Search results for "image processing"
showing 10 items of 3285 documents
Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow
2020
An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner and difficulty of the tasks such that the learner experiences a state of flow during the learning. Flow is a mental state that psychologists refer to when someone is completely immersed in an activity. Flow state is a multidisciplinary field of research and has been studied not only in psychology, but also neuroscience, education, sport, and games. The idea behind this paper is to try to achieve a flow state in a similar way as Elo’s chess skill rating (Glickman in Am Ches…
Public Service Media’s Funding Crisis in the Face of the Digital Challenge
2020
The funding crisis of Public Service Media (PSM) is also a crisis affecting its legitimacy, business model, audience, innovation and transformation required to adapt to the current digital ecosystem, which is dominated by the changes in the access and consumption ways available to citizens, as well as by the new telecommunications global players. Eleven European countries have cut back the budgets of their public service media organizations during the past five years, and those which haven’t done it yet are facing adjustment plans until 2020. Besides financial pressures, European PSM is also facing increasing opposition from private operators, populist parties and the constant appetite for …
Geometric deformation measurement and correction applied to dynamic streak camera images
2002
The complete procedure of measuring and correcting geometric deformations encountered with dynamic streak camera images in the picosecond range is presented and discussed. First, we describe the experimental setup derived from the well known spacing calibration grid method. The implemented measurement bench, adapted to time-resolved 1D imaging, notably exhibits a great accuracy and repeatability both in space and time thanks to a three-axis motorized translation stage and programmable delay lines. Second, we examine image restoration by two different analytical transform means (local versus global): results and performances of both are compared. Then we deal with final image reconstruction …
Digital Image Analysis Applied to Tumor Cell Proliferation, Aggressiveness, and Migration-Related Protein Synthesis in Neuroblastoma 3D Models
2020
Patient-derived cancer 3D models are a promising tool that will revolutionize personalized cancer therapy but that require previous knowledge of optimal cell growth conditions and the most advantageous parameters to evaluate biomimetic relevance and monitor therapy efficacy. This study aims to establish general guidelines on 3D model characterization phenomena, focusing on neuroblastoma. We generated gelatin-based scaffolds with different stiffness and performed SK-N-BE(2) and SH-SY5Y aggressive neuroblastoma cell cultures, also performing co-cultures with mouse stromal Schwann cell line (SW10). Model characterization by digital image analysis at different time points revealed that cell pro…
Selecting industrial robots for milling applications using AHP
2017
Abstract Industrial robots are usually used for pick-and-place applications, which require only point-to-point motion control. However, the recent developments, both in robot technology and in Computer Automated Machining (CAM) software, allow the use of these equipment in applications which require continuous path control, such as multi-axis milling processes. However, the producers do not offer robots specifically developed for this kind of application, thus the user has to choose the most appropriate robot for this goal from a wide range of general purpose robot types. This research work proposes a method based upon Analytic Hierarchy Process (AHP) for selecting the industrial robot for …
On Metadata Support for Integrating Evolving Heterogeneous Data Sources
2019
With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and tran…
Voltage Security Assessment by Using PFDT and CBR Methods in Emerging Power System
2018
Abstract This paper exhibits varied methods for voltage security assessment in a restructured power system. This paper primarily lays emphasis on two methods that are Probabilistic Fuzzy Decision Tree (PFDT) and Case Based Reasoning (CBR). In PFDT, Decision Tree plays an integral role for classification of system. For further classification of power system security, an algorithm is developed to categorise the buses which trouble the security most. After classification of system, by using minimum amount of load curtailment of voltages on buses which made insecure to secure load. Optimization of load is done by curtailing reactive power from insecure buses. In CBR, old cases from database are…
The impact of user’s availability on On-line Ego Networks: a Facebook analysis
2016
We have defined and implemented a Facebook application to log a Facebook dataset.We have studied and validated the structural properties of the whole dataset and of the Dunbar ego networks.We have analyzed the interactions of the users.The availability of the users in the Dunbar ego networks have been investigated.Our results reveal the presence of the temporal homophily property in the Dunbar ego networks. Online Social Networks (OSNs) are the most popular applications in todays Internet and they have changed the way people interact with each other. Understanding the structural properties of OSNs and, in particular, how users behave when they connect to OSNs is crucial for designing user-c…
A Proposal to Model Ancient Silk Weaving Techniques and Extracting Information from Digital Imagery - Ongoing Results of the SILKNOW Project
2019
Three dimensional (3D) virtual representations of the internal structure of textiles are of interest for a variety of purposes related to fashion, industry, education or other areas. The modeling of ancient weaving techniques is relevant to understand and preserve our heritage, both tangible and intangible. However, ancient techniques cannot be reproduced with standard approaches, which usually are aligned with the characteristics of modern, mechanical looms. The aim of this paper is to propose a mathematical modelling of ancient weaving techniques by means of matrices in order to be easily mapped to a virtual 3D representation. The work focuses on ancient silk textiles, ranging from the 15…
Preventing Overlaps in Agglomerative Hierarchical Conceptual Clustering
2020
Hierarchical Clustering is an unsupervised learning task, whi-ch seeks to build a set of clusters ordered by the inclusion relation. It is usually assumed that the result is a tree-like structure with no overlapping clusters, i.e., where clusters are either disjoint or nested. In Hierarchical Conceptual Clustering (HCC), each cluster is provided with a conceptual description which belongs to a predefined set called the pattern language. Depending on the application domain, the elements in the pattern language can be of different nature: logical formulas, graphs, tests on the attributes, etc. In this paper, we tackle the issue of overlapping concepts in the agglomerative approach of HCC. We …