Internet Devices Research Articles

Continuous-Time Dynamic Graph Networks Integrated with Knowledge Propagation for Social Media Rumor Detection

The proliferation of the Internet and mobile devices has made it increasingly easy to propagate rumors on social media. Widespread rumors can incite public panic and have detrimental effects on individuals. In recent years, researchers have found that both the spatial structure of rumor diffusion and the temporal features of propagation can be effective in identifying rumors. However, existing methods tend to focus on either spatial structure or temporal information in isolation, and few models can effectively capture both types of information. Additionally, most existing methods treat continuously changing temporal information as static snapshots, neglecting the precise timing of propagation. Moreover, as users repost and comment, background knowledge associated with the posts also evolves dynamically, which is often ignored. To address these limitations, we propose CGNKP (Continuous-time Dynamic Graph Networks integrated with Knowledge Propagation), a model that jointly captures the spatial structure and continuous-time features of post propagation to fully understand the dynamics of background knowledge. Specifically, we introduce a novel method for encoding continuous-time dynamic graphs, modeling the propagation process through two dynamic graphs: a temporal propagation graph (for posts diffusion) and a temporal knowledge graph (for knowledge diffusion). Extensive experiments on real-world datasets demonstrate that CGNKP significantly outperforms multiple strong baselines, achieving accuracies of 0.861 on the Twitter15 dataset and 0.903 on the Twitter16 dataset.

Pelatihan Santripreneur Melalui Pengenalan Digital Marketing Untuk Santri Pondok Pesantren Darul Ulum Tragung Batang

This Community Service Program aims to empower students of the Darul Ulum Tragung Islamic Boarding School, Batang, through digital marketing training to develop their ultra-micro businesses. This training was conducted in three stages: introduction to digital marketing, case studies from other Islamic boarding schools, and creation and management of a marketplace. The results of the training showed an increase in students' understanding of digital marketing strategies and their ability to manage a marketplace. Several obstacles such as limited internet access and devices, as well as limited time in the Islamic boarding school environment, were successfully overcome with an adaptive approach. This program succeeded in providing strong digital-based entrepreneurial provisions for students while strengthening partnerships between Islamic boarding schools and universities.

Enhancing or Compensating? Role of On- and Offline Social Capital and Technological Self-Efficacy on Subjective Well-Being among Immigrants and Natives.

The ability and self-efficacy to utilize the internet and technological devices has become critical during the COVID-19 pandemic. By examining the role of on- and offline social capital as a moderator in the relationship between technological self-efficacy (TSE) and subjective well-being, this study aims to contribute to the understanding of whether the social compensation or social enhancement hypotheses explain the well-being of immigrants in South Korea during the COVID-19 pandemic. We analyzed data from the 2020 Digital Divide Survey of immigrants (n = 700) and native-born Koreans (n = 6,910) aged ≥18 years. In the ordinary least squares regression model, subjective well-being (SWB) was the dependent variable and TSE was the independent variable. Online social capital, including bonding and bridging, was the moderating variable. Moreover, we tested the moderated moderation of nativity and on- and offline social capital. The results showed that bonding and bridging on- and offline social capital played a positive role in the SWB of both immigrants and native-born Koreans; bridging played a greater role among immigrants than among native-born Koreans. Furthermore, the interaction between TSE and online bonding social capital has a stronger association with the SWB of immigrants, as supported by the moderated moderation model. In line with the social enhancement hypothesis, immigrants with more online bonding social capital showed a stronger positive association between TSE and subjective well-being. Our results suggest that culturally adapted technological education for immigrants can be tailored to meet their unique needs and experiences.

Deep learning-based image encryption techniques: Fundamentals, current trends, challenges and future directions

In recent years, the number of digital images has grown exponentially because of the widespread use of fast internet and smart devices. The integrity authentication of these images is a major concern for the research community. So, the encryption schemes that are commonly used to protect these images are an important subject for many potential applications. This paper presents a comprehensive survey of recent image encryption techniques using deep learning models. First, we explain the reasons that image encryption using deep learning models is beneficial to researchers and the public. Second, we discuss various state-of-art encryption techniques using deep learning models and offer technical summaries of popular techniques. Third, we provide a comparative analysis of our survey and existing state-of-the-art surveys. Finally, by investigating existing deep learning-based encryption, we identify several important research challenges and possible solutions including standard security metrics. To the best of our knowledge, we are the first researchers to do a detailed survey of deep learning-based image encryption for digital images.

