Proceedings of the 4th Brazilian Technology Symposium (BTSym'18)

The proposal of this work is to present uprating techniques on a 230 kV transmission line to improve the transmission lines capacity, as well, comparison of uprating techniques which highlights the importance of the reconductoring technique. The methodology is validated through a computer application widely used by electric power companies to design and optimize new transmission lines, thus bringing significant gains in the heights of the conductors. Furthermore, introducing a competitive option so as to increase the transmission capacity of lines in operation. We also present some studies case conducted on a real trans-mission line in order to evaluate the benefits the techniques may offer at level voltage.

Mortar is nowadays a very common building material at the civil construction industry. It has been employed in different ways in buildings wherein it serves for laying blocks, wall and ceiling cladding, just to name a few applications. Therefore, maximum safety for buildings is achieved when many research findings are taken into account in order to minimize possible accidents during the construction or even after the work is done. Research studies are intended to provide a better quality to mortar and the required mechanical resistance when subjected to high tensile loadings. Thus, an alternative to enhance the properties of mortar is the use of additives in its composition, which are able to improve mechanical resistance, deformation characteristics and its technological behavior. However, despite many published results on the influence of such additives, few studies have been carried out on the influence of proteins on the mortar mechanical and technological behavior. Therefore, the aim of this research is to evaluate the changes in mechanical and technological behavior of cement mortar, made by incorporating whey protein and albumin to its composition. Protein contents of 2 and 10% in weight were chosen herein. The analysis was based on the protein content and mortar aging time. Data show that contents of 2 and 10% of whey protein and albumin had a significant influence on test results.

In this work, the terahertz frequency range is exploited. From organic materials to metamaterials, different algorithms able to extract their effective electromagnetic properties were developed. In order to characterize different concentrations of lactose, such samples were submitted to a terahertz time-domain spectroscopy (TTDS) to experimentally acquire their transmission spectrum. With only these input data, the retrieval method employed parametrization of the refractive index by using the Lorentz model. Extending the studies to metamaterials, single and hybrid geometries based on split ring resonator (SRR) were simulated and characterized utilizing the Kramer-Kronig relations in an algorithm whose response was the effective permittivity and permeability of this class of materials.

The SpaceWire standard, used in aerospace embedded applications, was developed to connect devices that operate at high data rates, having as goals the traffic control and payload transmission. This standard enables flexibility on transmission rates, which brings some challenges related to clock domains. In an effort to fulfill the essential system requirements, such as reliability and versatility, synchronization techniques are introduced to avoid possible problems related to the clock domain crossing. The objective of this work is to present a technique applied to SpaceWire Receiver that enables its operation at many signaling rates.

In this paper, an efficient numerical approach is developed for solving the baseline problem with interval uncertainties. Interval arithmetic is also utilized for developing the proposed method in the presence of uncertainties with only lower and upper bounds of parameters. In the proposed method, the equation of motion, performance index, and boundary conditions are first changed into some algebraic equations. This process converts the problem into an optimization problem. The presented technique is based on an interval extension of Chebyshev polynomials where its coefficients are achieved by world cup optimization algorithm, as a new optimization algorithm. The proposed method approximates the control and state variables as a function of time. The proposed solution is based on state parameterization, such that the state variable is approximated by the proposed interval Chebyshev polynomials with unknown interval coefficients. Finally, by solving the baseline problem in the presence of interval uncertainties, the reliability and effectiveness of the proposed method are demonstrated.

This work presents practical and simulated experiments designed to compare the efficacy of two satellite attitude control methods, using the satellite simulation platform developed by ITA, the MuSat, as a testbed. The first algorithm is based on feedback linearization, and is designed to suppress precession effects caused by the momentum wheels. The second algorithm is a controller based on the State Dependent Riccati Equation (SDRE) technique, which aims to optimize convergence iteratively. An attitude maneuver in the three axes of rotation was executed using the MuSat platform, using the two controller algorithms. A numerical simulation of these experiments using a computational model of the MuSat is also presented, providing a baseline for the experiment. Results indicate that while both algorithms perform similarly well under idealized conditions, the SDRE algorithm outperforms the feedback linearization controller, due to its higher precision and robustness characteristics.

It is increasingly common to use engineering techniques in the areas of health, in order to solve simple problems or even create new diagnostic methods. In the last decade, the Hough Transform has been widely used as a tool for segmentation of blood smear images for the purpose of counting blood cells. However, it is noted that the Watershed transform has been applied to perform the same function. Based on this, a methodology based on the Hough Transform was created, aiming to perform the detection and counting of erythrocytes and leukocytes and verify the applicability of the methodology when compared to others. The study was conducted based on the determination of accuracy and simulations performed on different hardware platforms and subsequent comparison with the WT-MO methodology. The results demonstrated that both methodologies are able to perform the task of detection and counting of blood cells in digital images of blood smear. However, the methodology based on the Watershed Transform best meets the criteria of speed and reliability (counts), which are indispensable to medical laboratory routine.

The evaluation of human blood is an important diagnostic method for the detection of diseases. The analysis of the erythrocytes contained in the blood contributes to the detection of anemia and leukemia, whereas the leukocyte analysis allows the diagnosis of inflammation and/or infections. The blood is analyzed through of the complete blood count test (CBC), which is dependent on automated and/or manual methodologies. The dependence of medical areas on new technologies leads the present study to the goal of developing an image segmentation algorithm that meets the criteria of efficiency and reliability for detection and counting of blood cells. The algorithm was developed through the Matlab software, being the image processing methodology based on the union of the Watershed transform and Morphological Operations, originating the WT-MO methodology. For the simulations, 30 blood smear images containing erythrocytes and leukocytes were used in a non-pathological state. The results showed that the WT-MO methodology presents high sensitivity (99%), specificity (96%) and accuracy (98,3%) when compared with the manual methodology. Therefore, the WT-MO methodology is an accurate, reliable and low-cost technique and can be applied as a third more accessible methodology to perform of the complete blood count test (CBC) in populations of underdeveloped and developing countries.

