Search results for: entropy weight method

Authors: Massimiliano Frezza, Sergio Bianchi, Augusto Pianese

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Introduced by Shannon in 1948 in the field of information theory as the average rate at which information is produced by a stochastic set of data, the concept of entropy has gained much attention as a measure of uncertainty and unpredictability associated with a dynamical system, eventually depicted by a stochastic process. In particular, the Shannon entropy measures the degree of order/disorder of a given signal and provides useful information about the underlying dynamical process. It has found widespread application in a variety of fields, such as, for example, cryptography, statistical physics and finance. In this regard, many contributions have employed different measures of entropy in an attempt to characterize the financial time series in terms of market efficiency, market crashes and/or financial crises. The Shannon entropy has also been considered as a measure of the risk of a portfolio or as a tool in asset pricing. This work investigates the theoretical link between the Shannon entropy and the multifractional Brownian motion (mBm), stochastic process which recently is the focus of a renewed interest in finance as a driving model of stochastic volatility. In particular, after exploring the current state of research in this area and highlighting some of the key results and open questions that remain, we show a well-defined relationship between the Shannon (log)entropy and the memory function H(t) of the mBm. In details, we allow both the length of time series and time scale to change over analysis to study how the relation modify itself. On the one hand, applications are developed after generating surrogates of mBm trajectories based on different memory functions; on the other hand, an empirical analysis of several international stock indexes, which confirms the previous results, concludes the work.

Keywords: Shannon entropy, multifractional Brownian motion, Hurst–Holder exponent, stock indexes

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Authors: Christina Roman, Deepak Koirala, Joseph A. Piccirilli

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Phage displaying synthetic Fab libraries have been used to obtain Fabs that bind to specific RNA targets with high affinity and specificity. These Fabs have been demonstrated to facilitate RNA crystallization. However, the antibody framework used in the construction of these phage display libraries contains numerous bulky, flexible, and charged residues, which facilitate solubility and hinder aggregation. These residues can interfere with crystallization due to the entropic cost associated with burying them within crystal contacts. To systematically reduce the surface entropy of the Fabs and improve their crystallization properties, a protein engineering strategy termed surface entropy reduction (SER) is being applied to the Fab framework. In this approach, high entropy residues are mutated to smaller ones such as alanine or serine. Focusing initially on Fab BL3-6, which binds an RNA AAACA pentaloop with 20nM affinity, the SER P server (http://services.mbi.ucla.edu/SER/) was used and analysis was performed on existing RNA-Fab BL3-6 co-crystal structures. From this analysis twelve surface entropy reduced mutants were designed. These SER mutants were expressed and are now being measured for their crystallization and diffraction performance with various RNA targets. So far, one mutant has generated 3.02 angstrom diffraction with the yjdF riboswitch RNA. Ultimately, the most productive mutations will be combined into a new Fab framework to be used in a optimized phage displayed Fab library.

Keywords: antibody fragment, crystallography, RNA, surface entropy reduction

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Yong Seong Kim, Seongbin Hong, So Hun Kim, Moonsuk Nam

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Background: Patients who undergo thyroidectomy due to thyroid cancer often complain weight gain, although they are on suppressive thyroid hormone treatment. The aim of this study is to know whether thyroid cancer patients gain the weight after thyroidectomy and weight change is dependent on estrogen state or use of rhTSH. Material and Method: We performed a retrospective chart review of subjects receiving medical care at an academic medical center. Two hundred two patients who underwent total thyroidectomy were included. As a control group, patients with thyroid nodule and euthyroidism were matched for age, gender, menopausal status. The weight changes occurring over first one year and thyroid function were assessed. Results: Mean age was 51±12 years and patients was composed with 38% of premenopausal, 15 % perimenopausal women, 37% of postmenopausal women and 20% of men. Patients with thyroid cancer gained 2.2 kg during the first year. It’ was not significantly different with control. However, weigh change in perimenopausal and post menopausal women gained more weight than control (P <0.05). Age, baseline body weight and weight gain were not correlated. Discussion: Patient who had undergone thyroidectomy gained more weight than their control, especially in peri- and postmenopausal women. Patients in this age should be monitored for their weight carefully.

