The Effect of Transport Amenities on Customer Satisfaction: An Empirical Study from the Online Travel Community

Few studies thus far have examined add-on services associated with mitigating hotel location disadvantages. Drawing on the Elaboration Likelihood Model, we in this study consider the variety of transport amenities as a peripheral cue and propose an econometric model that explores the impact of the transport amenities on customer satisfaction. We estimate the model using 187447 reviews assembled from a well-known online travel community in China. The results show that the variety of transport amenities has a significant positive impact on customer satisfaction. Furthermore, we find that the travelers’ type and transport convenience have a moderating effect on this relationship. From the perspective of the three-factor theory, we further reveal that the transport amenity is a basic factor for business travelers but an excitement factor for leisure travelers. A variety of robustness tests show that the conclusion of this study is robust

An integrative gene selection with association analysis for microarray data classification

The rising interest in integrative approach has shifted gene selection from purely data-centric to incorporating additional biological knowledge. Integrative gene selection is viewed as a promising approach in microarray data classification that took into consideration the complex relationships among genes. However, in most of the existing methods, the selection of genes is still based on expression values alone and biological knowledge is integrated at the end of analysis to verify experimental results or to gain biological insights. Thus, this paper proposed an integrative gene selection based on filter method and association analysis for selecting genes that are not only differentially expressed but also informative for classification. Association analysis is employed to integrate microarray data with multiple types of biological knowledge simultaneously, and to identify groups of genes that are frequently co-occurred in target samples. It has been tested on four cancer-related datasets, and two types of biological knowledge are incorporated, namely Gene Ontology (GO) and KEGG Pathways (KEGG). The experimental results show that the recommended GO based models, KEGG based models, and GO-KEGG based models outperformed the expression-only models by attaining better classification accuracies with lesser number of genes. The performance of the integrative models verified the efficiency and scalability of association analysis in mining microarray data

Negotiable Auction Based on Mixed Graph: A Novel Spectrum Sharing Framework

© 2015 IEEE. Auction-based spectrum sharing is a promising solution to improve the spectrum utilization in 5G networks. Along with the spatial reuse, we observe that the ability to adjust the coverage of a spectrum bidder can provide room to itself for further negotiation while auctioning. In this paper, we propose a novel economic tool, size-negotiable auction mechanism (SNAM), which provides a hybrid solution between auction and negotiation for multi-buyers sharing spectrum chunks from a common database. Unlike existing auction-based spectrum sharing models, each bidder of the SNAM submits its bid for using the spectrum per unit space and a set of coverage ranges over which the bidder is willing to pay for the spectrum. The auctioneer then coordinates the interference areas (or coverage negotiation) to ensure no two winners interfere with each other while aiming to maximize the auction's total coverage area or revenue. In this scenario, the undirected graph used by existing auction mechanisms fails to model the interference among bidders. Instead, we construct a mixed interference graph and prove that SNAM's auctioning on the mixed graph is truthful and individually rational. Simulation results show that, compared with existing auction approaches, the proposed SNAM dramatically improves the spatial efficiency, hence leads to significantly higher seller revenue and buyer satisfaction under various setups. Thanks to its low complexity and low overhead, SNAM can target fine timescale trading (in minutes or hours) with a large number of bidders and requested coverages

Enhancing Student Mark Management Through Web Based System

In search of technological modernization, the Internet is the main medium of delivery. Education today is seen as leading to the development of the information age. Hence the approach to education is also in line with the latest technology. The use of Information and Communication Technologies (ICT) in teaching and learning has become an important method to increase the efficiency and effectiveness of the education management process. On the other hand, the ICT is also used in education to manage student information. Management of student information especially students’ marks is a burdensome task, requiring lecturers to devote more time to complete the task within the stipulated time. Besides, the lecturers who teach more than one class and have more than one marking category such as quizzes, assignments and lab exercises find this task very complicated. The use of software such as Microsoft Excel can be helpful but cannot solve all mark management requirements due to limitation of its function. Therefore, an online students’ mark management system was developed to facilitate the process of mark calculation for the lecturers in the Faculty of Information Science and Technology. By using this system, lecturers can record each student’s marks and the system will automatically compute and issue the student’s grade. In addition, analysis will be conducted in which the system will generate reports and graphs for each subject. The system was developed using the ASP.NET web application development tool, programming language C# and JavaScript as the language support, whereas the Microsoft SQL Server is used as the database tool and ASP.NET Development Server as the web server

Framework for conference management system.

