Adequacy Degree Research Articles

Adecuación de la utilización de albúmina intravenosa en los pacientes ingresados en las unidades de hospitalización

Background and objectiveThe use of albumin is widespread and its use in many settings is still under debate. Frequently, inappropriate use is made in because of an analytical finding of hypoalbuminemia and / or in situations in which an attempt is made to correct a deficient nutritional status. In this study, the use of albumin in the hospitalized patient is analyzed, and evaluates the adequacy degree of its prescription to current recommendations. Methods and materialsRetrospective cross-sectional observational study conducted in a six-month secondary hospital. A review of intravenous albumin prescriptions of patients admitted to inpatient units was conducted. ResultsA total of 77 patients were included. The most prescribed appropriate indication was ascitic-hepatic syndrome (40%). In 39%, treatment with albumin was not indicated, observing in 22% that the justification for the prescription was only the analytical finding of hypoalbuminemia. The adequacy degree was significantly higher in the medical services than in the surgical ones (p < 0.005). The highest adequacy degree was found in patients admitted to digestive medicine, while in internal medicine and surgery the adequacy was lower (p < 0.005). ConclusionsThe use of albumin in our hospital has a wide margin of improvement, about 40% of the patients the prescriptions did not adjust to the recommendations of the clinical practice guidelines.

Assessing exception handling testing practices in open-source libraries

Modern programming languages (e.g., Java and C#) provide features to separate error-handling code from regular code, seeking to enhance software comprehensibility and maintainability. Nevertheless, the way exception handling (EH) code is structured in such languages may lead to multiple, different, and complex control flows, which may affect the software testability. Previous studies have reported that EH code is typically neglected, not well tested, and its misuse can lead to reliability degradation and catastrophic failures. However, little is known about the relationship between testing practices and EH testing effectiveness. In this exploratory study, we (i) measured the adequacy degree of EH testing concerning code coverage (instruction, branch, and method) criteria; and (ii) evaluated the effectiveness of the EH testing by measuring its capability to detect artificially injected faults (i.e., mutants) using 7 EH mutation operators. Our study was performed using test suites of 27 long-lived Java libraries from open-source ecosystems. Our results show that instructions and branches within catch blocks and throw instructions are less covered, with statistical significance, than the overall instructions and branches. Nevertheless, most of the studied libraries presented test suites capable of detecting more than 70% of the injected faults. From a total of 12,331 mutants created in this study, the test suites were able to detect 68% of them.

An intelligent sliding mode controller based on LAMDA for a class of SISO uncertain systems

This paper presents a new intelligent sliding mode controller based on LAMDA (Learning Algorithm for Multivariate Data Analysis), a fuzzy method used for supervised and unsupervised learning applicable to the detection of functional systemic states. LAMDA computes the Global Adequacy Degree (GAD) of an object to a class or functional state to determine its degree of similarity. An inference stage has been added to LAMDA to make it work as a controller, in combination with the basic features of a sliding mode control (SMC) and Lyapunov stability theory. The novelty of this proposal is that we have used the LAMDA algorithm to compute the SMC continuous and discontinuous control actions to obtain a chattering-free controller, which can then be applied to a class of SISO systems with variable dynamics and model uncertainties. Simulations on two nonlinear chemical processes have validated the proposal: 1) control of a continuous stirred tank reactor (CSTR) under bounded disturbances and reference changes, and 2) regulation of a mixing tank with variable parameters (variable dynamics). The experiments are compared with other control techniques, demonstrating that the proposed method can accurately control the tanks, improving the results in performance, robustness, and disturbance rejection.

Protocolo para avaliação de boas práticas de manejo na piscicultura no estado do Pará: um estudo de caso

Este estudo objetivou propor um protocolo para avaliação de boas práticas de manejo (BPM) na piscicultura. Para tanto, criou-se um protocolo inicial por meio de levantamento bibliográfico, observações em campo e entrevistas com piscicultores acerca do manejo em 32 pisciculturas comerciais no estado do Pará, para determinar os pontos passíveis de intervenções de baixa complexidade e custo reduzido. Posteriormente, foram definidos 21 procedimentos para compor o protocolo com as seguintes etapas: transporte, povoamento, biometria, manejo alimentar, qualidade da água e despesca. Para utilização, cada empreendimento deve ter seus procedimentos pontuados em 0 (zero), quando não cumpre o padrão estabelecido, ou 1 (um), quando cumpre. A soma das médias das respostas em cada etapa indica o grau de adequação do empreendimento em: pouco adequada (0 a 2), potencialmente adequada (2,1 a 4) ou adequada (4,1 a 6). Espera-se que o protocolo sugerido auxilie piscicultores na adoção de boas práticas de manejo, contribuindo para melhorar a adequação de seus empreendimentos.

