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Integrated pest management (IPM) seeks to minimize the environmental impact of pesticide application, and reduce risks to human and animal health. IPM is based on two important aspects – prevention and monitoring of diseases and insect pests – which today are being assisted by sensing and artificial-intelligence (AI) techniques. In this paper, we surveyed the detection and diagnosis, with AI, of diseases and insect pests, in cotton, which have been published between 2014 and 2021. This research is a systematic literature review. The results show that AI techniques were employed – mainly – in the context of (i) classification, (ii) image segmentation and (iii) feature extraction. The most used algorithms, in classification, were support vector machines, fuzzy inference, back-propagation neural-networks and recently, convolutional neural networks; in image segmentation,k-means was the most used; and, in feature extraction, histogram of oriented gradients, partial least-square regression, discrete wavelet transform and enhanced particle-swarm optimization were equally used. The most used sensing techniques were cameras, and field sensors such as temperature and humidity sensors. The most investigated insect pest was the whitefly, and the disease was root rot. Finally, this paper presents future works related to the use of AI and sensing techniques, to manage diseases and insect pests, in cotton; for instance, implement diagnostic, predictive and prescriptive models to know when and where the diseases and insect pests will attack and make strategies to control them.

El profesorado, es un factor de mucha importancia para el proceso educativo, como tal requiere de una mirada desde una perspectiva pedagógica y orientación de calidad en la formación inicial. Su calidad profesional como resultado de su formación eficiente, será una garantía fundamental para que pueda insertarse en el mercado laboral de la educación; teniendo esta orientación fue necesario conocer en qué medida, como institución formadora estamos contribuyendo a la formación de futuros formadores, motivo por el que se ha previsto como objetivo, determinar cómo la formación inicial docente, garantiza la inserción laboral de los egresados de la Facultad de Ciencias de la Educación. Se ha planteado como hipótesis, que la formación inicial docente, garantiza la inserción laboral de los egresados de la Facultad de Ciencias de la Educación; se determinó como nivel de investigación descriptiva y de diseño no experimental, en vista que estaba orientada a conocer la inserción laboral de los egresados de la Facultad de Ciencias de la Educación, como consecuencia de la formación inicial. Le corresponde método analítico, en vista que una vez obtenida la información respecto a la inserción laboral de los egresados, se logró analizar las fortalezas y debilidades en el proceso de formación. La población con que se trabajó estaba constituida por egresados de 2015 a 2018 de la Facultad de Ciencias de la Educación y la muestra por los egresados titulado de las Escuelas Profesionales de Educación Inicial, Primaria y Física. Se concluye que, la formación inicial docente desarrolladas en las Escuelas Profesionales de Educación Inicial, Primaria y Física; si garantizan la inserción laboral de sus egresados titulados en los años 2015, 2016, 2017 y 2018. Las tablas 1, 4, 7 y 10 evidencian objetivamente los porcentajes significativos de egresados que se insertaron al mercado laboral en instituciones educativas públicas y privadas tanto en condición de nombrados y contratados.

Industry 4.0 has gained drive in the last few years since most companies at the industrial level need to update and optimize their production chain. Restructuring their processes and improving their human resources skills is imperative if they want to remain competitive. This research presents the development of a virtual reality system for induction motor troubleshooting training. Two sample groups were taken as references. The first one was trained with the VR system, while the second group worked with a conventional methodology. With the use of the proposed system, there was a time reduction of 57.73%. In terms of knowledge acquisition, it was possible to confirm, with a p-value lower than 0.05, that the VR system is more efficient than the conventional methodology. Finally, the system’s usability was evaluated utilizing the System Usability Scale (SUS), obtaining an average value of 73.33.

Education has not evolved as it should, teaching-learning processes are orthodox and do not allow the total development of the student. This panorama is presented in all areas of learning, however, when speaking of exact sciences such as mathematics or physics these problems are more serious. For these reasons, this article proposes the development of a virtual reality system focused on the teaching of mathematics. This educational system is based on the Singapore method, whose benefits allow students to develop their potential and creativity, guiding them to the solution of real-life mathematical problems through reasoning and deduction processes. It also uses a HMD (head mounted display) and visual feedback in order to improve user immersion and generate a correct learning process. The present study has been applied in an educational unit of Ambato-Ecuador. Results showed a significant improvement in grades, for example, there was a 29.93% reduction in the number of students with grades in the range between 4.00 and 6.00, there was an increase of 27,02 % of students with grades in the range between 7.01 and 8.99 and an increase of 2.71 % of students with grades between 9.00 and 10.00.