Development of android-based self-assessment application for basic pencak silat techniques

In Physical Education learning (PE), the absence of effective self-assessment to measure basic pencak silat techniques can hinder student learning and skill development. This research aimed to develop an Android-based self-assessment application for basic pencak silat techniques in PE classes. The study follows the Research and Development (R&D) method, incorporating the ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. Through expert validation and field trials at State High School 1 Bengkalis, the application's feasibility and effectiveness were assessed. Results showed a high level of feasibility and effectiveness, with significant improvement in students' understanding and skills in basic pencak silat techniques. The application offers benefits such as ease of use for teachers, increased student interest, and clear learning objectives. However, challenges include dependence on internet connectivity and device limitations. Despite limitations, this study contributes to innovative and efficient learning aids, enhancing skill assessment in PE. The implications extend to curriculum integration and improved assessment methods for teachers, empowering students to monitor their progress and enhance their skills independently. Future research could explore broader applications in sports learning and address specific needs in pencak silat education.

A hybrid approach for Bengali sentence validation

Bengali is the official language of Bangladesh and is widely used in Bangladesh and West Bengal in India. Due to the growing accessibility of the internet and smart devices, the use of digital text material and documents in Bengali is growing with time. An automated Bengali Sentence Validation System is proposed in this study to effectively determine the correctness of sentences in such extensively available Bengali content. As far as we know, no substantial work has been done in the field of Bengali Sentence Validation utilizing deep learning approaches. Due to the lack of linguistic resources, sophisticated Natural Language Processing tools, and benchmark datasets, developing an automated Sentence Validation System for a limited-resource language like Bengali is challenging. Additionally, Bengali Sentences come in two morphological varieties (Sadhu-bhasha and Cholito-bhasha), making the validation process more challenging. The proposed automated Bengali Sentence Validation system contains the CNN-BiLSTM hybrid classifier model. As of now, there is no standard dataset for Bengali sentence validation. Due to the lack of a standard dataset, we collected Bengali sentences from different sources in Bangladesh and developed a Bengali Sentence Validation (BSV) Dataset with around 5000 labelled sentences arranged into two categories such as correct and incorrect. Experimental results demonstrate that the proposed system outperformed other classifier models and existing approaches for Bengali Sentence Validation and is able to categorize a wide range of Bengali sentences based on their correctness. The system’s F1 score for the Bengali Sentence Validation is 98%.

Необходимость установления цифрового следа при незаконном обороте лекарственных препаратов, содержащих наркотические средства, психотропные, сильнодействующие вещества

This article examines the use of the criminal element of the Internet and digital devices in criminal activities. The active use of information and telecommunication networks and digital devices in the commission of crimes in the field of illicit trafficking in medicines containing narcotic drugs, psychotropic and potent substances is emphasized. The concept of a digital footprint is given and its abandonment is indicated when a person uses digital devices and the Internet. The main advantages that the criminal world receives over the law enforcement system, with the active use of digitalization in the commission of crimes, are considered. It is pointed out the need for mandatory detection, fixation and analysis of digital traces in law enforcement activities, in order to identify the identity of the alleged offender and in order to establish the involvement of a person in the commission of a crime. Examples of the capabilities of law enforcement agencies in collecting a digital footprint in order to identify a person and establish involvement in a crime are given. The article summarizes the need to intensify the activities of law enforcement agencies related to the detection, fixation, consolidation and analysis of the digital footprint in order to fully and comprehensively document criminal acts and investigate criminal cases in the field of illicit trafficking in medicines containing narcotic drugs, psychotropic, potent substances.

