Mutual Coefficients Research Articles

Conditions at the interface between the space elevator tether and its climber

A simple space elevator consists of a single tether extending well beyond geosynchronous altitude and a payload-carrying device which grips and climbs the tether. A friction-based, opposing wheel climber was judged most likely to be constructed with present-day technology and it appears that mass-production of the tether material is also within reach. The physical conditions at the interface between the climber wheels and tether determine first of all the possibility of climbing and then the design parameters of the tether. Conditions such as lifting torque, tensile, compressive and shear strength, friction, interface temperature, thermal conductivity and radiative cooling were examined and used to set minimum requirements for the tether material. Graphene superlaminate (GSL), consisting of layers of single crystal graphene, appears to be an excellent tether material with a sufficiently high tensile strength. An increase in its inter-layer cross-bonding and a larger mutual coefficient of friction with the climber wheel material would allow it to satisfy the climbing conditions. A final determination of the suitability of GSL requires the measurement of a number of, as yet unknown, material properties. A list of such measurements is proposed and a partial list of trade studies and iterations of design for the tether are provided.

Comparison between Information Theoretic Measures to Assess Financial Markets

Information theoretic measures were applied to the study of the randomness associations of different financial time series. We studied the level of similarities between information theoretic measures and the various tools of regression analysis, i.e., between Shannon entropy and the total sum of squares of the dependent variable, relative mutual information and coefficients of correlation, conditional entropy and residual sum of squares, etc. We observed that mutual information and its dynamical extensions provide an alternative approach with some advantages to study the association between several international stock indices. Furthermore, mutual information and conditional entropy are relatively efficient compared to the measures of statistical dependence.

A DATA ANALYTICS-BASED APPROACH FOR QUANTITATIVE EXPLORATION OF THE RELATIONSHIP BETWEEN ENGINEERING PROGRAMS' MAJORS AND EDUCATIONAL OBJECTIVES

In outcome-based education, program education objects (PEOs) are essential components around which all program’s activities are centered. They represent graduates professional and career accomplishments within few years of graduation. In this paper, the relationship between the academic majors and PEOs of engineering programs is questioned and a data analytics-based approach to answer this question is proposed. More specifically, this paper applies three well-known data correlation measures, namely Pointwise Mutual Information, Correlation Coefficient, and Odds Ratio, to a PEOs dataset extracted from the self-study reports of a set of Engineering programs. The PEOs dataset has been linguistically pre-processed through cleaning, annotation using a set of PEOs labels, and projection to break down each multi-PEOs label data instance into several single PEOs data instances. After that, the three measures are applied to measure the relationship between Programs' Majors (PMs) and PEOs. The obtained results are then ranked based on PMs-PEOs correlation strength and the agreement analysis among the three measures show a remarkable consistency among them in their evaluation of the relationship between PMs and PEOs. Finally, the overall ranking of PEOs within each PM, computed as a majority vote of the ranking of the three measures, show that each PM has a unique pattern of ranked PEOs. This suggests that the nature of PM plays a key role in determining the PM-PEOs relationship pattern. The obtained PMs-PEOs quantitative correlations are very beneficial to the academicians particularly when designing new programs or reviewing existing ones.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0968/a.php" alt="Hit counter" /></p>

Feature Selection Using Maximum Feature Tree Embedded with Mutual Information and Coefficient of Variation for Bird Sound Classification

The classification of bird sounds is important in ecological monitoring. Although extracting features from multiple perspectives helps to fully describe the target information, it is urgent to deal with the enormous dimension of features and the curse of dimensionality. Thus, feature selection is necessary. This paper proposes a scoring feature method named MICV (Mutual Information and Coefficient of Variation), which uses the coefficient of variation and mutual information to evaluate each feature’s contribution to classification. And then, a method named ERMFT (Eliminating Redundancy Based on Maximum Feature Tree) based on two neighborhoods to eliminate redundancy to optimize features is explored. These two methods are combined as the MICV-ERMFT method to select the optimal features. Experiments are conducted to compare eight different feature selection methods with two sounds datasets of bird and crane. Results show that the MICV-ERMFT method outperforms other feature selection methods in the accuracy of the classification and is less time-consuming.

Dilatancy of frictional granular materials under oscillatory shear with constant pressure

We perform numerical simulations of a two-dimensional frictional granular system under oscillatory shear confined by constant pressure. We found that the system undergoes dilatancy as the strain increases. We confirmed that compaction also takes place at an intermediate strain amplitude for a small mutual friction coefficient between particles. We also found that compaction depends on the confinement pressure while dilatancy little depends on the pressure.