This essay aims to offer a new interpretation of the manuscript and print tradition of Garcilaso de la Vega’s sonnet 35, on the basis of a close analysis of its textual variants. Since Venezia Marciana It. IX, 137 ms precedes the 1574 editio princeps, we may rea-sonably assume that the three surviving witnesses contain different authorial variants of a rather fluid text Il contributo offre una diversa interpretazione della tradizione manoscritta e a stampa del sonetto 35 di Garcilaso de la Vega, proponendo, sulla base del riesame delle varian-ti e della dimostrabile anteriorità del ms. Venezia Marciana It. IX, 137 rispetto alla princeps del 1574, di assumere i tre testimoni come redazioni d’autore in progress ricon-ducibili a originali in movimento

A model for the dynamic behavior of an Euler-Bernoulli beam on a frictional-elastic foundation under the action of a uniformly moving concentrated load is presented. The frictional part of the foundation’s behavior is of the Coulomb type distributed over the beam’s length and may represent the dissipative behavior due to the frictional sliding between the aggregates composing railway ballasts. Critical velocities, energy balances and dynamic amplification factors are computed based on a formulation and a numeric algorithm that take into account the nonsmooth character of friction.

This paper analyses the dynamic behavior of Euler-Bernoulli beams on elastic foundations of the Winkler type submitted to moving loads. In particular, the usefulness of passive frictional damping devices, that present ecological and economic advantages with respect to viscous ones, in the context of minimizing the consequences of resonance phenomena is studied. A program in Matlab environment based on the finite element method (FEM) that simulates the dynamic behavior of the beam, foundation and frictional damping devices driven by a moving load, is developed and used to study the effect of the frictional dissipation on the values of the critical velocities and dynamic amplifications. The time integration of the global equations of the motion is performed using the nonsmooth contact dynamics method (NSCD) with persistent contact, especially conceived for friction problems which are governed by a nonsmooth constitutive law.

Personnel training is a continuous process that must be focused according to the needs of each industry. The denominated “learning tools” arise, which due to their self-explanatory and easy to use, allow personnel to acquire new skills and to improve their technical performance. Within these new tools of industrial learning, is the virtual reality (VR), whose functionality allows us to train personnel in order to solve emerging problems during the work process and overcome obstacles on the way to the next stage of the process. The development of virtual reality systems must adopt characteristics of software development methodologies. In this paper the application of an Agile Development Process for virtual reality training systems focused on the calibration, connection and assembly of HART transmitters in Oil and Gas Facilities is described.

Grease lubricants are extensively used in contacts, usually to reduce friction and wear. Under small amplitude sliding, however, as in rolling systems subject to vibration, there is significant lubricant decay. The present study analyses the fretting sliding response of two grease lubricants subjected to small (i.e. partial slip) and large displacement amplitude (i.e. gross slip fretting). Tribological behavior and associated wear volume were investigated as a function of displacement amplitude. The investigation confirmed that, below a threshold displacement amplitude, scarce lubrication induced significant wear activation, while, above threshold, low friction and a low wear response were observed. A new effective friction energy wear concept is introduced to quantify wear rate whatever the fretting sliding condition.

Today, to cope with the complexity of the global organization, the industrial company needs to be more structured. New processes have to be developed due to more and more ambitious quality requirements. A new problematic arises: what is needed to offer to all customers a product that meets the quality requirements of a local market? The main objective of this paper is to propose a quality requirements allocation method that matches the market specifications and the customer satisfaction. This is in contrast with the traditional allocation methods which are often time-consuming to implement or do not focus on the customer satisfaction for the definition of the quality targets. The proposed method is inspired from reliability allocation method and is formulated as a feasibility problem. In this context the notion of optimality of the solution is not being sought, the objective is “only” to find out a solution that satisfies the global target quality. This allows determining some local quality targets in accordance with industrial data.

