A multiple-criteria decision problem for optimal management of farm resources under uncertainty - a case study

An attempt is made to minimize the total operational cost and specific energy for rice cultivation, when the constraints relating to the availability of power sources and crop yield are supposed to be stochastic in nature. The Sequential Linear Goal Programming algorithm has been used to solve the resulting multiple objective optimization problem.     

Distributed decision propagation in mobile-agent proximity networks

This paper develops a distributed algorithm for decision/awareness propagation in mobile-agent networks. A time-dependent proximity network topology is adopted to represent a mobile-agent scenario. The agent-interaction policy formulated here is inspired from the recently developed language-measure theory. Analytical results related to convergence of statistical moments of agent states are derived and then validated by numerical simulation. The results show that a single (user-defined) parameter in the agent interaction policy can be identified to control the trade-off between Propagation Radius (i.e. how far a decision spreads from its source) and Localisation Gradient (i.e. the extent to which the spatial variations may affect localisation of the source) as well as the temporal convergence properties.

     

Measuring software dependability by robustness benchmarking

Inability to identify weaknesses or to quantify advancements in software system robustness frequently hinders the development of robust software systems. Efforts have been made to develop benchmarks of software robustness to address this problem, but they all suffer from significant shortcomings. The paper presents the various features that are desirable in a benchmark of system robustness, and evaluates some existing benchmarks according to these features. A new hierarchically structured approach to building robustness benchmarks, which overcomes many deficiencies of past efforts, is also presented. This approach has been applied to building a hierarchically structured benchmark that tests part of the Unix file and virtual memory systems. The resultant benchmark has successfully been used to identify new response class structures that were not detected in a similar situation by other less organized techniques     

An object-based coding scheme for frontal surface of defective fluted ingot

A novel image-based defect identification and coding technique has been proposed for fluted ingots, which are used for the production of locomotive wheels. The edge density map has been used for defect identification and an object-based coding approach has been applied for the storage of defective ingots. The complete scheme has been implemented in one of the integrated steel plants of India.     

Design and implementation issues for a class of distribution-free Phase II EWMA exceedance control charts

Distribution-free (nonparametric) control charts can play an essential role in process monitoring when there is dearth of information about the underlying distribution. In this paper, we study various aspects related to an efficient design and execution of a class of nonparametric Phase II exponentially weighted moving average (denoted by NPEWMA) charts based on exceedance statistics. The choice of the Phase I (reference) sample order statistic used in the design of the control chart is investigated. We use the exact time-varying control limits and the median run-length as the metric in an in-depth performance study. Based on the performance of the chart, we outline implementation strategies and make recommendations for selecting this order statistic from a practical point of view and provide illustrations with a data-set. We conclude with a summary and some remarks.     

Classifying and detecting anomalies in hybrid knowledge-based systems

The increasing need for hybrid Knowledge-Based Systems (KBS) that accommodate more complex applications has led to the need for new verification concerns that are more specific to the hybrid representation using objects and rule-based inference. Traditionally, verification of expert systems has focused solely on rule-based inference systems. Hybrid KBSs present additional verification problems not found in traditional rule-based systems. This paper is an investigation into the anomalies that may be present in a hybrid representation that warrant detection for the verification of the KBS. Many anomalies are due to the interaction of the component parts of the hybrid KBS. For example, subsumption anomalies arise due to an interaction between inheritance of objects and rule-based inference. In this paper, we extend the context of subsumption anomalies and introduce additional types of anomalies that may be present in the KBS. The goal of this research is to make hybrid KBSs more reliable by detecting such anomalies.     

Comparative analysis of in vitro ultraviolet radiation protection of fabrics woven from cotton and bamboo viscose yarns

Ultraviolet protection factor (UPF) of fabrics made of 100% cotton and 100% bamboo viscose yarns were studied and a comparative analysis carried out using curve fitting technique. Bamboo viscose fabrics showed higher shrinkage, cover percentage, areal density and UPF compared to its cotton counterpart woven with identical yarn counts and fabric sett. However, the predictive model of cotton fabric UPF using fabric areal density as the input was able to estimate the UPF of bamboo viscose fabrics with very good accuracy. Furthermore, the 100% cotton and 100% bamboo viscose fabrics showed the same UPF if their cover percentage and areal density is similar. It is inferred from the analysis that the apparently higher UPF of bamboo viscose fabrics can be attributed to their higher cover percentage and areal density instead of bamboo’s inherent UV protective property which has been claimed in various literatures.     

