External watchman routes

We consider the problem of finding a shortest watchman route from which the exterior of a polygon is visible (external watchman route). We present an O (n ⁴ log logn) algorithm to find shortest external watchman routes for simple polygons by transforming the external watchman route problem to a set of internal watchman route problems. Also, we present faster external watchman route algorithms for special cases. These include optimal O (n) algorithms for convex, monotone, star and spiral polygons and an O (n log logn) algorithm for rectilinear polygons.This work was supported in part by a grant from Texas Instruments, Inc. to S. Ntafos     

State of the academic field of IS in India

The field of information systems (IS) remains ill-defined, facing problems of recognition and identity crisis. Several papers and debates have been dedicated on this topic for over three decades. The focus of these debates have largely centered on the state of the IS field in Americas and Europe and with a limited study conducted in the Asia–Pacific context. This study attempts to assess the field in the Indian context and highlight the challenges and issues faced by IS faculties in India. Based on literature survey of the seminal papers in the field, we identified the salient topics of interest to IS researchers: identity of the IS field; diversity of the field; research approaches, methods and rigor; reference disciplines; journals and conferences; and IS course and curriculum. A two-phase study was carried out to explore the interest generated by the IS field in India. In the first phase, secondary data review of leading business schools in India was carried out to understand their focus on IS as an academic discipline. In the second phase, we conducted interviews of IS researchers from the premium business schools in India. In our study, we analyze the research focus of IS faculties in B-schools in India, analyze the composition of the faculty pool and the nature of research work undertaken by them. Our study points at the restricted focus of IS researchers in India around a few narrow areas, with a significant breadth of topics not being explored for research. We found the identity struggle of the field to be prominent, which was further compounded by the limited number of active, IS researchers. The growing importance of qualitative techniques in IS research, the challenges of developing a sound base in multiple reference disciplines and the need for making IS course interesting for business school students were some of the other significant observations. Our study also highlighted the paradox of the success of the IT industry in India leading to reduced enrollment of IS courses in B-Schools. We conclude by providing recommendations to B-school deans and directors.     

Motif patterns in 2D

Motif patterns consisting of sequences of intermixed solid and don’t-care characters have been introduced and studied in connection with pattern discovery problems of computational biology and other domains. In order to alleviate the exponential growth of such motifs, notions of maximal saturation and irredundancy have been formulated, whereby more or less compact subsets of the set of all motifs can be extracted, that are capable of expressing all others by suitable combinations. In this paper, we introduce the notion of maximal irredundant motifs in a two-dimensional array and develop initial properties and a combinatorial argument that poses a linear bound on the total number of such motifs. The remainder of the paper presents approaches to the discovery of irredundant motifs both by offline and incremental algorithms.     

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 TiO2 Nano-Filler on Electrical Properties of Na+ Ion Conducting PEO/PVDF Based Blended Polymer Electrolyte

Journal of Inorganic and Organometallic Polymers and Materials - Nanocomposite polymer electrolyte (NCPE) films based on a blend of two polymers poly (ethylene oxide) (PEO) and poly (vinylidene...     

Two Channel Thermally Tunable Band-Stop Filter for Wavelength Selective Switching Applications by Using 1D Ternary Superconductor Photonic Crystal

By studying temperature-dependent dispersion characteristics and group velocity of 1D ternary photonic crystal (TPC) composed of dielectric-superconductor-dielectric materials, a thermally tunable band-stop filter which is capable of stopping unique wavelength channels without causing any interference amongst equally spaced wavelength channels of full width at half maximum of 1 nm each as per the requirement of wavelength division multiplexing standards adopted by the International Telecommunication Union specifying channel spacing in terms of frequency (wavelength) is suggested. The proposed structure can efficiently work as a two-channel wavelength selective switch for wavelength division multiplexing (WDM)-based all-optical networks. This study also gives theoretical insight to design some new kind of optical memories and tunable buffers which holds data temporary and have potential applications in modern communication systems.     

