Fully Fuzzy Quadratic programming with unrestricted Fully Fuzzy variables and Parameters

There exist several methods for solving fuzzy linear or nonlinear programming problems under positivity fuzzy variables and restricted fuzzy coefficients. Due to the limitation of these methods, they can’t be applied for solving fully fuzzy linear or nonlinear programming problems with unrestricted fuzzy coefficients and fuzzy variables. In this paper an efficient method to find the fuzzy optimal solution for fully fuzzy quadratic programming (FFQP) problem with unrestricted variables and parameters has been proposed. All the coefficients and decision variables of both objective functions and the constraints are triangular fuzzy numbers. The proposed method is based on converted FFQP problem into crisp quadratic programming (CQP) problem. Finally an illustrative numerical example has been given to clarify the proposed solution method

A prototype framework for models of socio-hydrology: identification of key feedback loops and parameterisation approach

It is increasingly acknowledged that, in order to sustainably manage global freshwater resources, it is critical that we better understand the nature of human–hydrology interactions at the broader catchment system scale. Yet to date, a generic conceptual framework for building models of catchment systems that include adequate representation of socioeconomic systems – and the dynamic feedbacks between human and natural systems – has remained elusive. In an attempt to work towards such a model, this paper outlines a generic framework for models of socio-hydrology applicable to agricultural catchments, made up of six key components that combine to form the coupled system dynamics: namely, catchment hydrology, population, economics, environment, socioeconomic sensitivity and collective response. The conceptual framework posits two novel constructs: (i) a composite socioeconomic driving variable, termed the Community Sensitivity state variable, which seeks to capture the perceived level of threat to a community's quality of life, and acts as a key link tying together one of the fundamental feedback loops of the coupled system, and (ii) a Behavioural Response variable as the observable feedback mechanism, which reflects land and water management decisions relevant to the hydrological context. The framework makes a further contribution through the introduction of three macro-scale parameters that enable it to normalise for differences in climate, socioeconomic and political gradients across study sites. In this way, the framework provides for both macro-scale contextual parameters, which allow for comparative studies to be undertaken, and catchment-specific conditions, by way of tailored "closure relationships", in order to ensure that site-specific and application-specific contexts of socio-hydrologic problems can be accommodated. To demonstrate how such a framework would be applied, two socio-hydrological case studies, taken from the Australian experience, are presented and the parameterisation approach that would be taken in each case is discussed. Preliminary findings in the case studies lend support to the conceptual theories outlined in the framework. It is envisioned that the application of this framework across study sites and gradients will aid in developing our understanding of the fundamental interactions and feedbacks in such complex human–hydrology systems, and allow hydrologists to improve social–ecological systems modelling through better representation of human feedbacks on hydrological processes

Immunohistochemical localization of mdm-2, p27Kip1 and bcl-2 in Warthin's tumor of the parotid gland

<p>Abstract</p> <p>Background</p> <p>Warthin's tumor is a benign monomorphic adenoma with unclear origin that almost occur exclusively in the parotid gland. Etiology of Warthin's tumor as well as its malignant potential are still unclear. Therefore immunohistochemical assessment of Warthin's tumor may be useful to detect its origin or its malignant transformation potential.</p> <p>Aims and objectives</p> <p>The present study aims to investigate the immunohistochemical expression of murine double minute-2 (mdm-2), p27^Kip1and B cell lymphoma-2 (bcl-2) in Warthin's tumor of parotid gland and also to clarify the role of these proteins in the behavior of that tumor.</p> <p>Methods</p> <p>Twenty paraffin blocks of cases previously diagnosed as Warthin's tumor were collected for immunohistochemical staining with primary antibodies against mdm-2, p27^Kip1and bcl-2 using streptavidin-biotin immunoperoxidase staining system.</p> <p>Results</p> <p>All cases showed immunopositivity for mdm-2 and p27^Kip1while 18/20 showed bcl-2 immunopositivity. Both layers of the neoplastic epithelial cells that line the cystic spaces showed immunopositivity with all antibodies used. Goblet cells were mdm-2 immunonegative while myoepithelial cells were p27^Kip-1immunonegative. Areas of epithelial proliferation that formed buds were p27^Kip-1and bcl-2 immunopositive.</p> <p>Conclusion</p> <p>Mdm-2 played a tumor-suppressor role that might be implicated with the benign behavior of Warthin's tumor. The mutual expression of both p27^Kip1and bcl-2 suggested a protective role of these slowly proliferating cells from apoptosis to maintain their survival and elevated bcl-2 expression offers a significant protection against p27^Kip1-mediated apoptosis.</p

