Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling

In everyday life people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this paper, we analyze the influence of walking speed, gait pattern and input techniques on commonly used performance parameters like error rate, accuracy and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed-specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a tradeoff between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods

The prevalence of overweight, obesity and central obesity in six regions of Croatia: results from the Croatian Adult Health Survey [Prevalencija prekomjerne tjelesne težine, debljine i avdominalne debljine u šest regija Hrvatske]

Our aim was to estimate the prevalence of overweight, obesity and increased waist circumference in the adult population of Croatia and investigate regional differences in six regions of Croatia. Using the data from the 2003 Croatian Adult Health Survey we estimated the overall prevalence of overweight, obesity and increased waist circumference for the entire population of Croatia at 38.11%, 20.34% and 43.52%, respectively. For men, this was 43.2%, 20.1% and 34.98% and for women 33.6%, 20.6% and 51.13%, respectively for the three indicators of increased body weight. We found conflicting evidence as to whether the Mediterranean part of the country, compared with the continental part, bears a lesser degree of cardiovascular risk. Planners should pay particular attention to the Northern region, where the burden of increased body weight was the highest

Modelling and correcting for the impact of the gait cycle on touch screen typing accuracy

Walking and typing on a smartphone is an extremely common interaction. Previous research has shown that error rates are higher when walking than when stationary. In this paper we analyse the acceleration data logged in an experiment in which users typed whilst walking, and extract the gait phase angle. We find statistically significant relationships between tapping time, error rate and gait phase angle. We then use the gait phase as an additional input to an offset model, and show that this allows more accurate touch interaction for walking users than a model which considers only the recorded tap position

Factors Influencing the Stability of Low Temperature Tetragonal ZrO2

Various factors that influence the appearance of a tetragonal (t-) ZrO2 polymorph at room temperature have been extensively investigated. Several proposed models emphasize the role of anionic impurities (SO42-, OH-), crystallite size (surface energy), structural similarities between the starting material and t-ZrO2, lattice strains, water vapor, lattice defects (oxygen vacancies), etc. Our investigations, focused on the stability of low temperature t-ZrO2, showed that, regardless of the structural differences in the starting zirconium materials, their thermal decomposition products crystallized into a metastable t-ZrO2. The t-ZrO2 -> m-ZrO2 transforma-tion occurred during the cooling or further calcination in the pres-ence of air at atmospheric pressure. On the other hand, if these processes are performed in vacuum, the metastable phase is pre-served. These observations indicate that a metastable t-ZrO2 appears at room temperature as a result of stabilization caused by introduction of oxygen vacancies, similarly as in the solid Solutions with aliovalent cations. A decrease in the specific surface area of ZrO2 grains or the presence of the substances that enter into strong surface interactions with ZrO2 (SO42-, Cr2O3) prevents the diffusion of oxygen from the atmosphere into the ZrO2 lattice and due to this fact the metastable t-ZrO2 is stabilized. On the other hand, lattice strain and grain size of metastable t-ZrO2 could not be clearly related to its stability

System for automatic detection and classification of cars in traffic

Objective: To develop a system for automatic detection and classification of cars in traffic in the form of a device for autonomic, real-time car detection, license plate recognition, and car color, model, and make identification from video. Methods: Cars were detected using the You Only Look Once (YOLO) v4 detector. The YOLO output was then used for classification in the next step. Colors were classified using the k-Nearest Neighbors (kNN) algorithm, whereas car models and makes were identified with a single-shot detector (SSD). Finally, license plates were detected using the OpenCV library and Tesseract-based optical character recognition. For the sake of simplicity and speed, the subsystems were run on an embedded Raspberry Pi computer. Results: A camera was mounted on the inside of the windshield to monitor cars in front of the camera. The system processed the camera’s video feed and provided information on the color, license plate, make, and model of the observed car. Knowing the license plate number provides access to details about the car owner, roadworthiness, car or license place reports missing, as well as whether the license plate matches the car. Car details were saved to file and displayed on the screen. The system was tested on real-time images and videos. The accuracies of car detection and car model classification (using 8 classes) in images were 88.5% and 78.5%, respectively. The accuracies of color detection and full license plate recognition were 71.5% and 51.5%, respectively. The system operated at 1 frame per second (1 fps). Conclusion: These results show that running standard machine learning algorithms on low-cost hardware may enable the automatic detection and classification of cars in traffic. However, there is significant room for improvement, primarily in license plate recognition. Accordingly, potential improvements in the future development of the system are proposed

Hydrothermal Synthesis of Platinum Group Metal Nanoparticles

A novel route for the synthesis of platinum group metal nanoparticles has been reported. The synthesis is based on the addition of tetramethylammonium hydroxide (TMAH) to the aqueous PtCl(4), IrCl(3) or Rh(NO(3))(3) solution followed by the hydrothermal treatment of these precipitation systems at 160 degrees C. The mean size of nanoparticles was 9.2 nm for platinum, 21 nm for iridium, and 28 nm for rhodium. The average crystallite size was estimated at 7.4 nm for platinum, 3.1 nm for iridium and 3.5 nm for rhodium. The possible mechanism of platinum group metal nanoparticles formation is briefly discussed

Prevalence and five-year cumulative incidence of abdominal obesity in Croatian women of childbearing age: the CroHort study [Prevalencija i petogodišnja kumulativna incidencija abdominalne pretilosti u žena fertilne dobi u Hrvatskoj]

Generalised obesity is increasing in prevalence globally, however trends in abdominal obesity are less well known. In 2003, 1,999 women of childbearing age participated in the Croatian Adult Health Survey, of whom 598 (29.9%) participated in the second cycle in 2008. For 2008, the prevalence of abdominal obesity using the International Diabetes Federation (IDF) criterion (waist circumference > or = 80 cm) was estimated at 70.3% (95% CI 61.8% to 75.7%), whereas the prevalence of abdominal obesity using the National Cholesterol Education Program, Adult Treatment Panel III (NCEP ATP III) criterion (waist circumference > or = 88 cm) was estimated at 48.6% (42.6% to 54.7%). The preceding five-year cumulative incidence was 54.3% (44.5% to 64.2%) and 35.2% (28.0% to 42.4%) using the IDF and NCEP ATP III criteria, respectively. The burden of abdominal obesity is high and rapidly increasing in Croatian women of childbearing age, the key population subgroup for obesity control