IFringe: a fringe analysis application for mobile smart devices

Introduction: The introduction of Clinical Information Systems (CIS) to manage and store patient information has deeply modified the workflow of caregivers. As the information is no longer stored on a physical medium, caregivers depend on the presence of a computer to access patient data. This constraint has built up an invisible barrier between the source of information and the place of its use. The popularisation of mobile devices offers an oportunity to break this barrier by providing a ubiquitous access to information. The use of a mobile platform merges the advantages of a modern CIS and the mobility offered by paper. We have developed an application on a mobile device that nurses can carry along on all their visits. It allows the information gathered during their visits to be entered directly into the system. Method: The tool we present aims to manage the daily interventions of nurses. The interventions concern all kinds of treatments provided by nurses to patients. In the current organisation, nurses start their day by printing out all the daily interventions and use it as a procedure to follow. Every time a nurse performs an intervention, she takes a note indicating that the task has been done properly. When they have some spare time, nurses enter all the gathered information in the CIS. Once nurses are equipped with mobile devices, paper becomes useless. Consequently, the process is simplified. Replacing the paper by a mobile device application is not straightforward. In order to access patient information, the tool must be linked to the existing CIS of the hospital without creating too strong dependencies. Moreover, the mobile interface must be adapted to the specificities of the mobile device such as a smaller display size, a reduced computational power, a tactile-based interaction and a real-time usage. Results: In order to link the mobile application to the existing CIS, we relied on a Service Oriented Architecture (SOA). It was mandatory to think of a software architecture that would not create a dependency with any legacy system. Thus, we defined a gateway server providing centralised access for the mobile application to any required information to or from the CIS. Integrating any mobile application would only require integrating this bridge. The gateway server also clearly separates the services that are available remotely from the ones proposed as usual Web services. The developed application not only allows the validation of the interventions and the input of measures, but it also offers a simple way to define the context in which nurses are working. This context is necessary to identify the specific list of interventions for the patients under the caregiver’s responsibility. The current CIS of the HUG includes a module that provides information concerning the interventions. Its interface is adjusted for a personal computer screen. Since caregivers are accustomed to this organisation of the information, we aimed to develop an interface on a mobile device that guarantees a certain level of homogeneity with the existing PC application. However, a mobile device’s screen is of limited size, therefore the interface has been completely rebuilt to be adapted to the new display. To deal with the limited display size, we rely on hierarchy and indexicality principles. For instance, based on the hypothesis that all tasks belonging to one category and planned at the same time can be regrouped under a single item; we regroup the interventions of similar top level in a common item. Moreover, to minimise user manipulations, relevant items are automatically moved to the top. Conclusion: The current daily workflow of nurses cannot be managed consistently using a unique tool. The need to switch from paper to computer induces work overload and is a source of errors. Therefore, we have developed a program running on a mobile device that nurses can carry during their visits. This program allows to manage nurses' daily interventions in real-time. The development of such a tool has required a complete reconstruction of the classical personal computer interface. This new interface takes into account a smaller display size, an innovative interaction paradigm, and real-time constraints.

There has been an explosion of smart mobile devices over the last few years. These smart devices, such as smartphones and tablets, have changed many aspects of modern life. They have also enabled whole new industries to grow up that develop and manufacture of the smart devices. These companion products, however, are mostly built around the smart devices, instead of being tightly integrated into them, and fail to utilize the full capabilities of the smart devices. The main cause for their failure is that the software platforms these smart devices are built on are not open. This hinders efforts by device manufacturers or software developers to create innovative new products or product categories based on those software platforms.In this talk, we present Tizen (www.tizen.org), which is a fully open software platform for embedded systems. Tizen allows for everyone involved in building and using devices built on it to freely define, invent, add new features or business models, or create new device categories. Tizen offers an industry leading HTML5-based application APIs, the preferred development environment for apps and services for the future. The HTML5-based APIs make it easy for developers to create applications that run across various categories of devices such as mobile, in-vehicle infotainment (IVI), Digital TV, netbooks, health and medical devices, etc. In this talk we also present Tizen's optimization technologies that enable HTML5-based applications to enjoy performance comparable to that of native applications. We also describe how Tizen balances the trade-offs between performance and power consumption, which is of extreme importance for mobile devices.

