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An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…

Passive remote monitoring applications of underwater signal processing in a shallow water environment are an impactful area of research for environmental and marine-life monitoring. The majority of the sound source localization techniques require carefully placed synchronized hydrophone arrays, which can be complicated and hard to maintain. In this paper, we utilized the modal dispersions of…

The exponential growth in the number of automobiles over the past few decades has created a pressing need for a robust license plate identification system that can perform effectively under various conditions. In Morocco, as in other regions, local authorities, public organizations, and private companies require a reliable License Plate Recognition (LPR) system that takes…

The COVID-19 pandemic has caused a substantial death toll throughout the world. The pandemic has created a threat to public health, the economy, food systems, and the workplace. An increased reprioritization of health expenditure towards COVID-19 vaccines will impact on allocations to other medical facilities. In developing countries, hospitals shortage the infrastructure to facilitate patients.…

The detection and classification of fish is a prevalent and fascinating area of study. Numerous researchers develop skills in fish recognition in both aquatic and non-aquatic environments, which is beneficial for population control and the aquaculture industry, respectively. Rarely is research conducted to optimize the recognition of fish with diverse backgrounds. This paper proposes a…

This paper extends the idea of creating a Quantum Machine Learning classifier and applying it to real weather data from the weather station behind the Pa Sak Jonlasit Dam. A systematic study of classical features and optimizers with different iterations of parametrized circuits is presented. The study of the weather behind the dam is based…

People with visual impairment face daily struggle of navigating through unfamiliar places. This problem mainly caused by their lack of spatial awareness, i.e., the ability to estimate the distance between themselves and their surroundings. In order for visually impaired people to navigate independently, an effective navigation aid is required. The proposed navigation aid device utilizes…

Cyber security is based on different principles such as confidentiality and integrity of transmitted data. One of the main methods to send confidential messages is to use a shared secret to encrypt and decrypt them. Even if the amortized computational complexity of the hashing functions is Ο(1), there are several situations when it is not…

Determining the best candidates for a certain job rapidly has been one of the most interesting subjects for recruiters and companies due to high costs and times that takes the process. The accuracy of the models, particularly, is heavily influenced by the discriminant variables that are chosen for predicting the candidates scores. This study aims…

Traditional project planning in effort and duration estimation techniques remain low to medium accurate. This study seeks to develop a highly reliable and efficient hybrid Machine Learning model that can improve cost and duration prediction accuracy. This experiment compared the performance of five machine learning models across three different datasets and six performance indicators. Then…

Power losses exist naturally and have to be cared for in the operation of electrical power systems. Many researchers have worked on various methods and approaches to reduce losses by incorporating distributed generators (DG), particularly from renewable sources. These studies are based on the maximum unit penetration of the DGs, which is rarely achieved, resulting…

Subsurface Utility Engineering (SUE) is an international model for mapping and classifying underground surfaces according to their accuracy (acquisition method). Utilizing Geographic Information System (GIS) to map and present the SUE levels paved the way for producing a new Decision Support System (DSS) for the utility mapping process. The proposed system represents an efficient tool…

Sleep stage performs a vital role in people’s daily lives in the detection of sleep-related diseases. Conventional automated sleep stage classifier models are not efficient due to the complexity linked to the design of mathematical models and extraction of hand-engineering features. Further, quick oscillations amongst sleep stages frequently lead to indistinct feature extraction, which might…

To reduce the time necessary for determination of tsunami source parameters it is proposed to optimize the location of sensors system and to use only a part of the measured wave profile. Based on computation, it is possible to balance the number of sensors in use and the time period after the earthquake needed to…

This paper is an extension of the work originally presented in the 26th International Con- ference on Automation and Computing. This study regarding hardware prefetching aims at concealing cache misses, leading to maximizing the performance of modern processors. This paper leverages prefetch coverage improvement as a way to achieve the goal. Original work proposes two…

Many consequences can be resulted in mismanagement of crowd, which might get people injured or even lose their lives. Thus, crowd management helps in controlling overcrowded areas during events, and allowing authorities to monitor, manage and reduce incidents. Space science and technology have made huge leap in crowd management, let alone when this technology integrated…

Emotion is the most important component of being human, and very essential for everyday activities, such as the interaction between people, decision making, and learning. In order to adapt to the COVID-19 pandemic situation, most of the academic institutions relied on online video conferencing platforms to continue educational activities. Due to low bandwidth in many…

The rapid advancement of the Internet of Things (IoT) is distinguished by heterogeneous technologies that provide cutting-edge services across a range of application domains. However, by eavesdropping on encrypted WiFi network traflc, attackers can infer private information such as the types and working status of IoT devices in a business or residential home. Moreover, since…

The use of a battery to power an electrical or electronic system is accompanied by battery management, i.e. a set of measures intended to preserve it for preventative maintenance, thus the cost reduction. This management is generally based on two key parameters, the (remaining useful life) RUL and the (State-of-health) SOH, which relate respectively to…

Electroencephalography (EEG) is one of the most common and benign methods for analyzing and identifying abnormalities in the human brain. EEG is an incessant measure of the activities of the human brain. In contrast, when the measurement of EEG is bounded by time and the EEG is synchronized to an exterior stimulus, is known as…

Estimation of energy demand has important implications for economic and social stability leading to a more secure energy future. One-year-ahead energy demand estimation for Turkey has been proposed in this paper, using the metaheuristics method with GDP, the total population, and the quantities of imports and exports, as inputs variables. The records obtained from historical…

This article presents a roadmap for distribution grid µPMU hardware and software design consideration and implantation to ensure high performance within limited computational time of sampling frequency 512 samples/cycle. A proposed 12 channels, multi-voltage level µPMU hardware and rules of voltage and current transducer, analog filter, analog-to-digital converter, sampling rate definition, and PCB design and…

In this paper, we propose a highly accurate indoor position and direction estimation system using a simple fully connected deep neural network (DNN) model on Bluetooth Low Energy (BLE) Received Signal Strength Indicators (RSSIs). Since the system’s ultimate goal is to function as an indoor navigation system, the system estimates the indoor position simultaneously as…

A novel PVTL (Process, Voltage, Temperature, Leakage) detection circuit consisting of four individual detectors is proposed in the investigation. Voltage Variation Detector is composed of a feedback control block comprising multi-stage delay cells using high Vth devices such that 0.5% of VDD variation can be detected. Temperature Detector based on a current to pulse converter…

DNN implementation and deployment is quite a challenge within a resource constrained environment on real-time embedded platforms. To attain the goal of DNN tailor made architecture deployment on a real-time embedded platform with limited hardware resources (low computational and memory resources) in comparison to a CPU or GPU based system, High Performance SqueezeNext (HPS) architecture…