Search results for "Software"
showing 10 items of 7396 documents
FALCON - joint fair airtime allocation and rate control for DASH video streaming in software defined wireless networks
2020
Software Defined Wireless Networks offer an opportunity to enhance the performance of specific services by applying centralized mechanisms which make use of a global view of the network resources. This paper presents FALCON, a novel solution that jointly optimizes fair airtime allocation and rate recommendations for Server and Network Assisted DASH video streaming, providing proportional fairness among the clients. Since this problem is NP-hard, FALCON introduces a novel heuristic algorithm that is proved to achieve almost optimal results in a practical amount of time. The performance of FALCON is evaluated when used in conjunction with three referent Adaptive Bit Rate strategies (PANDA, BO…
Tasks and Digital Tools
2016
International audience; This chapter considers scholastic tasks with digital tools. The first two sections consider tasks in ‘ordinary’ classrooms (tasks for learning) and issues relating to tasks using mathematical software. The first section presents examples of tasks with digital tools to highlight potential problems and opportunities for learning. The second section considers issues arising from the literature on tasks design with and without digital tools. The final section looks at task-tool issues in larger-than-the-individual classroom research and in assessment; it also comments of avenues for further development
Mobile Electronic Commerce: Emerging Issues
2000
There are many definitions for Mobile Electronic Commerce (M-Commerce). We define M-Commerce as any type of transaction of an economic value having at least at one end a mobile terminal and thus using the mobile telecommunications network. The Wireless Application Protocol (WAP) plays an important role in m-commerce by optimizing Internet standards for the constraints of the wireless environment and thus bridging the gap between Internet and mobile world. Mobile Network Operators can play a major role in m-commerce by being strategically positioned between customers and content/service providers. In this paper we investigate the roles the operator can play in m-commerce and discuss respecti…
On marrying ontological and metamodeling technical spaces
2007
In software engineering, the use of models and metamodeling approaches (e.g., MDA with MOF/UML) for purposes such as software design or software validation is an established practice. Ontologies constitute domain models formalized using expressive logic languages for class definitions and rules. Hence, when seen from an abstract point of view, the two paradigms and their various technological spaces seem closely related. However, in the state-of-the-art research and practice the two technologies are just beginning to converge and the relationship between the two is still under exploration. In this paper, we give an outline of current ontology technologies, such as the Semantic Web standards…
Auxilum Medicine: A Cloud Based Platform for Real-Time Monitoring Medical Devices
2015
Nowadays, time is a very valuable resource and can make the difference between life and death. Having knowledge about this fact we decided to deal with one of the most important aspects of contemporary medicine, EMS (emergency medical services) response time. Modern systems that encourage intelligent communication methods between medical devices and doctors are a must in ubiquitous health care environments. Auxilum Medicine fosters a triple-win situation regarding the relationship between medical institutions, doctors and patients. Emergency patients should be treated with utmost care because their life is hanging by a thread if nobody is present to take immediate action. We are presenting …
Special issue on pattern recognition techniques in data mining
2017
Peer Reviewed
Hybrid descriptive-inferential method for key feature selection in prostate cancer radiomics
2021
In healthcare industry 4.0, a big role is played by radiomics. Radiomics concerns the extraction and analysis of quantitative information not visible to the naked eye, even by expert operators, from biomedical images. Radiomics involves the management of digital images as data matrices, with the aim of extracting a number of morphological and predictive variables, named features, using automatic or semi-automatic methods. Multidisciplinary methods as machine learning and deep learning are fully involved in this field. However, the large number of features requires efficient and effective core methods for their selection, in order to avoid bias or misinterpretations problems. In this work, t…
How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data
2020
This study examines how quickly we can predict users’ ratings on visual aesthetics in terms of simplicity, diversity, colorfulness, craftsmanship. To predict users’ ratings, first we capture gaze behavior while looking at high, neutral, and low visually appealing websites, followed by a survey regarding user perceptions on visual aesthetics towards the same websites. We conduct an experiment with 23 experienced users in online shopping, capture gaze behavior and through employing machine learning we examine how fast we can accurately predict their ratings. The findings show that after 25 s we can predict ratings with an error rate ranging from 9% to 11% depending on which facet of visual ae…
Invalid Syntax: NooJ Assisted Automatic Detection of Errors in Auxiliaries and Past Participles in Italian
2017
The work targets two areas of Italian morphosyntax: auxiliary selection (AS) and past participle agreement (PPA). In selecting such inflectional morphemes, learners of Italian commit frequent errors, even after a long period of constant study. We aim to enclose AS and PPA within the boundaries of NLP in order that a tool can be developed with a twofold purpose: first, it helps experts to build specific computer drills regarding AS and PPA; second, it assists self-taught learners in verifying whether their periphrastic sentences in Italian are well-turned. This area of Computer-Assisted Language Learning is currently poorly investigated. Further research might substantiate the importance of …
Automated quality control of next generation sequencing data using machine learning
2019
AbstractControlling quality of next generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterized common NGS quality features and developed a novel quality control procedure involving tree-based and deep learning classification algorithms. Predictive models, validated on internal data and external disease diagnostic datasets, are to some extent generalizable to data from unseen species. The derived statistical guidelines and predictive models represent a valuable resource for users of NGS data to better understand quality issues and perform automatic quality control. Our guidelines and software are available at the following …