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Khan, Muhammad Umair, Scott Uk-Jin Lee, Zhiqiang Wu, and Shanza Abbas. "Wake Lock Leak Detection in Android Apps Using Multi-Layer Perceptron." Electronics 10, no. 18 (September 9, 2021): 2211. http://dx.doi.org/10.3390/electronics10182211.
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With the proliferation of mobile devices, the popularity of Android applications (apps) has increased exponentially. Efficient power consumption in a device is essential from the perspective of the user because users want their devices to work all day. Developers must properly utilize the application programming interfaces (APIs) provided by Android software development kit to optimize the power consumption of their app. Occasionally, developers fail to relinquish the resources required by their app, resulting in a resource leak. Wake lock APIs are used in apps to manage the power state of the Android smartphone, and they frequently consume more power than necessary if not used appropriately (also called energy leak). In this study, we use a multi-layer perceptron (MLP) to detect wake lock leaks in Android apps because the MLP can solve complex problems and determine similarities in graphs. To detect wake lock leaks, we extract the call graph as features from the APK and embed the instruction and neighbor information in the node’s label of the call graph. Then, the encoded data are input to an MLP model for training and testing. We demonstrate that our model can identify wake lock leaks in apps with 99% accuracy.
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Zhu, Konglin, Zexuan Liu, Lin Zhang, and Xinyu Gu. "A Mobile Application Recommendation Framework by Exploiting Personal Preference with Constraints." Mobile Information Systems 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/4542326.
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Explosive mobile applications (Apps) are proliferating with the popularity of mobile devices (e.g., smartphones, tablets). These Apps are developed to satisfy different function needs of users. Majority of existing App Stores have difficulty in recommending proper Apps for users. Therefore, it is of significance to recommend mobile Apps for users according to personal preference and various constraints of mobile devices (e.g., battery power). In this paper, we propose a mobile App recommendation framework by incorporating different requirements from users. We exploit modern portfolio theory (MPT) to combine the popularity of mobile Apps, personal preference, and mobile device constraints for mobile App recommendation. Based on this framework, we discuss the recommendation approaches by constraints of phone power and limited mobile data plan. Extensive evaluations show that the proposed mobile App recommendation framework can well adapt to power and network data plan constraints. It satisfies the user App preference and mobile device constraints.
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Chadha, Priyanka, Shirin Alavi, and Vandana Ahuja. "Mobile Shopping Apps." International Journal of Cyber Behavior, Psychology and Learning 7, no. 4 (October 2017): 40–55. http://dx.doi.org/10.4018/ijcbpl.2017100104.
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This article describes how the retailing business has changed drastically in the recent times. The emergence of Internet and mobile channels are primarily responsible for this. The present generation comprises of a group of consumers with strong purchasing power and superior online habits in comparison to previous generations. The younger generation is much more experienced with the Internet and mobile devices and is thus more susceptible to engage in shopping through mobile apps. These empowered consumers are keen to have consistent customer experiences and are always challenging retailers to meet their evolving needs and demands. They can easily switch from one retailer to another with a couple of touches on their smart phones. These increased opportunities also increase competition. The mobile commerce helps the online retailers to present themselves fit in the market and uniquely use the cosmic opportunities. This article focuses on a set of ten different mobile shopping apps and identifies the functionalities offered by these apps. The article further proceeds to explore the specific consumer needs satisfied through mobile shopping which influence its adoption and usage.
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Giannella, Lorenza. "The power of online learning." Biochemist 39, no. 6 (December 1, 2017): 42–43. http://dx.doi.org/10.1042/bio03906042.
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We live in an era where technology is embedded in everything we do. We use the Internet and various apps numerous times every day to order our favourite takeaway, keep in touch with friends and book GP appointments. In this digital age, technology is also deeply influencing education and learning, especially in science.
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Langerman, David, and Alan George. "Real-time, High-resolution Depth Upsampling on Embedded Accelerators." ACM Transactions on Embedded Computing Systems 20, no. 3 (April 2021): 1–22. http://dx.doi.org/10.1145/3436878.
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High-resolution, low-latency apps in computer vision are ubiquitous in today’s world of mixed-reality devices. These innovations provide a platform that can leverage the improving technology of depth sensors and embedded accelerators to enable higher-resolution, lower-latency processing for 3D scenes using depth-upsampling algorithms. This research demonstrates that filter-based upsampling algorithms are feasible for mixed-reality apps using low-power hardware accelerators. The authors parallelized and evaluated a depth-upsampling algorithm on two different devices: a reconfigurable-logic FPGA embedded within a low-power SoC; and a fixed-logic embedded graphics processing unit. We demonstrate that both accelerators can meet the real-time requirements of 11 ms latency for mixed-reality apps. 1
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Du, Li, Vera Lúcia Raposo, and Meng Wang. "COVID-19 Contact Tracing Apps: A Technologic Tower of Babel and the Gap for International Pandemic Control." JMIR mHealth and uHealth 8, no. 11 (November 27, 2020): e23194. http://dx.doi.org/10.2196/23194.
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As the world struggles with the new COVID-19 pandemic, contact tracing apps of various types have been adopted in many jurisdictions for combating the spread of the SARS-CoV-2 virus. However, even if they are successful in containing the virus within national borders, these apps are becoming ineffective as international travel is gradually resumed. The problem rests in the plurality of apps and their inability to operate in a synchronized manner, as well as the absence of an international entity with the power to coordinate and analyze the information collected by the disparate apps. The risk of creating a useless Tower of Babel of COVID-19 contact tracing apps is very real, endangering global health. This paper analyzes legal barriers for realizing the interoperability of contact tracing apps and emphasizes the need for developing coordinated solutions to promote safe international travel and global pandemic control.
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Tseng, Chun Hsiung, Yung Hui Chen, Yan Ru Jiang, Chu Chun Chuang, Jia Hua Wu, and Han Ci Syu. "APP Rush, a Platform of Learning APP Development Skills for Information Management Students." Applied Mechanics and Materials 764-765 (May 2015): 843–47. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.843.
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Developing useful apps has never been an easy task. Although modern mobile phones/tablets have more and more computation power, it is still not possible to treat them as real computers. Hence, many apps rely on external components to provide services. However, this complicates the development of apps. Unlike students in the computer science department, information management students do not have equally solid programming background. App development related courses have a more rigid learning curve for them. In this paper, APPRush, a platform for developing usable apps and for learning app design skills, is proposed. Both students and ordinary app developers can benefit from the resulting platform.
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Mahmoud Almasri, Abdullah, and Luis Borges Gouveia. "Star-rating evaluation model for rating the energy-efficiency level of android google play apps." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 2 (April 1, 2021): 1599. http://dx.doi.org/10.11591/ijece.v11i2.pp1599-1612.