Toxoplasmosis is one of the most frequent parasitic diseases in the world, and the Toxoplasma gondii causes it, an obligate intracellular parasite that infects its hosts through the consumption of raw or under-cooked meat, vertical transmission, milk consumption without pasteurization, blood transfusions and contact contaminated environments. Given the wide geographical distribution of this parasite, many people may be infected in the latent phase. Because of the above, this study aims to carry out a bibliographical review of the literature demonstrating the parasitic cycle and especially the ways of diagnosis of the disease. Immunological diagnoses are of great importance, however, and the recent creation of new magnetic resonance imaging tools has been promising and may be used as a detection method for Toxoplasma gondii cysts in the future. Only the creation of new technology can lead to increasingly accurate, reliable diagnoses, being able to lead patients to the right pathways faster and even avoiding more serious consequences of the disease, caused by the delay in diagnosis.

The operating systems (OSs) created the possibility for people to interact with computer hardware, these same are made with an enormous number of lines of code for this kernel, usually developed with the languages of C and Assembly language programming. Thus, the objectives of this study are in the area of knowledge, development, and learning of construction, approach and design in the development of complex codes for the creation of an OS. In this present study, the build process from C code compulsorily uses a compiler. An assembler generates the machine code. Assembly language is crucial for real-time operation. Nevertheless, most of OS can be implemented with an additional language. After Assembly, the leanest Kernel code can be obtained with a low-level language like C/C++. The use of a proper boot manager or an existing one, such as Grand Unified Bootloader (GRUB), this itself once programmed, adds knowledge about the hardware developer. This project’s Kernel has been loaded into two virtual machines (one with Linux and one with Windows) and on a physical machine. These results demonstrated that the developed software is viable, relevance and academic potential, with high learning power, being able to serve as a starting point for several pieces of academic research.

The behavior of a system is studied through a simulation model. Once developed and validated, the simulation model can be used to investigate a wide variety of issues, as well as propose improvements. This research objective is to propose a novel simulation paradigm to improve the transmission of content in wireless telecommunication systems. The simulation environment employs a pre-coding process of bits based on the application of a technique relying on discrete events and signals before the modulation process. The signal transmission on the channel occurs in the discrete domain with the implementation of discrete entities in the process of bit generation applied at a low level of abstraction in a wireless telecommunication system. The simulation considered the advanced differential binary phase shift keying (DBPSK) as the modulation format for signal transmission in an AWGN channel, using different hardware platforms and in the studies. The results show improvements ranging from 9 to 35% in memory utilization, related to information compression, in the context of the research.

The recent climate change has forced people to live in extreme conditions, either excessive heat or cold, implying that they must adapt to survive in these situations. However, there are people who, because of their geographical condition and lack of resources, lack the means and tools to combat these climate changes. The context of this study is provided in a rural town located in the Arequipa region (Peru), whose inhabitants have to fight against frosts of up to −20 °C in an area without electricity. A viable solution to this problem is found through the design and implementation of a heating system using geothermal and photovoltaic energy, which are resources found in the area, according to a report of the Ministry of Energy and Mines. This study analyzes and researches the geographical and meteorological conditions of the region, for validating, through theory and simulations, whether the proposed system can supply the thermal energy required to maintain the indoor temperature at a minimum of 15 °C under extreme conditions. The system is designed after analyzing the best technological options and techniques currently available in the context studied for its ultimate financing and establishing guidelines and indicators for monitoring results.

In the mining industry, due to the extraction and processing of ore, a significant amount of tailings are produced which are discharged into deposits. In some cases, these are in contact with effluents and generate acid waters that pollute the environment and affect the health of the inhabitants. Additionally, these tailings within their composition contain valuable metals that can be reused through a process of mineral flotation. As a part of this research, a study based exclusively on laboratory tests was performed on the tailings deposit located in the Recuay–Peru district, where the presence of concentrations of Pb, Zn, and Ag at 48.36% was obtained, 23% and 250 g/TM. Thus, this study aims to take advantage of polymetallic tailings deposits that are in an abandonment state by extracting valuable ore through the flotation process based on their chemical composition and mineralogical characterization.

This paper covers the design of double balanced active mixers based on the Gilbert cell, exploring methods of conversion gain enhancement such as capacitive cross-coupling, PMOS current bleeding and a hybrid topology using both methods.

In recent years there has been an increasing interest in the development of applications on large surfaces that allow interaction with the user through gestures and multitouch events, this is how born the idea of Large Screen Surfaces Devices. Due to the current task of developing applications that rely on privative frameworks and having to rewrite the code to port the project to multiple platforms, we have seen as an opportunity the implementation of a cross-platform framework for the development of enterprise applications designed to support this technology. This paper presents the procedures for the creation of the framework and the implementation of two applications that validate the worked functionalities. Additionally, this Framework presents a low cost implementation compared to actual devices in the market.

In Latin America, the lack of electricity has been a serious problem for over several years. To overcome this lack of supply in electricity supply, hydraulic energy is now being used in a greater proportion to fulfill the electricity needs in the rural areas. Investigations have been conducted to assess the environmental conditions of these rural areas to optimize the functionality of turbines used for hydraulic energy generation. However, there are very few focused on turbines of less than 0.5 kW generation. The proposed study aims to analyze the positioning of the blades of the cross-flow turbines and designing an electric generation system for rural dwellings. A simulation of each evaluated design was performed, and the power generated from these turbines was calculated. The results show that the power outputs initially were high and stabilized at a value of approximately 180 W, hence satisfying the minimum demands of a rural house.

With the increasing number of individuals with chronic diseases and elderly people in Brazil, regular medical monitoring is necessary to monitor and preserve the physiological parameters. The present study developed a system of remote monitoring of body temperature, heart rate and oxygen saturation of the blood for the application in Home Care systems. The remote monitoring system developed has three stages that are able to collect the data, transmit this data via Wi-Fi to a cloud server and analyze them on a computer remotely. The designed system also notifies the user via his cell phone of the appropriate time and which measures to take according to a patient specific schedule and if the procedure was successful.

