Mobile Multimedia Research Articles

Facial expressions when learning with a Queer History App: Application of the Control Value Theory of Achievement Emotions

AbstractLearning analytics (LA) incorporates analyzing cognitive, social and emotional processes in learning scenarios to make informed decisions regarding instructional design and delivery. Research has highlighted important roles that emotions play in learning. We have extended this field of research by exploring the role of emotions in a relatively uncommon learning scenario: learning about queer history with a multimedia mobile app. Specifically, we used an automatic facial recognition software (FaceReader 7) to measure learners’ discrete emotions and a counter‐balanced multiple‐choice quiz to assess learning. We also used an eye tracker (EyeLink 1000) to identify the emotions learners experienced while they read specific content, as opposed to the emotions they experienced over the course of the entire learning session. A total of 33 out of 57 of the learners’ data were eligible to be analyzed. Results revealed that learners expressed more negative‐activating emotions (ie, anger, anxiety) and negative‐deactivating emotions (ie, sadness) than positive‐activating emotions (ie, happiness). Learners with an angry emotion profile had the highest learning gains. The importance of examining typically undesirable emotions in learning, such as anger, is discussed using the control‐value theory of achievement emotions. Further, this study describes a multimodal methodology to integrate behavioral trace data into learning analytics research.

Research on multi‐source mobile commerce service recommendation model of data fusion based on tree network

SummaryWith the rapid development of e‐commerce and computer technology, the recommendation service in business activities has no longer implemented by people, but by software technology. In general, the e‐commerce website recommendation service can have divided into two types: standardization and personalization. The design of the recommendation service should be as follows, the content presentation should meet the consumer's shopping needs; we need to provide different processing level information according to the consumer's cognitive level; appropriately select the expression and strengthen the credibility of the recommendation. This article proposes a multi‐source data fusion strategy of mobile commerce service recommendation for tree‐based networks. On this basis, the tree‐node relationship is stored through redundant data, thus achieving complete decoupling between tree‐type nodes and reaching the tree. The purpose is to have the efficient storage and access of structured data. For the multimedia mobile device is limited by hardware conditions, limited storage capacity, weak computing power, and so on, using client‐side cached partial data and on‐demand sequence request server data and other strategies, making full use of the hierarchical structure of tree structure to design efficient. The tree synchronization model enables efficient buffering and accessing of server data by mobile devices.

Optimized Lossless Embedded Compression for Mobile Multimedia Applications

Power consumption is a critical design factor in modern mobile chip design, in which the memory system with dynamic random-access memory (DRAM) consumes more than half of the entire system’s power. Without DRAM bandwidth compression, extreme multimedia operations such as 8K high dynamic range (HDR) recording and 8K video conference calling are not possible without sacrificing image quality or trimming because of thermal limitations or battery time sustainability constraints. Since heterogeneous processors are substantially involved in managing various types of fallbacks or software solutions, complicated compression algorithms for high-compression ratios are not actually adaptable owing to timing closure problems or high throughput requirements. In this paper, we propose evaluation metrics to assess lossless embedded compression (LEC) algorithms to reflect realistic design considerations for mobile multimedia scenarios. Furthermore, we introduce an optimized LEC implementation for contemporary multimedia applications in mobile devices based on the proposed metrics. The proposed LEC implementation enhances the compression ratio of LEC algorithms in other commercial application processors for contemporary premium smartphones by up to 9.2% on average, while maintaining the same timing closure condition.

Abstract 366: A Combined Community Health Worker and Text Messaging-based Intervention for Smoking Cessation in India

Background: Home-based Community Health Worker (CHW) led care is a mode of health promotion. We sought to evaluate the effectiveness of a CHW-led smoking cessation intervention, supplemented by text messages in a semi-urban region of India. Methods: We conducted a cluster randomized controlled trial (4/2018- 8/2019) in adult smokers residing in the eastern part of India. Participants in the intervention arm were offered CHW-led home visits that were focused on counseling. In addition, participants could choose to receive text messages. Both CHW counseling and test messages were adapted to the participant’s stage of change. The control group received brief education only. Our primary outcome was self-reported smoking cessation at the end of 12 months, verified by exhaled carbon monoxide levels. CHWs were interviewed at the end of the study. Results: A total of 234 (mean age 43±12.3, male 96.2%) participants were enrolled; 151 (64%) in the intervention arm and 83 (35.4%) in the control arm. At 12-months, 30 (19.8%) participants in the intervention arm and 12 (14.4%) in the control arm quit smoking (absolute risk difference=5.4%; OR 1.46, p = 0.71). There was large cluster-level heterogeneity in intervention uptake (figure). Highlights from the CHW interviews are described in the figure. Conclusion: CHW-led home-based counseling, supplemented by regular text messages, led to a slight increase in quit rates, especially among those exposed to a higher dose of the intervention. However, the difference in cessation rates was not statistically significant. Future studies should consider testing mobile application-based multimedia messaging options, as an enhanced supplement to CHW based counseling.

