Virtual Mobile Research Articles

A memetic algorithm for improved joint route selection and split-level management in next-generation wireless communications

The complexity of next-generation wireless communications, especially Beyond 5G and 6G communication systems, will be handled by artificial intelligence-based management paradigms. The joint selection of routes and functional split levels involves critical decisions that network infrastructure providers need to make to support requests from virtual Mobile Network Operators (vMNOs). These decisions comprise the assignment and configuration of physical network resources, which must comply with the specific quality of service restrictions of each vMNO request. Recent work defined a detailed mathematical model for this complex challenge, its formulation as a constrained, discrete optimization problem, and the first algorithmic approaches. It was also found that an evolutionary algorithm delivers higher-quality solutions than an ad-hoc heuristic, and faster running times compared to a well-known commercial solver. This paper introduces a memetic algorithm that exploits the strengths of the former evolutionary method while incorporating several key innovations: a domain-specific recombination operator; a specialized repairing procedure; an enhanced fitness evaluation scheme; and a multiobjective archiving strategy that preserves promising solution trade-offs. We conduct a comprehensive evaluation of the performance and behavior of this proposal, as well as the contribution of each specific design component. The results highlight that our memetic algorithm consistently outperforms previous approaches from the literature, providing better trade-offs in terms of solution quality and the rate at which vMNO requests are successfully fulfilled.

An intelligent resource allocation strategy with slicing and auction for private edge cloud systems

The convergence of transformative technologies, including the Internet of Things (IoT), Big Data, and Artificial Intelligence (AI), has driven private edge cloud systems to the forefront of research efforts. The access to massive terminals and the emergence of personalized services pose serious challenges for efficient resource management in power private edge cloud systems. To address the challenge of inequitable resource allocation in the private edge cloud, this work proposes an intelligent resource allocation strategy with a slicing and auction approach. By formalizing the resource allocation problem as a Mixed Integer Nonlinear Programming (MINLP) puzzle, the method transforms it into a hierarchical allocation challenge for Mobile Network Operators (MNOs), Mobile Virtual Network Operators (MVNOs), and power terminals. The proposed Multi-hop Progressive Auction Algorithm (MPAA) addresses the sliced resource allocation problem between MNOs and MVNOs. Furthermore, a Terminal Resource Allocation Strategy (TRAS) based on improved particle swarm optimization is proposed to solve the spectrum resource allocation problem between MVNOs and power terminals. Extensive simulation results show that the bidding overhead of MPAA is reduced by 6.12% and the average terminal satisfaction of TRAS is improved by about 1.3% compared to conventional methods, thus improving the utilization of wireless resources within the power AIoT.

THE IMPACT OF DIGITIZATION ON TOURISM SERVICES MARKETING STRATEGIES (A FIELD STUDY ON TOURISM COMPANIES IN NAJAF GOVERNORATE)

The research aims to study the impact of digitization on marketing strategies for tourism services. Tourism companies use modern technology that depends on re-planning and enhancing the work of tourism and travel companies, such as online reservation services and even virtual mobile phones, using digitized devices enhanced with artificial intelligence. Digitization is the necessity of the era within the digital reality with its technical, economic, and human dimensions. It has opened new horizons for effective social networking for tourism companies dealing with their customers to speed up the process of providing tourism services to them by understanding their needs for those services. Adopting marketing strategies in delivering tourism services has become inevitable, so this research emphasized lowering costs, focusing on customers, and adopting a culture of innovation and creativity. The research sample included 120 tourism and travel companies with managers at different levels and individuals working in them within the Holy Najaf Governorate. The questionnaire was used as a tool to collect primary data, which contains (35) questions. In light of this, primary data was obtained through the responses of 100 surveyed companies. Data analysis and tests of research hypotheses were conducted using the Statistical Package for the Social Sciences.

Effectiveness of Mobile Virtual Laboratory Based on Project-Based Learning to Build Constructivism Thinking

Constructivism as a theoretical basis in education is key, considering that this approach views learning as an active process where students play a role in constructing their own knowledge. Apart from that, the development of mobile and virtual technology is increasingly growing in the educational environment. This research explores the effectiveness of this approach in building constructivist thinking in learning electrical installation practices. The method used in this research is the 4D Define, Design, Develop and Disseminate model. The research instruments include an expert review validity questionnaire and an evaluation instrument for students’ perceptions of the effectiveness of the Mobile Virtual Laboratory Based on Project-Based Learning in building constructivism. The research results show that the Mobile Virtual Laboratory is valid based on expert assessment, in addition there has been a significant increase in students’ understanding of concepts and practical skills, with a high level of satisfaction with the use of the Mobile Virtual Laboratory. So, it can be concluded that the Mobile Virtual Laboratory based on Project-Based Learning can be an effective tool to support constructivist learning in electrical measurement practice. The results of this research open opportunities for further research on how Artificial Intelligence can build constructive thinking.