A Brain Computer Interface (BCI) provides a channel of communication and control amid the human brain and a computer or electronic device. In this paper we describe the implementation of all the main steps involved in the operation of a BCI system based on Steady State Visually Evoked Potential (SSVEP) paradigm. Also, we present a comparative study about the performance of our BCI employing two feature extraction techniques (Welch’s Method and Discrete Fourier Transform), and considering the signal analysis window of two sizes (4 and 6 s). The results guided the conception of an online BCI-SSVEP. Our system was successfully controlled by two volunteers, who completed the task of moving a foam block with a robotic manipulator.

The present work proposes an algorithm to calculate the QRS Score and the determination of confounders starting from Electrocardiographic (ECG) signals. The QRS Score is a parameter that indicates how big the scar is in the wall of the patient’s myocardium; It is also helpful in determining how healthy the heart is. Said parameter is calculated from signal information such as time measurements, amplitude relationships and waveforms. The evaluation of the ECG signals is usually done by visual perception of the graph paper where it is printed as a result of the electrocardiogram examination. However, the reproducibility of this method is 60% and the repeatability is 66%. This definitely affects the accuracy of the score obtained and therefore the diagnosis of a disease. The proposed algorithm aims to reduce the subjectivity of the analysis and standardize the punctuations to be obtained. The algorithm is made up of processing stages that involve the conditioning of the signal using finite impulse response (FIR) filters, decontamination of confounders by neural networks, detection of the QRS complex, detection of times and amplitudes and finally obtaining the QRS score from a table of criteria. Finally, the proposed algorithm obtained a reproducibility of 75% and a repeatability of 100% exceeding the performance of the specialist.

The power systems operation is in current evolution as new technologies are added and influence the dynamics of the system. Increased monitoring of the electric variables to be observed as a way to prevent oscillations and unstable transient effects also yields on the analysis of a lot of data. This paper describes two methodologies for assessment of the angular stability of small signals, using data obtained through measurements. A case with noise on measurement, and another without, will be used for evaluations of the methodologies. An acknowledged computational tool will be used to allow the comparative analysis and the results discussed.

Purpose: Evaluate the influence of rheological models for blood flow in the carotid artery bifurcation. Methods: The geometry (developed in SolidWorks) was based on the mean dimensions of several angiograms of adults and children. Newtonian and non-Newtonian (Casson, Carreau-Yasuda and Power Law models) hypothesis were admitted for modelling the rheological behavior of the blood. The parameters of the equations that govern the rheological behavior were taken from blood itself. The flow simulation was performed using open source software OpenFOAM, with the solvers nonNewtonianIcoFoam (non-Newtonian hypothesis) and icoFoam (Newtonian hypothesis). Both use the PISO algorithm. Results: In all models, the fluid presents a “detachment” in the non-divider wall. This behavior is more noted in the Newtonian hypothesis, which also presents “C” shaped profiles. Conclusions: The Newtonian behavior diverges from the non-Newtonian and the results demonstrate that there is a good concordance between the non-Newtonian models. For a mid-sized artery such as the carotid artery, the non-Newtonian hypothesis is more indicated. There are no significant differences between the Casson, Power Law and Carreau-Yasuda models.

This paper presents an implementation of Sobel edge detection in static images for the FPGA, described in Verilog, and for the respective software: Mathematica, MATLAB, OpenCV and in-house C++ written program. Comparisons in performance were made between the different applications. The results concluded that the FPGA was faster.

This work proposes a system capable of obtaining the geometric measurements of a Yagi antenna using digital image processing. The objective is to obtain the measurements automatically in 3D using the CST STUDIO software, which is a program specializing in electromagnetic simulations in 3D. The antenna images are acquired by means of a depth sensor and an RGB sensor. By applying image processing techniques such as thresholding, morphology, filtering, and segmentation, the image obtained by the RGB sensor will identify the parts that are comprised by the antenna and their measurements in pixels. Through the image obtained with the depth sensor, it will be possible to transform said measurements from pixels into a unit of length. To obtain these measurements with the least possible error, the system processes 30 samples and averages them to obtain the final measurements. With this process, it was possible to obtain a measurement error of 0.16 cm.

This paper presents a preliminary study of the development of an air navigation safety system based on one of the major physiological problems of the navigational pilot. This proposal primarily aims at the life safety of pilots and crew as well as the integrity of aircraft. In this context, the work brings a search of synaptic response patterns to different levels of hypoxia and, based on these, discuss actions of control of the aircraft.

This article presents a study of a neural network applied to estimate losses in core and winding of three-phase distribution network. The architecture of neural network used was the topology Multiple Layer Perceptron and training algorithm Levenberg-Marquard that use non-linear methods. From collate of data is create a database with all selected attribute for subsequently be used on simulation of artificial neural networks. All samples of learning are collected from transformers electric tests of automated software of routine testing used in diverse transformers industry and concessionaire of electric energy. The test stage represents 15% of samples, this part represents not supervision stage of training process where is possible observe ANN behavior after training stage (70% of samples) and validation (15% of samples). The evaluation of neural network was made by tools Mean Square Error, Linear Correlation Coefficient and graphic analyzer of cross-validation process. And in the training process obtain accuracy of 80 and 96% of data samples test of a transformer industry.

Once unthinkable, it is now possible to record and interpret brain signals to generate application commands through a Brain-Computer Interface (BCI). This innovative technology of human-computer interaction brings hope to people with severe motor disabilities to improve their quality of life and social insertion. This study aims to analyze the feasibility of using a BCI based on Steady State Visually Evoked Potentials (SSVEP) in the control of a wheelchair. For this purpose, a 3D simulator of a wheelchair was developed and the user interaction was analyzed. The results show the feasibility of controlling the wheelchair simulator by BCI-SSVEP. However, it is still necessary to analyze the interaction performance in a real environment and to make improvements in the BCI and in the control system to guarantee a safer and more efficient experience to the user.

