How to do a dissertation

The role of the supervisor• agree a timetable of meetings at the start of your project and stick to it;• make sure that each meeting has a focus eg “setting a research problem”,“analysing the data”;• send something that can form the basis of a discussion about your progress to your supervisor before each meeting. This could include your research plan, early results of your data collection or draft chapters;• turn up on time to each meeting you have arranged. Do not assume that your supervisor is available at all times to see you;• at the end of each

Techniques to Improve the word alignments in Statistical Machine Translation from English to Malayalam

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam translation using statistical models like translation model, language model and a decoder. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set up among the sentence pairs of the source and target language before subjecting them for training. This paper is deals with the techniques which can be adopted for improving the alignment model of SMT. Incorporating the parts of speech information into the bilingual corpus has eliminated many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

Unusual surface and edge morphologies, sp2 to sp3 hybridized transformation and electronic damage after Ar+ ion irradiation of few-layer graphene surfaces

Roughness and defects induced on few-layer graphene (FLG) irradiated by Ar+ ions at different energies were investigated using X-ray photoemission spectroscopy (XPS) and atomic force microscopy techniques. The results provide direct experimental evidence of ripple formation, sp2 to sp3 hybridized carbon transformation, electronic damage, Ar+ implantation, unusual defects and edge reconstructions in FLG, which depend on the irradiation energy. In addition, shadowing effects similar to those found in oblique-angle growth of thin films were seen. Reliable quantification of the transition from the sp2-bonding to sp3-hybridized state as a result of Ar+ ion irradiation is achieved from the deconvolution of the XPS C (1s) peak. Although the ion irradiation effect is demonstrated through the shape of the derivative of the Auger transition C KVV spectra, we show that the D parameter values obtained from these spectra which are normally used in the literature fail to account for the sp2 to sp3 hybridization transition. In contrast to what is known, it is revealed that using ion irradiation at large FLG sample tilt angles can lead to edge reconstructions. Furthermore, FLG irradiation by low energy of 0.25 keV can be a plausible way of peeling graphene layers without the need of Joule heating reported previously

Acute salinity stress alters the haemolymph metabolic profile of Penaeus monodon and reduces immunocompetence to white spot syndrome virus infection

Influence of acute salinity stress on the immunological and physiological response of Penaeus monodon to white spot syndrome virus (WSSV) infection was analysed. P. monodon maintained at 15‰ were subjected to acute salinity changes to 0‰ and 35‰ in 7 h and then challenged orally with WSSV. Immune variables viz., total haemocyte count, phenol oxidase activity (PO), nitroblue tetrazolium salt (NBT) reduction, alkaline phosphatase activity (ALP), acid phosphatase activity (ACP) and metabolic variables viz., total protein, total carbohydrates, total free amino acids (TFAA), total lipids, glucose and cholesterol were determined soon after salinity change and on post challenge days 2 (PCD2) and 5 (PCD5). Acute salinity change induced an increase in metabolic variables in shrimps at 35‰ except TFAA. Immune variables reduced significantly (Pb0.05) in shrimps subjected to salinity stress with the exception of ALP and PO at 35‰ and the reduction was found to be more at 0‰. Better performance of metabolic and immune variables in general could be observed in shrimps maintained at 15‰ that showed significantly higher post challenge survival following infection compared to those under salinity stress. Stress was found to be higher in shrimps subjected to salinity change to lower level (0‰) than to higher level (35‰) as being evidenced by the better immune response and survival at 35‰. THC (Pb0.001), ALP (Pb0.01) and PO (Pb0.05) that together explained a greater percentage of variability in survival rate, could be proposed as the most potential health indicators in shrimp haemolymph. It can be concluded from the study that acute salinity stress induces alterations in the haemolymph metabolic and immune variables of P. monodon affecting the immunocompetence and increasing susceptibility to WSSV, particularly at low salinity stress conditions

