Genetic Programming and Spatial Morphogenesis

This paper discusses the use of genetic programming (G.P.) for applications in the field of spatial composition. The G.P. was used to generate three-dimensional spatial forms from a set of geometrical structures. The approach uses genetic programming with a Genetic Library (G.Lib). G.P. provides a way to genetically breed a computer program to solve a problem. G. Lib enables genetic programming to define potentially useful subroutines dynamically during a run

Gait Data Augmentation using Physics-Based Biomechanical Simulation

This paper focuses on addressing the problem of data scarcity for gait analysis. Standard augmentation methods may produce gait sequences that are not consistent with the biomechanical constraints of human walking. To address this issue, we propose a novel framework for gait data augmentation by using OpenSIM, a physics-based simulator, to synthesize biomechanically plausible walking sequences. The proposed approach is validated by augmenting the WBDS and CASIA-B datasets and then training gait-based classifiers for 3D gender gait classification and 2D gait person identification respectively. Experimental results indicate that our augmentation approach can improve the performance of model-based gait classifiers and deliver state-of-the-art results for gait-based person identification with an accuracy of up to 96.11% on the CASIA-B dataset.Comment: 30 pages including references, 5 Figures submitted to ESW

One-shot learning of human activity with an MAP adapted GMM and simplex-HMM

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results

Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision

Spiking Neural Networks (SNNs) offer a biologically inspired approach to computer vision that can lead to more efficient processing of visual data with reduced energy consumption. However, maintaining homeostasis within these networks is challenging, as it requires continuous adjustment of neural responses to preserve equilibrium and optimal processing efficiency amidst diverse and often unpredictable input signals. In response to these challenges, we propose the Asynchronous Bioplausible Neuron (ABN), a dynamic spike firing mechanism to auto-adjust the variations in the input signal. Comprehensive evaluation across various datasets demonstrates ABN's enhanced performance in image classification and segmentation, maintenance of neural equilibrium, and energy efficiency.Comment: 10 page

Συστηματική ανασκόπηση της υγειονομικής περίθαλψης των αστέγων στις Ηνωμένες Πολιτείες

Οι Ηνωμένες Πολιτείες μαστίζονται από τεράστιο αριθμό αστέγων με κύριο πρόβλημα την έλλειψη στέγης και την παροχή υγειονομικής περίθαλψης. Συνέπειες της κακής υγιεινής των αστέγων αποτελούν σε ένα πρώτο στάδιο η ακραία φτώχεια, το σκληρό περιβάλλον διαβίωσης καθώς και το τραύμα. Η πρώτη εμφάνιση του φαινομένου της αστεγίας και οι γενιές που ακολούθησαν αποτυπώνονται στην συγκεκριμένη εργασία. Επιπλέον προσπαθεί να εξετάσει πως με την πάροδο του χρόνου οι Ηνωμένες Πολιτείες εφάρμοσαν στρατηγικές και προγράμματα για την αντιμετώπιση και βελτίωση του φαινομένου της αστεγίας, αν και κατά πόσο η ιατρική από την πλευρά της πρόσφερε σε αυτό το εγχείρημα μέσω της παροχής βοήθειας εκεί που υπήρχε η ανάγκη, στο δρόμο. Η παροχή φροντίδας και η σύνδεση αυτών των ατόμων με ολοκληρωμένη πρωτοβάθμια φροντίδα μέσω καταφυγίων και ξενώνων αποτελεί κορμό για την μελέτη του φαινομένου που ερευνούμε. Οι άστεγοι είναι κομμάτι της κοινωνίας και όχι οι κάτοικοι μιας αόρατης πόλης που εκεί βρίσκουν καταφύγιο.The United States is plagued by a huge number of homeless people with the main problem being lack of housing and healthcare. Consequences of poor hygiene of homeless people are in a first stage extreme poverty, harsh living environment as well as trauma. The first appearance of the phenomenon of homelessness and the generations that followed are reflected in this paper. Furthermore, it attempts to examine how over time the United States has implemented strategies and programs to address and improve the phenomenon of homelessness, and whether and to what extent medicine on its part has contributed to this endeavor by providing assistance where the need was there, on the street. The provision of care and linking these individuals to integrated primary care through shelters and hostels is the backbone for the study of the phenomenon we are investigating. The homeless are part of society, not the inhabitants of an invisible city where they find shelter

A novel event-based incipient slip detection using Dynamic Active-Pixel Vision Sensor (DAVIS)

In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments