The Practice of an Optimal Pricing Strategy for Maximizing Store Profits Using PRISM

The purpose of this paper is to introduce a process for implementing optimal pricing that uses PRISM to maximize store profits. PRISM is a system and process that uses data mining technology to process large volumes of data, then develops a probability model for customer purchases, and which then uses a heuristic approach to identify the pricing pattern that will maximize store profits. For this paper, we used customer purchase data from Japanese supermarkets to identify the optimal pricing pattern for curry roux, which would maximize store profits.2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, October 9-12, 2016

Managing a holistic supply chain network for proactive resilience

The 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), Budapest, Hungary, 9-12 October 2016

Influence of cultural factors in dynamic trust in automation

The use of autonomous systems has been rapidly increasing in recent decades. To improve human-automation interaction, trust has been closely studied. Research shows trust is critical in the development of appropriate reliance on automation. To examine how trust mediates the human-automation relationships across cultures, the present study investigated the influences of cultural factors on trust in automation. Theoretically guided empirical studies were conducted in the U.S., Taiwan and Turkey to examine how cultural dynamics affect various aspects of trust in automation. The results found significant cultural differences in human trust attitude in automation

Convex Polytopic Modeling of Diabetes Mellitus: A Tensor Product based approach

Tensor Product (TP) transformation based modeling and control can be useful in biomedical engineering, since complex nonlinear control tasks can be handled easier with it. Moreover, the modeling approach can handle the Linear Parameter Varying (LPV) models and produces a tensor based system description, which can be used during Linear Matrix Inequality (LMI) based controller design. The TP property makes the usability of the method beneficial as LMI connected techniques allows using the Lyapunov theorems. The aim of the current work is to demonstrate the usability of TP models in biomedical applications, i.e. diabetes modeling. The core model, the minimal model is investigated and simulation results are presented under Matlab

Comparison of protocol based cancer therapies and discrete controller based treatments in the case of endostatin administration

In the medical practice, there are several methods to administer anti-cancer drugs. A commonly used method is the intermittent bolus doses (BD) administration when the patient receives drug on given days and the therapy has rest periods between the injections. The amount of bolus doses can be the maximum tolerated dose (MTD) or less. Anti-cancer drug can be administered in low doses over prolonged periods without extended rest periods which is called as low-dose metronomic therapy (LDM). In addition, continuous infusion therapy is applicable within clinical environment, not yet as a portable device. The major disadvantage of these methods is the empiricism associated with determining the optimal biologic dose (OBD). In order to solve the problem, we have designed discrete-time controllers which realize automated optimal treatments

Superposition model for steady state visually evoked potentials

Steady State Visually Evoked Potentials (SSVEP) are signals produced in the occipital part of the brain when someone gaze a light flickering at a fixed frequency. These signals have been used for Brain Machine Interfacing (BMI), where one or more stimuli are presented and the system has to detect what is the stimulus the user is attending to. It has been proposed that the SSVEP signal is produced by superposition of Visually Evoked Potentials (VEP) but there is not a model that shows that. We propose a model for a SSVEP signal that is a superposition of the response to the rising and falling edges of the stimuli and that can be calculated for different frequencies. This model is based in the phase between the stimulus and the SSVEP signal considering that the phase is stable over the time. We fit the model for 4 volunteers that gazed stimuli in the frequencies of 9hz, 11hz, 13hz and 15hz, and duty-cycles of 20%, 35%, 50%, 65% and 80%. We found the parameters of the model for every volunteer using the data of Oz electrode and a genetic algorithm. The proposed model is useful for find the best duty-cycle of the stimulus and it can be useful for select a code in the stimuli different for a square signal, the model only consider one frequency at the same time, but the results showed that it could be possible to find a more generic model

Second-order and implicit methods in numerical integration improve tracking performance of the closed-loop inverse kinematics algorithm

A general approach to solve the inverse kinematics problem of series manipulators, i.e. finding the required joint motions for the desired end effector motions, is based on the linear approximation of the forward kinematics map and discretization of the continuous problem. Due to the linearization, first velocities are calculated, so numerical integration needs to be done to get the joint variables. This general solution is just a numerical approximation, thus improving the tracking performance of the inverse kinematics algorithm is of great importance. The application of several numerical integration techniques (implicit Euler, explicit trapezoid, implicit trapezoid) is analyzed, and a fix point iteration is given that can be used to calculate implicit solutions. The tracking performance of the spatial inverse positioning problem of a spatial manipulator is analyzed by checking the tracking error in the desired direction (i.e. along the derivative of the desired end effector path) and in the plane perpendicular to the desired direction. The application of the explicit and implicit trapezoid methods yielded much better tracking performance in the directions orthogonal to the desired direction when the end effector had to track a linear path, while the tracking performance in the desired direction was similar for all the methods. Simulations showed that the application of implicit and second-order methods in the numerical integration may greatly improve the tracking performance of the closed-loop inverse kinematics algorithm

Infectious Hospital Agents: an individual-based simulation framework

In this paper we present the plan, motivation, background, and the design of an agent-based simulation framework describing the spread of Hospital-Associated Infections (HAIs). We are developing a general simulation environment that is able to model wide range of pathogen transmission scenarios in hospital environment. The elements of the simulation include among others: admission and discharge patients, pathogen transmission via healthcare workers, colonization and infection, modelling hospital events, scheduling treatments, the interventions against HAI spreading. The evolution of the model is tracked in discrete time, and the simulation is driven by stochastic events sampled from predefined distributions. Our aim is to build a general, customisable and extensible simulation environment for the domain of HAIs, therefore the presented design is in Object-Oriented fashion. We implement the system in R using S4 classes, although the design is general. The results of the simulations are time series and transmission networks