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Despite increasing digitalization and automation, complex production processes often require human judgment/decision-making adaptability. Humans can abstract and transfer knowledge to new situations. People in production are an irreplaceable resource. This paper presents a new concept for digitizing human expertise and their ability to make knowledge-based decisions in the production area based on ontologies and causal Bayesian networks for further research. Dedicated approaches for the ontology-based creation of Bayesian networks exist in the literature. Therefore, we first comprehensively analyze previous studies and summarize the approaches. We then add the causal perspective, which has often not been an explicit subject of consideration. We see a research gap in the systematic and structured approach to ontology-based generation of causal graphs (CGs). At the current state of knowledge, the semantic understanding of a domain formalized in an ontology can contribute to developing a generic approach to derive a CG. The ontology functions as a knowledge base by formally representing knowledge and experience. Causal inference calculations can mathematically imitate the human decision-making process under uncertainty. Therefore, a systematic ontology-based approach to building a CG can allow digitizing the human ability to make decisions based on experience and knowledge. [ABSTRACT FROM AUTHOR]

These developments have the potential to foster additional innovation, facilitate future problem-solving and optimisation strategies, and ultimately contribute to mature OWC technologies. Keywords: optical communication; underwater optical wireless communication EN optical communication underwater optical wireless communication 87 90 4 08/24/23 20230801 NES 230801 Since 2011, optical wireless communication (OWC) technologies have gained momentum. These technologies include visible light communications (VLC), underwater VLC, Li-Fi, optical camera communications (OCC), visible light positioning, visible light sensing and free space optics, among others. [Extracted from the article]

This paper examines the impact of digital technologies and tools on business communication in the contemporary business environment through the prism of new communication channels. Every technological breakthrough throughout history has altered the way people communicate, beginning with the discovery of the printing press, telegraph, radio, and television. In the fifth industrial revolution and contemporary environment, business communication becomes increasingly focused on current digital technologies and tools. Traditional communication, which was inherently slow, is being phased out in favor of interactive and quick communication. Communication through modern digital technologies and tools has many benefits, but it also has some drawbacks, including the possibility of misunderstandings and conflict. This paper discusses the digital age’s key communication channels, including smart mobile phones, short messages (sms), multimedia messages (mms), voice mail, Viber, WhatsApp, iMessage, Skype, Google Hangouts, Slack, teleconferences, video conferences, e-mail, intranet, organizational social and professional networks, and various business communication applications. Besides from their essential characteristics and advantages, this paper highlights key limitations that should be considered in order to eliminate or lessen misunderstandings and conflict situations. [ABSTRACT FROM AUTHOR]

Computers and other digital communication media have replaced paper and pencil from the writer's desk. This development has confronted special collections with a problem, as digital papers are difficult to process using established digital preservation strategies, because of their individual and unique nature. According to the proposal suggested in this paper, the creators should instead be involved in the preservation process, and special collections should integrate pre-custodial forms of curation within their range of tasks. The article outlines the use of a cloud architecture as a suitable instrument for accomplishing this task. The benefits and the prospects for such a collection cloud are exposed and discussed. [ABSTRACT FROM AUTHOR]

This paper describes the research published during the period 2011-2020 by five leading Spanish peer-reviewed journals of communication, aiming to identify the most common theoretical frameworks and standard theories. A statistically representative sample of the articles published during that period was systematically selected from the five journals of communication ranked as having the greatest continuity and impact according to SJR-Scopus: Profesional de la Información, Comunicar, Communication & Society, Estudios sobre el Mensaje Periodístico and Revista Latina de Comunicación Social. A coding protocol that includes 13 variables and 74 categories was defined and applied to compare the type of theoretical frameworks and the theories in the different subject areas observed. The results show that although almost all the papers studied have a theoretical framework, fewer than half are grounded on recognizable theories. Specifically, journalism and digital communication are the two subject areas whose articles frequently include standard theories: in journalism by the support of classical theories of communication (framing, agenda setting, journalistic professional cultures and roles), and in digital communication by the support of more theoretically dispersed frameworks. Theoretical frameworks developed by literature review are common in other subject areas (such as audiovisual studies, public relations and documentation). [ABSTRACT FROM AUTHOR]

This paper examines the digital economy's impact on rural household consumption upgrading. Existing studies remain mainly at the level of rural consumption scale and rarely address the consumption structure. The specific impact of the development of the digital economy on rural consumption upgrading and its mechanisms of action deserves in-depth study and consideration. We analyzed the related content using the fixed-effect model, the instrumental variable method (IV), the mediation effect model, and three-year panel data from the China Family Panel Studies (CFPS). This study found that, at the scale level, the digital economy contributes to expanding rural household consumption. At the structural level, the digital economy significantly increases the share of enjoyment-oriented household consumption but has no significant effect on development-oriented consumption. Income is an important transmission mechanism for the digital economy to improve rural household consumption. Besides, the impact of the digital economy on the upgrading of rural consumption varies according to income level and age. [ABSTRACT FROM AUTHOR]

This paper discusses digital neighbourhood communication in rural areas and its effects on local communal life. Therefore, survey data as well as guided interviews of residents in Metelen, county Steinfurt (Germany), are analysed. The results indicate that using digital neighbourhood platforms in rural communities intensifies contacts and further strengthens the feeling of social participation.However, digital neighbourhood contacts do not facilitate relationships concerning analogous material exchange, such as lending items. Furthermore, the analysis of the qualitative interviews shows that digital neighbourhood communication is used in the organisation of community life, presents local activities, and simplifies the organisation of local customs. All in all, those digital structures are mainly used for information purposes. Consequently, digital neighbourhood relations must be regarded when developing and organising future public services, although a functional usage is required to achieve a successful outcome. As digital contact emerges from analogous contact, occasions and infrastructure to actually ensure direct contact are inevitable. [ABSTRACT FROM AUTHOR]