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The tremendous increase in smartphone usage is accompanied by an increase in the need for more energy. This preoperational relationship between modern technology and energy generates energy-greedy apps, and therefore power-hungry end users. With many apps falling under the same category in an app store, these apps usually share similar functionality. Because developers follow different design and development schools, each app has its energy-consumption habits. Since apps share similar features, an end-user with limited access to recharging resources would prefer an energy-friendly app rather than a popular energy-greedy app. However, app stores do not indicate the energy behavior of the apps they offer, which causes users to randomly choose apps without understanding their energy-consumption behavior. A review of the relevant literature was provided covering various energy-saving techniques. The results gave an initial impression about the popularity of the usage of two power-saving modes where the average usage of these modes did not exceed 31% among the total 443 Android users. To address this issue, we propose a star-rating evaluation model (SREM), an approach that generates a tentative energy rating label for each app. The model was tested on 7 open-source apps to act as a primary evaluation sample. To that end, SREM adapts current energy-aware refactoring tools to demonstrate the level of energy consumption of an app and presents it in a star-rating schema similar to the Ecolabels used on electrical home appliances. As per our results, SREM helped in saving 35% of smartphone energy.
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Silva, Rui, Markel Rico-González, Ricardo Lima, Zeki Akyildiz, José Pino-Ortega, and Filipe Manuel Clemente. "Validity and Reliability of Mobile Applications for Assessing Strength, Power, Velocity, and Change-of-Direction: A Systematic Review." Sensors 21, no. 8 (April 8, 2021): 2623. http://dx.doi.org/10.3390/s21082623.
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This systematic review aimed to (1) identify and summarize studies that have examined the validity of apps for measuring human strength, power, velocity, and change-of-direction, and (2) identify and summarize studies that have examined the reliability of apps for measuring human strength, power, velocity, and change-of-direction. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 435 studies initially identified, 23 were fully reviewed, and their outcome measures were extracted and analyzed. In total, 11 mobile applications were analyzed and summarized for their validity and reliability to test movement velocity, movement time, movement displacement, power output, and workload. The present systematic review revealed that the tested apps are valid and reliable for measuring bar movement velocity during lower and upper body resistance exercises; however, systematic bias was detected with heavier loads.
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Lam, Long W., and Angela J. Xu. "Power Imbalance and Employee Silence: The Role of Abusive Leadership, Power Distance Orientation, and Perceived Organisational Politics." Applied Psychology 68, no. 3 (October 10, 2018): 513–46. http://dx.doi.org/10.1111/apps.12170.
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Oose, Mathew Olekan, Oluwakemi E. Fapojuwo, and Jibril A. Agbabiaka. "Influence of Internet-based Mobile Phone Applications on Employees Job Commitment in Agricultural Research Institutes in Oyo State, Nigeria." Journal of Agricultural Extension 25, no. 2 (May 4, 2021): 43–53. http://dx.doi.org/10.4314/jae.v25i2.4.
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This study assessed factors influencing the use of internet-based mobile phone apps on employees on job commitment in agriculturalresearch institutes in Oyo State, Nigeria. A multistage sampling procedure was used to select 94 employees. The data were obtainedthrough a structured questionnaire and analyzed using percentages, chi-square analysis and principal component analysis (PCA). Result showed that Whatsapp ( x̄ =3.32), Emails (x̄ =3.23) and Opera mini(x ̄ =3.23) were the most frequently used internet-based mobile phone apps. The use of internet-based mobile apps enhances their job commitments ( x̄ =3.86) while using internet-based mobile apps saves time (x̄ =3.54). Fluctuations of internet connectivity (x̄ =2.71) and epileptic power supply ( x̄ =2.36) were factors influencing the use of internet-based mobile phone apps. Significant relationship (P≤0.05) existed between employees use of whatsApp (χ2=9.80), Email (χ2=6.60) and Instagram (χ2=-16.0) and job commitment. PCA reveals that fluctuation of internet connectivity (0.78) was the major determinants of employees’ use of internet-based mobile phone apps. It was concluded that whatsapp and emails positively influenced employees’ commitment to their job with favourable and positive perceive ease of use of these internet-based mobile apps. Therefore, the study recommended that stable and functional internet facilities should be in agricultural research institutes to enable employees explore the potentials of internet-based mobile phone apps.
Keywords: Internet-based mobile phone apps, job commitment, employees, agricultural research institutes
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Zhang, Jingwen, Christopher Calabrese, Jieyu Ding, Mingxuan Liu, and Biying Zhang. "Advantages and challenges in using mobile apps for field experiments: A systematic review and a case study." Mobile Media & Communication 6, no. 2 (September 5, 2017): 179–96. http://dx.doi.org/10.1177/2050157917725550.
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As smartphone’s computing power continues to grow and as mobile applications (apps) continue to dominate digital engagement, apps have become a new frontier for advancing field experiment methodology. Using apps may help researchers to scale up the reach, precisely control randomization and experiment materials, collect a variety of objective and self-reported data over time, and more conveniently replicate and adapt an experiment. We performed a systematic review on field experiments involving apps published between 2007 and 2017. Seven databases were scanned using a predefined search strategy. The database search retrieved 4,810 citations; 101 articles met the inclusion criteria. Our review suggests that scholars have only started to employ apps in field experiments in the last 4 years. Most studies only used apps as an experiment treatment instead of an experiment platform; therefore, researchers have yet to fully leverage the advantages. Almost all studies were from the health research domain and 77.2% used randomized controlled trial design. Only 7 studies utilized smartphone sensors for collecting data. Only one study reported cost and ethical concerns regarding using apps for the experiment. Given these findings, we reported a case study that targeted a minority racial group and leveraged the advantages of apps as an experiment platform and as a data collection tool to illustrate practical challenges and lessons learned regarding time, financial cost, and technical support. In conclusion, we suggest apps provide new ways to study causal mechanisms with experiment big data. Limitations of generalizability, retention, and design quality were discussed as well.
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Shofi, Niam, Iskandar Fitri, and Agus Iskandar. "Perancangan Sistem Manajemen Absensi Online dengan Barcode scanner Menggunakan Power Apps." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 5, no. 4 (November 18, 2021): 430. http://dx.doi.org/10.35870/jtik.v5i4.272.
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Attendance is a form of attachment or obligation between employees and companies, especially at PT. IDX with work locations for project employees who are spread across many companies and different office locations, namely in Jakarta and Bandung. Based on this study, an online-based employee attendance system using the barcode scanner method is applied, because previously employees were still using manual signatures with insufficient security systems and concerns about data leakage, with this attendance system employees do not need to sign manually, resulting in fraud. attendance can be avoided. The application of QR code technology to the employee attendance system can speed up the employee attendance process. Besides that, it can also help make it easier for the HRD Team in managing employee attendance reports to make it more effective and efficient.Keywords:Attendance Application, Attendance System, Power Apps, One Drive Application.
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Miatello, Ashleigh, Gillian Mulvale, Christina Hackett, Alison Mulvale, Ashwin Kutty, and Faten Alshazly. "Data Elicited Through Apps for Health Systems Improvement." International Journal of Qualitative Methods 17, no. 1 (October 1, 2018): 160940691879843. http://dx.doi.org/10.1177/1609406918798433.