The work consists in recognizing the gestures of the alphabet in Peruvian sign language using techniques of digital image processing and a model of Deep Learning (CNN). Image processing techniques are used for segmentation and tracking of the hand of the person making the gestures. Once the image of the segmented hand is used, a CNN classification model is used to be able to recognize the gesture. The image processing and CNN algorithms were implemented in the Python programming language. The database used was 23,000 images divided into 70% for training, 15% for testing and 15% for validation. Likewise, said data corresponds to 1000 images for each non-mobile gesture of the alphabet. The results obtained for the precision of the classifier were 99.89, 99.88 and 99.85% for the data of training, test and validation respectively. In the case of the Log Loss parameter, 0.0132, 0.0036, and 0.0107 were obtained for the training, testing and validation data, respectively.

This paper compares the control of a bidirectional converter connected to the grid using two different controllers: the conventional PI controller and a fuzzy controller. The approach is done by detailing the design of the fuzzy controller, indicating the inputs and outputs, pertinence functions, and inference rules. The performance of the controllers is evaluated based on simulations using Simulink/Matlab, so that the output current of the drive follows a given reference. This reference goes through changes, thus the transient behavior for each case can be studied. In the conclusion of this paper a quantitative and comparative comparison is done, in which the observed advantages of each controller analyzed are highlighted.

In this paper we establish a methodology for obtaining the I-V characteristic of fabricated and characterized resonant tunneling diodes (RTDs) based on experimental data available in the literature. In addition, a scaling factor is proposed, in order to taking account the reduction in the dimensionality between the reservoir and the active region. Hence, the proposed method allows preserving the physical meaning of the major parameters used in the theoretical model developed by Schulman et al. [1], while providing an acceptable fitting, at least, for the negative differential resistance (NDR) behavior of the I-V curve. The validation of the methodology is obtain by satisfactorily contrasting the simulated curve with the experimental data presented in Schulman et al. [1], for a RTD of the In $$_{0.53}$$ 0.53 Ga $$_{0.47}$$ 0.47 As/AlAs system. Finally, we extend the model proposed for another two RTDs of the GaAs/AlAs system manufactured and characterized by Yang et al. [2] and Alkeev et al. [3]. The simulated results show good agreement regarding experimental peak and valley currents, peak and valley voltages and peak-to-valley ratio (PVR), with a minimum concordance of 94.5 $$\%$$ % . Thus, this method can be use in the design of RTD, aiming its application in oscillator circuits.

The need of fresh water in our time has become a problem of important concern. Restore water for new uses makes purification an essential process to achieve a desired degree of quality. This need depends on each different purpose, such as purification of drinking water or recycle water for industrial need. Due to the toxic characteristics of non-biodegradable organic pollutants, new treatment technologies must be studied and Advanced Oxidation Processes (AOP’s) come up as suitable for degradation of a wide range of organic contaminants in polluted water. The optimization of photocatalysis is an important issue to turn this process viable. Organic pollutants in effluents threats the environment in several ways, in this context, textile dyes are the major responsible for the colored wastewaters disposed at effluents. This work presents the experimental results of utilizing HNO3 and NaNO3 mixture in aqueous solution for the optimization of the photocatalytic activity. 97% of the dye was degraded in 16 min. Thus, the mechanism of reaction is discussed about a new source of hydroxyl radicals which reacts with the pollutant, as it happens in troposphere.

The increasing fleet of automobiles in metropolitan centers challenges humanity for engineering solutions that allow parking multiple vehicles in confined spaces. A possible solution to this problem is in the verticalization of the spaces through the development of high-tech parking systems capable of parking multiple vehicles in limited spaces. A previous paper presented an innovative parking duplicator device launching a possible solution to the stated challenge. The current discussion presents an optimization study of the dimensions of the elevating platform of the parking duplicator device in the prior academic work. In this study, the search was for enhancing the equivalent stress at minimum weight and this was achieved by means of stress-strain analysis and CAD/CAM technics. First, a conceptual design was developed and the design characteristics of the elevating platform, i.e., a grid were defined. Secondly, the structural analysis of the grid was performed in the software MASTAN2®. The obtained results of the stress-strain analysis were used while analytically dimensioning the grid and so determining the optimal thickness of the elements that constitute it. The solutions were refined with the finite element method. Finally, a virtual prototype and a detailed project of the grid was developed on the software SOLIDWORKS® v. 2018. The obtained structure was a simple and inexpensive engineering solution for the elevator platform optimizing the parking system. The methodology applied in the project development of the present discussion demonstrated to be efficient and so it can be applied to the development of virtually any mechanical design.

Castor oil is one of the most important potential feedstocks for biodiesel production, but the product obtained has problems within the specific density and viscosity specifications. A wat to improve these properties is to produce biodiesel form blends of castor biodiesel oil with other biodiesel oils. On the other hand, the recycling of waste oils and fats to obtain biodiesel can help in the economic development of several regions in Brazil. This work includes producing biodiesel from blends of virgin castor oil and waste frying oil. Biodiesel production from blends of virgin castor oil (VCO) and waste cooking oil (WCO) from ethylic route and alkaline catalysis was studied in this work. Physico-chemical characterization of VCO (B1), WCO (B2) and three different blends (B3: 50%VCO + 50%WCO; B4: 25%VCO + 75%WCO; B5: 75%VCO + 25%WCO) were evaluated. Initial blend was characterized by acidity level, free fatty acid, saponification index, and density. Iodine and cetane index, glycerin, absence of triglycerides and rheological behavior were determined for obtained biodiesel. The results indicated that the acidity level dropped considerably after the transesterification, however only biodiesel from B1, B4 and B5 showed acidity index in accordance with the standard parameters. Nevertheless, B1 viscosity and cetane number lied outside the legislation. All samples were within the specified standard for iodine index and density. Despite the fact that B4 and B5 results were within the legislation for biodiesel, B4 would be a better alternative due to higher quantity of WCO.