The present study aims to measure the contributions of Prof. Anurag Kumar, who served as the Director at the Indian Institute of Science (IISc) in Bengaluru between August 2014 to July 2020. He has contributed 181 publications during his 36 years of career. He has published his majority of publications 171 (94.48%) in collaboration; most active collaborators with Prof. Anurag Kumar are Altman E. with (17) publications, Kuri Joy (15), Anand (14), and Singh (12). His highest Collaboration Coefficient found is 0.73 in 2013, and the highest Modified Collaboration Coefficient is 1.33 in the year 2018. The highest degree of collaboration observed for Prof. Anurag Kumar was 1.00. The highest Collaborative Index of Prof. Anurag found is 4.75 in the year 2016. His publications received 2595 citations so far, with 14.3 citations for each publication and an average citation of 72.08 per year. He has produced most of his publications in the field of computer science (45.9%). He preferred conference papers as his communication channel, where he published 100 (55.24%) papers out of 181. Prof. Anurag Kumar has contributed the highest (62) publication between 2005-2010, and he has published his first publication at the age of 30. [ABSTRACT FROM AUTHOR]

The text describes the organization of a Special Issue in the Sensors journal titled "Recent Trends and Advances in Telecommunications and Sensing." The Special Issue was based on papers presented at the 17th International Conference on Telecommunications (ConTEL) held at Graz University of Technology in Austria. The conference covered various topics related to telecommunications, including optical communications, satellite communications, IoT, and security. Nine papers were accepted for publication in the Special Issue, covering subjects such as network experimentation, optical camera communications in healthcare, and anomaly detection in firewall logs. The authors of the text are Erich Leitgeb, Maja Matijašević, Wilfried Gappmair, and Mario Kušek. [Extracted from the article]

Copyright of Sociologia (08723419) is the property of Universidade do Porto, Faculdade de Letras and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of the times, figurative expressions no longer meet the creative needs of artists and the aesthetic demands of the people. In order to express art in a more profound way, the perfect use of abstract graphics plays a crucial role in the success of the work. In recent years, there has been a surge in the creation of digital art, but there is relatively little theoretical literature on the combination of abstract graphics as a visual language and digital art. In addition, research on the theoretical aspects of digital art design is also relatively weak, so it is essential to analyse the formal aesthetics and innovative applications. In fact, digital art design has a very important role to play in promoting the development of creative cultural industries. In other words, the healthy development of digital art design can influence the future prospects of a country's creative and cultural industries. Digital art design is an integrated and complex production process and labour outcome. In addition to its human, aesthetic, and social value, digital art also has an economic value. Digital art is a new art form that combines digital technology and artistic aesthetics. As such, digital art is characterised by high technology, diverse forms, popularised art, and the advantages of high communication, interactivity, and influence, which can provide more assistance for the innovation and application of abstract graphics. Digital art is multifaceted and has an artistic expression that cannot be matched by other forms of technology. Abstract graphics, driven by digital art, are full of novelty and interest and can greatly enrich people's emotions and senses. Abstract graphics bring the experience of digital art to its fullest potential. The combination of digital art and abstract graphics offers more innovation and possibilities for the development of art and will bring great prosperity to art communication. With the widespread use of computer and network technology, the Internet has developed rapidly. In this context, digital art, as art created in a digital way and concept, has gained widespread attention. As a result, how to integrate existing computer resources in the new environment to build a model of digital art design effectiveness will cause a direct influence on the quality of digital art design with digital content innovation as the core. At the same time, as digital art becomes more and more popular, the demand for digital talents becomes very urgent. As a result, the cultivation of high-quality digital talents has become a major concern for society. Therefore, in order to explore the success of digital art design and the cultivation of digital art talents, and to better serve the innovation of digital art, this paper proposes a digital art effectiveness model based on the K-medoids algorithm. This model can provide a deeper and more comprehensive understanding of digital art and abstract graphics and provide theoretical support for professional design creation. [ABSTRACT FROM AUTHOR]

Long Short-Term Memory (LSTM)-Based Dog Activity Detection Using Accelerometer and Gyroscope. The third paper, authored by Jeong et al. [[14]], introduced a fall detection system that combines a simple threshold method (STM) and LSTM, creating the STM-LSTM-based fall detection system. With rapid advancements in artificial intelligence (AI), the Internet of Things (IOTs), and communication networks, the future of information and communication engineering (ICE) promises remarkable opportunities and challenges. 10.3390/app12199801 18 Zhang M., Wang C., Zhu W., Shen Y. An Intelligent DOA Estimation Error Calibration Method Based on Transfer Learning. [Extracted from the article]

This letter presents two results for multiuser wireless systems employing dirty-paper coding strategies along with greedy scheduling over the broadcast multiple-input multiple-output channel. Specifically, an efficient and suboptimal downlink scheduler is proposed to approximate the maximum sum rate using equal power allocation, and it is shown to approach the maximum sum rate of optimal power allocation for a large number of users under optimal scheduling. The second result demonstrates that the average maximum sum rate can be tightly upper bounded when spatial multiplexing is maximized. [ABSTRACT FROM AUTHOR]

