40,385 research outputs found

    Using Contactless Mobile Payment in the Vietnamese Restaurant Industry

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    This study develops a critical understanding of Contactless Mobile Payment (CMP) in the context of consumer behaviour and explores its use in the Vietnamese restaurant industry. An online survey was used to collect the data (n=153) from Vietnamese consumers. Data analysis was conducted with the use of SPSS and AMOS software. A Confirmatory Factor Analysis (CFA) in conjunction with Structural Equation Modelling (SEM) were employed to explore consumer perceptions regarding the use of CMP. The findings indicate that consumers find CMP a fast and convenient way to make transactions in Vietnamese restaurants. The findings also indicate the importance of ease of use and security. The study contributes to the understanding of consumer behaviour in regard to technology in the service industries context

    Miniaturización de antenas tipo microstrip mediante recubrimientos con materiales ferroeléctricos

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    La limitaci√≥n en el espacio donde se dispone la antena dentro de un dispositivo electr√≥nico ha promovido la investigaci√≥n de alternativas que permitan el desarrollo de antenas miniaturizadas con una amplia capacidad de emisi√≥n y recepci√≥n, siendo los materiales ferroel√©ctricos una de las opciones m√°s acertadas para reducir el tama√Īo de las antenas sin generar cambios significativos en el dise√Īo. Adicionalmente, estos materiales pueden ser obtenidos por diferentes t√©cnicas, dentro de las que sobresale sol-gel por su flexibilidad en deposici√≥n de pel√≠cula. Por ello, el presente trabajo se centra en la evaluaci√≥n del factor de miniaturizaci√≥n de antenas de parche microstrip recubiertas con materiales ferroel√©ctricos tales como titanato de estroncio (STO), titanato de bario-estroncio (BSTO), y titanato de bario (BTO), obtenidos v√≠a sol-gel y depositados mediante spin coating a 3000 rpm (20 s) con tratamiento t√©rmico a 700 ¬įC (1 h, 1 ¬įC/min). Estas antenas fueron dise√Īadas y simuladas dentro de un rango de frecuencia entre 1 y 8.5 GHz; se fabricaron por fotolitograf√≠a usando substratos de al√ļmina de 635 m con metalizaci√≥n en oro (3.0 m) y capa de adherencia de n√≠quel-cromo (0.2 m), para ser caracterizadas con el uso de un analizador vectorial de red (VNA). La ejecuci√≥n de esta investigaci√≥n se verific√≥ mediante difracci√≥n de rayos X, mostrando la presencia de estructuras cristalinas en fase perovskita c√ļbica, con par√°metros de red para STO, BSTO y BTO de 3.9012 ¬Ī 0.0049 √Ö, 3.9631 ¬Ī 0.0055 √Ö, y 4.0268 ¬Ī 0.0119 √Ö, respectivamente. La caracterizaci√≥n microestructural y morfol√≥gica permiti√≥ establecer las condiciones de deposici√≥n y de tratamiento t√©rmico de la pel√≠cula que permitieran uniformidad, homogeneidad y adherencia aceptable de la capa con poca presencia de defectos superficiales. Por su parte, la espectroscop√≠a de rayos X de energ√≠a dispersa cuantific√≥ composiciones elementales para STO de 1.48 ¬Ī 0.13 % wt Sr, y 0.54 ¬Ī 0.07 % wt Ti; BSTO: 0.69 ¬Ī 0.22 % wt Ba, 1.22 ¬Ī 0.12 % wt Sr, 0.63 ¬Ī 0.09 % wt Ti, y 6.05 ¬Ī 0.85 % wt O; y para BTO de 1.28 ¬Ī 0.23 % wt Ba, 0.74 ¬Ī 0.09 % wt Ti, y 7.28 ¬Ī 0.92 % O; todos estos materiales analizados en forma de pel√≠cula cristalizada y depositada sobre Al2O3/Ni-Cr/Au. Los espesores obtenidos para las pel√≠culas de STO, BSTO, y BTO fueron: 2.8130, 4.1070, y 3.9217 m; con constante diel√©ctrica de 92, 136, y 232; tangente de p√©rdida de 0.0112, 0.0104, y 0.0080, con operaci√≥n en 4.116 GHz (-12.6000 dB), 4.0800 GHz (-10.0900 dB), y 4.0200 GHz (-10.0900 dB), respectivamente para STO, BSTO y BTO. Por otro lado, las antenas recubiertas con STO, BSTO y BTO evidenciaron tasas de miniaturizaci√≥n de 4.7 %, 7.0 %, y 15.6 %, con frecuencia de operaci√≥n en 2.5925 GHz, 2.5300 GHz, y 2.2950 GHz, respectivamente. De este modo se comprob√≥ dentro de las instalaciones de la Universidad EAFIT la aplicabilidad de las pel√≠culas ferroel√©ctricas en los procesos de miniaturizaci√≥n de antenas