LAMDA-HAD, an Extension to the LAMDA Classifier in the Context of Supervised Learning

This paper proposes a new approach to improve the performance of Learning Algorithm for Multivariable Data Analysis (LAMDA). This algorithm can be used for supervised and unsupervised learning, based on the calculation of the Global Adequacy Degree (GAD) of one individual to a class, through the contributions of all its descriptors. LAMDA has the capability of creating new classes after the training stage. If an individual does not have enough similarity to the preexisting classes, it is evaluated with respect to a threshold called the Non-Informative Class (NIC), this being the novelty of the algorithm. However, LAMDA has problems making good classifications, either because the NIC is constant for all classes, or because the GAD calculation is unreliable. In this work, its efficiency is improved by two strategies, the first one, by the calculation of adaptable NICs for each class, which prevents that correctly classified individuals create new classes; and the second one, by computing the Higher Adequacy Degree (HAD), which grants more robustness to the algorithm. LAMDA-HAD is validated by applying it in different benchmarks and comparing it with LAMDA and other classifiers, through a statistical analysis to determinate the cases in which our algorithm presents a better performance.

Two-dimensional motion equations in water flow zone

The paper studies a two-dimensional water flow from a non-pressure rectangular or round pipe placed into a wide horizontal channel. To simplify the problem, the real three-dimensional flow is modeled as a two-dimensional zone by eliminating the liquid particles’ velocities and accelerations in the direction perpendicular to the flow zone. To describe the water flow motion law, L. Euler’s equations for the ideal fluid are used, taking into account the continuity equations and the Bernoulli equation. The two-dimensional flow models in the spreading zone with the adequacy degree sufficient for practice, describe the movement of water flows arising in the lower road drainage systems races, Liman irrigation systems, small bridges, water volley channels, various culverts and water-crossing facilities. The obtained dependences of the velocity distribution, depth and water flow geometry give an accuracy exceeding that known by the previously used methods both by the velocity values and by the boundary current lines geometry.

Adequacy Indicators Based on Pre-established Goals: An Implementation in a Colombian University

Key performance indicators are crucial for the strategic planning of both, public and private institutions. Composite indicators are a useful tool for conveying summary information about overall performance in a relatively simple way. The construction of these indicators implies several stages concerning collection of data, selection of criteria and individual indicators, normalization and weighting of criteria and indicators, aggregation and comparison of overall performance of the alternatives or options. However, due to the different nature of the decision criteria and indicators traditional normalization methods are not always suitable. This is the case in the proposal of composite indicators measuring students’ adequacy degree in higher education institutions. This concept involves several dimensions, criteria and individual indicators of diverse nature. In this paper, we try to overcome the normalization problems arising from this situation proposing a normalization method based on similarity of the options with an ideal target. Once indicators have been normalized, weights are determined and aggregation is conducted in an easy way allowing the overall assessment of the students in terms of their adequacy level. Based on this overall assessment an adequacy index is then proposed allowing classification of the students in three different groups reflecting different levels of difficulties in terms of their adequacy. Extra activities can be then planned by the institution in order to re-inforce the adequacy level of the students. The adequacy index proposal has been developed in the context of the Industrial University of Santander (Colombia).

On LAMDA clustering method based on typicality degree and intuitionistic fuzzy sets

The learning algorithm for multivariable data analysis (LAMDA) is a learning method to group or classify quantitative and qualitative historical data. LAMDA can be applied for self-learning and directed learning. Considering self-learning, LAMDA groups historical data through the global membership degrees of a sample with respect to a class, considering the contribution of all features for each sample. Such contribution is called marginal adequacy degree (MAD). To mix all MADs, several aggregation functions such as linear and geometrical connectives are used. The aggregation function calculates the global adequacy degree (GAD) of a sample with respect to a class. This procedure avoids assigning the class number as initial parameter due to that LAMDA applies an automatic threshold called non-informative class (NIC) which finds the best assignment of a portion of data to one class. One improvement for the LAMDA algorithm is the use of a full reinforcement operator called Yager–Rybalov Triple Pi, which can reduce the number of classes. However, this kind of solution ignores the degree to which one sample belongs to one class relative to all samples. Another limitation is that the classes reduction is not controlled by a parameter or an algorithm, which removes some classes required by a human expert. Such removed classes can be useful for the human expert in the data analysis of complex processes or for intelligent systems when the searching of additional information is required in decision-making. In this paper, the typicality degree and the intuitionistic fuzzy sets (IFSs) are used to propose one improvement of the LAMDA method in order to develop a strategy that avoids the loss of significant classes. This paper shows two functions: global typicality degree (GTD) and intuitionistic global adequacy degree (IGAD). By integrating both functions, a new function called typicality and intuitionistic global adequacy degree (TIGAD) is proposed. The proposal is applied in three study cases. The results show an improvement of clustering which were validated by the human expert and the information of data. Furthermore, the impact of the research is focused on data analysis, where the expert should make the best decision.

