We propose a DIDE-FPP composite algorithm to improve the spatial location accuracy of tunnel fires based on the distributed individuals differential evolution (DIDE) algorithm and the four-point positioning (FPP) method. Using the DIDE algorithm to s...
This work develops a new current-mode mixed signal Complementary Metal-Oxide-Semiconductor (CMOS) imager, which can capture images and simultaneously produce vehicle lane maps. The adopted lane detection algorithm, which was modified to be compatible...
Serial crystallography (SX) is a cutting-edge technique in structural biology, involving the systematic collection of X-ray diffraction data from numerous randomly oriented microcrystals. To extract comprehensive three-dimensional information about t...
In the era of big data, unsupervised learning algorithms such as clustering are particularly prominent. In recent years, there have been significant advancements in clustering algorithm research. The Clustering by Density Peaks algorithm is known as...
To solve the problem of low demodulation accuracy of conventional peak-to-peak algorithm for fiber-optic Fabry-Perot (FP) sensors due to failure of determining the interference order, a novel cavity length sequence matching demodulation algorithm bas...
R peak detection is crucial in electrocardiogram (ECG) signal analysis to detect and diagnose cardiovascular diseases (CVDs). Herein, the dynamic mode selected energy (DMSE) and adaptive window sizing (AWS) algorithm are proposed for detecting R peak...
Wireless accelerometers with various operating ranges have been used to measure tibial acceleration. Accelerometers with a low operating range output distorted signals and have been found to result in inaccurate measurements of peaks. A restoration a...
Recently, a signal sorting algorithm based on the congruence transform has been proposed, which is effective in dealing with the staggered Pulse Repetition Interval (PRI) signals. It can effectively sort the staggered PRI signals and obtain the sub-P...
DNA G-quadruplexes (G4) are non-canonical DNA structures that play key roles in various biological processes. Antibody-dependent sequencing is an important tool for identifying intracellularly formed DNA G4s, and peak calling is a crucial step in pro...
As a relatively novel density-based clustering algorithm, Density peak clustering (DPC) has been widely studied in recent years. DPC sorts all points in descending order of local density and finds neighbors for each point in turn to assign all points...
Doppler peaks extraction from massive raw data is a tricky part of coherent Doppler wind Lidar (CDWL) optimization. In this paper, a hybrid genetic/Powell algorithm (HGAP) is proposed to process the power spectrum of the measured signal from CDWL. Th...
The gravitational search algorithm is a global optimization algorithm that has the advantages of a swarm intelligence algorithm. Compared with traditional algorithms, the performance in terms of global search and convergence is relatively good, but t...
Accurate and precise measurement of the relative protein content of blood-based samples using mass spectrometry is challenging due to the large number of circulating proteins and the dynamic range of their abundances. Traditional spectral processing...
The outbreak of COVID-19 has caught humanity off guard. Peak-times differ in countries based on their characteristics and precautions taken by governments. In this study, we aimed to determine relative importance of indicators on the spread and to as...
This paper presents an algorithm for the measurement of the human heart rate, using photoplethysmography (PPG), i.e., the detection of the light at the skin surface. The signal from the PPG sensor is processed in time-domain; the peaks in the preproc...
Based on the generalized cross-correlation method (GCC), the period peaks in the cross-correlation function (CCF) of frequency shift keying (FSK) signals will degrade the estimation performance of time difference of arrival (TDOA), as well as the est...
This paper presents optimization of peak temperatures achieved during friction stir welding (FSW) of Al-6061-T6 alloys. This research work employed a novel approach by investigating the effect of FSW welding process parameters on peak temperatures th...
Due to the rapid advancement in the use of photovoltaic (PV) energy systems, it has become critical to look for ways to improve the energy generated by them. The extracted power from the PV modules is proportional to the output voltage. The relations...
Genetic Algorithms (GA) are a powerful set of tools for search and optimization that mimic the process of natural selection, and have been used successfully in a wide variety of problems, including evolving neural networks to solve cognitive tasks. D...
Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load f...
Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were no...
Photovoltaic (PV) systems-based energy generation is relatively easy to install, even at a large scale, because it is scalable in size and is thus easy to transport. Harnessing maximum power is only possible if maximum power tracking (MPPT) functiona...
To address the problem of expensive computation in traditional two-dimensional (2D) direction of arrival (DOA) estimation, in this paper, we propose a 2D DOA estimation method based on a reduced dimension and root-finding MUSIC algorithm for nested p...
Density peak clustering is the latest classic density-based clustering algorithm, which can directly find the cluster center without iteration. The algorithm needs to determine a unique parameter, so the selection of parameters is particularly import...
Photovoltaic (PV) systems have been used extensively worldwide over the past few years due to the mitigation of fossils fuels; it is the best source because of its eco-friendly nature. In PV systems, the main research area concerns its performance un...
