scholarly journals Towards Integrating Mobile Devices into Dew Computing: A Model for Hour-Wise Prediction of Energy Availability

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 86 ◽  
Author(s):  
Mathias Longo ◽  
Matías Hirsch ◽  
Cristian Mateos ◽  
Alejandro Zunino

With self-provisioning of resources as premise, dew computing aims at providing computing services by minimizing the dependency over existing internetwork back-haul. Mobile devices have a huge potential to contribute to this emerging paradigm, not only due to their proximity to the end user, ever growing computing/storage features and pervasiveness, but also due to their capability to render services for several hours, even days, without being plugged to the electricity grid. Nonetheless, misusing the energy of their batteries can discourage owners to offer devices as resource providers in dew computing environments. Arguably, having accurate estimations of remaining battery would help to take better advantage of a device’s computing capabilities. In this paper, we propose a model to estimate mobile devices battery availability by inspecting traces of real mobile device owner’s activity and relevant device state variables. The model includes a feature extraction approach to obtain representative features/variables, and a prediction approach, based on regression models and machine learning classifiers. On average, the accuracy of our approach, measured with the mean squared error metric, overpasses the one obtained by a related work. Prediction experiments at five hours ahead are performed over activity logs of 23 mobile users across several months.

2020 ◽  
Vol 70 (2) ◽  
pp. 401-416
Author(s):  
Hana Machů

Abstract If in the right-hand sides of given differential equations occur discontinuities in the state variables, then the natural notion of a solution is the one in the sense of Filippov. In our paper, we will consider this type of solutions for vector Dirichlet problems. The obtained theorems deal with the existence and localization of Filippov solutions, under effective growth restrictions. Two illustrative examples are supplied.


2017 ◽  
Vol 25 (2) ◽  
pp. 18
Author(s):  
Mariusz Kruk

<p>The paper discusses the results of a study which explored advanced learners of English engagement with their mobile devices to develop learning experiences that meet their needs and goals as foreign language learners. The data were collected from 20 students by means of a semi-structured interview. The gathered data were subjected to qualitative and quantitative analysis. The results of the study demonstrated that, on the one hand, some subjects manifested heightened awareness relating to the advantageous role of mobile devices in their learning endeavors, their ability to reach for suitable tools and retrieve necessary information so as to achieve their goals, meet their needs and adjust their learning of English to their personal learning styles, and on the other, a rather intuitive and/or ad hoc use of their mobile devices in the classroom.</p>


2021 ◽  
Author(s):  
Mohammad Rasheed Khan ◽  
Shams Kalam ◽  
Rizwan Ahmed Khan

Abstract This investigation presents a powerful predictive model to determine crude oil formation volume factor (FVF) using state-of-the-art computational intelligence (CI) techniques. FVF is a vital pressure-volume-temperature (PVT) parameter used to characterize hydrocarbon systems and is pivotal to reserve evaluation studies and reservoir engineering calculations. Ideally, FVF is measured at the laboratory scale; however, prognostic tools to evaluate this parameter can aid in optimizing time and cost estimates. The database utilized in this study is obtained from open literature and covers statistics of crude oils of Pakistan, Iran, UAE, and Malaysia. Resultantly, this allows to move step forward towards the creation of a generalized model. Multiple CI algorithms are considered, including Artificial Neural Networks (ANN) and Artificial Neural Fuzzy Inference Systems (ANFIS). Models for CI are developed utilizing an optimization strategy for various parameters/hyper-parameters of the respective algorithms. Unique permutations and combinations for the number of perceptron and their resident layers is investigated to reach a solution that provides the most optimum output. These intelligent models are produced as a function of the parameters intrinsically affecting FVF; reservoir temperature, solution GOR, gas specific gravity, and crude oil API gravity. Comparative analysis of various CI models is performed using visualization/statistical analysis and the best model pointed out. Finally, the mathematical equation extraction to determine FVF is accomplished with the respective weights and bias for the model presented. Graphical analysis using scatter plots with a coefficient of determination (R2) illustrates that ANN equation produces the most accurate predictions for oil FVF with R2 in excess of 0.96. Moreover, during this study an error metric is developed comprising of multiple analysis parameters; Average Absolute Error (AAE), Root Mean Squared Error (RMSE), correlation coefficient (R). All models investigated are tested on an unseen dataset to prevent the development of a biased model. Performance of the established CI models are gauged based on this error metric, which demonstrates that ANN outperforms the other models with error within 2% of the measured PVT values. A computationally derived intelligent model proves to provide the strongest predictive capabilities as it maps complex non-linear interactions between various input parameters leading to FVF.


2018 ◽  
pp. 1431-1447
Author(s):  
Barkha Narang ◽  
Jyoti Batra Arora

Mobile Commerce is a term to describe any commercial activity on a mobile device, such as a mobile phone (iPhone, Android, Blackberry) or a tablet (iPad, Galaxy Tab, Surface). This includes all steps of the customer journey; reach, attract, choose, convert and retain. Hence mobile commerce is probably best described as shopping that takes advantage of unique properties of mobile devices. It is also called as m-commerce. Pervasive computing aims at availability and invisibility. On the one hand, pervasive computing can be defined as availability of software applications and information anywhere and anytime. On the other hand, pervasive computing also means that computers are hidden in numerous so-called information appliances that we use in our day-to-day lives Characteristics of pervasive computing applications have been identified as interaction transparency, context awareness, and automated capture of experiences.