This research study is an attempt to investigate and recommend the applications and usefulness of social media as a knowledge sharing platform using smart mobile devices and students’ academic performances. Research literature reveals that further examination of this idea is a must as it is increasingly becoming an integral part and a current mandate for digital-era learners. This study is exploratory based on learners’ data which includes students from foundation, junior and senior courses at a university. The objective was to cognize learners’ perceptions on collaborative learning while using applications of social media knowledge platform and smart mobile devices. Structural Model approach is followed to validate the data and undertake the required analysis. The resulting analysis shows that a significantly positive relation exists between the available platforms of knowledge applications using smart devices and its substantial impact on students’ overall performances. In addition, it could be observed that generally students have positive and valuable perception on the use of social media knowledge platform and smart mobile devices in collaborative learning settings. Moreover, such settings encourage students-students’ interactions, studentsteachers’ interactions, and the growing trends of students to online experts’ interactions. Furthermore, it was noticed that these interactions improve students’ engagement with such platforms using smart devices, which consequently has significant positive impact on students’ academic performances. The findings propose the inculcation in students the positive role of the use of social media knowledge platforms using smart devices so to encourage collaborative learning, to enhance active learning, to be more dynamic & engaging, to broaden their domain-knowledge, and to promote academic researchoriented learning, which are all crucial for graduate employability.

Falls are a major health concern leading cause of fatal and non-fatal injuries for neurological disorders. Balance dysfunction is one of the common factors to determine fall risk in neurological patients. Preventative measures may help to reduce the incidence and severity of falls for detecting balance function and fall risk factors. However, the objective measures for balance require expensive equipment with the assessment of clinical expertise. A main gap remains in the evaluation method to objectively characterize the balance functions in individuals with high risk of falling. With the development of wearable and mobile devices, recent advances in smart mobile devices may provide a potential opportunity to manage the gap in the detailed quantification of balance impairments. The purpose of this study is to identify whether the biomechanical data measured by the mobile device is reliable to characterize the posture stability in various balance test conditions. A total of 39 children with Down syndrome completed four balance-testing tasks under altered base of support and vision. Simultaneous biomechanical measurements were gathered from the iPod and force plate analysis system during functional balance testing. The force plate and mobile system provided similar patterns of stability across groups. Correlation ([Formula: see text] between two systems for path length, 95% ellipse area, peak-to-peak, standard deviation and mean ranged from 0.60 to 0.99. We expect that the smart mobile device can provide reliable and accurate information to quantify the postural stability in individuals with elderly people or neurological disorders. The objectivity, portability and easy use of such mobile device make it ideal to apply in clinical environments for detecting balance functions and reducing the risk of falls in Down syndrome or other neurological patients.

Mobile and handheld devices are becoming an integral part of people’s work, life and entertainment. These lightweight pocket-sized devices offer great mobility, acceptable computation power and friendly user interfaces. As people are making business transactions and managing their online bank accounts via handheld devices, they are concerned with the security level that mobile devices and systems provide. In this chapter we will discuss whether these devices, equipped with very limited computation power compared to full-sized computers, can make equivalent security services available to users. We focus on the security designs and technologies of hardware, operating systems and applications for mobile and handheld devices.

Machine learning methods such as Adaptive Network-Based Fuzzy Inference System (ANFIS) have been widely employed in intelligent urban storm water disaster warning for the purpose of smart city. However, there exists lack of research proposed for applying ANFIS and mobile application (App) to reach the purpose of smart city. In order to accomplish the goal, the study integrates ANFIS and Qt Framework to develop a Typhoon Rainfall Forecasting System to real-time typhoon rainfall forecast via a mobile device. The Service is first built by applying cluster analysis to typhoon data (Tamsui Weather Station of Taiwan) during June 1967 and November 2020 to classify the data into four groups and then applying the ANFIS to construct the Service with data in each group. The fuzzy rule of ANFIS is established by grid partition method. Both the Service and App employ Qt Framework as the cross-operating development tool, and the App is transformed to a smart mobile device App of different platforms. The simulated results show the following: (1) Taking the example of typhoon Nakri in group 1, the lowest root mean square error (7.898 mm) and the lowest computation time (178 sec) were obtained for training with 1000 steps and three membership functions. (2) Using the optimal parameters of the typhoon belonging to that group can obtain better prediction results. The developed typhoon rainfall forecasting system App in the supplementary information demonstrates that the user can use the smart mobile device for real-time typhoon forecasting at the most three hours ahead easily.