GPU and VPU Enabled Virtual Mobile Infrastructure for 3-D Image Rendering and its Application in Telemedicine

GPU and VPU Enabled Virtual Mobile Infrastructure for 3-D Image Rendering and its Application in Telemedicine

Generating Mobile Virtual Tour Using UAV and 360 Degree Panorama for Geography-Environmental Learning in Higher Educationw

Nowadays, the limitations of media in geo-environmental learning present a significant challenge, as media plays an indispensable role in fostering students’ comprehensive understanding. Employing technology capable of delivering comprehensive landscape information is crucial for effective environmental education. Utilizing Unmanned Aerial Vehicles (UAVs) and 360-degree panoramic cameras represents a judicious technological choice, which can be seamlessly integrated into virtual tours. This research aims to develop a Mobile Virtual Tour (Movie-Tour) as a medium to support learning, especially for materials regarding environmental geography. The research and development (RnD) method is used in research with the ADDIE model (Analysis, Design, Development, Implementation and Evaluation). Data collection for the development of the product involved conducting a need assessment, performing validation tests and conducting trials with students. To gather field data for creating environmental geography materials for the Movie-Tour product, we utilized an Unmanned Aerial Vehicle (UAV) and a 360-degree stereoscopic camera. The results demonstrate that Movie- Tour is an educational medium capable of delivering an immersive learning experience and comprehensive materials, allowing for the virtual visualization of real-world conditions in the field. This capability enhances students’ engagement in exploring physical geography conditions, fosters independent knowledge acquisition, and nurtures their innate curiosity. Movie-Tour stands as a potent and practical educational tool, offering an effective and secure learning experience for students, eliminating the need for direct field visits.

Education of Patients With Atrial Fibrillation and Evaluation of the Efficacy of a Mobile Virtual Patient Environment: Protocol for a Multicenter Pseudorandomized Controlled Trial.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a leading cause of mortality and morbidity. Patient knowledge about AF and its management is paramount but often limited. Patients need to be appropriately informed about treatment options, medicinal adherence, and potential consequences of nonadherence, while also understanding treatment goals and expectations from it. Mobile health apps have experienced an explosion both in their availability and acceptance as "soft interventions" for patient engagement and education; however, the prolific nature of such solutions revealed a gap in the evidence base regarding their efficacy and impact. Virtual patients (VPs), interactive computer simulations, have been used as learning activities in modern health care education. VPs demonstrably improved cognitive and behavioral skills; hence, they have been effectively implemented across undergraduate and postgraduate curricula. However, their application in patient education has been rather limited so far. This work aims to implement and evaluate the efficacy of a mobile-deployed VP regimen for the education and engagement of patients with AF on crucial topics regarding their condition. A mobile VP app is being developed with the goal of each VP being a simple scenario with a set goal and very specific messages and will be subsequently attempted and evaluated. A mobile VP player app is being developed so as to be used for the design of 3 educational scenarios for AF management. A pseudorandomized controlled trial for the efficacy of VPs is planned to be executed at 3 sites in Greece, Ukraine, and Kazakhstan for patients with AF. The Welch t test will be used to demonstrate the performance of patients' evaluation of the VP experience. Our study is at the development stage. A preliminary study regarding the system's development and feasibility was initiated in December 2022. The results of our study are expected to be available in 2024 or when the needed sample size is achieved. This study aims to evaluate and demonstrate the first significant evidence for the value of VP resources in outreach and training endeavors for empowering and patients with AF and fostering healthy habits among them. PRR1-10.2196/45946.

