Perceived Vibration Strength in Mobile Devices: The Effect of Weight and Frequency.

In the United States, a nationwide Commercial Mobile Alert Service (CMAS) is being planned to alert cellular mobile device subscribers to emergencies occurring near the location of the mobile device. The plan specifies a unique audio attention signal as well as a unique vibration attention signal (for mobile devices set to vibrate) to identify that the incoming message pertains to an emergency. Ratings of vibration signals of varying lengths and patterns were obtained from 44 deaf users of mobile devices for the perceived effectiveness of the signal in getting their attention in an emergency situation. Longer signals received higher ratings than shorter ones, and three signals with temporal on-off patterns were rated significantly better than a constant vibration. The U.S. government's recommended vibration signal for the CMAS, an important feature for access to emergency alerts by deaf persons, is supported by the results of the study.

The value of a mobile communication device is its ability to organize and access important information quickly. Mobile devices are often associated with the cutting-edge technology of the last 4 years. Although having gained an increasing popularity over recent years, mobile devices have a history of 15 years. The first generation of mobile devices was the analog mobile phone. They were large and cumbersome, resembling a small briefcase. With the launch of the second generation, mobile phone units became smaller and easier to handle. Currently, third-generation phones are starting to be released, advancing in design and dynamic capabilities. By the year 2005, 76% of consumers will own an Internet compatible device, 66% will own a cell phone, 45% will own an Internet cell phone, and 10% will own a personal digitial assistant (Forrester, 2001). In today's information surge, business never stops. IDC Research has forecasted that an average of more than 36 billion person-to-person e-mails will be sent daily by 2005 (Juptner, 2001). Hence, mobile communication plays a major role in the success of most of today's business operations (Jones, 2001), and all businesses are continually faced with the challenge of engaging with the rapidly changing information technology age. One area of mobile communications that has been growing exponentially is mobile computing. Keywords: code division multiple access (CDMA); general packet radio service (GPRS); global positioning system (GPS); Internet cell phone; mobile communication device; personal digital assistant (PDA)

With increasing private and sensitive data stored in mobile devices, secure and effective mobile-based user authentication schemes are desired. As the most natural way to contact with mobile devices, finger touches have shown potentials for user authentication. Most existing approaches utilize finger touches as behavioral biometrics for identifying individuals, which are vulnerable to spoofer attacks. To resist attacks for on-touch user authentication on mobile devices, this paper exploits physical characters of touching fingers by investigating active vibration signal transmission through fingers, and we find that physical characters of touching fingers present unique patterns on active vibration signals for different individuals. Based on the observation, we propose a behavior-irrelevant on-touch user authentication system, TouchPass, which leverages active vibration signals on smartphones to extract only physical characters of touching fingers for user identification. TouchPass first extracts features that mix physical characters of touching fingers and behavior biometrics of touching behaviors from vibration signals generated and received by smartphones. Then, we design a Siamese network-based architecture with a specific training sample selection strategy to reconstruct the extracted signal features to behavior-irrelevant features and further build a behavior-irrelevant on-touch user authentication scheme leveraging knowledge distillation. Our extensive experiments validate that TouchPass can accurately authenticate users and defend various attacks.

The value of a mobile communication device is its ability to organize and access important information quickly. Mobile devices are often associated with the cutting‐edge technology of the last 4 years. Although having gained an increasing popularity over recent years, mobile devices have a history of 15 years. The first generation of mobile devices was the analog mobile phone. They were large and cumbersome, resembling a small briefcase. With the launch of the second generation, mobile phone units became smaller and easier to handle. Currently, third‐generation phones are starting to be released, advancing in design and dynamic capabilities. By the year 2005, 76% of consumers will own an Internet compatible device, 66% will own a cell phone, 45% will own an Internet cell phone, and 10% will own a personal digitial assistant (Forrester, ). In today's information surge, business never stops. IDC Research has forecasted that an average of more than 36 billion person‐to‐person e‐mails will be sent daily by 2005 (Juptner, ). Hence, mobile communication plays a major role in the success of most of today's business operations (Jones, ), and all businesses are continually faced with the challenge of engaging with the rapidly changing information technology age. One area of mobile communications that has been growing exponentially is mobile computing.

