Abstract Data Visualisation in Mobile VR Platforms

Data visualisation, as a key tool in data understanding, is widely used in science and everyday life. In order data visualisation to be effective, perceptual factors and the characteristics of the display interface play a crucial role. Virtual Reality is nowadays accepted as a valid medium for scientific visualisation, because of its inherent characteristics of real-world emulation and intuitive interaction. However, the use of VR in abstract data visualisation is still limited. In this research, I investigate the use and suitability of mobile phone-based Virtual Reality as a medium for abstract data visualisation. I develop a prototype VR Android application and visualise data using the Scatterplot and Parallel Coordinates methods. After that, I conduct a user study to compare the effectiveness of the mobile VR application compared to a similar screen-based one by implementing some data exploration scenarios. The study results, while not being statistically significant, show improved accuracy and speed in the mobile VR visualisation application. The main conclusions are two-fold: Virtual Reality is beneficial for abstract data visualisation, even in the case of limited processing power and display resolution. Mobile VR, an affordable alternative to expensive desktop VR set-ups can be utilized as a data visualisation platform

The Nutrient Composition of Three Mosquito (Diptera: Culicidae) Species, <i>Aedes caspius</i>, <i>Anopheles hyrcanus,</i> and <i>Culex pipiens</i>, Harvested from Rice Fields for Their Potential Utilization as Poultry Feed Ingredients

Increasing pressure on the world’s livestock production sector has stirred interest towards the exploration of insects as an alternative feed source. We examined the potential of wild-caught mosquitoes, harvested from rice-fields, to be utilised as poultry feed. Three mosquito species were identified in high abundance, namely Aedes caspius, Anopheles hyrcanus, and Culex pipiens, and their nutritional and microbiological profile was assessed at the species-level and as mixed samples collected from two different seasons (summer 2020 and 2021). Their nutritional potential was evaluated based on protein, fat, moisture and ash content, fatty acid and mineral profile, and antioxidant activity. The microbiological profile of each mosquito species was assessed by measuring the population of total viable count, Enterobacteriaceae, lactic acid bacteria, and coagulase-positive Staphylococci. Obtained values were compared to common edible insects and conventional livestock feedstuff. All mosquito samples presented an overall promising nutritional composition, stable between the two harvest seasons. Mosquitoes’ protein and fat content ranged from 54 to 62% and 16 to 28%, respectively. The examined species presented statistically significant differences in certain cases; Anopheles hyrcanus had the highest protein content (61.8% dry weight basis; dwb) and the highest antioxidant potential (45.9% ability to scavenge the DPPH radical). All mosquito samples were rich in minerals, containing high concentrations of calcium, phosphorus, and magnesium, minerals essential for poultry development. The GC/MS fatty acid profile revealed a high unsaturated character (65.2–71.5%), a predominance of palmitic (23.8–30.4%), palmitoleic (28.5–37.0%), and oleic (18.3–29.1%) acids, as well as the presence of essential linolenic (1.4–5.2%) and eicosipentanoic (1.5–2.4%) acids. The presence of microorganisms was confirmed across all species, at levels comparable to fresh food harvested from soil and farmed edible insects. Mosquitoes harvested from rice-fields exhibited an overall highly nutritious, stable profile, comparable and even superior to common feedstuff and edible insects, showing potential to be utilised as poultry feed components

Drone Control in AR: An Intuitive System for Single-Handed Gesture Control, Drone Tracking, and Contextualized Camera Feed Visualization in Augmented Reality

Traditional drone handheld remote controllers, although well-established and widely used, are not a particularly intuitive control method. At the same time, drone pilots normally watch the drone video feed on a smartphone or another small screen attached to the remote. This forces them to constantly shift their visual focus from the drone to the screen and vice-versa. This can be an eye-and-mind-tiring and stressful experience, as the eyes constantly change focus and the mind struggles to merge two different points of view. This paper presents a solution based on Microsoft’s HoloLens 2 headset that leverages augmented reality and gesture recognition to make drone piloting easier, more comfortable, and more intuitive. It describes a system for single-handed gesture control that can achieve all maneuvers possible with a traditional remote, including complex motions; a method for tracking a real drone in AR to improve flying beyond line of sight or at distances where the physical drone is hard to see; and the option to display the drone’s live video feed in AR, either in first-person-view mode or in context with the environment

Drone Control in AR: An Intuitive System for Single-Handed Gesture Control, Drone Tracking, and Contextualized Camera Feed Visualization in Augmented Reality

Traditional drone handheld remote controllers, although well-established and widely used, are not a particularly intuitive control method. At the same time, drone pilots normally watch the drone video feed on a smartphone or another small screen attached to the remote. This forces them to constantly shift their visual focus from the drone to the screen and vice-versa. This can be an eye-and-mind-tiring and stressful experience, as the eyes constantly change focus and the mind struggles to merge two different points of view. This paper presents a solution based on Microsoft’s HoloLens 2 headset that leverages augmented reality and gesture recognition to make drone piloting easier, more comfortable, and more intuitive. It describes a system for single-handed gesture control that can achieve all maneuvers possible with a traditional remote, including complex motions; a method for tracking a real drone in AR to improve flying beyond line of sight or at distances where the physical drone is hard to see; and the option to display the drone’s live video feed in AR, either in first-person-view mode or in context with the environment