The goat breeding has increased the participation on the agricultural scenario, where goat’s milk and its derivatives have conquered and maintained the new markets. The present work aims to analyze sensorial and rheological parameters of cured cheese produced with goat milk, by acid coagulation. The same product was prepared in a conventional manner, which is, with cow’s milk. The products were analyzed with regard to the physical, chemical, texture and sensorial properties. The results presented in sensorial tests demonstrate that only for the texture, the products presented no significant difference, although rheological tests have found the penetration of about 37% higher in the cheese prepared from goat’s milk. The other sensorial attributes showed significant differences between the two products, where the cheese made from goat’s milk had slight preference, by the tasters.

Microalgae constitutes an adequate environmental alternative: besides the accumulation of lipids, they capture CO2 of the atmosphere and absorb contaminants present in aquatic environments. This work used Chlorella vulgaris, cultivated in a pretreated wastewater effluent generated by Lorena School of Engineering. The tests were carried out with effluents collected on different days because of the variation of their concentration along the week. Chlorella vulgaris presented good adaptation to the university effluent, reaching a maximum cell density of 1.92 × 107 cells/mL and a dry biomass concentration of 1.74 g/L. It obtained satisfactory concentrations of lipids per gram of biomass (0.095–0.164 mg/g). In addition, it promotes nitrate removal rates between 54 and 78.74%, and COD reduction between 17.73 and 36.13%. The cultivation of the microalgae Chlorella vulgaris in effluent proved to be a good alternative to promote the accumulation of lipids and the improvement of water quality.

A photovoltaic cell junction forms a photovoltaic panel that has small efficiency, occasioning a maximum power unavailability. The maximum power depends on temperature and irradiation’s environmental conditions. To provide maximum power, it is recommended to add an electronic system known as maximum follower. The Maximum Power Tracker, also known as MPPT (Maximum Power Point Tracking), alters the operation of the converter connected to the photovoltaic panel array, thereby allowing maximum power availability regardless of irradiation and temperature values. Some MPPT algorithms are used to allow the optimization of solar energy. As a result of the maximum power efficiency, the MPPT Conductance Incremental algorithm was used. Through the software MatLab/Simulink $$^{\circledR }$$ ® , the modeling and simulation of the photovoltaic panel was carried out. The output current and the power of the photovoltaic panel depends on the Irradiation. The Incremental Conductance algorithm was efficient, given that the results obtained with this algorithm compared to the output power values of the photovoltaic panel presented relative errors lower than 10%.

Positive definiteness and Hurwitz stability of the interval systems are discussed. A linear matrix inequality representation is introduced to simplify the analysis of the interval system. First, it is shown that the interval matrix can be stable if it has 2 conditions. Afterward, they converted to linear matrix inequalities for simplifying the conditions solution. A Lyapunov function is introduced to prove the new representation based on linear matrix inequalities.

This work summarizes the operating features for type II second-order Phase-Locked Loop (PLL)-based Frequency Synthesizers (FS) from the set of equations of linear dynamic modeling for defining the corresponding block level and system level transfer functions and developing the reference design equations for the Low Pass Filter (LPF) components sizing.

This work describes the implementation and operation features for a Phase-Locked Loop (PLL) architecture-based frequency synthesizer for clock generation and digital systems driving. From a programmable structure, considering an input reference frequency FREF = 50 MHz, schematic level simulation results indicate the possibility for generation of 3 distinct output frequencies, according to the transient response limits: TP (peak time) = 1.9 µs, TS (settling time) = 2 µs, and MP (maximum overshoot) <8%. The system was implemented through Cadence Virtuoso Analog Environment (ADE) from UMC CMOS technology (0.18 um), considering power supply VDD = 1.8 V.

This work deals with different types of residential energy monitoring methods, comparing their advantages and disadvantages. More specifically, this works focus on the relationship between these methods and the usage of state sensors devices. They are classified as: ILM (Intrusive Load Monitoring), where power information is acquired per household appliance and NILM (Non-intrusive Load Monitoring), where only one meter is used to get the total energy consumption information. Although, the first method is more effective for regular consumers to help saving energy, both of them provide good energy estimation values. We have shown that when comparing both methods, the state sensor devices can assist to reduce computational efforts for NILM disaggregation algorithms and to infer energy estimate with ILM techniques. Comparing with the commercial devices, the last method can be considered an important and low cost solution, with only 10% error rate.

Nowadays the business environment is very dynamic and has been influenced by the development of new technologies that affect from the factory floor to the business model. This is a phenomenon that entails the digital transformation of several spheres of the organization, such as leadership, strategy, operations, culture, governance, among others. This work aimed to develop and validate (content and semantics) an instrument to evaluate the maturity degree of organizational digital transformation. The process consisted of four main phases beginning with the (i) establishment of the instrument; followed by (ii) initial validation and restructuring; (iii) then a second evaluation, with representatives of the academic and entrepreneurial spheres; (iv) and ending with layout and settings for digital research platform. It was observed that the evaluators presented a high level of agreement in each one of the questions, also considered relevant for the subject studied (>58%). However, they disagreed on which question relates to each organizational dimension. Therefore, new adjustments were made in order to leave the writing of the questions clearer and more specific in relation to their respective organizational dimension. The evaluation process resulted in a digitalization management instrument with 16 multiple-choice questions, two at each of the eight dimensions: strategy, leadership, products, operations, culture, people, governance and technology. The developed instrument can be applied by any organizational profile and the simplified data processing allows the manager to identify the digitalization maturity degree of the company.

This paper aims at presenting an R&D view on how Data Science may be inter-related with smart city management, especially in terms of supporting predictive analyses. Trends on this fast-growing scenario are pointed out as well as some experiences and applications that the authors’ institution has built up or may come to develop.