Recently, smart phones such as the Galaxy S and IPhone, and tablet PCs such as the Galaxy Tab have been introduced and become widespread in the market, thus the environment for wireless Internet services has been improving. As the market has improved, consumer preferences for mobile devices and the relationship between these devices and wireless Internet services regarding consumer preferences have become a very important issue. However, although there have been a considerable number of studies on the demand for mobile devices, it is not easy to find previous studies on the relationship between consumer preferences for specific attributes of wireless Internet services and the demand for mobile devices. The main purpose of this study is to analyze which mobile device is more likely to be preferred or become the main channel for wireless Internet services and how the demand for each mobile device is influenced by consumer preferences for specific attributes of wireless broadband Internet services used on it, and to induce managerial implications based on the main findings. To derive the results on consumer preferences, conjoint analysis is used. The survey was conducted using 1,000 Korean consumers. In the survey, respondents are allowed to choose more than one hypothetical alternative representing a mobile device combined with a certain type of wireless broadband Internet service if they desired. To estimate the consumer preferences quantitatively, a multivariate probit model is used. According to the estimation results, owing to their portability, smart phones are more likely to become a major channel for wireless Internet services despite their drawbacks in terms of display size and performance. Portability is the most important factor affecting the choice of a mobile device when using wireless Internet services. Therefore, manufacturers of mobile devices for wireless Internet services should improve the overall functionality and performances of mobile devices without negatively affecting portability. However, at the same time, consumer preferences for specific attributes of wireless Internet services are found to affect the demand of each mobile device much differently. Therefore, the prediction that smart phones will be the prevalent mobile device for use of wireless Internet services can be somewhat changed, depending on which and how wireless Internet services are provided to each mobile device and how they affect the demand for each mobile device. As mentioned above, there are significant differences between mobile devices with regard to the effects of mobility, data transfer speed, type of contents or Internet interface for wireless Internet services. It is found that the mobility of wireless Internet service is highly valued for smaller devices, but not much for notebook PCs. In contrast, data transfer speed and similarities in the type of contents or Internet interface to those provided by fixed broadband Internet services become more important for larger mobile devices. Thus, it is necessary for wireless Internet service providers to differentiate and optimize their contents and Internet interfaces properly for various mobile devices. Additionally, it is reasonable that manufacturers of smart phones focus on mobility and portability (or convenience) rather than adding sophisticated functions or pursuing higher-level specifications. Further, for smart phones, for which mobility and convenience are important, wireless Internet service providers should develop and provide easy and convenient programs, rather than advanced programs that require high device performance. Lastly, with respect to individual demographics, young and highly educated people are more likely to be consumers of newly introduced mobile devices for using wireless Internet services. Therefore, these young and highly educated consumers should be considered a major target for manufacturers of mobile devices for wireless Internet services.

In cases of nuclear disasters it is desirable to know one's personal exposure to radioactivity and the related health risk. Usually, Geiger-Mueller tubes are used to assess the situation. Equipping everyone with such a device in a short period of time is very expensive. We propose a method to detect ionizing radiation using the integrated camera of a mobile consumer device, e.g., a cell phone. In emergency cases, millions of existing mobile devices could then be used to monitor the exposure of its owners. In combination with internet access and GPS, measured data can be collected by a central server to get an overview of the situation. During a measurement, the CMOS sensor of a mobile device is shielded from surrounding light by an attachment in front of the lens or an internal shutter. The high-energy radiation produces free electrons on the sensor chip resulting in an image signal. By image analysis by means of the mobile device, signal components due to incident ionizing radiation are separated from the sensor noise. With radioactive sources present significant increases in detected pixels can be seen. Furthermore, the cell phone application can make a preliminary estimate on the collected dose of an individual and the associated health risks.

