Advances In Communication Technologies Research Articles

Agile technology planning : Embracing change to improve the hybrid workplace experience

In the evolving landscape of hybrid work environments, organisations face the challenges of bridging the gap between remote and in-office employees and attracting a younger workforce while adapting to the rapid pace of technological change. This paper presents a comprehensive strategy for creating effective hybrid workspaces prioritising connectivity, collaboration and digital equity. Central to this strategy is integrating appreciative inquiry principles with agile process management tools, aiming to foster a culture of innovation and inclusion. The demographic shift towards a younger, tech-savvy workforce, alongside the continuous advancement in communication technologies, necessitates a new approach to workplace design and technology integration. The paper outlines a roadmap for organisations to navigate the complexities of the hybrid work model, ensuring a connected and empowered workforce.

Transformative Shifts: From Puritanical Rigidities to Cosmopolitan Flexibilities in Islamic Education

This journal explores the evolving dynamics within Islamic educational paradigms in the context of increasing global interconnectedness. The study investigates the transition from rigid, puritanical educational models, which emphasize strict adherence to traditional interpretations and practices, towards more flexible, cosmopolitan approaches that accommodate diversity, inclusivity, and global perspectives. Through a comprehensive literature review and qualitative analysis of case studies from various Islamic educational institutions worldwide, the research identifies key factors driving this shift. These include the influence of globalization, advancements in information and communication technologies, and the growing recognition of the need for educational systems that prepare students for the complexities of a pluralistic world. The article argues that embracing cosmopolitan flexibility in Islamic education does not necessitate the abandonment of core religious values. Instead, it advocates for a balanced approach that integrates traditional Islamic teachings with contemporary pedagogical methods and curricula that promote critical thinking, intercultural understanding, and ethical reasoning. By highlighting successful examples of transformative educational practices, the study aims to provide a framework for policymakers, educators, and scholars to develop and implement educational models that reconcile the rich heritage of Islamic knowledge with the demands of modern, globalized societies. The findings suggest that such an approach not only enhances the quality and relevance of Islamic education but also fosters a more inclusive and cohesive global Muslim community.

Research on high-entropy spinel microwave absorption materials: Exploration of machine learning and experimental integration

With the advancement of electronic communication technology, the intensity of electromagnetic radiation is increasing, and traditional wave-absorbing materials no longer meet the demands in various current environments. Spinel ferrite is one of the earliest materials used for absorbing electromagnetic waves, and the introduction of "high entropy" and controlling the degree of entropy disorder can achieve performance regulation. Nonetheless, the lengthy testing period and high costs associated with trial and error have posed challenges, limiting the development of high entropy microwave absorbing materials. This study utilized machine learning techniques to construct a high-entropy spinel microwave absorption property database. The design of CoxNi0.4-xCu0.2Zn0.2Mn0.2Fe2O4 (X = 0, 0.1, 0.2, 0.3, 0.4) was informed by the SHAP plots of the GBR model. Machine learning demonstrates that factors such as cobalt and nickel content, particle size, and others significantly influence microwave absorption performance. The experimental result manifests it and Co content regulate the microwave absorbing performance through adjusting the defect density and particle size. The CoxNi0.4-xCu0.2Zn0.2Mn0.2Fe2O4 with optimized Co content achieved a reflection loss (RL) of −45.32 dB, and an effective absorption bandwidth (EAB) of 6.48 GHz. This approach significantly reduced the research period, presented a novel research methodology for other scholars, and expedited the research progress in the field of microwave absorbing materials.

A Sense of Belonging in Online Post-Traditional Students: What Matters?