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A promising approach to meeting the need in many jurisdictions for timely, in-depth qualitative health systems experience data, is to elicit feedback through smartphone and web applications (apps). Apps offer an appealing tool to elicit data from patients and family members who may feel stigma when receiving some services and a power imbalance when providing feedback to health-care providers. In this article, we examine the effectiveness of a suite of smartphone and web apps called myExperience ( myEXP) that were created to gather care experiences of youth, family members, and service providers as part of an experience-based co-design (EBCD) study in Ontario involving youth with mental disorders. We analyzed data from 12 triads of youth (aged 16–24), family members, and service providers gathered between August 2015 and December 2016. We used qualitative content analysis to understand participant feedback on the myEXP apps and identify thematic categories that emerged from experience data elicited through the myEXP apps. We found overall that the myEXP apps were more effective at eliciting experience data from youth compared with family members and service providers. Rich experience data were gathered from youth about treatment plans in real time through the apps. The apps also showed important promise as reflective tools for all participants. They may offer advantages in research that seeks to improve responsiveness in service delivery and build mutual understanding. The apps also offer choice in how data are elicited, encourage more candid feedback and help to overcome stigma, which are important considerations for some vulnerable populations. For service redesign research using approaches such as EBCD, apps offer real-time data gathering that can complement and enhance traditional approaches such as retrospective interviews and observation.
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Maceli, Kristen M. "Changes In The Development Process Of Mobile Phone Applications Bring Opportunities For Developers And More Options To Consumers." Journal of Business Case Studies (JBCS) 7, no. 3 (April 28, 2011): 31. http://dx.doi.org/10.19030/jbcs.v7i3.4266.
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Consumers are becoming increasingly comfortable with technology. As their knowledge and use of technology has increased, so too have their expectations and roles in the technology environment. New technology brings about new products, and the process of developing new products is ongoing. Research and development, turnaround times, product introduction timing, and development efforts of the competition all influence the process. The race to move new technology to the market as quickly as possible has significantly changed the development process. Individuals now have development opportunities that generally belonged to corporations years ago. As Smartphones become more mainstream, the race to create applications (apps) for the devices has presented entrepreneurial opportunities for companies and individuals alike. Not only is the demand for apps increasing, but the power of apps is also increasing. Apps have the ability to affect consumer demands and, ultimately, impact what is available in the marketplace.
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Wai, Iris Shuk Han, Sara Sze Yan Ng, Dickson K. W. Chiu, Kevin K. W. Ho, and Patrick Lo. "Exploring undergraduate students’ usage pattern of mobile apps for education." Journal of Librarianship and Information Science 50, no. 1 (August 30, 2016): 34–47. http://dx.doi.org/10.1177/0961000616662699.
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In recent years, with the general adoption of smartphones with computing power comparable to desktop computers, mobile applications (apps) have experienced a surge in popularity. However, there are few studies conducted about their educational use, especially in Southeast Asia. To close this research gap, this study aims to provide a current overview of mobile apps usage in higher education. Besides exploring the actual use of apps, the technology acceptance model was applied to examine (1) undergraduate students’ perceptions, which involve perceived usefulness and perceived ease of use, towards adopting mobile apps for educational purposes, and (2) their overall attitude toward such adoption. Both quantitative and qualitative methods were used to collect data from 150 undergraduate students in Business, Education, and Engineering in Hong Kong. The results show undergraduate students use mobile apps frequently to engage in learning activities related to their academic studies, with a particularly focus on communication and collaborative working, accessing academic resources, and checking a dictionary. However, the discrepancies in using apps for academic purposes are not significant between the three faculties. Meanwhile, perceived usefulness has a more positive impact on overall attitude compared with the impact of perceived ease of use. The investigation will help tertiary institutions, library service providers, and educators develop and assess strategic planning for education collaborating with mobile apps. This paper could also give app developers some suggestions for app design based on actual usage and students’ information needs.
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Thanigan, Jayanthi, Srinivasa N. Reddy, Priya Sethuraman, and J. Irudhaya Rajesh. "Understanding Consumer Acceptance of M-Wallet Apps." Journal of Electronic Commerce in Organizations 19, no. 1 (January 2021): 65–91. http://dx.doi.org/10.4018/jeco.2021010104.
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The m-wallet apps market in India is an evolving industry. M-wallet app companies could use the consumer insights from this study to design suitable strategies to retain existing users and attract new customers. Earlier studies in m-wallet app adoption in India have been restricted to GPRS services only. This study is unique in extending use of the UTAUT model theoretical framework to understand the factors influencing customers using the evolved 4G technology in India. The research hypothesis, based on the extended UTAUT model, was empirically tested using structural equation modeling. There was a significant improvement in the overall explanatory power of the extended UTAUT model over the original UTAUT.
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He, Gaofeng, Bingfeng Xu, Lu Zhang, and Haiting Zhu. "On-Device Detection of Repackaged Android Malware via Traffic Clustering." Security and Communication Networks 2020 (May 31, 2020): 1–19. http://dx.doi.org/10.1155/2020/8630748.
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Malware has become a significant problem on the Android platform. To defend against Android malware, researchers have proposed several on-device detection methods. Typically, these on-device detection methods are composed of two steps: (i) extracting the apps’ behavior features from the mobile devices and (ii) sending the extracted features to remote servers (such as a cloud platform) for analysis. By monitoring the behaviors of the apps that are running on mobile devices, available methods can detect suspicious applications (simply, apps) accurately. However, mobile devices are typically resource limited. The feature extraction and massive data transmission might consume substantial power and CPU resources; thus, the performance of mobile devices will be degraded. To address this issue, we propose a novel method for detecting Android malware by clustering apps’ traffic at the edge computing nodes. First, a new integrated architecture of the cloud, edge, and mobile devices for Android malware detection is presented. Then, for repackaged Android malware, the network traffic content and statistics are extracted at the edge as detection features. Finally, in the cloud, similarities between apps are calculated, and the similarity values are automatically clustered to separate the original apps and the malware. The experimental results demonstrate that the proposed method can detect repackaged Android malware with high precision and with a minimal impact on the performance of mobile devices.
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Ouyang, Yi, Bin Guo, Xing Tang, Xiuqiang He, Jian Xiong, and Zhiwen Yu. "Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network." ACM Transactions on Knowledge Discovery from Data 15, no. 4 (June 2021): 1–21. http://dx.doi.org/10.1145/3442201.
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With the rapid development of mobile app ecosystem, mobile apps have grown greatly popular. The explosive growth of apps makes it difficult for users to find apps that meet their interests. Therefore, it is necessary to recommend user with a personalized set of apps. However, one of the challenges is data sparsity, as users’ historical behavior data are usually insufficient. In fact, user’s behaviors from different domains in app store regarding the same apps are usually relevant. Therefore, we can alleviate the sparsity using complementary information from correlated domains. It is intuitive to model users’ behaviors using graph, and graph neural networks have shown the great power for representation learning. In this article, we propose a novel model, Deep Multi-Graph Embedding (DMGE), to learn cross-domain app embedding. Specifically, we first construct a multi-graph based on users’ behaviors from different domains, and then propose a multi-graph neural network to learn cross-domain app embedding. Particularly, we present an adaptive method to balance the weight of each domain and efficiently train the model. Finally, we achieve cross-domain app recommendation based on the learned app embedding. Extensive experiments on real-world datasets show that DMGE outperforms other state-of-art embedding methods.
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Viswanathan, C., P. Sailaja, G. Manimala, and V. Prasanna Srinivasan. "Learning Based Download of Health Care Confidentiality Apps Iot with Power Storage." Journal of Physics: Conference Series 1964, no. 4 (July 1, 2021): 042094. http://dx.doi.org/10.1088/1742-6596/1964/4/042094.