In this article, we are going to illustrate the GNSS raw measurement on the latest MediaTek platform in 2017 with Android-N or the later version of Android releases. With the opening of the raw measurement in the location framework of Android-N in 2016, the GNSS raw measurement and navigation message are much easier to be obtained on the mobile devices. The new interfaces on mobile device provide the possibility to develop some advanced applications on single device or between multiple devices. The kinds of application almost could not be done on the mobile devices in the past. The raw measurement also could be used for improving positioning accuracy with combining the cloud based services or small cluster of devices. Sub-meter level accuracy on mobile devices is also becoming possible. Since 2016, Google announced the first version of GNSS raw measurements API along with the ‘N’ release (Android-N). This allows the end users of Android-platform and APP developers finally have the opportunity to directly access the un-processed/un-filtered GNSS raw measurement. This information was used to be obtained in single-chip GNSS solution or geodetic purpose receiver. With the new API of GNSS raw measurement, the traditional tricks on signal-chip solution become possible on the mobile phone as well. The further applications and integration in the application level is also expected through combining the raw measurement with multiple sensor sources on mobile devices. With the MediaTek new designed chipset, the GNSS raw measurements from four GNSS constellations can be provided simultaneously, including GPS, GLONASS, BeiDou and Galileo. The more GNSS constellations mean more satellite visibility. In point of raw measurement, the device will have more chance to get the well-locked raw measurement, including code-phase and carrier-phase. The most straightforward possible improvement is on speeding up the convergence of RTK (Real-Time-Kinematic) application with more well-locked raw measurements from different constellations. The sub-meter level positioning accuracy is also becoming possible on mobile devices with the proper aiding information or algorithm. As a mobile chipset vendor, the raw measurement API is not only for the positioning or application purpose. Furthermore, it provides a unified interface to collect data for examining the quality of hardware design on mobile devices. Especially, there are multiple radio devices coexisting with GNSS RF devices. Any improper hardware design might harm the measurement quality of GNSS signal. Before Android-N, the manufactory of mobile devices only can qualify the GNSS performance for the final positioning result in cheap way. After Android-N, this new API provides a new way to allow the manufactory has the chance to aware the hardware design quality in really early stage and have the chance to improve it if necessary. We are going to share what kind of benefits can be obtained. In summary, we will illustrate some of possible applications by using the new API on single mobile or between multiple devices on the MediaTek latest platform. The corresponding concepts and results will be shared. The possible ways to validate the design of hardware will also be discussed.

In an ideal world, blind people could navigate any new route without training, travel by underground/metro during rush hour without problems, and explore with confidence. Environments can be diverse and dynamic and unfortunately no universal gadget-aid solution yet exists to help navigation. Advances in mobile phone technology and entertainment devices such as the Kinect are allowing for new application scenarios to arise. In this paper, a system that could help interface a person to a wide range of environments is presented. The Path Force Feedback Belt system takes at a fixed rate dual images of the environment using a mobile device, it reconstructs a 3D model of the surroundings, and extracts features such as sidewalk corners, walls, and obstacles. The mobile device then determines which of the force feedback actuators on a 360° belt worn on the waist has to be signaled, hence providing path feedback.

With the rapid advancement of wireless communication technologies, mobile devices become very useful ubiquitous terminals. Typical devices are mobile phones with web browsing facilities, but there are many types of computing abilities. A low-end mobile phone has less ability than a smart phone with a complete operating system providing a platform for application developers. In general, there are typical shortcomings for mobile phone devices such as narrow bandwidth and the small-sized display. Therefore, document summarisation on mobile phones is one of the most convenient applications. This paper proposes compact and fast approaches that can summarise documents on mobile devices efficiently. The proposed method improves unsupervised schemes using the original non-negative matrix factorisation (NMF) that can determine the paragraph precedence without morphological and syntax analyses. In order to speed up the summarisation, the proposed technique is applied to the NMF method. From simulation results for test data of DUC2006, it turns out that the matrix size could be reduced by about 95% and the precision of summarisation speeding becomes 8.5 times faster than the original method without degrading the precision of extracted paragraphs.

