Shared Medium Research Articles

The Joint Media Engagement Scale (JMES): An instrument for measuring shared media use with children aged 1 to 5 years old.

The digital media landscape is rapidly shifting, and some children begin using digital media in infancy. As with book reading, young children need adult guidance to learn from digital media. Joint media engagement (JME) occurs when preschool children and their parents actively use digital media together. JME during early childhood is associated with increased learning from media. However, there are no validated scales of JME. In the present study, parents of 353 1-to-5-year olds answered a series of questions about their media use and behaviours. Exploratory factor analysis yielded two scales, one for viewing video content together and one for playing digital games together. Convergent validity was established by comparison to the widely used Television Mediation Scale. Together, these findings establish the JME instrument as a valid and reliable tool for measuring joint media engagement during early childhood.

NDN multicast over wireless networks: A survey on fundamentals, challenges, and open issues

Wireless devices have shown remarkable growth in data demand in the last decade due to the proliferation of smart devices and the emergence of bandwidth-hungry applications. This increasing data traffic demand is overcrowding the radio frequency spectrum, leading wireless multicast schemes to become a popular research topic again, as they provide efficient data dissemination. NDN supports multicast communication by design. It is a networked system formed by named entities that adopt a communication model focusing on the content rather than its location. The architecture follows a receiver-driven communication model through which content consumers retrieve data through semantically meaningful names instead of specific destinations. Its properties are essential for multicast communication on ad hoc networks, as its features provide enhanced support for dynamic topologies, decentralized control, and the self-organization of participant nodes that communicate without needing a pre-existing network infrastructure. However, despite the wireless medium being broadcast by nature, NDN multicast is still challenging in wireless scenarios, especially in ad hoc environments, due to the node’s high mobility, link instability, constant handovers, and data transmission over a shared medium. Hence, this survey discusses the benefits of NDN for mobile scenarios through an in-depth analysis of NDN multicast features, focusing on fundamentals, challenges, and open issues when applied to wireless networking.

A genetic scheduling strategy with spatial reuse for dense wireless networks

Novel networking technologies such as massive Internet-of-Things and 6G-and-beyond cellular networks are based on ultra-dense wireless communications. A wireless communication channel is a shared medium that demands access control, such as proper transmission scheduling. The SINR model can improve the performance of ultra-dense wireless networks by taking into consideration the effects of interference to allow multiple simultaneous transmissions in the same coverage area and using the same frequency band. However, scheduling in wireless networks under the SINR model is an NP-hard problem. This work presents a bioinspired solution based on a genetic heuristic to solve that problem. The proposed solution, called Genetic-based Transmission Scheduler (GeTS) produces a complete transmission schedule optimizing size, increasing the number of simultaneous transmissions (i.e., spatial reuse) thus allowing devices to communicate as soon as possible. Simulation results are presented for GeTS, including a convergence test and comparisons with other alternatives. Results confirm the ability of the solution to produce near-optimal schedules.

Uncovering the authorship: Linking media content to social user profiles

The extensive spread of fake news on social networks is carried out by a diverse range of users, encompassing private individuals, newspapers, and organizations. With widely accessible image and video editing tools, malicious users can easily create manipulated media. They can then distribute this content through multiple fake profiles, aiming to maximize its social impact. To tackle this problem effectively, it is crucial to possess the ability to analyze shared media to identify the originators of fake news. To this end, multimedia forensics research has advanced tools that examine traces in media, revealing valuable insights into its origins. While combining these tools has proven to be highly efficient in creating profiles of image and video creators, it is important to note that most of these tools are not specifically designed to function effectively in the complex environment of content exchange on social networks. In this paper, we introduce the problem of establishing associations between images and their source profiles as a means to tackle the spread of disinformation on social platforms. To this end, we assembled SocialNews, an extensive image dataset comprising more than 12,000 images sourced from 21 user profiles across Facebook, Instagram, and Twitter, and we propose three increasingly realistic and challenging experimental scenarios. We present two simple yet effective techniques as benchmarks, one based on statistical analysis of Discrete Cosine Transform (DCT) coefficients and one employing a neural network model based on ResNet, and we compare their performance against the state of the art. Experimental results show that the proposed approaches exhibit superior performance in accurately classifying the originating user profiles.