The impact of internet device diversity on depressive symptoms among middle-aged and older adults in China: A cross-lagged model of social participation as the mediating role

BackgroundDepressive symptoms is more prevalent in middle-aged and older populations, and the development of Internet technology has brought new challenges and opportunities for the mental health of this group. This study aims to explore the bidirectional relationship between Internet device diversity and levels of depressive symptoms through longitudinal data analysis, as well as investigate the mediating role of social participation. MethodsData for the analysis was retrieved from the China Health and Retirement Longitudinal Study (CHARLS) in 2015, 2018, and 2020, which included 9259 middle-aged and older adults. The sum of the number of devices mentioned by each participant was calculated to assess the diversity of internet device use, a weighted total score of how frequently and to what extent individuals had participated in various social activities in the past month was calculated to measure the social engagement, and the Center for Epidemiological Studies Depression Scale was used to calculate depressive symptoms. A cross-lagged mediation model and bivariate correlation analysis were employed to examine the longitudinal relationships among depressive symptoms, internet device diversity, and social participation. Age, gender, highest education level, marital status, drinking status, smoking history, self-rated health, sleep duration, and chronic health conditions were adjusted as covariates. ResultsThe results from the three waves of longitudinal data revealed mutual predictive relationships among internet device diversity, social participation, and depressive symptoms. The mediating effect was significant (β = −0.612, 95 % CI −0.796 to −0.429), with significant gender differences observed. Furthermore, our findings indicated that social participation functioned as a protective factor against depressive symptoms, and the association between social participation and depressive symptoms was not a straightforward linear relationship. This suggests that participation in social activities (either high or low) is associated with a lower risk of depressive symptoms compared to no social participation, with no gender differences. ConclusionsThis study suggests that there is a relationship between internet device diversity and lower levels of depressive symptoms among middle-aged and older adults in China. Social participation mediates the relationship between internet device diversity and depressive symptoms, and different levels of social engagement have different effects on depressive symptoms. It is recommended to increase support for social participation among middle-aged and older adults, strengthen structural social capital, and better leverage the use of the internet to reduce depressive symptoms levels and promote the physical and mental well-being of this population.

Lightweight High‐Throughput TRNG Based on Single‐Node Boolean Chaotic Structure

ABSTRACTWith the rise of the Internet and electronic devices, the security of network information is gaining attention, and the true random number generator (TRNG) is playing an increasingly crucial role in information security. TRNG, based on Boolean chaotic entropy source, has drawn significant interest due to its uncomplicated circuit design and minimal hardware resource usage. However, most existing structures consist of two‐input or three‐input logic devices, forming a complex multinode, geometrically symmetric Boolean chaotic network using multiple logic devices. This network configuration results in increased complexity and reduced throughput. This study introduces an entropy source based on Boolean chaos utilizing single‐node and four‐input XOR gates, which can be easily placed and routed on Xilinx Artix‐7 FPGA. It requires only 29 LUTs and 5 DFFs without any postprocessing, achieving a throughput of up to 700 Mb/s. The output of TRNG has successfully passed various tests including the autocorrelation test, NIST SP800‐22, NIST SP800‐90B, AIS‐31, and TESTU01 tests with favorable results. Furthermore, by applying a three‐stage XOR chain postprocessing on Xilinx Spartan‐6 FPGA and Xilinx Virtex‐6 FPGA, it has passed the NIST SP800‐22 and NIST SP800‐90B tests at 300 Mb/s. The structure was also tested using Xilinx Virtex‐6 FPGA under different temperature and voltage conditions, passing the NIST SP800‐90B IID test.

Adaptive incentive mechanism with predictors for on-time attended home delivery problem

The widespread use of the Internet and smart devices has led to a fast growth in online shopping, offering new chances for online retailers to boost profits. However, this expansion has also brought various challenges, such as the heavy workload faced by delivery riders. To meet customers’ delivery time preferences and increase earnings, riders often work long hours, especially during busy periods. This study explores how historical delivery data can be used to balance workload in on-time attended home delivery. Drawing on the actual delivery operations and data of an online shopping platform, we propose a framework that combines delivery demand and customer behavior predictors with an adaptive incentive system to balance rider workload. Specifically focusing on same-day attended home delivery, we introduce a method to forecast future delivery demand, an algorithm to estimate customer choice behavior using a simple model, and an adaptive incentive system to influence customer decisions and achieve workload balance. We show that as order volume increases, the proposed incentive system achieves the pre-determined workload target. Using real data, we conduct numerical experiments which not only underscore the superior predictive performance of our models but also affirm the efficacy of the proposed incentive structure.