A memoryless bivariate Gaussian source is transmitted to a pair of receivers over an average-power limited bandwidth-matched Gaussian broadcast channel. Based on their observations, Receiver 1 reconstructs the first source component while Receiver 2 reconstructs the second source component both seeking to minimize the expected squared-error distortions. In addition to the source transmission digital information at a specified rate should be conveyed reliably to Receiver 1–the “stronger” receiver. Given the message rate we characterize the achievable distortions region. Specifically, there is an ${\sf SNR}$ -threshold below which Dirty Paper coding of the digital information against a linear combination of the source components is optimal. The threshold is a function of the digital information rate, the source correlation and the distortion at the “stronger” receiver. Above this threshold a Dirty Paper coding extension of the Tian-Diggavi-Shamai hybrid scheme is shown to be optimal. [ABSTRACT FROM AUTHOR]

Torsional oscillations greatly affect performance and. determine the bandwidth (BW) and damping of speed loops. Backlash due to gear reducers can also contribute to the triggering of oscillations, especially when the drive runs at very low load torque. This paper presents a detailed evaluation of these effects in typical electromechanical drive trains applied to paper machine sections. The cases evaluated consider torsional oscillations in two-mass and three-mass systems, and the effect of shaft diameter and length on the resonant frequencies of three typical paper machine sections. Time-domain response plots are evaluated to show the effect of speed response overshoot, reducer backlash, and step or ramp speed commands. Based on these results, mechanical design guidelines are given for the most significant drive train components in order to minimize torsional oscillations of the speed-controlled drive system. [ABSTRACT FROM AUTHOR]

A growing number of online journals and academic platforms are adopting light peer review or 'publish then filter' models of scholarly communication. These approaches have the advantage of enabling instant exchanges of knowledge between academics and are part of a wider search for alternatives to traditional peer review and certification processes in scholarly publishing. However, establishing credibility and identifying the correct balance between communication and scholarly rigour remains an important challenge for digital communication platforms targeting academic communities. This paper looks at a highly influential, government-backed, open publishing platform in China: Science Paper Online, which is using transparent post-publication peer-review processes to encourage innovation and address systemic problems in China's traditional academic publishing system. There can be little doubt that the Chinese academic publishing landscape differs in important ways from counterparts in the United States and Western Europe. However, this article suggests that developments in China also provide important lessons about the potential of digital technology and government policy to facilitate a large-scale shift towards more open and networked models of scholarly communication. [ABSTRACT FROM AUTHOR]

In this correspondence, we compare the achievable throughput for the optimal strategy of dirty paper coding (DPC) to that achieved with suboptimal and lower complexity linear precoding techniques (zero-forcing and block diagonalization). Both strategies utilize all available spatial dimensions and therefore have the same multiplexing gain, but an absolute difference in terms of throughput does exist. The sum rate difference between the two strategies is analytically computed at asymptotically high SNR. Furthermore, the difference is not affected by asymmetric channel behavior when each user has a different average SNR. Weighted sum rate maximization is also considered. In the process, it is shown that allocating user powers in direct proportion to user weights asymptotically maximizes weighted sum rate. [ABSTRACT FROM AUTHOR]

A microstrip line on very thin membrane substrate (0.05 mm) is slot-coupled through a thick air substrate (12.7 mm) to excite an L-band radiating patch element. A breadboard unit achieved a relatively wide bandwidth of 100 MHz (8%). Very narrow coupling slot is used with aspect ratio of 160 (conventional slot aspect ratio is between 10 to 30). This new feed design makes the thin-membrane or inflatable array antenna technology more practical. It reduces the number of thin-membrane layers required for a dual-pol wide-band inflatable array from three layers in a previous design to two layers. In addition, this technology allows the thin-membrane array antenna elements to be readily integrated with thin-membrane-mounted transmit/receive (T/R) modules. Calculation shows that, without the patch, the micros trip line and slot combination can also radiate as a paper-thin (0.05 mm) radiator at the L-band frequencies. [ABSTRACT FROM AUTHOR]

This article reviews the development of digital twin and summarizes the evolution of the concept of digital twin. The key words and abstracts of 1187 relevant papers in recent 5 years are quantitatively analyzed, and 13 key nodes are obtained. Then it analyzes the content of 9 systematic review articles and summarizes 15 core contents. Then select 115 application examples from the articles. Through the above three steps, nine descriptive general characteristics of digital twin system are summarized: Entity object; Virtual object; Twinning degree; Communication; Data; Functionality; Human-computer interaction; systematicness; and Cost control. This paper will explain these features in detail and summarize the application examples of classifying each feature. This paper aims to summarize the development of digital twin in recent years and propose a description method of system characteristics according to the application scenario of digital twin and the increasingly complex situation of the system. [ABSTRACT FROM AUTHOR]

Copyright of Military Technical Courier / Vojnotehnicki Glasnik is the property of Military Technical Courier / Vojnotehnicki Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nyquist-Shannon sampling principles extract Discrete-Time (DT) signals from Continuous-Time (CT) signals and are crucial in all Digital Signal Processing (DSP) areas, both in purely Discrete-Time (DT) systems and in processed signals as DT signals or CT analog signals. Multi-rate signal processing makes use of down-sampling, up-sampling, compression and expansion in many applications. Our work in this paper aims to highlight the mathematical models of multi-rate signal processing concepts on down/up sampling, multi-state and poly-phase decompositions for DSP and digital communications. We formulate and graphically illustrate the mathematical models in a case study of the analysis of multi-rate signal processing. [ABSTRACT FROM AUTHOR]

