circumventing the possibility of a singular point of failure. Infractions to copyright poses a significant barrier to protecting commercial image and video information. The IPFS blockchain technology offers on-chain preservation for copyright information and off-chain storing for distinct multimedia files. The enhanced perceptual hashing algorithm significantly enhances the precision of identifying connections to identify digital image piracy. The photographers and designers that submit their photographs on websites are experiencing significant dissatisfaction due to a prevalent practice in which others attempt to claim credit and profit from the initial creator's effort.

Design, implementation, and evaluation of a virtual pulmonary rehabilitation training course for medical interns in COVID-19.

Pulmonary rehabilitation has an influential role in improving the symptoms, reducing subacute and chronic complications, and increasing the performance of patients with COVID-19. Medical interns can play an essential role in training patients. Since, at the time of the research, these concepts were not in the general medical curriculum in Iran, the interns were not trained in this field. This study aimed to design, implement, and evaluate the virtual training course for pulmonary rehabilitation for medical interns in the COVID-19 crisis. A cross-sectional study (with an instructional design approach) was conducted at an academic center in 2021 on 25 medical interns. The newly designed educational content included multimedia files and educational videos offered to the participants. The data collection tools were pre- and post-test, attitude, and satisfaction evaluation questionnaires. Data were analyzed using SPSS (one-sample and paired t-test). The average age of the participants was 26.24 ± 0.92, and most were women (14 (56%)). The average knowledge score after the course (18.52 ± 4.44) compared to before (11.12 ± 2.38) was significant (P < 0.001). The average score of attitudes (55.04 ± 6.49) and satisfaction (92.92 ± 10.69) had a significant difference (P < 0.001 and P < 0.001) and indicated the desirability of the course. Considering the results of this course in improving students' knowledge, attitude, and satisfaction, it is suggested to add this topic to the general medical curriculum (pulmonary or infectious diseases courses).

Parallel BFS through pennant data structure with reducer hyper‐object based data hiding for 3D mesh images

AbstractData hiding refers to the technique employed to conceal sensitive data within various forms of multimedia, such as video, audio, text, 2D images, 3D images, and more, while also being able to successfully extract said information from the multimedia file. Although numerous data hiding techniques exist for 2D images, research on data hiding in 3D images is still in its early stages. Current 3D image steganography methods suffer from limitations in terms of embedding capacity and time complexity. To overcome these difficulties, we propose a novel 3D image steganographic technique using Parallel Breadth First Search (PBFS) with hyper‐object. Our approach utilizes the PBFS searching strategy, along with layer synchronization, to embed private information within the vertices of the 3D mesh images. To maximize the effectiveness of the process and minimize time, cost, complexity, and execution, we involved the data structure “bag” to parallelize the BFS. The implementation of bags is based on the pennant data structure. This methodology obtained an impressive Embedding Capacity (EC) of 9.00 bits per vertex (bpv) while maintaining superior visual quality and time complexity. Consequently, the proposed methodology holds great potential for widespread utilization across numerous sectors, including private and government organizations such as intelligence agencies, intellectual property rights management, cloud data security, defense, covert communication, medical imagery, and more.

Using Modern Learning Method to Teach Pharmacy Students Psychopharmacotherapy.

Applying modern educational methods for digital native students seems necessary. Active learning strategies promote students' skills and knowledge. This study was conducted to design and evaluate active learning methods by teaching psychopharmacotherapy to pharmacy students. This was a quasi-experimental study with three randomized study groups (control, game, and multimedia), using a pre-and post-test design, conducted on 155 students of 5-year pharmacy in 2022 at the Faculty of Pharmacy of Tehran University of Medical Sciences, Iran. Overall, 18 clinical cases were designed for the basic structure of interventions. After teaching psychopharmacotherapy contents through lecturing, the pre-test was held. The next steps were playing the educational game, studying the multimedia case-based learning files, and then completing questionnaires, respectively. Then, a post-test was held. 65.33% of participants were female and 34.66% were male. The pre-test and post-test scores comparison showed no difference in control group (P=0.409). However, in the serious game and multimedia groups, the average score of pre-test and post-test had a statistically significant difference (P<0.001, P=0.002 respectively), this difference was higher in the serious game group. Questionnaire evaluation showed substantial differences between game and multimedia groups. The educational interventions were able to improve student's knowledge and skills so they can better help patients and promote public health. In the sections of Confidence, Social Interactions, Fun, Focused attention, Learnability, Relevance, and Perceived Learning, the serious game far outweighed the multimedia case-based learning.

