Search results for "computer.software_genre"
showing 10 items of 3858 documents
A Rule-Based Multi-agent System for Road Traffic Management
2009
Road Traffic presents a high dynamism which makes necessary the development of traffic management and control strategies to improve traffic flows and more important, road safety. This dynamism makes necessary the use of intelligent systems to support traffic organizations and road operators to cope with incidents. In this paper we introduce a new expert system to support traffic management when weather problems occur in the road network. The system uses multiagent technology to work with the specific characteristics of traffic domain and is able to work in two modes: a) coordinately, where all the agents works to solve problems in large networks and b) locally where due to communications pr…
IOWA Operators and Its Application to Image Retrieval
2014
This paper presents a relevance feedback procedure based on logistic regression analysis. Since, the dimension of the feature vector associated to each image is typically larger than the number of evaluated images by the user, different logistic regression models have to be fitted separately. Each fitted model provides us with a relevance probability and a confidence interval for that probability. In order to aggregate these set of probabilities and confidence intervals we use an IOWA operator. The results will show the success of our algorithm and that OWA operators are an efficient and natural way of dealing with this kind of fusion problems.
A systematic approach to deriving incremental type checkers
2020
Static typing can guide programmers if feedback is immediate. Therefore, all major IDEs incrementalize type checking in some way. However, prior approaches to incremental type checking are often specialized and hard to transfer to new type systems. In this paper, we propose a systematic approach for deriving incremental type checkers from textbook-style type system specifications. Our approach is based on compiling inference rules to Datalog, a carefully limited logic programming language for which incremental solvers exist. The key contribution of this paper is to discover an encoding of the infinite typing relation as a finite Datalog relation in a way that yields efficient incremental up…
Visual Information Fidelity with better Vision Models and better Mutual Information Estimates
2021
Design of a sun tracker for the automatic measurement of spectral irradiance and construction of an irradiance database in the 330-1100 nm range
2007
Abstract An automatic global and direct solar spectral irradiance system has been designed based on two LICOR spectroradiometers equipped with fibre optics and remote cosine sensors. To measure direct irradiance a sun tracker based on step motors has been developed. The whole system is autonomous and works continuously. From the measurements provided by this system a spectral irradiance database in the 330–1100 nm range has been created. This database contains normal direct and global horizontal irradiances as well as diffuse irradiance on a horizontal plane, together with total atmospheric optical thickness and aerosol optical depth.
Retrieving Quantum Information with Active Learning
2019
Active learning is a machine learning method aiming at optimal design for model training. At variance with supervised learning, which labels all samples, active learning provides an improved model by labeling samples with maximal uncertainty according to the estimation model. Here, we propose the use of active learning for efficient quantum information retrieval, which is a crucial task in the design of quantum experiments. Meanwhile, when dealing with large data output, we employ active learning for the sake of classification with minimal cost in fidelity loss. Indeed, labeling only 5% samples, we achieve almost 90% rate estimation. The introduction of active learning methods in the data a…
Guidance Provided by Teacher and Simulation for Inquiry-Based Learning: a Case Study
2016
Current research indicates that inquiry-based learning should be guided in order to achieve optimal learning outcomes. The need for guidance is even greater when simulations are used because of their high information content and the difficulty of extracting information from them. Previous research on guidance for learning with simulations has concentrated on guidance provided by the simulation. Little research has been done on the role of the teacher in guiding learners with inquiry-based activities using simulations. This descriptive study focuses on guidance provided during small group investigations; pre-service teachers (n = 8) guided third and fifth graders using a particular simulatio…
Multidimensional scaling and stock location assignment in a warehouse: an application
1999
By means of an application, in the present paper, the suitability of a multivariate statistical methodology, as multidimensional scaling (MDS), to solve an optimization problem is shown. In particular, considering the stock location assignment problem in the warehouse of a supermarket chain, the solution gained by applying MDS to a set of seven variables is compared with the one obtainable by considering the usual techniques applied in this context. A wide discussion of results is reported. Copyright © 1999 John Wiley & Sons, Ltd.
Combined Elephant Herding Optimization Algorithm with K-means for Data Clustering
2018
Clustering is an important task in machine learning and data mining. Due to various applications that use clustering, numerous clustering methods were proposed. One well-known, simple, and widely used clustering algorithm is k-means. The main problem of this algorithm is its tendency of getting trapped into local minimum because it does not have any kind of global search. Clustering is a hard optimization problem, and swarm intelligence stochastic optimization algorithms are proved to be successful for such tasks. In this paper, we propose recent swarm intelligence elephant herding optimization algorithm for data clustering. Local search of the elephant herding optimization algorithm was im…
Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms
2016
We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in…