Mobile Devices and Mobile Data-Issues of Identity and Reference

2001 ◽  
Vol 16 (2-4) ◽  
pp. 323-336 ◽  
Author(s):  
Peter Lucas
Keyword(s):  
Mobile Devices ◽  
Mobile Data

scholarly journals Handheld versus Mobile Data Acquisitions for Spatial Analysis of Natural Turfgrass Sports Fields

HortScience ◽  
2016 ◽  
Vol 51 (9) ◽  
pp. 1176-1183 ◽  
Author(s):  
Chase M. Straw ◽  
Rebecca A. Grubbs ◽  
Kevin A. Tucker ◽  
Gerald M. Henry
Keyword(s):  
Mobile Devices ◽  
Soil Compaction ◽  
Correlation Coefficients ◽  
Penetration Resistance ◽  
Handheld Devices ◽  
Moderate Correlation ◽  
Mobile Data ◽  
Sampling Grid ◽  
Normalized Difference Vegetative Index ◽  
Sports Fields

Research compared handheld and mobile data acquisitions of soil moisture [volumetric water content (VWC)], soil compaction (penetration resistance), and turfgrass vigor [normalized difference vegetative index (NDVI)] of four natural turfgrass sports fields using two sampling grid sizes (4.8 × 4.8 m and 4.8 × 9.6 m). Differences between the two sampling grid sizes were minimal, indicating that sampling with handheld devices using a 4.8 × 9.6 m grid (120–130 samples) would achieve results similar to the smaller grid size. Central tendencies and data distributions varied among the handheld and mobile devices. Moderate to strong correlation coefficients were observed for VWC and NDVI; however, weak to moderate correlation coefficients were observed for penetration resistance at three of the four locations. Kriged maps of VWC and NDVI displayed similar patterns of variability between handheld and mobile devices, but at different magnitudes. Spatial maps of penetration resistance were inconsistent due to device design and user reliability. Consequently, mobile devices may provide the most reliable results for penetration resistance of natural turfgrass sports fields.

Buongiorno! MyAlert

2009 ◽  
pp. 1738-1753
Author(s):  
Guillermo de Haro ◽  
José María García
Keyword(s):  
Mobile Devices ◽  
Charles Darwin ◽  
Vice President ◽  
Internet Services ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
The Creation ◽  
European Sector ◽  
Bubble Burst

In 1999 Jorge Mata, vice president of Broadvision and former expert in interactive solutions for Banco Santander and McKinsey, decided to leave everything to create MyAlert. The company was born on the basis of offering the same Internet services on the new and growing mobile devices. With a strong financial capitalization after raising more than 50 million euros during the bubble burst, in 4 years the company figures were in the black, and the journey had led to the creation of the European sector of mobile data services market and the European leader in that sector. As Charles Darwin emphasized, if a being wants to survive in a shifting environment, it must evolve at least as fast as the medium itself: Buorngiorno! MyAlert ruled the change.

Securing Mobile Data Computing in Healthcare

2011 ◽  
pp. 1930-1939
Author(s):  
Willy Susilo
Keyword(s):  
Mobile Devices ◽  
Point Of Care ◽  
Healthcare Providers ◽  
Data Communication ◽  
Handheld Devices ◽  
Mobile Data ◽  
Case Examples ◽  
Healthcare Environment ◽  
Security Models ◽  
Ward Rounds

Access to mobile data and messages is essential in healthcare environment as patients and healthcare providers are mobile. This is inline with the need of ubiquitous computing in everyday life. Mobile and wireless devices can assist in ensuring patient’s safety by providing easy availability of the data at the point of care. Portability and accessibility of these devices enhances use of them in healthcare environment. However, data integrity and confidentiality of information in them need to be ensured to provide safe, effective and efficient healthcare. Mobile healthcare involves conducting healthcare related activities through using mobile devices such as a smart phone, Personal digital assistant (PDA), wireless enabled computer, iPod and so on. Mobile computing is suitable for healthcare as healthcare providers are mobile. These would be suitable for conducting patient’s healthcare activities in emergencies, ward rounds, homecare, chronic disease management, conducting clinical trials, and so on. There are various projects using mobile devices to enhance patient’s care. With the advancement of medical informatics, telemedicine and information technology, mobile data devices play an enormous role in healthcare system. In this chapter, we outline the need of mobile devices in healthcare, usage of these devices, underlying technology and applications, importance of security of these devices, securing mobile data communication in healthcare through different security models and case examples of applications that we have developed, in particular (1) iPathology tool on iPod, (2) securing healthcare information using Pocket PC 2003, and (3) securing information on handheld devices. There were several incidents in the past due to the insecurity of mobile devices that can leak information to anyone who does not have access to the information. In this chapter, we will illustrate several techniques that we have developed to protect these malicious activities and how these are applicable for securing mobile data computing in healthcare.

Buongiorno! My Alert

2011 ◽  
pp. 29-47
Author(s):  
Guillermo D. Haro
Keyword(s):  
Mobile Devices ◽  
Charles Darwin ◽  
Vice President ◽  
Internet Services ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
The Creation ◽  
European Sector ◽  
Bubble Burst

In 1999 Jorge Mata, vice president of Broadvision and former expert in interactive solutions for Banco Santander and McKinsey, decided to leave everything to create MyAlert. The company was born on the basis of offering the same Internet services on the new and growing mobile devices. With a strong financial capitalization after raising more than 50 million euros during the bubble burst, in 4 years the company figures were in the black, and the journey had led to the creation of the European sector of mobile data services market and the European leader in that sector. As Charles Darwin emphasized, if a being wants to survive in a shifting environment, it must evolve at least as fast as the medium itself: Buorngiorno! MyAlert ruled the change.