The fast growing popularity of smartphones and tablets enables us the use of various intelligent mobile applications. As many of those applications require position information, a smart mobile device provides positioning methods such as GPS, WiFi, or Cell-ID based positioning services. However, those positioning methods have different characteristics of energy efficiency, accuracy, and service availability. In this paper, we present an Energy- Efficient Cooperative and Opportunistic Positioning System (ECOPS) for heterogeneous mobile devices. ECOPS facilitates mobile devices with estimated locations using WiFi in cooperation with a few available GPS broadcasting devices, in order to achieve high energy efficiency and accuracy within available budget constraints. ECOPS estimates the location using heterogeneous positioning services and the combination methods including a received signal strength indicator, 2D trilateration, and available power measurement of mobile devices. The evaluation shows that ECOPS significantly reduces energy consumption and achieves the good accuracy of a location.

Mobile Cloud Computing (MCC) is getting growing interest due to its wide applicability in variety of social, industrial, and commercial mobile applications. Mobile and smart devices can share complex computational operations with Cloud Service Providers (CSPs). It also provides storage, access polices enforcement, and security operations. In many cases, CSP requires services from crowd contributors CC s for data collection, sharing, and mobile application support. It requires trust management for CC s to guard against malicious CC s and ensure security and privacy of data. However, end users or data requesters also demand reliable security solutions for sharing their data or accessing data from unknown CC s. To ensure strong security, mobile devices are not computationally feasible to perform complex cryptographic operations for desired privacy. To resolve these issues, we propose Reputation-aware Trust and Privacy Preservation scheme for MCC. In first phase, we deal with the trust management by utilizing reputation aware selection of CC s and leverage cloud services where CSP maintains trust score for CC s and data requesters. In second phase, we manage privacy preservation by using our proposed Anonymous Secure-shell Ciphertext-policy Attribute Based Encryption (AS-CABE). We have also proposed a hybrid policy tree mechanism for dynamic attribute selection used for security solutions and key management. Next, an anonymous secure shell is maintained between the CC s and the crowd servers to ensure registration after approval from trusted authority. In the similar vein, we propose outsourced encryption and decryption mechanism for mobiles that further utilize encryption and decryption service providers for complex operations. To the best of our knowledge, we are the first one to deal with the trust issues of data requester and privacy concerns of CC s and users both at the same time. After that, we have presented the security analysis to analyze AS-CABE against security attacks. Finally, the results are presented that ensure the supremacy of our proposed scheme as compared to counterparts in terms of reputation score, storage, computation, trust, resilience, encryption, and decryption time.

Smart mobile devices have become an essential part of our lives, both professionally and privately. As we expand our digital presence and usage of these devices, we also increase the amount of evidence left behind. Locard's principle states that every contact leaves a trace, a principle applicable not only to traditional crime but also the cyber realm. This project addresses an area in which this principle is applied, in terms of wireless networks and their access points that have been identified through the wireless scanning process. Both access points and smart devices use different, yet similar, network frames to advertise their existence before a connection can be established between two devices. These frames contain the data that this project aims to locate, MAC addresses, which are uniquely identifiable data, that can be used to identify any device that holds a wireless interface. By analysing the mobile device of a user after a short, city centre walk, the MAC addresses of nearby wireless access points were identified and used to retrace the route travelled by the user. However, as the information was only found in volatile memory, there was a limited timeframe to capture this data.

The widespread adoption of social network applications and smart mobile devices has yielded a massive amount of data transmitted through the networks. Fortunately, social network service providers offer a wide range of storage capacity and data management functionality. Accordingly, the data can be uploaded to the social servers for processing and then accessible elsewhere. Nevertheless, considering the untrusted nature of the social servers, it becomes crucial to protect the data before uploading it to the server. Unfortunately, encryption incurs another severe problem in providing search functionality on encrypted data stored on the server. In addition, most of the existing solutions are inefficient to deploy on mobile devices due to the limited resources and computing capabilities. To address this issue, we propose an authorized equality test on identity‐based cryptosystem (AET‐IBC) scheme in this article. The scheme allows the server to test if two different ciphertexts encapsulate the same message. Besides, it supports different authorization methods to enhance the privacy. Furthermore, based on the random oracle model, we prove the security of the proposed scheme to be equivalent to the modified bilinear Diffie‐Hellman intractable assumption. Finally, the efficiency analysis shows that the AET‐IBC scheme is practicable and convenient for mobile social networking applications.

In recent years, smart mobile devices have come to be widely used in our life spaces. This development has the potential to create major changes in the ways people communicate in public spaces. This paper presents two studies on a user’s personal space while using a device in public: the first investigated mobile device use between three people; the second examined communicating private information on large, interactive displays in public spaces. Then, we introduced the basic concept for our future research on personal space while using mobile devices in public.

