http://repository.ias.ac.in/39608/1/49_pub.pdf

A review of imperative technologies for wastewater treatment I: oxidation technologies at ambient conditions

A review of imperative technologies for wastewater treatment II: hybrid methods

The [2 + 2] photocycloaddition is undisputedly the most important and most frequently used photochemical reaction. In this review, it is attempted to cover all recent aspects of [2 + 2] photocycloaddition chemistry with an emphasis on synthetically relevant, regio-, and stereoselective reactions. The review aims to comprehensively discuss relevant work, which was done in the field in the last 20 years (i.e., from 1995 to 2015). Organization of the data follows a subdivision according to mechanism and substrate classes. Cu(I) and PET (photoinduced electron transfer) catalysis are treated separately in sections 2 and 4, whereas the vast majority of photocycloaddition reactions which occur by direct excitation or sensitization are divided within section 3 into individual subsections according to the photochemically excited olefin.

http://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.5b00723

Recent Advances in the Synthesis of Cyclobutanes by Olefin [2+2] Photocycloaddition Reactions

A review of applications of cavitation in biochemical engineering/biotechnology

CLINICAL NEUROSURGERY Edited by Barnes Wordall. Vol. 18. (Pp. 557; illustrated; £8 25.) Churchill Livingstone: Edinburgh. 1971. CLINICAL NEUROSURGERY Edited by G. T. Tindall. Vol. 19. (Pp. 598; illustrated; £12.) Churchill Livingstone: Edinburgh. 1972. The Congress of Neurosurgeons began in 1951 on the initiative of a group of younger neurosurgeons. In the last 20 years its membership has grown from 69 to over 1,000, but it has retained its original intentions and virility by a constitution which ensured that the office bearers and organizers were always young men. Residents in training are encouraged to join, financial concessions make it possible for them to attend meetings, and these are organized as an educational exercise, by inviting established authorities to give lectures on selected topics, chosen to provide a balanced programme. As a result Clinical Neurosurgery is a valuable volume which all neurosurgeons look forward to each year; it is in quite a different class from the usual conference tome, full of brief and unconnected papers of widely varying quality. As the title suggests Clinical Neurosurgery includes excellent clinical reviews but the two recent volumes include also a section of seminars on fundamental research-in volume 18 on coma and sleep, in volume 19 on basic mechanisms of memory. It is also the custom to invite a senior neurosurgical citizen as guest of honour and his two or three papers afford an opportunity for historical and philosophical reflections as well as an experienced perspective on clinical and experimental work. Add to this the refreshing presidential address, from one of the (angry?) young men of neurosurgery and it will be clear that these volumes really do include something of interest for every neurosurgeon, whatever his own interests or prejudices. It is a relief to be able so warmly to recommend these books, when the question posed by so many other books is whether anyone would really want to read them. The most recent volume has a more consistent theme than former ones, and that is 'head injury'. It includes papers on mechanisms as revealed by animal experiment and by a pathologist who visited the scene of the accident before examining the brains of head injury fatalities. There are chapters on engineering and socio-psychological aspects of accident prevention, as well as down to earth clinical accounts of metabolic disorders, testing for acoustic vestibular 36 damage, and aspects of prognosis. This is a significant contribution to the literature on head injury.

https://jnnp.bmj.com/content/jnnp/37/3/361.3.full.pdf

The working brain (an introduction to neuropsychology)

Outliers in real time speaker recognition can be viewed as a disturbing element and one of the reason of the degradation of the recognition accuracy. In speaker space, outliers may consider as non-intrinsic speaker's information in clean environment or noise information in noisy environment. So detection of outliers purify the speaker space with most speaker specific feature vectors in both clean and noisy environment. There are several methodology to detect outliers but in this paper we use a distance based method to mitigate the effects of outliers and incorporate fusion techniques to improve the recognition accuracy of speaker recognition system. Distances are taken from Minkowski family up to third order and also Mahalanobis distance which is a probabilistic distance. In fusion methodology we use GMM as a single classifier with complementary feature sets, MFCC and IMFCC. In this paper, we fuse the score of MFCC and IMFCC with a equal weight method. This method not only improves the recognition accuracy but simultaneously improve the detection rate of outliers with respect to the base line feature set.