Design and Implementation of Long Range Wide Area Networks for Future Industrial IoT Applications

Background: The evolution of Long Range Wide Area Networks (LoRaWAN) is a potential candidate for next generation networks for managing the massive number of devices in the Industrial Internet of Things (IIoT). LoRaWAN is more suitable for transmitting smaller intermittent data but using smaller bandwidth over a long distance. Objective: This research paper proposes to design a Low Power Wide Area Network (LPWAN) to provide long-range data transfer for Industrial IoT applications, especially for industrial sensor data. Methods: This research work deploys the experimental setup of LoRaWAN devices using LoRa gateways and Internet of Things network server to evaluate its performance for IIOT applications. Results: The deployment of this LoRaWAN has demonstrated its long range, low power, stability and low deployment cost through extensive performance evaluation carried out. LoRaWAN has been analyzed for its coverage and throughput performance. Conclusion: Through performance analysis, potential enhancements have been identified to overcome its shortcomings. This paper concludes the feasibility of deploying LoRaWAN technology for the future generation IIOT applications.

Computing advertising intelligent computing and push based on artificial intelligence in the big data era

In the era of big data, intelligent computation and precise targeting of advertisements rely on artificial intelligence (AI) technology to enhance advertising effectiveness and user experience. As advertising media shift from traditional outlets to the internet and mobile devices, manually filtering and targeting advertisements has become increasingly ineffective due to the vast amount of information and user groups. Consequently, AI-based advertisement computation and targeting technologies have emerged. This paper explores how modern technologies and AI applications can be used to achieve intelligent computation, filtering, and targeting of advertisements, thereby improving ad effectiveness and profitability. The study optimizes ad targeting effectiveness and increases return on investment (ROI) by comparing ad campaigns between Group A, which did not use ad targeting algorithms, and Group B, which employed AI-based targeting algorithms. The experimental results show that the average ROI for tourism, shopping, and rental ads in Group A were 153.03 %, 232.32 %, and 192.57 %, respectively, while Group B's average ROI were 173.96 %, 288.74 %, and 216.12 %. These results indicate that AI-based ad targeting algorithms can significantly improve the ROI of ad campaigns compared to non-algorithmic approaches, suggesting that ad targeting algorithms can help advertisers achieve higher profits.

GIÁO DỤC KỸ NĂNG CÔNG DÂN SỐ THEO CHƯƠNG TRÌNH GIÁO DỤC PHỔ THÔNG 2018 CẤP TIỂU HỌC

With the development of digital technology, children around the world as well as in Vietnam have access to the Internet and digital devices from a very early age. This early exposure provides an initial advantage that aids in the successful implementation of digital transformation, but it also poses potential risks. How can we ensure that children are safe and creative in the online environment while also enhancing their qualifications and skills, thereby contributing to the development of the nation’s human resources? In this report, we present the context of digital transformation, along with the practical, legal, and scientific foundations for educating students in digital citizenship skills. Based on this context, we offer solutions and implementation strategies to effectively teach digital citizenship skills at the elementary level. Keywords: Digital citizenship education; primary education; digital competencies; digital competency framework; digital transformation.

A Novel Blockchain-Based Privacy-Preserved Data Sharing Using Deep Maxout Network in Federated Learning

The quick emergence in the quantity of data produced through the linked devices of Internet of Things (IoT) models opened the novel potential to improve service qualities for budding tools considering data sharing. However, privacy problems are main issues of data providers for sharing data. The outflow of confidential data causes severe problems beyond the loss in finance of providers. A blockchain-based secured data-sharing model is devised for dealing with various kinds of parties. Thus, data-sharing issue is modeled as a machine learning issue by adapting federated learning (FL). Here, data privacy is controlled by sharing data in spite of exposing genuine data. At last, the FL is combined in consensus task of permissioned blockchain for accomplishing federated training. Here, the data model learning is executed using a deep maxout network (DMN), which is trained using jellyfish search African vultures optimization (JSAVO). Moreover, the data-sharing records are generated to share data amid data providers and requestors. The proposed JSAVO-based DMN outperformed with better accuracy of 93.3%, FPR of 0.054, loss function of 0.067, mean square error (MSE) of 0.346, mean average precision of 94.6, RMSE of 0.589, computational time of 17.47[Formula: see text]s, and memory usage of 48.62[Formula: see text]MB.

