Search results for "LAB"
showing 10 items of 7932 documents
Stackelberg-Cournot and Cournot equilibria in a mixed markets exchange economy
2012
In this note, we compare two strategic general equilibrium concepts: the Stackelberg-Cournot equilibrium and the Cournot equilibrium. We thus consider a market exchange economy including atoms and a continuum of traders, who behave strategically. We show that, when the preferences of the small traders are represented by Cobb-Douglas utility functions and the atoms have the same utility functions and endowments, the Stackelberg-Cournot and the Cournot equilibrium equilibria coincide if and only if the followers’ best responses functions have a zero slope at the SCE.
Domain-Knowledge Optimized Simulated Annealing for Network-on-Chip Application Mapping
2013
Network-on-Chip architectures are scalable on-chip interconnection networks. They replace the inefficient shared buses and are suitable for multicore and manycore systems. This paper presents an Optimized Simulated Annealing (OSA) algorithm for the Network-on-Chip application mapping problem. With OSA, the cores are implicitly and dynamically clustered using knowledge about communication demands. We show that OSA is a more feasible Simulated Annealing approach to NoC application mapping by comparing it with a general Simulated Annealing algorithm and a Branch and Bound algorithm, too. Using real applications we show that OSA is significantly faster than a general Simulated Annealing, withou…
Fuzzy Clustering of Histopathological Images Using Deep Learning Embeddings
2021
Metric learning is a machine learning approach that aims to learn a new distance metric by increas- ing (reducing) the similarity of examples belonging to the same (different) classes. The output of these approaches are embeddings, where the input data are mapped to improve a crisp or fuzzy classifica- tion process. The deep metric learning approaches regard metric learning, implemented by using deep neural networks. Such models have the advantage to discover very representative nonlinear embed- dings. In this work, we propose a triplet network deep metric learning approach, based on ResNet50, to find a representative embedding for the unsupervised fuzzy classification of benign and maligna…
A GPU-Based DVC to H.264/AVC Transcoder
2010
Mobile to mobile video conferencing is one of the services that the newest mobile network operators can offer to users With the apparition of the distributed video coding paradigm which moves the majority of complexity from the encoder to the decoder, this offering can be achieved by introducing a transcoder This device has to convert from the distributed video coding paradigm to traditional video coding such as H.264/AVC which is formed by simpler decoders and more complex encoders, and allows to the users to execute only the low complex algorithms In order to deal with this high complex video transcoder, this paper introduces a graphics processing unit based transcoder as base station The…
Technological, Organisational and Socio-Interactional Affordances in Simulation-Based Collaborative Learning
2021
Analysis of the applicability of a learning technology requires an evaluation of how the affordances of the learning environment respond to users’ needs. We examine affordances in a simulation-based collaborative learning environment from the learners’ viewpoint. Our analysis focuses on three types of affordances: technological, organisational and socio-interactional. The findings show how teams of learners employ the different types of affordances in their collaborative tasks. In addition, our analysis illustrates the interdependent and interlinked nature of the affordances. We offer an analytical understanding of the dynamics among different kinds of affordances and show how they can be a…
Ranking-Oriented Collaborative Filtering: A Listwise Approach
2016
Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains in terms of ranking accuracy, being able to estimate a precise preference ranking of items for each user rather than the absolute ratings (as rating-oriented CF algorithms do). Conventional memory-based ranking-oriented CF can be referred to as pairwise algorithms. They represent each user as a set of preferences on each pair of items for similarity calculations and predictions. In this study, we propose ListCF, a novel listwise CF paradigm that seeks improvement in bot…
SCCF Parameter and Similarity Measure Optimization and Evaluation
2019
Neighborhood-based Collaborative Filtering (CF) is one of the most successful and widely used recommendation approaches; however, it suffers from major flaws especially under sparse environments. Traditional similarity measures used by neighborhood-based CF to find similar users or items are not suitable in sparse datasets. Sparse Subspace Clustering and common liking rate in CF (SCCF), a recently published research, proposed a tunable similarity measure oriented towards sparse datasets; however, its performance can be maximized and requires further analysis and investigation. In this paper, we propose and evaluate the performance of a new tuning mechanism, using the Mean Absolute Error (MA…
Feedback linearization control of wind turbine equipped with doubly fed induction generator
2017
This paper focuses on several control techniques of a wind turbine of rated power of about 1 MW. In particular, a wind generator equipped with an asynchronous doubly-fed induction machine has been considered and its dynamic model in MATLAB/SIMULINK environment has been implemented. Starting from this model the feedback linearization control has been derived, and several simulations have been carried out, with the aim of compare its dynamic performances with the classical field oriented control, and with the V/f control. The results allow us to conclude that a DFIG controlled by a feedback linearization technique ensures better dynamic performance.
A framework to determine maximum capacity of interconnecting DGs in distribution networks
2018
Interconnecting Distributed Generation (DG) in the distribution network is considered as an important area of power system planning. When the DG placed inappropriately, the DG can have negative impact on some important and critical characteristics of system performance such as increased power losses, degraded voltage profile, and mis-coordination between protection devices. This paper introduces a framework to determine the maximum capacity limits of interconnecting DG units in radial distribution networks in order to keep protection scheme unchanged, while the voltage profile remains within acceptable range and on the same time having the minimum power losses in the network; applying this …
Performance Evaluation of a Three- Phase Five-Level Quasi-Z-Source Cascaded H-Bridge for Grid-Connected Applications
2018
In the field of the PV generation, Quasi-Z-source cascaded H-bridge (qZS-CHB) inverters are promising due to their features of modularity and high voltage conversion ratio. Thus, new topology structures and innovative modulation techniques are continuously being developed to improve the performance in terms of voltage stress and harmonic content. This paper proposes an innovative modulation technique that allows reducing the voltage stress and a specially designed grid-connected control strategy is also introduced. Through simulations in MATLAB, it has been validated that the performance of a three-phase five-level qZS-CHB is improved with the proposed solution.