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To automatically design improvements of stochastic numerical optimization algorithms is challenging due to the high computation time required to ensure sufficiently rigorous evaluation of synthesized programs. In this paper, we develop evaluation methodology that is used with the evolutionary automatic programming system ADATE to enhance two variants of the differential evolution algorithm, namely,...
Code bloat is a phenomenon in Genetic Programming (GP) that increases the size of individuals during the evolutionary process. Over the years, there has been a large number of research that attempted to address this problem. In this paper, we propose a new method to control code bloat and reduce the complexity of the solutions in GP. The proposed method is called Substituting a subtree with an Approximate...
A support system sports training is considered as a socio-economic system, describes its main components, functions, and approaches to create. Described the international experience of creation and functioning of organisation of a system of support athletic training, based on different principles. Characterized the state of the sport industries and the characteristics the system of support athletic...
In this paper we present a skeleton-free Kinect system to estimate body mass index (BMI) of human bodies. Unlike other systems in the literature, the proposed system does not require a scale to measure the weight. The weight of observed subjects are estimated using body surface area (BSA) regression. The proposed system employs the state-of-the-art deep residual network to extract meaningful features...
In today's increasingly tech-based economy, many high-salary jobs are created in the STEM fields. These jobs often are either in or related to engineering, and thus establishing an educational engineering pipeline is critical to supply this demand. In Maine, no state-wide assessment data of engineering literacy in K-12 schools is available. Information is needed to assess if the current quantity and...
This work presents improvements to a neuroevolution algorithm called Evolutionary eXploration of Augmenting Convolutional Topologies (EXACT), which is capable of evolving the structure of convolutional neural networks (CNNs). While EXACT has multithreaded and parallel implementations, it has also been implemented as part of a volunteer computing project at the Citizen Science Grid to provide truly...
The paper introduces a proposal for an automated magnetic resonance (MR) image segmentation called Case-Based Genetic Algorithm Location-Dependent Image Classification (CBGA-LDIC) and presents its evaluation results. This method finds an appropriate cell set towards efficient image segmentation. It uses location-dependent image classification (LDIC), which is integrated by genetic algorithm (GA) combined...
Advances in highly multi-parametric measurements by mass cytometry have made possible the accurate detection of acute myeloid leukemia (AML) cells in complex cell populations. However, current informatics methods bottlenecks data processing by being labor-intensive, time-consuming, and prone to user bias. To address these problems, major efforts have been made to automate the detection of AML cells...
We discuss several ways to accelerate genetic algorithm-based instance selection, where the two objectives are a minimal number of training instances and maximal accuracy of the classifier (we use neural networks) on the test data. We discuss several ways to accelerate the process, but we especially focus on two parameters: fitness function and chromosome length reduction. We evaluate different fitness...
This paper presents an effective internship program to optimize learners' skills at technical high schools in South Africa. This is based on combined training programs by compiled by Resolution Circle; presented to the Gauteng Department of Education (GDE) and to the graduate interns. Recommendations are made with respect to when effectively optimized, the use of these graduate interns in technical...
In this paper, Self-adaptive Differential Evolutionary Extreme Learning Machine (SaDE-ELM) was proposed as a new class of learning algorithm for single-hidden layer feed forward neural network (SLFN). In order to achieve good generalization performance, SaDE-ELM calculates the error on a subset of testing data for parameter optimization. Since SaDE-ELM employs extra data for validation to avoid the...
Nowadays with the rapid development of network-based services and users of the internet in everyday life, intrusion detection becomes a promising area of research in the domain of security. Intrusion detection system (IDS) can detect the intrusions of someone who is not authorized to the present computer system automatically, so intrusion detection system has emerged as an essential component and...
In a game it is often the case that there are multiple roles or types of actors with different goals. One possible target for automatic content generation is to create multiple different software agents for these distinct roles. This paper outlines a technique, based on the multiple worlds model, for creating such actors via evolution. The objective function is based on the performance of the actors...
Latent Dirichlet Allocation(LDA) does not consider the input feature selection. The topic of each word is allocated by LDA in original feature space, which contains many insignificant words and affects quality of topics. In this paper, we proposed a feature selection method based on Genetic Algorithm(GA), which reduces the dimension of LDA input features and makes the generated topic more meaningful...
The gray Verhulst model has the extremely widespread application in the study of minority, poor information and uncertainty question when the data show saturated state or s-shaped sequences. However the gray Verhulst model built by weakening the randomness of data sequence, lacking of self-organizing and self-learning. Some scholars study on this issue, and put forward a kind of gray Verhulst-BPNN...
This paper proposes a Genetic Algorithm (GA) approach to clean a given classifier training set for remote sensing image analysis. Starting from an initial set of training data, the new method called GA-Training Label Purifying (GA-TLP) consists of the significant training sample selection using GAs in order to maximize the classifier accuracy. This means to retain the most informative samples and...
Many new Internet of Things (IoT) applications such a disaster early warning systems, video-streaming, automated driving and similar, are increasingly being built by using advanced component based software engineering approaches. Software components can include various executable images, such as container or Virtual Machine images, scripts and others. Achieving adequate Quality of Service (QoS) for...
Multiple studies have suggested the central nervous system (CNS) generates motions by using modular control of muscles and joints (synergies). However, the synergies reported by these studies are task dependent and might not reflect the true control strategies adopted by the CNS. Studying exploratory motions (EMs) can reveal biomechanical constraints and motor control strategies in healthy and clinical...
Chronic Obstructive Pulmonary Disease (COPD) is a highly prevalent condition with a deterioration of the quality of life, physical function, and important morbidity. Exercise has been shown that it can improve physical capacity and a better quality of life. The objective was to observe the feasibility of using a new gameplay exergame approach safely and easily with this population. Furthermore, quadricep...
The aim of this paper is to present a comparison between the performance of virtual and conventional rehabilitation of upper limb gross motor function. To this purpose we define two rehabilitation exercises with a high degree of similarity. The virtual exercise is a computer implementation of the well known game “whack a mole” and the conventional exercise is based on a “shape-sorter” didactic toy...
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