A novel quasi-oppositional chaotic antlion optimizer for global optimization

This paper proposes a novel quasi-oppositional chaotic antlion optimizer (ALO) (QOCALO) for solving global optimization problems. ALO is a population based algorithm motivated by the unique hunting behavior of antlions in nature and exhibits strong influence in solving global and engineering optimization problems. In the proposed QOCALO algorithm of the present work, the initial population is generated using the quasi-opposition based learning (QOBL) and the concept of QOBL based generation jumping is utilized inside the main searching strategy of the proposed algorithm. Utilization of QOBL ensures better convergence speed of the proposed algorithm and it also provides better exploration of the search space. Alongside the QOBL, a chaotic local search (CLS) is also incorporated in the proposed QOCALO algorithm. The CLS guides local search around the global best solution that provides better exploitation of the search space. Thus, a better trade-off between exploration and exploitation holds for the proposed algorithm which makes it robust. It is observed that the proposed algorithm offers better results than the original ALO in terms of solution quality and convergence speed. The proposed QOCALO algorithm is implemented and tested, successfully, on nineteen mathematical benchmark test functions of varying complexities and the experimental results are compared to those offered by the basic ALO and some other recently developed nature inspired algorithms. The efficacy of the proposed algorithm is further utilized to solve three real world engineering optimization problems viz. (a) the placement and sizing problem of distributed generators in radial distribution networks, (b) the congestion management problem in power transmission system and (c) the optimal design of pressure vessel.     

Nuclear Data Sheets for A = 211

The evaluated spectroscopic data are presented for 11 known nuclides of mass 211 (Hg, Tl, Pb, Bi, Po, At, Rn, Fr, Ra, Ac, Th). The ²¹¹Pa nuclide is included here but its identification remains uncertain. For ²¹¹Hg, ²¹¹Tl, ²¹¹Ac and ²¹¹Th nuclei, only the ground–state information is available. Their decay characteristics are mostly unknown. ²¹¹Fr is suggested to decay partially through ε decay mode, but its decay scheme remains poorly known. While high–spin excitations, including several isomers, are well studied in ²¹¹Pb, ²¹¹Bi, ²¹¹Po, ²¹¹At, ²¹¹Rn and ²¹¹Fr, the particle–transfer data are available for only ²¹¹Po and ²¹¹Bi.This evaluation was carried out as part of joint IAEA–ICTP workshop for Nuclear Structure and Decay Data, organized and hosted by the IAEA, Vienna and ICTP, Trieste, August 6–17, 2012. This work supersedes previous A=211 evaluation (2004Br45) published by E. Browne which covered literature before January 2003.     

A fluorogenic peptide containing the processing site of human SARS corona virus S-protein: kinetic evaluation and NMR structure elucidation

Human severe acute respiratory syndrome coronavirus (hSARS-CoV) is the causative agent for SARS infection. Its surface glycoprotein (spike protein) is considered to be one of the prime targets for SARS therapeutics and intervention because its proteolytic maturation by a host protease is crucial for host-virus fusion. Using intramolecularly quenched fluorogenic (IQF) peptides based on hSARS-CoV spike protein (Abz-(755)Glu-Gln-Asp-Arg-Asn-Thr-Arg-Glu-Val-Phe-Ala-Gln(766)-Tyx-NH(2)) and in vitro studies, we show that besides furin, other PCs, like PC5 and PC7, might also be involved in this cleavage event. Through kinetic measurements with recombinant PCs, we observed that the peptide was cleaved efficiently by both furin and PC5, but very poorly by PC7. The cleavage could be blocked by a PC-inhibitor, alpha1-PDX, in a dose-dependent manner. Circular dichroism spectra indicated that this peptide possesses a high degree of sheet structure. Following cleavage by furin, the sheet content increased, possibly at the expense of turn and random structures. (1)H NMR spectra from 2D COSY and ROESY experiments under physiological buffer and pH conditions indicated that this peptide possesses a structure with a turn at its C-terminal segment, close to the cleavage site. The data suggest that the cleavable peptide bond is located within the most exposed domain; this is supported by the nearby turn structure. Several strong to weak NMR ROESY correlations were detected, and a 3D structure of the spike IQF peptide that contains the crucial cleavage site R(761) E has been proposed.