This paper presents a brief analysis of the aspects of environmental education and the role it plays in society, especially since it is related to environmental awareness, behavior and attitudes in students at higher education levels.The aim is to study the initial validation of an instrument to measure the attributes of Environmental education, environmental knowledge, environmental attitudes, pro-environmental behaviors, and intentions through the Cronbach variable.
Technological advances have generated great changes in the optimization of resources, times, and costs, increasing profits and performance.Therefore, decision-making requires a sophisticated and powerful tool that helps the field of decision making.Currently, there is a wide variety of algorithms, but it is difficult to determine which one provides the best results.The materials used in this research contemplate the particle swarm optimization (PSO) algorithm in its classical form and the MOORA-PSO and DA-PSO hybrids.Where these hybrids use the multi-criteria decision-making methods (MCDM): Multi-objective optimization using ratio analysis (MOORA) and Dimensional Analysis (DA).Furthermore, the algorithms are implemented in a computer system.The methodology begins with understanding the algorithms and methods employed.Continue the integration of PSO with MOORA and DA.Followed by the comparison of the algorithms.Ending with the publication of the results and findings found.Therefore, the objective of the research is to compare PSO with two hybrids, identifying which algorithm has the greatest potential for decision-making.The results obtained have been successful, demonstrating that the DA-PSO hybridization has greater potential for decision-making.In addition, the MOORA-PSO hybridization indicates that the initial control parameters are crucial for its performance.
Nowadays given the new industrial revolution, it is necessary to know what challenges and advantages we can find in the supply chain.Therefore, that in turn will cause an impact before the imminent entry of industry 5.0 in a competitive environment.In addition, as well as identify the possible barriers and benefits that we can have in industry and in turn in the social sphere.In this sense, some questions will be proposed such as Is I 4.0 focused solely on technology?Does I 4.0 help meet the implementation of I 5.0?Are they interdependent or dependent on each other?What technologies and processes will we have to adapt to meet the purposes of I 5.0?Subsequently, an analysis of the logistics process of an industry in Cd.Juá rez will be carried out to generate a proposal on improvement to the logistics process using the strategies of industry 4.0 and contemplating the objectives of what would be an industry 5.0, verifying these theories with a program of simulation to later see the possible scope.
The hotel industry has a negative effect on the environment, since its activities generate large consumption of resources and greenhouse gas emissions, which is why the World Tourism Organization makes a strong call to all its sectors to move towards a sustainable development model.In the hotel industry, indicators have been used to improve sustainable performance, however, these sustainable indicators are scattered in the literature, which makes it difficult to select them.Therefore, Harmony Search (HS) is proposed to determine which are the best indicators to evaluate the environmental impact generated by the hotel industry.As a result of the HS search, a list of 20 indicators was obtained, which best met the selection criteria: frequency of use, level of application and year of publication.
The objective of this work is to determine the control structure that avoids the concentration drop due to the nonlinear effect of the binary azeotrope present in the distillation process of the azeotropic ethanol-water mixture, for this purpose a Smith predictive control structure is applied, which is compared with the behavior of a system with delay and an integral proportional control.This applied to a previously characterized experimental plant, for the simulation, the analysis of the step response of each of the proposed systems is performed, confirming that the predictor eliminates the overshoot in the behavior of the system during the distillation while the implemented PI control maintains them even when the response speed of it is lower.
Lean Manufacturing is a methodology that companies from different sectors have implemented for several years, which has given significant results.Although it is a methodology that has been implement-ed since the 70's, it is still in force despite the technological era that has been advancing in recent years.The different Industrial Revolutions have brought with them important advances in terms of technology, always seeking to make life easier for human beings.From Industry 3.0, where we begin to talk about technology and intelligent machines, it has sought to automate processes and replace handmade or manual production in companies.Therefore, one might think that just as companies must adapt to these new trends, methodologies, such as Lean Manufacturing, should also transition to automation or the use of technology for their application.If Industry 3.0 already showed important signs in the advancement of technology, with Industry 4.0 it was confirmed that this technology would be present in our daily lives and in the processes of companies.In fact, in developed countries such as Japan and Germany there is already widespread talk of Industry 5.0, an industry that seeks to return to the human being as an important part of industrial processes, which in Industries 3.0 and 4.0 had passed into the background to give way and greater importance to the use of technology.With the new industrial revolution (5.0) there is even talk of new technologies and tools for improving the production processes of companies.Companies seeking to adapt to the use of technology and seek to continue competing in the market and even seek a better position against the competition must make strong capital investments to acquire the technology necessary for their processes.And those decision-makers need to have a very broad picture and make sure that those investments work and have the expected results.One of the important tools in Industry 5.0 that can help in decision making is simulation.The simulation helps in visualizing how a process works without the need for it to be already implemented in a real way, that is, adjustments and improvements can be made without these implying a change or an investment in the real process.Therefore, we can have data that approximates the data that can throw us a process that is already working physically.If you are looking to analyze data from a process that is already physically implemented, simulation helps determine which part of the process requires improvement or change.