This article introduces an extension of standard geometric programming (GP) problems, called quasi geometric programming (QGP) problems. The idea behind QGP is very simple, it means that a problem becomes a GP problem when some variables are kept constant. The consideration of this particular kind of nonlinear and possibly non-smooth optimization problem is motivated by the fact that many engineering problems can be formulated, or well approximated, as a QGP problem. However, solving a QGP problem remains a difficult task due to its intrinsic nonconvex nature. This is why this article introduces some simple approaches for easily solving this kind of nonconvex problem. The interesting thing is that the proposed methods do not require the development of a customized solver and work well with any existing solver able to solve conventional GP problems. Some considerations on the robustness issue are also presented. Various optimization problems are considered to illustrate the ability of the proposed methods ...

This paper is concerned with solving nonconvex optimization problems arising in various engineering sciences. In particular, we focus on the design of a robust flux estimator of induction machines and the optimal design of on-chip spiral inductors. To solve these problems, a recently developed optimization method, called the heuristic Kalman algorithm (HKA), is employed. The principle of HKA is to explicitly consider the optimization problem as a measurement process designed to give an estimate of the optimum. A specific procedure, based on the Kalman estimator, was developed to improve the quality of the estimate obtained through the measurement process. The main advantage of HKA, compared to other stochastic optimization methods, lies in the small number of parameters that need to be set by the user. Based on HKA a simple but effective design strategy for robust flux estimator and on-chip spiral inductors is developed. Numerical studies are conducted to demonstrate the validity of the proposed design procedure.

This paper presents a simple but effective tuning strategy for robust static output feedback (SOF) controllers with minimal quadratic cost in the context of multiple parametric uncertainties. Finding this type of controller is known to be computationally intractable using conventional techniques. This is mainly due to the non-convexity of the resulting control problem, which has a fixed structure. To solve this kind of control problem easily and directly, without using any complicated mathematical manipulations, we utilize Kharitonov's theorem and an evolutionary algorithm (EA) for the resolution of the underlying constrained optimization problem. Using Kharitonov's theorem, a family of bounded, robustly stable static output feedback controllers can be defined and EA is used to select the controller that ensures a minimal quadratic cost within this family. The resulting tuning strategy is applicable to both stable and unstable systems, without any limitations on the order of the process to be controlled. A numerical study was conducted to demonstrate the validity of the proposed tuning procedure.

In this work a new optimization method, called the heuristic Kalman algorithm (HKA), is presented. This new algorithm is proposed as an alternative approach for solving continuous, non-convex optimization problems. The principle of HKA is to explicitly consider the optimization problem as a measurement process designed to give an estimate of the optimum. A specific procedure, based on the Kalman estimator, was developed to improve the quality of the estimate obtained through the measurement process. The main advantage of HKA, compared to other metaheuristics, lies in the small number of parameters that need to be set by the user. Further, it is shown that HKA converges almost surely to a near-optimal solution. The efficiency of HKA was evaluated in detail using several non-convex test problems, both in the unconstrained and constrained cases. The results were then compared to those obtained via other metaheuristics. The numerical experiments show that HKA is a promising approach for solving non-convex optimization problems, particularly in terms of computation time and success ratio.

This paper presents a new dynamic reliability approach which is able to take into account the various operating conditions under which the considered system has evolved (past and present). To this end, we propose a differential model of failure rate, combined with the state space representation of the process, as well as a parameterization procedure. A numerical example shows the practical applicability of the proposed approach.

Agricultural vehicle manufacturers are employing new semi-active cab suspensions using Magnetorheological (MR) technology. The use of MR technology in cab suspensions is a logical next step in improving operator safety and comfort. The speed and simplicity of MR technology enables the use of low-stiffness springs without the compromise between ride and stability, and can provide roll, isolation and pitch stability. MR fluids are materials that respond to a magnetic field with a dramatic change in rheological behavior. These fluids can reversibly change instantaneously from a free-flowing liquid to a semi-solid with controllable yield strength when exposed to a magnetic field. MR systems have been developed with a modular, integrated approach that can include a damper containing MR fluid, air spring, automatic electronic leveling, sensors, controller, and CANbus data communication.

