A Model of Attitudes toward the Acceptance of Mobile Phone Use in Public Places

Since the first commercial launch of cellular telecoms by NET in Tokyo Japan in 1979 and the launch of the NMT system in Denmark, Finland, Norway and Sweden in 1981, the mobile phone has undergone continual incremental innovation for changing market needs. This study investigates the factors affecting the attitudes towards the social acceptance of mobile phones in public places and how this attitude affects its usage. Theories on innovation and technology acceptance were reviewed, and studies relating demographic factors to technology acceptance were examined. A model was proposed relating the usage frequency and attitudes towards acceptance of mobile phone in public places to demographic factors, such as country, age, education, gender, and work status. A survey was conducted among mobile phone users, and the sample consisted of 1079 respondents in the United States, France, Italy, Turkey, and Finland. A structural equation model was developed to analyze the survey data. Results of the analysis indicate that the attitudes about mobile phone use in public places depend on country, and age factors. This attitude in turn significantly affects the usage frequency of mobile phones. In addition, usage frequency also is affected by gender and work status. Implications of the findings for both academicians and practitioners are discussedAttitudes about Mobile Phone Use, Simultaneous Relationships, Demographic Factors, Mobile Phone Voice Messaging, Mobile Phone Text Messaging

Robust Inference for State-Space Models with Skewed Measurement Noise

Filtering and smoothing algorithms for linear discrete-time state-space models with skewed and heavy-tailed measurement noise are presented. The algorithms use a variational Bayes approximation of the posterior distribution of models that have normal prior and skew-t-distributed measurement noise. The proposed filter and smoother are compared with conventional low-complexity alternatives in a simulated pseudorange positioning scenario. In the simulations the proposed methods achieve better accuracy than the alternative methods, the computational complexity of the filter being roughly 5 to 10 times that of the Kalman filter.Comment: 5 pages, 7 figures. Accepted for publication in IEEE Signal Processing Letter

3D angle-of-arrival positioning using von Mises-Fisher distribution

We propose modeling an angle-of-arrival (AOA) positioning measurement as a von Mises-Fisher (VMF) distributed unit vector instead of the conventional normally distributed azimuth and elevation measurements. Describing the 2-dimensional AOA measurement with three numbers removes discontinuities and reduces nonlinearity at the poles of the azimuth-elevation coordinate system. Our computer simulations show that the proposed VMF measurement noise model based filters outperform the normal distribution based algorithms in accuracy in a scenario where close-to-pole measurements occur frequently.Comment: 5 page

TAXONOMY DEVELOPMENT IN INFORMATION SYSTEMS: DEVELOPING A TAXONOMY OF MOBILE APPLICATIONS

The complexity of the information systems field often lends itself to classification schemes, or taxonomies, which provide ways to understand the similarities and differences among objects under study. Developing a taxonomy, however, is a complex process that is often done in an ad hoc way. This research-in-progress paper uses the design science paradigm to develop a systematic method for taxonomy development in information systems. The method we propose uses an indicator or operational level model that combines both empirical to deductive and deductive to empirical approaches. We evaluate this method by using it to develop a taxonomy of mobile applications, which we have chosen because of their ever-increasing number and variety. The resulting taxonomy contains seven dimensions with fifteen characteristics. We demonstrate the usefulness of this taxonomy by analyzing a range of current and proposed mobile applications. From the results of this analysis we identify combinations of characteristics where applications are missing and thus are candidates for new and potentially useful applications.taxonomy, design science, mobile application

CED: Color Event Camera Dataset

Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called 'events'. Event cameras offer advantages over conventional frame-based cameras in terms of latency, high dynamic range (HDR) and temporal resolution. Until recently, event cameras have been limited to outputting events in the intensity channel, however, recent advances have resulted in the development of color event cameras, such as the Color-DAVIS346. In this work, we present and release the first Color Event Camera Dataset (CED), containing 50 minutes of footage with both color frames and events. CED features a wide variety of indoor and outdoor scenes, which we hope will help drive forward event-based vision research. We also present an extension of the event camera simulator ESIM that enables simulation of color events. Finally, we present an evaluation of three state-of-the-art image reconstruction methods that can be used to convert the Color-DAVIS346 into a continuous-time, HDR, color video camera to visualise the event stream, and for use in downstream vision applications.Comment: Conference on Computer Vision and Pattern Recognition Workshop

Universal optical transmission features in periodic and quasiperiodic hole arrays

We investigate the influence of array order in the optical transmission properties of subwavelength hole arrays, by comparing the experimental spectral transmittance of periodic and quasiperiodic hole arrays as a function of frequency. We find that periodicity and long-range order are not necessary requirements for obtaining enhanced and suppressed optical transmission, provided short-range order is maintained. Transmission maxima and minima are shown to result, respectively, from constructive and destructive interference at each hole, between the light incident upon and exiting from a given hole, and surface plasmon polaritons (SPPs) arriving from individual neighboring holes. These SPPs are launched along both illuminated and exit surfaces, by diffraction of the incident and emerging light at the neighboring individual subwavelength holes. By characterizing the optical transmission of a pair of subwavelength holes as a function of hole-hole distance, we demonstrate that a subwavelength hole can launch SPPs with an efficiency up to 35%, and with an experimentally determined launch phase φ = π/2, for both input-side and exit-side SPPs. This characteristic phase has a crucial influence on the shape of the transmission spectra, determining transmission minima in periodic arrays at those frequencies where grating coupling arguments would instead predict maxima

Computing the expected makespan of task graphs in the presence of silent errors

International audienceApplications structured as Directed Acyclic Graphs (DAGs) of tasks correspond to a general model of parallel computation that occurs in many domains, including popular scientific workflows. DAG scheduling has received an enormous amount of attention, and several list-scheduling heuristics have been proposed and shown to be effective in practice. Many of these heuristics make scheduling decisions based on path lengths in the DAG. At large scale, however, compute platforms and thus tasks are subject to various types of failures with no longer negligible probabilities of occurrence. Failures that have recently received increasing attention are " silent errors, " which cause a task to produce incorrect results even though it ran to completion. Tolerating silent errors is done by checking the validity of the results and re-executing the task from scratch in case of an invalid result. The execution time of a task then becomes a random variable, and so are path lengths. Unfortunately, computing the expected makespan of a DAG (and equivalently computing expected path lengths in a DAG) is a computationally difficult problem. Consequently, designing effective scheduling heuristics is preconditioned on computing accurate approximations of the expected makespan. In this work we propose an algorithm that computes a first order approximation of the expected makespan of a DAG when tasks are subject to silent errors. We compare our proposed approximation to previously proposed such approximations for three classes of application graphs from the field of numerical linear algebra. Our evaluations quantify approximation error with respect to a ground truth computed via a brute-force Monte Carlo method. We find that our proposed approximation outperforms previously proposed approaches, leading to large reductions in approximation error for low (and realistic) failure rates, while executing much faster