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Kaye, Barbara K., and Thomas J. Johnson. "An APPetite for APPs: A Comparison of Heavily Reliant and Light Reliant App Users on Political Activity and Media Reliance." Social Science Computer Review 37, no. 4 (May 20, 2018): 451–65. http://dx.doi.org/10.1177/0894439318774856.
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The ubiquity of mobile devices and the apps that power them has spurred concerns that they are contributing to the decline in news media use. Mobile devices, however, have been credited with spurring political participation. In its examination of app-reliant individuals, this study found that reliance on apps positively predicts political participation, and respondents who rely heavily on mobile apps for political information are more politically active than light app users on six of the seven measures of nononline participation and three of the six measures of online political activity. Heavy-reliant users also rely more heavily on all six online-only media tested than light app users and rely more heavily on broadcast television news, CNN, and news magazines. Data were collected from October 31, 2016, through November 2, 2016, from 644 respondents of a national online panel.
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Margulieux, Lauren E., Dar-Wei Chen, Joseph D. McDonald, Keith R. Bujak, Thomas M. Gable, Cale M. Darling, Laura M. Schaeffer, and Laura H. Barg-Walkow. "Online Collaboration Applications Evaluated Based on Ease of Use." Ergonomics in Design: The Quarterly of Human Factors Applications 24, no. 2 (April 2016): 21–30. http://dx.doi.org/10.1177/1064804615611273.
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Many online applications promise to unlock the power of collaborative work by connecting people from around the world. Finding an app that is appropriate for a task and easy to use, however, can be difficult. In this study, we evaluated 20 popular apps according to the basic work functions they accomplish (e.g., sharing files) and their adherence to the classic usability standards outlined by Nielsen and Molich. The results can help teams find apps that perform functions that are necessary for their tasks and ensure that the selected app is the best option for the team’s productivity.
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Hu, Jinlong, Junjie Liang, and Shoubin Dong. "iBGP: A Bipartite Graph Propagation Approach for Mobile Advertising Fraud Detection." Mobile Information Systems 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/6412521.
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Online mobile advertising plays a vital financial role in supporting free mobile apps, but detecting malicious apps publishers who generate fraudulent actions on the advertisements hosted on their apps is difficult, since fraudulent traffic often mimics behaviors of legitimate users and evolves rapidly. In this paper, we propose a novel bipartite graph-based propagation approach, iBGP, for mobile apps advertising fraud detection in large advertising system. We exploit the characteristics of mobile advertising user’s behavior and identify two persistent patterns: power law distribution and pertinence and propose an automatic initial score learning algorithm to formulate both concepts to learn the initial scores of non-seed nodes. We propose a weighted graph propagation algorithm to propagate the scores of all nodes in the user-app bipartite graphs until convergence. To extend our approach for large-scale settings, we decompose the objective function of the initial score learning model into separate one-dimensional problems and parallelize the whole approach on an Apache Spark cluster. iBGP was applied on a large synthetic dataset and a large real-world mobile advertising dataset; experiment results demonstrate that iBGP significantly outperforms other popular graph-based propagation methods.
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Wang, Elizabeth, Kathleen Abrahamson, Pi Ju Liu, and Azza Ahmed. "Can Mobile Technology Improve Weight Loss in Overweight Adults? A Systematic Review." Western Journal of Nursing Research 42, no. 9 (November 25, 2019): 747–59. http://dx.doi.org/10.1177/0193945919888224.
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The purpose of this systematic review was to identify evidence concerning the effectiveness of mobile applications and wearable devices for weight loss in overweight adults. A database search of PubMed and CINAHL yielded 12 eligible articles following the application of inclusion and exclusion criteria. Inclusion criteria consisted of studies primarily pertaining to obesity, inclusion of adult population only (18 years and older), use of experimental study designs only, use of mobile apps or wearable devices as intervention(s), and primary outcome of weight loss. Overall, the research evidence suggests that mobile apps and wearables are effective self-regulating tools for weight loss. Although study design concerns, such as lack of non-intervention comparator groups, prevent a definitive conclusion regarding the relative power of mobile apps and wearables over other self-monitoring methods, evidence indicates that mobile technology can be used as integral tools within overarching weight loss strategies recommended in the primary care setting.
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Munos, Bernard, Pamela C. Baker, Brian M. Bot, Michelle Crouthamel, Glen de Vries, Ian Ferguson, John D. Hixson, et al. "Mobile health: the power of wearables, sensors, and apps to transform clinical trials." Annals of the New York Academy of Sciences 1375, no. 1 (July 2016): 3–18. http://dx.doi.org/10.1111/nyas.13117.
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Lv, MingQi, Chao Huang, TieMing Chen, and Ting Wang. "A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification." Mobile Information Systems 2020 (February 14, 2020): 1–12. http://dx.doi.org/10.1155/2020/4521723.
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With the rapid growth of mobile Apps, it is necessary to classify the mobile Apps into predefined categories. However, there are two problems that make this task challenging. First, the name of a mobile App is usually short and ambiguous to reflect its real semantic meaning. Second, it is usually difficult to collect adequate labeled samples to train a good classifier when a customized taxonomy of mobile Apps is required. For the first problem, we leverage Web knowledge to enrich the textual information of mobile Apps. For the second problem, the mostly utilized approach is the semisupervised learning, which exploits unlabeled samples in a cotraining scheme. However, how to enhance the diversity between base learners to maximize the power of the cotraining scheme is still an open problem. Aiming at this problem, we exploit totally different machine learning paradigms (i.e., shallow learning and deep learning) to ensure a greater degree of diversity. To this end, this paper proposes Co-DSL, a collaborative deep and shallow semisupervised learning framework, for mobile App classification using only a few labeled samples and a large number of unlabeled samples. The experiment results demonstrate the effectiveness of Co-DSL, which could achieve over 85% classification accuracy by using only two labeled samples from each mobile App category.
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El hafidy, Abderrahim, Taoufik Rachad, Ali Idri, and Ahmed Zellou. "Gamified Mobile Applications for Improving Driving Behavior: A Systematic Mapping Study." Mobile Information Systems 2021 (August 14, 2021): 1–24. http://dx.doi.org/10.1155/2021/6677075.
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Many research works and official reports approve that irresponsible driving behavior on the road is the main cause of accidents. Consequently, responsible driving behavior can significantly reduce accidents’ number and severity. Therefore, in the research area as well as in the industrial area, mobile technologies are widely exploited in assisting drivers in reducing accident rates and preventing accidents. For instance, several mobile apps are provided to assist drivers in improving their driving behavior. Recently and thanks to mobile cloud computing, smartphones can benefit from the computing power of servers in the cloud for executing machine learning algorithms. Therefore, many mobile applications of driving assistance and control are based on machine learning techniques to adjust their functioning automatically to driver history, context, and profile. Additionally, gamification is a key element in the design of these mobile applications that allow drivers to develop their engagement and motivation to improve their driving behavior. To have an overview concerning existing mobile apps that improve driving behavior, we have chosen to conduct a systematic mapping study about driving behavior mobile apps that exist in the most common mobile apps repositories or that were published as research works in digital libraries. In particular, we should explore their functionalities, the kinds of collected data, the used gamification elements, and the used machine learning techniques and algorithms. We have successfully identified 220 mobile apps that help to improve driving behavior. In this work, we will extract all the data that seem to be useful for the classification and analysis of the functionalities offered by these applications.