The goal of this paper is to estimate the percentage structure of electricity generation by type of technology in Mexico for the period 1992-2016.Modern portfolio theory and the capital asset pricing model of Sharpe and Litner were used.Results show that using only portfolio theory is not possible to find non-negative percentages in all the technologies.When a risk-free asset is included, there is a region where all technologies have a positive participation in electricity generation.The efficient frontier is found at 20% for wind technology share and for the rest of technologies, shares are almost equallydistributed among them.
The goal of this paper is to research the impact of VR games on physical activity, and whether a certain effort exists that would make exercising using the VR technology possible and give motivation to physically active as well as physically inactive people.Although there has been re-search proving VR games enable physical activity and motivation, there is no information about the level of physical activity that physically active and inactive persons experience, nor is there any information on the difference in their motivation to exercise when being immersed into a virtual world.By using the VR equipment, playing Beat Saber game and listening to "Eye of the Tiger", as well as by analyzing the questionnaire, the obtained results will show that it is more difficult to motivate physically active people to engage in this type of exercise.However, as far as the strain is concerned, there is almost no difference between the two groups.
With the advancement of bioengineering and nano-technology, next-generation network architecture is being equipped with nano-devices to improve its scalability.Inspired by naturally existing biological phenomena of communication, molecular communication-based nano-networks are designed on the same principles.In existing communication systems, information is transmitted by electromagnetic or electrical signals.However, these methods of communication are inconvenient for many applications where the ratio of antenna size to the wavelength of a signal is a constraint.In such scenarios, a molecular communication scheme can be employed to solve such issues.Here chemical signals act as information carriers.These signals are biocompatible and can be used in body area networks (BANs).In this paper, a nanonetwork in which communication through diffusion takes place is simulated and evaluated for various signal metrics (delay, distortion, bit rate).The concentration of molecules in pheromone signaling communication can be used as a channel transfer function in the respective molecular communication model used in nano-devices.A stochastic Single-Input-Single-Output (SISO) communication system is simulated for purpose of analysis.
The development of electricity users induces significant design needs in the field of electrical installations.These needs naturally arise from increased requirements, with regard to the quantity and quality of service provided by these facilities.Therefore, the consumption of electrical energy is increasing day by day, and the assurance of its supply has become an unavoidable imperative.The continuity of this offer requires a suitable design and sizing of the HV/A transformer stations, which constitute the essential part in the field of the distribution of electrical energy.Through this report, we tried to make a study on the substations of distribution HV whereas our objective was to gather the most possible information in order to work out a document, which makes it possible to give the maximum of details on the coordination of insulation in HV/A substation equipment.
Flow convection in agriculture greenhouse is one of the most important factors on the growth and fruiting of plants. The present work focused on natural convection in an open greenhouse heated by ridge tubes in presence of plants. Analyses are performed for different boundary conditions imposed at the roof such as constant temperature, convective heat flux, and convective and radiative heat flux. The governing equations comprising continuity, momentum and energy equations are solved by Ansys-Fluent software. In each case, the average velocity and temperature of the air are determined. The obtained results are presented in terms velocity and temperature profiles. Isothermal lines and velocity vectors showed that by increasing the convective heat transfer coefficient, the average temperature and average airflow velocity decrease. The outcomes of this study help build greenhouses with dimensions and materials to suitable for the given external conditions.
Today the MapReduce frameworks become the standard distributed computing mechanisms to store, process, analyze, query and transform the Bigdata. While processing the Bigdata, evaluating the performance of the MapReduce framework is essential, to understand the process dependencies and to tune the hyper-parameters. Unfortunately, the scope of the MapReduce framework in-built functions is limited to evaluate the performance till some extent. A reliable analytical performance model is required in this area to evaluate the performance of the MapReduce frameworks. The main objective of this paper is to investigate the performance effect of the MapReduce computing models under various configurations. To accomplish this job, we proposed an analytical transient queuing model, which evaluates the MapReduce model performance for different job arrival rates at mappers and various job completion times of mappers as well as the reducers too. In our transient queuing model, we appointed an efficient multi-server queuing model M/M/C for optimal waiting queue management. To conduct the experiments on proposed analytics model, we selected the Bigdata applications with three mappers and two reducers, under various configurations. As part of the experiments, the transient differential equations, average queue lengths, mappers blocking probability, shuffle waiting probabilities and transient states are evaluated. MATLAB based numerical simulations presented the analytical results for various combinations of the input parameters like λ, µ1 and µ2 and their effect on queue length.
The brushless DC motors (BLDCM) are capable of maintaining a constant speed in situations where speed and power are controlled at the same time. This motor, compared to DC motors, is able to generate far more power and simultaneously operate. An open-loop BLDCM output with hardware support and a three-segment method on closed-loop BLDCM were both examined in this study. The research provides a brushless DC motor model that considers the motor's commutation behavior. To make sure that the drive system for BLDC motors works properly, it is important to know the exact torque value, which is based on the back-EMF. The BLDC motor is simulated in MATLAB/Simulink after a basic mathematical model is developed. In open-loop circuits, the intensity may be adjusted by varying the pulse width (or duty), and the motor speed can be increased or decreased by altering the input voltage. Pulse widths and speeds are measured and compared to real-world hardware in this study. This paper presents a comparison of the outcomes of the BLDC motors based on the examination of time responses.