Online education has experienced a rapid growth and continued to grow, which is driven by the advances in information and communication technologies that facilitate effective interactions both within and outside the online classroom in high education. Despite these advancements, post-traditional students, characterized by their diverse and complex identities, face unique challenges in forming connections within online learning environments. This research focuses on sense of belonging, which is crucial for promoting and consolidating online learning experiences. For post-traditional students, little is currently known about the extent to which they feel a sense of belonging and the factors that influence it. In this research study, we surveyed a sample of online post-traditional learners and used a mixed-methods approach to examine how they feel accepted and valued and how their identities such as academic program, gender, and ethnicity are related to belonging. Our findings indicate that post-traditional learners report an overall moderate level of belonging, with university support, acceptance, and meaningful relationships with faculty and staff being pivotal. Our research did not find significant differences between students in different academic programs or gender groups. However, Hispanic students reported a higher sense of belonging, which can be contextualized within the framework of our university’s designation as a Hispanic-Serving Institution (HSI). By pinpointing the critical and negligible factors affecting sense of belonging, this study provides a comprehensive set of actionable strategies to cultivate a more engaging and supportive online learning environment.

Data autonomy: beyond personal data abuse, sphere transgression, and datafied gentrification in smart cities

The ‘smart city’ has been driven by advances in information and communication technologies, with the aim of integrating these technologies with urban infrastructures for improved optimisation, automation and control. Smart cities have emerged as a response to the challenges faced by megacities and are likely to manifest the ‘datafying’ society in the public space. However, the pervasive nature of data collection, continuous analysis and inference, and long-term data storage result in a potentially problematic reconfiguration of society that undermines individual and collective autonomy. This article proposes the concept of ‘data autonomy’ as a guiding principle for the development of smart cities, addressing challenges related to the potential misuse of personal data, sphere transgression, and datafied gentrification. Section II. explores concerns related to data protection law, which can be understood as a proxy for the relationship between the individual and society, highlighting power dynamics and the autonomy of individuals and communities. Section III. discusses the concept of sphere transgression, where tech giants expand their influence in society without adequate expertise or accountability. Section IV. examines the potential impact of datafied gentrification on individual and collective autonomy. Building on the challenges identified throughout these sections, this paper proposes ‘data autonomy’ as a guiding principle for smart city development in section V., promoting a value-based approach centred on human dignity. To make it practicable, increased interdisciplinary collaboration in the development of smart cities is needed, with a particular focus on improved design and impact assessment methodologies.

The Urgency of Stakeholder Cyberspace Collaboration to Support Indonesia’s National Defense

In today's interconnected digital world, stakeholder collaboration in cyberspace is crucial for national defense. Advances in information and communication technology have transformed daily life but also introduced complex cyber threats like cyber warfare, cybercrimes, and cyber terrorism, challenging security and stability. The objective of this study is to emphasize the importance of collaboration among diverse stakeholders in enhancing national defense against cyber threats. The methodology involves analyzing existing literature and case studies to understand the impact of collaboration on cybersecurity maturity and national defense strategies. The research findings, derived from SWOT and PESTLE analyses, have highlighted the strengths and weaknesses in collaboration, underscoring the significance of leveraging strengths and addressing weaknesses to establish a robust defense framework. To enhance national defense against cyber threats, a holistic approach is essential, combining political collaboration, economic partnerships, social awareness programs, technological advancements, legal harmonization, and environmental resilience strategies. Key recommendations include fostering regular communication among stakeholders, pooling resources for cybersecurity investments, promoting cybersecurity education, integrating advanced technologies like AI and IoT security solutions, and aligning legal frameworks across jurisdictions.

Research on extremely low frequency electromagnetic wave model and simulation in wellbore communication