Multi-Agent Federated Reinforcement Learning Strategy for Mobile Virtual Reality Delivery Networks

Multi-Agent Federated Reinforcement Learning Strategy for Mobile Virtual Reality Delivery Networks

Development of a Mobile Virtual Reality Application based on Morris Water Maze for the Evaluation of Spatial Memory in Human Beings

Development of a Mobile Virtual Reality Application based on Morris Water Maze for the Evaluation of Spatial Memory in Human Beings

Multi-Slice Privacy-Aware Traffic Forecasting at RAN Level: A Scalable Federated-Learning Approach

Next-generation mobile networks are expected to meet the requirements of a wide range of new vertical services. Hence, the network slicing concept has been introduced, in which Mobile Virtual Network Operators (MVNOs) are allowed to provide various types of services over the same physical infrastructure, owned by an Infrastructure Provider (InP). To cope with an ever-changing traffic demand, MVNOs seek to pre-allocate/reconfigure the resources at the base stations in an anticipatory manner, based on traffic demand predictions. Ideally, conducting per-slice traffic forecasting requires information that is likely to disclose MVNO confidential information (i.e., business strategy or private user data). To secure data ownership while conducting traffic forecasting, we propose the Federated Proximal Long Short-Term Memory (FPLSTM) framework, which allows MVNOs to train their local models with their private dataset at each base station; subsequently, an associated InP global model can be updated through the aggregation of the local models. The results obtained by training the models on a real-world dataset indicate that the forecasting performance of our proposed approach is as accurate as state-of-the-art centralized solutions, while improving data privacy. To enable scalability, we further propose the Information-based Clustering FPLSTM (IC-FPLSTM) and Random Clustering FPLSTM (RC-FPLSTM) frameworks, dealing with large-scale cellular networks. These solutions demonstrate computation and communication cost efficiency significantly above the state-of-the-art.

Blockchain-Based Computing Resource Trading in Autonomous Multi-Access Edge Network Slicing: A Dueling Double Deep Q-Learning Approach

We investigate the computing resource allocation in multi-access edge network slicing (NS) in the context of revenue and multi-access edge computing (MEC) resource management. The significant variety of slice resource utilization levels across slice tenants (i. e., Mobile Virtual Network Operators (MVNOs)) challenges MEC resource management in NS with MEC, leading to virtual machine resource (VMR) (i. e., computing resource) wastage or scarcity. As a result, for efficient MEC resource management, the infrastructure provider (InP) encourages dynamic resource sharing and trading (DRST) of unutilized slice VMR quotas. Nevertheless, cellular network security and privacy issues deter MVNOs from collaborating on effective DRST. The security characteristics inherent in blockchain have recently gained much interest for secure resource trading. Thus, this paper proposes a unique hierarchical blockchain-based inter-slice computing resource trading (ISCRT) scheme for peer-to-peer (P2P) MVNOs in an autonomous multi-sliced MEC-based 5G network. For secure ISCRT transactions, a consortium blockchain network with hyperledger smart contracts (SC) is designed. We model the demand and pricing problems of buyer and seller MVNOs for the unutilized VMRs using a two-stage Stackelberg game. Then, to obtain the Stackelberg equilibrium (SE), an enhanced dueling double deep Q-network (D3QN) algorithm is proposed, which intelligently determines the optimal demand and pricing policies of MVNOs for the unutilized VMRs during ISCRT transactions at negotiation intervals. Simulation analysis shows that the proposed enhanced D3QN algorithm outperforms benchmark schemes in terms of the MVNO slice-level satisfaction and VMR utilization while reducing double-spending attacks in ISCRT settings by 16% and increasing both players’ utility.

Free Moving Gaze-related Electroencephalography in Mobile Virtual Environments

Free Moving Gaze-related Electroencephalography in Mobile Virtual Environments

Maximizing Resource Efficiency in Wireless Networks through Virtualization and Opportunistic Channel Allocation.

Wireless cellular networks have become increasingly important in providing data access to cellular users via a grid of cells. Many applications are considered to read data from smart meters for potable water, gas, or electricity. This paper proposes a novel algorithm to assign paired channels for intelligent metering through wireless connectivity, which is particularly relevant due to the commercial advantages that a virtual operator currently provides. The algorithm considers the behavior of secondary spectrum channels assigned to smart metering in a cellular network. It explores spectrum reuse in a virtual mobile operator to optimize dynamic channel assignment. The proposed algorithm exploits the white holes in the cognitive radio spectrum and considers the coexistence of different uplink channels, resulting in improved efficiency and reliability for smart metering. The work also defines the average user transmission throughput and total smart meter cell throughput as metrics to measure performance, providing insights into the effects of the chosen values on the overall performance of the proposed algorithm.

Wayfinding and path integration deficits detected using a virtual reality mobile app in patients with traumatic brain injury.

