A computer-based anaglyphic system for the treatment of amblyopia

Ali Rastegarpour Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Purpose: Virtual reality (VR)-based treatment has been introduced as a potential option for amblyopia management, presumably without involving the problems of occlusion and penalization, including variable and unsatisfactory outcomes, long duration of treatment, poor compliance, psychological impact, and complications. However, VR-based treatment is costly and not accessible for most children. This paper introduces a method that encompasses the advantages of VR-based treatment at a lower cost. Methods: The presented system consists of a pair of glasses with two color filters and software for use on a personal computer. The software is designed such that some active graphic components can only be seen by the amblyopic eye and are filtered out for the other eye. Some components would be seen by both to encourage fusion. The result is that the patient must use both eyes, and specifically the amblyopic eye, to play the games. Results: A prototype of the system, the ABG InSight, was found capable of successfully filtering out elements of a certain color and therefore, could prove to be a viable alternative to VR-based treatment for amblyopia. Conclusion: The anaglyphic system maintains most of the advantages of VR-based systems, but is less costly and highly accessible. It fulfills the means that VR-based systems are designed to achieve, and warrants further investigation. Keywords: amblyopia, computer-based, open source, virtual reality, color filters, 3-

Energy Management in Buildings: Lessons Learnt for Modeling and Advanced Control Design

This paper presents a comparative analysis of different modeling and control techniques that can be used to tackle the energy efficiency and management problems in buildings. Multiple resources are considered, from generation to storage, distribution and delivery. In particular, it is shown what are the real needs and advantages of adopting different techniques, based on different applications, type of buildings, boundary conditions. This contribution is based widely on the experience performed by the authors in the recent years in dealing with existing residential, commercial and tertiary filed buildings, with application ranging from local temperature control up to smart grids where buildings are seen as an active node of the grid thanks to their ability to shape the thermal and electrical profile in real time. As for control models, a wide range of modeling techniques are here investigated and compared, from linear time-invariant models, to time-varying, to nonlinear ones. Similarly, control techniques include adaptive ones and real-time predictive ones

An Adaptive Underfloor Heating Control with External Temperature Compensation

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Hermeneutic Approach to Quantum Learning

This paper aims to discover the key components of quantum theory in learning through hermeneutic research method. Quantum theory is exactly against the theory of simplicity. While the theory of simplicity has been influenced by modernity and the insights from Descartes and Newton who believe that phenomena can be reduced to their simplest form, quantum theory emphasizes holism and holds that all the components of being are dynamic and interconnected. Cartesian reductionism led to the linear causality between phenomena, which believed that phenomena were predictable and controllable, and therefore certain, but the Quantum perspective instead focused on the complexity and entanglement of relationships rather than on linearity and simplicity. Discussions on Quantum learning were started by quantum theory. Emphasizing on holism, entanglement, and the complex interactive relationship between phenomena, they focused on both objective and extrinsic capacities as well as subjective and intrinsic capacities. This perspective of Quantum thinking leads to cooperative learning, dynamic classrooms, learning through conscious and subconscious memory, data processing and conceptualization, input data processing cycles, visual learning, auditory and motor- sensory learning, subjective learning and consideration of learning context, which all consider holism and entanglement in learning

A Multivariable Self-tuning Controller for a D-type Water Tube Industrial Boiler

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A Cross-cultural Comparison of Objectivity in Childhood Games: Iran and the United States

Games have been introduced as a means for studying cross-cultural differences and societies. This paper presents a case study in analogous games played by children in two different countries with two different cultures – Iran and the United States. Four examples are presented to demonstrate that games played by Iranian children are subject to less objectivity in their rules. Therefore, nonobjectivity may be a phenomenon that has roots in the society and the many differences between the two societies may very well be the results of this fundamental difference. If the presence of objectivity in childhood game rules could be, in actuality, indicative of objectivity in social and civil interactions in the everyday lives of the people, the direction of causality remains to be established. In other words, it remains unclear whether the games influence the culture or are influenced by the mandates of the society

Hierarchical Nonlinear MPC for Large Buildings HVAC Optimization

This paper studies the problem of performance improvement and energy consumption reduction of the heating, ventilation and air conditioning system of a large-scale university building through the application of nonlinear predictive control strategies concerning also practical and implementation issues. The system consists of two heat pumps, a water-to-water and an air-to-water type, and two different air handling units, which regulate and circulate air in all thermal zones. In such applications, prediction of the future dynamical behavior of the heat pumps is extremely important to enforce efficiency, but it is also very challenging due to the load dependency and nonlinearity of the coefficient of performances of those heat pumps. On the other hand, another source of potential model mismatch is the nonlinear characterization of the heat transfer coefficients of the AHU induced by variable air and water velocity, which gives rise to a non-trivial nonlinear system. To do so, two nonlinear model predictive control strategies are investigated to deal with many physical constraints and nonlinear problems. Finally, a sensitivity and robustness analysis are performed to highlight the merits, defects and impacts of those control algorithms on the energy performance of the building

Neural network predictive schemes for building temperature control: a comparative study

Starting from an application of a real medium-size university building, the present paper focuses on the comparison among different ways to synthesize a predictive control scheme to improve the energy performance for heating, ventilation and air conditioning system of the building. The main motivation is the comparison among a nonlinear predictive control structure previously developed (based on first principle equations) with a predictive control whose prediction model is an artificial neural network. Particular emphasis is given on how to tune the neural network to gain good closed-loop performance. Twenty-one different networks are designed and tuned in order to correlate their closed-loop performance with the type and length of training data set, for building energy efficiency applications. Finally, a linear time-variant predictive control is given, obtained as analytical linearization along the future system trajectory, of the nonlinear equations of the neural network model. The goal is to add to the comparison a low computational burden (linear controller) still derived from nonlinear data-driven methods

Predictive control-oriented models of a domestic air-To-water heat pump under variable conditions

Air-To-water heat pumps are quite often integrated with a hot-water tank, to better decouple the generation from the delivery of heat in buildings and to improve the overall performance of the system. The estimation and prediction of the coefficient of performance of the heat pump is extremely important to enforce efficiency, but it is also a very challenging task, due to the strong dependency of the performance on disturbances and operating conditions. Another source of potential model mismatch is the variable water flow rate in the condenser side induced by the heat pump low-level control logic, which gives rise to a non-Trivial nonlinear system. In this letter, we tackle the problem to develop and properly tune an equivalent control-oriented model for the system, i.e. heat pump and tank, under variable flow rate conditions on both the condenser and load side, while still preserving good prediction capabilities of the model, with no tank temperature nor mass flow rate sensors. In particular, we focus on a real case study consisting in an air-To-water heat pump system and a 150{m2} building located in SYSLAB, Department for Electrical Engineering, Risoe Campus, Denmark Technical University. The quality of the developed models is then evaluated through a nonlinear model predictive controller suitably designed and checked against detailed reference models previously developed. Finally, different sensitivity analyses are performed, which witness the robustness of the proposed algorithm