Over recent years, as digitalization and intelligence in oil wellbore have increased, so have the stricter requirements for wireless communication technology in terms of distance, accuracy, and portability. As a result, it’s necessary to rely on more advanced and efficient wireless communication technologies to meet the industry’s needs. However, traditional communication technologies such as cables and optical fibers have inherent shortcomings in construction, data interpretation, and cost. ELF electromagnetic waves are an ideal solution for communication in complex wellbore conditions due to long-distance communication and strong penetration capabilities, making it a highly effective option. Based on the theory of network splitting, this paper establishes a polygonal multiple-delays uncertainty coupled complex network model of ELF electromagnetic waves propagating through the casing in layered media and designs a controller, including expressions for the intensity of the magnetic and electric fields in different directions, and the propagation and distribution characteristics in different media. We determined that the optimal transmitting frequency of ELF electromagnetic waves under general conditions is 12.7 Hz. Based on field experiments, we verified that ELF electromagnetic waves can enable wireless wellbore communication within 1500 m without relays. We also analyzed the impact of casing thread deformation on ELF electromagnetic wave propagation due to high-temperature and high-pressure environments. We used simulation experiments to solve the distribution relationship between the electric and magnetic fields of the solenoids through casing and strata, as well as the coupling coefficients between the transmitting and receiving solenoids, and explore how different transmitting frequencies affect the efficiency of signal propagation. Both theories and experiments have verified the correctness of the model, and have also demonstrated the reliability and continuity of using ELF electromagnetic waves to achieve wireless wellbore communication, which provides a theoretical basis and feasibility for subsequent engineering applications.

Ambidextrous Leadership: Mitigating Turnover Intentions in Millennial Workforce

Introduction/Main Objectives: This study aims to decrease the intention of millennial employees to leave startup companies in Indonesia through the roles of Ambidextrous Leadership, Work-Life Balance, Career Development, and job satisfaction. Background Problems: The startup industry in Indonesia is rapidly growing alongside advancements in information and communication technology, yet still faces high turnover rates. Novelty: The uniqueness of this research lies in its focus on Ambidextrous Leadership, which combines exploration, exploitation, and flexibility, aligning well with the millennial generation's penchant for change and the development of new ideas in startup companies. Research Methods: This research adopts a quantitative method with a causal research design. A sample of 300 respondents is chosen through the snowball sampling technique. Data analysis involves utilizing SEM-PLS to examine the research hypotheses. Finding/Results: In the context of startup companies, Ambidextrous Leadership, Work-Life Balance, and Career Development play crucial roles in enhancing job satisfaction and reducing employee Turnover Intention. Conclusion: The managerial implication is that startup company leaders need to adopt an Ambidextrous Leadership approach, prioritize Work-Life Balance, and provide clear Career Development opportunities to retain talent and improve employee satisfaction.

A cellular automata based secured reversible data hiding scheme for dual images using bit-reversal permutation technique

With the rapid development of advanced communication technology, protection of confidential data during transmission through public channel has become a challenging issue. In this context, the design of a data hiding scheme needs to ensure reversibility, robustness against various malicious attacks, and unaltered visual quality even after embedding high amount of secret data. To meet the above requirements, Cellular Automata along with Bit-Reversal Permutation technique have been utilized on dual-image with the target to enhance the robustness of suggested scheme due to distribution of secret information within two stego images which is hard to extract without both stego simultaneously. The proposed scheme makes a trade-off among visual quality, security and embedding capacity as essential for ensuring innocuous communication. The experimental results and comparison with the state-of-art methods establishes that the proposed scheme ensures high degree of robustness against different venomous attacks. This approach may be beneficial to private and public sector practitioners and government agencies to protect valuable multimedia secret data from adversarial cyber attacks.

“Hello, It’s Me, Auntie Netta! I am Calling from Abroad”: Aunties and Digital Diasporas in Nimmi Harasgama’s Online Performances

The structure of diaspora in the twenty-first century cannot be fully understood without due attention to how diasporic relations to home are mediated by digital technologies. I suggest we must look in the direction of diasporic cultural production that utilizes such technologies to better understand how postcolonial spatiality is unmistakably commensurate with digital diasporas, or advancements in communication technologies that foster new cartographies. This study posits that the campy embodiment of the auntie figure by the Sri Lankan actress Nimmi Harasgama on YouTube (2009–2015) re-imagines diasporic affiliations to home/s by locating and encapsulating diaspora within circuits of digital connectivity. Harasgama’s YouTube alter-ego “Auntie Netta,” is an asylum-seeking diasporic character whose itinerary is makeshift. However, her communication with her friend “Gladys” via Skype calls remains constant. Both beyond and through the jest abundant in these clips, the calls remain an anchor to Netta’s historical sense of self and signify an embodied mapping of the transnational subjecthood occupied by both Netta and her creator, Harasgama. Through a close analysis of Harasgama’s performance and complication of the familiar figure of the auntie, I suggest that the digital diaspora is necessarily configured and co-constructed by the diasporic body, nostalgic memory, and digital connectivity.