The positive contributions that small and medium-sized enterprises (SMEs) make in the iron and mining industries are vital for the development of the global economy. However, their costly operations in disadvantaged regions and the green economy interests of financial institutions have made them face more financial obstacles that decrease their export and financial performance. In this regard, their ability to use marketing communication tools that are included in the dynamic capability of Resource-based View theory (RBV) can reduce their exporting and financial performance concerns. This is because using these marketing communication tools presents them with less costly marketing solutions and provides competitive advantages for SMEs against their larger-sized rivals. In this regard, this paper aims to analyze the impact of one-way (telemarketing, direct mail, website, etc.) and two-way marketing communication tools (social media platforms) on SMEs' export intention and financial performance from the iron and mining industries. The research team collected data from 1221 SMEs operating in Eastern European countries via an internet-mediated questionnaire to hit this target. The impacts of the marketing communication tools on export intention and financial performance are analyzed via the Binary Logistic Regression Test. The results show that while using one-way and two-way marketing communication tools does not affect the export intention of SMEs, it negatively affects their financial performance. The reason for these results might be related to the location and sector in which SMEs operate. [ABSTRACT FROM AUTHOR]

Copyright of ModaPalavra e-periódico is the property of Universidade do Estado de Santa Catarina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is a response to a comment made by Robertas Damaševičius regarding an article on info-autopoiesis and artificial general intelligence (AGI). The response addresses specific points raised in the comment and clarifies the author's position. It emphasizes that info-autopoiesis, the self-creation of information, is fundamental only to humans and not achievable by artificial creations. The article argues for the impossibility of achieving AGI using info-autopoiesis and suggests that resources should be directed towards more achievable goals in AI. The response also discusses the relationship between biological aspects of human intelligence and AI research, highlighting the use of neural networks and considering the architecture of AGI. It concludes by stating that info-autopoiesis sets a limit to human knowledge based on fundamental principles and that all human creations are syntactic and incapable of semantic interpretation. The text discusses the concept of info-autopoiesis and its application to AI research. Info-autopoiesis is a framework that aims to explain how living organisms function, and the paper explores its potential implications for AI and AGI development. The author acknowledges the limitations of info-autopoiesis and emphasizes the need for interdisciplinary collaboration and ethical considerations in AI research. The text concludes by suggesting areas for further research and expressing gratitude for the comments and suggestions provided by Robertas Damaševičius. [Extracted from the article]

In this paper we discuss the creation of the Stephen Hawking Archive through processes of collaboration, and human and technological mediation. We focus on the production of documents including scientific and popular writings, correspondence and lectures in different media and forms of communication from handwriting, diagrams and typing to word processing and digital communication. We consider these processes to think about what is important in the Stephen Hawking Archive, including where authorship is located, and what this shows about scientific collaboration and communication in the late twentieth and early twenty-first century. We also briefly consider how archivists have mediated the Archive since it was received by Cambridge University Library (CUL) in 2021 through its arrangement and description, and we look forward to developing the Archive in the future, including the possibility of acquiring further digital files to include in the Archive. [ABSTRACT FROM AUTHOR]

This paper first presents six (6) types of benchmark amplitude design specifications, including variable low-pass specification, variable high-pass specification, variable bandpass specification, variable bandstop specification, variable notch-frequency specification, and variable notch-width specification. The design specifications can be taken as typical benchmark specifications targeted at testing as well as validating the effectiveness of various newly developed algorithms for designing various typical variable filters (VFs). Then, the paper provides a novel unity-bounded (UB) function developed for ensuring the stability of those VFs with recursive structures. Finally, a wide variety of simulation results are included for validating the design performance as well as the assured stability by using both the benchmark design specifications and the novel UB function. [ABSTRACT FROM AUTHOR]

The competition inside higher education institutions, namely universities, is tightening, putting emphasize on competitive intelligence (CI) function. At the same time, communication has shifted to digital channels, this trend was largely influenced by Corona virus pandemic. This presents a challenge for university reputation measurement and ranking, while the electronic word to mouth (E-wom) is more challenging to measure, control or influence than the issues measured in traditional university rankings. While traditional metrics are based on measuring academic reputation via surveys and gathering data from research organisations, this paper presents a way to include AI, namely chatGPT and big-data based media-analytics with social media sentiment to aid analysing the reputation of a University. Results based on Finnish universities indicate, that differences between media visibility and sentiment exist, and can be to some extent utilized in rating universities in local level and also generalize to global level, finally targeting to URS (University reputation score) -index. Due to complexity of measuring the reputation of the university strictly via AI and automated opinion mining, several limitations exist. The context of Finnish universities were chosen in order to limit the scope of the analysis. [ABSTRACT FROM AUTHOR]

