Search results for "Abstract data type"
showing 10 items of 1140 documents
A new method for forecasting energy output of a large-scale solar power plant based on long short-term memory networks a case study in Vietnam
2021
Abstract This paper proposes a new model for short-term forecasting power generation capacity of large-scale solar power plant (SPP) in Vietnam considering the fluctuations of weather factors when applying the Long Short-Term Memory networks (LSTM) algorithm. At first, a configuration of the model based on the LSTM algorithm is selected in accordance with the weather and operating conditions of SPP in Vietnam. Not only different structures of LSTM model but also other conventional forecasting methods for time series data are compared in terms of error accuracy of forecast on test data set to evaluate the effectiveness and select the most suitable LSTM configuration. The most suitable config…
Towards a mean body for apparel design
2016
This paper focuses on shape average with applications to the apparel industry. Apparel industry uses a consensus sizing system; its major concern is to fit most of the population into it. Since anthropometric measures do not grow linearly, it is important to find prototypes to accurately represent each size. This is done using random compact mean sets, obtained from a cloud of 3D points given by a scanner and applying to the sample a previous definition of mean set. Additionally, two approaches to define confidence sets are introduced. The methodology is applied to data obtained from a real anthropometric survey. This paper has been partially supported by the following grants: TIN2009-14392…
Extraction of Airways from CT (EXACT'09)
2012
Contains fulltext : 107854.pdf (Publisher’s version ) (Open Access) This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part o…
Design and implementation of a course scheduling system using Tabu Search
2002
Abstract Building a course timetable is a difficult and lengthy task which universities devote a large amount of human and material resources to every year. We have developed a computer package to solve this problem. The program runs on a PC and the user may set the objectives and parameters from among a wide range of possibilities. It has a user-friendly interface for the user to input the relevant data and obtain the corresponding results. The optimization process is based on a set of heuristic algorithms. The core is a Tabu Search procedure for which several strategies have been developed and tested in order to get a fast and powerful algorithm. The first tests of the package have produc…
An Efficient Traceable Attribute-Based Authentication Scheme with One-Time Attribute Trees
2015
Attribute-based authentication (ABA) is a way to authenticate signers by means of attributes and it requests proof of possessing required attributes from the one to be authenticated. To achieve the property of traceability, required attributes should be combined with the signer’s attribute private keys in order to generate a signature. In some schemes, signers’ attribute keys are related to attribute trees, so changing attribute trees will cause the regeneration of all related attribute keys. In this paper, we propose an efficient traceable ABA scheme, where the generation of signers’ attribute keys is independent from attribute trees. Thus the same set of attribute keys can be used with a …
Learning Automata-Based Solutions to the Multi-Elevator Problem
2019
In the last century, AI has been the topic of interest in many areas, where the focus was on mimicking human behaviour. It has been researched to be incorporated into different domains, such as security, diagnosis, autonomous driving, financial prediction analysis and playing games such as chess and Go. They also worked on different subfields of AI such as machine learning, deep learning, pattern recognition and other relevant subfields. Our work in a previous paper [1] focused on a problem that has not been tackled using AI before, which is the elevator-problem. In which we try to find the optimal parking floor for the elevator for the single elevator problem. In this paper, our work exten…
An Efficient Multi-Show Unlinkable Attribute Based Credential Scheme for a Collaborative E-Health Environment
2017
Modern electronic healthcare (e-health) systems constitute collaborative environments in which patients' private health data are shared across multiple domains. In such environments, patients' privacy can be violated through the linkability of different user access sessions over patient health data. Therefore, enforcing anonymous as well as multi-session unlinkable access for the users in e-health systems is of paramount importance. As a way of achieving this requirement, more emphasis has been given to anonymous attribute credentials, which allows a user to anonymously prove the ownership of a set of attributes to a verifier and thereby gain access to protected resources. Among the existin…
Global sensitivity analysis of the A-SCOPE model in support of future FLEX fluorescence retrievals
2014
In support of ESA's Earth Explorer 8 candidate mission FLEX (FLuorescence EXplorer), a Photosynthesis Study has been initiated to quantitatively link fluorescence to photosynthesis. This led to the development of A-SCOPE, a graphical user interface software package that integrates multiple biochemical models into the soil-vegetation-atmosphere-transfer model SCOPE. Its latest version (v1.53) has been successfully verified and was subsequently evaluated through a global sensitivity analysis. By using the method of Saltelli [4], the relative importance of each input variable to model outputs was quantified through first order and total effect sensitivity indices. Variations in leaf area index…
Studying the feasibility of a recommender in a citizen web portal based on user modeling and clustering algorithms
2006
This paper presents a methodology to estimate the future success of a collaborative recommender in a citizen web portal. This methodology consists of four stages, three of them are developed in this study. First of all, a user model, which takes into account some usual characteristics of web data, is developed to produce artificial data sets. These data sets are used to carry out a clustering algorithm comparison in the second stage of our approach. This comparison provides information about the suitability of each algorithm in different scenarios. The benchmarked clustering algorithms are the ones that are most commonly used in the literature: c-Means, Fuzzy c-Means, a set of hierarchical …
A neural network approach to movement pattern analysis.
2004
Movements are time-dependent processes and so can be modelled by time-series of coordinates: E.g., each articulation has geometric coordinates; the set of the coordinates of the relevant articulations build a high-dimensional configuration. These configurations--or "patterns"--give reason for analysing movements by means of neural networks: The Kohonen Feature Map (KFM) is a special type of neural network, which (after having been coined by training with appropriate pattern samples) is able to recognize single patterns as members of pattern clusters. This way, for example, the particular configurations of a given movement can be identified as belonging to respective configuration clusters, …