This paper presents an effective method to design a PID (or PI) controller for nonlinear systems where desirable robustness and performance properties must be maintained across a large range of operating conditions. For this purpose, an uncertain multimodel of the original nonlinear system is used. The uncertainties affecting the system are treated as stochastic matrices. Based on this multimodel representation a robust PID controller can be designed in order to obtain acceptable performance for all operating conditions. Numerical examples show the practical applicability of the proposed method.

In this paper, we investigate the problem of robust synthesis of a static output feedback controller, with guaranteed quadratic cost, in the context of multiple parametric uncertainties. To solve this problem, a random optimization technique based on a bisection method is proposed. The principle is as follows: for a given initial stabilizing controller of the nominal system, the proposed approach iteratively generates a sequence of matrices with a decreasing quadratic cost. Using a bisection method, this procedure is stopped when the controller reaches the best possible nominal performance that satisfies a given guaranteed quadratic cost. A numerical example shows the practical applicability of the proposed method.

In this paper, we investigate the problem of robust synthesis of a static output feedback controller, with guaranteed H2∕H∞ cost, in the context of multiple parametric uncertainties. To solve this problem, a random optimization technique based on a bisection method is proposed. The principle is as follows: For a given initial stabilizing controller of the nominal system, the proposed approach iteratively generates a sequence of matrices with a decreasing H2∕H∞ cost. By a bisection method, this procedure is stopped when the controller reaches the best possible nominal performance that satisfies a given guaranteed H2∕H∞ cost. Numerical examples show the practical applicability of the proposed method.

Magnetorheological (MR) fluid is a functional, smart or controllable fluid, which responds to magnetic field, changing its rheological properties. The increased resistance to flow of an MR fluid is proportional to the strength of magnetic fi eld. A typical MR fluid consists of iron particles, suspended in a carrier liquid such as synthetic oil or water. Proprietary additives, to discourage gravitational settling and promote particle suspension, are added to enhance lubricity, modify viscosity, and inhibit wear. In recent years devices and systems using MR fluid technology have been commercialized across wide industry applications, including automotive, industrial and civil engineering. In that development two key issues for the commercial success of MR fluid technology-durability and settling-have shown continual improvement as a result of formulation research. As a result, MR fluids today are strong, durable, adaptable and highly developed with fundamental material data and device design and models.

The aim of thid paper is to present a general method of nonlinear control system by nonlinear state feedback. For this purpose, a global stabilization method is proposed based on the Krasovskij functions. Sufficient conditions of stability are given. However, the general resolution of this problem leads to a nonlinear system of partial derivative equations, which are difficult to solve. To overcome this difficulty a global nonlinear function equivalent, locally, to a control by linear state feedback is used. The implementation of this approach is illustrated with an industrial example: the control position of a pneumatic jack. The modeling of this system leads to a nonlinear state model. The results presented shows the invariance of the dynamic and static perfonnances in relation to the operating point.

The aim of this paper is to present a general method of a nonlinear control system by fuzzy supervision of a conventional control. This approach belongs to the class of methods based on the use of the linearized system. The particularity of this work lies in the proposed algorithms to realize the parametric adaptation of control law and running equilibrium estimation. These two aspects have been solved by the use of a fuzzy supervisor based on a Takagi-Sugeno rules. The rules bases are built by the knowledge of the gains and the equilibrium, for a fixed number of operating points. The gains are calculated using a local synthesis by poles placement. The implementation of this method is presented on a real example for which a generator of reference trajectory is presented. The results available are compared with the ones obtained by use of Isidori linearizing control method and lead to the validation of this method.

The aim of this paper is to present a classifier based on a fuzzy inference system, the final decision being made with the help of a thresholder. For this classifier, a parameterization method which is not necessarily based on an iterative training is presented. This approach can be seen as a pre-parameterization of the classifier which allows the building up of a base set of rules, and initialise the parameters of membership function. A continuous and derivable version of the previous classifier is also presented. For this last classifier an iterative learning algorithm based on a gradient method is suggested. An example using the learning basis IRIS, which is a benchmark for the problems of classification, is presented. This example allows us to compare the performance of this classifier with the works of other authors. Finally this classifier is applied to the diagnosis of a D.C. motor showing the utility of this method.