Unique English: An English Learning Application for Remedial Program Using Gamification Approach

Literacy and Numeracy Screening (LINUS) that implemented in Malaysia as an educational program to improve literacy and numeracy among Year 1 to Year 3 pupils in all primary schools has been terminated in 2019. However, school-level remedial program still exists and its related application is limited in the market as there is no centralized syllabus for English remedial program yet. Therefore, an English learning application for remedial program called Unique English is designed with Multimedia Mobile Content Development to overcome this problem by using previous LINUS centralized constructs. An application testing has been carried out in S.K. Pintas Raya, Parit Raja which involves pupils in remedial program and received satisfactory results with 83.2 % positive feedbacks obtained thus it can be concluded that Unique English is suitable to be implemented in remedial program.

Mobile Multimedia Education for Language Disorders

This article describes the importance of new multimedia tools that provide multi-sensory education for language learning, especially for students who need special education. These contemporary appliances stimulate the senses, enter the motiva-tion and reinforce the memory. In particular, these tools advance language skills such as comprehension, oral language and vocabulary, speaking expressions, reading capacities and writing abilities. Also, the evaluation for students with lan-guage disorders lies on cognitive and metacognitive capabilities, being created by these interactive media devices.

Adversarial android malware detection for mobile multimedia applications in IoT environments

In this paper, we propose two defense methods against adversarial attack to a malware detection system for mobile multimedia applications in IoT environments. They are Robust-NN and a combination of convolutional neural network and 1- nearest neighbors(C4N) which modify training data that has been poisoned by an adversarial attack. As a result, the trained machine learning model will be accurate and if the malicious program is entered by any IoT device, the model generates necessary alerts. We provide an explanation of the used attack method and the algorithms proposed to defend against this attack. In order to evaluate the suitability of the proposed defense methods, sufficient analysis is presented, i.e. Drebin, Contagio and Genome datasets which include benign and malware Android apps are applied to perform experiments. To confirm the effectiveness of the suggested defense algorithms, this paper compared their performance with two state-of-the-art defense algorithms used to detect adversarial samples, namely e2SAD and EAT. The experiments are performed on two types of API and Permission features from the mentioned datasets. The results confirm that accuracy rates of classification algorithms decrease to 40% after attack in some cases (related to Drebin dataset by reviewing API feature sets). Additionally, the accuracy rates increase to 94.94% and 96.03% by applying Robust-NN and C4N algorithms, respectively. Therefore, they are comparable with existing cutting-edge defense algorithms. Also, the adversarial attack increased the FPR to 45.81% which will be reduced to 4.84% and 4.15% using Robust-NN and C4N, respectively. Consequently, the proposed methods will be robust against adversarial attacks.

Incoming Traffic Control of Fronthaul in 5G Mobile Network for Massive Multimedia Services

The cloud radio access network (C-RAN) is composed of optical networks and is known to a fronthaul network. In the fronthaul network, remote radio heads (RRHs) connect to a baseband processing unit (BBU) and BBUs connect to the BBU pool in the 5G core network. Multimedia traffic in radio is transmitted to the core network through the fronthaul network. Although the fronthaul is an optical network, bandwidth of the fronthaul is insufficient for mobile multimedia services because mobile multimedia services are based on large amounts of data. Therefore, it is necessary to control the bandwidth usage in the fronthaul. In 5G mobile networks, RRHs can use a mobile edge computing (MEC) server as an edge cloud and can perform complicated operations in the MEC using knowledge of fronthaul. The proposed method controls incoming traffic to the fronthaul network using knowledge according to the network condition in the fronthaul. When the bandwidth of the fronthaul becomes full due to a large amount of traffic, incoming traffic to the fronthaul network is controlled. The MEC server acts as a buffer for incoming multimedia traffic. Through the proposed method, transmission efficiency for massive multimedia traffic in the fronthaul can be improved. The performance is validated through computer simulation.