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Flood, Derek, Rachel Harrison, Claudia Iacob, and David Duce. "Evaluating Mobile Applications." International Journal of Mobile Human Computer Interaction 4, no. 4 (October 2012): 37–65. http://dx.doi.org/10.4018/jmhci.2012100103.
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The power of mobile devices has increased dramatically in the last few years. These devices are becoming more sophisticated and allow users to accomplish a wide variety of tasks while on the move. The ease with which mobile apps can be created and distributed has resulted in a number of usability issues becoming more prevalent. This paper describes the range of usability issues encountered at all stages of the mobile app life cycle, from when users begin to search for an app to when they finally remove the app from their device. Using these results the authors developed a number of guidelines for both app developers and app platform developers that will improve the overall usability of mobile apps.
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Jadad, Hamid A., Abderezak Touzene, and Khaled Day. "Offloading as a Service Middleware for Mobile Cloud Apps." International Journal of Cloud Applications and Computing 10, no. 2 (April 2020): 36–55. http://dx.doi.org/10.4018/ijcac.2020040103.
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Recently, much research has focused on the improvement of mobile app performance and their power optimization, by offloading computation from mobile devices to public cloud computing platforms. However, the scalability of these offloading services on a large scale is still a challenge. This article describes a solution to this scalability problem by proposing a middleware that provides offloading as a service (OAS) to large-scale implementation of mobile users and apps. The proposed middleware OAS uses adaptive VM allocation and deallocation algorithms based on a CPU rate prediction model. Furthermore, it dynamically schedules the requests using a load-balancing algorithm to ensure meeting QoS requirements at a lower cost. The authors have tested the proposed algorithm by conducting multiple simulations and compared our results with state-of-the-art algorithms based on various performance metrics under multiple load conditions. The results show that OAS achieves better response time with a minimum number of VMs and reduces 50% of the cost compared to existing approaches.
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Schwartz, Christian, Tobias Hoßfeld, Frank Lehrieder, and Phuoc Tran-Gia. "Angry Apps: The Impact of Network Timer Selection on Power Consumption, Signalling Load, and Web QoE." Journal of Computer Networks and Communications 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/176217.
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The popularity of smartphones and mobile applications has experienced a considerable growth during the recent years, and this growth is expected to continue in the future. Since smartphones have only very limited energy resources, battery efficiency is one of the determining factors for a good user experience. Therefore, some smartphones tear down connectionsto the mobile network soon after a completed data transmission to reduce the power consumption of their transmission unit. However, frequent connection reestablishments caused by apps which send or receive small amounts of data often lead to a heavy signalling load within the mobile network. One of the major contributions of this paper is the investigation of the resulting tradeoff between energy consumption at the smartphone and the generated signalling traffic in the mobile network. We explain that this tradeoff can be controlled by the connection release timeout and study the impact of this parameter for a number of popular apps that cover a wide range of traffic characteristics in terms of bandwidth requirements and resulting signalling traffic. Finally, we study the impact of the timer settings on Quality of Experience (QoE) for web traffic. This is an important aspect since connection establishments not only lead to signalling traffic but also increase the load time of web pages.
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Dhiman, Neeraj, Neelika Arora, Nikita Dogra, and Anil Gupta. "Consumer adoption of smartphone fitness apps: an extended UTAUT2 perspective." Journal of Indian Business Research 12, no. 3 (November 17, 2019): 363–88. http://dx.doi.org/10.1108/jibr-05-2018-0158.
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Purpose The purpose of this paper is to examine the determinants of user adoption of smartphone fitness apps in context of an emerging economy. Design/methodology/approach The present study uses the extended unified theory of acceptance and use of technology (UTAUT2) as the base model along with two additional constructs, i.e. self-efficacy and personal innovativeness. The data collection was done through an online survey, wherein a total of 324 valid responses were obtained for the statistical analysis. All the hypothesized relationships were tested through partial least square structural equation modelling (PLS-SEM) using an open source programming language and software environment, i.e. R Software along with plspm-package. Findings Significant predictors of smartphone fitness app adoption intention include effort expectancy, social influence, perceived value, habit and personal innovativeness. Further, this study confirms significant relationship between personal innovativeness and habit, self-efficacy and effort expectancy and effort expectancy and performance expectation. This study reveals that personal innovativeness is the strongest predictor of behavioural intention. Contrary to the expectations, factors like performance expectancy, facilitating conditions and hedonic motivation did not influence behavioural intention. Practical implications This study gives significant clues to app developers that can drastically influence the adoption of fitness apps. The findings suggest that marketers should focus on users with high personal innovativeness that can further act as role models and significantly influence their social circle. Interestingly, the findings suggest that fitness apps, as compared to other apps, should not emphasize much on the hedonic value of their offerings. Originality/value This study is one of the few studies to examine the adoption of smartphone fitness apps in an emerging economy context by using extended version of UTAUT2 model. Further, this study shows how new endogenous and exogenous variables (i.e. self-efficacy and personal innovativeness) contribute to better explanatory power of the UTAUT2 framework.
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Alia, Mandra Nur, Bagong Suyanto, and Vinsensio Dugis. "Industrial relations dominance in the ride sharing transportation apps." Jurnal Studi Komunikasi (Indonesian Journal of Communications Studies) 4, no. 2 (July 1, 2020): 357. http://dx.doi.org/10.25139/jsk.v4i2.2443.
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The development of digitalisation has penetrated the transportation sector. Indonesia has become a market for ride-sharing startups which has proliferated in the past three years. This article aimed to understand the hidden interests and dominance occurring in industrial relations in the sharing economy system in Grab Indonesia, especially in GrabCar services. The formulations of the problem in this paper were: whether the cause of the conflict between Grab company and its business partners reflected the company's or business partners’ hidden interests? And then, what were the implications of the conflict on industrial relations for Grab and its partners?. This study used a qualitative approach with the Verstehen method to find the deepest and intersubjective meanings of social actions. This research applied the theory of conflict, industrial relations, and partnerships. Data sources in this study were primary sources in the form of interviews and secondary sources through newspapers, journals, books and webpages. The results showed that the cause of the conflict between Grab and its business partners revealed hidden interests of the company and some of its business partners. and also, conflicts caused imbalance and dominance of industrial relations in which the company has stronger power and authority than its business partners.
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Cruz, Luis, and Rui Abreu. "Improving Energy Efficiency Through Automatic Refactoring." Journal of Software Engineering Research and Development 7 (August 17, 2019): 2. http://dx.doi.org/10.5753/jserd.2019.17.
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The ever-growing popularity of mobile phones has brought additional challenges to the software development lifecycle. Mobile applications ought to provide the same set of features as conventional software, with limited resources: such as limited processing capabilities, storage, screen and, not less important, power source. Although energy efficiency is a valuable requirement, developers often lack knowledge of best practices. In this paper, we propose a tool to improve the energy efficiency of Android applications using automatic refactoring — Leafactor. The tool features five energy code smells that tend to go unnoticed. In addition, we study whether automatic refactoring can aid developers to ship energy efficient mobile applications with a dataset of 140 free and open source apps. As a result, we detect and fix code smells in 45 Android apps, from which 40% have successfully merged our changes into the official repository.
