A new method for classifying nuts using image processing and k-means++ clustering

Artificial saliva induced structural breakdown of surimi gels with starch under continuous compressive motions

Food texture perception is dynamic, influenced by food properties and oral processing. Using the Repeatable Dual Extrusion Cell (RDEC), the oral processing dynamics of surimi gel with different corn starch concentrations (0-15%) in the presence of 1 ml artificial saliva or water were studied. The force-time curve showed increased peak forces with higher corn starch concentrations, peaking significantly at 10%, then decreasing at 15%. Salivary amylase played a crucial role in gel sample degradation, especially in samples with 5% starch, with a work value depletion ratio of 0.535 for sample with 1 ml water (SGW-5) and 0.406 for sample with 1 ml saliva (SGS-5). SEM analysis confirmed the formation of a continuous starch network with reduced intermolecular spaces in SGS-5. The starch-iodine complex showed decreasing order with increasing starch concentration, and SGS-5 exhibited the highest degradation rate (61.61 ± 0.92%). Mathematical modeling revealed that initial decay rates (k1) in gel sample decreased with increasing starch concentration, and samples with starch and artificial saliva had higher initial degradation rates. These findings highlight the intricate interplay between saliva and starch in the surimi gel matrix under continuous compressive motions by RDEC apparatus, providing insights for formulating food products with tailored textures properties.

Design and Implementation of Web-Based Virtual Mobile Robot Laboratory for Engineering Education

A web-based virtual and remote laboratory environment is developed, realized and proposed for real time control and monitoring of a mobile robot in an indoor environment. In this laboratory, a real time and continuous video stream of indoor laboratory environment is viewed by wireless IP camera mounted to the ceiling. The localization of the robot is also implemented using this IP camera. In this environment, a virtual target and virtual obstacles are located anywhere on the video image taken by the user. The robot is guaranteed to arrive at the virtual target avoiding virtual obstacles using the shortest path. The video stream of the robot’s navigation is monitored through the web environment. The robot is controlled by a BeagleBoard-xM single board computer. The PC web server symmetrically communicates with the other web server on the BeagleBoard-xM, executing developed application software. Since genetic algorithms generate alternative solutions, it is utilized as a path planning algorithm. Parameters such as population size and maximum generation of genetic algorithms applied to get the shortest path for the robot are tuned via the web-based virtual laboratory environment. The robot is also controlled manually through the web environment. At the conclusion of the experiments, the results are monitored on the web-based virtual laboratory environment. A low-cost mobile robot virtual remote laboratory is designed and implemented for engineering education in this paper. Consequently, survey and some experimental works, of the usability and performance of the RRC-Lab (remote robot control-laboratory) system are confirmed by students.