MATHEMATICAL MODEL OF THE ADAPTABLE DISCHARGE CONTROL SYSTEM IN A TOKAMAK WITH AN IRON CORE

The previously developed adaptation models of the program regime used the so-called “local” adaptation model, i.e. when the correction of the control currents was carried out at each moment of time regardless of their change at other times. The main element was that the adaptation algorithms used were linear, i.e. are based on the linearization of the Kirchhoff system of equations describing the evolution of the control currents during the discharge. In this paper, an algorithm for “global” adaptation of control currents is proposed. It is based on a mathematical model for controlling the discharge in an iron-core tokamak, taking into account the nonlinear behavior of a ferromagnetic. In this model, the evolution of currents is described by the Kirchhoff equations with nonlinear mutual induction coefficients, and the restrictions on the control currents, voltages, and the equilibrium and stability conditions for the plasma are included in the corresponding discrepancy functional. To find the discharge scenario, the optimal control problem is formulated and solved. The algorithm of “global” adaptation consists in the fact that information about the previous discharges is included in the minimized functional, and then the problem of optimal control is solved and a new program scenario of the discharge and the corresponding control currents and voltages are found. As a result, the model of adaptation of the program regime, first, is nonlinear, i.e. nonlinearized Kirchhoff equations are used to describe the evolution of the control currents, and, secondly, the “global” one, since the correction of all currents is carried out interdependently and consistently during the entire discharge scenario. This approach allows us to redistribute the currents in advance in the critical situation (for example, additional heating) and provide the required program regime. This is especially important in an iron-core tokamak, when the connections between the control currents become highly nonlinear. In this work, using the example of the problem of additional heating for the T-15 tokamak, the work of the “global” adaptation algorithm is demonstrated.

The Stochastic Evolution Game of Knowledge Sharing in the Infrastructure PPP Supply Chain Network

Due to the complexity and randomness of environmental change, the knowledge-sharing behavior of members in the PPP supply chain will be affected by random disturbance factors. Traditional evolutionary game models cannot describe this effect. In this study, Gaussian white noise is introduced into the stochastic evolutionary game model of PPP supply chain knowledge sharing. The numerical simulation of the model is carried out to analyze the influence of parameter changes on the strategy selection of enterprise groups. The result shows that the strong knowledge power enterprise group is more sensitive with the variation of parameters than that of the weak knowledge power enterprise group. However, the weak enterprise group has a more vital willingness to share knowledge. Incentive measures can increase the knowledge-sharing benefits and promote the strong knowledge powerful enterprise group toward the sharing strategy. Increasing the mutual trust coefficient, reducing the sharing cost, and improving the enterprise’s transformation ability will help both sides to evolve into the sharing strategy more quickly. This study would have significance for PPP project performance and industry innovation.

Frequency-Tracking Algorithm Based on SOGI-FLL for Wireless Power Transfer System to Operate ZPA Region

The wireless power transfer (WPT) system has attracted attention for energy transmission without physical contact. However, a WPT system has low coupling condition because of a big air gap between transmitter and receiver coils. The low coupling condition has a high leakage inductance. To overcome this problem, we design a proposed system for WPT using series-series (S-S) topology of one resonant circuit. To obtain the higher efficiency power conversion of the WPT system, it has to operate the resonant frequency in the zero phase angle (ZPA) point even under mutual coefficient and load variation. Therefore, we propose the resonant frequency tracking algorithm to operate ZPA point based on the second order generalized integrator-frequency locked loop (SOGI-FLL) method. This proposed frequency-tracking algorithm can estimate ZPA point by changing switching frequency. We can reduce the switching loss with this proposed algorithm and improve the low conversion efficiency of the WPT system. The performance of the proposed frequency-tracking algorithm is automatically verified through various coupling coefficients and the load variation.

Electrical and electrochemical properties of imidazolium and phosphonium-based pNIPAAM ionogels

The electrical and electrochemical properties of two ionogel materials based on the poly(N-isopropylacrylamide) gel with 1-ethyl-3-methylimidazolium ethyl sulfate and trihexyltetradecyl-phosphonium dicyanamide ionic liquids are investigated. The current-voltage curves show a current rectification for both ionogels and ionic liquids after inducing ion adsorption on gold electrode surface. The polymer matrix of the ionogels mitigates ion adsorption, resulting in lower rectification ratios when comparing with the corresponding ionic liquids. The stability and the electrochemical window (ECW) of the ionogels are calculated from cyclic voltammograms and compared with the ones obtained for the ionic liquids. The widest electrochemical window is achieved by the phosphonium ionic liquid and its ionogel. Finally, the effect of the absorbed atmospheric water and the mutual coefficient diffusion of the redox active species inside the IO is calculated. This work widens the knowledge of the behavior of ionogel materials characterized on gold electrode interfaces.