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Vongas, John G., and Raghid Al Hajj. "Competing Sexes, Power, and Testosterone: How Winning and Losing Affect People's Empathic Responses and What this Means for Organisations." Applied Psychology 64, no. 2 (June 12, 2014): 308–37. http://dx.doi.org/10.1111/apps.12030.
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Marceglia, S., F. Pinciroli, and S. Bonacina. "A Pictorial Schema for a Comprehensive User-oriented Identification of Medical Apps." Methods of Information in Medicine 53, no. 03 (2014): 208–24. http://dx.doi.org/10.3414/me13-01-0093.
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SummaryObjectives: The huge amount of released medical apps prevents medical app users from believing that medical scientific societies and other accreditation bodies as well, have the resources and the power for assigning to any medical app a quality score. By the time being, any medical app user has to take the risks related to the frequently insufficient accreditation of that app. Providing clear user-oriented schemas, to be adopted both when putting a medical App on the market and when an App comes to be evaluated by a cohort or single users, becomes crucial. The aim of our research was to define a pictorial identification one-shot schema for a comprehensive user-oriented identification of medical apps.Methods: Adopting a pictorial approach is common in software design modeling. To build up our identification schema we started from the limited number of Apps already available on a web site of app reviews (iMedicalApps.com), and we identified an appropriately large set of attributes for describing medical apps. We arranged the attributes in six main families. We organized them in a one-shot comprehensive pictorial schema. We adopted a traffic light color code for assessing each attribute, that was sufficient to provide simple elements of alerts and alarms regarding a single App. Then, we considered apps from iMedicalApps.com web site belonging to three medical specialties: cardiology, oncology, and pharma and analyzed them according to the proposed pictorial schema.Results: A pictorial schema having the attributes grouped in the families related to “Responsible Promoters”, “Offered Services”, “Searching Methods”, “Applications Domains”, “Envisaged Users”, and “Qualifiers and Quantifiers” has been identified. Furthermore, we produced a one-shot pictorial schema for each considered app, and for each medical specialty, we produced it also in an aggregated form.Conclusions: The one-shot pictorial schema provides a useful perception of when and where to use a considered app. It fits positively the expectations of potential but different user’s profiles. It can be a first step towards a systematic assessment of apps from the user viewpoint.
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Mitchell, Scott S. D. "“Warning! You’re entering a sick zone”." Online Information Review 43, no. 6 (October 14, 2019): 1046–62. http://dx.doi.org/10.1108/oir-03-2018-0075.
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Purpose Traditional public health methods for tracking contagious diseases are increasingly complemented with digital tools, which use data mining, analytics and crowdsourcing to predict disease outbreaks. In recent years, alongside these public health tools, commercial mobile apps such as Sickweather have also been released. Sickweather collects information from across the web, as well as self-reports from users, so that people can see who is sick in their neighborhood. The purpose of this paper is to examine the privacy and surveillance implications of digital disease tracking tools. Design/methodology/approach The author performed a content and platform analysis of two apps, Sickweather and HealthMap, by using them for three months, taking regular screenshots and keeping a detailed user journal. This analysis was guided by the walkthrough method and a cultural-historical activity theory framework, taking note of imagery and other content, but also the app functionalities, including characteristics of membership, “rules” and parameters of community mobilization and engagement, monetization and moderation. This allowed me to study HealthMap and Sickweather as modes of governance that allow for (and depend upon) certain actions and particular activity systems. Findings Draw on concepts of network power, the surveillance assemblage, and Deleuze’s control societies, as well as the data gathered from the content and platform analysis, the author argues that disease tracking apps construct disease threat as omnipresent and urgent, compelling users to submit personal information – including sensitive health data – with little oversight or regulation. Originality/value Disease tracking mobile apps are growing in popularity yet have received little attention, particularly regarding privacy concerns or the construction of disease risk.
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Hendl, Tereza, Ryoa Chung, and Verina Wild. "Pandemic Surveillance and Racialized Subpopulations: Mitigating Vulnerabilities in COVID-19 Apps." Journal of Bioethical Inquiry 17, no. 4 (August 25, 2020): 829–34. http://dx.doi.org/10.1007/s11673-020-10034-7.
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AbstractDebates about effective responses to the COVID-19 pandemic have emphasized the paramount importance of digital tracing technology in suppressing the disease. So far, discussions about the ethics of this technology have focused on privacy concerns, efficacy, and uptake. However, important issues regarding power imbalances and vulnerability also warrant attention. As demonstrated in other forms of digital surveillance, vulnerable subpopulations pay a higher price for surveillance measures. There is reason to worry that some types of COVID-19 technology might lead to the employment of disproportionate profiling, policing, and criminalization of marginalized groups. It is, thus, of crucial importance to interrogate vulnerability in COVID-19 apps and ensure that the development, implementation, and data use of this surveillance technology avoids exacerbating vulnerability and the risk of harm to surveilled subpopulations, while maintaining the benefits of data collection across the whole population. This paper outlines the major challenges and a set of values that should be taken into account when implementing disease surveillance technology in the pandemic response.
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Alazab, Moutaz. "Automated Malware Detection in Mobile App Stores Based on Robust Feature Generation." Electronics 9, no. 3 (March 5, 2020): 435. http://dx.doi.org/10.3390/electronics9030435.
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Many Internet of Things (IoT) services are currently tracked and regulated via mobile devices, making them vulnerable to privacy attacks and exploitation by various malicious applications. Current solutions are unable to keep pace with the rapid growth of malware and are limited by low detection accuracy, long discovery time, complex implementation, and high computational costs associated with the processor speed, power, and memory. Therefore, an automated intelligence technique is necessary for detecting apps containing malware and effectively predicting cyberattacks in mobile marketplaces. In this study, a system for classifying mobile marketplaces applications using real-world datasets is proposed, which analyzes the source code to identify malicious apps. A rich feature set of application programming interface (API) calls is proposed to capture the regularities in apps containing malicious content. Two feature-selection methods—Chi-Square and ANOVA—were examined in conjunction with ten supervised machine-learning algorithms. The detection accuracy of each classifier was evaluated to identify the most reliable classifier for malware detection using various feature sets. Chi-Square was found to have a higher detection accuracy as compared to ANOVA. The proposed system achieved a detection accuracy of 98.1% with a classification time of 1.22 s. Furthermore, the proposed system required a reduced number of API calls (500 instead of 9000) to be incorporated as features.
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Li, Ching, Chia-Wen Lee, Tzu-Chun Huang, and Wei-Shiang Lai. "Perspectives of Platform Operators, Content Producers, and Information Receivers toward Health and Fitness Apps." Information 11, no. 10 (October 14, 2020): 481. http://dx.doi.org/10.3390/info11100481.