Keywords: weight gain, thyroidectomy, thyroid cancer, weight chance

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Authors: Saumya R. Jha, Krishanu Biswas, Nilesh P. Gurao

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Several recent investigations have revealed medium entropy alloys exhibiting better mechanical properties than their high entropy counterparts. This clearly establishes that although a higher entropy plays a vital role in stabilization of particular phase over complex intermetallic phases, configurational entropy is not the primary factor responsible for the high inherent strengthening in these systems. Above and beyond a high contribution from friction stresses and solid solution strengthening, strain hardening is an important contributor to the strengthening in these systems. In this regard, researchers have developed severe plastic deformation (SPD) techniques like High Pressure Torsion (HPT) to incorporate very high shear strain in the material, thereby leading to ultrafine grained (UFG) microstructures, which cause manifold increase in the strength. The presented work demonstrates a meticulous study of the variation in mechanical properties at different radial displacements from the center of HPT tested equiatomic ternary FeMnNi synthesized by casting route, which is a low stacking fault energy FCC alloy that shows significantly higher toughness than its high entropy counterparts like Cantor alloy. The gradient in grain sizes along the radial direction of these specimens has been modeled using microstructure entropy for predicting the mechanical properties, which has also been validated by indentation tests. The dislocation density is computed by FEM simulations for varying strains and validated by analyzing synchrotron diffraction data. Thus, the proposed model can be utilized to predict the strengthening behavior of similar systems deformed by HPT subjected to varying loading conditions.

Keywords: high pressure torsion, severe plastic deformation, configurational entropy, dislocation density, FEM simulation

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Authors: Peng Li, Chuanri Li, Tao Li

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Reliability allocation is quite important during early design and development stages for a system to apportion its specified reliability goal to subsystems. This paper improves the reliability fuzzy allocation method and gives concrete processes on determining the factor set, the factor weight set, judgment set, and multi-grade fuzzy comprehensive evaluation. To determine the weight of factor set, the modified trapezoidal numbers are proposed to reduce errors caused by subjective factors. To decrease the fuzziness in the fuzzy division, an approximation method based on linear programming is employed. To compute the explicit values of fuzzy numbers, centroid method of defuzzification is considered. An example is provided to illustrate the application of the proposed reliability allocation method based on fuzzy arithmetic.

Keywords: reliability allocation, fuzzy arithmetic, allocation weight, linear programming

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Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Dalibor Štys, Kryštof M. Stys, Maryia Chkalova, Petr Kouba, Aliaxandr Pautsina, Dalibor Štys Jr., Jana Pečenková, Denis Durniev, Tomáš Náhlík, Petr Císař

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In this article, a construction and some properties of the 5iD viewer, the system recording simultaneously five views of a given experimental object is reported. Properties of the system are demonstrated on the analysis of fish schooling behavior. It is demonstrated the method of instrument calibration which allows inclusion of image distortion and it is proposed and partly tested also the method of distance assessment in the case that only two opposite cameras are available. Finally, we demonstrate how the state trajectory of the behavior of the fish school may be constructed from the entropy of the system.

Keywords: 3D positioning, school behavior, distance calibration, space vision, space distortion

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Authors: Bongjae Lee, Beom Goo Hwang, Hye Mi Park

