Advances In Communication Technologies Research Articles

Peran Media Sosial Instagram Sebagai Media Promosi Objek Wisata Tankayo Eco Park

This study aims to determine the Role of Instagram Social Media as a Promotional Media for Tankayo Eco Park Sharia Malalo Tourism Object. Role is defined as having a positive meaning and is expected to be able to influence or achieve company goals. The role of Instagram social media is carried out as a result of advances in communication and internet technology which have caused significant changes in consumer behavior in seeking information. To describe this research using the AISAS theory created by Dentsu, 2005, there are 5 elements in this model, namely attention, interest, search, action, and share. This research uses qualitative methods through observation, interviews and documentation. The results showed that the management of the Tankayo Eco Park Syariah tourist attraction made Instagram the main platform in carrying out its promotional activities. Instagram social media acts as a promotional media for Tankayo Eco Park Syariah attractions by posting content in the form of photos and videos to introduce Tankayo to potential visitors carried out by the Instagram admin. Tankayo Eco Park Syariah also receives free promotions obtained through the Instagram accounts of visitors who create content and tag Tankayo Eco Park Syariah Instagram. The use of Instagram social media by Tankayo Eco Park Syariah is able to attract visitors to come directly to the attraction

Person's Temperament and Character Type Detection Based on Modern Information and Communication Technologies

The popularity of e-learning systems is growing because of their effectiveness. It is necessary to adjust learning/training scenarios for every trainee, using advanced information and communication technologies (ICT) tools to achieve this. However, it is not often respected that people have different perceptions of information. A learning system should consider the temperament and character of an applicant/trainee. Since people with the same temperament have approximately the same ability to perceive and process information, as well as similar labour skills, the learning system must first determine the applicant's temperament and after that, based on this, determine how long it will take him to absorb a certain amount of information from the training course. Testing is used for recognition of the applicant’s temperament. But traditional tests–questionnaires are long and the applicant can manipulate with answers. Apart from those, there are other types of tests: color tests, picture tests, figures tests, drawing tests, etc. The advantage of such tests is that they are based on the subconscious processes and thus, are more free from manipulations with answers, take far less time, and less depend on the mood swings. Moreover, according to S. Dellinger, the applicant's temperament type represents a fuzzy set, because a person has one dominant temperament and one secondary temperament, with relevantly different credibility levels. This means, that the determination of a person’s temperament should be implemented in a fuzzy environment, not in a classical environment. For this reason, we want to implement the first part of the teaching system, using this paper. Particularly, we aimed to create a quick and free-from-manipulations test-program, which would allow, determine the type of applicant’s temperament for e-learning individualization needs and determin the innate working skills. The specific fuzzy method is applied. The program was successfully tested on different people.

A Study on a Radio Source Location Estimation System Using High Altitude Platform Stations (HAPS).

Currently, there is a system in Japan to detect illegal radio transmitting sources, known as the DEURAS system. Even though crackdowns on illegal radio stations are conducted on a regular basis every year, the number of illegal emission cases still tends to increase, as ordinary citizens are now able to handle advanced wireless communication technologies, e.g., via software-defined radio. However, the current surveillance system may not be able to accurately detect the source in areas where large buildings are densely packed, such as urban areas, due to the effects of reflected waves. Therefore, in this study, we proposed a system for estimating the location of the source of transmission using a high-flying unmanned aerial vehicle called HAPS. The simulation results using numerical analysis software show that the proposed system can estimate the location of the source over a wider area and with higher accuracy than conventional monitoring systems.

Telecom-band multiwavelength vertical emitting quantum well nanowire laser arrays

Highly integrated optoelectronic and photonic systems underpin the development of next-generation advanced optical and quantum communication technologies, which require compact, multiwavelength laser sources at the telecom band. Here, we report on-substrate vertical emitting lasing from ordered InGaAs/InP multi-quantum well core–shell nanowire array epitaxially grown on InP substrate by selective area epitaxy. To reduce optical loss and tailor the cavity mode, a new nanowire facet engineering approach has been developed to achieve controlled quantum well nanowire dimensions with uniform morphology and high crystal quality. Owing to the strong quantum confinement effect of InGaAs quantum wells and the successful formation of a vertical Fabry–Pérot cavity between the top nanowire facet and bottom nanowire/SiO2 mask interface, stimulated emissions of the EH11a/b mode from single vertical nanowires from an on-substrate nanowire array have been demonstrated with a lasing threshold of ~28.2 μJ cm−2 per pulse and a high characteristic temperature of ~128 K. By fine-tuning the In composition of the quantum wells, room temperature, single-mode lasing is achieved in the vertical direction across a broad near-infrared spectral range, spanning from 940 nm to the telecommunication O and C bands. Our research indicates that through a carefully designed facet engineering strategy, highly ordered, uniform nanowire arrays with precise dimension control can be achieved to simultaneously deliver thousands of nanolasers with multiple wavelengths on the same substrate, paving a promising and scalable pathway towards future advanced optoelectronic and photonic systems.

On Development of a SIM-Based Prototype for Enhancing the Usability of Mobile Value-Added Services

The advent of Mobile Value-Added Services (VAS) has witnessed widespread adoption in developing regions, notably within East Africa. This surge is attributed to advancements in information and communication technology, 3G/4G proliferation, growth of mobile internet accessibility, and rising smartphone penetration. Despite this progress, a significant segment of the population continues to rely on basic phones. Studies have shown that the text-based applications used on these types of mobile phones still pose significant obstacles in delivering a user-friendly VAS experience. This paper explores the potential for improving the usability of mobile value-added services on basic phones. We employed an action research approach, utilizing quantitative and qualitative data collection methods. Questionnaires gathered feedback on end-user testing, while in-depth interviews with five industry experts provided insights into potential solutions. This multi-faceted approach ensures a comprehensive understanding of user feedback and expert insights, culminating in the design of an intuitive SIM-based user interface prototype. This highly customised prototype prioritises services and functionalities simplify the user experience through improved navigability and accessibility. The effectiveness of this prototype was quantitatively analysed using descriptive statistics, focusing on ease of use, efficiency, effectiveness, and user satisfaction. With an average ease of use score of 85.8%, a geometric mean time on task of 29.43 seconds, and a user satisfaction score of 79.5%, the prototype demonstrates impressive functionality and garners acclaim for improved navigation and information discovery from users and experts. Further, comparative analysis from expert interviews reveald a more nuanced understanding of technology preferences for basic phone usability, contrary to previous studies. Building upon these demonstrably positive results, the paper concludes by advocating for user interface standardisation and recommending user-generated content for a more inclusive VAS ecosystem.

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.