Design of a Generalized Predictive Controller for Temperature Control in a Cement Rotary Kiln

In this paper a generalized predictive controller (GPC) for effective control of clinkerization temperature in a cement rotary kiln is designed. By using methods for identification of dynamic systems a mathematical model of the plant under study is obtained, whose validation results showed a high adequacy degree. The design of the GPC controller is performed based on the mathematical model obtained. It is shown that the designed controller allows controlling the plant under study with a high accuracy considering different real industrial operation scenarios. The comparative simulation results of the control system with PID and GPC controllers showed a better performance when the GPC controller is applied.

Comunicación pública de la ciencia y ética periodística. La representación del bosón de Higgs

En este artículo, nos ocupamos de determinar el grado de adecuación de la representación del conocimiento a la ética periodística cuando se hace uso de imágenes que son el resultado de los hallazgos científicos. Para ello, analizamos la forma de presentar visualmente la información aparecida en prensa, concretamente en el diario El País, en relación al considerado el descubrimiento científico más relevante de los últimos tiempos: el bosón de Higgs. Los resultados de la investigación, muestran la estrategia de representación y comunicación pública del descubrimiento, así como la escasa observancia de los principios éticos mínimos en la práctica periodística en el proceso consolidación del supuesto hallazgo en el imaginario colectivo de la denominada “partícula de Dios”.

Identification of the Functions of Response to Loading for Stationary Systems

We investigate the solution to the parametric identification problem for loaded systems of differential equations. We propose to use iterative methods based on the first-order optimization methods. For this purpose, we obtain formulas for the gradient of the objective functional, which assesses the adequacy degree of the obtained parameters. The results of numerical solution to some test problems are given.

A new criterion to validate and improve the classification process of LAMDA algorithm applied to diesel engines

This work proposes a new criterion to validate and improve the classification efficiency of the Learning Algorithm Multivariable and Data Analysis (LAMDA) fuzzy algorithm, which is an algorithm that combines the concepts of neural networks architecture and fuzzy clustering. LAMDA is based on finding the Global Adequacy Degree (GAD) of one data (individual) to a class (functional state), considering the contributions of each descriptor or variable. LAMDA is capable of generating new classes after the training stage and it uses probability density functions (PDF) for the estimation of similarity analysis between classes in order to determine the grouping criterion. The LAMDA algorithm was used here to identify new functional states that were not included during the training stage. However, this algorithm induced significant uncertainties when the recognized classes, corresponding to engine operating modes, exhibited similar membership degree values (MDV). To solve this, a new criterion to validate functional states after recognition (LAMDA-FAR), based on the minimum and maximum distances among MDV was developed. Both LAMDA and LAMDA-FAR algorithms were used in supervised learning mode to classify a historical database obtained from an experimental mapping methodology of an automotive diesel engine operating under several steady state conditions. For each engine operating mode the engine speed (rpm), exhaust gas temperature (°C) and accelerator pedal position (%) were measured as the representative variables to carry out the classification. Both algorithms were trained with 70% of the historical database. The remaining 30% of the data, as well as new engine operating modes (not taken into account during the training stage), were used to validate classifier results. It was found that the LAMDA algorithm alone was unable to properly classify similar engine operating modes, while the LAMDA-FAR algorithm showed 100% efficiency for both known and unknown operating modes. This high efficiency and low computational cost tool can be used to improve engine control strategies based on experimental mapping methods, as well as to monitoring and controlling on-line vehicle performance.

Adequacy Degree between Supply and Demand for Intellectual Capital Information in the Annual Reports in an Emerging Country: The Tunisian Case

In the setting of this paper, we compare the usefulness perception of 42 items of voluntary information on intellectual capital of 22 Tunisian financial analysts and portfolios managers with the degree of their disclosure in the annual reports of 50 firms listed on the Stock Exchange Securities of Tunisia. The analysis is led on the primary data extracted from a survey and from secondary data extracted from annual reports. Given the purpose of our study, we developed a weighted disclosure index comparing the supply of information on intellectual capital in annual reports and user’s demand. Results highlight the existence of an important gap between the supply and the demand of voluntary information on intellectual capital. More specifically, the offer of the majority of information diverges completely with their demand by the Tunisian financial market.

Audit Of The Adequacy Degree For The Principle Of Activity Continuity

Abstract Our entire research concerning audit of the adequacy degree for the principle of continuity in the activity of an entity is based on the personal experience in auditing the financial statements and mainly on looking for a plausible answer to the following question: „Does the auditor opinion expressed in an Audit Report totally support the credibility assessment of financial statements?” The answer for this question is that „the Auditor report supports the assessment of financial statements but is not a warranty regarding the future viability of the economic agent”. This warranty, if the timing is not too optimistic, is insured by the action undertaken by the auditor in the direction of auditing of the degree of adequacy of the principle of activity continuity.