    Modelling Digital Avatars: a tuple space approach

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    Preprint de: A. Pérez-Vereda, C. Canal, E. Pimentel. Modelling Digital Avatars: a tuple space approach, Science of Computer Programming, vol. 203, Elsevier, 2020, DOI: https://doi.org/10.1016/j.scico.2020.102583.The development of the Internet of Things (IoT) came with the manufacturing of a huge amount of smart things equipped with sensors for making them aware of their environment, and with network connection for allowing remote interaction with them. However, most smart things still lack enough autonomy and context-awareness, hindering them from being people-friendly and actually useful for their users' everyday tasks. IoT devices should take advantage of their sensors and smartness to react automatically to the needs of their users and to provide seamless interactions with them. Within this field, the authors work on the design of Digital Avatars, a mobile computing framework for dynamically programming interactions among smart devices. The framework is based on the virtual profile of the user, which is inferred, stored, and shared by their smartphone. The profile provides a personalized context for running scripts which interact with IoT devices. This way, smartphones become a digital avatar of the user, capable of acting as a personal and seamless interface with their IoT environment. In this work, we present a formalization of Digital Avatars by means of a Linda-based approach with multiple shared tuple spaces. By means of a case study, we show how properties of the systems can be proved, and we briefly describe an implementation of both the Digital Avatars framework and the case study

    EnTruVe: ENergy and TRUst-aware Virtual Machine Allocation in VEhicle Fog Computing for Catering Applications in 5G

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    It is undoubted that fog computing contributes in catering the latency-stringent applications of 5G, and one of the enabling technologies that fundamentally ensure the success of fog computing is virtualization as it offers isolation and platform independence. Although the emergence of vehicle-based fog (referred to as v-fog) facilities can certainly benefit from these desirable features of virtualization, there are several challenges that need to be addressed in order to realize the full potential that v-fogs can offer. One of the challenges of virtualization in v-fog is Virtual Machine (VM) migration. There are several factors that trigger a VM migration in a v-fog such as vehicle resource depletion. VM migrations would not only lead to nonessential usage of valuable resources (e.g. energy, bandwidth, memory) in the v-fogs, but also incur various overheads and performance degradation throughout the whole network. Thus, minimizing VM migrations is necessary. Furthermore, to ensure the seamless VM migrations between v-fogs, trust of v-fogs is required. While there exists studies of trust in the virtualization of cloud, they are irrelevant to v-fogs as v-fogs are different in nature (i.e. heterogeneous, mobile) from the cloud. Additionally, trust is not included in the decision making mechanisms of VM allocation for vehicular environments in the existing works. Moreover, as vehicle resources are constrained, their energy has to be utilized efficiently. In this paper, we propose EnTruVe, an ENergy and TRUst-aware VM allocation in VEhicle fog computing solution that aims to minimize the number of VM migration while reducing VM processing associated energy consumption as much as possible. The VM allocation algorithm in EnTruVe provides a larger selection pool of v-fogs that meets the VMs requirements (e.g. trust, latency), thereby ensuring higher chances of success of VM allocation. Using Analytic Hierarchy Process (AHP), the proposed EnTruVe solution evaluates the v-fogs based on a set of metrics (e.g. energy consumption, end-to-end latency) to select the optimal v-fog for a VM allocation. Results obtained demonstrate that EnTruVe has the least number of VM migrations and it is the most energy efficient solution. Additionally, it shows that EnTruVe provides the highest utilization of v-fogs of up to 57.6% in comparison to other solutions as the number of incoming requests increases