Secure workflow scheduling algorithm utilizing hybrid optimization in mobile edge computing environments

The rapid advancement of mobile communication technology and devices has greatly improved our way of life. It also presents a new possibility that data sources can be used to accomplish computing tasks at nearby locations. Mobile Edge Computing (MEC) is a computing model that provides computer resources specifically designed to handle mobile tasks. Nevertheless, there are certain obstacles that must be carefully tackled, specifically regarding the security and quality of services in the workflow scheduling over MEC. This research proposes a new method called Feedback Artificial Remora Optimization (FARO)-based workflow scheduling method to address the issues of scheduling processes with improved security in MEC. In this context, the fitness functions that are taken into account include multi-objective, such as CPU utilization, memory utilization, encryption cost, and execution time. These functions are used to enhance the scheduling of workflow tasks based on security considerations. The FARO algorithm is a combination of the Feedback Artificial Tree (FAT) and the Remora Optimization Algorithm (ROA). The experimental findings have demonstrated that the developed approach surpassed current methods by a large margin in terms of CPU use, memory consumption, encryption cost, and execution time, with values of 0.012, 0.010, 0.017, and 0.036, respectively.

Factors influencing use of eHealth services during and after the COVID-19 pandemic.

The rapid advancement of information and communication technologies has made eHealth applications increasingly available and accessible. The COVID-19 pandemic has accelerated the need for remote health service provision. This research aims to explore the usage, perceptions, and knowledge of eHealth interventions during and after the COVID-19 pandemic. A cross-sectional survey was conducted in 2021 (during the pandemic) and 2023 (post-pandemic) using a structured questionnaire based on the Technology Acceptance Model (TAM) and the eHealth Literacy Scale (eHEALS). The survey, conducted in Greece, included 638 participants in total (277 in 2021 and 361 in 2023). Structural equation modeling was employed to assess the factors influencing eHealth adoption. The findings indicate a slight increase in positive perceptions of eHealth usefulness, intention to use, and actual usage over the 2years. However, concerns remain regarding the ease of use and eHealth literacy. eHealth literacy significantly predicts the perceived usefulness and ease of use of eHealth services, both of which predict the intention to use them. Additionally, higher education levels are positively associated with eHealth literacy, while older age is negatively associated with ease of use. Gender did not significantly impact these factors. These findings were consistent across both surveys. Policy-makers should focus on simplifying eHealth services, removing technical barriers, and enhancing the population's eHealth literacy to promote wider adoption of eHealth services.

A comparison between machine and deep learning models on high stationarity data

Advances in sensor, computing, and communication technologies are enabling big data analytics by providing time series data. However, conventional models struggle to identify sequence features and forecast accuracy. This paper investigates time series features and shows that some machine learning algorithms can outperform deep learning models. In particular, the problem analyzed concerned predicting the number of vehicles passing through an Italian tollbooth in 2021. The dataset, composed of 8766 rows and 6 columns relating to additional tollbooths, proved to have high stationarity and was treated through machine learning methods such as support vector machine, random forest, and eXtreme gradient boosting (XGBoost), as well as deep learning through recurrent neural networks with long short-term memory (RNN-LSTM) cells. From the comparison of these models, the prediction through the XGBoost algorithm outperforms competing algorithms, particularly in terms of MAE and MSE. The result highlights how a shallower algorithm than a neural network is, in this case, able to obtain a better adaptation to the time series instead of a much deeper model that tends to develop a smoother prediction.