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CO₂ capture products manufactured through Carbon Capture and Utilization (CCU) Plant that collect CO₂ directly from power plants require accurate measurements of the amount of CO₂ captured. For this purpose, two tests were carried out on the weight loss test. And one was analyzed using a carbon dioxide quantification device. First, the ignition loss analysis was performed by measuring the weight of the sample at 550°C after the first conversation and then confirming the loss when ignited at 950°C. Second, in the thermogravimetric analysis, the sample was divided into two sections of 40 to 500°C and 500 to 800°C to confirm the reduction. The results of thermal weight loss analysis and thermogravimetric analysis were confirmed to be almost similar. However, the temperature of the ignition loss analysis method was 950°C, which was 150°C higher than that of the thermogravimetric method at a temperature of 800°C, so that the difference in the amount of weight loss was 3 to 4% higher by the heat loss analysis method. In addition, the tendency that the CO₂ content increases as the reaction time become longer is similarly confirmed. Third, the results of the wet titration method through the carbon dioxide quantification device were found to be significantly lower than the weight loss method. Therefore, based on the results obtained through the above three analysis methods, we will establish a method to analyze the accurate amount of CO₂. Acknowledgements: This work was supported by the Korea Institute of Energy Technology Evaluation and planning (No. 20152010201850).

Keywords: carbon capture and utilization, CCU, CO2, CO2 capture products, analysis method

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Authors: S. Aouabdi, M. Taibi

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The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.

Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics

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Authors: Jong-Yeon Kim, Kwang-Bok Shin, Tae-Hwan Ko

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The purpose of this paper is to suggest a weight-reduction design method for the aluminum extrusion carbody structure of a double deck high-speed train using size optimization method. The size optimization method was used to optimize thicknesses of skin and rib of the aluminum extrusion for the carbody structure. Thicknesses of 1st underframe, 2nd underframe, solebar and roof frame were selected by design variables in order to conduct size optimization. The results of the size optimization analysis showed that the weight of the aluminum extrusion could be reduced by 0.61 tons (5.60%) compared to the weight of the original carbody structure.

Keywords: double deck high-speed train, size optimization, weigh-reduction, aluminum extrusion

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Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu

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The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.

Keywords: complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment

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Authors: Morteza Ghanbarpour, Rahmatollah Khodabandeh

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In this study, second law of thermodynamic is employed to evaluate heat pipe thermal performance. In fact, nanofluids potential to decrease the entropy generation of cylindrical heat pipes are studied and the results are compared with experimental data. Some cylindrical copper heat pipes of 200 mm length and 6.35 mm outer diameter were fabricated and tested with distilled water and water based Al2O3 nanofluids with volume concentrations of 1-5% as working fluids. Nanofluids are nanotechnology-based colloidal suspensions fabricated by suspending nanoparticles in a base liquid. These fluids have shown potential to enhance heat transfer properties of the base liquids used in heat transfer application. When the working fluid undergoes between different states in heat pipe cycle the entropy is generated. Different sources of irreversibility in heat pipe thermodynamic cycle are investigated and nanofluid effect on each of these sources is studied. Both experimental and theoretical studies reveal that nanofluid is a good choice to minimize the entropy generation in heat pipe thermodynamic cycle which results in higher thermal performance and efficiency of the system.

Keywords: heat pipe, nanofluid, thermodynamics, entropy generation, thermal resistance

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Authors: Manjit Singh

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Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

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Authors: Liang Hu

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The innovation of refractory high-entropy alloy (RHEA) formed from refractory metals W, Ta, Mo, Nb, Hf, V, and Zr was firstly implemented in 2010 to obtain better strength at high temperature than conventional HEAs based on Al, Co, Cr, Cu, Fe and Ni. Due to the refractory characteristic and high chemical activity at elevated temperature, electrostatic levitation technique has been utilized to fulfill the rapid solidification of RHEA. Several RHEAs consisting W, Ta, Mo, Nb, Zr have been selected to perform the undercooling and rapid solidification by ESL. They are substantially undercooled by up to 0.2TL. The evolution of as-solidified microstructure and component redistribution with undercooling have been investigated by SEM, EBSD, and EPMA analysis. According to the EPMA results of composing elements at different undercooling levels, the chemical distribution relevant to undercooling was also analyzed.