In vitro simulation of the liver first-pass effect with biotransformation-competent HepG2 cells to study effects of MG-132 on liver and cancer cells.

Liver biotransformation is the major route for drug metabolism in humans, often catalysed by cytochrome P450 (CYP) enzymes. This first-pass effect can lead to hepatotoxicity and influences the bioavailability of drugs. We aimed to establish in vitro culture systems simulating the liver first-pass to study effects of the proteasome inhibitor MG-132 simultaneously on hepatocytes and cancer cells. The first-pass effect was simulated by conditioned medium transfer (CMT) from pre-treated HepG2 CYP3A4-overexpressing cells to either pancreatic cancer cell line PANC-1 or primary colon cancer cells, and by indirect co-culture (CC) of liver and cancer cells in a shared medium compartment. Experimental proteasome inhibitor MG-132 was used as test substance as it is detoxified by CYP3A4. Cancer cells showed higher viabilities in the first-pass simulation by CMT and CC formats when compared to monocultures indicating effective detoxification of MG-132 by HepG2 CYP3A4-overexpressing cells. HepG2-CYP3A4 cells showed reduced viabilites after treatment with MG-132. We successfully established two different culture systems to simulate the liver first-pass effect in vitro. Such systems easily allow to study drug effects simultaneously on liver and on target cancer cells. They are of great value in pre-clinical cancer research, pharmaceutical research and drug development.

StegoBackoff: Creating a Covert Channel in Smart Grids Using the Backoff Procedure of IEEE 802.11 Networks

A smart grid constitutes an electrical infrastructure that integrates communication technologies to optimize electricity production, distribution, and consumption. Within the smart grid, IEEE 802.11 networks play a crucial role in facilitating communication between smart meters and data collectors, operating within a shared transmission medium. However, a notable challenge arises due to the lack of certainty regarding the genuine identity of data recipients. In response, we present a solution—a novel covert channel leveraging the IEEE 802.11 backoff procedure—to transmit data that requires special protection. Implemented using the ns-3 simulator, our covert channel achieved a throughput of 140,000 bps when single covert station realized transmission in the wireless channel, and 880 bps in a populated environment characterized by high traffic volumes. This performance metric shows that our mechanism is better than other covert channels, where the performance in saturated conditions usually does not exceed several hundred bps. This covert channel represents a new approach to fortifying data integrity and privacy within smart grid communication.

Constructing the digital ark: How China utilizes shared media to foster online information collaboration and crisis management in public emergency response

With the prevalence of collaborative editing tools, such as shared documents, a digital rescue platform functionality has emerged to address major unforeseen events, displaying notable self-organizing characteristics. This study examines the transformative role of sharing technologies in crisis communication, using documents from the 2021 Zhengzhou flood and adopting an actor-network theory perspective. Investigating how sharing technology influences situational information, the findings highlight its creation of a real-time, collaborative, and detailed crisis information environment, fostering self-rescue initiatives and positive emotional support. The shift from a closed situational information pool to a dynamic digital network underscores the evolving landscape of crisis communication in the digital age. Self-negotiation and self-restraint mechanisms mitigate rumor transmission, providing robust information support for subsequent rescue efforts. This research contributes valuable insights into the intricate dynamics of sharing technologies in crisis communication.

Analisis Pembagian Laba Rugi Pada Usaha Joint Venture Aida Jaya Gorden di Desa Hargomulyo Lampung Timur

This research aims to analyze the profit and loss distribution mechanism in the Aida Jaya curtain joint venture with Marti convection, analyze the influence of financial performance on profit and loss distribution, and analyze the contribution of mature parties who influence the distribution of profit and loss. This study used descriptive qualitative method. The research results show that: (1) Profit and loss distribution is carried out with a ratio of 7:3 according to the initial capital of each party; (2). Financial performance does not affect the sharing ratio, but does affect the amount of profit or loss that is shared, (3) Contribute to the content of Aida Jaya Gorden in the form of production facilities and Konveksi Marti which provides production personnel, which greatly influences the success of this joint venture. This means you can use shared media to share your thoughts with others who already have large joint ventures.

