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Sex estimation is used in forensic anthropology to assist the identification of individual remains. However, the estimation techniques tend to be unique and applicable only to a certain population. This paper analyzed sex estimation on living individual child below 19 years old based on length of 19 bones of left hand using hybrid Particle Swarm Optimization-Artificial Neural Network (PSO-ANN) technique...
The presented work studies an application of a technique known as a semismooth Newton (SSN) method to accelerate the convergence of distributed quadratic programming LASSO (DQP-LASSO) - a consensus-based distributed sparse linear regression algorithm. The DQP-LASSO algorithm exploits an alternating directions method of multipliers (ADMM) algorithm to reduce a global LASSO problem to a series of local...
Multilayer perceptron (MLP) based artificial neural network (ANN) equalizers, deploying back propagation (BP) training algorithm, have been profusely used for equalization earlier. However this algorithm suffers from slow convergence rate, depending on the size of network. In this paper, Levenberg-Marquardt and Scaled Conjugate algorithms are proposed to train an MLP based ANN for least square (LS)...
This paper presents a practical approach for voltage stability margin (VSM) monitoring in a pilot project, in which two related steps are considered. Through the planning stage of a practical project, it is necessary to make the grid observable to actualize the VSM monitoring during the operation. So, an observability based VSM monitoring scheme is proposed in this work. Firstly, using observability...
Accurate computation of software effort, cost and time required ahead would greatly reduce risk and maximize profit. Estimating software effort or computing the required function point helps project manager to better estimate the time and budget required for a project. Many statistical models were proposed in the past. These models suffer many problems related to parameter estimation and structure...
In this work, we propose to jointly perform Chinese word segmentation (CWS) and punctuation prediction (PU) in a unified framework using deep recurrent neural network (DRNN). We further perform a comparative study among the joint frameworks, the isolated prediction and the pipeline methods that link the two tasks sequentially, on a social media corpus. Our experimental results show that joint models...
We consider long-haul sensor networks where sensors are remotely deployed over a large geographical area to perform certain tasks, such as tracking and/or monitoring of one or more dynamic targets. A remote fusion center fuses the information provided by these sensors to improve the accuracy of the final estimates of certain target characteristics. In this work, we pursue artificial neural network...
An artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm has been developed. The proposed ANN based controller has the ability to estimate wind speed by tracking the maximum power point (MPP) and the optimal rotor speed with very low error compared to the conventional MPPT methods. The algorithm is based on two series neural networks, one for wind speed estimation and...
The most important function of a sensor network is to collect information from the environment. For many applications, it is important that the location or sensor that originates the collected information is ascertained. This article presents the detection of a mobile sensor's location in an indoor environment with the help of known location sensors (anchors) placed in the environment. Anchor sensors...
Previous studies on human-pose estimation rely on the design of factors to represent underlying probability distributions. However, designing factors is laborious and yet, the designed factors may not represent the underlying probability distributions. In this paper, we propose to use a neural network to automatically design factors in one of the existing models called the action-mixture model (AMM)...
We present a novel approach to automated estimation of agreement intensity levels from facial images. To this end, we employ the MAHNOB Mimicry database of subjects recorded during dyadic interactions, where the facial images are annotated in terms of agreement intensity levels using the Likert scale (strong disagreement, disagreement, neutral, agreement and strong agreement). Dynamic modelling of...
By employing state-of-the-art automated design and optimization techniques from the field of evolutionary computation, engineers are able to discover electrical machine designs that are highly competitive with respect to several objectives like efficiency, material costs, torque ripple and others. Apart from being Pareto-optimal, a good electrical machine design must also be quite robust, i.e., it...
For succeed the early warning system development programme for space activity plan at Tawau, Sabah Malaysia, we studied the variation of rainfall and precipitation over convective system activity. We use five variables data such as the surface meteorological data (Pressure, Temperature and Relative Humidity), rainfall data, and precipitation. The surface meteorological data are taken from weather...
In this study, a novel method for estimating wrist forces from surface electromyogram (EMG) measured from the upper limb is proposed, which can be applied for unilateral transradial amputees. Three degrees of freedom (DoFs) of wrist including flexion-extension, abduction-adduction, and pronation-supination were used. We first classify feature vectors extracted from the EMG signals into three classes...
This paper studies the problem of static sensor selection for ensuring K-diagnosability in bounded Petri nets. An integer linear programming problem is formulated to determine the minimal number of randomly selected sensors that make K-diagnosable net system with respect to a fault. This value is an estimate of the minimum number of sensors that assures the K-diagnosability of a given fault, which...
Two of the three most important causes of Information Technology projects failure have been related to a poor resource estimation. In average, software developers expend from 30% to 40% more effort than is estimated. Because that no single technique to estimate software development effort is best for all situations, it is important to propose new models to compare their results and then generate more...
The objective of this paper is to develop an easy, efficient and robust algorithm for the analysis of electrocardiogram signals. The technique used in this algorithm is based on the use of Moving Average Filters and Adaptive Thresholding for QRS complex detection. Several established ECG databases published on PhysioNet with sampling frequency ranging from 128Hz–1KHz, were used for analyzing the technique...
Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim...
One of the problem with complex machines is the sensor used to measure the outputs or the states of the machine. The sensors are prone to noise and add to design complexity. To overcome these problems, sensorless techniques are used as substitutes to common physical sensors. This paper presents sensorless estimation of position and velocity of a two wheeled inverted pendulum (TWIP) mobile robot, using...
In power electronic systems, capacitor is one of the reliability critical components. Recently, the condition monitoring of capacitors to estimate their health status have been attracted by the academic research. Industry applications require more reliable power electronics products with preventive maintenances. However, the existing capacitor condition monitoring methods suffer from either increased...
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