Tuning mesoporous molecular sieve SBA-15 for the immobilization of α-amylase

The present work describes the immobilization of α-amylase over well ordered mesoporous molecular sieve SBA-15 with different pore diameters synthesized by post synthesis treatment (PST) hydrothermally after reaction at 40°C. The materials were characterized by N 2 adsorption–desorption studies, small angle X-ray diffraction, scanning electron microscopy and high resolution transmission electron microscopy. Since α-amylase obtained from Bacillus subtilis has dimensions of 35 × 40 × 70 Å it is expected that the protein have access to the pore of SBA-15 (PST-120°C) with diameter 74 Å. The pore dimension is appropriate to prevent considerable leaching. The rate of adsorption of the enzyme on silica of various pore sizes revealed the influence of morphology, pore diameter, pore volume and pH.

High resolution optogalvanic spectrum of N2-rotational structure of (11, 7) band in the first positive system

High resolution optogalvanic spectrum of the (11, 7) band in the first positive system of nitrogen molecule has been recorded from 17179 to 17376 cm- 1. Assignment of 432 rotational lines belonging to the 27 branches of this band has been carried out.

High resolution optogalvanic study in nitrogen discharge

Doppler limited high resolution spectrum in the wavelength region 17224 to 17236 cm−1 of the first positive system (B 3Π g −A 3Σ u + ) of the N2 molecule is recorded by optogalvanic spectroscopic technique using a single mode ring dye laser. It is observed that the intensity and line width of the rotational line increase with the discharge current. Dependence of the collision broadening coefficient on the current was also evaluated.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

A Novel Cache Resolution Technique For Cooperative Caching In Wireless Mobile Networks

Cooperative caching is used in mobile ad hoc networks to reduce the latency perceived by the mobile clients while retrieving data and to reduce the traffic load in the network. Caching also increases the availability of data due to server disconnections. The implementation of a cooperative caching technique essentially involves four major design considerations (i) cache placement and resolution, which decides where to place and how to locate the cached data (ii) Cache admission control which decides the data to be cached (iii) Cache replacement which makes the replacement decision when the cache is full and (iv) consistency maintenance, i.e. maintaining consistency between the data in server and cache. In this paper we propose an effective cache resolution technique, which reduces the number of messages flooded in to the network to find the requested data. The experimental results gives a promising result based on the metrics of studies.

PEER TO PEER CACHE RESOLUTION MECHANISM FOR MOBILE AD HOC NETWORKS

In this paper we investigate the problem of cache resolution in a mobile peer to peer ad hoc network. In our vision cache resolution should satisfy the following requirements: (i) it should result in low message overhead and (ii) the information should be retrieved with minimum delay. In this paper, we show that these goals can be achieved by splitting the one hop neighbours in to two sets based on the transmission range. The proposed approach reduces the number of messages flooded in to the network to find the requested data. This scheme is fully distributed and comes at very low cost in terms of cache overhead. The experimental results gives a promising result based on the metrics of studies.

A novel Sigma–Delta based parallel analogue-to-residue converter

Animportant step in the residue number system(RNS) based signal processing is the conversion of signal into residue domain. Many implementations of this conversion have been proposed for various goals, and one of the implementations is by a direct conversion from an analogue input. A novel approach for analogue-to-residue conversion is proposed in this research using the most popular Sigma–Delta analogue-to-digital converter (SD-ADC). In this approach, the front end is the same as in traditional SD-ADC that uses Sigma–Delta (SD) modulator with appropriate dynamic range, but the filtering is doneby a filter implemented usingRNSarithmetic. Hence, the natural output of the filter is an RNS representation of the input signal. The resolution, conversion speed, hardware complexity and cost of implementation of the proposed SD based analogue-to-residue converter are compared with the existing analogue-to-residue converters based on Nyquist rate ADCs

The diagnosis of severe thunderstorms with high-resolution WRF model

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’westers’(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region

An Improved Color Video Super-Resolution Using Kernel Regression and Fuzzy Enhancement

An improved color video super-resolution technique using kernel regression and fuzzy enhancement is presented in this paper. A high resolution frame is computed from a set of low resolution video frames by kernel regression using an adaptive Gaussian kernel. A fuzzy smoothing filter is proposed to enhance the regression output. The proposed technique is a low cost software solution to resolution enhancement of color video in multimedia applications. The performance of the proposed technique is evaluated using several color videos and it is found to be better than other techniques in producing high quality high resolution color videos

Single Frame Image Super Resolution Using Learned Directionlets

In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. This method uses directionlets to effectively capture directional features and to extract edge information along different directions of a set of available high resolution images .This information is used as the training set for super resolving a low resolution input image and the Directionlet coefficients at finer scales of its high-resolution image are learned locally from this training set and the inverse Directionlet transform recovers the super-resolved high resolution image. The simulation results showed that the proposed approach outperforms standard interpolation techniques like Cubic spline interpolation as well as standard Wavelet-based learning, both visually and in terms of the mean squared error (mse) values. This method gives good result with aliased images also.

Emotional Intelligence As A Determinant Of Conflict Style Adoption Of Managers: A Theoretical Perspective

Successful management is dependent heavily on the manager’s ability to handle conflict effectively. The workforce has been increasingly becoming diversified vis-à-vis the gender, culture and ethnicity. The present work environment has in itself contributed to sowing seeds of conflict with greater diversity, hostility, complexity and newer business competencies in the work context.The classic study of Mintzberg’s Managerial roles approach (1973) also says that a manager has to spend sufficient time and energy in solving conflict as he has to take roles as a negotiator, and dispute handler. An understanding of the conflict and role that it plays in influencing employee behavior constructively or destructively is immense. Therefore conflict when left unmanaged can lead to diminished cohesiveness amongst employees, productivity and reduced organizational fitness. To manage conflict effective conflict resolution strategies that have constructive outcomes is called for. Conflict resolution style theorists opine that collaborative or integrative style, where there is high concern for task and people is considered to give positive individual and organizational outcomes, while the withdrawing /avoidance style and forcing / dominating style are considered to be ineffective in managing conflict. Though managers have typical preferences in the styles followed it need not necessarily be the typical response as it depends on the context, power relationships, emotions etc. The adoption of conflict styles of managers however is dependent on variables like gender orientation, cultural values, personality orientation, underlying relationships – public/private. The paper attempts to draw the importance of managing conflicts at workplace positively and the need for effective conflict resolution strategies. The conflict style adopted and the variables that affect the adoption of each style are discussed and possible interventions at the workplace are suggested

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images