A Survey on Haptic Technologies for Mobile Augmented Reality

Augmented reality (AR) applications have gained much research and industry attention. Moreover, the mobile counterpart—mobile augmented reality (MAR) is one of the most explosive growth areas for AR applications in the mobile environment (e.g., smartphones). The technical improvements in the hardware of smartphones, tablets, and smart-glasses provide an advantage for the wide use of mobile AR in the real world and experience these AR applications anywhere. However, the mobile nature of MAR applications can limit users’ interaction capabilities, such as input and haptic feedback. In this survey, we analyze current research issues in the area of human-computer interaction for haptic technologies in MAR scenarios. The survey first presents human sensing capabilities and their applicability in AR applications. We classify haptic devices into two groups according to the triggered sense: cutaneous/tactile : touch, active surfaces, and mid-air; kinesthetic : manipulandum, grasp, and exoskeleton. Due to MAR applications’ mobile capabilities, we mainly focus our study on wearable haptic devices for each category and their AR possibilities. To conclude, we discuss the future paths that haptic feedback should follow for MAR applications and their challenges.

Performance Investigation of Routing Protocol with the velocity of 30 m/s for Random Mobility Model

A mobile ad-hoc network (MANET) is a network of mobile nodes short of Infrastructure, linked by wireless links. While mobility is the key feature of MANETs, the frequent movement of nodes may lead to link failure. A mobile multi-hop wireless ad hoc network carries a dynamic structure feature, and each node has mobility; due to this, the network has altered topology change dynamically. Developing the wireless ad hoc network protocol is the major challenge because, compared to the wired routing node, all node is mobile, energy limitation, the node's physical location, and multicast routing. In this article, a comparative investigation of routing protocol performance for large wireless ad hoc networks (100 nodes) under the impact of the random mobile environment with the velocity of 30 m/sec for 1800 seconds with ten different results for each node-set. The comparative analysis includes packet delivery ratio, throughput, packet dropping ratio, routing overhead, and end-to-end delay quality of service (QoS) metrics. It concludes that Ad-hoc On-demand Distance Vector protocol performance is more stable as the number of nodes & traffic increase in the random mobility environment.

Routine Vaccine Simulation for Infants in a Mobile Environment

Purpose–Thisstudy aimed to develop and evaluate the Routine Vaccine Simulation for Infants. The routine vaccine simulation application was developed for the health workers and parents to provide basic information and press the importance of the vaccination to infants.Method–The researchers used the fourth-generation technique (4GT) for the software development life cycle of the application. The technique adapted contains four major parts namely, requirements gathering, design strategy, implementation, and testing.Results–The application was tested and evaluated by health workers, parents, and IT practitioners from the academe and the industry. The evaluation was based on criteria for core app quality. Descriptive and inferential statistics were employed for data presentation and interpretation. As a whole, the evaluation of the android-based routine vaccine simulation application was found excellent in most of its features. The finding asserts the adherence to the standards of android developmentapplicationsand conforms to the expectations of the app’s potentialusers. Conclusion–The development of a routine vaccine app for infants serves as a new platform for immunization awareness and education. Once information given in the app is taken earnestly, infants will be protected against diseases. Thus, controversies surrounding vaccination hesitancies can be decreased.Recommendations–A thorough information dissemination and education campaign regarding vaccine safety can be initiated in the local communities to address the issues on vaccine safety and hesitancy.Research Implications–The healthcare system in the communities through the local government unit (LGU) willbe able to benchmark and implement the information dissemination and education to mothers and health workers using the app.

Contextual Bandit Based Rate Adaptation Mechanism for IEEE 802.11 Mobile Wireless LANs

<div>Rate adaptation (RA) is used in IEEE 802.11 WLANs to determine the optimal datarate for a particular channel condition. It becomes especially difficult to determine the optimal datarate for the new High-Throughput WLANs (802.11ac/ax) since the number of available datarates in these standards are very high. Moreover, a mobile environment poses additional challenge in RA as the channel conditions will keep on changing from time to time. In this paper, we propose a Contextual Bandits based Rate Adaptation (ContRA) algorithm for mobile users in IEEE 802.11ac/ax standards. Based on the Received Signal Strength Indicator (RSSI) range that the receiver is currently in, the RA algorithm tries to determine the optimal rate from the rate set suitable for packet transmission in that RSSI range. Performance studies show that the proposed RA algorithm is able to adapt to changing channel conditions and quickly choose a suitable datarate for those channel conditions.</div>

Contextual Bandit Based Rate Adaptation Mechanism for IEEE 802.11 Mobile Wireless LANs

<div>Rate adaptation (RA) is used in IEEE 802.11 WLANs to determine the optimal datarate for a particular channel condition. It becomes especially difficult to determine the optimal datarate for the new High-Throughput WLANs (802.11ac/ax) since the number of available datarates in these standards are very high. Moreover, a mobile environment poses additional challenge in RA as the channel conditions will keep on changing from time to time. In this paper, we propose a Contextual Bandits based Rate Adaptation (ContRA) algorithm for mobile users in IEEE 802.11ac/ax standards. Based on the Received Signal Strength Indicator (RSSI) range that the receiver is currently in, the RA algorithm tries to determine the optimal rate from the rate set suitable for packet transmission in that RSSI range. Performance studies show that the proposed RA algorithm is able to adapt to changing channel conditions and quickly choose a suitable datarate for those channel conditions.</div>

A set of criteria for evaluating map application design in a mobile environment

With the appearance of smartphones and affordable mobile phone plans including (internet) data within the last decade, mobile cartography in the sense of map applications became available to a wide user group including professionals and non-professionals. This paper defines the field of mobile cartography, deals with new research areas and prerequisites concerning mobile cartography and a set of criteria for evaluating map applications has been derived. For this work, the criteria have been applied to several map applications in order to evaluate them and present recent features and possible actions. In particular, the focus has been set on high-quality map applications for Austria and on novel navigation and routing capabilities. Results showed that the guideline presented in this paper can already be well applied but can still be improved upon.