2012 ◽  
pp. 1593-1608 ◽  
Author(s):  
Kashif Munir ◽  
Lawan A. Mohammed

Mobile devices are gradually becoming prevalent in our daily life, enabling users in the physical world to interact with the digital world conveniently. Mobile devices increasingly offer functionality beyond the one provided by traditional resources processor, memory and applications. This includes, for example, integrated multimedia equipment, intelligent positioning systems, and different kinds of integrated or accessible sensors. For future generation grids to be truly ubiquitous we must find ways to compensate for the limitations inherent in these devices and integrate them into the grid, in order to leverage available resources and broaden the range of supplied services. On the other hand, most of mobile devices do not have the sufficient capabilities to be either direct clients or services in the grid environment. The existing middleware platforms like Globus do not fully address mobility, yet extending the potential of the Grid to a wider audience promises increase in its flexibility and productivity. This chapter looks into design architecture for mobile computing environment. Focus is given to security and its policies that will enhance the performance of grid computing in terms of secure design, architecture, accessibility, and mobility.


Author(s):  
Barkha Narang ◽  
Jyoti Batra Arora

Mobile Commerce is a term to describe any commercial activity on a mobile device, such as a mobile phone (iPhone, Android, Blackberry) or a tablet (iPad, Galaxy Tab, Surface). This includes all steps of the customer journey; reach, attract, choose, convert and retain. Hence mobile commerce is probably best described as shopping that takes advantage of unique properties of mobile devices. It is also called as m-commerce. Pervasive computing aims at availability and invisibility. On the one hand, pervasive computing can be defined as availability of software applications and information anywhere and anytime. On the other hand, pervasive computing also means that computers are hidden in numerous so-called information appliances that we use in our day-to-day lives Characteristics of pervasive computing applications have been identified as interaction transparency, context awareness, and automated capture of experiences.


2009 ◽  
pp. 279-289
Author(s):  
Emerson Loureiro ◽  
Frederico Bublitz ◽  
Loreno Oliveira ◽  
Nadia Barbosa ◽  
Angelo Perkusich ◽  
...  

The fast development on microelectronics has promoted the increase on the computational power of hardware components. On the other hand, we are facing a significant improvement on energy consumption as well as the reduction of the physical size of such components. These improvements and the emergence of wireless networking technologies are enabling the development of small and powered mobile devices. Due to this scenario, the so-called pervasive computing paradigm, introduced by Mark Weiser in 1991 (Weiser, 1991) is becoming a reality. Such a paradigm envisions a world where environments are inhabited by computing devices, all of them seamlessly integrated into peoples’ lives, and effectively helping to carry on their daily tasks. Among others, one major characteristic of Weiser’s vision is that each device in an environment becomes a potential client or provider of resources. Not surprisingly, pervasive computing environments are becoming dynamic repositories of computational resources, all of them available to mobile users from the palm of their hands. However, devices can unpredictably join and leave such environments. Thus, resources can be dynamically made available or unavailable. Such a scenario has a great impact on the way that resources are found and used. In the case of static environments, such as the Web, it is reasonable to look up and access resources, such as Web pages, knowing the address of their providers beforehand. On the other hand, for dynamic environments, such as the pervasive computing ones, this is not a reasonable approach. This is due to the fact that one cannot guarantee that the provider of a resource will be available at any moment, because it may have left the environment or simply turned off. A better approach would be to discover these resources based on their descriptions, or any other feature that does not require the client to know the specific address of their providers. To this end, some of the current pervasive computing solutions, like Wings (Loureiro, Bublitz, Oliveira, Barbosa, Perkusich, Almeida, & Ferreira, 2006), Green (Sivaharan, Blair, & Coulson, 2005), RUNES (Costa, Coulson, Mascolo, Picco, & Zachariadis, 2005), and Scooby (Robinson, Wakeman, & Owen, 2004), are making use of a novel approach from the branch of distributed applications, the service-oriented computing paradigm (Papazoglou, 2003; Huhns & Singh, 2005). This is due to the fact that such a paradigm provides a crucial element for pervasive computing systems, the ability for dynamically binding to remote resources (Bellur & Narenda, 2005), which enables mobile devices to find needed services on demand. However, pervasive environments may be structured in different ways. They can range from wired networks to completely wireless ones, where communication among the devices is performed in an ad hoc way. Such a characteristic indicates that the way services are provisioned in a pervasive computing environment should fit in its organization, in order to enhance the access to the services available. Considering the above discussion, in this article we provide a review on service provision and its applicability in pervasive computing. More precisely, we will list the existing service provision approaches and discuss the characteristics and problems associated with each one, as well as their usage in pervasive computing environments. We start by providing introductory concepts of service-oriented and pervasive computing, respectively in the service-oriented computing and pervasive computing sections. Next, we present the service provision techniques available and how they can be applied for pervasive computing environments. The main current solutions within this scope will be introduced in the service oriented technologies section. Some of the future trends associated with research for service provision in pervasive computing environments will be presented in the future research trends section. Finally, in the conclusions sect


Author(s):  
K. Ju

Java 2 Micro Edition (J2ME), .NET Compact Framework (.NET CF), and Active Server Pages .NET (ASP.NET) Mobile Controls are commonly used alternatives in mobile programming. They provide an environment for applications to run on mobile devices. However, they are different in many ways, such as supported mobile devices, architecture, and development. Hence, it is important for mobile application developers to understand the differences between them in order to choose the one that meets their requirement. Therefore, in this article we will discuss the general architecture of J2ME, .NET CF and ASP.NET Mobile Controls and compare the three alternatives.


2020 ◽  
Vol 50 (5) ◽  
pp. 688-718 ◽  
Author(s):  
Matías Hirsch ◽  
Cristian Mateos ◽  
Juan Manuel Rodriguez ◽  
Alejandro Zunino

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