Correlations for the log-mean temperature difference (LMTD) correction factor are given which are useful for computerized solutions since most texts only provide graphical factors.
In this paper, by using the way of weight coefficients and technique of real analysis, a more accurate multidimensional discrete Mulholland-type inequality with the best possible constant factor is given, which is an extension of (3).
In this paper, by using the way of weight coefficients and technique of real analysis, a more accurate multidimensional discrete Mulholland-type inequality with the best possible constant factor is given, which is an extension of the Mulholland inequality.
In this paper, by the use of weight coefficients, the transfer formula and the technique of real analysis, a new multidimensional Hilbert-type inequality with multi-parameters and a best possible constant factor is given, which is an extension of some published results.
In this paper, by the use of weight coefficients, the transfer formula and the technique of real analysis, a new multidimensional Hilbert-type inequality with multi-parameters and a best possible constant factor is given, which is an extension of (4) and (5).
In this paper, by using the way of weight coefficients and technique of real analysis, a Hardy-Hilbert-type inequality with parameters and a best possible constant factor is given, which is with the kernel (frac{(min {x,c_{1}y})^{alpha}}{(max{x,c_{1}y})^{lambda+alpha}}) similar to (9).
In this paper, by means of the weight functions, the technique of real analysis and Hermite-Hadamard's inequality, a more accurate half-discrete Hardy-Hilbert-type inequality related to the kernel of logarithmic function and a best possible constant factor is given, which is an extension of (8) in a particular kernel of degree 0 similar to (7).
In this paper, by means of weight coefficients and techniques of real analysis, a new Hardy-Hilbert-type inequality with multiparameters and the best possible constant factor is given, which is with the kernel k_{lambda} x,y)=frac{(min{x,y})^{alpha}}{(max{x,y})^{lambda +alpha}} similar to (4).
In this paper, by the use of the way of weight coefficients, the transfer formula and technique of real analysis, a multidimensional discrete Hilbert's inequality with parameters and a best possible constant factor is given, which is an extension of (4) for k_{lambda}(m,n =prod_{k=1}^{s} frac{(min{m,c_{k}n})^{frac {gamma}{s}}}{(max{m,c_{k}n})^{frac{lambda+gamma}{s}}}.
In this paper, by applying weight coefficients and technique of real analysis, a half-discrete Hardy-Hilbert-type inequality related to the kernel of hyperbolic secant function and the best possible constant factor is given, which is an extension of (11) for (lambda=0) and a particular kernel.
Redistricting expert Alan Clayton is concerned that black and Latino voters could lose ground under the new criteria, which he said are too vague about how much weight should be given to which factors and what constitutes "communities of interest". And, he said, a citizens panel need not be responsive to constituent groups the way lawmakers would be.