Legal protection for informal sector workers in employment development in Indonesia: challenges and opportunities

This research aims to investigate, rationalize and identify the issue of legal protection for informal workers which is in the critical category. Therefore, this article is entitled Legal Protection for Informal Sector Workers in Employment Development in Indonesia: Challenges and Opportunities. The research method used is a normative juridical approach, document study, using qualitative methods in analyzing data and using secondary data as the source. The results of this research found that Law Number 6 of 2023 concerning the Determination of Government Regulations instead of Law Number 2 of 2022 concerning Job Creation into Law (Undang-Undang Nomor 6 Tahun 2023 tentang Penetapan Peraturan Pemerintah Pengganti Undang-Undang Nomor 2 Tahun 2022 Tentang Cipta Kerja Menjadi Undang-Undang or UU 6/2023) does not regulate informal workers at all, so there is a vacuum in terms of legal protection for informal workers in Indonesia. Therefore, national legislation is needed regarding legal protection for informal workers, which essentially contains work agreements between employers and informal workers/labourers. In this way, the government and the legislature are expected to be able to establish regulations and legislation to protect informal and vulnerable workers amidst the increasing informalization of the labour market due to the impact of accelerated advances in information and communication technology.

A Novel Deep Learning Approach for Real-Time Critical Assessment in Smart Urban Infrastructure Systems

The swift advancement of communication and information technologies has transformed urban infrastructures into smart cities. Traditional assessment methods face challenges in capturing the complex interdependencies and temporal dynamics inherent in these systems, risking urban resilience. This study aims to enhance the criticality assessment of geographic zones within smart cities by introducing a novel deep learning architecture. Utilizing Convolutional Neural Networks (CNNs) for spatial feature extraction and Long Short-Term Memory (LSTM) networks for temporal dependency modeling, the proposed framework processes inputs such as total electricity use, flooding levels, population, poverty rates, and energy consumption. The CNN component constructs hierarchical feature maps through successive convolution and pooling operations, while the LSTM captures sequence-based patterns. Fully connected layers integrate these features to generate final predictions. Implemented in Python using TensorFlow and Keras on an Intel Core i7 system with 32 GB RAM and an NVIDIA GTX 1080 Ti GPU, the model demonstrated a superior performance. It achieved a mean absolute error of 0.042, root mean square error of 0.067, and an R-squared value of 0.935, outperforming existing methodologies in real-time adaptability and resource efficiency.

False Data Injection Attack Detection, Isolation, and Identification in Industrial Control Systems Based on Machine Learning: Application in Load Frequency Control

The integration of advanced information and communication technology in smart grids has exposed them to increased cyber attacks. Traditional model-based fault detection systems rely on mathematical models to identify malicious activities but struggle with the complexity of modern systems. This paper explores the application of artificial intelligence, specifically machine learning, to develop fault detection mechanisms that do not depend on these models. We focus on operational technology for fault detection, isolation, and identification (FDII) within smart grids, specifically examining a load frequency control (LFC) system. Our proposed approach uses sensor data to accurately identify threats, demonstrating promising results in simulated environments.

Terrorism as a Transnational Crime that Threatens Indonesia

This paper aims to (1) analyze Indonesia's vulnerability against terrorism; and (2) analyze efforts to counter-terrorism in Indonesia. In compiling this paper, the author collected secondary data in the form of written documentaries, namely mass media articles, journal articles and relevant books. The study results indicate that terrorism is a transnational crime with a major threat to the nation and state. In Indonesia there have been several acts of suicide bombing terrorism in the name of religious teachings. Suicide bomb terrorists consider this to be a sacred duty that is obligatory and of great benefit to their group. Indonesia's vulnerability to terrorism is determined by demographic, geographic, economic and ideological factors. Advances in information and communication technology and the increase in the number of internet users in Indonesia can also provide opportunities for cyberterrorism to occur. In carrying out counter-terrorism, the Indonesian government implements pre-emptive, preventive and repressive efforts. One of the counter-terrorism programs that raises pros and cons in Indonesian society is the involvement of the TNI. According to the author, the TNI should only be involved in counter-terrorism assistance if the National Police and BNPT experience difficulties or obstacles. A military counter-terrorism approach has the potential to violate human rights, especially against parties who are merely suspected of having been exposed to radical ideology.