Diagnostics of electric transport traction electric machines

Improving the reliability of trolley traction motors can be achieved by further improving the traction motor design and their control parameters in the manufacture, repair and operation on the line. Technical diagnostics of traction motor parameters plays an important role in solving these problems.Known diagnostics methods of traction motors allow to detect their faults. But there is a need to improve these methods, taking into account the capabilities of modern measuring systems and information processing tools. This will allow to improve the performance indicators of urban electric transport enterprises due to improving the operational reliability of traction motors and extending their service life. The relevance of this problem is also caused by the tendency to increase the probability of correct and accurate diagnosis at various faults in electric machines.The operational reliability of trolley motors was comprehensively analyzed, and regularities of their parameters change during operation depending on several factors were determined in this paper. Mathematical modeling of traction motors to determine their parameters change during operation was conducted. An algorithm for diagnosing and determining the operational reliability of trolley traction motor elements using the boundary criteria was developed and the reliability calculation methods, allowing to predict failures of traction motor elements with a high adequacy degree were proposed. Practical recommendations for the rational selection of diagnostic parameters of traction motors were given.

Studies of diversity of benthic fauna of lakes in Mari El Republic by rank distribution method in perspectives of application to water quality biological benchmark

The dataset on benthic fauna diversity obtained by ecological monitoring of lakes (Mari El Republic) was analyzed for applicability in water quality biological benchmark. The effect of several parameters on biodiversity were tested: (1) calculation errors in species number definition, (2) application of certain evaluation method of rank distribution parameters, (3) adequacy degree of distribution model, (4) evenness: diversity ratio, (5) hydrochemical parameters of lake, and (6) “sampling site effect” (natural reserve area impact). The biodiversity characteristics were suggested, which highly correlated to obtained data. The critical level for each characteristic was proposed to define favorable and adverse conditions of benthic communities. Practical recommendations were given for using studied parameters in the evaluation of the water quality biological benchmark in Mari El Republic.

Numerical modeling of complex plastic deformation of metals along plane and spatial trajectories of arbitrary curvature and torsion

The mathematical model of thermoplasticity describing the processes of complex plastic deformation of structural materials (metals and their alloys) along plane and spatial trajectories of arbitrary curvature and torsion is developed. For evaluating the adequacy degree of constitutive relations of elastoplasticity and the range of their applicability, numerical investigations of complex plastic deformation (by the example of steel 45) along the trajectories having the form of a circle and the screw trajectories of constant curvature and torsion are carried out. The obtained numerical results are compared with the data of full-scale experiments. It is shown that the developed model of thermoplaciticity describes qualitatively and quantitatively the main effects of complex plastic deformation of metals under arbitrary non-proportional combined (P-q-M) force loading.

Construction of self-learning fuzzy controllers using autonomous adaptive control methodology

A method of constructing adaptive fuzzy controllers using autonomous adaptive control methodology is considered. Knowledge in the system is represented in the form of fuzzy production rules. New rules are automatically generated by clustering empirical data obtained using substractive method in the course of system operation. The system is adapted with application of a special quantity calculated for each rule, the “adequacy degree”, which specifies the weight of the rule in the course of control. The method developed can be used for constructing applied control systems of dynamic objects. This opportunity is shown experimentally using the problems of balancing an inverted pendulum and stabilizing the angular motion of a spacecraft.

Experimental Dynamics of Electromechanical Pulse Energy Conversion Systems

This paper develops methodology in the experimental research of the dynamics of electromechanical pulse energy conversion systems (PECSs) through the example of the dc electric drive with pulsewidth-modulation (PWM) control. The universal structure of the experimental plant was developed, which allowed the production of experimental bifurcation diagrams, time-series data, and phase-plane projections with variation of PECS controller parameters as well as load parameters. The approach to the experimental parameter identification (measuring) of the dc electric drive with PWM control was proposed. The adequacy degree of typical simplifications of electromechanical PECS mathematical models was studied both experimentally and theoretically.

Performance analysis of a trickle irrigation subunit installed in an apple orchard

Studies were carried out to evaluate the "xique-xique" irrigation system of a trickle irrigated subunit. Initial results showed that the system's performance was average, any Emission Uniformity, Statistical Uniformity and Coefficient of Global Variation were 74.51, 77.69, and 22.31%, respectively. The efficiency parameters were below expectations, and values of Application Efficiency (Ae), Storage Efficiency (Se), Deep Percolation (Dp), Deficit Degree (DD) and Adequacy Degree (a) were 100, 47.83, 0, 52.17 and 0% respectively. By adopting new management procedures, it was possible to improve the system's efficiency, reaching values of 90.20, 91.68, 9.80, 8.32 and 52.87% for Ae, Se, Dp, DD and "a", respectively.