A 35-year-old man suffered simultaneously from nodular sclerosis Hodgkin's disease (HD), Langerhans' cell histiocytosis and multiple myeloma (MM). There was no prior history of irradiation or chemotherapy, and clinically the lymphoma was confined to cervical lymph nodes. Immunohistochemically, neoplastic lymphoma cells reacted with CD15 and CD30 markers. The patient's bone marrow exhibited a diffuse infiltration by rather atypical plasma cells showing kappa immunoglobulin light-chain restriction. At 14 months after the diagnosis, after autologous bone marrow transplantation, the clinical evolution is favourable with complete remission of the diseases. This is the first time that the coexistence of these three haematological disorders has been discussed, and only the fourth documented case of simultaneous HD and MM. Speculations about the significance of this finding are discussed.

Summary The development of a large-cell non-Hodgkin's lymphoma in a patient suffering from chronic lymphocytic leukaemia is known as Richter's syndrome, representing one of the possible anaplastic transformations of the leukaemia. Cutaneous involvement is an extremely rare event. The case of a 45-year-old man with B-cell chronic lymphocytic leukaemia is reported. Five years later multiple cutaneous nodules developed on his extremities. Biopsies of the skin showed a diffuse large-cell lymphoma, bearing the same cell surface immunoglobulin light chain isotype as the leukaemia, suggesting the original relationship between both neoplasms.

Broadening functionality of artificial intelligence and machine learning techniques shows that they are very useful computational intelligence methods. In the present study the potential of various artificial intelligence techniques to predict and analyze the damage is investigated. Pre-treated experimental data was used to determine the wear of contacting surfaces as a criterion of damage that can be useful for a life-time prediction. The benefit of acquired knowledge can be crucial for the industrial expert systems and the scientific feature extraction that cannot be underestimated. Wear is a very complex and partially formalized phenomenon involving numerous parameters and damage mechanisms. To correlate the working conditions with the state of contacting bodies and to define damage mechanisms different techniques are used. Neural network structures are implemented to learn from experimental data, genetic programming to find a formula describing the wear volume and fuzzy inference system to impose physically meaningful rules. To gain data for the creation and verification of the model, experiments were conducted on commonly used chromium steel under dry and base oil bath-lubricated fretting test apparatus. Decisive factors for a comparison of used AI techniques are their: performance, generalization capabilities, complexity and time-consumption. Optimization of the structure of the model is done to reach high robustness of field applications.

Con l’edizione critica procurata da Cesare Bozzetti nel 1980 le Rime di Galeazzo di Tarsia hanno conseguito una sistemazione inappuntabile sotto il profilo testuale, mentre sul piano dell’esegesi l’alone di mistero che circondo la vita del poeta, nonostante la benemerita ricostruzione offertane con dovizia di corredo documen tale da Carlo De Frede, oppone ancora in piu punti notevoli resistenze a una pacifica interpretazione, sicche in alcuni casi esse continuano a rimanere «disperate», secon...

The main objective of this paper is to present a new optimization approach, which we call heuristic Kalman algorithm (HKA). We propose it as a viable approach for solving continuous nonconvex optimization problems. The principle of the proposed approach is to consider explicitly the optimization problem as a measurement process designed to produce an estimate of the optimum. A specific procedure, based on the Kalman method, was developed to improve the quality of the estimate obtained through the measurement process. The efficiency of HKA is evaluated in detail through several nonconvex test problems, both in the unconstrained and constrained cases. The results are then compared to those obtained via other metaheuristics. These various numerical experiments show that the HKA has very interesting potentialities for solving nonconvex optimization problems, notably concerning the computation time and the success ratio.

Multipurpose contact lens care products have been developed to provide wearers with simpler lens care regimens. Although previous studies have shown that the multipurpose products can be formulated without increasing the risk of irritation or other adverse reactions, questions still remain regarding the effectiveness of multipurpose products that are labeled with cleaning indications. The following is a report of a 3-month study conducted to compare two approved surfactant contact lens cleaning products (Bausch & Lomb® ReNu® Multi-Purpose Solution and Alcon® Opti-Clean® II Daily Cleaner) when used in the care of soft (hydrophilic) contact lenses worn for daily or extended wear. Patients (N = 181) used the study surfactant lens cleaning products in conjunction with their current lens care regimens in a paired-lens, left-eye/right-eye comparison. Quantitative analysis of lens protein uptake levels (ninhydrin test) and microscopic examination showed no significant differences between lenses cleaned with the ReNu Multi-Purpose Solution and the Opti-Clean II Daily cleaner. We conclude that the clinical performance of the ReNu Multi-Purpose Solution is equivalent to that of the Opti-Clean II Daily Cleaner.

