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The U.S. Army requires the evaluation of new weapon and vehicle systems through the use of experimental testing and Vulnerability/Lethality (V/L) modeling & simulation (M&S). The current M&S methods being utilized often require significant amounts of time and subject matter expertise. This typically means that quick results cannot be provided when needed to address new threats encountered...
Outlier detection is a method to improve performances of machine learning models. In this paper, we use an outlier detection method to improve the performance of our proposed algorithm called decision boundary making (DBM). The primary objective of DBM algorithm is to induce compact and high performance machine learning models. To obtain this model, the DBM reconstructs the performance of support...
This paper proposes ANN based method for fingerprint ROI (Region of Interest) segmentation. Proposed ANNs where trained with 10000 samples extracted from 20 fingerprint images (in grey-scale and binary modes). The experimental results, including three statistical performance indicators, shows very good performance of the proposed method on a test database of 200 fingerprint images.
Providing security by means of using traditional methods such as PINs, Passwords, access cards are being vulnerable to various attacks and are easily hacked by intruders or unauthorized users. The aim is to develop an efficient personal identification system to provide secure access for legitimate users which is a challenging task. In order to avoid these problems, the use of biométrie traits reliably...
The differences between normal speech and whisper, particularly in terms of their acoustic characteristics, are serious problem of ASR (Automatic Speech Recognition) systems. This paper presents the preliminary results of the new way of speech signal pre-processing, which is based on inverse filtering. This method of signal pre-processing improves whisper recognition with ANNs (Artificial Neural Networks)...
This paper describes an implementation of speech recognition that recognizes and suppresses ten (10) defined profane and vulgar Filipino words. The adapted speech recognition architecture was that of the Oregon Graduate Institute's (OGI) Center for Spoken Language and Learning (CSLU). It utilizes a hybrid Hidden Markov Model/ Artificial Neural Network (HMM/ANN) keyword spotting framework. The feature...
This article explains the discrimination of wines through an electronic tongue, using machine learning algorithms and signal processing techniques: Principal Component Analysis (PCA) and Artificial Neural Networks (ANN), where the model of the multilayer perceptron was implemented. A database for wine quality was used and a study was conducted with a green wine of northeastern Portugal. The analysis...
Query response time prediction is an important and challenging problem in database systems. Especially for applications which handle large amounts of data or where time loss and deadlocks are hardly tolerated, it is very useful to predict the query response times before actual execution. This paper aims to predict query response times automatically using neural network-based approaches, and compares...
This paper presents a methodology for mid-term load forecasting using Artificial Neural Networks (ANN). The inputs to ANN are real time data available from Supervisory Control and Data Acquisition and Distribution Management Systems (SCADA/DMS) databases. Due to a number of reasons, historical data stored in SCADA/DMS databases is affected by distorted measurements that can jeopardize the load forecasting...
The Electrocardiogram (ECG) is undoubtedly the most used biological signal in the clinical world and it is a means for detection of several cardiac abnormalities. Pattern recognition, diagnostic classification of ECGs constitutes an interesting application of Artificial Neural Networks (ANNs). This paper illustrates the ability of a feed-forward back propagation using Neural Network for classify unknown...
Data mining has been used in several studies to uncover hidden information within dataset and to predict outcomes after application of algorithms. In this study, neural connection was adapted as data mining tool where supervised multilayer perceptron which is the architecture with back propagation learning algorithms was used on a new automobile data after application of clustering to remove outliers...
Offline handwritten text recognition requires several preprocessing stages. Many different preprocessing techniques have been proposed in the literature based either on geometrical heuristics or on statistical models. Unfortunately, these approaches usually fail when dealing with short sentences or isolated words. One statistical technique for text line preprocessing is based on the detection and...
The abnormalities of the kidney can be identified by ultrasound imaging. The kidney may have structural abnormalities like kidney swelling, change in its position and appearance. Kidney abnormality may also arise due to the formation of stones, cysts, cancerous cells, congenital anomalies, blockage of urine etc. For surgical operations it is very important to identify the exact and accurate location...
The typical inherent mismatch between the test and training corpora and by that between 'target' and 'source' sets usually leads to significant performance downgrades. To cope with this, this study presents a feature transfer learning method using Denoising Auto encoders (DAEs) to build high order subspaces of the source and target corpora, where features in the source domain are transferred to the...
Several research groups have developed automated sleep-wakefulness classifiers for night wrist actigraphic (ACT) data. These classifiers tend to be unbalanced, with a tendency to overestimate the detection of sleep, at the expense of poorer detection of wakefulness. The reason for this is that the measure of success in previous works was the maximization of the overall accuracy, disregarding the balance...
Rehabilitation robotic plays an important role in therapeutic exercises by combining robots with computer serious games into an attractive therapeutic platform. However, measuring the degree of engagement of the user is not a trivial task. The difficulty of applying question-based techniques, particularly for patients who have the speech capacity compromised due to cerebrovascular accidents, has inspired...
As the exponential growth of the Internet database, searching nearest neighbors in a high dimensional space using linear time algorithms has become impractical. In recent years, hashing based approximated nearest neighbor search has been studied intensively and successfully applied to many fields. The major challenge of hashing researches is to trade-off the similarity preservation with the code length...
Biometric recognition involves measuring unique physiological or behavioural traits of human being. Unimodal biometric system involves measuring single trait but it has several limitations like noisy data, lack of performance, spoofing, etc. To overcome the limitations of unimodal biometric system, this paper proposes a multimodal biometric system consisting of a combination of face, ear (physical...
The design of transmitarray antennas usually utilizes a database consisting of the complex transmission coefficient values of an element as a function of its controllable geometrical features. In the design process this database needs to be “inverted” so that transmission coefficients can be input and geometrical feature values output. When more than one such feature applies the latter process is...
Internet has opened new interesting scenarios in the fields of commerce and marketing. In particular, the idea of e-commerce has enabled customers to perform their transactions in a faster and cheaper way than conventional markets, and it has allowed companies to increase their sales volume thanks to a world-wide visibility. However, one of the problems that can strongly affect the performance of...
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