Keywords: chemical distribution, high-entropy alloy, rapid solidification, undercooling

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Authors: Muhammad Bilal Ameen, M. Zubair Akbar Qureshi

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The current investigation of two-dimensional hybrid nanofluid flows with two coaxial parallel disks has been presented. Consider the hybrid nanofluid has been taken as steady-state. Consider the coaxial disks that have been porous. Consider the heat equation to examine joule heating and viscous dissipation effects. Nonlinear partial differential equations have been solved numerically. For shear stress and heat transfer, results are tabulated. Hybrid nanoparticles and Eckert numbers are increasing for heat transfer. Entropy generation is expanded with radiation parameters Eckert, Reynold, Prandtl, and Peclet numbers. A set of ordinary differential equations is obtained to utilize the capable transformation variables. The numerical solution of the continuity, momentum, energy, and entropy generation equations is obtaining using the command bvp4c of Matlab as a solver. To explore the impact of main parameters like suction/infusion, Prandtl, Reynold, Eckert, Peclet number, and volume fraction parameters, various graphs have been plotted and examined. It is concluded that a convectional nanofluid is highly compared by entropy generation with the boundary layer of hybrid nanofluid.

Keywords: entropy generation, hybrid nano fluid, heat transfer, porous disks

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Authors: C. D. Gomez-Esparza, Z. V. Hernandez-Castro, C. A. Rodriguez-Gonzalez, R. Martinez-Sanchez, A. Duarte-Moller

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Recently, the high entropy alloys (HEA) are the focus of attention in metallurgical and materials science due to their desirable and superior properties in comparison to conventional alloys. The HEA field has promoted the exploration of several compositions including the addition of non-metallic elements like carbon, which in traditional metallurgy is mainly used in the steel industry. The aim of this work was the synthesis of equiatomic FeCrNiMnTi high entropy alloys, with minor carbon content, by mechanical alloying and sintering. The effect of the addition of carbon nanotubes and graphite were evaluated by X-ray diffraction, scanning electron microscopy, and microhardness test. The structural and microstructural characteristics of the equiatomic alloys, as well as their hardness were compared with those of an austenitic AISI 321 stainless steel processed under the same conditions. The results showed that porosity in bulk samples decreases with carbon nanotubes addition, while the equiatomic composition favors the formation of titanium carbide and increased the AISI 321 hardness more than three times.

Keywords: carbon nanotubes, graphite, high entropy alloys, mechanical alloying

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Authors: Salma Parvin, M. A. Alim

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The convective and radiative heat transfer performance and entropy generation on forced convection through a direct absorption solar collector (DASC) is investigated numerically. Four different fluids, including Cu-water nanofluid, Al₂O₃-waternanofluid, TiO₂-waternanofluid, and pure water are used as the working fluid. Entropy production has been taken into account in addition to the collector efficiency and heat transfer enhancement. Penalty finite element method with Galerkin’s weighted residual technique is used to solve the governing non-linear partial differential equations. Numerical simulations are performed for the variation of mass flow rate. The outcomes are presented in the form of isotherms, average output temperature, the average Nusselt number, collector efficiency, average entropy generation, and Bejan number. The results present that the rate of heat transfer and collector efficiency enhance significantly for raising the values of m up to a certain range.

Keywords: DASC, forced convection, mass flow rate, nanofluid

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren

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Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.

Keywords: flywheel energy storage, fuzzy, optimization, stress analysis

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Authors: Farshid Fathinia

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Numerical computation of unsteady laminar three-dimensional natural convection and entropy generation in an inclined cubical trapezoidal air-filled cavity is performed for the first time in this work. The vertical right and left sidewalls of the cavity are maintained at constant cold temperatures. The lower wall is subjected to a constant hot temperature, while the upper one is considered insulated. Computations are performed for Rayleigh numbers varied as 103 ≤ Ra ≤ 105, while the trapezoidal cavity inclination angle is varied as 0° ≤ ϕ ≤ 180°. Prandtl number is considered constant at Pr = 0.71. The second law of thermodynamics is applied to obtain thermodynamic losses inside the cavity due to both heat transfer and fluid friction irreversibilities. The variation of local and average Nusselt numbers are presented and discussed.While, streamlines, isotherms and entropy contours are presented in both two and three-dimensional pattern. The results show that when the Rayleigh number increases, the flow patterns are changed especially in three-dimensional results and the flow circulation increases. Also, the inclination angle effect on the total entropy generation becomes insignificant when the Rayleigh number is low.Moreover, when the Rayleigh number increases the average Nusselt number increases.