Analisis Laporan Keuangan Laba Rugi Pada Usaha Penjualan Pupuk Kelompok Tani di Desa Purwoadi 19 A

This research aims to analyze the profit and loss distribution mechanism in the Aida Jaya curtain joint venture with Marti convection, analyze the influence of financial performance on profit and loss distribution, and analyze the contribution of mature parties who influence the distribution of profit and loss. This study used descriptive qualitative method. The research results show that: (1) Profit and loss distribution is carried out with a ratio of 7:3 according to the initial capital of each party; (2). Financial performance does not affect the sharing ratio, but does affect the amount of profit or loss that is shared, (3) Contribute to the content of Aida Jaya Gorden in the form of production facilities and Konveksi Marti which provides production personnel, which greatly influences the success of this joint venture. This means you can use shared media to share your thoughts with others who already have large joint ventures.

Deep Learning-Based Location Spoofing Attack Detection and Time-of-Arrival Estimation through Power Received in IoT Networks

In the context of the Internet of Things (IoT), location-based applications have introduced new challenges in terms of location spoofing. With an open and shared wireless medium, a malicious spoofer can impersonate active devices, gain access to the wireless channel, as well as emit or inject signals to mislead IoT nodes and compromise the detection of their location. To address the threat posed by malicious location spoofing attacks, we develop a neural network-based model with single access point (AP) detection capability. In this study, we propose a method for spoofing signal detection and localization by leveraging a feature extraction technique based on a single AP. A neural network model is used to detect the presence of a spoofed unmanned aerial vehicle (UAV) and estimate its time of arrival (ToA). We also introduce a centralized approach to data collection and localization. To evaluate the effectiveness of detection and ToA prediction, multi-layer perceptron (MLP) and long short-term memory (LSTM) neural network models are compared.

Routing algorithms in internet of things complex network with the role of machine learning

In recent years, the growth of internet-based technologies increased at a rapid pace. The development of technologies such as the Internet of Things (IoT) influenced the enormous increase in the use of data and internet services. IoT devices use different algorithms for facilitating connectivity between devices and control them. However, ensuring smooth connectivity using protocols across a shared medium of network resources is challenging. IoT ecosystems utilize several routing algorithms to deliver the best path/ route for network traffic to control cyber physical systems. These routing algorithms allow IoT networks to use network routes, thereby increasing network traffic mobility effectively. So, a comprehensive survey is needed, which paves the path for researchers. Specifically, this survey investigates and compares the routing solutions in the IoT environment from different perspectives than current surveys such as safety, flow control of data and other essential parameters in IoT physical and nonphysical systems.

Business Strategy Analysis via Instagram @Laukita Using the Peso Approach

Branding is a marketing strategy that aims to communicate messages from a business to consumers. Laukita is here by bringing branding to people's minds with a fast food theme that is different from competitors in terms of presentation and the menu variants they offer. The aim of this research was to understand and analyze the branding strategy used by Laukita in the Covid-19 pandemic era, especially through social media. Researchers use the Social Media theory put forward by Nasrullah, with the PESO concept model from Gini Dietrich. The research method in this study used a descriptive qualitative type. The data used in this research was primary data obtained from interviews with sources and secondary data obtained through literature study. The results of the research showed that paid media elements have an important role in the Laukita branding development process, then earned media elements using reviewers and influencers, supported by shared media elements that use Laukita's social media, and owned media elements that manage all Laukita media channels so that they can Do strong branding in the minds of consumers

Tracing Practices – questioning and circulating archives

Our exposition comes out of a conversation and explorative research process about the performative potential of archives, both publicly and personally, shaped by four different artistic mediums and practices in film, performance art, choreography and essay writing. The shared medium has been through the use of text and online communication. The research was developed through ongoing monthly meetings and notes that were taken since April 2019. From those meetings, we laid a structure where we each created our parts of what became the score for "Living and Lasting", which we first performed in Oslo and then in Berlin in 2022*. This score is the pivot point of our exposition. Our working process includes considerable elements of risk and surprise by alternating between collaborative meetings and individual work. The first time we perform a new piece none of us know exactly what or how the others will present. Along with the audience, we experience portions of the text, movements, and media put together for the first time, without knowing whether the whole thing will coalesce, diverge, or fall apart. (*) In Oslo at the 2022 Nordic Summer University (NSU) and in Berlin at the symposium “Who tells y/our story?” ​​by the artistic research project MEMORYWORK (2021-2024).