Intelligent Cache Management for Mobile Data Warehouse Systems

2008 ◽  
pp. 1539-1556
Author(s):  
Shi-Ming Huang ◽  
Binshan Lin ◽  
Qun-Shi Deng
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Mobile Devices ◽  
Mobile Environment ◽  
Data Mining Technique ◽  
Mobile Data ◽  
Personal Use ◽  
Query Efficiency ◽  
Intelligent Cache ◽  
Cache Mechanism

This research proposes an intelligent cache mechanism for a data warehouse system in a mobile environment. Because mobile devices can often be disconnected from the host server and due to the low bandwidth of wireless networks, it is more efficient to store query results from a mobile device in the cache. For more personal use of mobile devices, we use a data mining technique to determine the pattern from a record of previous queries. Then the data, which will be retrieved by the user, are prefetched and stored in the cache, thus, improving the query efficiency. We demonstrate the feasibility of the proposed approach with experiments using simulation. Comparison of our approach with a standard approach indicates that there is a significant advantage to using mobile data warehouse systems.

scholarly journals A Mobile Application Recommendation Framework by Exploiting Personal Preference with Constraints

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Konglin Zhu ◽  
Zexuan Liu ◽  
Lin Zhang ◽  
Xinyu Gu
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Mobile Applications ◽  
Mobile Application ◽  
Mobile Apps ◽  
Mobile App ◽  
Network Data ◽  
Mobile Data ◽  
Personal Preference ◽  
Battery Power

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.

Assessment of Surgical Needs in Nepal Using Mobile Devices: Mobile Data Collection in a Developing Country

2016 ◽  
Vol 223 (4) ◽  
pp. e119
Author(s):  
Eugenia E. Lee ◽  
Sagar Chawla ◽  
Sanjeev Shrestha ◽  
John Pathak ◽  
Alain Labrique ◽  
...  
Keyword(s):  
Data Collection ◽  
Developing Country ◽  
Mobile Devices ◽  
Mobile Data ◽  
Mobile Data Collection

scholarly journals Energy efficient target set selection and buffer management for D2D mobile data offloading

2021 ◽  
pp. 1-10
Author(s):  
Prince Sharma
Keyword(s):  
Mobile Devices ◽  
Clustering Algorithm ◽  
Data Communication ◽  
D2d Communication ◽  
Significant Feature ◽  
Communication Link ◽  
Community Based ◽  
Data Offloading ◽  
Mobile Data ◽  
Target Set

Data offloading offers a significant solution to the problem of explosive rise in mobile data traffic. A naive approach would be to utilize the infrastructure (cellular tower, WiFi, femtocell) or other mobile devices to offload data. However, increasing the number of a cellular towers, WiFi, or femtocells is costlier deal for data delivery. Recently, device-to-device (D2D) paradigm of data communication has emerged out as one of the most promising solutions to deal with cost effective cellular traffic offloading. D2D communication provides a direct communication link between closely located mobile users. Another significant feature of D2D is its content centric nature, which makes it useful in data offloading. In this paper, we have addressed the issue of data offloading in mobile devices and proposed a hybrid model of D2D communication with ad-hoc nature. The paper also considers the issues like memory constraints of the devices, pruning of replicated messages and energy efficiency to increase the lifetime of the battery. Considering all the constraints and trade off, we have modeled our problem into optimal target selection problem and distributed community detection problem, both of which are NP-hard. We propose a clustering algorithm to optimize the cooperative mobile nodes. The proposed algorithm uses the betweenness centrality and k-means for optimizing target set section. Our proposed algorithm requires less time in terms of computational complexity with limited space. We compare it with the community-based approach in terms of load transferred for varying target set sizes for validation. The simulation results of the suggested algorithm may reduce the energy requirements up to 16.7% and is able to accommodate 80% more traffic as compared to the community-based algorithm.

Context: What’s Going On?

Tap ◽  
2017 ◽  
Author(s):  
Anindya Ghose
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Historical Data ◽  
Mobile Technologies ◽  
Mobile Data ◽  
Time Signals

This chapter discusses the need for businesses to leverage mobile technologies in order incentivize customers to walk into their store at any given point in time. They can also influence who they want walking into their stores by combining their historical data with real-time signals from mobile devices. The key is to know who their customers are. In the mobile economy, knowing the customer starts with identifying each customer's multiple personas. For instance, depending on context, customers can be in “parent mode,” “work mode,” or “family mode.” The remainder of the chapter looks at several contextual questions and the role that mobile data can play in answering them. These questions include: Why is the customer there? What does the customer want now? How is the customer feeling now?

Conservation of Mobile Data and Usability Constraints

2011 ◽  
pp. 40-55
Author(s):  
Rania Mokhtar ◽  
Rashid Saeed
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
Cyber Security ◽  
Data Encryption ◽  
Mobile Environment ◽  
Mobile Data ◽  
Security Technologies ◽  
User Data ◽  
Security Standard ◽  
Stored Information

An important part of ISO/IEC 27002 cyber security standard is the conservation of confidentiality that falls under its computer facility protection part which insures that the computer and its stored information can only be accessed by the authorized users. Securing mobile devices and mobile data to ensure the confidentiality, integrity, and availability of both data and security applications requires special consideration to be paid to the typical mobile environment in which a mobile computing device would be utilized. Protecting mobile devices includes multiple security technologies such as the right identification of its particular user, data encryption, physical locking devices, monitoring and tracking software, and alarms. This chapter reviews security-specific hardware and software applied to mobile computing and presents its advantages and drawbacks. Then it considers the concept of usability constraints in context of mobile computing security and introduces the seamless security method for identity proof of a particular user or device.

Sign in / Sign up

Export Citation Format

Share Document