This study investigates the multimodal potential of conference presentations for specialized knowledge dissemination purposes during the International Summit on Human Gene Editing. The methodological framework combines a genre perspective with a social semiotic reading of multimodal artefacts, focusing on the main canvas of analysis represented by the video recording of a PowerPoint-based conference presentation, with the parallel corpus of slides and commissioned papers. The study pursues the aim to assess how different semiotic codes interact in the resulting multimodal artefact, and, specifically, how video recording of conference presentations contributes to the dissemination of scientific knowledge on human gene editing in slides and papers. The findings pinpoint the disappearance of elements typical of dissemination and popularization from the papers and the PowerPoint slides, and at the same time confirm that videos provide adaptive choices for integrating different modes for the fullest knowledge dissemination attempt, with some minor technical shortcomings. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to provide a systematic review of omni-channel marketing (OCM) literature and explore how it relates to business-to-business (B2B) marketing campaign development in the digital era. OCM's evolution is tracked, exposing the areas in which research is most prevalent while also recognising knowledge gaps. Informed by these literature insights, the changing B2B channel dynamics that present within a digital era customer journey are appraised. An OCM model for B2B marketing campaign development is produced and avenues to further research are presented. Design/methodology/approach: This paper uses a systematic approach to explore OCM literature. This review informs an OCM model for B2B marketing campaign development to help advance conceptualisation of OCM B2B customer engagement as an emerging phenomena in the digital era. Findings: With just 21 papers identified, OCM is assumed to fit the criteria of an emerging concept as proposed in previous research studies. The proposed model presents the changing B2B omni-channel dynamics that can be used to create B2B OCM strategies, incorporating the myriad of B2B customer channels and touchpoints currently fabricating the modern B2B marketing terrain. Research limitations/implications: Conceptual in nature, there is a need for more empirical research to fully comprehend the emerging OCM landscape and how it relates to B2B customer dynamics. Originality/value: This research provides much-needed conceptualisation of data capture and management strategies for B2B marketing campaign development across the omni-channel in the digital era. While systematic literature reviews exist within the OCM realm, none have charted the current OCM literature. [ABSTRACT FROM AUTHOR]

Knowledge diffusion in regional innovation ecosystems is an important factor that influences the regional innovation efficiency. In regional innovation ecosystems under digital empowerment, the knowledge diffusion enables the optimal allocation of innovation resources and promotes the sustainable development and ecological evolution of regional innovation ecosystems. In this paper, a SEIR (Susceptible–Exposed–Infected–Recovered) model is proposed for knowledge diffusion in regional innovation ecosystems under digitization. The basic reproduction number of the proposed model is calculated and its stability is validated. Finally, the expressions for the optimal control system and the optimal control parameters are presented. According to the research conclusions of this paper, the knowledge-diffusion ability of innovation agents in an innovation ecosystem affects the knowledge diffusion in a system; the contact rate between innovation agents affects the efficiency of knowledge diffusion in the system and the structure of the system; the digital transmission ability of innovation agents affects the breadth of knowledge diffusion in the system; and the self-learning ability of innovation agents affects the efficiency of knowledge diffusion in the system.The digital technologies help heterogeneous innovation agents in regional innovation ecosystems to break down the knowledge silos. At the same time, the digital technologies enhance the ability of innovation agents to absorb and learn knowledge in regional innovation ecosystems under digitization, thereby increasing the infection rate of knowledge diffusion in such systems.These conclusions extend the theoretical boundaries of innovation ecosystems and knowledge diffusion and offer management implications for enterprises and governments in decision-making. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach to enhancing multi-level security using steganography, a method of concealing information within non-secret data. This paper introduces an innovative approach to multi-level security enhancement using steganography, the art of concealing information within non-obvious data. Our proposed method uniquely combines Dynamic Least Significant Bit (DLSB) steganography with Wavelet Obtained Weights (WOW) steganographic algorithms, forging a sophisticated and adaptable system for secret data embedding. In our enhanced approach, we start by embedding text into an image using an optimized version of DLSB steganography. This refined technique adapts intelligently to the image's local contrast, thereby preserving its visual quality and ensuring the integrity of the embedded information. Subsequently, the payload image is merged with a cover image through the WOW algorithm. This step optimally selects pixels for data embedding, creating a steganographic image that is virtually indistinguishable from the original. The novelty of our work lies in the seamless integration of these two advanced steganographic techniques, which significantly elevates the security and invisibility aspects beyond the current state-of-the-art methods in digital steganography. For validation, we utilized a pretrained MobileNet model to differentiate between original and stego images. This model plays a crucial role in demonstrating the indetectability of our method, achieving an impressive accuracy of 85% in distinguishing stego images from their originals. Our rigorous testing across various metrics — including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Bit Error Rate (BER), and Mean Squared Error (MSE) — showcases the effectiveness of our approach. The results indicate a robust performance, marking a significant advancement in secure digital communication. In this paper, we focus primarily on the detailed presentation of our results and the significant contributions of our current research, setting a strong foundation for future exploration in increasing robustness against steganalysis and improving the statistical invisibility of the steganography process. [ABSTRACT FROM AUTHOR]

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parallel processing capabilities of modern central processing units (CPUs), namely the availability of multiple cores and multithreading. The proposed multi-threaded implementations for computing DKraP coefficients divide the computations into multiple independent tasks, which are executed concurrently by different threads distributed among the independent cores. This multi-threaded approach has been evaluated across a range of DKraP sizes and various values of polynomial parameters. The results show that the proposed method achieves a significant reduction in computation time. In addition, the proposed method has the added benefit of applying to larger polynomial sizes and a wider range of Krawtchouk polynomial parameters. Furthermore, an accurate and appropriate selection scheme of the recurrence algorithm is introduced. The proposed approach introduced in this paper makes the DKraP coefficient computation an attractive solution for a variety of applications. [ABSTRACT FROM AUTHOR]