A cooperative construction method for the measurement matrix and sensing dictionary used in compression sensing

A measurement matrix and sensing dictionary are the basic tools for signal compression sampling and reconstruction, respectively, which are important aspects in the field of compression sensing. Previous studies which have divided the measurement matrix and sensing dictionary into two separate processes did not make full use of their inherent intercorrelations. In case of which could be fully utilized, the mutual coherence of the atoms of measurement matrix and sensing dictionary can be further reduced under the premise of ensuring that the original signal information is stored, which could improve the accuracy of signal recovery. The present study attempted to reduce the mutual coherence between the sensing dictionary and measurement matrix by proposing the t-average mutual coherence coefficient as an evaluation index for the sensing dictionary. A mathematical model for co-constructing a measurement matrix and sensing dictionary is firstly proposed. Then, the measurement matrix and sensing dictionary cooperative construction(MSCA)algorithm is proposed to solve the model at a faster rate. The simulated results for sparse signal and binary image show that the proposed algorithm has faster computing speed and higher solution precision than the state-of-the-art construction algorithms.

Электродинамические силы, действующие на контур с током в поле соленоида при его перемещении вдоль оси

The advisability of using expressions for the mutual inductance coefficients and electrodynamic forces of interaction in a system of circular solenoids and loops with a common axis that were obtained previously from an analytical study is shown on particular examples. The numerical results obtained from the expressions representing the mutual inductance coefficients in the form of written series are compared with the other known recommendations involving the use of tables or graphs. An expression for theelectrodynamic force of interaction between the loop and a solenoid with current is presented, and dependences for them constructed for different positions of the loop along the solenoid axis are given.

Prediction of hepatocellular carcinoma patient survival using machine learning classification rules.

e15649 Background: The outcome prediction of hepatocellular carcinoma (HCC) is conventionally determined by evaluating tissue samples obtained during surgical removal of the primary tumor focusing on their clinical and pathologic features. Recently, accumulating evidence suggests that cancer development is comprehensively modulated by the host’s immune system underlying the importance of immunological biomarkers for the prediction of HCC prognosis. However, an integrated predictive algorism incorporating clinical characteristic and immune features still remain to be established. Methods: We obtained respectable stage II HCC specimens, along with adjacent para-tumor tissues from 221 patients who underwent surgical resection at Eastern Hepatobiliary Surgery Hospital, (Shanghai, China) from 2015 through April 2018. Characteristics such as CD8+, CD163+, tumor-infiltrating lymphocytes (TILs) were obtained for further model construction used to predict the status of 3 survival indexes: Overall Survival (OS ,≤ 24 or > 24 month), Progression Free Survival (PFS, ≤ 6 or > 6 month), and Recurrence/Death (RD). Mutual information and coefficient between each feature and the survival indexes were tested to remove low scoring features after data cleaning and standardization. Furthermore, recursive features selection was preformed to obtain the optimal features combination. Finally, supervised learning techniques include either boosting or bagging strategy were used to fit and predict model with a grid-search method optimizing the parameters. Meanwhile, a cross validation procedure with 0.2 proportion of test cohort was randomly carried out for 10 times to evaluate the model. Results: We finally confirmed 15 biomarkers from the 46 candidates as features for the survival status prediction by using a 221 patients cohort. Among them, the top 10 most important biomarkers, included both clinical and immune attributes. The AUC of our model for survival indexes (OS, PFS, RD) was ranged from 0.76 (RD) to 0.8 (PFS), and the accuracy was above 0.85. Conclusions: We describe the integrative analysis of the clinical and immune features which collectively contribute to the survival index of HCC. Machine learning techniques, such as Gradient Boosting and random forest classifier , have a great promise for using in HCC cancer survival prediction.

О коэффициентах взаимной индукции и силах взаимодействия круговых коаксиальных контуров

An analysis of the literature suggesting expressions for mutual inductances and interaction forces in circular coaxial loops with current in parallel planes may lead to conclusions lacking strict uniqueness. These literary sources [1—10] are quite diverse in nature, and expressions with full elliptical integrals, including their numerical realization, occupy a significant place in them. The article considers alternative expressions for the mutual induction coefficients and interaction forces between circular coaxial loops. The advantage of using these expressions with the associated second-kind Legendre functions with a semi-integer index for numerical realization is shown.

