Search results for "400"
showing 10 items of 1272 documents
Exploring Lightweight Deep Learning Solution for Malware Detection in IoT Constraint Environment
2022
The present era is facing the industrial revolution. Machine-to-Machine (M2M) communication paradigm is becoming prevalent. Resultantly, the computational capabilities are being embedded in everyday objects called things. When connected to the internet, these things create an Internet of Things (IoT). However, the things are resource-constrained devices that have limited computational power. The connectivity of the things with the internet raises the challenges of the security. The user sensitive information processed by the things is also susceptible to the trusability issues. Therefore, the proliferation of cybersecurity risks and malware threat increases the need for enhanced security in…
Seeking Information on Social Commerce: An Examination of the Impact of User- and Marketer-generated Content Through an Eye-tracking Study
2021
Following the growing popularity of social commerce sites, there is an increased interest in understanding how consumers decide what products to purchase based on the available information. Consumers nowadays are confronted with the task of assessing marketer-generated (MGC) as well as user-generated information (UGC) in a range of different forms to make informed purchase-related decisions. This study examines the information types and forms that influence consumers in their decision-making process on social commerce. Building on uses and gratifications and dual-process theories, we distinguish between marketer and user generated content, and differentiate formats into informational and no…
Evaluation of Deep Learning and Conventional Approaches for Image Recaptured Detection in Multimedia Forensics
2022
Image recaptured from a high-resolution LED screen or a good quality printer is difficult to distinguish from its original counterpart. The forensic community paid less attention to this type of forgery than to other image alterations such as splicing, copy-move, removal, or image retouching. It is significant to develop secure and automatic techniques to distinguish real and recaptured images without prior knowledge. Image manipulation traces can be hidden using recaptured images. For this reason, being able to detect recapture images becomes a hot research topic for a forensic analyst. The attacker can recapture the manipulated images to fool image forensic system. As far as we know, ther…
Finite-Time Distributed Energy-to-Peak Control for Uncertain Multiagent Systems
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/260201 Open Access This paper investigates the finite-time distributed L2-L∞ consensus control problem of multiagent systems with parameter uncertainties. The relative states of neighboring agents are used to construct the control law and some agents know their own states. By substituting the control input into multiagent systems, an augmented closed-loop system is obtained. Then, we analyze its finite-time boundedness (FTB) and finite-time L2-L∞ performance. A sufficient condition for the existence of the designed controller is given with the f…
Validating retinal fundus image analysis algorithms: issues and a proposal.
2013
This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running …
Mathematical Learning Opportunities in Kindergarten through the Use of Digital Tools: Affordances and Constraints
2013
Accepted version of an article in the journal: Nordic Journal of Digital Literacy. Also available from the publisher at: http://www.idunn.no/ts/dk/2013/03/mathematical_learning_opportunities_in_kindergarten_through This study aims at scrutinising the mathematical learning opportunities of children engaging with digital tools and the emerging affordances and constraints faced in such settings. By adopting a sociocultural perspective on learning and development, the multimodal analysis of the adult-child interaction shows that the children are participants in processes of appropriating the mathematical concepts of sorting and counting. Affordances are taken advantage of by the adults and cons…
Network measures in animal social network analysis : Their strengths, limits, interpretations and uses
2020
International audience; We provide an overview of the most commonly used social network measures in animal research for static networks or time‐aggregated networks. For each of these measures, we provide clear explanations as to what they measure, we describe their respective variants, we underline the necessity to consider these variants according to the research question addressed, and we indicate considerations that have not been taken so far. We provide a guideline indicating how to use them depending on the data collection protocol, the social system studied and the research question addressed. Finally, we inform about the existent gaps and remaining challenges in the use of several va…
Perspectives and reflections on teaching linear algebra
2020
Abstract This paper presents ‘expert opinions’ on what should be taught in a first-year linear algebra course at university; the aim is to gain a generic picture and general guiding principles for such a course. Drawing on a Delphi method, 14 university professors—called ‘experts’ in this study—addressed the following questions: What should be on a first-year linear algebra undergraduate course for engineering and/or mathematics students? How could such courses be taught? What tools (if any) are essential to these two groups of students? The results of the investigation, these experts’ opinions, mainly concern what should be in a linear algebra course (e.g. problem-solving and applications)…
Design and Investigation of a Touch Gesture for Dividing in a Virtual Manipulative Model for Equation-solving
2020
AbstractPhysical models for equation solving typically lack feedback regarding their appropriate use. Such feedback is possible in virtual environments and could be implemented in hybrid models. Based on an epistemological analysis, this article presents a touch gesture as a way for users to signal they want to divide both sides of an equation and a design for feedback on the use of this so-called ‘division gesture’. The design is investigated by contrasting a case study, in which students used an app with the division gesture, with a preparatory study where students had to perform corresponding actions on physical manipulatives. This investigation revealed insight into feedback functions, …
Real-time people counting system using a single video camera
2008
This is the copy of journal's version originally published in Proc. SPIE 6811. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7 There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter…