For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sens...
Genomic selection (GS) is revolutionizing plant breeding. However, its practical implementation is still challenging, since there are many factors that affect its accuracy. For this reason, this research explores data augmentation with the goal of im...
Due to the limited memory and computing resources in the real application of target detection, the method is challenging to implement on mobile and embedded devices. In order to achieve the balance between detection accuracy and speed in pedestrian-i...
Space-to-ground laser communication (SGLC) offers a paradigm-shifting solution to overcome the bandwidth constraints of radio frequency systems by leveraging laser beams for ultra-high data throughput, although its link availability probability is si...
In recent years, much research has focused on using machine learning (ML) for disease prediction based on gene expression (GE) data. However, many diseases have received considerable attention, whereas some, including Alzheimer’s disease (AD),...
The power consumption data in buildings can be viewed as a time series, where outliers indicate unreasonable energy usage patterns. Accurately detecting these outliers and improving energy management methods based on the findings can lead to energy s...
The main objective of this paper is to compensate power factor using teaching learning based optimization (TLBO), determine the capacitor bank optimization (CBO) algorithm, and monitor a system in real-time using cloud data logging (CDL). Implemented...
The airborne transient electromagnetic (TEM) method is widely used in land applications but faces challenges in marine applications due to the strong masking effects of seawater. The accuracy of the inverse Laplace transform algorithm strongly affect...
The thermal response of a magnetic solid to an applied magnetic field constitutes magnetocaloric effect. The maximum magnetic entropy change (MMEC) is one of the quantitative parameters characterizing this effect, while the magnetic solids exhibiting...
Glaucoma is a common eye disease that damages the optic nerve and leads to loss of vision. The disease shows few symptoms in the early stages, making its identification a complex task. To overcome the challenges associated with this task, this study...
During the contribution of a metaheuristic algorithm for solving complex problems, one of the major challenges is to obtain the one that provides a well-balanced exploration and exploitation. Among the possible solutions to overcome this issue is to...
Plant nitrogen concentration (PNC) is a key indicator reflecting the growth and development status of plants. The timely and accurate monitoring of plant PNC is of great significance for the refined management of crop nutrition in the field. The rapi...
We propose in this paper a two-phase approach that decomposes the process of solving the three-dimensional single Container Loading Problem (CLP) into subsequent tasks: (i) the generation of blocks of boxes and (ii) the loading of blocks into the con...
Unmanned traffic signal control is regarded as a sustainable intelligent management methodology. However, it faces the challenge of unpredictable traffic flow due to stochastic arrivals. The digital twin (DT) has emerged as a promising approach to ad...
Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on p...
High penetration of renewable energy sources into isolated microgrids (µGs) is considered a critical challenge, as µGs’ operation at low inertia results in frequency stability problems. To solve this challenge, virtual inertia contr...
In object-based image analysis (OBIA), the appropriate parametrization of segmentation algorithms is crucial for obtaining satisfactory image classification results. One of the ways this can be done is by unsupervised segmentation parameter optimizat...
Major depressive disorder (MDD) is a mental illness with high incidence and complex etiology, that poses a serious threat to human health and increases the socioeconomic burden. Currently, high-accuracy biomarkers for MDD diagnosis are urgently neede...
With the global spread of the novel coronavirus, avoiding human-to-human contact has become an effective way to cut off the spread of the virus. Therefore, contactless gesture recognition becomes an effective means to reduce the risk of contact infec...
Wireless networks beyond 5G will mostly be serving myriads of sensors and other machine-type communications (MTC), with each device having different requirements in respect to latency, error rate, energy consumption, spectral efficiency or other spec...
The extensive use of genomic selection (GS) in livestock and crops has led to a series of genomic-prediction (GP) algorithms despite the lack of a single algorithm that can suit all the species and traits. A systematic evaluation of available GP algo...
Accurate multivariate load forecasting plays an important role in the planning management and safe operation of integrated energy systems. In order to simultaneously reduce the prediction bias and variance, a hybrid ensemble learning method for load...
Digital holography (DH) is a novel, real-time, non-destructive, and quantitative phase-contrast imaging method that is particularly suitable for label-free live biological cell imaging and real-time dynamic monitoring. It is currently a research hots...
Various gait parameters can be used to assess the risk of falling in older adults. However, the state-of-the-art systems used to quantify gait parameters often come with high costs as well as training and space requirements. Gait analysis systems, wh...
1 January 2023
Hospital-Acquired Pressure Injury (HAPI), known as bedsore or decubitus ulcer, is one of the most common health conditions in the United States. Machine learning has been used to predict HAPI. This is insufficient information for the clinical team be...
At the core of every system for the efficient control of the network steady-state operation is the AC-power-flow problem solver. For local distribution networks to continue to operate effectively, it is necessary to use the most powerful and numerica...
