Security-Aware Routing on Wireless Communication for E-Health Records Monitoring Using Machine Learning

An ad hoc structure is self-organizing, self-forming, and system-free, with no nearby associations. One of the significant limits we must focus on in frameworks is leading. As for directions, we can send the packet or communications from the sender to the recipient node. AODV Routing Protocol, a short display that will make the tutorial available on demand. Machine Learning (ML) based IDS must be integrated and perfected to support the detection of vulnerabilities and enable frameworks to make intrusion decisions while ML is about their mobile context. This paper considers the combined effect of stooped difficulties along the way, problems at the medium get-right-of-area to impact layer, or pack disasters triggered by the remote control going off route. The AODV as the Routing MANET protocol is used in this work, and the process is designed and evaluated using Support Vector Machine (SVM) to detect the malicious network nodes.

Unsupervised Learning for Human Mobility Behaviors

Learning human mobility behaviors from location-sensing data are crucial to mobility data mining because of its potential to address a range of analytical purposes in mobile context reasoning, including exploration, inference, and prediction. However, existing approaches suffer from two practical problems: temporal and spatial sparsity. To address these shortcomings, we present two unsupervised learning methods to model the mobility behaviors of multiple users (i.e., a population), considering efficiency and accuracy. These methods intelligently overcome the sparsity in individual data by seeking temporal commonality among users’ heterogeneous location behaviors. The advantages of our models are highlighted through experiments on several real-world mobility data sets, which also show how our methods can realize the three analytical purposes in a unified manner.

Exploring the Antecedents of Online Learning Satisfaction: Role of Flow and Comparison Between use Contexts

Learners’ satisfaction plays a critical role in the success of online learning platform. Many factors that affect online learning satisfaction have been addressed by previous studies. However, the mechanisms by which these factors are associated with online learning satisfaction are not sufficiently clear. Moreover, the difference in the antecedents of online learning satisfaction between two use contexts- Mobile context and PC context, was rarely examined. Based on the Stimulus-Organism-Response (S-O-R) framework, we investigate the key factors (self-efficacy, social interaction, platform quality, teacher’s expertise) affecting flow and highlights its role in online learning satisfaction, which is empirically tested through an online survey of 333 online learners. Results show that self-efficacy, teacher’s expertise, platform quality, and social interaction positively affect online learning satisfaction through the mediation of flow. Use contexts not only moderate the relationship between flow and online learning satisfaction, but also between social interaction, platform quality, teacher’s expertise, and flow. These new findings expand educators with ways to increase flow, add to knowledge about the relationship between flow and online learning satisfaction and provide references for online learning platforms to enhance learners’ online learning satisfaction under multiple-version affordances.

Research of Contextual Semantic Reasoning Model Based on Domain Ontology

With the development of mobile network technology and the popularization of mobile terminals, traditional information recommendation systems are gradually changing in the direction of real-time and mobile information recommendation. Information recommendation brings the problem of user contextual sensitivity within the mobile environment. For this problem, first, this paper constructs a domain ontology, which is applicable to the contextual semantic reasoning model. Second, based on the “5W + 1H” method, this paper constructs a context pedigree of the mobile environment using a model framework of a domain ontology. The contextual factors of the mobile environment are divided into six categories: the What-object context, the Where-place context, the When-time context, the Who-subject context, the Why-reason context, and the How-effect context. Then, considering the degree of influence of each contextual factor from the mobile context pedigree to the user is different, this paper uses contextual conditional entropy to calculate the contextual weight of each contextual attribute in the recommendation process. Based on this, a contextual semantic reasoning model based on a domain ontology is constructed. Finally, based on the open dataset provided by GroupLens, this paper verifies the validity and efficiency of the model through a simulation experiment.

