A Chloride Ion-Selective Potentiometric Sensor Based on a Polymeric Schiff Base Complex

This paper describes the fabrication of an ion-selective electrode in which a polymeric Schiff base complex of cobalt(II) is used as the ionophore.The main advantage of the electrode is that it is mechanically stable upto 3 months..The electrode shows a linear response in the range of 2.5 × 10-5-0.5 × 10-1 mol dm-3. The response time of the electrode is 30 s.The pH range at which the electrode works is 3.8 to 6.8. The electrode was found to be selective towards chloride ion in the presence of ions like Na+, Ca2+, Mn2+, ,Fe3+, Co2+, Ni2+, Cu2+, Zn2+, CH3COO-, NO3-, SO42- ,Br- and NO2-.

A sensitive fibre optic pH sensor using multiple sol–gel coatings

The fabrication and characterization of a fibre optic pH sensor based on evanescent wave absorption is presented. The unclad portion of a multi-mode optical fibre is coated with a pH sensitive dye, which is immobilized by the sol–gel route. The sensitivity of the device has been found to increase when multiple sol–gel coatings are used as the sensing region. The dynamic range and the temporal response of the sensor are investigated for two different dyes, namely bromocresol purple and bromocresol green. The performance of the device is evaluated in terms of the results obtained during actual measurements.

A sensitive fibre optic pH sensor using multiple sol–gel coatings

The fabrication and characterization of a fibre optic pH sensor based on evanescent wave absorption is presented. The unclad portion of a multi-mode optical fibre is coated with a pH sensitive dye, which is immobilized by the sol–gel route. The sensitivity of the device has been found to increase when multiple sol–gel coatings are used as the sensing region. The dynamic range and the temporal response of the sensor are investigated for two different dyes, namely bromocresol purple and bromocresol green. The performance of the device is evaluated in terms of the results obtained during actual measurements

A sensitive fibre optic pH sensor using multiple sol–gel coatings

The fabrication and characterization of a fibre optic pH sensor based on evanescent wave absorption is presented. The unclad portion of a multi-mode optical fibre is coated with a pH sensitive dye, which is immobilized by the sol–gel route. The sensitivity of the device has been found to increase when multiple sol–gel coatings are used as the sensing region. The dynamic range and the temporal response of the sensor are investigated for two different dyes, namely bromocresol purple and bromocresol green. The performance of the device is evaluated in terms of the results obtained during actual measurements

A sensitive fibre optic pH sensor using multiple sol-gel coatings

The fabrication and characterization of a fibre optic pH sensor based on evanescent wave absorption is presented. The unclad portion of a multi-mode optical fibre is coated with a pH sensitive dye, which is immobilized by the sol–gel route. The sensitivity of the device has been found to increase when multiple sol–gel coatings are used as the sensing region. The dynamic range and the temporal response of the sensor are investigated for two different dyes, namely bromocresol purple and bromocresol green. The performance of the device is evaluated in terms of the results obtained during actual measurements.

A fiber optic concentration sensor

A simple fiber optic concentration sensor based on the coupling of light f rom one fiber to another through a solution is discussed. The operational characteristics of the sensor are illustrated by taking the solutions of potassium permanganate and fast green dye as samples.The extrinsic type sensor described here shows linearity at lower concentrations.

Changing Role of Academic Libraries in the E-learning Environment: Issues and Challenges

The development of computer and network technology is changing the education scenario and transforming the teaching and learning process from the traditional physical environment to the digital environment. It is now possible to access vast amount of information online and enable one to one communication without the confines of place or time. While E-learning and teaching is unlikely to replace face-to-face training and education it is becoming an additional delivery method, providing new learning opportunities to many users. It is also causing an impact on library services as the increased use of ICT and web based learning technologies have paved the way for providing new ICT based services and resources to the users. Online learning has a crucial role in user education, information literacy programmes and in training the library professionals. It can help students become active learners, and libraries will have to play a greater role in this process of transformation. The significance of libraries within an institution has improved due to the fact that academic libraries and information services are now responsible for e-learning within their organization.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

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.