Most health care systems use various physiological signals to provide an accurate diagnosis performance. The main common signals functional in health care applications are the electrocardiogram (ECG) and photoplethysmogram (PPG). ECG signal represents the electrical cardiac activity of the heart, while the PPG signal measures the changes in the blood volume. There are several applications in which the ECG combined with PPG can be used in the field of medical health care. This survey illustrates the various applications that combine features from the ECG and PPG signals. The review manifests the techniques, methodologies used in the data acquisition, pre-processing of the signals. The feature extraction and classification phases for both ECG and PPG are explained. The limitations, challenges, and future directions for the combined application of ECG and PPG are clarified to solve the medical problems that existed, presented, and feasible. This study aims to increase the interest in applying the combination between ECG and PPG signals in more applications and to obtain optimal measurements related to cardiac activity.
This work is part of the study and implementation of a fuzzy PWM control structure (fuzzy pulse width modulation) of an induction machine (MAS) on a circuit-based platform reconfigurable FPGA type. We first presented a strategy for the hardware implementation of a fuzzy inference system on a programmable logic circuit of FPGA type, through the hardware description language (VHDL) and Xilinx generator system (XSG). Secondly we proposed Fuzzy-PWM architecture for the improvement of response time of an asynchronous machine (MAS) and finally we validate the proposed hardware co-simulation architecture in real time on the ML402 development kit (based on FPGA Xilinx Virtex-4) and Simulink / Matlab.
Reliability, safety, and fault-tolerant control (FTC) for power systems are substantially raised in several industrial applications. It is critical to correctly diagnosis the faults occurring in a drive system to avoid harmful accidents and to ensure continuity of operation. It is necessary to design proper control techniques to recover the faulty system’s performance/functionality to its nominal level. This research work divided into two parts a design scheme of intelligent fault-tolerant control based artificial intelligence techniques (AI) is described and implemented integrates common knowledge acquisition methods with techniques developed in the fields of model-based diagnosis (MBD) to reach the so-called towards intelligent fault tolerant control to provide reliability and maintain the stability of the system in desired performance automatically; This paper presents the first part of this scheme proposes stator-flux oriented (SFO) control with GA-tuned proportional-integral-derivative (PID) controller. The principle is to set the q axis component of stator current invariant during healthy and faulty operating mode. The overall development scheme is summarized and an example illustrates features of the methods performed on a 1.0kW SynRM drive. Results presented have shown that the FT controller scheme developed is potentially capable of dealing with a larger number of faults and can successfully keep a good dynamic performance during faulty mode.
This article provides a full hardware implementation for direct torque control (DTC) of an asynchronous motor (AM) on the Field Programmable Gate Array (FPGA). Due to its high processing frequency, the FPGA circuit presents an alternative for achieving a high performance DTC implementation. This cannot be achieved by any DSP or microcontroller application. The proposed hardware architecture implements three components of DTC control strategy (the integral proportional speed regulator, the estimation and the switching blocks). This implementation has the advantage of being faster, more efficient and with minimum hardware resources on the target FPGA board. The hardware architecture of the DTC control was designed and simulated in Matlab / Simulink using XSG blocks, then synthesized with the Xilinx ISE 14.2 tool, implemented and validated on the Xilinx Virtex-4 FPGA circuit by Hardware in the Loop process.
In this paper, an attempt has been made to enhance the dynamic behaviour of Automatic Generation Control (AGC) of two areas two units using both Thyristor Controlled Series Compensator (TCSC) placed in the tie-line and Superconducting Magnetic Energy Storage (SMES) units are considered in both areas. For more realistic study, the effects of Governor Dead Band (GDB) and Generation Rate Constraints (GRCs) are taken into account for both areas. However, to conduct the system to better dynamic responses, we have implemented a PI-PD cascade controller. After that, a well-known and powerful optimisation algorithm named Firefly Algorithm (FA) is employed by evaluating the Integral of the Squared Error (ISE). From the obtained results, the implemented methods prove its efficiency from different view of points such as: minimisation of Overshoot and Undershoot Peaks (PO), (PU) and Settling Time (ST).
The main purpose of localization in wireless sensor networks is to determine the location of the randomly collected sensors. Recently, bio-inspired localization techniques have become popular thanks to its precise and fast solution. In this paper, a recently developed meta-heuristic algorithm based on the social behavior of chickens called chicken swarm optimization (CSO) is used to solve the node localization problem. The studies that we have carried out have demonstrated the clear effect of our proposed approach by changing the characteristics of the network and the number of chickens used, as well as its ability to improve a classical approach based on CSO; and the comparison results with PSO showing the superiority of proposed approach.
