Evolving diverse ensembles using genetic programming has recently been proposed for classification problems with unbalanced data. Population diversity is crucial for evolving effective algorithms. Multilevel selection strategies that involve additional colonization and migration operations have shown better performance in some applications. Therefore, in this paper, we are interested in analysing the performance of evolving diverse ensembles using […]
Research Papers
Energy-efficient sensing method for table grapes cold chain management
Energy efficiency of the wireless sensor network (WSN) is one of the dominating issues in the non-stop table grapes cold chain monitoring. The aim of this paper is to propose an energy-efficient sensing method for the non-stop cold chain management of table grapes in order to reduce the average energy consumption of WSN devices and […]
Development and evaluation on a wireless multi-gas-sensors system for improving traceability and transparency of table grape cold chain
There is increasing requirement to improve traceability and transparency of table grapes cold chain. Key traceability indicators including temperature, humidity and gas microenvironments (e.g., CO2, O2, and SO2) based on table grape cold chain management need to be monitored and controlled. This paper presents a Wireless Multi-Gas-Sensors System (WGS2) as an effective real-time cold chain […]
A Fast Signal Denoising Algorithm Based on the LPA-ICI Method for Real-Time Applications
We propose a new algorithm for denoising of additive white Gaussian noise-corrupted signals, based on the intersection of confidence intervals (ICI) algorithm, called the fast intersection of confidence intervals (FICI) algorithm. The proposed approach combines the FICI algorithm, used for the adaptive filter support size selection, with the local polynomial approximation (LPA) method, used as […]
Semi-automated detection of anterior cruciate ligament injury from MRI
Background and objectives: A radiologist’s work in detecting various injuries or pathologies from radiological scans can be tiresome, time consuming and prone to errors. The field of computer-aided diagnosis aims to reduce these factors by introducing a level of automation in the process. In this paper, we deal with the problem of detecting the presence […]
Postharvest Quality Monitoring and Variance Analysis of Peach and Nectarine Cold Chain with Multi-Sensors Technology
Fresh peaches and nectarines are very popular for their high nutritional and therapeutic value. Unfortunately, they are prone to rapid deterioration after harvest, especially if the cold chain is not well maintained. The objective of this work is to study the environmental fluctuation and the quality change of fresh peaches and nectarines in cold chain. […]
Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its […]
Multilayer Network of Language: a Unified Framework for Structural Analysis of Linguistic Subsystems
Recently, the focus of complex networks’ research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena — multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is […]
MMP-9 triggered self-assembly of doxorubicin nanofiber depots halts tumor growth
A central challenge in cancer care is to ensure that therapeutic compounds reach their targets. One approach is to use enzyme-responsive biomaterials, which reconfigure in response to endogenous enzymes that are overexpressed in diseased tissues, as potential site-specific anti-tumoral therapies. Here we report peptide micelles that upon MMP-9 catalyzed hydrolysis reconfigure to form fibrillar nanostructures. […]
What makes classification trees comprehensible?
Classification trees are attractive for practical applications because of their comprehensibility. However, the literature on the parameters that influence their comprehensibility and usability is scarce. This paper systematically investigates how tree structure parameters (the number of leaves, branching factor, tree depth) and visualisation properties influence the tree comprehensibility. In addition, we analyse the influence of […]