Outlier removal and fusion techniques for robust speaker recognition applications

This paper introduces scattering transform for speech emotion recognition (SER). Scattering transform generates feature representations which remain stable to deformations and shifting in time and frequency without much loss of information. In speech, the emotion cues are spread across time and localised in frequency. The time and frequency invariance characteristic of scattering coefficients provides a representation robust against emotion irrelevant variations e.g., different speakers, language, gender etc. while preserving the variations caused by emotion cues. Hence, such a representation captures the emotion information more efficiently from speech. We perform experiments to compare scattering coefficients with standard mel-frequency cepstral coefficients (MFCCs) over different databases. It is observed that frequency scattering performs better than time-domain scattering and MFCCs. We also investigate layer-wise scattering coefficients to analyse the importance of time shift and deformation stable scalogram and modulation spectrum coefficients for SER. We observe that layer-wise coefficients taken independently also perform better than MFCCs.

Deep scattering network for speech emotion recognition.

The Bayesian belief network is a powerful knowledge representation and reasoning tool under conditions of uncertainty to analyze gene expression patterns. Nowadays, this is an important tool to construct mathematical models based on probability to identify any particular dominant Genetic Network of any organism under observation. The present study deals with analysis of a set of micro array data collected at a regular interval of time throughout the growth phase of a fungus Burkholderia pseudomalli. In the first phase of the study, emphasis was given to recover a set of most dominant genes among the set of all possible expressed genes found in the microarray experiment. These dominant genes are then used to find out a dominant Genetic Network by applying the Bayesian Algorithm. Thus, the most dominant genetic network for the growth and development of the fungus under consideration was obtained. The genetic network represents the set of responsible genes in the growth process and their inter relationships. The Microarray data set represents the external manifestation of internal genetic activity resulting into genetic network. Here, from the set of 5289 genes in 47 consecutive time instances, were taken for analysis. Out of them, 400 most pertinent genes for the growth process were determined using a new technique namely ‘Fidelity Matrix Process’. Genetic Network for these 400 genes has been constructed and studied using Bayesian Belief Network Technique. The present reduction method was found to be more efficient in terms of computation when compared contemporary studies done many scientists. The results of the present study may be extensively applied in reducing a huge number of genetic expression rate data without any complex computation, studying unknown biological processes and systems, treating complicated diseases and even designing drugs for some incorrigible syndromes.

Determination and study of a dominant Genetic Network responsible for the growth of a fungus using the concepts of Bayesian Algorithm

Hydrologists use various machine learning approaches for segmenting water bodies for carrying out various panning activities. Conventional approaches are mainly clustering or classification based a...

River body extraction using convolutional neural network

The records of surgical history are seen in approximately 89.74% closer to records of health records of patients with Parkinson's disease. However, compared to the control group, this ratio does not show very significant differences. However, one of the straightforward ideas we can get from this ratio is that for every 100 PD patients, 89 PD patients are undergoing at least one surgery in their lifetime. Therefore, it is essential to find the relationship between surgical history and the occurrence of PD. In this study, 12 surgical history-related questions were asked, classified into a PD group and a control group, and tested for gender (Male and Female). Significant participation in the surgical history of PD is seen, and in most cases, cranial or brain surgery has an 81% to 85% chance of developing PD.

Goutam Saha

Papers

Outlier removal and fusion techniques for robust speaker recognition applications

Deep scattering network for speech emotion recognition.

Determination and study of a dominant Genetic Network responsible for the growth of a fungus using the concepts of Bayesian Algorithm

River body extraction using convolutional neural network

Impact of Surgical History on Parkinson's Disease Progression