Bandwidth-Delay-Product-Based ACK Optimization Strategy for QUIC in Wi-Fi Networks

QUIC has drawn extensive attention in supporting low latency and secure Internet of Things (IoT) communications due to its efficient handshake and default end-to-end encryption. However, in Wi-Fi enabled IoT communications with contentions for shared media, QUIC’s inherent acknowledgment (ACK) policy may induce non-negligible control overhead and limited data throughput. To address the problem, this paper designs and implements an ACK frequency optimization scheme for QUIC by exploiting the tailored bandwidth-delay product (BDP) at the receiver, named QUIC-BDP. To accurately estimate real-time BDP, we design an “ACK-PING" strategy to compensate for the accuracy of round-trip timing estimation and utilize exponential averaging and sliding window filtering for stable bandwidth estimation. Experiments results show that our proposed QUIC-BDP balances between the robustness and throughput performance while maintaining stable performance in lossy cases, with a reduced energy cost. Particularly, QUIC-BDP achieves up to a 67% gain in goodput compared to the original QUIC, and it improves goodput by up to 38% and 28% compared to existing solutions MSQUIC and QUIC-1:10, respectively. In addition, QUIC-BDP reduces energy cost by up to 50% compared to the original QUIC.

Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model.

It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies exclusively utilising in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets able to translate into clinical therapies. Although this is increasingly recognised, and work towards addressing the issue is becoming routinary much remains poorly understood. For instance, knowledge regarding the biochemical mechanisms through which cancer cells manipulate non-cancerous cell metabolism, and the subsequent impact on their survival and proliferation remains limited. Additionally, the variations in these processes across different cancer types and progression stages, and their implications for therapy, also remain largely unexplored. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with 13C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells.

PENINGKATAN KEMAMPUAN BERPIKIR KRITIS MELALUI MODEL THINK PAIR SHARE BERBANTUAN MEDIA MONOPOLI BUDAYA PADA SISWA KELAS V SDN MUKTIHARJO KIDUL 03

The type of research used in this study was Classroom Action Research which was carried out in 2 cycles, each cycle consisting of 2 meetings. Each cycle consists of 4 stages, namely planning, implementing, observing, and reflecting. The subjects in this study were fifth grade students at SDN Muktiharjo Kidul 03, totaling 16 students consisting of 6 male students and 10 female students. The focus of this research is the improvement of teachers' teaching skills and students' critical thinking. The test was tested using expect judgment validation, while the data analysis used was quantitative and qualitative analysis. The results showed an increase in students' critical thinking in cycle I reached 78.9 with classical completeness reaching 63% in the sufficient category, while in cycle II the results of students' critical thinking abilities classically reached 85.4 with classical completeness reaching 88% in the good category. This proves that increasing critical thinking can be improved through the Think Pair Share model assisted by Monopoly media learning in class V SDN Muktiharjo Kidul 03. Based on the results of class action research conducted in class V SDN Muktiharjo Kidul 03 it can be concluded that students' critical thinking can be increased through the model assisted by Think Pair Share media assisted by Mobudus media in class V SDN Muktiharjo Kidul 03. The researcher suggests that in applying the Think Pair Share model assisted by Mobudus media teachers must be more skilled and innovative in increasing student participation in learning activities.

Event-triggered controller design for active suspension systems: An adaptive backstepping method with error-dependent gain

This paper studies an adaptive control problem for active suspension systems (ASSs) with parameter uncertainties based on the event-triggered mechanism (ETM). The main focus of this work is to improve the transient response of the body and save the communication resources of the in-vehicle network. The controller area network (CAN) is the most widely utilized in-vehicle communication network in automotive systems, so it is a vital issue that how to improve the utilization of the CAN resources since the CAN has a low bandwidth as a shared media. To this end, we present two error-dependent fixed and relative threshold ETMs to achieve satisfactory suspension performance while significantly reducing the communication burden on the CAN. Then, in the recursive design process, the backstepping strategy with error-dependent gain is employed to improve the transient response of the systems. Meanwhile, the radial basis function neural networks are adopted to identify the unknown nonlinearities in ASSs. Finally, the developed adaptive control algorithm ensures that all the signals in the closed-loop suspension systems are bounded in presence of uncertainties. Simulation results based on the professional vehicle simulation software Carsim verify the effectiveness of the presented scheme.

