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The objective of this research is to propose the estimator of the population mean for incomplete data by using information of simple linear relationship model in the data set. In addition, the factorization of the likelihood function is created to derive the maximum likelihood estimator for the population mean. The simulation study was conducted for…

This paper presents an adaptive step-size and variable leaky least mean square algorithm based on nonlinear adaptive filter with the adaptive lookup table using spline interpolation. An adaptive step-size approach is proposed with the energy of squared previous and present errors to boost up the convergence rate. A modified variable leaky mechanism is proposed with…

Forecasting solar PV power output holds significant importance in the realm of energy management, particularly due to the intermittent nature of solar irradiation. Currently, most forecasting studies employ statistical methods. However, deep learning models have the potential for better forecasting. This study utilises Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU) and hybrid LSTM-GRU deep…

The Conv-TasNet and Demucs algorithms, can differentiate between two mixed signals, such as music and speech, the mixing operation proceed without any support information. The network of convolutional time-domain audio separations is used in Conv-TasNet algorithm, while there is a new waveform-to-waveform model in Demucs algorithm. The Demucs algorithm utilizes a procedure like the audio…

The intention of this research is to study and design an automated agriculture commodity price prediction system with novel machine learning techniques. Due to the increasing large amounts historical data of agricultural commodity prices and the need of performing accurate prediction of price fluctuations, the solution has largely shifted from statistical methods to machine learning…

Effective Fetal Electrocardiogram (FECG) Extraction provides medical workers with precise knowledge for monitoring fetal health condition during gestational age. However, Fetal ECG Extraction still remains a challenge as the signal is weak and contaminated with noises of different kinds, more significantly maternal ECG. In this work, a new Moth Flame optimization algorithm (MFO)-based adaptive filter…

Wireless sensor networks (WSNs) are having large demands in enormous applications for the decade. The main issue in WSNs is estimating the exact location of unknown nodes. All applications are dependent on the location information of unknown nodes in WSNs. Location information of mobile anchor node is used to estimate the location of unknown nodes.…

Android Operating system (OS) has been used much more than all other mobile phone’s OS turning android OS to a major point of attack. Android Application installation serves as a major avenue through which attacks can be perpetrated. Permissions must be first granted by the users seeking to install these third-party applications. Some permissions can…

Knowledge-based approach is wield used in various NLP applications. For example, to evaluate the semantic similarity between words, the semantic evidence in lexical ontologies (wordnets) is commonly used. The success of the English WordNet (EnWN) in this domain has inspired the creation of several wordnets in different languages, including the Arabic WordNet (ArWN). The English…

A real-time embedded system requires plenty of measurements to fallow the Nyquist criteria. The hardware built for such a large number of measurements, is facing the challenges like storage and transmission rate. Practically it is very much complex to build such costly hardware. Compressive Sensing (CS) will be a future alternate technique for the Nyquist…

Estimation of displacement is an information required for daily operation monitoring systems to monitor human health or to locate users in buildings, basements, tunnels and similar places which under the same conditions that the global positioning signal (GPS) level is from very weak to completely absent; and is the measurement technique by using multimetric data…

Over the last decades, numerous distributed consensus-based algorithms have found a wide application as a complementary mechanism for data aggregation in wireless sensor networks. In this paper, we provide an analysis of the generalized Metropolis-Hastings algorithm for data aggregation with a fully-distributed stopping criterion. The goal of the implemented stopping criterion is to effectively bound…

Education has seen the rapid development of online learning. Many researchers have conducted studies on the use of recommendation systems in online learning. However, until now, several similar studies still focus on the accuracy of the prediction results. Various obstacles were encountered related to changes in the face to face learning process into online learning.…

Estimation Solar radiation is the most significant part of the optimization of solar power. This may be achieved if the solar radiation is predicted well in advance. Meteorological stations have radiation measuring devices like pyranometer, pyrheliometer, radiometer, solarimeter, etc. however, it may not be available at the location of interest for researchers. Due to this…

Bull service is the natural copulation by a purebred male carabao with a female counterpart. This is part of the bull loan agenda of the Philippine Carabao Center-Visayas State University (PCC-VSU), one of the 12 regional centers of PCC. For the past years, PCC-VSU used averaging of bull services count of previous years and sometimes…

Synthetic aperture radar (SAR) is an imaging device mounted on a moving platform. Its ability to identify a weak target from a nearby strong one depends upon the peak side lobe ratio (PSLR). This paper is intended to ameliorate such important ratio through the use of windowing of the transmitted pulse and studying the noise…

An artificial neural network (ANN) computing system can be significantly influenced by its implementation type. The software implemented ANN can produce high accuracy output with slow computation time performance compared to hardware implemented ANN which runs at a faster computation time but with low accuracy. Normally, software implementation reduces the proficiency and efficiency of the…

The article proposes a Digital Predistortion (DPD) methodology that substantially meliorates the linearity of limited range Mobile Front Haul links for the extant Long-Term Evolution (LTE) and future (5G) networks. Specifically, the DPD is employed to Radio over Fiber links that contrive of Vertical Cavity Surface Emitting Lasers (VCSELs) working at 850 nm. Both, Memory…

In this work, a compact system for the automatic estimation of the tilt angle at any location of the world is presented. The system components are one computer, one GPS receiver and one Python program. The tilt angle is calculated through the maximization of the flux of direct radiation incident upon a flat solar collector.…

In the present study a computer model of a pumping well has been developed and calibrated by using two slave programs of Geo-Slope software, i.e. (SIGMA/W and SEEP/W). The model has been used to study the behaviour of watertable and drawdown in an aquifer during pumping. SIGMA/W program was used to compute initial pore-pressure within…

Forecasting the gold price movement’s volatility has essential applications in areas such as risk management, options pricing, and asset allocation. The multivariate model is expected to generate more accurate forecasts than univariate models in time series data like gold prices. Multivariate analysis is based on observation and analysis of more than one statistical variable at…

NOX and SO2 gas pollution have a direct impact on health problems and environmental damage. Therefore, to map the emission patterns and predict the resulting impacts, complete data and information on emissions of the two pollutants are needed. In Indonesia, data on NOX and SO2 emissions that are recorded over a long period of time…

Normalized Metered Energy Consumption (NMEC) is a solution for investors in determining the best energy-saving strategy for buildings. But on the other hand, investors need a fast and reliable evaluation results in measuring how effective the savings methods they use without wasting money. To address this issue, we selected Facebook’s latest predictive time series method…

This investigation deals with the identification of the suitable empirical models for predicting radio wave propagation path losses in Erbil city of Kurdistan region in Iraq. For this purpose, two sites of Korek Telecom operating at 1800 MHz and 2100 MHz have been selected at urban and sub-urban environments in the city and seven different…

Analytical researches on a potential performance of multipath multiple-input multiple-output (MIMO) systems inspire the development of new technologies that decompose a MIMO channel into independent sub-channels on the condition of constrained transmit power. Moreover, in current studies of inter-symbol interference (ISI) MIMO systems, there is an assumption that channel state information (CSI) at receivers and/or…