The industrial demand for higher reliability of various components is one of the main flywheels of the research and development in the field of modelling of complex phenomena. There is a need to characterize the wear behaviour of the interface under fretting wear conditions in ball bearing application. Pre-treated experimental data was used to determine the wear of contacting surfaces as a criterion of damage that can be useful for a life-time prediction. The benefit of acquired knowledge can be crucial for the industrial expert systems and the scientific feature extraction that cannot be underestimated. Wear is a very complex and partially-formalized phenomenon involving numerous parameters and damage mechanisms. To correlate the working conditions with the state of contacting bodies and to define damage mechanisms different techniques are used. The use of our approaches in the prediction of the response of the system to different test conditions is validated. Two physical models, based on Archard and Energetic approach, are compared with artificial neural network model and genetic programming. Decisive factors for a comparison of used AI techniques are their: performance, generalization capabilities, complexity and time-consumption. Optimization of the structure of the model is done to reach high robustness of field applications. Finally, application of the wear level information to forecast a probability of damage is presented.

Changes in the amplitude of Hoffmann reflex (H-reflex) may reflect variations in the characteristics of the largely monosynaptic circuitry that is explored and are a possible target for diagnostic and physical therapeutic intervention. However, previous attempts to induce predictable changes in the H-reflex amplitude by transcutaneous electrical nervous stimulation (TENS) have generally failed. Previous workers applied fixed frequency in the low- (2-5 Hz) or in the high- (100 Hz) field, but they did not attempt to vary frequency and/or impulse duration in time.We evaluated the effect of a new type of painless electric stimulation, i.e. frequency rhythmic electrical modulation system (FREMS). FREMS is characterized by the use of transcutaneous electric pulses with sequentially modulated frequency (f: 1-39 Hz) and width (w: 10-40 micro s) at constant, perceptive threshold voltage (approximately 150 V). FREMS was applied at the abductor hallucis muscle (AHM), as conditioning stimulus of the H-reflex which was recorded ipsilaterally at the soleus muscle, according to the classic method, in 10 normal volunteers (age range 21-40 years).H-reflex amplitude was substantially decreased (-50%) during FREMS and H-reflex amplitude variations were influenced by w/f variation in time during FREMS subphase C in a predictable way (r(2)=0.43; P0.001). Our results suggest an effective ability of FREMS to modulate H reflex amplitude.The ability to achieve large and predictable changes of the H-reflex amplitude simply by modulating both frequency and duration of a conditioning painless electrical stimulation offers new possibilities for the treatment of diseases characterized by motoneuron excitability abnormalities.

This paper presents a simple but effective method for finding a robust output feedback controller via a random search algorithm. The convergence of this algorithm can be guaranteed. Moreover, the probability to find a solution as well as the number of random trials can be estimated. The robustness of the closed-loop system is improved by the minimization of a given cost function reflecting the performance of the controller for a set of plants. Simulation studies are used to demonstrate the effectiveness of the proposed method.

During the last several years there have been developed many systems which are able to simulate the human brain behavior. To achieve this goal, two of the most important paradigms used, are the Neural Networks and the Artificial Intelligence. Both of them are primary tools for development of systems to capable of performing tasks such as: handwritten characters, voice, faces, signatures recognition and so many other biometric applications that have attracted considerable attention during the last few years. In this paper a new algorithm for cursive handwritten characters recognition based on the Spline function is proposed, in which the inverse order of the handwritten character construction task will be used to recognize the character. From the sampled data obtained by using a digitizer board, the sequence of the most significant points (optimal knots) of the handwriting character will be obtain, and then the natural Spline function and the steepest descent method will be used to interpolate and approximate character shape, Using a training set consisting of the sequence of optimal knots, each character model will be constructed. Finally the unknown input character will be compared by all characters models to get the similitude scores. The character model with higher similitude score will be considered as the recognized character of the input data. The proposed system is evaluated by computer simulation and simulation results show the global recognition rate with 93.5%.