Development and analysis of new implementations of MAC proto-cols and mobility models in LoRa networks

The technological revolution known as Internet of Things (IoT) brings together several areas of science and technology, such as data acquisition, energy consumption, Wireless Sensor Networks (WSN), data analyses and processing among others. IoT gets its name from the several applications, from wearables to cars connected to the network, spanning the transportation, health, electronics, water, and electricity industries. This massive addition of LoRa devices for its own application brings the problems of a shared medium such as frame collision. Additionally, as the devices are often battery powered there is a need to analyze the battery consumption. It was found that there is a lack of tools to estimate the consumption and performance of a network. In this paper, we implement new medium access control mechanisms for LoRaSim simulator, based on CSMA/CAD (Carrier Sense Multiple Access with Collision Avoidance and Detection). This addition tests the influence a different access protocol has on the LoRa network and its resilience. As part of this study the new access protocol is built on the existing simulator LoRaSim to study the difference between the access protocol currently used in LoRa, an ALOHA protocol variant, CSMA/CA (CSMA with Collision Avoidance) and CSMA/CAD with the purpose of analyzing the difference in collision between protocols and the respective energy consumption in mobility scenarios.

The Marketing Strategies of Online Shop Owners in Qatar: A Guide towards Establishing a Start-Up Business among Entrepreneurs

Introduction: Especially with the past CoVid-19 pandemic, prevalent online business owners have been establishing their shops thus online shopping being on the rise. This situation would mean that there are some new owners who would lack marketing strategy knowledge, which is why this study focuses on analyzing the marketing strategies used by online shop owners in Qatar as a guide to establishing start-up businesses among entrepreneurs. Methodology: A self-made survey questionnaire was thoroughly created and validated using the quantitative descriptive research design. One hundred (100) online shop owners in Qatar were selected as the respondents of the study. It discusses the demographic profile of the online shop owners and the utilization of the four marketing strategies following the PESO model, or Paid media strategies, Earned media strategies, Shared media strategies, and Owned media strategies, and which ones were dominantly applied based on the respondents age, sex, years of business operation, and business scale. Result: The results showed that the majority of the online shop owners are 26-30 years old, in the business for less than a year, belong to the micro business scale, and utilize Earned media strategies. Paid media strategies have never been applied, while Earned media strategies, Shared media strategies, and Owned media strategies have been rarely applied. The age group 26-30, male online business owners, in the business for 3 years and above, and belong to the small business scale have the highest level of application of marketing strategies. Discussion: The conclusion drawn from this study states that most online shop owners in Qatar deem publicity like press mentions, blogs, and online community posts. However, there was not much of a gap according to their demographic profile. In terms of age, sex, years of business operation, and business scale, it can be seen that the marketing strategies only revolved around Earned media strategies and Shared media strategies. Recommendation: It is recommended that online shop owners should learn and employ the best suitable marketing strategy to keep their online business successful and sustainable.

The interplay between social media virality metrics and message framing in influence perception of pro-environmental messages and behavioral intentions

Present study explored how message framing (gain vs loss) and social media virality metrics (e.g. the number of ‘likes’ and ‘shares’; SMVM) affect pro-environmental message’s influence perception and behavioral intention. In a 2 (framing: gain vs loss) × 2 (SMVM: high vs low) between-subjects experiment (N = 404), participants were exposed to Facebook posts about mitigating climate change. Major findings indicate: (1) gain framing, compared to loss, resulted in increased social desirability perception of pro-environmental messages when they are accompanied by high numbers of likes and shares; (2) social desirability perception mediated the effect of message framing on third person perception (TPP) but not on second person perception (SPP); (3) numbers of likes and shares affected participants’ message influence perceptions (TPP and SPP), and this was mediated by social desirability perception; and (4) message influence perceptions were found to be significant predictors of participants’ intentions for climate change mitigation actions. Study results implicate that SMVM can signal media content popularity and this can further affect social desirability and influence perceptions of the content. Message framing appeared to have an effect on how one thinks media content influence other people, especially in the presence of high levels of endorsement by others. The potential role of SPP, the perception of shared media influence, in augmenting public awareness and engagement is discussed in detail.