Intelligent Classification of JPEG files by Support Vector Machines with Content-based Feature Extraction

Nowadays, multimedia files play a basic role in supporting evidence analysis for making decisions about a crime through looking at files as a digital guide or evidence. Multimedia files such as JPG images are a common format because many documents and memorial images on laptops are valuable. In addition, many JPG images on Laptops are valuable and have fewer structure contents, making recovery possible when their file system is missing. However, intelligent systems for fully recovering corrupted JPG images into their original form is a challenging research issue. In this research, a support vector machine (SVM) as intelligent classifier algorithm is proposed to classify JPG or non-JEG image clusters as part of multimedia files. The SVM classifies the data clusters on three content-based feature extraction (entropy, byte frequency distribution, and rate of change approach to derive cluster features) methods to optimize the identification of JPG image content. The SVM classifier is applied using a radial basis and polynomial kernel functions in MATLAB software. The experimental results show that the accuracy of classification of the SVM classifier with the polynomial function is 96.21%, and the SVM classifier with the radial basis function is 57.58%.

Study on the timeliness of English teaching for college students under the background of multimedia

Abstract Starting with the actual multimedia English teaching, this paper analyzes the advantages of an intelligent learning environment as well as the application of virtual reality technology in English teaching. Comparing the traditional CAI courseware development with the courseware development based on virtual reality technology, it is proposed to use wavelet transform to decompose multimedia image resources, establish a static 3D virtual model library, transmit multimedia image files, and convert virtual reality-based network multimedia English teaching courseware. Propose a speech recognition algorithm based on DNN-HMM to help construct a multi-context virtual reality interaction mode. Examine the attitudes of students in different grades towards the use of virtual simulation technology in English teaching. Analyze the role of teaching timeliness in multimedia courseware and analyze the English classroom interaction in an interactive multimedia environment. In terms of student satisfaction, “your attitude towards the application of virtual simulation technology in English classes” is related to “the application of virtual simulation technology in English classes helps to open up new ways of English education, innovate new methods of education, and improve the carrier of education.” The correlation results are x 2 =32.051, p =0.000, showing 0.01 level of significance. It indicates that students believe that using virtual simulation technology in teaching can innovate English teaching and that using multimedia courseware can also enhance the timeliness of English teaching. The university’s English teaching mode using multimedia courseware and interactive multimedia environments can enhance English performance, and 80.37% of students believe it has timeliness in teaching.

Notice of Violation of IEEE Publication Principles: Fault Detection Using Industrial Video Information

Notice of Violation of IEEE Publication Principles Fault Detection Using Industrial Video Information by Y. Zhang, Z. Wang, Y. Fu and X. Li, in the IEEE Transactions on Industrial Electronics, vol. PP, no. 99 After careful and considered review of the content of this paper and associated multimedia content by a duly constituted expert committee, this work has been found to be in violation of IEEE's Publication Principles. This paper and associated multimedia files contain fraudulent data and images. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper and refrain from future references. In this study, a new data-modelling algorithm, referred to as relaxed independent component analysis, is proposed for the purpose of industrial video process monitoring. The contributions are as follows. (1) Physical variables and image data are unified in a framework to propose fault detection method of industrial process for the first time. (2) We find that independent components are sensitive to extract features of image and physical variables. In original KICA method, KPCA+ICA are used to extract nonlinear independent components. Since ICA is linear method, the original method only extracts semi-nonlinear independent components. In our method, the complete nonlinear independent components are extracted using the independence criterion. (3) A process monitoring approach of relaxed independent component analysis is presented. When applied to the monitoring of an electrical fused magnesia furnace, it can effectively improve the accuracy of forecasting the non-Gaussian process and reduce the ratio of false alarms compared to kernel principle component analysis and traditional kernel independent component analysis.

A New Method for Intelligent Multimedia Compression Based on Discrete Hartley Matrix

Multimedia data (video, audio, images) require storage space and transmission bandwidth when sent through social media networking. Despite rapid advances in the capabilities of digital communication systems, the high data size and data transfer bandwidth continue to exceed the capabilities of available technology, especially among social media users. The recent growth of multimedia-based web applications such as WhatsApp, Telegram, and Messenger has created a need for more efficient ways to compress media data. This is because the transmission speed of networks for multimedia data is relatively slow. In addition, there is a specific size for sending files via email or social networks, because much high-definition multimedia information can reach the Giga Byte size. Moreover, most smart cameras have high imaging resolution, which increases the bit rate of multimedia files of video, audio, and image. Therefore, the goal of data compression is to represent media (video, audio, images, etc.) as accurately as possible with the minimum number of bits (bit rate). Traditional data compression methods are complex for users. They require a high processing power for media data. This shows that most of the existing algorithms have loss in data during the process of compressing and decompressing data, with a high bitrate for media data (video, audio, and image). Therefore, this work describes a new method for media compression systems by discrete Hartley matrix (128) to get a high speed and low bit rate for compressing multimedia data. Finally, the results show that the proposed algorithm has a high-performance speed with a low bit rate for compression data, without losing any part of data (video, sound, and image). Furthermore, the majority of users of social media are satisfied with the data compression interactive system, with high performance and effectiveness in compressing multimedia data. This, in turn, will make it easier for users to easily send their files of video, audio, and images via social media networks.