Antecedents and Consequences of Trust and Loyalty in Physical Banks Affecting Mobile Payments

The way of payment has changed in recent years: people have turned away from physical payment methods to virtual payment methods. The traditional banking industry is facing challenges brought by new technologies. The main purpose of this study is to investigate customer trust and loyalty transferring from physical banks to mobile payments because mobile payment platforms are a self-service technology. The goal is to create an eco-platform to facilitate transition from a cash-based economy to a cashless economy. This study is the first attempt to integrate platform management, electronic marketing (online trust and online loyalty), and relationship marketing (offline trust and offline loyalty) into one model. We theoretically and empirically take certain factors into consideration to further explore the transfer impact of physical to mobile payments, which is not discussed in literature. The SEM (structural equation modelling) analysis from the 353 respondents in this study found that trust from both the physical and mobile contexts has positively influenced loyalty. Additionally, customers’ trust and loyalty transfer from the physical to the mobile environment has had a significantly positive effect between the physical and mobile environment. Corporate reputation and structure assurance have also significantly positively affected physical trust and mobile trust, respectively. The findings also reveal that the structure assurance plays an essential role in mobile payment. Users may have certain concerns about the procedure of transactions and their personal information. Theoretical and practical implications are provided.

Automatic Depression Detection of Mobile-Based Text-dependent Speech Signals Using a Deep CNN Approach: A Prospective Cohort Study (Preprint)

BACKGROUND In the future, automatic diagnosis of depression based on speech could complement mental health treatment methods. Previous studies have reported that acoustic properties can be used to recognize depression, including mel-frequency cepstrum coefficients (MFCCs) applied to speech recognition. However, there are few studies in which these characteristics allow differential diagnosis of patients with depressive disorder. OBJECTIVE This paper proposes a framework to help with automatic depression detection in a mobile environment where speech data can be easily obtained. Specifically, we recorded speech data by performing a predefined text-based speech reading task on mobile, investigated whether the recorded data can screen for depression, and proposed a deep learning-based framework that helps in automatic depression detection. METHODS We recruited 125 patients who met the criteria for major depressive disorder (MDD) and 113 healthy controls without current or past mental illness. Participants' voices were recorded on smart-phone while performing the task of reading predefined text-based sentences. We investigated the differences in the voice characteristics between MDD and healthy control groups using statistical analysis. We also investigated the possibility of automatic depression detection using the proposed log mel (LM) spectrogram-based deep Convolutional Neural Networks (CNN) architectures and machine learning models. RESULTS We found that there were statistically discernable differences between MDD and control groups in the MFCC features extracted through the utterances of reading predefined text-based sentences. Moreover, the best accuracies achieved with LM spectrogram-based CNN and softmax classifier on the speech data are 80.00% accuracy. Our results show that the deep-learned acoustic characteristics lead to better performances of classifiers than those using the conventional approach. CONCLUSIONS Conclusions: In conclusion, this study suggests that the analysis of speech data recorded while reading text-dependent sentences could help predict depression status automatically by capturing characteristics of depression. Our method can contribute to an approach that allows individuals to easily and automatically assess their depressive state anytime, anywhere, without the need for experts to conduct psychological assessments on-site.

From keyword to keywords: the role of keyword portfolio variety and disparity in product sales

PurposeThis study investigates the effect of keyword portfolio characteristics on sales in paid search advertising. The authors propose two keyword portfolio characteristics (variety and disparity) and examine the effects of portfolio variety and portfolio disparity on direct and indirect sales in both PC and mobile environment.Design/methodology/approachBy conducting a field study at a large e-commerce platform, the authors use a negative binomial model to develop empirical findings that provide insights into paid search advertising strategies.FindingsFor main effect, (1) portfolio variety has a negative effect on direct sales. However, (2) portfolio disparity has positive effects on both direct and indirect sales. Advertising channels influence the contribution of keyword portfolio to sales. (3) On mobile devices, portfolio variety positively affects both direct and indirect sales. However, portfolio disparity negatively affects both direct and indirect sales. (4) On PCs, portfolio variety negatively affects both direct and indirect sales. However, portfolio disparity positively affects both direct and indirect sales on PC.Practical implicationsThe findings provide advertisers with insights into how to manage keyword portfolio between mobile devices and PCs.Originality/valueThe current study shifts the attention from keyword to keywords (keyword portfolio), which extends the paid search literature. Moreover, it also contributes to the literature by comparing the relative effectiveness of mobile and PC search advertising.

Web Service Discovery Approaches for Dynamic Mobile Environment

Mobile web service (MWS) discovery is taking a new direction due to the explosion of users accessing mobile services using diverse mobile devices, coupled with the persistent changes in a dynamic mobile environment (DME). This leads to renewed adoption of lightweight solutions for the identification of the most suitable web services that correspond with the service requests. Contemporary mobile web service discovery approaches are plagued with performance and accuracy problems and are rarely compatible with the DME. The objective of this systematic literature review is to develop a more rigorous understanding and identify recent research trends in mobile web service discovery techniques in a dynamic mobile environment. This review followed the systematic literature review (SLR) guidelines. Essential information was extracted from the 76 relevant articles in line with the formulated questions and finally reported after in-depth analysis. The results of this study discuss the critical contributions and limitations of the proposed approaches.