Health Information Seeking on the Internet Among Patients With and Without Cancer in a Region Affected by the 2011 Fukushima Triple Disaster: Cross-Sectional Study.

Health information seeking via the internet among patients with cancer in disaster-affected areas is underresearched. This study aims not only to assess the extent and means of web-based health information seeking among patients with cancer living in the disaster-affected area of the 2011 Fukushima triple disaster but also to compare these patterns with those without cancer, identifying distinct and shared factors influencing their web-based health information behaviors. We surveyed 404 patients (263 with and 141 without cancer) from the surgery department outpatient office at Minamisoma Municipal General Hospital, from October 2016 to January 2017. The survey included self-administered questions on internet and digital device use. Descriptive analyses were performed to examine the use patterns of digital devices and the internet and their impact on health information seeking across different age groups of patients with and without cancer. Multivariable logistic regression was used to examine factors associated with web-based health information seeking, stratifying by cancer diagnosis. The proportion of participants who sought health information on the internet was comparable between patients with cancer and patients without cancer (19% vs 17.4%; P=.71). Digital device use varied significantly with age, with peak smartphone use occurring among the youngest cohorts for both groups. Multivariable logistic regression revealed that patients with cancer using smartphones or tablets daily were significantly more likely to gather web-based health information (odds ratio [OR] for smartphones 3.73, 95% CI 1.58-8.80; OR for tablets 5.08, 95% CI 1.27-20.35). Trust in institutional websites also significantly influenced web-based health information gathering among patients with cancer (OR 2.87, 95% CI 1.13-7.25). Conversely, among patients without cancer, unemployment was associated with a lower likelihood of seeking web-based health information (OR 0.26, 95% CI 0.08-0.85), whereas trust in both institutional and personal websites significantly increased this likelihood (OR for institutional websites 6.76, 95% CI 2.19-20.88; OR for personal websites 6.97, 95% CI 1.49-32.58). This study reveals that a small proportion of both patients with cancer and patients without cancer engage in health information seeking via the internet, influenced by age, digital device use, and trust in institutional websites. Given the growing prevalence of digital literacy, strategies to enhance accessible and reliable web-based health information should be developed, particularly for patients with cancer in postdisaster settings. Future efforts should focus on tailored health communication strategies that address the unique needs of these populations.

Analysis of the Content of Ideological and Political Education for College Students from the Perspective of Online Communication

With the popularity of the Internet and mobile smart devices, online communication has become increasingly common among college students. However, online communication also brings some negative influences, such as information overload, false information, and cyberbullying. Therefore, ideological and political education for college students needs to strengthen the perspective of online communication, guiding them to use online communication tools correctly, avoid negative influences, and improve their online communication literacy and civility.

CHALLENGE OF EDUCATORS IN TIMES OF REMOTE TEACHING

The present work addresses the challenges faced by educators during the period of remote teaching, driven by the COVID-19 pandemic. The rapid transition from the face-to-face to the virtual environment has brought numerous difficulties to education professionals. First, we discussed technological adaptation, since many educators needed to acquire new skills and competencies to use online teaching platforms and digital tools. Lack of proper training and familiarity with educational technologies were crucial issues in this shift. In addition, we address social inequalities and those aggravated by remote teaching. The lack of access to the internet and adequate devices in disadvantaged communities has resulted in an imbalance in access to education, creating a worrying scenario for educational inclusion. Another relevant point was the challenge of student engagement. The presence of face-to-face interaction and the difficulties in establishing a meaningful connection with students in the virtual environment impacted motivation and interest in educational activities. The work also highlights the increased workload for educators. The transition to remote learning follows extreme dedication and a work-life balance. The need to prepare classes adapted to the digital environment and constant communication with students and families have met additional challenges.