Periodic Solution for a Stochastic Predator-Prey Model with Impulses and Holling-II Functional Response

Considering the mutual interference between species, a stochastic predator-prey model with impulses and Holling-II functional response is proposed in this paper. Firstly, by constructing an equivalent system without impulses, the existence of a globally unique positive solution is proved. Secondly, in cases of the mutual coefficient m = 1 and 0 m < 1, by constructing suitable Lyapunov functional, the existence of T-periodic solution is investigated under some certain conditions. Finally, numerical simulation is introduced to verify our main results.

Interplay between polydispersity, inelasticity, and roughness in the freely cooling regime of hard-disk granular gases.

A polydisperse granular gas made of inelastic and rough hard disks is considered. Focus is laid on the kinetic-theory derivation of the partial energy production rates and the total cooling rate as functions of the partial densities and temperatures (both translational and rotational) and of the parameters of the mixture (masses, diameters, moments of inertia, and mutual coefficients of normal and tangential restitution). The results are applied to the homogeneous cooling state of the system and the associated nonequipartition of energy among the different components and degrees of freedom. It is found that disks typically present a stronger rotational-translational nonequipartition but a weaker component-component nonequipartition than spheres. A noteworthy "mimicry" effect is unveiled, according to which a polydisperse gas of disks having common values of the coefficient of restitution and of the reduced moment of inertia can be made indistinguishable from a monodisperse gas in what concerns the degree of rotational-translational energy nonequipartition. This effect requires the mass of a disk of component i to be approximately proportional to 2σ_{i}+〈σ〉, where σ_{i} is the diameter of the disk and 〈σ〉 is the mean diameter.

Functional Response and Mutual Interference ofCotesia vestalis(Hymenoptera: Braconidae) onPlutella xylostella(Lepidoptera: Plutellidae)1

Abstract Functional response and mutual interference of Cotesia vestalis (Haliday) was studied on second-instar diamondback moth, Plutella xylostella (L.), larvae. The parasitoid exhibited Type II functional response to its host with attack rates of 0.045 (Holling disc equation) and 0.122 (Rogers random equation) and a handling time of 0.85 h (Holling disc equation) and 1.18 h (Rogers random equation). Theoretical maximum number of hosts that could be parasitized over a period of 24 h by the parasitoid was estimated to be 28.8 (Holling equation) and 20.3 (Rogers equation). Per capita number of parasitization decreased significantly from 12.4 to 3.8 with the increase in the parasitoid density from 2 to 8, indicating that mutual interference occurs when two or more numbers of parasitoid females forage in the same arena. The relationship between searching efficiency (E) and density (P) of the parasitoid was log E = –0.205 + 0.769 log P, with a mutual interference coefficient of 0.77.

Sezonowość odpływu z wybranych zlewni karpackich = Seasonality of outflow in selected Carpathian catchments

This article details an analysis of seasonality of outflow carried out for 12 Carpathian catchments. The latter were selected in such a way as to fully represent various conditions of outflow formation in the Carpathian Mountains, i.e. the region of Poland in which hydrological processes are most dynamic. Daily series of discharges for the years 1951-2010 provided the basis for the research, albeit with the series lengths used in analyses of particular rivers varying in length from 40 to 60 years. In the case of each water-gauge section selected, calculations were made for the seasonality index (IS), time of concentration coeffi cient (WPK), outflow concentration index (GMO) and half-outflow term index (TPO). Multiannual variability and mutual correlation coefficients for the above parameters were also calculated, with these characteristics together describing various aspects to the seasonality of river outflow. The results of the research conducted show that values for the mean seasonality indexes characterising the outflow in Carpathian catchments are slightly lower than those calculated for amounts of precipitation. In addition, their spatial differentiation is relatively weak, while their variability over time is distinctly high. The mean time of concentration coefficient (WPK) for the Carpathian catchments does differ markedly from place to place, occurring between 4th Apri l and 3rd June. However, in the cases of the rivers draining the western part of the Beskid Mountains and Tatras, the outflow concentration occurs relatively late (after 5th May), while it is relatively early (before 5th May) in the cases of the rivers in the eastern part of the Beskids. The long-term variability of WPK in the Carpathian Mountains is less than half as great as that characterising the seasonality index (25.2% to 55.7% on average), though no significant trends could be noted for long-term series of those characteristics. Timing related to Oliver’s concentration coefficient (GMO) reveals aspects of seasonality similar to those presented by Markham’s seasonality index (IS). Due to this fact it would be more appropriate to name it an “outflow seasonality index” rather than an “outflow concentration index”. Mean multiannual half-outflow terms (TPOśr) in the Carpathian catchments are strongly diversified and appear between 15th April and 21st May. Low TPOśr was noted in rivers of a nival-pluvial and nival well-shaped regime. Low TPOśr was found with the pluvial-nival regime. The spatial differentiation to the multiannual variability of TPOśr in the Carpathian Mountains is limited. It is most limited in the case of rivers in the Tatra Mountains. Statistical analyses of multiannual series for all the seasonality parameters examined show that, in the Carpathian area, the seasonal structure to the outflow is relatively stable over the long term (given a lack of significant trends), with year-to-year fluctuations and changes being random in nature. The relative mean mass diagram curve for Carpathian catchments has two points of inflection confirming the nival-pluvial or pluvial-nival regimes. The regional curve offers a very effective presentation of the seasonal distribution of outflow in the Carpathian Mountains.