Smart mobile devices coupled with the Internet of Things (IoT) and Artificial Intelligence (AI) have emerged as a key enabler of modern digital health applications. While cloud computing is now a well established paradigm for analysing IoT captured data in mobile health applications, on-board analysis of data using AI approaches such as Deep Learning (DL) is gaining significant momentum. This is driven primarily by advances in on-board resources enabling modern mobile devices to execute complex DL models, while also offering improved response time and accuracy for rapid decision-making, and enhanced user privacy. While the number of mobile digital health applications that use IoT and DL is increasing, progress is currently impeded by a lack of framework for profiling and evaluating the performance of DL models on mobile devices. To this end, we propose MobDL, a framework for profiling and evaluating DL models running on smart mobile devices. We present the architecture of this framework and devise a novel evaluation methodology for conducting quantitative comparisons of various DL models running on mobile devices. Three diverse digital health applications using heterogeneous data (e.g. image, time series) are introduced. We conduct extensive experimental evaluations using several DL models that have been developed using the data sets obtained for the three digital health applications to validate the effectiveness of the proposed MobDL framework.

It is our great pleasure to welcome you to the 2010 ACM Multimedia Workshop on Mobile Cloud Media Computing -- MCMC'10. The mission of this workshop is to timely address the challenges and opportunities in applying advanced multimedia technology, cloud computing, pattern recognition, signal processing, user interface, and graphics techniques to mobile systems, given the proliferating market of mobile and portable devices that have been widely spreading in both consumer (e.g. smart phones, music/video player, mobile TV, and digital cameras) and enterprise markets (e.g. medical, control, surveillance, etc.). MCMC brings together relevant researchers to explore intelligent multimedia technologies and applications for mobile devices, especially to leverage the emerging media cloud computing platform. The call for papers attracted 20 submissions from Asia, Europe, and the United States. Among them there are 4 invited papers. The program committee accepted 8 papers from general submission. Together with the 4 invited papers, this workshop covers a variety of topics, including mobile experience computing, mobile networking and content delivery, multimedia computing on mobile devices, and some other interesting mobile multimedia applications. The highlight of the technical program is the keynote speech by Prof. Ramesh Jain on Crawling Is Difficult in Clouds. We hope that the proceedings based on the technical program will serve as a valuable reference for mobile media and cloud media researchers and developers.

Nowadays, mobile devices, such as smartphones, tablets or smartwatches, are essential items in our daily life. Further, more and more people use smart mobile devices in their everyday work for remote controlling, observing diagrams, performing web analytics, etc. However, the full potential of mobile devices is not tapped yet; built-in sensors such as accelerometers or gyroscopes offer a wide range of interaction capabilities, which are still often not fully used in nowadays mobile applications. On the other hand, desktops are still the dominating working device, but with significantly differing interaction means. With additional hand tracking devices capturing the user's gestures additional input possibilities are available but still often unused. In this paper, we investigate on a concept for orientation-based touch-less interaction. Depending on the type of device - traditional desktop or a mobile device - we use an interaction metaphor called "Waggle"; utilizing of tilting and turning of either the user's hand or the mobile device itself for additional input possibilities. Based on the results of two pilot studies for both environments, basic parameters for future design decisions are derived: on the one hand, the maximum angle for basic rotation axes are evaluated. On the other hand, different discretizations of tilt and turn angles are investigated. Based on the outcome of both studies the optimal configuration for the use of the Waggle interaction metaphor in future applications on both mobile and desktop environments are defined.

As mobile devices and applications continue to grow in popularity worldwide, so do the rise of cybersecurity attacks and threats to daily users of both Android and iOS devices on a widespread basis. These attacks not only target mobile devices at the application level but also at the Operating System (OS) device level and Application Programming Interface (API) level extending the Internet of Things (IoT). This paper will address the security vulnerabilities in Android Operating System at the intersection of APIs, device OS, and application-level vulnerabilities by identifying an intersection of commonalities to create mitigation strategies and best practices for securing mobile devices for organizations. The study recommends the adoption of processes of authentication on mobile devices and web-based log-ins as well as access control mechanisms that can mitigate the overlapping security challenges of APIs, mobile devices OS and applications using optimal resources to enhance security. This was achieved by analyzing the threats and vulnerabilities of API.KeywordsAPIsSecurity vulnerabilitiesMobile OSAndroidiOS