The ability to navigate is supported by a wide network of brain areas which are particularly vulnerable to disruption brain injury, including traumatic brain injury (TBI). Wayfinding and the ability to orient back to the direction you have recently come (path integration) may likely be impacted in daily life but have so far not been tested with patients with TBI. Here, we assessed spatial navigation in thirty-eight participants, fifteen of whom had a history of TBI, and twenty-three control participants. Self-estimated spatial navigation ability was assessed using the Santa Barbara Sense of Direction (SBSOD) scale. No significant difference between TBI patients and a control group was identified. Rather, results indicated that both participant groups demonstrated 'good' self-inferred spatial navigational ability on the SBSOD scale. Objective navigation ability was tested via the virtual mobile app test Sea Hero Quest (SHQ), which has been shown to predict real-world navigation difficulties and assesses (a) wayfinding across several environments and (b) path integration. Compared to a sub-sample of 13 control participants, a matched subsample of 10 TBI patients demonstrated generally poorer performance on all wayfinding environments tested. Further analysis revealed that TBI participants consistently spent a shorter duration viewing a map prior to navigating to goals. Patients showed mixed performance on the path integration task, with poor performance evident when proximal cues were absent. Our results provide preliminary evidence that TBI impacts both wayfinding and, to some extent, path integration. The findings suggest long-lasting clinical difficulties experienced in TBI patients affect both wayfinding and to some degree path integration ability.

Service Function Chains multi-resource orchestration in Virtual Mobile Edge Computing

Next-Generation Networks (NGNs) provide efficient services to improve the overall network performance, especially in Internet of Things (IoT) networks. However, service placement requires a significant cost in terms of multi-resource chaining guarantees. Therefore, the balance between improving network performance and optimizing resources orchestration is still a fundamental issue to assure the benefits of NGNs with optimal resources’ utilization. In this paper, we present new approaches for Service Function Chain (SFC) orchestration in Virtual Mobile Edge Computing (VMEC) environments, where IoT devices are used as on-demand virtual edge servers. We propose Optimal SFC Placement in VMEC over AI-IoT (OSPV) algorithm to select the optimal virtual mobile edge (VME) according to heterogeneous computing resources constraints. Moreover, to deal with OSPV complexity issues in dense IoT networks, we propose an Efficient SFC Placement in VMEC over AI-IoT (ESPV) algorithm that selects sufficient VME nodes for services operations and deployments. Furthermore, recent Deep Learning (DL) techniques such LSTM and GRU are implied to predict mobility and energy consumption sequences of IoT devices. These instances introduce feasible sets of IoT nodes, where the optimization algorithms should operate. Results show the efficiency of the DL instances and prove that the prediction awareness prevents the selected VME from failure and disconnection during the communication. Moreover, the proposed optimization algorithms are implemented and evaluated under different computing scenarios. Then, they are compared according to total allocated servers and SFC placement time. Optimization results show that both algorithms are efficient in terms of predetermined key performance indicators compared to the state of the art.

Development and Implementation of a Mobile Virtual Laboratory on Electrical Circuit Materials Using a Prophetic Integrated

Development and Implementation of a Mobile Virtual Laboratory on Electrical Circuit Materials Using a Prophetic Integrated

Mobile Carrier Change Intention Analysis Based on IT Service Management Platform

The purpose of this study is to understand the user intention to continue or change mobile carriers, considering the current mobile phone market in Japan. The market was mainly shared by three Major Mobile-Carriers (3MMC): docomo, au, and SoftBank. However, the number of Mobile Virtual Network Operators (MVNOs) customers has been increasing recently, and Rakuten Mobile has entered the mobile phone market as a Mobile Network Operator (MNO). Currently, the mobile phone market is highly competitive and there is little difference in mobile phone services offered by various carriers. Under such competitive conditions, mobile carriers need an appropriate method to develop service strategies to maintain or increase their market share. To understand users’ mobile carrier change intention, we classified each carrier’s users into two user segments based on continuous or change intention and analyzed the differences between the segments. We showed that the user segmentation model can extract information about the differences in characteristics of two user segments from their decision-making factors and user attributes with respect to mobile services. Understanding these differences is important as carriers consider when and what strategies to implement in order to maintain or increase market share.