We discuss an interconnectivity framework for data and content delivery to mobile devices that allows data of higher priority to reach the mobile unit in the shortest time possible. Two possible scenarios are presented; one that connects the servers in an N-cube configuration network, and another that shows the same N servers connected in a grid type network. The goal is to minimize the rate of data jumps from server to server until it reaches the mobile device. As the mobile user travels, the mobile device registers itself with the next server and the session is migrated from the old server to the new one without interruptions, in an analogous way, cell phones move from one cell to another. Starting with the idea that all data is not equal (in importance/priority), this article suggest a framework topology for intelligent mobile computing that guarantees data will reach the mobile device in a minimum amount of time, assuring at the same time the privacy of transmission. The integration of this type of technology into the 3r d Generation (3G), and 4t h Generation (4G) mobile computing is also discussed. Pervasive computing is rapidly emerging as the next generation of computing with the underlying premise of simplicity (of use), minimal technical expertise, reliability, and intuitive interactions. As technology continues to advance and mobile devices become more and more omnipresent, the aim towards achieving easier computing, more availability and prevalence is becoming a given. Through the clever use of advanced technologies, the new generation of intelligent mobile computing has the opportunity to serve user needs via prevalent computing devices that are ever more transportable and connected to an increasingly ubiquitous network structure. Mobile communication is changing as the trends of media convergence including the Internet and its related electronic communication technologies and satellite communications collide into one. A change is being ushered by the 3G (3r d Generation) mobile technology with the usability and usefulness of information delivered to mobile devices taking on added features. For example, multimedia messaging, as opposed to voice transmissions, being delivered to cell phones has rendered such mobile devices an integral part of people’s lives and a core part of how they conduct their daily business rather than an add on tool (Buckingham, 2001). The 3G mobile phone system aims at unifying the disparate standards of current second generation wireless systems. The idea is to eliminate the different types of global networks being adopted with a single standard network. This will allow for the delivery of multimedia content and propagation through the network without the need for conversion from one standard to another. 3G systems need smaller cells thus the need for more base stations (mostly due to their operating frequency, power requirements, and modulation) and in many cases will not be feasible to install them in areas where population is not so dense (i.e., rural areas) (Garber, 2002). Because of these requirements and conditions, a better way to deliver the communication must be established. However, global access to such mobile devices will create data delivery challenges and servers can become clogged with unwanted communication, like that of wired Internet access. The need for moving relevant data to mobile devices in the shortest time possible becomes of utmost importance.

Employees are constantly engaging in new technologies that allow them to be more productive. The increased ubiquity of information and communication technologies, in particular the use of mobile devices, has coincidentally increased the amount of time employees spend on work-related tasks each week. This paper attempts to better understand if individuals who are required to use mobile devices and those who voluntarily use them will have differing perceptions on mobile device use, usefulness (of the mobile device), work overload, flexibility in work structure, and work-life conflict. Secondary data from a previous study, surveying 185 working individuals of various demographics, was analyzed. The results suggest many differences in perceptions between the two groups. The findings have practical importance as managers and firms consider providing mobile devices to employees or allowing them to connect their own devices to work related systems.

Mobile banking, sometimes referred to as M-Banking, Mbanking or SMS Banking, is a term used for performing balance checks, account transactions, payments, credit applications and other banking transactions through a mobile device such as a mobile phone or Personal Digital Assistant (PDA). Mobile banking has until recently most often been performed via SMS or the Mobile Web. Apple's initial success with iPhone and the rapid growth of phones based on Google's Android (operating system) have led to increasing use of special client programs, called apps, downloaded to the mobile device hence increasing the number of banking applications that can be made available on mobile phones . This in turn has increased the popularity of mobile device use in regards to personal banking activities. Due to the characteristics of wireless medium, limited protection of the nodes, nature of connectivity and lack of centralized managing point, wireless networks tend to be highly vulnerable and more often than not they become subjects of attack. This paper proposes to identify potential threats associated with communication between a mobile device and the back end server in mobile banking applications. The paper should be able to identify the techniques associated with Man in the middle attacks during communication between a mobile device and a back end server and propose controls that will ensure that data theft does not occur during such sessions.

BackgroundMobile electronic devices, such as mobile phones and PDAs, have emerged as potentially useful tools in the facilitation and maintenance of weight loss. While RCTs have demonstrated a positive impact of mobile interventions, the extent to which mobile electronic devices are more effective than usual care methods is still being debated.ResultsElectronic databases were systematically searched for RCTs evaluating the effectiveness of mobile electronic device interventions among overweight and obese adults. Weighted mean difference for change in body weight was the primary outcome. The search strategy yielded 559 citations and of the 108 potentially relevant studies, six met the criteria. A total of 632 participants were included in the six studies reporting a mean change in body weight. Using a random-effects model, the WMD for the effect of using mobile electronic devices on reduction in body weight was −1.09 kg (95% CI −2.12, −0.05). When stratified by the type of mobile electronic device used, it suggests that interventions using mobile phones were effective at achieving weight loss, WMD = −1.78 kg (95% CI −2.92, −0.63).ConclusionsThis systematic review and meta-analysis suggests that mobile electronic devices have the potential to facilitate weight loss in overweight and obese populations, but further work is needed to understand if these interventions have sustained benefit and how we can make these mHealth tools most effective on a large scale. As the field of healthcare increasingly utilizes novel mobile technologies, the focus must not be on any one specific device but on the best possible use of these tools to measure and understand behavior. As mobile electronic devices continue to increase in popularity and the associated technology continues to advance, the potential for the use of mobile devices in global healthcare is enormous. More RCTs with larger sample sizes need to be conducted to look at the cost-effectiveness, technical and financial feasibility of adapting such mHealth interventions in a real clinical setting.