Detection of helicopters using neural nets

Artificial neural networks (ANNs), in combination with parametric spectral representation techniques, are applied for the detection of helicopter sound. Training of the ANN detectors was based on simulated helicopter sound from four helicopters and a variety of nonhelicopter sounds. Coding techniques based on linear prediction coefficients (LPCs) have been applied to obtain spectral estimates of the acoustic signals. Other forms of the LPC parameters such as reflection coefficients, cepstrum coefficients, and line spectral pairs (LSPs) have also been used as feature vectors for the training and testing of the ANN detectors. We have also investigated the use of wavelet transform for signal de-noising prior to feature extraction. The performance of various feature extraction techniques is evaluated in terms of their detection accurac

Comparative analysis of diversity based on morphoagronomic traits and molecular markers in durum wheat under heat stress

The objectives of this study were to compare the application and utility of sequence-related amplified polymorphism (SRAP) and target region amplification polymorphism (TRAP) techniques for the analysis of genetic diversity among durum wheat genotypes under heat stress and to compare genetic diversity estimated using molecular markers with morpho-agronomic performance under heat stress. Six durum wheat genotypes were used in this study. They were evaluated phenotypically for heat tolerance. The dendrogram generated from standardized morpho-agronomic data separated the six durum wheat genotypes into three main groups. The dendrogram generated from the standardized morpho-agronomic data separated the six durum wheat genotypes into three clusters, which diverged at similarity index of 0.72. The dendrogram based on SRAP markers differed from that based on TRAP markers. The combined dendrogram (SRAP, TRAP and morpho-agronomic data) agrees better with the grouping of these durum wheat genotypes depending on pedigree and the dendrogram generated by morpho-agronomic data alone.Key words: Durum wheat, genetic diversity, heat tolerance, morpho-agronomic, sequence-related amplified polymorphism (SRAP) markers, target region amplification polymorphism (TRAP) markers

Fast Methods Fbr Split Codebooks

This paper presents a fast method for building and searching split codebooks for vector quantization. The proposed method is evaluated in near transparent quality vector quantization of Line Spectral Frequencies (LSF) at 24-bit per frame. The method is based on a family of fractals called Space-Filling Curves (SFC). The SF curves achieve a significant saving in the complexity of vector quantization by reducing the problem to quantization in one-dimensional space. The paper presents algorithms for the generation of the SFC mapping utilizing the self-replication feature of the curves, and a number of simulation experiments to demonstrate the effectiveness of the method. It is shown that the SFC can reduce the search complexity of split codebooks by a factor of 8-32 times with a slight degradation in the vector quantization performance

Fast Methods Fbr Split Codebooks

This paper presents a fast method for building and searching split codebooks for vector quantization. The proposed method is evaluated in near transparent quality vector quantization of Line Spectral Frequencies (LSF) at 24-bit per frame. The method is based on a family of fractals called Space-Filling Curves (SFC). The SF curves achieve a significant saving in the complexity of vector quantization by reducing the problem to quantization in one-dimensional space. The paper presents algorithms for the generation of the SFC mapping utilizing the self-replication feature of the curves, and a number of simulation experiments to demonstrate the effectiveness of the method. It is shown that the SFC can reduce the search complexity of split codebooks by a factor of 8-32 times with a slight degradation in the vector quantization performance

A Dynamic Programming Algorithm For Days-Off Scheduling With Sequence Dependent Labor Costs

This paper presents a dynamic programming (DP) algorithm for solving a labor scheduling problem with several realistic days-off scheduling constraints and a cost structure that depends on the work sequence for each employee. The days-off scheduling constraints include the following: (1) each employee is assigned no more than three workdays per week, (2) each employee is assigned at least two consecutive off days per week, and (3) any work stretch cannot exceed four consecutive workdays. The sequence-dependent cost structure assumes that the daily wage of each employee depends on two factors: (1) whether the given workday is weekend or a regular workday, and (2) the sequence of work patterns assigned in previous days. A DP algorithm suited to instances of moderate size is used to determine the optimum work assignments that minimize the total labor cost, while satisfying the work demand under the stated constraints