Cellular-D2D Resource Allocation Algorithm Based on User Fairness

As more and more mobile multimedia services are produced, end users are increasingly demanding access to high-speed, low-latency mobile communication networks. Among them, device-to-device (D2D) communication does not need the data to be forwarded through the base station relay but allows the two mobile devices adjacent to each other to establish a direct local link under control of the base station. This flexible communication method reduces the processing bottlenecks and blind spots of the base station and can be widely used in dense user communication scenarios such as transportation systems. Aiming at the problem of high energy consumption and improved quality of service demands by the D2D users, this paper proposes a new scheme to effectively improve the user fairness and satisfaction based on the user grouping into clusters. The main idea is to create the interference graph between the D2D users which is based on the graph coloring theory and constructs the color lists of the D2D users while cellular users’ requirements are guaranteed. Finally, those D2D users who can share the same channel are grouped in the same cluster. Simulation results show that the proposed scheme outperforms the existing schemes and effectively improve system performance.

Puzzle Wira : Sarana Edupreneurship Berbasis Mobile Multimedia Untuk Generasi Alpha di Era Disrupsi Teknologi

This study aims to offer an interactive entrepreneurship learning model based mobile multimedia for alpha generation. This paper is presented on a conceptual basis from literature study so that there are no statistical tests and empirical studies in its research methods. Data and information obtained from various secondary literature such as government websites, national and international journals, books and proceedings. Then, the data and information obtained are presented descriptively accompanied by an analysis of the results of group discussions with the Multimedia Development Life Cycle (MDLC) as a reference for model development in order to provide scientific studies that can be further developed. The conclusion of this paper is: puzzle wira can support government policy to be able to immediately converge conventional edupreneurship into interactive edupreneurship as early as possible so that the concept of entrepreneurship becomes familiar to the society so that it can spur society to become entrepreneurs as early as possible.

An Energy Efficient OFDM–MIMO Systems for Multimedia Data Transmission Based on Hybrid Fuzzy Approach

In a 4G cellular communication system, energy efficiency and power consumption are the key parameters in evaluating and designing communication system in multimedia. In this paper, an efficient model with high energy is proposed for multiple input multiple output orthogonal frequency division multiplexing (MIMO–OFDM) mobile multimedia systems with less power consumption. Providing high-speed video coding technique, which is designed to substantially improve coding efficiency compared with other coding techniques. Next to that erasures coding and Wyner–Ziv coding is used for encoding and compression process. Finally, efficient energy based optimized power allocation with hybrid Fuzzy Grey Wolf Optimization (GWO) algorithm is presented to reduce the power consumption of MIMO–OFDM mobile multimedia communication systems. The value of power which is consumed at the 30th iteration is 20 W and the energy efficiency is 92% for the 20 W power. Experimental results show that the proposed hybrid Fuzzy GWO algorithm can assure the required service with maximum efficiency in MIMO–OFDM.

JEWISH HERITAGE IN THE CREATIVE CITIES OF CENTRAL AND EASTERN EUROPE: TOURISM, TECHNOLOGIES AND PROSTHETIC MEMORY

This paper deals with Jewish mobile multimedia cultural-heritage, root-diaspora tours and apps. The author presents and compares UNESCO Creative Cities Network of Central and Eastern Europe in which Jewish communities were numerous before the World War II – Budapest (Hungary), Kraków (Poland), Prague (Czech Republic), Kaunas (Lithuania). Also, article deals with other cities of Jewish cultural heritage that are not listed in UNESCO Creative Cities Network as Warsaw, Poland and Vilnius, Lithuania, but propose multimedia tours. I will analyse, how aspects of creative city are included and highlighted in multimedia tours and apps. Visiting of memory sites is very relevant aspect of memory culture, related to other creative and cultural industries – tourism, heritage, museums etc. Cityscape and sites of memory of the Holocaust as cultural topography materialize and embody traumas, regrets, and responsibility to remember past. Contemporary technologies as mobile multimedia tours and apps are designed to aid travellers and tourists to find heritage and other touristic objects in a map, it provides general practical information, as well as maps, photos, augmented reality, and Jewish itineraries. Herewith these new technologies are changing very deeply not only travelling habits or photography practices, they fundamentally transform our relation with cultural heritage and memory. Mobile phones became not only devices for communication, but also as digital prosthetic memory.