    Image classification over unknown and anomalous domains

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    A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to some task or data type. This thesis investigates the challenges of learning models that generalize well over multiple unknown or anomalous modes and domains in data, and presents new solutions for learning robustly in this setting. Initial investigations focus on normalization for distributions that contain multiple sources (e.g. images in different styles like cartoons or photos). Experiments demonstrate the extent to which existing modules, batch normalization in particular, struggle with such heterogeneous data, and a new solution is proposed that can better handle data from multiple visual modes, using differing sample statistics for each. While ideas to counter the overspecialization of models have been formulated in sub-disciplines of transfer learning, e.g. multi-domain and multi-task learning, these usually rely on the existence of meta information, such as task or domain labels. Relaxing this assumption gives rise to a new transfer learning setting, called latent domain learning in this thesis, in which training and inference are carried out over data from multiple visual domains, without domain-level annotations. Customized solutions are required for this, as the performance of standard models degrades: a new data augmentation technique that interpolates between latent domains in an unsupervised way is presented, alongside a dedicated module that sparsely accounts for hidden domains in data, without requiring domain labels to do so. In addition, the thesis studies the problem of classifying previously unseen or anomalous modes in data, a fundamental problem in one-class learning, and anomaly detection in particular. While recent ideas have been focused on developing self-supervised solutions for the one-class setting, in this thesis new methods based on transfer learning are formulated. Extensive experimental evidence demonstrates that a transfer-based perspective benefits new problems that have recently been proposed in anomaly detection literature, in particular challenging semantic detection tasks

    Development and evaluation of a treatment package for men with an intellectual disability who sexually offend

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    Sex offending in the general population has been a focus of interest for some time due to the damaging nature of the behaviour, and the need to reduce recidivism. Theoretical and clinical advances (Finke1hor, 1986; HM Prison Service, 1996; Marshall, Anderson, & Fernandez, 1999; Serran & Marshall, 2010) in treatment for sex offenders in the general population have been extended to men with an intellectual disability at risk of sexual offending (Lindsay, 2009). The purpose of this project is to develop and evaluate the SOTSEC-ID version cftrus model. Participants are adult males from 15 different locations across England and Wales, with an intellectual disability or borderline cognitive functioning and who have committed sexual offences. A pilot study clarified assessments and procedures, and individual data over several years is presented. A qualitative study using Interpretive Phenomenological Analysis (JP A) illustrates the 'meaning making' of participants' treatment experience through six major themes. A reliability and validity study assesses the four main quantitative measures, QACSO, SAKA, SOSAS, and VESA, finding limited support for criterion validity for the SOSAS and SAKA, excellent inter-rater reli"ability for all four main measures, and good to excellent inter-rater reliability on all but the SAKA Finally, a quantitative study, in collaboration with the wider SOTSEC-ID group, uses a repeated measures design to compare the QACSO, SOSAS and SAKA across pre-group, post-group and follow. up. Significant main effects and post-hoc comparisons were in the predicted direction for all measures. A range of information on demographic, clinical and criminogenic factors including offending during treatment or follow-up are also presented. A recidivism rate of 12.3% over a year was calculated for the sample. The treatment model and collaborative framework is recommended for wider adoption

    Analysis of reliable deployment of TDOA local positioning architectures

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    .Local Positioning Systems (LPS) are supposing an attractive research topic over the last few years. LPS are ad-hoc deployments of wireless sensor networks for particularly adapt to the environment characteristics in harsh environments. Among LPS, those based on temporal measurements stand out for their trade-off among accuracy, robustness and costs. But, regardless the LPS architecture considered, an optimization of the sensor distribution is required for achieving competitive results. Recent studies have shown that under optimized node distributions, time-based LPS cumulate the bigger error bounds due to synchronization errors. Consequently, asynchronous architectures such as Asynchronous Time Difference of Arrival (A-TDOA) have been recently proposed. However, the A-TDOA architecture supposes the concentration of the time measurement in a single clock of a coordinator sensor making this architecture less versatile. In this paper, we present an optimization methodology for overcoming the drawbacks of the A-TDOA architecture in nominal and failure conditions with regards to the synchronous TDOA. Results show that this optimization strategy allows the reduction of the uncertainties in the target location by 79% and 89.5% and the enhancement of the convergence properties by 86% and 33% of the A-TDOA architecture with regards to the TDOA synchronous architecture in two different application scenarios. In addition, maximum convergence points are more easily found in the A-TDOA in both configurations concluding the benefits of this architecture in LPS high-demanded applicationS

    Transportation Planning, Policy, and Electric Micro-Mobilities: A Knowledge Synthesis of Recent Publications

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    This SSHRC-funded (Grant #972-2020-1009) scoping review synthesizes existing research (2010-2021) related to both private and shared electric micro-mobilities (i.e. e-bikes, e-scooters, e-unicycles, e-skateboards). It considers themes such as: rider demographics, usage, and motivations; mobility justice; benefits of and barriers to EMM use; safety and injuries; modal shift among forms of transportation; rider satisfaction with mode choice; environmental impact; conflict and controversy; EMM pilot programs; and EMM integration, legislation, and policy recommendations. Aside from scholarship, media reports are also included, in order to speak to the environment in which the research takes place
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