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106 articles for “mean square error”
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Automated Thyroid Nodule Detection in Ultrasound Image using Optimal Neural Network Classifier
Abstract: Malignant thyroid nodule detection is an important issue in thyroid ultrasonography image processing. Literature reports many algorithms in this domain. This research aims to design optimal decision support system (DSS) for ultrasound thyroid nodule image characterization into benign and malignant classes. Thyroid nodule region is segmented to extract texture features from thyroid nodule ultrasound images acquired from 38 patients using gray level co-occurrence matrix (GLCM) and statistical properties. These features …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 2, 2015 · pp. 15–25 Read article
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A Novel Approach of Medical Image Fusion using Wavelet Transforms
Abstract: Image processing applications have been growing rapidly in real world. The term fusion means an approach to extract the useful information from several modalities. Image fusion (IF) is used to integrate the complementary information obtained from multisensor, multiview and/or multitemporal and get an image of more information and the quality of which cannot be achieved from any individual image. Different fusion algorithms are useful in many applications like medical diagnosis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 18–25 Read article
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Financial Forecast: Systematic Analysis Using Principal Component Analysis
Abstract: The most popular technique for data exploration and analysis across all scientific disciplines that can influence the classification model's accuracy is principal component analysis (PCA). In this study, the high dimensionality of the stock market is examined in order to forecast market movements using PCA in conjunction with linear regression. While reducing data redundancy, PCA can aid in enhancing the predictive performance of machine learning techniques. The New York Stock …
Published in E-Commerce for Future & Trends · Vol. 9, Issue 2, 2022 · pp. 18–24 Read article
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Simulation of Image Processing and Restoration Through A Base Image Using Matlab
Abstract: Basically, in image processing the main work is done on pixels and its value. Basically, an image is a two-dimensional function f(x, y), where x and y are spatial coordinates. Here, in the present study geometrical transformation is being used for image restoration and processing. Steps are carried some for the result outcome. First the image is read in the algorithm, further the coordinates and pixels are being specified, and …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 8, Issue 1, 2021 · pp. 31–40 Read article
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Hybrid Feature Selection Approach for Stability Prediction for Intracerebral Hemorrhage Patients
Abstract: Intra Cerebral Hemorrhage (ICH) stability estimation is useful for enhancing diagnosis accuracy, selecting the best course of treatment, and clinically evaluating variations with healthy individuals. Due to their low predictive value, the clinical application of several ICH progression scoring systems is constrained. The dataset includes clinical parameters including age, Glasgow Coma Scale (GCS), and CT Angiography (CTA) spot that have been retrieved using geometric features from the segmented bleeding volume …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 9–17 Read article
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Energy and Exergy Analysis of Ammonia Water Operated Vapour Absorption Refrigeration System Using Artificial Neural Network Approach
Abstract: In this study, energy and exergy analysis have been performed of the ammonia-water operated vapour absorption refrigeration (VAR) system. Authors have trained artificial neural network (ANN) for predicting thermodynamic properties (specific enthalpy and specific entropy) of working fluid (ammonia-water). Authors have achieved coefficient of multiple determination (R2) value 0.9999 and the root mean square error (RMSE) value 0.00211 for input data set of saturated liquid and R2 value 0.999999 and …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 2, Issue 1, 2015 · pp. 7–20 Read article
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Comparative Analysis of FIR Digital Filters for Noise Reduction in EMG Signal
Abstract: In the performance of electromyogram (EMG) signal, signal acquisition must be noise free. This paper deals with the application of digital finite impulse response (FIR) filter on the raw EMG signal. In this paper different window techniques are used to design FIR filter and after designing the filters their values are used to calculate signal-to-noise ratio (SNR), power spectral density (PSD), and standard deviation. The results of SNR, PSD and …
Published in Recent Trends in Electronics Communication Systems · Vol. 3, Issue 1, 2016 · pp. 56–60 Read article
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Interference Effect Analysis of Pilot Contaminated Massive MIMO Downlink with Different Pre-coders and Channel Estimation
Abstract: A new idea in cellular MU-MIMO is the use of large numbers of BS antennas to serve several single-antenna terminals simultaneously. In multi-cell environments, adjacent cells using the same spectrum cause a pilot contamination problem and degrade signal quality. This pilot overhead can be reduced by reusing pilot sequences in nearby cells; however, this potentially introduces interference in the channel estimation phase, the so-called "pilot contamination" effect. The achievable rate …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 4, Issue 2, 2017 · pp. 1–9 Read article
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Extraction of High Resolution DEM from Cartosat-1 Stereo Imagery using Rational Math Model and Its Accuracy Assessment for a Part of Snow Covered NW-Himalaya
Abstract: This paper reports the experiments carried out for extraction of DEMs from Cartosat-1 stereo imagery using stereo correlation technique for Manali region. The focus of this paper was to assess the accuracy of extracted DEM with respect to DGPS observations, DEM generated from digitized contours of Survey of India (SoI), 1:50,000 scale topographic map(converted to ellipsoidal height using egm2008 geoid model) as well as well-known freely available DEMs ASTER GDEM …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 23–34 Read article
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Mathematical Modelling of Thin-layer Drying Process of Bamboo (Bambusa bambos) Shoots at Varying Temperature
