Reconstruction of reflectance spectra using weighted principal component analysis

The weighted principal component analysis technique is employed for reconstruction of reflectance spectra of surface colors from the related tristimulus values. A dynamic eigenvector subspace based on applying certain weights to reflectance data of Munsell color chips has been formed for each particular sample and the color difference value between the target, and Munsell dataset is chosen as a criterion for determination of weighting factors. Implementation of this method enables one to increase the influence of samples which are closer to target on extracted principal eigenvectors and subsequently diminish the effect of those samples which benefit from higher amount of color difference. The performance of the suggested method is evaluated in spectral reflectance reconstruction of three different collections of colored samples by the use of the first three Munsell bases. The resulting spectra show considerable improvements in terms of root mean square error between the actual and reconstructed reflectance curves as well as CIELAB color difference under illuminant A in comparison to those obtained from the standard PCA method. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 360–371, 2008     

Genetic evidence for the role of isocytochrome c2 in photosynthetic growth of Rhodobacter sphaeroides Spd mutants

In Rhodobacter sphaeroides, cytochrome c2 (cyt c2)-deficient mutants are photosynthetically incompetent (PS-). However, mutations which suppress the photosynthetic deficiency (spd mutations) of cyt c2 mutants increase the levels of a cyt c2 isoform, isocyt c2. To determine whether isocyt c2 was required for photosynthetic growth of Spd mutants, we used Tn5 mutagenesis to generate a PS- mutant (TP39) that lacks both cyt c2 and isocyt c2. DNA sequence analysis of wild-type DNA that restores isocyt c2 production and photosynthetic growth to TP39 indicates that it encodes the isocyt c2 structural gene, cycI. The Tn5 insertion in TP39 is approximately 1.5 kb upstream of cycI, and our results show that it is polar onto cycI. The cycI gene has been physically mapped to a region of chromosome I that is approximately 700 kb from the R. sphaeroides photosynthetic gene cluster. Construction of a defined cycI null mutant and complementation of several mutants with the cycI gene under the control of the cyt c2 promoter region indicate that an increase in the levels of isocyt c2 alone is necessary and sufficient for photosynthetic growth in the absence of cyt c2. The data are discussed in terms of the obligate role of isocyt c2 in cyt c2-independent photosynthesis of R. sphaeroides.     

An extended minimax disparity to determine the OWA operator weights

This paper contributes to extend the minimax disparity to determine the ordered weighted averaging (OWA) model based on linear programming. It introduces the minimax disparity approach between any distinct pairs of the weights and uses the duality of linear programming to prove the feasibility of the extended OWA operator weights model. The paper finishes with an open problem.     

Threshold cryptography based on Asmuth-Bloom secret sharing

In this paper, we investigate how threshold cryptography can be conducted with the Asmuth-Bloom secret sharing scheme and present three novel function sharing schemes for RSA, ElGamal and Paillier cryptosystems. To the best of our knowledge, these are the first provably secure threshold cryptosystems realized using the Asmuth-Bloom secret sharing. Proposed schemes are comparable in performance to earlier proposals in threshold cryptography.     

A comparison between reliability analyses based primarily on disjointness or statistical independence: The case of the generalized indra network

A switching expression is readily convertible to a reliability expression if (a) all ORed terms are disjoint, and (b) all ANDed sums are statistically independent. The usual approach of system reliability analysis makes a primary use of (a) and a secondary use of (b). An alternative approach reverses the roles of (a) and (b). Symbolic reliability expressions for the source-to-terminal reliability of a generalized Indra network (GIN) with nonidentical components are derived by the two approaches. For this particular case, the second approach leads to a shorter, more elegant derivation and simpler novel results. Typical plots of the GIN reliability functions are presented and their properties are discussed.     

Screening for diabetic retinopathy: the utility of nonmydriatic retinal photography in Egyptian adults

BACKGROUND AND OBJECTIVE: Drug resistance has become a major cause of treatment failure in patients with acute leukemia. P-glycoprotein (Pgp), which is associated with the multidrug resistance (MDR) phenotype, has been reported to be an important predictor of treatment outcome. The aim of this study was to analyze the value of Pgp expression in bone marrow or peripheral blood as a predictor of the response to remission induction chemotherapy as well as the duration of remission in patients with de novo acute myeloid leukemia (AML). DESIGN AND METHODS: We examined the expression of Pgp in 82 patients with de novo AML using an immunocytochemical assay with the C219 monoclonal antibody. RESULTS: Twenty-seven of the 82 patients (33%) were C219-positive in from 1% to 100% of their cells. Thirteen cases (16%) showed a positive reaction in more than 50% of the leukemic cells. Only hyperleukocytosis was significantly associated with higher expression of Pgp. Although 8 of the 13 cases (62%) with more than 50% of cells having Pgp expression were CD34-positive, this association was not statistically significant. A univariate analysis of resistance to induction therapy showed a significantly higher resistance rate in patients with increased Pgp expression (P = 0.01) as well as in those patients with decreased reactivity to myeloperoxidase. The multivariate analysis revealed the independent prognostic value of Pgp expression. C219 reactivity did not have an influence on remission duration. INTERPRETATION AND CONCLUSIONS: Our data indicate that P-glycoprotein expression is a reliable marker of resistance to induction treatment in patients with de novo AML.     

Uniform modeling of parameter dependent nonlinear systems

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. Modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ’multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.     

Optimal Development of Agricultural Sectors in the Basin Based on Economic Efficiency and Social Equality

The limitation of freshwater resources and the growing demand for water, make the issue of water resource development planning and water allocation among stakeholders even more important. Ideally, water allocation should be economically efficient and socially equitable. In this study, a water allocation model is presented in an integrated framework that considers the interaction of water supply and demand according to economic and social factors. To achieve this, a reliability-based multi-objective optimization - simulation approach has been employed. The objective functions of the problem are: 1) maximizing GDP from agricultural sectors and 2) maximizing social equality in different provinces of the basin (measured using the Williamson coefficient). The fair development and allocation among the shared provinces in the basin can reduce conflicts in the region. Karkheh basin has been considered as a case study and decision variables of the problem are area under cultivation of agricultural development sectors in different provinces. The results show that, without harming the income of the agricultural sector, the spatial distribution of development projects can be done in such a way that equality (according to income level and the number of people working in each province) is achieved. One of the solutions of Pareto front compared to previous studies shows that, in addition to an increase of about 12% of the objective function 1 (GDP), the value of the objective function 2 (Williamson coefficient) decreased from 1.19 to 0.98. This indicates a decrease in income inequality among the provinces of the basin.

     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.

     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.