Macrobenthos And Its Relation To Ecosystem Dynamics In The Cochin Estuary

Cochin estuary is a shallow brackish water body situated on the south west coast of India. It is a tropical positive estuary extending between 90 40’ and 100 12’ N and 760 10’and 760 30’ E with its northern boundary at Azhikode and southern boundary at Thannermukkom bund.The abundance of benthic fauna in an ecosystem shows the close relationship to its environment and reflects the characteristics of an ecological niche. Seasonal and monthly variations in the distribution of macrobenthos in relation to sediment characteristics were conducted in Cochin estuary from 2009-10 periods. Oxidation-reduction potential showed reducing trends that affected the distribution and diversity of fauna. Seasonal variations in water quality and river discharge pattern affected the faunal composition in the different stations. Sewage mixing was the principal source of organic pollution in the Cochin estuary. The sediment pH was generally on the alkaline side ranging from 4.99 at St.9 and 8.33 at St.1.The Eh ranged from -11mV at St.3 to -625mV at St.2.The temperature varied from 260C to 320C in the estuary. The moisture content ranged from 1.63 to 12.155%, that of organic carbon from 0 09 at St. 6 to 4.29% at St.9 and that of organic matter from 0.16 to 7.39%. Seasonally, the average of Eh was highest during the monsoon (156.22 mV) and in the pre monsoon (140.94 mV). The average pH for the 9 study stations was 7.68 during monsoon period and 7.08 during post monsoon. Based on group wise seasonal analysis, the average mean abundance was maximum for polychaetes (43.47) followed by nematodes (33.62), crustaceans (21.62), molluscs (11.94) and Pisces (0.05) in the estuary. Monsoon season was most favourable for benthic faunal abundance followed by the post monsoon period in the study. The series of human interventions like dredging, discharge of industrial effluents, urbanisation and related aspects had a strong influence on the distribution, abundance of benthic macrofauna in the wetland.

Collection and Assets Management: One University Library’s Journey to the Future

Academic libraries worldwide have witnessed a number of trends and paradigm shifts over the last decade. It is vital for university libraries to develop a collection of high standards to satisfy academics and researchers for supporting the vision and mission of a university. The area of collection development and management is the most important part of any library. This paper reports on the problems and prospects of collection and asset management of the University Library of Cochin University of Science and Technology (CUSAT). The insight for the paper comes from the authors’ first-hand experience supported by literature review. Detailed information regarding the purchase of books, serials, policies regarding the acquisition, and changing trends and problems were collected from the official records with the help of a structured data sheet. The study discovers the current trends in collection and asset management in CUSAT and point out the changes likely to be adopted in future.

A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

A Reinforcement Learning Approach to Economic Dispatch using Neural Networks

This paper presents a Reinforcement Learning (RL) approach to economic dispatch (ED) using Radial Basis Function neural network. We formulate the ED as an N stage decision making problem. We propose a novel architecture to store Qvalues and present a learning algorithm to learn the weights of the neural network. Even though many stochastic search techniques like simulated annealing, genetic algorithm and evolutionary programming have been applied to ED, they require searching for the optimal solution for each load demand. Also they find limitation in handling stochastic cost functions. In our approach once we learn the Q-values, we can find the dispatch for any load demand. We have recently proposed a RL approach to ED. In that approach, we could find only the optimum dispatch for a set of specified discrete values of power demand. The performance of the proposed algorithm is validated by taking IEEE 6 bus system, considering transmission losses

Simple approach to determine resonant frequencies of microstrip antennas

A simple approach for accurate determination of the resonant frequencies of microstrip antennas of regular geometries is developed and presented. In this approach, a generalised empirical formula for the computation of effective dielectric permittivity is given which takes into account the ratio of the fringing area to the area of the patch. A correction to the equivalent side length of an equilateral triangular patch, previously published, is modified and a new formula is given. A correction to the effective dimensions of an elliptical microstrip antenna is also carried out. Numerical results obtained for the resonant frequencies of elliptical, circular, rectangular and equilateral-triangular microstrip antennas are in good agreement with the available theoretical and experimental results reported by others. The present approach is more efficient, simpler and more accurate

GA-based Optimization of a Fourth-order Sigma-delta Modulator for WLAN

Over-sampling sigma-delta analogue-to-digital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In the sigma-delta modulator design the scaling coefficients determine the overall signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourthorder multi-bit sigma-delta modulator for Wireless Local Area Networks (WLAN) receiver with feed-forward path and the optimum coefficients are selected using genetic algorithm (GA)- based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The focus of this paper is the identification of the best coefficients suitable for the proposed topology as well as the optimization of a set of system parameters in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.