Wiki communities’ management tools in conditions of digitization

The rise of local and global challenges (such as COVID-19, wars, natural disasters, etc.) requires advanced communication and information technologies to support economic development. The study aims to form a theoretical basis and practical tools for creating and functioning of wiki communities. Wiki communities are a new form of social association based on Internet communications of socio-economic subjects (individuals and organizations), in which each participant has equal rights to receive information, exchange opinions, and generate solutions. The theoretical basis involves substantiating the key principles on which wiki communities are formed, e.g., decentralization, openness, peering, sharing, and mass nature of activity. Wiki communities are represented by a set of specific types, such as professional, academic and research, custom, creative, public and non-commercial communities. The specific managing activities of wiki communities are described by several classification levels, such as operational activities, ensuring security, quality assurance, and motivation. The wiki community management toolkit includes a goal-setting algorithm, decision-making procedures, communications, rules of operation, typical tasks, areas of application, the operation and development cycle, and functional capabilities. It allows effective transfer of information, communication in real-time, and mutually enriching each other in forming knowledge and innovation. AcknowledgmentThe publication was prepared in the framework of the research project “Restructuring of the national economy in the direction of digital transformations for sustainable development” (№0122U001232) from National Research Foundation.

Lifestyle construction on Instagram media on consumer behavior of students at the Faculty of Da'wah and Communication

ABSTRACT Teenagers' playtime and study time, especially students, are influenced by advances in communication technology, both positively and negatively. Students use social media to communicate with friends, share homework, play games, and/or fill their free time, to do college assignments. This study aims to examine how students of the Islamic Communication and Broadcasting Study Program at UIN Sumatera Utara use Instagram in their daily lives related to the wasteful behavior of students. The method used in the study is qualitative carried out through observation by conducting direct observations, interviews conducted through interaction, and documentation made in references from literature related to the focus of the study. The results of the study indicate that Instagram plays an important role in shaping the lifestyle of consumptive students. Students are often influenced by content that displays a luxurious lifestyle, which encourages them to shop for unnecessary items and try to display an ideal image on social media. This finding is consistent with the theory of social construction which states that social media users can create reality through interaction on the platform. This study highlights the use of Instagram social media which can influence student behavior that tends to be consumptive, although this is not entirely a problem caused by the presence of social media in the current era. Keywords: Social Media, Instagram, Behavior.

Design and performance evaluation of a compact radiation absorber for 5G applications

Introduction: The emergence of electromagnetic wave pollution as a new form of pollution in human society is attributed to the advancements in communication technology and the electronic information business. In addition to harming priceless electronic equipment, these electromagnetic radiation and interference issues brought on by electrical and electronic devices have a major negative influence on human productivity and wellbeing. The secret to getting rid of electromagnetic radiation interference (EMI) and improving performance is electromagnetic shielding technology. Metamaterial absorber is a type of metamaterial that absorb EMI radiation. The benefits of metamaterial absorbers include their lightweight, simple construction, and excellent absorptivity.Methods: This paper proposes a novel metamaterial absorber for EMI radiation absorption. It consists of dielectric layers, metamaterial shielding layer and transmission line. The reflection of radiation is reduced by miniaturization of metamaterials.Results and Discussion: Simulation results show that the proposed design has better performance as compared to existing methods. The operating frequency range is from 23.1 to 28.3 GHz. The values of S21 with and without shielding are −5 dB and −0.05 dB, and the shielding effectiveness is 10.10 dB and a maximum of 12.63 dB.