Abstract

The shortage of experimental platforms needed for learning IT systems in a hands-on way is one reason for the lack of quality education in the area of IT. For most students who have access to a PC, their ability to experiment on that machine is limited by the risk of possible irrecoverable damage their experimentation may cause to the equipment. We report the development of a 'Virtual Laboratory for Systems and Software' that teaches the basics of Linux. The goal of this laboratory is to give the students a platform through which they can learn the essentials of linux. The student interacts with a virtual instance of a linux machine through the browser on his machine to learn basic tasks of linux system administration. The student's machine could be running any operating system (not necessarily linux). This obviates the need to have a linux machine on the part of the student. The lab consists of a suite of experiments designed as web applications which are based on IT Workshop courses at undergraduate level in universities.

Abstract

Distributed and concurrent development of virtual labs across multiple institutes and teams presents several challenges, both organizational and technical in nature. We present models for managing the process of virtual lab development, deployment and distribution. Close to twenty labs in computer science and chemical sciences are currently following our model. The architecture is designed to ultimately encourage and support a community ecosystem where teachers or students from any college could contribute to lab development, and a college could choose to subscribe to a set of virtual labs. Our deployment model, yet to be fully implemented, has as its back end a flexible virtualization architecture for running experiments and and a package based distribution model that encourages community participation in the use of virtual labs.

Abstract

We define the class of primal maps using the concepts of mapcode theory and show that a map is primal if and only if it is partial recursive.

Abstract

A set X together with a finite collection of self-maps on X is called a multiple discrete flow. We develop the theory of fair convergence for multiple flows and show how the UNITY programs of Chandy and Misra can be reformulated in terms of this theory.

Abstract

Prediction of electric load is very important issue for modern day power system engineers and a very good day ahead prediction of electric load is required for efficient performance of various Energy Management System (EMS) functions such as unit commitment, economic dispatch, fuel scheduling, and unit maintenance. A fuzzy based approach for day ahead prediction of electric load using Mahalanobis distance has been chosen in this work. Mahalanobis distance provides the similar characteristic days from the historical data set based on some independent variables generally of climate and time (such as temperature, day of the week, month etc.) and that are used to predict the dependent variable, i.e., day ahead electric load demand. The independent variables considered for the distance measure include the hourly humidity values, hourly temperatures values, and the day type variable.The similarity between the load on the day of prediction and that on similar characteristic days, which is evaluated using fuzzy system

Abstract

IISc Bangalore has developed a recognition engine for Tamil printed text, which has been tested on 1000 document images of pages scanned from books printed between 1950 and 2000. IIIT Hyderabad has developed a XML based annotated database for storing the 5000 images of scanned pages and the corresponding typed text in Unicode. CDAC, Noida has developed an efficient evaluation tool, which compares the OCR output text to the reference typed text (ground truth) and flashes the substitution, deletion and insertion errors in different colours on the screen, so that the design team can quickly identify the issues with the OCR and make corrective steps for improving the performance. IIT Delhi has proposed and developed a novel scheme for segmenting only the text regions from document images containing pictures. The OCRs uses Karhunen-Louve transform (KLT) as features and a support vector machine (SVM) classifier with RBF kernel in a discriminative directed acyclic graph (DDAG) configuration. They assume an uncompressed input image of the document page, scanned at a minimum of 300 dpi with 256 gray levels (not binary or two-level). Tamil OCR currently gives over 94% recognition accuracy at the Unicode level, evaluated on over 1000 printed pages, some of them also containing old Tamil letters.

Abstract

Conventionally optimal control theory has been used in the theoretical design of laser pulses through the direct variation in the electric field of the laser pulse as a function of time. This often leads to designed laser pulses which contain a broad and seemingly arbitrary frequency structure that varies in time in a manner which may be difficult to realize experimentally. In contrast, the experimental design of laser pulses has used a genetic algorithm (GA) approach, varying only those laser parameters actually available to the experimentalist. We investigate in this paper the possibility of using GA optimization methods in the theoretical design of laser pulses to bring about quantum state transitions in molecules. This allows us to select only a small limited number of parameters to vary and to choose these parameters so that they correspond to those available to the experimentalist. In the paper we apply our methods to the vibrational-rotational excitation of the HF molecule. We choose a small limited number of frequencies and vary only the associated electric field amplitudes and pulse envelopes. We show that laser pulses designed in this way can lead to very high transition probabilities.

Abstract

Structural and electronic properties of diastereomers of tetrahydrofuran amino acids (TAA) derived tripeptide, Boc-TAA-Leu-Val-OMe, are studied using density functional theory. Predicted secondary folding patterns with hydrogen bonded pseudocycles of different sizes in peptides containing (2R,5S)-cis-TAA and (2S,5R)-cis-TAA are confirmed by detailed NMR studies of both, and single crystal X-ray analysis of the former. A novel unusual folding pattern emanating from three-centered hydrogen bond is found in peptide with (2R,5S)-cis relationship. Stereochemical control on the orientation of interacting sites is substantiated by structural analysis of the peptides. Using natural bonding orbital and atoms in molecules analyses, charge transfer interactions are analyzed.

Abstract

Optimal control theory is used to design a laser pulse for the multiphoton dissociation of the Fe– CO bond in the CO-heme compounds. The study uses a hexacoordinated iron–porphyrin– imidazole–CO complex in its ground electronic state as a model for CO liganded to the heme group. The potential energy and dipole moment surfaces for the interaction of the CO ligand with the heme group are calculated using density functional theory. Optimal control theory, combined with a timedependent quantum dynamical treatment of the laser-molecule interaction, is then used to design a laser pulse capable of efficiently dissociating the CO-heme complex model. The genetic algorithm method is used within the mathematical framework of optimal control theory to perform the optimization process. This method provides good control over the parameters of the laser pulse, allowing optimized pulses with simple time and frequency structures to be designed. The dependence of photodissociation yield on the choice of initial vibrational state and of initial laser field parameters is also investigated. The current work uses a reduced dimensionality model in which only the Fe–C and C–O stretching coordinates are explicitly taken into account in the timedependent quantum dynamical calculations. The limitations arising from this are discussed in Sec. IV.

Abstract

We present a scalable and incremental approach for creating interactive image-based walkthroughs from a dynamically growing collection of photographs of a scene. Prior approaches, such as [16], perform a global scene reconstruction as they require the knowledge of all the camera poses. These are recovered via batch processing involving pairwise image matching and structure from motion (Sfm), on collections of photographs. Both steps can become computational bottlenecks for large image collections. Instead of computing a global reconstruction and all the camera poses, our system utilizes several partial reconstructions, each of which is computed from only a small subset of overlapping images. These subsets are efficiently determined using a Bag of Words-based matching technique. Our framework easily allows an incoming stream of new photographs to be incrementally inserted into an existing reconstruction. We demonstrate that an imagebased rendering framework based on only partial scene reconstructions can be used to navigate large collections containing thousands of images without sacrificing the navigation experience. As our system is designed for incremental construction from a stream of photographs, it is well suited for processing the ever-growing photo collections.