Keywords: transient natural convection, trapezoidal cavity, three-dimensional flow, entropy generation, second law

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Authors: Bahar Hazal Yalçınkaya, Bayram Yılmaz, Mustafa Özilgen

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Brain information transmission in the neuronal network occurs in the form of electrical signals. Neural work transmits information between the neurons or neurons and target cells by moving charged particles in a voltage field; a fraction of the energy utilized in this process is dissipated via entropy generation. Exergy loss and entropy generation models demonstrate the inefficiencies of the communication along the dendritic trees. In this study, neurons of 4 different animals were analyzed with one dimensional cable model with N=6 identical dendritic trees and M=3 order of symmetrical branching. Each branch symmetrically bifurcates in accordance with the 3/2 power law in an infinitely long cylinder with the usual core conductor assumptions, where membrane potential is conserved in the core conductor at all branching points. In the model, exergy loss and entropy generation rates are calculated for each branch of equivalent cylinders of electrotonic length (L) ranging from 0.1 to 1.5 for four different dendritic branches, input branch (BI), and sister branch (BS) and two cousin branches (BC-1 & BC-2). Thermodynamic analysis with the data coming from two different cat motoneuron studies show that in both experiments nearly the same amount of exergy is lost while generating nearly the same amount of entropy. Guinea pig vagal motoneuron loses twofold more exergy compared to the cat models and the squid exergy loss and entropy generation were nearly tenfold compared to the guinea pig vagal motoneuron model. Thermodynamic analysis show that the dissipated energy in the dendritic tress is directly proportional with the electrotonic length, exergy loss and entropy generation. Entropy generation and exergy loss show variability not only between the vertebrate and invertebrates but also within the same class. Concurrently, single action potential Na⁺ ion load, metabolic energy utilization and its thermodynamic aspect contributed for squid giant axon and mammalian motoneuron model. Energy demand is supplied to the neurons in the form of Adenosine triphosphate (ATP). Exergy destruction and entropy generation upon ATP hydrolysis are calculated. ATP utilization, exergy destruction and entropy generation showed differences in each model depending on the variations in the ion transport along the channels.

Keywords: ATP utilization, entropy generation, exergy loss, neuronal information transmittance

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Authors: Yao Cheng, Weihua Zhang

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Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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Authors: Houda Jalali, Hassan Abbassi

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In this numerical work, natural convection and entropy generation of Al₂O₃–water nanofluid in square cavity have been studied. A two-dimensional steady laminar natural convection in a differentially heated square cavity of length L, filled with a nanofluid is investigated numerically. The horizontal walls are considered adiabatic. Vertical walls corresponding to x=0 and x=L are respectively maintained at hot temperature, T_h and cold temperature, T_c. The resolution is performed by the CFD code "FLUENT" in combination with GAMBIT as mesh generator. These simulations are performed by maintaining the Rayleigh numbers varied as 10³ ≤ Ra ≤ 10⁶, while the solid volume fraction varied from 1% to 5%, the particle size is fixed at dp=33 nm and a range of the temperature from 20 to 70 °C. We used models of thermophysical nanofluids properties based on experimental measurements for studying the effect of adding solid particle into water in natural convection heat transfer and entropy generation of nanofluid. Such as models of thermal conductivity and dynamic viscosity which are dependent on solid volume fraction, particle size and temperature. The average Nusselt number is calculated at the hot wall of the cavity in a different solid volume fraction. The most important results is that at low temperatures (less than 40 °C), the addition of nanosolids Al₂O₃ into water leads to a decrease in heat transfer and entropy generation instead of the expected increase, whereas at high temperature, heat transfer and entropy generation increase with the addition of nanosolids. This behavior is due to the contradictory effects of viscosity and thermal conductivity of the nanofluid. These effects are discussed in this work.