In order to solve the problem of interference and spectrum optimization caused by D2D (device-to-device) communication multiplexing uplink channel of heterogeneous cellular networks, the allocation algorithm based on the many-to-one Gale-Shapley (M21...
This paper presents a 20 GS/s four-channel time-interleaved sample-and-hold amplifier (SHA), which aims to improve the harmonic distortion performance, eliminate the common-mode voltage fall in track-to-hold transition, and solve the difficulty of ti...
Background: To compare the clinical performance of a new PCa serum biomarker based on fPSA glycoprofiling to fPSA% and PHI. Methods: Serum samples from men who underwent prostate biopsy due to increased PSA were used. A comparison between two equal g...
This paper presents a 12-bit 2.4 GS/s analog-to-digital converter (ADC) employing four time-interleaved (TI) pipelined channels with a novel on-chip timing mismatch calibration in 40 nm CMOS process. TI architecture can increase the effective samplin...
The Cutting Stock Problem (CSP) is an optimization challenge that involves dividing large objects into smaller components while considering various managerial objectives. The problem’s complexity can differ based on factors such as object dimen...
Sparse Bayesian learning-based space–time adaptive processing (SBL-STAP) algorithms can achieve superior clutter suppression performance with limited training sample support in practical heterogeneous and non-stationary clutter environments. Ho...
In recent years, the socio-economic development in the Tibet region of China has experienced substantial growth. However, transportation increasingly strains the region’s fragile ecological environment. Most studies overlook the accurate measur...
In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization i...
Gastric adenocarcinoma (GA) is a significant global health issue with poor prognosis, despite advancements in treatment. Although molecular classifications, such as The Cancer Genome Atlas (TCGA), provide valuable insights, their clinical utility rem...
A proton exchange membrane electrolyzer can effectively utilize the electricity generated by intermittent solar power. Different methods of generating electricity may have different efficiencies and hydrogen production rates. Two coupled systems, nam...
This paper presents a 2-GS/s voltage–time hybrid pipelined analog-to-digital converter (ADC) with a 14-bit digital output, implemented in a 28-nm CMOS process. To alleviate the gain–bandwidth–power trade-off in deeply scaled technol...
The impact of convection and radiation on the thermal distribution of the wavy porous fin is examined in the present study. A hybrid model that combines the differential evolution (DE) algorithm with an artificial neural network (ANN) is proposed for...
This study introduces an Enhanced Local Search (ELS) technique integrated into the Bee Colony Optimization (BCO) algorithm to address the Economic Dispatch (ED) problem characterized by a continuous cost function. This paper combines Lambda Iteration...
When dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. Multi-objective optimization a...
As unmanned aerial vehicles (UAVs) are widely used in various fields, there is an increasing demand for UAV anti-jamming, multipath mitigation, and covert secrecy. Frequency-hopping binary offset carrier (FH-BOC) signals possess higher anti-jamming a...
The flutter phenomenon is a potentially destructive aeroelastic vibration studied for the design of aircraft structures as it limits the flight envelope of the aircraft. The aim of this work is to propose a heuristic design of a piezoelectric actuato...
Aiming at the problems of target detection models in traffic scenarios including a large number of parameters, heavy computational burden, and high application cost, this paper introduces an enhanced lightweight real-time detection algorithm, which e...
Nanosatellites in Low Earth Orbit (LEO) are an attractive platform for commercial and scientific missions, but their downlink capacity is constrained by bandwidth and by low ground station duty cycles (often under 5%). These limitations are particula...
Manual forestland classification methods, which rely on predetermined scoring criteria and subjective interpretation, are commonly used but suffer from limitations such as high labor costs, complexity, and lack of scalability. This study proposes an...
Compared to using images in the visible and near-infrared (VNIR) wavelength range only, remotely sensed satellite imagery from the spectral wavelengths of both VNIR and shortwave infrared (SWIR), such as Sentinel-2A and Worldview-3, is more effective...
The objectives of this study were to assess the accuracy and precision of a system combining an IMU-instrumented sock and a validated algorithm for the estimation of the spatio-temporal parameters of gait. A total of 25 healthy participants (HP) and...
Radiomics has the potential to aid prostate cancer (PC) diagnoses and prediction by analyzing and modeling quantitative features extracted from clinical imaging. However, its reliability has been a concern, possibly due to its high-dimensional nature...
Wind speed (WS) is an important factor in wind power generation. Because of this, drastic changes in the WS make it challenging to analyze accurately. Therefore, this study proposed a novel framework based on the stacking ensemble machine learning (S...
A novel multi-class classification method for bacteria detection termed quantum-behaved particle swarm optimization-based kernel extreme learning machine (QPSO-KELM) based on an electronic nose (E-nose) technology is proposed in this paper. Time and...
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