Matrix based Key Generation to Enhance Key Avalanche in Advanced Encryption Standard

In symmetric block ciphers, substitution and diffusion operations are performed in multiple rounds using sub-keys generated from a key generation procedure called key schedule. The key schedule plays a very important role in deciding the security of block ciphers. In this paper we propose a complex key generation procedure, based on matrix manipulations, which could be introduced in symmetric ciphers. The proposed key generation procedure offers two advantages. First, the procedure is simple to implement and has complexity in determining the sub-keys through crypt analysis. Secondly, the procedure produces a strong avalanche effect making many bits in the output block of a cipher to undergo changes with one bit change in the secret key. As a case study, matrix based key generation procedure has been introduced in Advanced Encryption Standard (AES) by replacing the existing key schedule of AES. The key avalanche and differential key propagation produced in AES have been observed. The paper describes the matrix based key generation procedure and the enhanced key avalanche and differential key propagation produced in AES. It has been shown that, the key avalanche effect and differential key propagation characteristics of AES have improved by replacing the AES key schedule with the Matrix based key generation procedure

Faster techniques to evolve wavelet coefficients for better fingerprint image compression

In this article, techniques have been presented for faster evolution of wavelet lifting coefficients for fingerprint image compression (FIC). In addition to increasing the computational speed by 81.35%, the coefficients performed much better than the reported coefficients in literature. Generally, full-size images are used for evolving wavelet coefficients, which is time consuming. To overcome this, in this work, wavelets were evolved with resized, cropped, resized-average and cropped-average images. On comparing the peak- signal-to-noise-ratios (PSNR) offered by the evolved wavelets, it was found that the cropped images excelled the resized images and is in par with the results reported till date. Wavelet lifting coefficients evolved from an average of four 256 256 centre-cropped images took less than 1/5th the evolution time reported in literature. It produced an improvement of 1.009 dB in average PSNR. Improvement in average PSNR was observed for other compression ratios (CR) and degraded images as well. The proposed technique gave better PSNR for various bit rates, with set partitioning in hierarchical trees (SPIHT) coder. These coefficients performed well with other fingerprint databases as well.

Developing a Child Friendly Text-to-Speech System

This paper discusses the implementation details of a child friendly, good quality, English text-to-speech (TTS) system that is phoneme-based, concatenative, easy to set up and use with little memory. Direct waveform concatenation and linear prediction coding (LPC) are used. Most existing TTS systems are unit-selection based, which use standard speech databases available in neutral adult voices.Here reduced memory is achieved by the concatenation of phonemes and by replacing phonetic wave files with their LPC coefficients. Linguistic analysis was used to reduce the algorithmic complexity instead of signal processing techniques. Sufficient degree of customization and generalization catering to the needs of the child user had been included through the provision for vocabulary and voice selection to suit the requisites of the child. Prosody had also been incorporated. This inexpensive TTS systemwas implemented inMATLAB, with the synthesis presented by means of a graphical user interface (GUI), thus making it child friendly. This can be used not only as an interesting language learning aid for the normal child but it also serves as a speech aid to the vocally disabled child. The quality of the synthesized speech was evaluated using the mean opinion score (MOS).

A socio friendly approach to the analysis of emotive speech

This paper describes certain findings of intonation and intensity study of emotive speech with the minimal use of signal processing algorithms. This study was based on six basic emotions and the neutral, elicited from 1660 English utterances obtained from the speech recordings of six Indian women. The correctness of the emotional content was verified through perceptual listening tests. Marked similarity was noted among pitch contours of like-worded, positive valence emotions, though no such similarity was observed among the four negative valence emotional expressions. The intensity patterns were also studied. The results of the study were validated using arbitrary television recordings for four emotions. The findings are useful to technical researchers, social psychologists and to the common man interested in the dynamics of vocal expression of emotions