Keywords: entropy generation, heat transfer, nanofluid, natural convection

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: Nyashadzashe Chiraga, Anthony Walker, Glen Bright

Abstract:

The manufacturing industry is currently experiencing a paradigm shift into the Fourth Industrial Revolution in which customers are increasingly at the epicentre of production. The high degree of production customization and personalization requires a flexible manufacturing system that will rapidly respond to the dynamic and volatile changes driven by the market. They are a gap in technology that allows for the optimal flow of information and optimal manufacturing operations on the shop floor regardless of the rapid changes in the fixture and part demands. Information is the reduction of uncertainty; it gives meaning and context on the state of each cell. The amount of information needed to describe cellular manufacturing systems is investigated by two measures: the structural entropy and the operational entropy. Structural entropy is the expected amount of information needed to describe scheduled states of a manufacturing system. While operational entropy is the amount of information that describes the scheduled states of a manufacturing system, which occur during the actual manufacturing operation. Using Anylogic simulator a typical manufacturing job shop was set-up with a cellular manufacturing configuration. The cellular make-up of the configuration included; a Material handling cell, 3D Printer cell, Assembly cell, manufacturing cell and Quality control cell. The factory shop provides manufactured parts to a number of clients, and there are substantial variations in the part configurations, new part designs are continually being introduced to the system. Based on the normal expected production schedule, the schedule adherence was calculated from the structural entropy and operation entropy of varying the amounts of information communicated in simulated runs. The structural entropy denotes a system that is in control; the necessary real-time information is readily available to the decision maker at any point in time. For contractive analysis, different out of control scenarios were run, in which changes in the manufacturing environment were not effectively communicated resulting in deviations in the original predetermined schedule. The operational entropy was calculated from the actual operations. From the results obtained in the empirical study, it was seen that increasing, the efficiency of a factory communication system increases the degree of adherence of a job to the expected schedule. The performance of downstream production flow fed from the parallel upstream flow of information on the factory state was increased.

Keywords: information entropy, communication in manufacturing, mass customisation, scheduling

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Authors: Vera Varazashvili, Murman Tsarakhov, Tamar Mirianashvili, Teimuraz Pavlenishvili, Tengiz Machaladze, Mzia Khundadze

Abstract:

Standard Gibbs energy of formation ΔGfor(298.15) of lanthanide-iron double oxides of garnet-type crystal structure R3Fe5O12 - RIG (R – are rare earth ions) from initial oxides are evaluated. The calculation is based on the data of standard entropies S298.15 and standard enthalpies ΔH298.15 of formation of compounds which are involved in the process of garnets synthesis. Gibbs energy of formation is presented as temperature function ΔGfor(T) for the range 300-1600K. The necessary starting thermodynamic data were obtained from calorimetric study of heat capacity and by using the semi-empirical method for calculation of ΔH298.15 (formation). Thermodynamic functions for standard temperature – enthalpy, entropy and Gibbs energy - are recommended as reference data for technological evaluations. Through the isostructural series of rare earth-iron garnets the correlation between thermodynamic properties and characteristics of lanthanide ions are elucidated.

Keywords: calorimetry, entropy, heat capacity, Gibbs energy of formation, rare earth iron garnets

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Authors: Mokali Veeresham

Abstract:

The microstructure and texture evolution of cryo rolled and annealed ductile TaHfNbZrTi refractory high entropy alloy was investigated. To obtain that, the alloy is severely cryo rolled and subsequently annealed for the recrystallization process. The cryo rolled – 90% shows the presence of very fine grains and microstructural heterogeneity. The cryo rolled samples are annealed at a temperature ranging from 800°C to 1400°C, the partial recrystallization is observed at 800°C annealed condition, and at higher annealing temperatures the complete recrystallization process is noticed. The development of ND fiber texture is observed after the annealing.

Keywords: refractory high entropy alloy, cryo-rolling, annealing, microstructure, texture

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

Abstract:

The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

Procedia PDF Downloads 106