Abstract: Fe1-xMnxS thin films with concentration x=0.02, 0.04, 0.06, 0.08, 0.1 have been deposited on glass substrates by a simple Chemical Bath Deposition (CBD) method at 90 oC. The X-ray Diffraction analysis of deposited thin films revealed the growth of mono-phasic mackinawite (FeS) structure with crystallite size in the range from 4.06 to 5.95 nm as a function of manganese concentrations. The other structural parameters like stacking faults, dislocation density and lattice strain affirmed the improvement in crystal structure and phase stability in manganese doped FeS thin films. Scanning Electron Micrographs depicted the growth of nano-flakes and nano-flowers in case of pure FeS thin films while for manganese doped iron sulfide thin films, homogeneity of the deposited material was observed to improve with distinct boundaries of almost spherical nanostructures. The direct energy band gap of FeS mono-phasic thin films was observed to decrease from 2.23 to 1.89 eV as the concentration of manganese increases in host lattice. The prepared thin films with tunable optical properties would have potential applications in energy conversion and optoelectronic devices.
Abstract In this paper, first we present some interesting identities associated with Green’s functions and Fink’s identity, and further we present some interesting inequalities for r -convex functions. We also present refinements of some Hardy–Littlewood–Pólya type inequalities and give an application to the Shannon entropy. Furthermore, we use the Čebyšev functional and Grüss type inequalities and present the bounds for the remainder in the obtained identities. Finally, we use the obtained identities together with Hölder’s inequality for integrals and present Ostrowski type inequalities.
As the title suggests, the present dissertation deals with the re�nements of Jensen- Ste�ensen and related inequalities.We extend some classical results and give some new re�nements of several well known inequalities including Jensen's inequality, Jensen- Ste�ensen inequality, Hermite-Hadamard inequality, majorization-type inequality, generalized weighted Favard and Berwald inequalities.We also provide the re�nements of some companion inequalities to the Jensen's inequality, namely Slater's inequality and the inequalities obtained by M. Mati�c and J. Pe�cari�c in [4]. We sharpen the lower bounds of the Jensen's functional.Some inequalities in terms of G^ateaux derivatives for convex functions are also provided.Finally, we present not only the generalizations of Hardy-Littlewood-P�olya inequality [26, Theorem 134] but also generalizations of some results given in [8] and [36].
Compared to commonly used loss-based congestion control algorithms predominantly used in Transmission Control Protocol (TCP) implementations, congestion-based congestion control called BBR has shown much better performance in resource-abundant modern communication links. However, for a high influx of TCP sessions on the bottleneck switch, clusters in High-Performance Compute (HPC) nodes and data centers face resource constraints because of the immense workload during orchestration and relocation of workflows across the resource pool. This article discusses how to resolve this problem, commonly known as TCP incast, through efficient queue management of the bottleneck link and adding a shaper function in the standard BBR algorithm. We analyzed TCP incast issue for two efficient versions of congestion control i.e., BBR and CUBIC (named after the cubic function used instead of linear function), in a highly overloaded convergent switch of the cluster. It is noticeable that the queuing delay and buffer build-up are two essential parameters in causing TCP Incast. Hence, we used the M/G/1/B queuing model when multiple TCP sessions generate the network traffic and different buffer build-up scenarios are analyzed in the bottleneck node of HPC clusters. Based on the findings of our queuing analysis, we propose an incast recovery BBR algorithm that introduces additional controls like Incast shaping to deal with queue build-up during TCP incast. The effects of these modifications in BBR implementation are studied in terms of performance parameters like flow completion time, throughput, RTT variations, and fairness to other competing flows are significant compared with standard BBR and CUBIC implementations.
A chemical compound in the form of graph terminology is known as a chemical graph. Molecules are usually represented as vertices, while their bonding or interaction is shown by edges in a molecular graph. In this paper, we computed various connectivity indices based on degrees of vertices of a chemical graph of indium phosphide (InP). Afterward, we found the physical measures like entropy and heat of formation of InP. Then, we fitted curves between different indices and the thermodynamical properties, namely, heat of formation and entropy. Curve fitting was done in MATLAB through different methods based on linearity and nonlinearity. Furthermore, we depicted our results numerically and graphically. These numerical systems may give an approach to concentrate on the thermodynamical properties of the compound design of InP at an exceptional level that will help understand the connection between framework measurement and these actions.
In this paper, we use an identity of Fink and present some interesting identities and inequalities for real valued functions and r-convex functions respectively. We also obtain generalizations of some Hardy-Littlewood-P?lya type inequalities. In addition, we use the Cebysev functional and the Gr?ss type inequalities and find the bounds for the remainder in the obtained identities. Finally, we present an interesting result related to the Ostrowski type inequalities.
In this paper, we present some generalizations of an inequality of Hardy-Littlewood-Pólya.We give the n-exponential convexity and log-convexity of the functions associated with the linear functionals defined as the non-negative differences of the generalized inequalities and prove the monotonicity property of the generalized Cauchy means obtained via these functionals.Finally, we give several examples of the families of functions for which the results can be applied.An example of above theorem is given below (see [3, Theorem 134]).