Abstract: AbstractThe present study was carried out for understanding the drying mechanism in bamboo shoots and thereby helpful for selection and designing of appropriate drying system. Thin-layer drying characteristics of bamboo shoot slices were determined experimentally as a function of temperature using a laboratory tray dryer. Six mathematical models (Henderson and Pabis, Logarithms, Newton, Page, Two term, Wang and Sing) for describing the thin-layer drying behaviour of bamboo shoot slices were …
Published in Research & Reviews : Journal of Botany · Vol. 3, Issue 1, 2014 · pp. 1–9 Read article
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The Milklipidometric Model: A Mathematical Equation-based on Electric Conductivity to Predict Butterfat Concentrations in Bovine Milk
Abstract: The milklipidometric model is a mathematical equation to predict butterfat in raw milk and it is based on electric conductivity principle. The model differs from the existing equations in that it uses variables (electric conductivity, and volume fraction of whole milk ) which can be easily measured and it predicts fat at wide temperature, range of 5–60°C. Accurate results can be obtained even using commercial electrical conductivity meters, hence making …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 8, Issue 1, 2019 · pp. 10–21 Read article
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The Study of Temporal Variations in Ionosonde foF2 and GPS TEC at Multan and Islamabad during Low and High Solar Activity in Solar Cycle 24
Abstract: The study of temporal variations in critical frequency of the F2 layer (foF2) and total electron content (TEC) calculated from satellites of GPS (Global Positioning System) has been conducted at Multan (Geog. Lat: 30.16°N, long: 71.53°E) and Islamabad (33.66°N, 73.23°E) during low solar activity (LSA) year 2009 and relatively high solar activity (HSA) year 2012 of solar cycle (SC) 24. In general, it has been observed that the diurnal variations …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 2, 2018 · pp. 8–17 Read article
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Modelling of Flood in Lagos using Artificial Neural Network
Abstract: Flooding events have caused havoc to live and properties in recent times. Flooding could be caused by several factors some of which are rainfall, temperature, and relative humidity, which lead to rise in water level. The method of artificial neural networks (ANN) was used in this work to model flood occurrence in Lagos, Nigeria. Meteorological data were collected from the Nigeria Meteorological Agency (NIMET) and Nigeria Hydrological survey Agency (NHSA) …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 7, Issue 2, 2018 · pp. 50–57 Read article
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Marshall-Olkin Exponential Power Distribution and Applications
Abstract: We introduce a new distribution namely Marshall-Olkin Exponential Power Distribution and its properties were studied. The problem of estimation of parameters was considered and validated with respect to a real data on failure times. The stress-strength reliability analysis was also carried out. Average mean square error, Average confidence length, Coverage probability etc. were computed using simulated data. Using the proposed model we developed autoregressive processes with minification structure. Keywords: Marshall-Olkin …
Published in Research & Reviews : Journal of Statistics · Vol. 6, Issue 3, 2017 · pp. 22–33 Read article
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Geospatial Depiction of Groundwater Level Disparities on a Temporal Component over Portions of Cuddapah District, India Using Contemporary Geo Tools and Interrelated Statistics
Abstract: This paper mainly focuses on comparing methods such as Deterministic methods, Geostatistical methods and Interpolation methods in order to obtain a good fit to represent groundwater level disparities existed in the study area from 1996 to 2015. Inverse Distance Weighting, Global Polynomial Interpolation, Radial Basis Functions, Local Polynomial Interpolation, Kriging, Empirical Bayesian Kriging, Kernel smoothing and Diffusion Kernel were the methods tested for the present study. The data set procured …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 2, 2017 · pp. 13–29 Read article
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Estimation of Reliability for a Two Parameter Inverse Chen Distribution
Abstract: The problem of estimation of reliability, when and are two independent random variables follow inverse Chen distribution, is considered in the paper. Maximum likelihood estimators of under simple random sampling and ranked set sampling are obtained. Also, Bayesian estimation using Lindley's approximation technique is proposed to draw inference about . Reliability estimators are compared using mean squared error criteria and real data analysis is carried out for illustration purpose. Keywords: …
Published in Research & Reviews : Journal of Statistics · Vol. 8, Issue 1, 2019 · pp. 17–25 Read article
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An Application of Artificial Neural Networks for Air Quality Prediction of SO2 Concentrations in Calabar Metropolis
Abstract: The past few years have seen intense enhancements in our aptitude to simulate complicated physical systems using computers, which has led to the use of artificial neural networks (ANNs) in various capacities of scientific research. The artificial neural network has been applied to various ecological pollution complications and which has revealed some degree of precision. The study aims to advance a neural network air quality forecast model for the complex …
Published in Research & Reviews : Journal of Physics · Vol. 9, Issue 3, 2020 · pp. 8–11 Read article
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Short-Term Load Demand Forecasting using Chaos Theory and ANFIS
Abstract: In the electrical power sector, forecasting of load demand is an important process for effective planning of future expansion and periodical operations including unit commitments, fuel scheduling, short-term maintenance, security assessments, reducing spinning reserve, reliability analysis etc. Accurate load predictions are also necessary to utilize the electrical energy efficiently and to minimize the conflicts between the demand and supply of electricity. As electric load pattern of a region is very …
Published in Trends in Electrical Engineering · Vol. 6, Issue 2, 2016 · pp. 50–57 Read article
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Development and Implementation of Indoor Location-based Service in Museums Based on Bluetooth Low Energy Standard and Triangulation Algorithm
Abstract: Location-based services (LBS) in indoor locations are for providing information needed by users, and this information can be provided to users based on a Geofence. The most important component of location-based service systems is the Global Positioning System (GPS), which does not have the ability to determine the location in an indoor location. In this research, LBS Android software was developed for museums with the possibility of providing multimedia information …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article