The paper purpose is to explore the feelings of exclusion and anger expressed on digital platforms by a community of women identifying within the Femcel subculture. The term "Femcel" is a portmanteau of "female" and "incel" (involuntary celibate), referred to women unable to obtain romantic or sexual relationships despite their desires and efforts. This sense of frustration, within the realm of digital communications, is heightened by the architecture of platforms, which reinforces and perpetuates existing power hierarchies, confining individuals within echo chambers. This paper analyses the most important online Femcel communities on Reddit, named "Vindicta", through digital ethnography facilitated by the NVivo software. The body of academic literature addressing women's distress to sexual inadequacy is insufficient; conversely, male Incels have garnered scholarly and journalistic attention for their lack of sexual capital. The study has underscored that despite Incel women being considered unattractive and "undesirable", they lament the lack of authorization to lay claim to an identity based on this state of abjection. This is due to the presumption that any woman could seduce a man if she really wanted to, consequently disregarding the recognition of the Femcel figure as a legitimate identity, in contrast to the treatment of male Incels. [ABSTRACT FROM AUTHOR]

The ever-growing threats in cybersecurity growing with the rapid development of quantum computing, necessitates the development of robust and quantum-resistant cryptographic systems. This paper introduces a novel cryptosystem, Public Key Cryptosystem based on Systematic Polar Encoding (PKC-SPE), based on the combination of systematic polar encoding and public-key cryptographic principles. The Systematic Polar Encoding (SPE), derived from the well-established field of polar codes, serves as the foundation for this proposed cryptographic scheme. Here, we have used MATLAB Software to introduce and implement the PKC-SPE Cryptosystem. The paper examines key generation, encryption, and decryption algorithms, providing insights into the adaptability and efficiency of systematic polar encoding in public-key cryptography. We assess the efficiency of the PKC-SPE Cryptosystem in three aspects: key size, computational complexity, and system implementation timings. In addition, we compare the PKC-SPE Cryptosystem with PKC-PC cryptosystem and find that it has reduced key sizes ( P r = 0.8436 kbytes). The results obtained through simulations validate the effectiveness of the proposed cryptosystem and highlighting its potential for integration into real-world communication systems. Thus, in the paradigm shift to quantum computing, the PKC-SPE cryptosystem emerges as a promising candidate to secure digital communication in the quantum computing era. [ABSTRACT FROM AUTHOR]

Digital financial inclusion and common prosperity are pivotal elements in promoting the sustainable socioeconomic development of China. This study introduces a novel Multi-Criteria Decision Analysis (MCDA) method to evaluate the Common Prosperity Index (CPI). Using this index, alongside the Digital Financial Inclusion Index (DFII) released by Peking University, it examines the evolution of the coupling coordination relationship between digital financial inclusion and common prosperity within the Yangtze River Delta (YRD) urban agglomeration from 2011 to 2021. By integrating gravity models and social network analysis, in this paper, we thoroughly investigate the spatiotemporal evolution characteristics of the spatial network of this coupling coordination relationship. The results indicate that both the DFII and CPI generally exhibit an upward trend, but the decline in the coupling degree reflects a weakened interaction strength between them. Specifically, Anhui significantly lags behind Jiangsu, Zhejiang, and Shanghai in the development of digital financial inclusion and common prosperity, indicating regional development imbalances. Furthermore, the strength of spatial connections in city coupling coordination has significantly increased, with Nanjing's siphon effect on cities in Anhui becoming markedly stronger, and the number of core cities in the network increasing, which demonstrates a geographical proximity feature in network development. Additionally, the overall network characteristics are transitioning towards higher density and "small-world" properties, suggesting a trend toward network stabilization. The disparity in centrality among cities has decreased, with an overall enhancement in centrality, where the spatial spillover effects from core areas such as Hangzhou-Ningbo, Nanjing-Changzhou, and Shanghai-Suzhou-Wuxi significantly promote the development of peripheral cities. Based on these findings, this paper proposes policy recommendations for the sustainable development of digital financial inclusion and common prosperity in the YRD region. [ABSTRACT FROM AUTHOR]

In the ever-evolving landscape of digital marketing, the role of social media in shaping effective communication strategies is paramount. This research paper delves into the world of data-driven insights to examine how social media channels contribute to the success of digital communication efforts. This paper focuses on exploring the multifaceted aspects of social media's impact on brand visibility, engagement, and customer interaction. The data was analyzed quantitatively using descriptive statistics while Analysis of Variance was used to establish associations between variables. The study revealed that major factors influencing the social media's effectiveness in digital communication are Content, Customer Interaction and Social Media metrics. As a result of comprehensive analysis, this research paper not only provides valuable insights into the current state of social media's effective-ness in digital communication but also offers practical recommendations for businesses looking to optimize their social media strategies. In an era where data reigns supreme, this research findings serve as a guide for harnessing the power of social media as a dynamic and influential tool in the digital communication arsenal. [ABSTRACT FROM AUTHOR]

This paper addresses the scientific production of pharmaceutical communication in Spain around the COVID-19 crisis, in which information overload, amplified by the digital media, evidenced the relevance of communication in the digital society. The research observes the evolution and characteristics of such studies, identifying scientific fields and disciplines related to communication, thematic lines, agents and publics. To this end, it proposes an exploratory review study adjusted to the PRISMA protocol with a search strategy including three databases (Scopus, WOS and Dialnet) and whose filtration produced a final population of 56 publications on Spanish pharmaceutical communication between 2018 and 2022. The results point to a greater production of scientific papers around the year of the pandemic. These papers were published by university institutions in health sciences journals, although differences in authorship by gender were detected. Most of them are empirical papers, with a predominance of mixed content analyses. The field of public relations stands out, but terminological confusion was also detected. This leads to a reflection on its causes and solutions in favour of the transparency and accountability in pharmaceutical communication. [ABSTRACT FROM AUTHOR]