Changes in Technical Equipment and Patient Perspectives Navigating Towards Enhanced Digitalization in Breast Cancer Across Pre-COVID-19 and Early COVID-19 Eras

IntroductionThe potential benefits of eHealth support in enhancing patient care, satisfaction, and cancer outcomes are well-established; however, its integration into routine care has been gradual. The emergence of the COVID-19 pandemic in 2020 dramatically affected cancer patients, imposing multifaceted challenges that impede traditional doctor-patient interactions. Consequently, there has been a surge in the adoption of eHealth for supporting oncological therapies. This study investigates the fundamental prerequisites for transitioning to a more digitally oriented routine care, focusing on the availability of appropriate technical equipment and the cultivation of a positive mindset towards eHealth among breast cancer patients. Patients and MethodsIn 2013, 2016, and 2020, breast cancer patients participated in surveys utilizing a comprehensive paper questionnaire encompassing 29 inquiries about their health status, technical equipment, and attitudes toward digital therapy support. ResultsA total of 959 patients participated in the interviews. Comparative analyses between the 2013, 2016, and 2020 surveys revealed a widespread increase in internet access and device ownership across various age groups. By 2020, 3 quarters of patients were utilizing the internet for health-related topics. Notably, there has been a considerable improvement in patients' personal attitudes towards eHealth and their expectations for future digital therapy support. DiscussionOver the seven years spanned by the surveys, there has been a substantial positive shift in the attitudes of breast cancer patients towards eHealth, accompanied by a marked improvement in their technical equipment. This study reveals that the essential prerequisites for digital therapy support now appear to be prevalent among breast cancer patients.

Wafer scale WS2 based ultrafast photosensing and memory computing devices for neuromorphic computing

Integration of optical sensors with memristors can establish the bridge between photosensing and memory devices for Internet of Things (IoT) based applications. This paper presents the realization of integrated sensing and computing memory (ISCM) devices using tungsten disulfide (WS2) and their application for neuromorphic computing. The ISCM device fabrication process is scalable as microfabrication steps followed on 2″ wafer, ISCM device testing and image classification for neuromorphic computing. The photosensing/memory tests were conducted using electrical and optical stimulations (broadband spectrum). The fabricated photosensing device offers a higher responsivity (8 A W−1), higher detectivity (2.85 × 1011 Jones) and fast response speed (80.2/78.3 μs) at 950 nm. The memory device has shown a set/reset time of 51.6/73.5 μs respectively. Further, the repeatability, stability and reproducibility tests were conducted by stimulating the device with different modulating frequencies. The frequency modulation tests confirm that the ISCM devices are stable and perfect candidate for real-time IoT applications. Moreover, the device’s potentiation and depression results were used for image classification with the accuracy of 98.27%. These demonstrated device’s test results provide possibilities to fabricate the smart sensors with integrated functionalities.

Exploring the Influence of Financial Literacy on Mobile Financial Service Usage: An Ordered Probit Analysis

Mobile financial service, an emerging form of financial services that has developed alongside the internet and mobile devices, are becoming increasingly significant in the global financial market. Financial literacy is crucial for safely and effectively using these services, as it equips individuals with the necessary knowledge and skills to navigate the digital financial landscape, make informed decisions, and manage their finances responsibly. This study explores the link between financial literacy and the use of mobile financial services, aiming to promote financial inclusion and help users benefit from mobile banking technologies. The results indicate that the impact of objective financial literacy varies significantly across different types of mobile financial services. It boosts the utilization of mobile banking services, with coefficient 0.025 (p<0.01), while simultaneously reducing the frequency of mobile payments and transfers, with coefficients -0.041 and -0.012 respectively (p<0.01). The results also show that subjective financial literacy always positively relate to the use of mobile banking, mobile payments and mobile transfers, with coefficients 0.038, 0.044 and 0.03 respectively (p<0.01). Further, this paper investigates how financial literacy miscalibration affects the use of mobile financial services. The results show that individuals who over-evaluated their financial literacy are more likely to use mobile financial services than individuals who under-evaluated or correct-evaluated their financial literacy. The results serve as decisive evidence for policymakers to enhance consumer financial literacy, thereby improving their use of mobile financial services. Future studies could delve deeper into the underlying reasons for the differential impact of objective financial literacy on various MFS types.