Implementasi m-learning berbasis Mobile Context Aware System (MCAS) dalam pembelajaran Geografi pada masa pandemi Covid-19

Learning during the Covid-19 pandemic caused learning activity to be online and causes student’s boredom in Geography. Therefore, teachers must integrating the technology in learning process, with mobile learning (M-Learning) based on mobile context aware systems (MCAS). The study purpose is to determine student’s opinions about implementation of MCAS based M-Learning during the pandemic. This research is a descriptive qualitative with a mix method approach used collection techniques field research and literature study. The results showed that students had a positive opinion regarding the implementation of MCAS based M-Learning during the pandemic, with an average score of 3.40-3.70 out of 4.00. Pembelajaran pada masa pandemi Covid-19 menyebabkan pembelajaran menjadi online sehingga menyebabkan terjadinya kejenuhan siswa dalam proses pembelajaran Geografi. Oleh karena itu, guru harus mampu mengintegrasikan teknologi dalam pembelajaran, melalui mobile learning (M-Learning) berbasis mobile context aware systems (MCAS). Penelitian ini bertujuan mengetahui opini siswa dalam penerapan M-Learning berbasis MCAS pada masa pandemi. Jenis penelitian ini termasuk kualitatif deskriptif dengan pendekatan mix method serta teknik pengumpulan data berupa penelitian lapangan serta studi kepustakaan. Hasil penelitian menunjukkan bahwa siswa memiliki opini positif terkait implementasi M-Learning berbasis MCAS pada masa pandemi, dengan perolehan skor rata-rata skor 3,40-3,70 dari 4,00.

The influence of mobile application design features on users' stickiness intentions as mediated by emotional response

PurposeThe purpose of this paper is to determine the influence of mobile design features on consumers' mobile app stickiness intentions, as mediated by users' emotional response (pleasure, arousal and dominance).Design/methodology/approachUsing the stimulus–organism–response model, this study employed conditional process modelling to investigate the influence of three categories of mobile design features on users' stickiness intentions. The emotional responses of pleasure–arousal–dominance were investigated for their mediating effect. The participants included women aged 18–36.FindingsDesign features provided consumer-led interactions’ influence on emotional responses of pleasure, arousal and dominance. Mobile design features were not a significant predictor of stickiness intentions. Arousal was a significant mediator of mobile design features on stickiness intentions, whereas dominance had no mediating effects.Originality/valueThis paper extends the growing research on mobile applications by investigating design features using Magrath and McCormick's (2013) mobile marketing design framework. This paper also adds to the body of knowledge on stickiness within a mobile context.

Mobile Pedestrian Navigation and Augmented Reality in the Virtualization of the Territory

Establishing the meanings and relationships that exist between the creation of heritage educational content of applications with elements of mobile pedestrian navigation and mobile augmented reality and learning processes through mobile devices is the objective of this research. From this portable and mobile context, a teaching process linked to territorial information on the architectural and historical heritage corresponding to the cities of Salamanca (Spain) and Santiago (Chile) has been developed, proving its educational effectiveness. Methodologically, the research focuses on two areas: the educational design of recourses for learning through augmented reality and mobile pedestrian navigation on heritage contents and the determination of the modes of understanding and educational effectiveness of the app created in relation to other traditional learning tools. In this way, the construction of a patrimonial thematic unit has been developed with the determination of the scope of this tool in the mobile learning processes considering the processes of identity and local culture.

Digital Technologies as Tools to Promote Tourism and Territorial Development

Digital platforms can facilitate the establishment of collaboration networks between tourists and local agents, promoting the importance of dialogue, as well as the opportunity for constant innovation. In this way, digital platforms can help tourists co-create their most valuable experiences with other tourists and influence a tourism destination's success. This chapter aims to describe the process of studying and analysing the possibility of implementing a digital solution, which intends to encourage interactions between different local agents and tourists, facilitating communication processes and collaboration and encouraging the joint creation of innovative “bottom-up” initiatives. Considering the different potentialities of the mobile context for tourism, health, and wellness, it was decided to develop a mobile application, which aims to facilitate their communication processes, allowing for constant connectivity inside the network. This article presents the main results of the development and validation process of the mobile application prototype.