Rapid Re-Identification Risk Assessment for Anonymous Data Set in Mobile Multimedia Scene

Ubiquitous mobile multimedia applications bring great convenience to users. However, when enjoying mobile multimedia services, users provide personal data to service platforms. Although the service platforms always claim that the collected personal data are de-identified, the risk of re-identifying users through linkage attacks still exists and is incalculable. This paper proposes a rapid prediction model for the overall re-identification risk based on the statistics of data sets (i.e., the number of individuals, number of attributes, distribution of attribute values, and attribute dependency). Our proposed model reveals the impact of statistics on the overall re-identification risk and adopts random sampling and semi-random sampling methods to predict the overall re-identification risk of data sets with and without strong dependency ordered attribute pairs. Experimental results show that for the data sets without strong dependency ordered attribute pairs, the random sampling method has a high prediction accuracy (the prediction error is less than 0.05). For the data sets with strong dependency ordered attribute pairs, the semi-random sampling method has a high prediction accuracy (the prediction error is less than 0.09). Exploiting our model, governments and individuals can quickly assess the privacy leakage risk of their data sets, given only the statistic of the data sets. Besides, this model can also evaluate the privacy risk of data collection schemes in advance according to historical statistics, and identify suspected services.

Enhancing Rescue Operations With Virtualized Mobile Multimedia Services in Scarce Resource Devices

The aim of this article is to present an architecture to support reconfigurable multimedia services for a practical emergency environment use case of rescue operations. Specifically, radio communication and video surveillance services are provided by means of a small device carried by a mobile vehicle. This solution is validated by implementing a digital mobile radio (DMR) standard radio hotspot and a video streaming server in an unmanned aerial vehicle (UAV) that conveys a device with scarce resources in order to minimize power consumption. To achieve a fast and flexible deployment of the envisioned services, a virtualization-based approach is proposed. Namely, a Kubernetes orchestrator is used to manage the life-cycle of services deployed on a small resource device, endowing the architecture with scalability and management flexibility. This article describes the executed performance tests that measured key parameters such as deployment time and recovery time after disconnection. Highly promising results were obtained, showing that the proposed architecture can be deployed in less than 4 minutes and can recover from network disconnections in less than 10 seconds. Thus, the performance, reliability and flexibility of the overall solution are demonstrated.

An Efficient Implementation of Parallel Parametric HRTF Models for Binaural Sound Synthesis in Mobile Multimedia

The extended use of mobile multimedia devices in applications like gaming, 3D video and audio reproduction, immersive teleconferencing, or virtual and augmented reality, is demanding efficient algorithms and methodologies. All these applications require real-time spatial audio engines with the capability of dealing with intensive signal processing operations while facing a number of constraints related to computational cost, latency and energy consumption. Most mobile multimedia devices include a Graphics Processing Unit (GPU) that is primarily used to accelerate video processing tasks, providing high computational capabilities due to its inherent parallel architecture. This paper describes a scalable parallel implementation of a real-time binaural audio engine for GPU-equipped mobile devices. The engine is based on a set of head-related transfer functions (HRTFs) modelled with a parametric parallel structure, allowing efficient synthesis and interpolation while reducing the size required for HRTF data storage. Several strategies to optimize the GPU implementation are evaluated over a well-known kind of processor present in a wide range of mobile devices. In this context, we analyze both the energy consumption and real-time capabilities of the system by exploring different GPU and CPU configuration alternatives. Moreover, the implementation has been conducted using the OpenCL framework, guarantying the portability of the code.

Development and Pretesting of Risk-Based Mobile Multimedia Message Content for Young Adult Hookah Use.

Background. Hookah is one of the most commonly used tobacco products among U.S. young adults due in part to widespread misperceptions that it is not harmful or addictive. There is growing evidence that hookah tobacco is associated with health harms and can lead to addiction. Research on interventions to address these misperceptions by communicating the harms and addictiveness of hookah use is needed. Aims. This study developed and pretested mobile multimedia message service (MMS) message content communicating the risks of hookah tobacco use to young adult hookah smokers. Method. Message content, delivery, and pretesting were tailored to participants' risk beliefs, hookah use frequency, and responses to simulated text message prompts. Participants viewed 4 of 12 core MMS messages randomized within-subjects and completed postexposure measures of message receptivity and emotional response (e.g., worry). Results. The sample included 156 young adult (age 18-30 years) hookah smokers; 31% smoked hookah monthly and 69% weekly/daily. Prior to viewing messages, a majority endorsed beliefs reflecting misperceptions about the risks of hookah tobacco. Postexposure measures showed participants were receptive to the messages and the messages evoked emotional response. As anticipated, messages produced similar receptivity and there were few differences in emotional response between the messages tested. Discussion. Young adult hookah tobacco smokers were receptive to tailored mobile MMS messages and messages evoked emotional response, two critical precursors to behavior change. Conclusion. Findings indicate that research testing the efficacy of tailored MMS messaging as a strategy for reducing hookah tobacco use in young adults is warranted.