This paper presents a Web-based Conference Management System framework that is intended to support multiple conferences and facilitate the conference management starting from the conference preparation until the attendance tracking process during conference day. The framework derived from the analysis of several web-based related applications. The framework is presents and the results are discussed

A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research

Surrogate-based optimization of tidal turbine arrays: a case study for the Faro-Olhão inlet

This paper presents a study for estimating the size of a tidal turbine array for the Faro-Olhão Inlet (Potugal) using a surrogate optimization approach. The method compromises problem formulation, hydro-morphodynamic modelling, surrogate construction and validation, and constraint optimization. A total of 26 surrogates were built using linear RBFs as a function of two design variables: number of rows in the array and Tidal Energy Converters (TECs) per row. Surrogates describe array performance and environmental effects associated with hydrodynamic and morphological aspects of the multi inlet lagoon. After validation, surrogate models were used to formulate a constraint optimization model. Results evidence that the largest array size that satisfies performance and environmental constraints is made of 3 rows and 10 TECs per row.Eduardo González-Gorbeña has received funding for the OpTiCA project (http://msca-optica.eu/) from the Marie Skłodowska-Curie Actions of the European Union's H2020-MSCA-IF-EF-RI-2016 / GA#: 748747. The paper is a contribution to the SCORE pro-ject, funded by the Portuguese Foundation for Science and Technology (FCT–PTDC/AAG-TEC/1710/2014). André Pacheco was supported by the Portuguese Foun-dation for Science and Technology under the Portuguese Researchers’ Programme 2014 entitled “Exploring new concepts for extracting energy from tides” (IF/00286/2014/CP1234).info:eu-repo/semantics/publishedVersio

Local antiferromagnetic exchange and collaborative Fermi surface as key ingredients of high temperature superconductors

Cuprates, ferropnictides and ferrochalcogenides are three classes of unconventional high-temperature superconductors, who share similar phase diagrams in which superconductivity develops after a magnetic order is suppressed, suggesting a strong interplay between superconductivity and magnetism, although the exact picture of this interplay remains elusive. Here we show that there is a direct bridge connecting antiferromagnetic exchange interactions determined in the parent compounds of these materials to the superconducting gap functions observed in the corresponding superconducting materials. High superconducting transition temperature is achieved when the Fermi surface topology matches the form factor of the pairing symmetry favored by local magnetic exchange interactions. Our result offers a principle guide to search for new high temperature superconductors.Comment: 12 pages, 5 figures, 1 table, 1 supplementary materia

FXR1P but not FMRP regulates the levels of mammalian brain-specific microRNA-9 and microRNA-124

Mammalian brain-specific miR-9 and miR-124 have been implicated in several aspects of neuronal development and function. However, it is not known how their expression levels are regulated in vivo. We found that the levels of miR-9 and miR-124 are regulated by FXR1P but not by the loss of FXR2P or FMRP in vivo, a mouse model of fragile X syndrome. Surprisingly, the levels of miR-9 and miR-124 are elevated in fmr1/fxr2 double-knock-out mice, in part reflecting posttranscriptional upregulation of FXR1P. Indeed, FXR1P is required for efficient processing of pre-miR-9 and pre-miR-124 in vitro and forms a complex with Dicer and pre-miRNAs. These findings reveal differential roles of FMRP family proteins in controlling the expression levels of brain-specific miRNAs