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This study aimed to develop and evaluate the performance of a service system platform based on the Internet of Things (IoT) for monitoring nutritional deficiencies in plants and providing fertilizer recommendations. There are two distinct differences between this work and previous ones; namely, this service system platform has been developed based on IoT using a system engineering approach and its performance has been evaluated using dependability. We have successfully developed and integrated a service system platform and chlorophyll meter that is based on IoT. We have also successfully tested the performance of the service system platform using the JMeter software. The dependability value measured from the five tested variables (reliability, availability, integrity, maintainability, and safety) showed a value of 0.97 which represents a very good level of system confidence in not failing to deliver services to users under normal operational conditions. From a future perspective, this platform can be used as an alternative service to monitor nutrient deficiencies in plants and provide fertilization recommendations to increase yields, reduce fertilizer costs, and prevent the use of excessive fertilizers, which can cause environmental pollution.

Until now, many studies were conducted on microorganisms in order to make the best use of them and prevent the loss. As a type of microorganism that is widely utilized by humans, the yeast has a simple single cell structure that can represent many other complex cell processes and generally has almost elliptical shapes making it easier to model for further investigation. In this study, we model yeast cells with two dimensional circular granular particles and the interaction between them are modeled by the force of gravity, normal force, and Stokes force. The growth and birth factor of yeast cells are modeled stochastic with the simulation is done by using javascript programming language. From the simulation results obtained, showing the growth of yeast cells in the colony has a behavior that is in accordance with the theory, which grows exponentially, as well as the growth of the size of the colony radius whose growth rate is half to the rate of growth of its number of cells.

The pattern of yeast budding formation is essential in yeast colony expansion. By exploring how Saccharomyces cerevisiae as model cell grows, the distinction of pathological and non-pathological eukaryotic cells can be further understood. This research explores the use of FIJI software and network theory to characterize the formation pattern of Saccharomyces cerevisiae colony. By using speed distribution and degree distribution, three potential networks are compared: barbell network, relaxed caveman network, and triangular lattice network. Triangular lattice network emerges as the most suitable network to model yeast colony growth.

Grains configuration snapshots of Brazil-nut effect (BNE) in two-dimension are physically modeled using disk-formed objects, e.g., buttons and magnetic pin. These BNE configurations are artificially designed to mimic the real ones observed in experiments. A computer scanner is used to capture the configurations. Obtained images are then digitized using web browser running a HTML equipped with a JavaScript code, which is built mainly only for this work. From digitization process all grains positions (granular bed and intruder) are obtained, which is later analyzed using the simplest model, i.e., potential energy. Since the minimum energy principle (MEP) suggests that a closed system should go to its state with minimum internal energy, our BNE system must also obey it. Evolution of only the intruder seems to violate MEP but not for the whole system. Grains compaction plays important role, so that the system can achieve its configuration with minimum potential energy., Comment: 4 pages, 7 figures, submitted to International Conference on Advances in Education Technology (ICAET 2014)

Brazil-nut Effect (BNE) experiment in (real) two-dimension is conducted. Container, bed particles, and intruder are made from the same material, i.e. 2 mm thickness acrylic plate. Dimensionless acceleration r and vibration frequency f are in the range of 2-4 and 13-17 Hz, respectively. It is observed that rise time Trise decreases with the increase of Γ similar to reported by others, but there is a range of f and Γ, where Trise increases with the increase of Γ due to occurrence of Leidenfrost effect, which reduces convection flow of granular particles.

Using hard sphere collision scheme and molecular dynamics method simulation, two-dimension Brazil-Nut Effect (BNE) is conducted. BNE inital configurations are artificially created to obtain number of contacts between the grains, called as contactopy. It is observed that from initial condition until the end of BNE observation, center-of-mass in vertical direction tends to decrease, while contactopy tends to increase, which are similar to the reported results in a Gedankenexperiment (Viridi et al., 2014). Initial configurations which are also dependent on contactopy influence the rise time since it can override influence of density ratio that should affect rise time (Mobius et al., 2001). We investigate on how the intruder rise time influenced by contactopy, as well as density.