Digital notch filters are useful for removing sinusoidal signals with a single frequency or multi-frequencies. For some applications, the sinusoidal signals being processed may change frequencies, and thus the notch filter must also have a variable notch frequency. Such a digital filter with a variable notch-frequency (VNF) is called variable notch-frequency (VNF) digital filter. Generally speaking, a VNF filter has the ability to change its notch frequency continuously, and can remove sinusoidal signals with variable frequencies. To design a recursive VNF filter, guaranteeing its stability is the top-priority issue. In this paper, a recursive VNF filter is designed by utilizing the least Lp-norm criterion, and the stability is guaranteed through adopting the stability-guarantee methodology based on parameter transformations. To perform the parameter transformations, a function that meets a special condition is required, and such a function is called unity-bounded function. In this paper, various unity-bounded functions are developed for the parameter-transformation-based stability guarantee. The unity-bounded functions play a crucial role in the stability guarantee. This paper details how to design a stable VNF filter by incorporating the parameter transformations employing the unity-bounded functions into the Lp-norm minimization of the magnitude response. Theoretically, the stability of the recursive VNF filter resulting from the design is definitely guaranteed. Moreover, since the coefficients of the designed VNF are variable, changing the filter coefficients enables the user to get a VNF filter with updated notch frequency. [ABSTRACT FROM AUTHOR]

In order to improve the digital communication effect of Chinese classic literary works, this paper combines virtual reality technology to carry out the digital system design of Chinese classic literary works, improve the digital design effect of Chinese classic literary works, and develop an augmented reality interaction method based on the HoloLens platform. Moreover, this paper analyzes the lighting model in computer graphics and the rendering process of three-dimensional objects in combination with the digitization requirements of literary works and realizes the rendering of special effects by customizing the lighting model in the shader. The research shows that the digital design system of Chinese classic literary works based on virtual reality technology proposed in this paper has a good effect on the digital protection of Chinese classic literary works. [ABSTRACT FROM AUTHOR]

The grid terminal deploys numerous types of communication equipment for the digital construction of the smart grid. Once communication equipment failure occurs, it might jeopardize the safety of the power grid. The massive amount of communication equipment leads to a dramatic increase in fault research and judgment data, making it difficult to locate fault information in equipment maintenance. Therefore, this paper designs a knowledge-graph-driven method for intelligent decision making on power communication equipment faults. The method consists of two parts: power knowledge extraction and user intent multi-feature learning recommendation. The power knowledge extraction model utilizes a multi-layer bidirectional encoder to capture the global features of the sentence and then characterizes the deep local semantics of the sentence through a convolutional pooling layer, which achieves the joint extraction and visual display of the fault entity relations. The user intent multi-feature learning recommendation model uses a graph convolutional neural network to aggregate the higher-order neighborhood information of faulty entities and then the cross-compression matrix to solve the feature interaction degree of the user and graph, which achieves accurate prediction of fault retrieval. The experimental results show that the method is optimal in knowledge extraction compared to classical models such as BERT-CRF, in which the F1 value reaches 81.7%, which can effectively extract fault knowledge. User intent multi-feature learning recommendation works best, with an F1 value of 87%. Compared with the classical models such as CKAN and KGCN, it is improved by 5%~11%, which can effectively solve the problem of insufficient mining of user retrieval intent. This method realizes accurate retrieval and personalized recommendation of fault information of electric power communication equipment. [ABSTRACT FROM AUTHOR]

This paper proposes an all-digital calibration algorithm that utilizes a reference channel to suppress the timing mismatch in the Time-Interleaved Analog-to-Digital Converter (TIADC). The output of the reference channel is aligned with each sub-channel in turn, therefore enabling the simultaneous sampling and conversion of the same input signal. First, the statistical characteristics across the channels are employed for estimating the timing mismatch; then, by comparing the output difference between the reference channel and the sub-channels that are sampled simultaneously, the deviation of the derivator can be calibrated. Finally, combining both calibration results yields an accurate final output. This proposed algorithm provides an effective solution to improve TIADC performance in high-speed data acquisition systems. The proposed architecture is applied to a 12-bit 2.4 GS/s four-channel TIADC model, and then its effectiveness is verified. The simulation results exhibit that the Effective Number Of Bits (ENOB) at an input signal frequency of 984 MHz shows a remarkable improvement from 6.88 bits to 11.92 bits. The effectiveness of this technique is also demonstrated through the off-chip calibration of a commercial 12-bit four-channel 2 GS/s TIADC using a 680 MHz input signal that is based on the actual chip results. [ABSTRACT FROM AUTHOR]

In order to improve the effect of English classroom teaching, this paper builds an immersive teaching model of English classroom based on IoT networks and digital twin technology. Moreover, in order to reduce the cost of the system, simplify the system structure, and enable learners to observe the stereoscopic display image with the naked eye, this paper builds an immersive hemispherical projection teaching system, designs the overall structure of the system and various components of the hardware, and studies the projection image predistortion algorithm. In addition, this paper uses the immersive experience between virtual reality technology and immersive teaching as a connection point to design an immersive teaching based on VR and apply it to teaching practice to test the effect of immersive teaching, and perfect the immersive teaching design model based on VR. Finally, this paper designs an experiment to verify and analyze the performance of the system. The experimental results show that the English classroom immersive teaching model based on digital twin technology constructed in this paper is effective. [ABSTRACT FROM AUTHOR]

