A friendly online C compiler to improve programming skills based on student self-assessment

This paper presents an online C compiler designed so that students can program their practical assignments in Programming courses. What is really innovative is the self-assessment of the exercises based on black-box tests and train students’ skill to test software. Moreover, this tool lets instructors, not only proposing and classifying practical exercises, but also evaluating automatically the efforts dedicated and the results obtained by the students. The system has been applied to the 1st-year students at the Industrial Engineering specialization at the Universidad Politecnica de Madrid. Results show that the students obtained better academic performance, reducing the failure rate in the practical exam considerably with respect to previous years, in addition that an anonymous survey proved that students are satisfied with the system because they get instant feedback about their programs.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Industrial uses of isotopes, chemical reaction mechanisms and kinetics, and radiochemistry : a selected list of references /

This bibliography contains 417 annotated references on uses of isotopes in industry and in chemical reaction mechanisms and kinetics. The references were taken from the 1957-1958 open literature. Also included are a list of journals from which the references were selected, an author index, an isotope index, and a graphical depiction of typical applications.

Power control in cognitive radios, Internet-of Things (IoT) for factories and industrial automation

Cognitive radio (CR) is fast emerging as a promising technology that can meet the machine-to machine (M2M) communication requirements for spectrum utilization and power control for large number of machines/devices expected to be connected to the Internet-of Things (IoT). Power control in CR as a secondary user can been modelled as a non-cooperative game cost function to quantify and reduce its effects of interference while occupying the same spectrum as primary user without adversely affecting the required quality of service (QoS) in the network. In this paper a power loss exponent that factors in diverse operating environments for IoT is employed in the non-cooperative game cost function to quantify the required power of transmission in the network. The approach would enable various CRs to transmit with lesser power thereby saving battery consumption or increasing the number of secondary users thereby optimizing the network resources efficiently.

Fabrication and optimizing of metal nano silicate as toxic metal absorbent from sea water

Pure Water, is a crucial demand of creature life. Following industrial development, extra amount of toxic metals such as chromium enters the environmental cycle through the sewage, which is considered as a serious threat for organisms. One of the modern methods of filtration and removal of contaminants in water, is applying Nano-technology. According to specific property of silicate materials, in this article we try to survey increased power in composites and various absorption in several morphologies and also synthesis of Nano-metal silicates with different morphologies as absorbent of metal toxic ions. At first, we synthesize nano zink silicate with three morphologies considering context and the purpose of this survey. 1) Nano synthesis of zink silicate hollow cavity by hydrothermal method in mixed solvent system of ethanol/glycol polyethylene. 2) Zink nano wires silicate in a water-based system by controlling the amount of sodium silicate. 3) Synthesis of nano zink silicate membrane. After synthesizing, we measured the cadmium ion absorbance by synthesized nano zink silicates. Controlling PH, is the applied absorption method. Next step, we synthesized nano zink-magnesium silicate composite in two various morphologies of nanowires and membrane by different precent of zink and magnesium, in order to optimize synthesized nano metal silicate. We used zink nitrate and magnesium nitrate and also measured cadmium absorption by synthesized nano metal silicates in the same way of PH control absorption. In the 3rd step, in order to determine the impact of the type of metal in nano metal silicate, we synthesized nano magnesium silicate and compared its absorption with nano zink silicate. Furthermore, we calculated the optimal concentration in one of synthesizes. Optimal concentration is the process which has the maximum absorption. While applying two methods of absorption in the test, finally we compared the effect of absorption method on the absorption level. Below you find further steps of synthesis: 1) Using IR, RAMAN, XRD spectroscopy to check the accuracy of synthesis. 2) Checking the dispersion of nano particles in ethanol solution by light microscope. 3) Measuring and observing particles with scanning electron microscope (SEM). 4) Using atomic absorption device for measuring the cadmium concentration in water-based solutions. The nano metal silicates were synthesized successfully. All of synthesized nano absorbents have the cadmium ion absorbency. The cadmium absorption via nano absorbents depend on various factors such as kind of metal in nano silicate and percent of metal in nano metal silicate composite. Meanwhile the absorption and PH control of medium containing the absorbent and solution would affect the cadmium absorption.

An activity theory framework for industrial design

Ethnography has gained wide acceptance in the industrial design profession and curriculum as a means of understanding the user. However, there is considerable confusion about the particularities of its practice accompanied by the absence of an interoperable vocabulary. The consequent interdisciplinary effort is a power play between disciplines whereby the methodological view of ethnography marginalises its theoretical and analytical components. In doing so, it restricts the potential of ethnography suggesting the need for alternative methods of informing the design process. This article suggests that activity theory, with an emphasis on human activity as the fundamental unit of study, is an appropriate methodology for the generation of user requirements. The process is illustrated through the adaptation of an ethnographic case study, for the design of classroom furniture in India.