Screen photos often suffer from moiré patterns, which significantly affect their visual quality. Although many deep learning-based methods for removing moiré patterns have been proposed, they fail to recover images with complex textures...
This research proposes the dandelion optimizer (DO), a bioinspired stochastic optimization technique, as a solution for achieving maximum power point tracking (MPPT) in photovoltaic (PV) arrays under partial shading (PS) conditions. In such scenarios...
In the context of multi-array multi-target bearing-only localization, due to the existence of direction-finding errors, the crossing results of bearing lines cannot accurately determine correspondence with targets. Under conditions that clutter inter...
The development of a sensor that can measure balance during quiet standing and predict stepping response in the event of perturbation has many clinically relevant applica- tions, including closed-loop control of a neuroprothesis for standing. This st...
This study presents a new imaging-based algorithm for simultaneously determining multiple velocity fields from stratified crossflows optically captured in a single field of view. The concept implements an additional automatic peak finding scheme into...
In current traffic congestion scenarios, electric vehicles (EVs) have the problem of reduced battery life and continuous decline in endurance. Therefore, this study proposes an optimization method for electric vehicle charging scheduling based onthe...
Besides many benefits deriving from the energy transition process, it is not uncommon for modern power systems to be faced with difficulties in their operation. The issues are dominantly related to the non-dispatchable nature of renewable energy sour...
Detecting R-peak location is very important in electrocardiogram (ECG) analysis. Most existing algorithms focus on separating extreme data points to find R-peaks without ECG wave morphology consideration. As a result, we propose a new algorithm using...
The retrieval of sun-induced chlorophyll fluorescence is greatly beneficial to studies of marine phytoplankton biomass, physiology, and composition, and is required for user applications and services. Customarily phytoplankton chlorophyll fluorescenc...
Advances in technology and population growth are two factors responsible for increasing electricity consumption, which directly increases the production of electrical energy. Additionally, due to environmental, technical and economic constraints, it...
In the estimation of the direction of arrival (DOA) for interference signals, the direction-finding error of the multiple signal classification (MUSIC) algorithm will increase in the case of multiple interferences or when the interfering signal power...
This paper presents a model predictive approach to the energy-aware control of tasks’ execution in an assembly line. The proposed algorithm takes into account both the need for optimizing the assembly line operations (in terms of the minimizati...
The USEPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) is one of the most extensively implemented numerical models for simulating urban runoff. Parameter optimization is essential for reliable SWMM model simulat...
Nowadays, the demand for communication multi-carriers’ channels, where the sub-channels are made mutually independent by using orthogonal frequency division multiplexing (OFDM), is widespread both for wireless and wired communication systems. E...
This paper proposes a novel sparse array design and an efficient algorithm for two-dimensional direction-of-arrival (2D-DOA) estimation. By analyzing the hole distribution in coprime arrays and introducing supplementary elements, we design a Compleme...
Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the acc...
The ability to predict the size of information cascades in online social networks is crucial for various applications, including decision-making and viral marketing. However, traditional methods either rely on complicated time-varying features that a...
Dengue virus (DENV) is the world’s most common arboviral infection, with an estimated 3.9 million people at risk of the infection, 100 million symptomatic cases and 10,000 deaths per year. Current diagnosis for DENV includes the use of molecula...
Smart grid technology has given users the ability to regulate their home energy use more efficiently and effectively. Home Energy Management (HEM) is a difficult undertaking in this regard, as it necessitates the optimal scheduling of smart appliance...
Understanding the balance between robustness and evolvability is crucial in evolutionary dynamics. This study aims to determine how varying mutation rates and valley depths affect this interplay during adaptation. Using a two-peak fitness landscape m...
The basic work of power data research is anomaly detection. It is necessary to find a method suitable for processing current power system data. Research proposes an algorithm of fast density peak clustering with Local Outlier Factor (LOF). The algori...
We propose a new peak searching algorithm (PSA) that uses Bayesian optimization to find probability peaks in a dataset, thereby increasing the speed and accuracy of clustering algorithms. Wireless sensor networks (WSNs) are becoming increasingly comm...
The accurate determination of chlorophyll a (Chl a) is often limited by the instability of conventional fluorescence height algorithms in algal bloom waters characterized by diverse phytoplankton morphology and red-shifted reflectance peaks. In this...
Implementing real-time prediction and warning systems is an effective approach for mitigating flash flood disasters. However, there is still a challenge in improving the accuracy and reliability of flood prediction models. This study develops a hydro...
The clustering algorithm plays an important role in data mining and image processing. The breakthrough of algorithm precision and method directly affects the direction and progress of the following research. At present, types of clustering algorithms...
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