Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis.

A critical issue in image analysis for analyzing animal behavior is accurate object detection and tracking in dynamic and complex environments. This study introduces a novel preprocessing algorithm to bridge the gap between computational efficiency and segmentation fidelity in object-based image analysis for machine learning applications. The algorithm integrates convolutional operations, quantization strategies, and polynomial transformations to optimize image segmentation in complex visual environments, addressing the limitations of traditional pixel-level and unsupervised methods.

Prognostic Value of ISS and TRISS Scores in Tunisian Terrorism Victims.

Introduction: Injuries caused by terrorism attacks are one of the urgent problems of the society and the health system. In this work, we aimed to assess the injury severity score (ISS) and trauma injury severity score (TRISS) in Tunisian military combatants injured during terrorism attacks.

Materials And Methods: A total of 153 victims of terrorism admitted to the Military Hospital of Tunis between January 2012 and January 2017 were included.

Sequential Behavior of Broiler Chickens in Enriched Environments under Varying Thermal Conditions Using the Generalized Sequential Pattern Algorithm: A Proof of Concept.

Behavior analysis is a widely used non-invasive tool in the practical production routine, as the animal acts as a biosensor capable of reflecting its degree of adaptation and discomfort to some environmental challenge. Conventional statistics use occurrence data for behavioral evaluation and well-being estimation, disregarding the temporal sequence of events. The Generalized Sequential Pattern (GSP) algorithm is a data mining method that identifies recurrent sequences that exceed a user-specified support threshold, the potential of which has not yet been investigated for broiler chickens in enriched environments.

Classifying Chewing and Rumination in Dairy Cows Using Sound Signals and Machine Learning.

This research paper introduces a novel methodology for classifying jaw movements in dairy cattle into four distinct categories: bites, exclusive chews, chew-bite combinations, and exclusive sorting, under conditions of tall and short particle sizes in wheat straw and Alfalfa hay feeding. Sound signals were recorded and transformed into images using a short-time Fourier transform. A total of 31 texture features were extracted using the gray level co-occurrence matrix, spatial gray level dependence method, gray level run length method, and gray level difference method.

Energy Assessment from Broiler Chicks' Vocalization Might Help Improve Welfare and Production.

Vocalization seems to be a viable source of signal for assessing broiler welfare. However, it may require an understanding of the birds' signals, both quantitatively and qualitatively. The delivery of calls with a specific set of acoustic features must be understood to assess the broiler's well-being.