Brazil is a country whose electrical energy generation comes mainly from hydroelectric and thermoelectric power plants. In order to optimize the water resource and minimize the cost of electricity generation, the National System Operator—ONS solves an optimization problem known as hydrothermal dispatch. In this way, the hydrothermal dispatch problem was solved using the stochastic dual dynamic programming, taking into account constraints imposed by hydroelectric plants and also restrictions imposed by thermoelectric plants, such as transport and generation of natural gas. For the implementation of the dispatch, we used real operation data of the Brazilian National Integrated System of the year 2015, referring to three subsystems: North, Northeast and Southeast/Midwest. The results of the simulations are presented for the different operating situations and explain how the restrictions imposed by natural gas influence the operational cost and the mode of operation of the electric power generating units.

Human capital is recognized as a pillar of the creation of intellectual capital and is fundamental for the productivity and functioning of organizations. From a contemporary perspective, human capital ceases to be considered only as cost and is seen as an investment, once it is possible to measure it. The objective of this article was to measure some existing approaches to capital human measurement, using as a methodological tool a bibliometric research in the last 11 years of the papers submitted and approved at EnAnpad, which is an event organized by the National Association of PostGraduate Studies and Research in Administration (ANPAD). The bibliometric research was elaborated by quantitative documentary analysis. The results showed, among others, a great diversity of areas in relation to how this theme is treated. This leads to reflections on how human capital has been gaining space for discussions in various organizational environments. There is a sign that from this subject, before, certainly, a discussion almost restricts the area of human resources, now goes beyond the walls and departmental currencies.

In a rapidly changing business environment, companies are continually striving to increase productivity and maintain competitiveness. Projects become the delivery mechanism for the products and services of these organizations, which use more and more knowledge workers who benefit from accumulated knowledge and learn from other projects. Thus, the transfer of knowledge, in the area of strategic management, has an important role in the integration of knowledge to optimize the delivery of products and services. This study aimed to identify the best practices of knowledge transfer and evaluate if they are applicable in project management. For this, a theoretical survey was carried out identifying the knowledge transfer practices and, later, a instrument was developed, which was applied to the Brazilian project management community. The data treatment involved the application of test of Equal Variances and One Way ANOVA to prioritize results. There were 365 responses and the dimensions Culture, Leadership and Communication were identified as the most relevant for the transfer of knowledge in project management, being critical success factors among the members of the project team.

Facing the importance of knowing the correlation between the controllable variables of a lyophilization and their impact on quality parameters established by regulatory agencies of health products the correlation between the freezing rate and the speed of sublimation achieved during the lyophilization of an immunobiological product. For this, performed in which the lyophilization parameters have been set, the temperature and pressure cycles were identical, with the exception of the two freezing rates which in the first experiment (batch A) was −0.22 °C/min and second experiment (batch B) was −1.77 °C/min. For these experiments, the mass reduction velocity was measure during the sublimation step in the lyophilization process. 1. The effects of freezing stability of the proteins vary significantly. 2. The immunobiological product evaluated was sensitive to the two freezing rates applied. With the control of parameters of the lyophilization process, in particular nucleation, is reduce the drying time and consequently the process. 3. The freezing rate of −0.22 °C/min can be used as a freezing rate appropriate to the lyophilization process of the immunobiological product studied since this condition optimized the mass reduction time during the sublimation stage and above all preserved the requirements of the final product quality. 4. With this, it becomes possible to rationalize the costs of inputs and energy related to the production of this immunobiological, as well as conscious maintenance of natural and ecological resources available for this purpose.

The recent climate change has forced people to live in extreme conditions, either excessive heat or cold, implying that they must adapt to survive in these situations. However, there are people who, because of their geographical condition and lack of resources, lack the means and tools to combat these climate changes. The context of this study is provided in a rural town located in the Arequipa region (Peru), whose inhabitants have to fight against frosts of up to −20 °C in an area without electricity. A viable solution to this problem is found through the design and implementation of a heating system using geothermal and photovoltaic energy, which are resources found in the area, according to a report of the Ministry of Energy and Mines. This study analyzes and researches the geographical and meteorological conditions of the region, for validating, through theory and simulations, whether the proposed system can supply the thermal energy required to maintain the indoor temperature at a minimum of 15 °C under extreme conditions. The system is designed after analyzing the best technological options and techniques currently available in the context studied for its ultimate financing and establishing guidelines and indicators for monitoring results.

In recent years, project management in consulting firms has grown due to greater demands for goods and services. However, this growth has meant that due to inefficiencies in the management, delays in project delivery times are generated. In addition, the same situation occurs for performance of personnel’s competences, as well as in defining the scope of the project. Therefore, this article proposes a model for the application of Project Management Body of Knowledge (PMBOK) based on knowledge management, which consists of the following areas: stakeholder management, risk management, cost management, time management, human resources management, quality management, integration management, and scope management. To show the ease of use of this model, a case study was conducted in an engineering consulting firm. The results of the application of the model were successful: the delay in project delivery times was reduced by 70% and the risks that may exist during execution were reduced by 67%. In addition, the company highlighted the success of the application of knowledge management because it improved the interaction and skills of staff by facilitating the implementation of the model.

The logistics processes of companies seek an adequate supply of merchandize, streamline processes, reduce costs, and distribution of their products to the customer in an efficient manner and allow them to develop corrective planning in order to be competitive in the market. However, these processes are less efficient in importing companies of the SME sector. Therefore, this article proposes the application of a change management model to improve the logistics process that generates a real transformation. This model is structured in three phases: first, pre-Implementation, which refers to participatory leadership and resistance to change; second, implementation of logistics management; and third, sustainability of the model over time. The model was validated in a Peruvian SME importer of household goods, whose satisfactory results implied an increase in available storage capacity, reduction of logistics costs, satisfaction of change, and organizational culture.