MOBILE APP INTERVENTION TO PROMOTE BREAST CANCER SCREENING IN OLDER KOREAN AMERICAN WOMEN

To promote breast cancer screening behavior in older Korean American women, a mobile phone multimedia messaging intervention (mMammogram) was developed. The current study explored how the mMammogram intervention can be applied and improved for wide dissemination and implementation in other older racial/ethnic immigrant populations. Three focus groups were conducted with 14 older Korean American women who completed the mMammogram. Three themes emerged: (1) emphasis on knowledge improvement (understanding of breast cancer screening); (2) assistance of bilingual health navigators to promote mammography (e.g., setting up appointment and transportation); and (3) consideration of technology literacy (e.g., training for use of smartphone and connectivity issues). Mobile app intervention combined with bilingual health navigation services can be an acceptable and effective intervention medium to promote mammogram, which will bring about a positive change in women’s health screening behavior, especially for newly arrived immigrant populations.

Research on Video Encryption and Privacy Protection in Cloud Monitoring System Based on H.264

: Cloud monitoring technology is an important maintenance and management tool for cloud platforms.Cloud monitoring system is a kind of network monitoring service, monitoring technology and monitoring platform based on Internet. At present, the monitoring system is changed from the local monitoring to cloud monitoring, with the flexibility and convenience improved, but also exposed more security issues. Cloud video may be intercepted or changed in the transmission process. Most of the existing encryption algorithms have defects in real-time and security. Aiming at the current security problems of cloud video surveillance, this paper proposes a new video encryption algorithm based on H.264 standard. By using the advanced FMO mechanism, the related macro blocks can be driven into different Slice. The encryption algorithm proposed in this paper can encrypt the whole video content by encrypting the FMO sub images. The method has high real-time performance, and the encryption process can be executed in parallel with the coding process. The algorithm can also be combined with traditional scrambling algorithm, further improve the video encryption effect. The algorithm selects the encrypted part of the video data, which reducing the amount of data to be encrypted. Thus reducing the computational complexity of the encryption system, with faster encryption speed, improve real-time and security, suitable for transfer through mobile multimedia and wireless multimedia network.

The millimeter frequency range as a perspective for 5G networks

The currently widely used 4G cellular networks face many challenges. The growing demand for high-resolution mobile multimedia applications is bringing these networks to their practical limits. 5G networks, the next generation of wireless communications, are standardized to ease the burden on current infrastructure by offering significantly higher data rates through increased channel bandwidth. Given the lack of accessible frequencies traditionally used for mobile communications, millimeter bandwidths (mmWave) are quite a challenging alternative. This technology is a cornerstone of upcoming 5G networks, allowing faster data speeds and much higher bandwidth than ever before, but not every 5G network will necessarily use this frequency band, at least not all the time. As with any new technology, there are unavoidable problems that need to be overcome. The purpose of the research and analysis in this article is to systematize issues and solutions related to the potential problems of spectrum sharing in mmWave frequency range, its suitability for long-distance communications, indoors, in bad weather conditions, as well as biological aspects, and relevant conclusions have been done to meet these challenges.

Efficient user authentication protocol for distributed multimedia mobile cloud environment

The rapid growth of smart-phone users, mobile services and mobile applications, poses the challenges of storage space, processing capability, and battery lifetime at the users smart phones. Mobile cloud computing helps to overcome these challenges. Presently, when a mobile user wants to subscribe to various Multimedia based cloud service providers (MBCSPs), he/she need to register separately for each of MBCSP. Although one can use single sign-on methods, they are unreliable due to the presence of any untrusted server. Hence, we propose a three-factor mobile user authentication protocol for Distributed Multimedia based cloud services. Our proposed method consists of strong authentication between the mobile user and multimedia-based cloud service providers using session key agreement, choice-based MBCSPs registration, initial mobile user identity registration checking, time of validity for secret key issued by Registration center (RC) to mobile user and time of validity for secret key issued by RC to MBCSPs respectively. We have verified our protocol with various attack scenarios using informal analysis, formal proof using BurrowsAbadiNeedham (BAN) logic and formal security analysis using Automated Validation of Internet Security Protocols and Applications tool (AVISPA) respectively. Our proposed protocol provides better performance and foolproof security.