Complex Systems: Phenomenology, Modeling, Analysis

In this paper a short overview on complex systems and their basic features, as well as the models and mathematical tools developed for their analysis, is given. This review is formed according to the related experience, activity and scientific interests of the author, namely focused on mainly in nonlinear time series analysis and statistics and their applications on different physical systems. In particular, rough outlines are given concerning the phenomenology of complex systems, e.g. far from equilibrium thermodynamics and Tsallis statistics, power law scaling, multi-fractality, low dimensional chaos, SOC, strange kinetics and anomalous diffusion and turbulent intermittency. In addition, a non-complete list of models, based on equations or agent based, is briefly described such as Kuramoto – Sivashinsky equation, cubic complex Ginzburg-Landau Equation, reaction-diffusion Equation, fractional equations, cellular automata, complex networks and artificial neural networks. A more extended review is provided concerning the nonlinear time series analysis complex systems, describing tools like mutual information, flatness coefficient, structure functions, Tsallis q-triplet, correlation dimension and Lyapunov exponents in the reconstructed phase space, which can provide valuable information for the complex system’s dynamics. Finally, applications of nonlinear time series analysis on various physical systems, such as earthquakes, Earth’s magnetosphere, solar plasma and solar wind, plastic deformation of materials, epilepsy, economical indices and DNA structure, are provided.

Computation of the electric field in the vicinity of overhead power line towers

There are many numerical models for computing extremely low-frequency electric and magnetic fields of high-voltage substations and power lines. More accurate computation results can be obtained using 3D algorithms. In this paper, a 3D quasistatic model for computation of the scalar electric potential and electric field intensity distribution of overhead power lines is presented. Phase conductors, shield wires and towers of overhead power lines are modelled using thin-wire cylindrical segments of active and passive conductors and using subparametric spatial 2D finite elements. Self and mutual coefficients of these components are numerically computed using an originally developed advanced double 2D numerical integration. Thereafter, they are included in the system of linear equations for computation of the charge density distribution. Special attention is given to examining the influence of the overhead power line towers on the electric field intensity distribution in their close vicinity. Therefore, a computer program for detailed segmentation of typical steel lattice towers of various types is developed. The accuracy of the presented model is verified by comparing the obtained results with other computed and measured published results.

Quenching mechanism of 5BDTC by aniline using Stern–Volmer plots

The quenching mechanism of 5,6-benzo-3-[1-(4,5-dicarbomethoxy-1,2,3-triazoloacetyl)] coumarin (5BDTC) by aniline using Stern–Volmer plots in six different solvents, namely, 1,4 dioxane, dimethyl formamide, dichloromethane, toluene, tetrahydrofuran, and acetonitrile. The Stern–Volmer plots are found to be nonlinear with a positive deviation in all six solvents. To interpret these results we have invoked ground-state complex formation and sphere of action static quenching models. Using these models, various quenching rate parameters have been determined. The magnitudes of these parameters suggest that the sphere of action static quenching model agrees well with the experimental results. Hence, the positive deviation is attributed to the static and dynamic quenching. Further, with the use of the finite sink approximation model, it was possible to check these bimolecular reactions as diffusion-limited and to estimate independently distance parameter R′ and mutual diffusion coefficient D. Finally an effort has been made to correlate the values of R′ and D with the values of the encounter distance R and the mutual coefficient D determined using Edward’s empirical relation and the Stokes–Einstein relation.