Smart bus monitoring systems are used to provide real-time information about vehicles such as location, arrivals, average speed, journey time, and so on. These systems add values to the transportation service and bring benefits to both users and managers. This paper presents Circulino, an IoT solution for monitoring a University campus public transportation system. This solution was developed within the University’s Smart Campus project and includes collecting geolocation data from the public transportation vehicles and generating useful information for the university community. The solution developed provides information that allows service managers to automatically monitor in real time the bus schedule accomplishment. In addition, the IoT Circulino solution allows the university community to monitor in real time the bus arrival at a specific bus stop, and other information that aid in planning the use of the transportation system. The solution implements the smart mobility concept and can be used in smart cities as well.

Currently, deficient ventilation systems are a frequently observed problem in mining. Such deficient ventilation systems lead to the recirculation of stale air or air with toxic gases. This translates into an increase in the costs of ventilation and electrical consumption for the mining organizations as conventional and practical solutions simply include options such as buying a greater number of fans. Moreover, this problem also exposes the mine workers to an unsafe work environment with unfavorable conditions that could end in minor, incapacitating, or fatal accidents. Therefore, this research seeks to optimize ventilation systems by introducing the Ventsim software tool to develop efficient coverage, addressing, flow, circuit or network characterization, and air balancing in conjunction with avoiding the stagnation of toxic gases in underground work. The primary result of the proposed model’s application in this study was the reduction in ventilation costs related to electricity consumption.

Currently, in open-pit mining operations, the highest cost among all processes is that of transporting trucks, whether in fuel, roads, tires, or spare parts, among other factors. Therefore, this article proposes the use of the Six Sigma methodology of continuous improvement as a quality management tool to reduce the downtime of the truck fleet to obtain better productivity in operations. The results of the investigation in the case study allowed to visualize that with the election of an optimal fleet appropriate for the conditions given in a mining project, the values of productivity and efficiency improve considerably. This is reflected in a better use of the machinery and in the reduction of unproductive times.

In a chemical laboratory of analysis of concentrates of minerals there are delays in the delivery of results report to the clients, failing to meet the deadlines; so this research aims to solve the problem through the 5 Lean Six Sigma steps that consists in: Defining, Measuring, Analyzing, Improving and Controlling (DMAIC). The findings suggested that the focus on the data collection, by the technical analyst, of the following values: the molar mass in the EDTA solution and the volumetric expense of the chemical reaction of the sample would have the greatest impact on the decrease of the retests.

Electrical energy consumption of a residence is usually monitored by a meter installed at its entrance and it is composed by the sum of consumptions of installed devices. Energy disaggregation estimates the consumption of each device at each instant of time. This paper presents two main contributions. First, we address disaggregation using data mining techniques by clustering methods, that is, k-Means and Expectation and Maximization (EM). We demonstrate that we can obtain superior disaggregation accuracy from more complex methods. The second contribution, we elaborate clusters (dictionaries) considering that the states of operation of the devices and the signal of total consumption are dependent instances. We use Reference Energy Disaggregation Data Set (REDD), Waikato Environment for Knowledge Analysis (WEKA) and MATLAB.

Sustainability adoption at the civil construction has been increasing over the years in a search for sustainable alternatives to reduce pollution and waste. One of those sustainable practices which has received great attention in the last few years is the application of bamboo as a raw material. In fact, bamboo has been employed in different areas, such as in the food industry, handicrafts, housewares, and furniture. Its main features are flexibility, durability, lightweight, strength, low cost and versatility, which enable its application at the construction industry. However, its use requires specific treatments, such as fungicide and insecticide, along with careful procedures for harvesting, curing and drying. Therefore, the aim of this research is to evaluate the potential use of bamboo as a building material for the construction industry by means of mechanical tests. Measurements were performed at the Materials Laboratory, School of Engineering from the Mackenzie Presbyterian University, Campus Higienópolis. The analysis was based on two bamboo species, which were chosen after interviewing experts in the field and searching the literature. For comparison purposes, two bamboo species were studied: Dendrocalamus aesper and Phyllostachys pubescens, which were chosen according to suggestions from experts in the field and by searching the literature, especially those contributions based on physico-chemical tests with other bamboo species. Based on the analyzed experimental data, the results evidenced the bamboo species studied herein could be applied to civil contruction. Both species chosen for this work provided suitable mechanical characteristics, since the average compressive strength for the Dendrocalamus aesper species was 83.14 MPa and for the Phyllostachys pubescens species was 97.67 MPa. The tensile strength for the Dendrocalamus aesper was 180.71 Mpa, whereas for Phyllostachys pubescens was 121.88 MPa. These results are in good agreement to the literature, which makes these bamboo species suitable as a sustainable alternative for the construction industry.

The high degree of freedom of hand movements produces a high variability of shapes and hand appearances that still challenges hand gesture recognition algorithms. This paper presents an approach to recognize sign language fingerspelling. Our approach, named histogram of oriented point cloud vectors (HOPC), is based on a new descriptor computed only from depth images. The segmented depth image is mapped into a 3D point cloud and divided into subspaces. In each subspace, 3D point vectors are mapped into their spherical coordinates around its centroid. Next, it is computed their orientations angles $$H_\varphi $$ H φ and $$H_\theta $$ H θ onto two cumulative histograms. Normalized histograms are concatenated to form the image descriptor and used to train a Support Vector Machine classifier (SVM). To assess the feasibility of our approach, we evaluated it on a public data-set of American Sign Language (ASL) composed of more than 60,000 images. Our experiments showed a recognition accuracy average of 99.46%, achieving the state of the art.

The turnover rate of personnel in companies in the service sector is approximately 10%. In Peru, this figure is above 15%, which generates high cost overruns for organizations. Companies with the highest turnover are the service companies, and the operational staff is regarded the key factor of these organizations. Previous research has been carried out on this issue, and the solutions are models with the objective of retaining employees, using Employer Branding, Endomarketing, and Talent Management techniques. However, for this study, a model based on the combination of these techniques was designed and applied. Thus, it is intended that the model managed to meet the concerns raised and to reduce costs in companies. The model was applied in a company in the fast food sector, aiming the frontline/operational personnel of the organization. The results showed that an agile recruitment process and development of personnel training significantly reduces high rates of personnel turnover and the costs presented by this. Additionally, it is proven that the leadership of store managers plays an important role in increasing employee satisfaction and commitment within the organization.