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The interactive mechanism among platform operators, content producers, and information receivers is increasingly complex in human–computer symbiosis. The purpose of this study is to identify the interactive value among platform operators, content producers, and information receivers with regard to information through the health and fitness apps by adopting an advanced Analytic Hierarchy Process (AHP) method derived from professional perspectives of app users and operators, key opinion leaders, scholars, and officers. The AHP method was allocated weightings to the evaluation criteria from the twelve panelists from three groups of platform operators, content producers, and information receivers. After focus group interviews were conducted, four dimensions and twelve sub-dimensions of the initial health and fitness apps were obtained as follows: Content category: Monitoring, exercise, journaling, and sleeping; (2) User reviews: Fuctionality, interactivity, and criticism; (3) Content updates: New feature, correctness, and new language; (4) Platform terms: Privacy, accuracy, ownership, and right of use. The study integrated the panelists’ opinions toward health and fitness apps and analyzed the weight of each indicator according to their importance by Power Choice V2.5. The results revealed that the weights of dimensions of health and fitness apps were sorted by content category, user review, platform terms, and content update, as well as that the weights of the top six sub-dimensions were followed: monitoring, exercise, functionality, interactivity, privacy, and accuracy. Content producers suggested increasing the popularity of their products by adding new features, whereas information receivers preferred to correct problems. Content producers and information receivers graded platform terms as less essential, whereas platform operators rated platform terms higher. This study can contribute to assisting the health and fitness industry and the overall strategic operative process by identifying how the effectiveness in the procedures, estimative process, and cost-down can enhance competitiveness to further improve users experience and satisfaction.
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Isin, Engin, and Evelyn Ruppert. "The birth of sensory power: How a pandemic made it visible?" Big Data & Society 7, no. 2 (July 2020): 205395172096920. http://dx.doi.org/10.1177/2053951720969208.
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Much has been written about data politics in the last decade, which has generated myriad concepts such as ‘surveillance capitalism’, ‘gig economy’, ‘quantified self’, ‘algorithmic governmentality’, ‘data colonialism’, ‘data subjects’ and ‘digital citizens’. Yet, it has been difficult to plot these concepts into an historical series to discern specific continuities and discontinuities since the origins of modern power in its three major forms: sovereign, disciplinary and regulatory. This article argues that the coronavirus pandemic in 2020 brought these three forms of power into sharp relief but made particularly visible a fourth form of power that we name ‘sensory power’, which has been emerging since the 1980s. The article draws on early studies of power by Michel Foucault, subsequent studies on biopower and biopolitics that expanded on them, and studies in the past decade that focused on data produced from apps, devices and platforms. Yet, despite its ambition, the article is inevitably an outline of a much larger project.
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Hsiung, Hsin-Hua, and Wei-Chi Tsai. "The Joint Moderating Effects of Activated Negative Moods and Group Voice Climate on the Relationship between Power Distance Orientation and Employee Voice Behavior." Applied Psychology 66, no. 3 (March 7, 2017): 487–514. http://dx.doi.org/10.1111/apps.12096.
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Yang, Yanxiang, and Joerg Koenigstorfer. "Determinants of Fitness App Usage and Moderating Impacts of Education-, Motivation-, and Gamification-Related App Features on Physical Activity Intentions: Cross-sectional Survey Study." Journal of Medical Internet Research 23, no. 7 (July 13, 2021): e26063. http://dx.doi.org/10.2196/26063.
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Background Smartphone fitness apps are considered promising tools for promoting physical activity and health. However, it is unclear which user-perceived factors and app features encourage users to download apps with the intention of being physically active. Objective Building on the second version of the Unified Theory of Acceptance and Use of Technology, this study aims to examine the association of the seven determinants of the second version of the Unified Theory of Acceptance and Use of Technology with the app usage intentions of the individuals and their behavioral intentions of being physically active as well as the moderating effects of different smartphone fitness app features (ie, education, motivation, and gamification related) and individual differences (ie, age, gender, and experience) on these intentions. Methods Data from 839 US residents who reported having used at least one smartphone fitness app were collected via a web-based survey. A confirmatory factor analysis was performed, and path modeling was used to test the hypotheses and explore the influence of moderators on structural relationships. Results The determinants explain 76% of the variance in the behavioral intention to use fitness apps. Habit (β=.42; P<.001), performance expectancy (β=.36; P<.001), facilitating conditions (β=.15; P<.001), price value (β=.13; P<.001), and effort expectancy (β=.09; P=.04) were positively related to behavioral intention to use fitness apps, whereas social influence and hedonic motivation were nonsignificant predictors. Behavioral intentions to use fitness apps were positively related to intentions of being physically active (β=.12; P<.001; R2=0.02). Education-related app features moderated the association between performance expectancy and habit and app usage intentions; motivation-related features moderated the association of performance expectancy, facilitating conditions, and habit with usage intentions; and gamification-related features moderated the association between hedonic motivation and usage intentions. Age moderated the association between effort expectancy and usage intentions, and gender moderated the association between performance expectancy and habit and usage intentions. User experience was a nonsignificant moderator. Follow-up tests were used to describe the nature of significant interaction effects. Conclusions This study identifies the drivers of the use of fitness apps. Smartphone app features should be designed to increase the likelihood of app usage, and hence physical activity, by supporting users in achieving their goals and facilitating habit formation. Target group–specific preferences for education-, motivation-, and gamification-related app features, as well as age and gender differences, should be considered. Performance expectancy had a high predictive power for intended usage for male (vs female) users who appreciated motivation-related features. Thus, apps targeting these user groups should focus on goal achievement–related features (eg, goal setting and monitoring). Future research could examine the mechanisms of these moderation effects and their long-term influence on physical activity.
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Gruenwald, Hermann. "Logistics Information Systems (LIS) on the Go-Mobile Apps and Social Media." Information Management and Business Review 7, no. 4 (August 30, 2015): 64–73. http://dx.doi.org/10.22610/imbr.v7i4.1164.
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Logistics has evolved over the past few decades from transportation and warehousing to global Supply Chain Management (SCM). This requires the coordination of the flow of material, money and information. The velocity of doing business has increased and manual operations have been automated. Modern Logistic Information Systems (LIS) with all its logistics related sub systems are replacing muscle power with brain power and pencil and paper with smart phones and social media. The virtual aspect of logistics has become equally important to the physical realm of transportation and warehousing. Supply Chain Management (SCM) deals with getting the right stuff to the right people at the right time in the right amount. To accomplish this task there are a number of more or less integrated logistics software application. Demand forecasting models based on historical data from data marts and data warehouses with built in seasonality and pricing models. Load planning software to appropriately palletize, containerize and load trucks, trains and vessels. Route planning software with real time traffic and weather updates combined with Global Positioning Systems (GPS) to reduce transportation time and fuel costs. Warehouse Management Systems (WMS) to receive, put-away, store, receive and marshal the shipment. Electronic documents accompany the shipment from purchase order, letter of credit to customs clearing and back-haul charges. While these applications in the past have been mostly desktop applications used in the office at the management level, the move is to mobile applications. The footprint of LIS is getting smaller and is moving from the desktop to the Smartphone. At the core of any logistic information systems (LIS) is electronic communication. With the advent of the internet and social media personal communication has taken on other forms. With smart phones and tablets like the I-Phone and I-Pad e-commerce advanced to m-commerce. While technology enables the global supply chain, how do future logistics professionals feel about applying this cutting edge communication technology in their personal and professional lives? This quantitative study compares the aptitude of Thai logistics management students towards the use of social media and modern mobile telecommunication technology in their personal lives and in the context of professional use in connection with logistics information systems (LIS).
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Fang, Yu-Hui. "Exploring task-service fit and usefulness on branded applications continuance." Journal of Services Marketing 31, no. 6 (September 11, 2017): 574–88. http://dx.doi.org/10.1108/jsm-07-2016-0256.