Despite the huge advances in digital communications in the last decade, physical documents are still the most common media for information transfer, especially in the official context. However, the readily available document processing devices and techniques (printers, scanners, etc.) facilitate the illegal manipulation or imitation of original documents by forgers. Therefore, verification of the authenticity and detection of forgery is of paramount importance to all agencies receiving printed documents. We suggest an unsupervised forgery detection framework that can distinguish whether a document is forged based on the spectroscopy of the document's ink. The spectra of the tested documents inks (original and questioned) were obtained using laser-induced breakdown spectroscopy (LIBS) technology. Then, a correlation matrix of the spectra was calculated for both the original and questioned documents together, which were then transformed into an adjacency matrix aiming at converting it into a weighted network under the concept of graph theory. Clustering algorithms were then applied to the network to determine the number of clusters. The proposed approach was tested under a variety of scenarios and different types of printers (e.g., inkjet, laser, and photocopiers) as well as different kinds of papers. The findings show that the proposed approach provided a high rate of accuracy in identifying forged documents and a high detection speed. It also provides a visual output that is easily interpretable to the non-expert, which provides great flexibility for real-world application. [ABSTRACT FROM AUTHOR]

This paper proposes an automatic air-to-ground (A2G) channel model selection method based on machine learning (ML) using digital surface model (DSM) terrain data. In order to verify whether a communication network for a new non-terrestrial user service such as Urban Air Mobility (UAM) satisfies the required performance, it is necessary to perform a simulation reflecting the characteristics of the corresponding terrain environments as accurately as possible. For this simulation, A2G channel models corresponding to various terrain environments and a method of automatically classifying the terrain type of the simulation area must be provided. Many A2G channel models based on actual measurement results exist, but the practical automatic topography classification method still needs to be developed. This paper proposes the first practical automatic topography classification method using a two-step neural network-based classifier utilizing various geographic feature data as input. Since there is no open topography dataset to evaluate the accuracy of the proposed method, we built a new dataset for five topography classes that reflect the characteristics of Korea's topography, which is also a contribution of our study. The simulation results using the new data set show that the proposed ML-based method could increase the selection accuracy compared to the technique for direct classification by humans or the existing cross-correlation-based classification method. Since the proposed method utilizes the DSM data, open to the public, it can easily reflect the different terrain characteristics of each country. Therefore, the proposed method can be effectively used in the realistic performance evaluation of new non-terrestrial communication networks utilizing vast airspace such as UAM or 6G mobile communications. [ABSTRACT FROM AUTHOR]

Long period digital random sequence plays an important role in reliable communications and high security scenarios. This paper improved the method of generating long period digital random sequences based on the Residue Number System (RNS) and the Chinese Remainder Theorem (CRT), and a sequence mapping method after CRT extension. This paper proves that the period of sequence after mapping will not degenerate if the modulus used in the mapping stage is coprime with the period of the original sequence. By using the parallelism of RNS, the proposed method can generate sequences at high speed with fewer hardware resources. The NIST test results show that the pass rate of each test item is above 98.40%, which meets the NIST test confidence requirements, confirming the randomness of the generated sequences. An image encryption test is given as one of the example applications of the generated sequences. On the theoretical basis, by jointly optimizing the sequence mapping and iteration procedure, a hardware implementation architecture is also presented in this paper. The implementation is based on Xilinx XC7Z020CLG484-3 FPGA and compared with the implementations of classical chaotic maps. The results show that the proposed architecture has longer sequence period with less hardware resource consumption and higher generation speed and is more general. Meanwhile, the proposed architecture has fast phase switching ability, which is about 10 clock periods. This is one of the key attributes when the sequence is used in communication systems. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? First, the combination of the methods of machine learning with psychological methods to predict the user's OCEAN personality model could achieve a higher accuracy; Second, the model proposed in this paper that is a combination of LDA plus BP neural network is generally superior to the combination model of the same type. What is the implication of the main finding? First, through digital footprints and understanding the rules of user behavior, user behavior can be predicted and targeted recommendations made; Second, it was found that predicting the user's OCEAN personality model and then their behavior can provide an effective method for micro-directional recommendations in network communication. In the era of big data, the Internet is enmeshed in people's lives and brings conveniences to their production and lives. The analysis of user preferences and behavioral predictions of user data can provide references for optimizing information structure and improving service accuracy. According to the present research, user's behavior on social networking sites has a great correlation with their personality, and the five characteristics of the OCEAN (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) personality model can cover all aspects of a user's personality. It is important in identifying a user's OCEAN personality model to analyze their digital footprints left on social networking sites and to extract the rules of users' behavior, and then to make predictions about user behavior. In this paper, the Latent Dirichlet Allocation (LDA) topic model is first used to extract the user's text features. Second, the extracted features are used as sample input for a BP neural network. The results of the user's OCEAN personality model obtained by a questionnaire are used as sample output for a BP neural network. Finally, the neural network is trained. A mapping model between the probability of the user's text topic and their OCEAN personality model is established to predict the latter. The results show that the present approach improves the efficiency and accuracy of such a prediction. [ABSTRACT FROM AUTHOR]