Mobile Virtual Field Trip and Geography Education: Potential Exploration of Complex Problem Solving and Spatial Intelligence Capabilities

This study aims to determine the effect of M-VGFT media on students' Complex Problem Solving and Spatial Intelligence abilities. Quasi-experimental research with post-test-only group design method. The design used two experimental groups with a purposive or judgment sampling method considering the average class value. X.2 Social Science group (14 boys and 20 girls), X.3 Social Science group (17 boys and 17 girls), and X.4 Social Science (17 boys and 17 girls). The subjects of this study were first-year high school students in the even semester of the 2021/2022 academic year. Hypothesis testing using independent sample t-test to determine the effect of M-VGFT media on the ability of students' Complex Problem Solving and Spatial Intelligence in the subject of Geography on Volcanism. The results showed a significant influence between M-VGFT media on students' Complex Problem Solving Ability and Spatial Intelligence in Madrasah Aliah Negeri Baru. However, there are differences in the influence between male and female students on the two variables.

Enabling Mobile Virtual Reality with Open 5G, Fog Computing and Reinforcement Learning

Virtual reality (VR) is an emerging technology reshaping interactive experience and can be widely applied in gaming, operation training, and so on. Despite its great potentials, most existing VR solutions suffer from low mobility support, high latency, quick battery drain, as well as high cost of user devices. To overcome these issues, a mobile VR system is designed and implemented. The basic idea is to take advantage of 5G and fog computing to realize high bandwidth and low latency VR service. Meanwhile, our design features the integration of an open 5G base station (BS) and an intelligent controller. With the help of artificial intelligence (AI) and the interfaces provided by the BS and fog VR servers, the controller can wisely adjust both the BS-level and application-level parameters to enhance system performance. Using our prototype system, the impact of various parameters, the superiority of fog computing over cloud computing in supporting VR, and the effectiveness of AI in optimizing system performance are all demonstrated. In addition, multi-dimensional resource optimization for VR delivery and strategy design for VR service migration are identified as two promising future research directions.

Using Mobile Virtual Reality Simulation to Prepare for In-Person Helping Babies Breathe Training: Secondary Analysis of a Randomized Controlled Trial (the eHBB/mHBS Trial).

BackgroundNeonatal mortality accounts for approximately 46% of global under-5 child mortality. The widespread access to mobile devices in low- and middle-income countries has enabled innovations, such as mobile virtual reality (VR), to be leveraged in simulation education for health care workers.ObjectiveThis study explores the feasibility and educational efficacy of using mobile VR for the precourse preparation of health care professionals in neonatal resuscitation training.MethodsHealth care professionals in obstetrics and newborn care units at 20 secondary and tertiary health care facilities in Lagos, Nigeria, and Busia, Western Kenya, who had not received training in Helping Babies Breathe (HBB) within the past 1 year were randomized to access the electronic HBB VR simulation and digitized HBB Provider’s Guide (VR group) or the digitized HBB Provider’s Guide only (control group). A sample size of 91 participants per group was calculated based on the main study protocol that was previously published. Participants were directed to use the electronic HBB VR simulation and digitized HBB Provider’s Guide or the digitized HBB Provider’s Guide alone for a minimum of 20 minutes. HBB knowledge and skills assessments were then conducted, which were immediately followed by a standard, in-person HBB training course that was led by study staff and used standard HBB evaluation tools and the Neonatalie Live manikin (Laerdal Medical).ResultsA total of 179 nurses and midwives participated (VR group: n=91; control group: n=88). The overall performance scores on the knowledge check (P=.29), bag and mask ventilation skills check (P=.34), and Objective Structured Clinical Examination A checklist (P=.43) were similar between groups, with low overall pass rates (6/178, 3.4% of participants). During the Objective Structured Clinical Examination A test, participants in the VR group performed better on the critical step of positioning the head and clearing the airway (VR group: 77/90, 86%; control group: 57/88, 65%; P=.002). The median percentage of ventilations that were performed via head tilt, as recorded by the Neonatalie Live manikin, was also numerically higher in the VR group (75%, IQR 9%-98%) than in the control group (62%, IQR 13%-97%), though not statistically significantly different (P=.35). Participants in the control group performed better on the identifying a helper and reviewing the emergency plan step (VR group: 7/90, 8%; control group: 16/88, 18%; P=.045) and the washing hands step (VR group: 20/90, 22%; control group: 32/88, 36%; P=.048).ConclusionsThe use of digital interventions, such as mobile VR simulations, may be a viable approach to precourse preparation in neonatal resuscitation training for health care professionals in low- and middle-income countries.