A generalization of the Chebyshev type inequalities for Sugeno integrals

In this paper, we give a generalization of the Chebyshev type inequalities for Sugeno integral with respect to non-additive measures. The main results of this paper generalize most of the inequalities for Sugeno integral obtained by many researchers. Also, some conclusions are drawn and some problems for further investigations are given.     

Frontier-based performance analysis models for supply chain management: State of the art and research directions

Effective supply chain management relies on information integration and implementation of best practice techniques across the chain. Supply chains are examples of complex multi-stage systems with temporal and causal interrelations, operating multi-input and multi-output production and services under utilization of fixed and variable resources. Acknowledging the lack of system’s view, the need to identify system-wide and individual effects as well as incorporating a coherent set of performance metrics, the recent literature reports on an increasing, but yet limited, number of applications of frontier analysis models (e.g. DEA) for the performance assessment of supply chains or networks. The relevant models in this respect are multi-stage models with various assumptions on the intermediate outputs and inputs, enabling the derivation of metrics for technical and cost efficiencies for the system as well as the autonomous links. This paper reviews the state of the art in network DEA modeling, in particular two-stage models, along with a critical review of the advanced applications that are reported in terms of the consistency of the underlying assumptions and the results derived. Consolidating current work in this range using the unified notations and comparison of the properties of the presented models, the paper is closed with recommendations for future research in terms of both theory and application.     

ASRSM: A Sequential Experimental Design for Response Surface Optimization

Most preset response surface methodology (RSM) designs offer ease of implementation and good performance over a wide range of process and design optimization applications. These designs often lack the ability to adapt the design on the basis of the characteristics of application and experimental space so as to reduce the number of experiments necessary. Hence, they are not cost‐effective for applications where the cost of experimentation is high or when the experimentation resources are limited. In this paper, we present an adaptive sequential response surface methodology (ASRSM) for industrial experiments with high experimentation cost, limited experimental resources, and high design optimization performance requirement. The proposed approach is a sequential adaptive experimentation approach that combines concepts from nonlinear optimization, design of experiments, and response surface optimization. The ASRSM uses the information gained from the previous experiments to design the subsequent experiment by simultaneously reducing the region of interest and identifying factor combinations for new experiments. Its major advantage is the experimentation efficiency such that for a given response target, it identifies the input factor combination (or containing region) in less number of experiments than the classical single‐shot RSM designs. Through extensive simulated experiments and real‐world case studies, we show that the proposed ASRSM method outperforms the popular central composite design method and compares favorably with optimal designs. Copyright © 2012 John Wiley & Sons, Ltd.     

Siting of PV power plants on inclined terrains

Most of the studies conducted on solar energy assessment and solar system siting focus on flat terrains that are usually difficult and expensive to acquire in urban areas. This paper investigates the possibility of using inclined terrains for siting photovoltaic (PV) power plants surrounding urban area. Both analytical analysis and simulations are carried out in order to analyse and validate the effectiveness and benefits of the use of inclined land for PV siting. Geographical information system and numerical weather prediction were used to implement the suggested original approach and to select suitable inclined terrains for the PV system installation and to calculate the total generation potential for energy production. Muscat, the capital of Oman, was selected as a reference for the implementation of this approach.     

Impact of Offloading on the Efficiency of Wireless Access Networks

International Journal of Wireless Information Networks - Wireless access networks need to deliver a satisfactory level of Quality of Service (QoS) to their subscribers. The service quality can be...     

Prediction of heavy oil viscosity using a radial basis function neural network

Heavy oil and extra heavy oil resources comprise about 75% of petroleum resources. The most important characteristic of heavy oils is their viscosity. Consequently, to extract and prepare these kinds of crude oil for use, great emphasis should be put on viscosity. The present study highlights the application of intelligent model named radial basis function (RBF) network optimized by genetic algorithm for estimation of diluted heavy oil viscosity in presence on kerosene. The input parameters of model were temperature and mass fraction of kerosene. The output of model was viscosity of heavy oil. Genetic algorithm was utilized to optimize the tuning parameters of RBF model. The outcomes of this study showed that the proposed model is accurate in estimation of target data.     

Viable Mycobacterium avium ssp. paratuberculosis isolated from calf milk replacer

When advising farmers on how to control Johne's disease in an infected herd, one of the main recommendations is to avoid feeding waste milk to calves and instead feed calf milk replacer (CMR). This advice is based on the assumption that CMR is free of viable Mycobacterium avium ssp. paratuberculosis (MAP) cells, an assumption that has not previously been challenged. We tested commercial CMR products (n = 83) obtained from dairy farms around the United States by the peptide-mediated magnetic separation (PMS)-phage assay, PMS followed by liquid culture (PMS-culture), and direct IS900 quantitative PCR (qPCR). Conventional microbiological analyses for total mesophilic bacterial counts, coliforms, Salmonella, coagulase-negative staphylococci, streptococci, nonhemolytic Corynebacterium spp., and Bacillus spp. were also performed to assess the overall microbiological quality of the CMR. Twenty-six (31.3%) of the 83 CMR samples showed evidence of the presence of MAP. Seventeen (20.5%) tested positive for viable MAP by the PMS-phage assay, with plaque counts ranging from 6 to 1,212 pfu/50 mL of reconstituted CMR (average 248.5 pfu/50 mL). Twelve (14.5%) CMR samples tested positive for viable MAP by PMS-culture; isolates from all 12 of these samples were subsequently confirmed by whole-genome sequencing to be different cattle strains of MAP. Seven (8.4%) CMR samples tested positive for MAP DNA by IS900 qPCR. Four CMR samples tested positive by both PMS-based tests and 5 CMR samples tested positive by IS900 qPCR plus one or other of the PMS-based tests, but only one CMR sample tested positive by all 3 MAP detection tests applied. All conventional microbiology results were within current standards for whole milk powders. A significant association existed between higher total bacterial counts and presence of viable MAP indicated by either of the PMS-based assays. This represents the first published report of the isolation of viable MAP from CMR. Our findings raise concerns about the potential ability of MAP to survive manufacture of dried milk-based products.     

The relaxed optimal control problem for Mean-Field SDEs systems and application

The present study deals with a new approach of optimal control problems where the state equation is a Mean-Field stochastic differential equation, and the set of strict (classical) controls need not be convex and the diffusion coefficient depends on the term control. Our consideration is based on only one adjoint process, and the necessary conditions as well as a sufficient condition for optimality in the form of a relaxed maximum principle are obtained, with application to Linear quadratic stochastic control problem with mean-field type.     

Subspace-based technique for speech encryption

The use of signal processing techniques in cryptographic field is an attractive approach in recent years. As an example, the intractability of the under-determined blind source separation (BSS) problem has been used for the proposal of BSS-based speech encryption. However, some weaknesses of this proposal from a cryptographic point of view have been recently published. In this paper, we propose a new encryption method that bypass these weaknesses. The proposed approach is based on the subspace concept together with the use of nonlinear functions and key signals. An interesting feature of the proposed technique is that only a part of the secret key parameters used during encryption is necessary for decryption. Furthermore, if no plain-text is fed to the encryption algorithm, the latter will provide no contents. Analysis results show that the proposed method significantly enhances the security level of existing BSS-based speech encryption methods.