As the most immediately impacted population, survivors’ mobility and distribution characteristics are closely linked to earthquake emergency response. Accurate population distribution and mobility data are vital foundational resources for post-disaster decision-making. With the help of mobile phone location data within the earthquake-stricken area, we explore novel rapid assessment approaches to identifying perceived impact area.The widespread adoption of smart mobile devices in China has led to the installation of numerous third-party applications. These applications rely on push notification services enabled by Push Software Development Kits (SDKs) provided by mobile service providers. These SDKs, compliant with data security standards, collection scopes, and transmission protocols, utilize built-in functional modules to periodically collect user-authorized geolocation data. This data encompasses device identifiers, GPS coordinates, WiFi signatures, cellular base station logs, and network connectivity metadata. After encryption, these multi-source data streams inputs are aggregated into structured mobile location datasets. They can provide high-resolution insights into population mobility patterns during disasters.At 9:05 (Beijing time) on 7 January 2025, an earthquake with magnitude Ms 6.8 hit Dingri County, Tibet Autonomous Region, which killed 126 people. We collected a mobile phone location dataset covering a 150 km radius from the epicenter, spanning 38 hours from 9:00 on 6 January to 1:00 on 8 January. It comprises 146,123 records. Each record includes four mobile location-based indicators, namely (1) Active Base Stations (base stations scanned and periodically reported by mobile devices), (2) Active Wi-Fi Hotspots (Wi-Fi hotspots scanned and periodically reported by mobile devices), (3) Mobile Devices (mobile devices that obtain services through multiple positioning methods) and (4) Wi-Fi-Connected Devices (mobile devices connected to Wi-Fi hotspots). Utilizing natural neighbor interpolation and Thiessen polygon interpolation methods, we analyzes changes in four mobile location-based indicators and their spatiotemporal distribution characteristics before and after the earthquake, summarizing crowd movement patterns and communication behaviors after the Dingri earthquake. The results indicate an uneven distribution of population and differing dynamics in mobile phone signal activity. This reflects different behavioral patterns and the potential perceived extent of the earthquake. Within 50 km of the epicenter, all four indicators showed varying degrees of decline post-earthquake, while areas beyond 100 km exhibited short-term surges, reflecting differentiated behavioral responses based on seismic impact severity. In areas experiencing strong shaking, risk avoidance behavior predominated, while in areas where shaking was noticeable but less severe, communication behavior was more prominent. Mobile data decline zones showed high spatial correlation with intensity VIII+ regions, proving their effectiveness as rapid indicators for identifying strongly affected areas. Notably, mobile location data enabled accurate identification of strongly affected zones within 30 min post-earthquake.The research establishes a theoretical-technical framework supporting three critical post-disaster applications: (1) dynamic population distribution sensing, (2) behavioral pattern analysis of affected populations, and (3) rapid evaluation of seismic perception zones.

There is tremendous growth in the amount of digital video creation and communication with the proliferation of mobile consumer electronic devices such as cellular phones with video capture and display capabilities. This trend will continue with the demand for higher spatial and temporal video resolutions accompanied by 3D and multiview video. Since it is not practical to store or transmit the raw digital video data, it is essential to reduce it with digital video compression. To cope with the vast amount of raw digital video data, digital video compression standards use increasingly more complex algorithms. These algorithms achieve higher compression at the same quality at the expense of significant computational complexity. Therefore, it is essential to design low power digital video compression hardware especially for mobile devices. In this talk, I will present two sets of power reduction techniques for digital video compression hardware. The ones in the first set reduce the power consumption with no impact on the video quality. The ones in the second set trade off video quality for power consumption which also enables adjusting video quality based on available energy in the battery of a mobile device for graceful degradation. I will show the impact of these techniques on the power consumption of digital video compression hardware implementing H.264/AVC and H.265/HEVC standards.