Microarrays are being used to express thousands of genes at a time which is helpful to diagnose and cure many diseases with higher accuracy using diagnostic classifiers. However, 90% of the time gene expression datasets contain multiple missing values because of slide scratches, hybridization error, image corruption and etc. These missing values affect classifiers accuracy as most of the classi...

Researchers in robotics and other human-related fields have been studying human motion behaviors to understand and mimic them in humanoid motion prediction, obstacle avoidance, and ergonomic studies. Human motion, however, is not an easy system or kinematic to study when it includes highly complex relationships between factor—such as human anthropometry and speed and the output motion profile f...

To improve overall fault detection and diagnostic (FDD) performance, many of the techniques proposed for automated FDD rely on the use of steady-state models for expected values of operating states under normal operating conditions. Furthermore, on-line measurements and models for overall performance (e.g., EER) are useful in evaluating whether faults are serious enough for service to be perfor...

In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately...

Time-varying delays adversely affect the performance of networked control systems (NCS) and in the worst-case can destabilize the entire system. Therefore, modelling network delays is important for designing NCS. However, modelling time-varying delays is challenging because of their dependence on multiple parameters such as length, contention, connected devices, protocol employed, and channel l...

AIM The aim of this study is to prove that facial surface electromyography (sEMG) conveys sufficient information to predict 3D lip shapes. High sEMG predictive accuracy implies we could train a neural control model for activation of biomechanical models by simultaneously recording sEMG signals and their associated motions. MATERIALS AND METHODS With a stereo camera set-up, we recorded 3D lip ...

Artificial Neural Networks (ANN), which are biologically inspired tools, serve as an alternative to regression analysis for complex data. Based on CP or proximate analysis (PA) of ingredients, two types of ANN and linear regression (LR) were evaluated for predicting amino acid levels in corn, wheat, soybean meal, meat and bone meal, and fish meal. The two ANN were a three layer Backpropagation ...

Dynamic modulus is a key evaluation index of the high-modulus asphalt mixture, but it relatively difficult to test and collect its data. The purpose achieve accurate prediction dynamic mixture further optimize design process mixture. Five high-temperature performance indexes were selected. correlation between above five was analyzed. On this basis, models based on small sample data established ...

The influence of various drying characteristics in the experiment was explored this study. time and moisture content were used to evaluate experimental outcomes. bitter gourd slices using a halogen dryer done at varied thicknesses (3, 5, 7 mm) temperatures (60 °C, 65 °C 70 °C). results revealed that equilibrium are considerably affected by material thickness temperature. Furthermore, Generalize...

Floods occur frequently worldwide. The timely, accurate mapping of the flooded areas is an important task. Therefore, unsupervised approach proposed for automated area from bi-temporal Sentinel-2 multispectral images in this paper. First, spatial–spectral features before and after flood are extracted to construct change magnitude image (CMI). Then, certain pixels non-flood obtained by performin...