A forensic-driven data model for automatic vehicles events analysis

Digital vision technologies emerged exponentially in all living areas to watch, play, control, or track events. Security checkpoints have benefited also from those technologies by integrating dedicated cameras in studied locations. The aim is to manage the vehicles accessing the inspection security point and fetching for any suspected ones. However, the gathered data volume continuously increases each day, making their analysis very hard and time-consuming. This paper uses semantic-based techniques to model the data flow between the cameras, checkpoints, and administrators. It uses ontologies to deal with the increased data size and its automatic analysis. It considers forensics requirements throughout the creation of the ontology modules to ensure the records’ admissibility for any possible investigation purposes. Ontology-based data modeling will help in the automatic events search and correlation to track suspicious vehicles efficiently.

Assessment of Brassicaceae Seeds Quality by X-ray Analysis

A serious problem of vegetable production is the quality of sown seeds. In this regard, assessment of seed quality before sowing and storage is of great practical interest. The modern level of scientific research requires the use of instrumental automated methods of seed quality evaluation, allowing to obtain more information and in a shorter time. The material for the study was a variety of samples from the collection of Brassica oleracea L., var. capitata, Raphanus sativus L., var. radicula, and Lepidium sativum L. seeds from the Federal Scientific Center of Vegetable Breeding and the Timofeev Selection Station. Digital X-ray images of seeds were obtained using a mobile X-ray diagnostic device PRDU-02. Automatic analysis of digital X-ray images was performed in the software “VideoTesT-Morphology 5.2.” The following latent defects of cabbage seeds of economic importance were revealed and identified: irregular darkening, significant “patterning” with deep separation of embryo parts, “angularity of seeds” leading to the loss of their viability. Automatic analysis of digital X-ray images of seeds confirmed the informativeness of brightness indices of digital X-ray images, as well as shape indices. Their connection with sowing qualities of the studied seeds was established.

Giant Unilamellar Vesicle Electroformation: What to Use, What to Avoid, and How to Quantify the Results

Since its inception more than thirty years ago, electroformation has become the most commonly used method for growing giant unilamellar vesicles (GUVs). Although the method seems quite straightforward at first, researchers must consider the interplay of a large number of parameters, different lipid compositions, and internal solutions in order to avoid artifactual results or reproducibility problems. These issues motivated us to write a short review of the most recent methodological developments and possible pitfalls. Additionally, since traditional manual analysis can lead to biased results, we have included a discussion on methods for automatic analysis of GUVs. Finally, we discuss possible improvements in the preparation of GUVs containing high cholesterol contents in order to avoid the formation of artifactual cholesterol crystals. We intend this review to be a reference for those trying to decide what parameters to use as well as an overview providing insight into problems not yet addressed or solved.

Counting trees - methods of automatic analysis of photogrammetric data in forests of the continental region

The paper is devoted to the methods of automatic analysis of photogrammetric data in forests of the continental region. It also discusses how automatic tree counting can be used to manage forests. Experimental research was conducted to verify two methods: Faster R-CNN and Template Matching to automatically detecting tree objects in the continental region characterized by mixed forests with a large predominance of conifers. The research was done based on photogrammetric data taken in four areas belonging to forest districts subordinate to the Regional Directorate of State Forests in Zielona Góra. Data was collected from drones and small airplanes with a photogrammetric container. The results show that both methods can be used for analyzes in specific cases. Moreover, the level of Recall shows the advantage of Faster R-CNN methods for the photogrammetric data collected during the flights in various weather conditions.