Search results for "Benchmark"

Deep Convolutional Neural Networks for Fire Detection in Images

2017

Detecting fire in images using image processing and computer vision techniques has gained a lot of attention from researchers during the past few years. Indeed, with sufficient accuracy, such systems may outperform traditional fire detection equipment. One of the most promising techniques used in this area is Convolutional Neural Networks (CNNs). However, the previous research on fire detection with CNNs has only been evaluated on balanced datasets, which may give misleading information on real-world performance, where fire is a rare event. Actually, as demonstrated in this paper, it turns out that a traditional CNN performs relatively poorly when evaluated on the more realistically balance…

Hydraulic vs. Electric: A Review of Actuation Systems in Offshore Drilling Equipment

2016

This article presents a survey on actuation systems encountered in offshore drilling applications. Specifically, it focuses on giving a comparison of hydraulic and electric drivetrains along with detailed explanations of their advantages and drawbacks. A significant number of industrial case studies is examined in addition to the collection of academic publications, in order to accurately describe the current market situation. Some key directions of research and development required to satisfy increasing demands on powertrains operating offshore are identified. The impact of the literature and application surveys is further strengthened by benchmarking two designs of a full-scale pipe handl…

A Feature Rich Distance-Based Many-Objective Visualisable Test Problem Generator

2019

In optimiser analysis and design it is informative to visualise how a search point/population moves through the design space over time. Visualisable distance-based many-objective optimisation problems have been developed whose design space is in two-dimensions with arbitrarily many objective dimensions. Previous work has shown how disconnected Pareto sets may be formed, how problems can be projected to and from arbitrarily many design dimensions, and how dominance resistant regions of design space may be defined. Most recently, a test suite has been proposed using distances to lines rather than points. However, active use of visualisable problems has been limited. This may be because the ty…

Redesigning Computer-Supported Work Processes with Dual Information Systems: The Work Process Benchmarking Service

1999

The conceptual design of most computer-based information systems reflects a dualism of technology. During the development phase, part of the work-domain-related knowledge is formalized and encoded in the software, making it difficult for users to reflect on and use this knowledge. This design/use dualism contributes to the deterioration of the interpretive flexibility of information systems. We propose an information systems architecture called Dual Information Systems (DIS) that helps bridge the design/use dualism by providing organizations with a set of services that enable and reinforce both effective, institutionalized working and the questioning and (re)construction of computer-support…

An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems

2015

This paper presents a new preference based interactive evolutionary algorithm (I-SIBEA) for solving multiobjective optimization problems using weighted hypervolume. Here the decision maker iteratively provides her/his preference information in the form of identifying preferred and/or non-preferred solutions from a set of nondominated solutions. This preference information provided by the decision maker is used to assign weights of the weighted hypervolume calculation to solutions in subsequent generations. In any generation, the weighted hypervolume is calculated and solutions are selected to the next generation based on their contribution to the weighted hypervolume. The algorithm is compa…

A dynamic program analysis to find floating-point accuracy problems

2012

Programs using floating-point arithmetic are prone to accuracy problems caused by rounding and catastrophic cancellation. These phenomena provoke bugs that are notoriously hard to track down: the program does not necessarily crash and the results are not necessarily obviously wrong, but often subtly inaccurate. Further use of these values can lead to catastrophic errors.In this paper, we present a dynamic program analysis that supports the programmer in finding accuracy problems. Our analysis uses binary translation to perform every floating-point computation side by side in higher precision. Furthermore, we use a lightweight slicing approach to track the evolution of errors.We evaluate our…

Yritysvastuuraportoinnin vertailukelpoisuus ja raportoinnin kehittäminen : case KONE Oyj

2013

Tämän tutkimuksen tarkoitus oli selvittää vastuuraportoinnin vertailtavuutta parantavia tekijöitä ja miten vertailukelpoisuutta voidaan kehittää yrityksissä. Tutkimuksen kohdeyrityksenä on KONE Oyj, jonka vastuuraportoinnin parantamiseksi annettiin kehitysehdotuksia. Tutkimuksen metodologinen lähestymistapa on kvalitatiivinen case-tutkimus. Tutkimus toteutettiin kahdella metodilla: Ensimmäinen osa sisältää vastuuraporttien vertailututkimuksen, jossa vertailtiin KONEen, ThyssenKruppin, Metson ja Ahlstromin vastuuraportteja raportoinnin selittävien teorioiden, GRI:n sisältö- ja laatutekijöiden, sertifiointien ja standardien, sisällön jatkuvuuden ja lukujen esittämisen sekä ulkoisen varmennuks…

2D motif basis applied to the classification of digital images

2016

The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. Different types of features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the set of candidate features. Recently, a special class of bidimensional motifs, i.e. 2D motif basis has been introduced in the literature. 2D motif basis showed to be powerful in capturing the r…

HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers

2017

HyperLabelMe is a web platform that allows the automatic benchmarking of remote-sensing image classifiers. To demonstrate this platform's attributes, we collected and harmonized a large data set of labeled multispectral and hyperspectral images with different numbers of classes, dimensionality, noise sources, and levels. The registered user can download training data pairs (spectra and land cover/use labels) and submit the predictions for unseen testing spectra. The system then evaluates the accuracy and robustness of the classifier, and it reports different scores as well as a ranked list of the best methods and users. The system is modular, scalable, and ever-growing in data sets and clas…

2014

This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel function has the nonlinear attribute and can better handle the case where samples and attributes are massive. In addition, with forehand optimizing the parameters using the cross-validation technique, SVM can produce high accuracy in fault detection. Therefore, there is no need to deal with original data or refer to other algorithms, making the classification problem simple to handle. In order to…