To make the purchase or sale of a product through the internet, an intermediary is needed to validate certain operations, which make the products more expensive; according to INEI (National Institute of Statistics and Informatics), 68% of Peruvian agricultural sector distrusts the use of the internet for the sale of their products, so it is unlikely that they will carry out certain operations over the internet. As a result, two emerging technologies were created that offer new opportunities for the design of decentralized markets, allowing to increase the security of transactions, saving money by not depending on an intermediary, increasing the confidence of farmers and ensuring transparency and immutability of each transaction; these technologies are the Smart Contracts and Blockchain. They are technologies store information in a shared and transparent system for all the members; likewise, that the records of transactions cannot be altered, thus ensuring the transparency and immutability of the information. This document proposes a model that uses the Smart Contract and Blockchain technologies applied in the Peruvian agricultural business sector, which allows both the buyer and seller to commercialize agricultural products.

The identification of patients within medical institutions is an important issue to provide better care in health centers and avoid identity personifications. The risk of medical identity theft is one important factor for patient safety. Technologies are improving, such as fingerprints, atrial biometry or electrocardiograms to improve safety measures. However, biometric counterfeiting methods have increased and violated the security of these technological models. This article proposes a technological model of facial recognition to efficiently identify patients according to cognitive services in medical centers. The technological model was implemented in the UROGINEC clinic for the proof of concept. The results of the identification of the patient were successful with a precision percentage of 95.82 in an average of 3 s. This allowed the clinic to prevent identity theft with alert messages and improved the user experience within the medical institution.

In this paper, we propose a technology model of predictive analysis based on machine learning for the evaluation of credit risk. The model allows predicting the credit risk of a person based on the information held by an institution or non-traditional sources when deciding whether to grant a loan. In this context, the financial situation of borrowers and financial institutions is compromised. The complexity of this problem can be simplified using new technologies such as Machine Learning in a Cloud Computing platform. Azure was used as a tool to validate the technological model of predictive analysis and determine the credit risk of a client. The proposed model used the Two-Class Boosted Decision Tree algorithm that gave us a greater AUC of 93% accuracy, this indicator was taken as having greater repercussion in the proof of concept developed because it is wanted to predict more urgently the number of possible applicants who do not comply with the payment of debits.

This article will bring an analysis of the electric power quality of the Electronic Laboratory of the Federal University of Tocantins. The proposed methodology was developed in two stages. The first one consists of obtaining the database through the acquisition of the oscillography images of the electrical network, in which the Laboratory is inserted using Fluke Power Log equipment. These images were recorded in the 34-h period, where there were moments of use and disuse of the Laboratory. In the second stage of the methodology, an algorithm was developed to read the input data (oscillography of the created database), to detect possible anomalies, to classify them, to generate a report showing the events occurred and to propose specific solutions. This algorithm is one of the most recent Artificial Intelligence in the bibliography, called the Artificial Immunological System. In order to perform the detection of the disturbances, the input signals were scanned, and through this process, these data are separated in periods, compared to a set of detectors previously established to finally assess the affinity between they. Therefore, this research aims to present a method based on Artificial Intelligence that helps in the correction of voltage events, providing greater reliability and quality of electric energy.

This article describes a prototype of an electric power meter in the monophasic and biphasic levels. Its purpose is to monitor residential consumption, based on a low-cost microcontroller, which through sensors can obtain the current and voltage values to find the variants of power and cost. The communication is established through a web server that is developed in the C language in conjunction with the Arduino libraries.

Operation research concepts can help healthcare facilities with unplanned situations, crisis, and handling of supplies, utilities, and strategies. A methodology for dealing with the Man-Hour (MH) distribution in a cellular type Healthcare Organization (HCO) is introduced, and its goal is to maximize the use of resources and workforce. The problem is modeled via Linear Programming (LP), which results in a minimal cost flow problem with the simplex algorithm. The proposed framework (MCFP) can motivate individuals, reward ability and individual knowledge (not only moneywise) plus improving patient care. Such model can help to devise a software tool for decision making with performance and efficiency; it brings direct profit for the HCO and its staff due to the superior management of their MHs, and it increases the benefits to the community they serve. The methodology models MHs in an HCO to optimize management, decision-making tasks, and resource distribution.

Environmental education is becoming a topic increasingly addressed in society, being of extreme importance for the participation of the individual in the midst of a community. Since the 1760s, with the Industrial Revolution, man began the degradation of the environment as a source of natural resources for the rapid production of the industrial means of the time, generating a great problem with different types of pollution in the world, among them the management of solid waste. It was only in the mid-1970s that this vision began to be changed. In Brazil, after many years, the National Policy on Solid Waste (Law 12,305 of 2010) was instituted aiming at the non-generation, reduction, reuse and adequate final destination in a way that does not harm the environment. The problem of waste only grows each year, generating concern about the future. n this way, environmental education enters as an instrument of awareness of people from the influence of individuals with society. Therefore, this work was developed for children, in the case students of the Pio XII Application School, aiming at the reduction and adequate management of solid waste, applying a suitable environmental education for a significant change of behavior from the creation of materials (primer and games easy to understand issues related to solid waste management.

Mathematics is a discipline much feared by most students in schools. Handing out strategies to demystify this discipline through interdisciplinarity, that is, to show how mathematics can be used in other branches of knowledge is our goal. Thinking about this issue, we developed the POEMATHICS Project as an alternative activity for the teaching of mathematics allied to the Portuguese language teaching. This initiative consists of relating the mathematics with the written language. Students should develop poems, poetry, texts, stories, music, etc., using mathematical terms and ideas. To promote this activity is necessary the participation of teachers of a language (this work deals with English examples and a workshop done in Portuguese) and Mathematics so that students can be accompanied and together awaken the pleasure of learning as well as improving math and linguistic skills.