Optimization of Aspergillus niger Fermentation for the Production of Glucose Oxidase

A number of nutritional factors influencing glucose oxidase (EC 1.1.3.4) production by Aspergillus niger NCIM 545 were studied. The synthesis of glucose oxidase by A. niger was investigated in two steps using submerged fermentation at 30 ± 2 °C and 180 rpm for 96 h. Primarily, nutritional components were selected by one-factor-at-a-time method, and the significance of each component with respect to glucose oxidase production was identified by Plackett–Burman design (seven variables including six nutritional viz. sucrose, sodium nitrate, peptone, calcium carbonate, magnesium sulfate, and potassium dihydrogen phosphate, and one dummy or unassigned variable were studied with eight experiments). In the second step, concentration of most significant factors and their interaction were studied with response surface methodology (central composite design). Each variable in the design was studied at five different levels, with all variables taken at a central coded value of zero. Considerable amount of glucose oxidase was produced from A. niger species with sucrose as the carbon source, sodium nitrate as the inorganic nitrogen source, and peptone as the organic nitrogen source. Glucose oxidase activity increased remarkably by 28.93 fold (from 0.00993 to 0.29 U ml⁻¹) with CaCO₃-supplemented media. The outcome of Plackett–Burman design showed CaCO₃, peptone, and MgSO₄ as significant parameters. Further optimization using a three-factor central composite design with 20 experiments increased yield of glucose oxidase from 0.29 to 2.05 U ml⁻¹ (sevenfold) with a decrease in cultivation time from 96 to 72 h.     

Cellular Internalization of Water‐Soluble Helical Aromatic Amide Foldamers

The intracellular transport of drugs and therapeutics represents one of the most exciting and challenging areas at the interface of chemistry, biology, and medicine. Most of the effort in this field so far has been devoted to the development of peptide‐based delivery systems that can translocate therapeutic agents into their intracellular targets. More recently, the use of bioinspired non‐natural foldamers has resulted in the successful delivery of cargo molecules, which possess a wide range of sizes and physicochemical properties across the cell membrane. We report herein the synthesis of aromatic amide foldamers and their biological evaluation as cell‐penetrating agents. By using a well‐established synthetic route, a series of fluorescein‐labeled cationic aryl amide conjugates has been constructed, and their cellular uptake into various human cell lines has been analyzed by flow cytometry and fluorescence microscopy. The assays revealed that longer oligomers achieve greater cellular translocation, with octamer Q8 proving to be a remarkable vehicle for all three cell lines. Biological studies have also indicated that these helices are biocompatible, thus showing promise in their application as cell‐penetrating agents and as vehicles to deliver biologically active molecules into cells.     

Integrated evolutionary neural network approach with distributed computing for congestion management

Electric supply industry is facing deregulation all over the world. Under deregulated power supply scenario, power transmission congestion has become more intensified and recurrent, as compared to conventional regulated power system. Congestion may lead to violation of voltage or transmission capacity limits, thus threatens the power system security and reliability. Also the growing congestion may lead to unanticipated divergent electricity pricing. Owing to these facts congestion management has become a crucial issue in the deregulated power system scenario.Fast and precise prediction of nodal congestion prices in real time deregulated/spot power market may enable market participants and system operators to keep pace with the congestion by taking preventive measures like transaction rescheduling, bids (both for supplying and consuming electricity) modification, regulated dispatch of electric power, etc. This paper proposes an integrated evolutionary neural network (ENN) approach to predict nodal congestion prices (NCPs) for congestion management in spot power market. Distributed computing is employed to tackle the heterogeneity of the data in the prediction of NCP values. Developed ENNs have been trained and tested under distributed computing environment, using a message passing paradigm. Proposed hybrid approach for NCP prediction is demonstrated on a 6-bus test power system with and without distributed computing. The proposed approach not only demonstrated the computing efficiency of the developed ENN model over the conventional optimal power flow method but also shows the time saving aspect of distributed computing.