Non-fragile robust optimal guaranteed cost control of uncertain 2-D discrete state-delayed systems

This paper is concerned with the problem of non-fragile robust optimal guaranteed cost control for a class of uncertain two-dimensional (2-D) discrete state-delayed systems described by the general model with norm-bounded uncertainties. Our attention is focused on the design of non-fragile state feedback controllers such that the resulting closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible parameter uncertainties and controller gain variations. A sufficient condition for the existence of such controllers is established under the linear matrix inequality framework. Moreover, a convex optimisation problem is proposed to select a non-fragile robust optimal guaranteed cost controller stabilising the 2-D discrete state-delayed system as well as achieving the least guaranteed cost for the resulting closed-loop system. The proposed method is compared with the previously reported criterion. Finally, illustrative examples are given to show the potential of the proposed technique.     

ILP-assisted de novo drug design

The accurate and early detection of epileptic seizures in continuous electroencephalographic (EEG) data has a growing role in the management of patients with epilepsy. Early detection allows for therapy to be delivered at the start of seizures and for caregivers to be notified promptly about potentially debilitating events. The challenge to detecting epileptic seizures, however, is that seizure morphologies exhibit considerable inter-patient and intra-patient variability. While recent work has looked at addressing the issue of variations across different patients (inter-patient variability) and described patient-specific methodologies for seizure detection, there are no examples of systems that can simultaneously address the challenges of inter-patient and intra-patient variations in seizure morphology. In our study, we address this complete goal and describe a multi-task learning approach that trains a classifier to perform well across many kinds of seizures rather than potentially overfitting to the most common seizure types. Our approach increases the generalizability of seizure detection systems and improves the tradeoff between latency and sensitivity versus false positive rates. When compared against the standard approach on the CHB–MIT multi-channel scalp EEG data, our proposed method improved discrimination between seizure and non-seizure EEG for almost 83 % of the patients while reducing false positives on nearly 70 % of the patients studied.     

An improved timestamp-based remote user authentication scheme

To protect the remote server from various malicious attacks, many authentication schemes have been proposed. Some schemes have to maintain a password verification table in the remote server for checking the legitimacy of the login users. To overcome potential risks of verification tables, researchers proposed remote user authentication schemes using smartcard, in which the remote server only keeps a secret key for computing the user’s passwords and does not need any verification table for verifying legal user. In 2003 Shen, Lin, and Hwang proposed a timestamp-based password authentication scheme using smartcards in which the remote server does not need to store the passwords or verification table for user authentication. Unfortunately, this scheme is vulnerable to some deadly attacks. In this paper, we analyze few attacks and finally propose an improved timestamp-based remote user authentication scheme. The modified scheme is more efficient and secure than original scheme.     

OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Pre-Existing Ontologies

There has been an explosion in the types, availability and volume of data accessible in an information system, thanks to the World Wide Web (the Web) and related inter-networking technologies. In this environment, there is a critical need to replace or complement earlier database integration approaches and current browsing and keyword-based techniques with concept-based approaches. Ontologies are increasingly becoming accepted as an important part of any concept or semantics based solution, and there is increasing realization that any viable solution will need to support multiple ontologies that may be independently developed and managed. In particular, we consider the use of concepts from pre-existing real world domain ontologies for describing the content of the underlying data repositories. The most challenging issue in this approach is that of vocabulary sharing, which involves dealing with the use of different terms or concepts to describe similar information. In this paper, we describe the architecture, design and implementation of the OBSERVER system. Brokering across the domain ontologies is enabled by representing and utilizing interontology relationships such as (but not limited to) synonyms, hyponyms and hypernyms across terms in different ontologies. User queries are rewritten by using these relationships to obtain translations across ontologies. Well established metrics like precision and recall based on the extensions underlying the concepts are used to estimate the loss of information, if any.     

Design of fructose-2,6-bisphosphatase inhibitors: a novel virtual screening approach

Fructose-2,6-bisphosphatase (FBPase-2) is a switch between gluconeogenesis and glycolysis in the hepatic cells. The structural features required for inhibitory activity of FBPase-2 were unidentified; no leads are available for inhibiting this important enzyme. In this paper pharmacophore mapping, molecular docking methods were employed in a virtual screening strategy to identify leads for FBPase-2. A receptor based pharmacophore map was modeled which comprised of important interactions as observed in co-crystal of rat liver isozyme with the product inhibitor fructose-6-phosphate. The pharmacophore model was validated against two databases of best docked structural analogues of fructose-2,6-bisphosphate and fructose-6-phosphate. The query generated was submitted for flexible search of ligands in chemical databases, namely LeadQuest, Maybridge and NCI. The hits obtained were further screened by molecular docking using FlexX.     

Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).     

Effect of impurities (graphite) on the high-temperature creep properties of NiAl

Previous high-temperature compression creep studies of NiAl have shown peculiar behaviour in the temperature range 700 to 900° C, which was perhaps due to precipitation of impurities in the matrix. To isolate the impurity effect, high-purity NiAl samples with 0.15 at% and 0.20 at% carbon (graphite) additions have been creep tested at four temperatures between 700 and 850° C. Addition of graphite has been shown to produce a significant reduction in the creep strength of the alloyS. However, alloys with higher graphite concentrations have shown better creep resistance than those with lower graphite concentrations. Transmission electron microscopy indicates the presence of competing softening and hardening mechanisms in the alloys. Softening is due to the graphite particles acting as a dislocation source. Hardening results from a grain-boundary hardening mechanism due to the graphite particles segregating at grain boundaries and a dislocation-impurity (fine graphite) interaction, developing a Cottrell-like atmosphere.     

Densification of Alumina and Silica in the Presence of a Liquid Phase

Alumina and silica powders were sintered at 1250° to 1460°C in the presence of liquid phases containing CaO, A1₂O₃, and SiO₂. The data were analyzed using the equation D = K log t +C and the Arrhenius equation. The activation energy for sintering decreases with increasing amounts of liquid phase.     

Exact fuzzy optimal solution of fully fuzzy linear programming problems with unrestricted fuzzy variables

Kumar et al. (Appl. Math. Model. 35:817?C823, 2011) pointed out that there is no method in literature to find the exact fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems and proposed a new method to find the fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. There may exist several FFLP problems with equality constraints in which no restriction can be applied on all or some of the fuzzy variables but due to the limitation of the existing method these types of problems can not be solved by using the existing method. In this paper a new method is proposed to find the exact fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy coefficients and unrestricted fuzzy variables. The proposed method can also be used to solve the FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. To show the advantage of the proposed method over existing method the results of some FFLP problems with equality constraints, obtained by using the existing and proposed method, are compared. Also, to show the application of proposed method a real life problem is solved by using the proposed method.     

崛起的印度钢铁业

一、印度钢铁工业发展历史和现状从远古时代开始,铁在人类的生活中就非常重要。无论是战争还是和平年代,钢铁对现代文明的发展是必不可少的。为了了解印度的钢铁工业,首先有必要简要地回顾一下印度的钢铁制造史。印度是一个古老的国度,文化遗产丰富。印度是一片不同地域间存在惊人差异的土地,而两百多年的殖民统治更造就了多样化的印度。除了几家糖厂和纺