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Purpose Providing that branded applications (apps) became a new trend in mobile marketing, the purpose of this study, thus, is to explore how to promote app users’ continuance intention and purchase intention (i.e. “app continuance”) toward a specific branded app. Design/methodology/approach By integrating both goods-dominant logic (GDL) and service-dominant logic (SDL), this study uses a unifying model to examine whether perceived usefulness and task-service fit (TSF) have different effects on the two parts of app continuance. This study identifies task characteristic and four service characteristics (interactivity, presence, localization and ubiquity) as antecedents of TSF. Furthermore, psychological barriers are examined as mediators of TSF and purchase intention within SDL. Data collected from 631 users of the targeted branded apps support all of the proposed hypotheses. Findings The findings show that besides perceived usefulness, TSF is an essential determinant of both app continuance in the context of branded apps and a partial mediator of psychological barriers between TSF and purchase intention. Originality/value Unlike prior studies, which have focused on traditional GDL to examine continuance intention, this study incorporates SDL and the notion of psychological barriers to explore such matters. The evidence concerning the significantly higher explanatory power of the full model suggests that a deeper understanding of the antecedents of app continuance is possible when the alternative view is taken into consideration, thus providing a promising avenue for future research.
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Holloway, Donell, Lelia Green, and Carlie Love. "‘It'S All about the APPS’: Parental Mediation of Pre-Schoolers' Digital Lives." Media International Australia 153, no. 1 (November 2014): 148–56. http://dx.doi.org/10.1177/1329878x1415300117.
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A young mother with a two-year-old and a four-year-old is asked about her experience of parenting. ‘I can't believe how much is different, ‘she says, ‘between the first child and the second. It's all about the apps.’ Elsewhere in the room, the two pre-schoolers are absorbed in collaborative play with an iPad. Across the continent, a distant relative prepares for a pre-arranged Skype session with her young niece and nephew. She wonders whether the youngest, who has never video-conferenced before, will recognise and talk to her. These children are growing up with a game changer. What had been hailed as ‘the Semantic Web’ is turning out to be something creatively different. This article uses a series of vignettes to examine the power of the app, from Playschool Playtime to Skype, to highlight, analyse and discuss young children's (aged from birth to five) digital interventions facilitated by a download and touchscreen technologies.
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Feenstra, Sanne, Jennifer Jordan, Frank Walter, Jin Yan, and Janka I. Stoker. "The Hazard of Teetering at the Top and Being Tied to the Bottom: The Interactive Relationship of Power, Stability, and Social Dominance Orientation with Work Stress." Applied Psychology 66, no. 4 (July 2, 2017): 653–73. http://dx.doi.org/10.1111/apps.12104.
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Inupakutika, D., D. Akopian, P. Chalela, and A. G. Ramirez. "Performance analysis of Mobile Cloud Computing Architectures for mHealth app." Electronic Imaging 2020, no. 3 (January 26, 2020): 335–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.3.mobmu-332.
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Mobile Health (mHealth) applications (apps) are being widely used to monitor health of patients with chronic medical conditions with the proliferation and the increasing use of smartphones. Mobile devices have limited computation power and energy supply which may lead to either delayed alarms, shorter battery life or excessive memory usage limiting their ability to execute resource-intensive functionality and inhibit proper medical monitoring. These limitations can be overcome by the integration of mobile and cloud computing (Mobile Cloud Computing (MCC)) that expands mobile devices' capabilities. With the advent of different MCC architectures such as implementation of mobile user-side tools or network-side architectures it is hence important to decide a suitable architecture for mHealth apps. We survey MCC architectures and present a comparative analysis of performance against a resource demanding representative testing scenario in a prototype mHealth app. This work will compare numerically the mobile cloud architectures for a case study mHealth app for Endocrine Hormonal Therapy (EHT) adherence. Experimental results are reported and conclusions are drawn concerning the design of the prototype mHealth app system using the MCC architectures.
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Ruli A. Siregar, Riki, Hengki Sikumbang, Iriansyah BM Sangadji, and Indrianto. "KWh Meter Smart Card Model Token For Electrical Energy Monitoring." MATEC Web of Conferences 218 (2018): 03002. http://dx.doi.org/10.1051/matecconf/201821803002.
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This research Producer Electric meter Appliance model base on smart card kWh (kilo Watt hour). The card power meter Is use to calculate the prepaid electricity meter using the 20-digit voucher number as a charging medium. Utilizing a smart card, the token number in the prepaid electricity meter can help reduce the error rate when entering the token number, the model destination is created. Hardware design and with apps to detect how much energy is used to store basic data to help view history of usage. Using smart cards and microcontrollers in apps that come from a usage history in the Pulse usage category will help users know their usage in efficient, normal, and wasteful categories. The results of this research is a meter model with credit card for charging pulses, and data processing applications as devices that can be used for various electricity consumption. The information system is used as a model validation with pulse input that provides information about the use of electrical energy and as a determinant to save the time and time required to make optimal energy
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Leslie, Mitch. "COVID-19 Fight Enlists Digital Technology: Contact Tracing Apps." Engineering 6, no. 10 (October 2020): 1064–66. http://dx.doi.org/10.1016/j.eng.2020.09.001.
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Andreeva, Magdalena. "THE CLOUD COMPUTING – AN APPLICATION OF GOOGLE APPS IN E-LEARNING." Knowledge International Journal 30, no. 6 (March 20, 2019): 1655–61. http://dx.doi.org/10.35120/kij30061655a.
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Cloud computing is the next stage in the web service evolution, providing computing power, applications, business processes etc., delivered as a service on demand. Nowadays the online service delivery progresses and gets into different areas of life. The information and communication technologies thrust permanently in the education. It is quite natural for the cloud computing to find their application.In a cloud computing system, there's a significant workload shift. Local computers have no longer to run applications. Instead of them the network of computers, which forms the cloud, handles it. Besides, the hardware and software requirements on the user's computer decrease. The only thing that the user needs to run the cloud computing service is a Web browser and an Internet connection.E-learning is popularized and enforced in many training institutions, especially in the distance and part-time learning. It is universal and can be used both in the education process and in training employees, enhancing their qualification, competence check, and more.In the paper is discussed the cloud model, which has five essential characteristics, three service models and four deployment models.Google Apps is popular public Software as a Service (SaaS) cloud service model, which provides software applications developed by Google. The Google Apps package includes communication tools – Gmail, Calendar, Hangout and Google+, personal disk space, which can be shared – Drive, applications for collaborative work – Docs, Sheets, Slides, Forms and Sites. All applications are costless after free registration and login to the platform. The Google Apps can be used to develop shared Web-based learning materials. The main advantage is that they are free, accessible at any time, from anywhere and any device. Another feature is that they do not have specific hardware and software requirements. A device with an Internet connection and a browser is enough.A detailed overview of Google Apps tools is made in the article and their application in the e-learning is proposed. In conclusion of the study is summarized that the Google Apps package can be: 1) used to prepare and share learning materials; 2) used to create knowledge tests, quizzes and receive any feedback information; 3) used for collaborative work with the tools; 4) used to manage and share events calendar, timetables, to-do-lists and more; 5) used for practical exercises to work with office tools. All this is free and publicly accessible at any time, from any device.