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In this paper an advanced iris-biometric comparator is presented. In the proposed scheme an analysis of bit-error patterns produced by Hamming distance-based iris-code comparisons is performed. The lengths of sequences of horizontal consecutive mis-matching bits are measured and a frequency distribution is estimated. The difference of the extracted frequency distribution to that of an average genuine...
Nowadays a huge volume of biomedical data (images, genes, etc) are daily generated. The interpretation of such data involves a considerable expertise. The misinterpretation and/or misdetection of a suspicious clinical finding leads to increasing the negligence claims, and redundant procedures (e.g. biopsies). The analysis of biomedical data is a complex task which are performed by specialists on whose...
This study aims to present time series-based forecasting for Malaysian crude palm oil prices using neural network algorithms. Daily prices of soy bean oil and currency exchange rates are tested as input features, in addition to crude palm oil prices. Efforts are focused on finding the optimal network structures for the modelling of crude palm oil price forecasting. Neural network structures with an...
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
Wearable sensors have the potential to enable clinical-grade ambulatory health monitoring outside the clinic. Technological advances have enabled development of devices that can measure vital signs with great precision and significant progress has been made towards extracting clinically meaningful information from these devices in research studies. However, translating measurement accuracies achieved...
Iris liveness detection methods have been developed to overcome the vulnerability of iris biometric systems to spoofing attacks. In the literature, it is typically assumed that a known attack modality will be perpetrated. Then liveness models are designed using labelled samples from both real/live and fake/spoof distributions, the latter derived from the assumed attack modality. In this work it is...
Gait recognition aims to identify people through the analysis of the way they walk. The challenge of model-free based gait recognition is to cope with various intra-class variations such as clothing variations and carrying conditions that adversely affect the recognition performances. This paper proposes a novel method which combines Statistical Dependency (SD) feature selection with Globality-Locality...
In the biomedicine domain, a large number of papers are published every day, which is crucial to search for the relevant answers for the user's query. However, documents are not exactly what the users want. Instead, snippets, small segments from the documents, are more proper to meet the requirement of the users. Hence, this paper proposes a biomedical snippet retrieval framework to exactly locate...
Software effort estimation is very crucial and there is always a need to improve its accuracy as much as possible. Several estimation techniques have been developed in this regard and it is difficult to determine which model gives more accurate estimation on which dataset. Among all proposed methods, the Radial Basis Function Neural (RBFN) networks models have presented promising results in software...
Software effort estimation is very crucial and there is always a need to improve its accuracy as much as possible. Several estimation techniques have been developed in this regard and it is difficult to determine which model gives more accurate estimation on which dataset. Among all proposed methods, the Radial Basis Function Neural (RBFN) networks models have presented promising results in software...
In this paper, an online signature verification system based on the segmentation of online signature is proposed. The two set of features i.e shape features and dynamic features are extracted and a feature vector concatenating these two set of features is obtained. Euclidean distance is used as a classifier and a writer dependent threshold is used for verification purpose. In order to evaluate the...
Interconnected computing units are used more and more in our daily lives, starting from the transportation systems and ending with gas and electricity distribution, together with tenths or hundreds of systems and sensors, called critical infrastructures. In this context, cyber protection is vital because they represent one of the most important parts of a country's economy thus making them very attractive...
Human tracking across multiple cameras is highly demanded for large scale video surveillance. To successfully track human across multiple uncalibrated cameras that have no overlapping field of views, a system to train more reliable camera link models is proposed in this paper. We employ a novel approach of combining multiple camera links and building bidirectional transition time distribution in the...
Machine learning (ML) techniques such as artificial neural network (ANN) and support vector machine (SVM) have been increasingly used to predict harmful algal blooms (HABs). In this paper, we use the biweekly data in Tolo Harbour, Hong Kong, and choose several machine learning methods to develop prediction models of algal blooms. Three different kinds of models are designed based on back-propagation...
The precipitous advancements in the field of modeling of dynamical systems, which are the result of numerous relevant investigations, are the evidence of its fundamental importance. Not only does the modeling of the behavior of dynamical systems such as biological systems play an important role in the accurate perception and analysis of these systems, but it also becomes feasible to perfectly predict...
The Modeling and Simulation (M&S) branch at Dugway Proving Ground provides high-fidelity simulation that support a variety of United States Army testing programs. Dugway Proving Ground's primary mission is to provide developmental and production testing to support the nation's chemical and biological (CB) defense programs. To enhance existing test programs, Dugway incorporates many capabilities...
We investigate the application of similarity-based classification to biometric recognition, interpreting similarity functions used in biometric systems (i.e., matching algorithms) as kernel functions. This leads us to formulate biometric recognition as a distinct two-class classification problem for each client, which can be solved even when no representation of biometric samples in a feature space...
Nowadays, biopolymer has been actively used in two important areas in our daily activities; packaging and medical devices. One of the important criteria in production of biopolymer is the quality of the polymer. Therefore, a method of controlling biopolymer quality (i.e. molecular weight) is certainly indispensable in this matter. Moreover, biopolymerization is a nonlinear process that requires a...
In adversarial classification tasks like spam filtering, intrusion detection in computer networks, and biometric identity verification, malicious adversaries can design attacks which exploit vulnerabilities of machine learning algorithms to evade detection, or to force a classification system to generate many false alarms, making it useless. Several works have addressed the problem of designing robust...
After a model-based discussion of terms like skills, competences and creativity, methods for assessment will be analyzed with respect to their applicability in general and in particular to problems of engineering education.
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