Optical and Thermal Properties of Diethyl-(2R, 3R) (1)-tartrate Based Chiral Polyurethanes with Main Chain Amido Chromophores

The toluene diisocyanate based optically active chiral polyurethanes were synthesized according to the symmetry conditions. The noncentrosymmetric (both charge asymmetry and spatial asymmetry) environment were attained by the incorporation of the chiral units (diethyl-(2R,3R)(þ)-tartrate) and donor-acceptor building blocks in the main chain which induce a helical conformation in the macromolecular chain. A series of optically active polyurethanes containing chiral linkages in the polymer back bone have been synthesized by using DBTDL catalyst by incorporating the amido diols which were obtained by the aminolysis of e-caprolactone by using the diamines, diaminoethane, diaminobutane, and diaminohexane respectively. The effect of incorporation of the chiral molecule diethyl-(2R,3R)(þ)-tartrate on the properties of polyurethanes was studied by changing the chromophores and also by varying the chiral-chromophore composition. Various properties of polyurethanes were investigated by UV, Fluorescence, TG/DTA, XRD, polarimetric techniques, Kurtz-Perry powder techniques, etc.

Isosorbide based chiral polyurethanes: optical and thermal studies

A new class of chiral polyurethanes containing amido linkages in the polymer backbone have been synthesized by reacting toluene diisocyanate with isosorbide (IS) chiral moiety and the chromophores [N,N0-ethane- 1,2-diyl bis(6-hydroxy hexanamide), N,N0-butane-1,4-diyl bis(6-hydroxy hexanamide) and N,N0-hexane-1,6-diyl bis (6-hydroxy hexanamide)]. The corresponding chromophores were obtained by the aminolysis of e-caprolactone by using the diamines, diaminoethane, diaminobutane and diaminohexane, respectively. All the polymers were synthesized according to the symmetry conditions so as to obtain the non-centrosymmetric environment. A series of polyurethanes were synthesized by varying the chiral– chromophore composition. The polyurethanes developed were characterized by optical and thermal methods.

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

A Framework of Statistical Machine Translator from English to Malayalam

In this paper we describe the methodology and the structural design of a system that translates English into Malayalam using statistical models. A monolingual Malayalam corpus and a bilingual English/Malayalam corpus are the main resource in building this Statistical Machine Translator. Training strategy adopted has been enhanced by PoS tagging which helps to get rid of the insignificant alignments. Moreover, incorporating units like suffix separator and the stop word eliminator has proven to be effective in bringing about better training results. In the decoder, order conversion rules are applied to reduce the structural difference between the language pair. The quality of statistical outcome of the decoder is further improved by applying mending rules. 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

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Extension schemes for the Alignment Model of English-Malayalam Statistical Machine Translator

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating 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. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant 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.

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

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

On the optical and electrical properties of rf and a.c. plasma polymerized aniline thin films

Polyaniline is a widely studied conducting polymer and is a useful material in its bulk and thin film form for many applications, because of its excellent optical and electrical properties. Pristine and iodine doped polyaniline thin films were prepared by a.c. and rf plasma polymerization techniques separately for the comparison of their optical and electrical properties. Doping of iodine was effected in situ. The structural properties of these films were evaluated by FTIR spectroscopy and the optical band gap was estimated from UV-vis-NIR measurements. Comparative studies on the structural, optical and electrical properties of a.c. and rf polymerization are presented here. It has been found that the optical band gap of the polyaniline thin films prepared by rf and a.c. plasma polymerization techniques differ considerably and the band gap is further reduced by in situ doping of iodine. The electrical conductivity measurements on these films show a higher value of electrical conductivity in the case of rf plasma polymerized thin films when compared to the a.c. plasma polymerized films. Also, it is found that the iodine doping enhanced conductivity of the polymer thin films considerably. The results are compared and correlated and have been explained with respect to the different structures adopted under these two preparation techniques

An Optical limiter based on Ferrofluids

We report an optical limiter based on ferrofluids which has a very high shelf life and remarkable thermal stability, which are important requirements for sustainable use with intense lasers. The colloidal suspensions contain nanosized particles of approximately 80 Å diameter, with a number density of the order of 1022 /m3. The nonlinear optical transmission of the samples is studied using nanosecond and femtosecond laser pulses. Excited state absorption phenomena contribute to enhanced limiting in the nanosecond excitation regime. An advantageous feature of ferrofluids in terms of device applications is that their optical properties are controllable by an external magnetic field.

Studies on the optical band gap and cluster size of the polyaniline thin films irradiated with swift heavy Si ions

Polyaniline thin films prepared by RF plasma polymerisation were irradiated with 92MeV Si ions for various fluences of 1 1011, 1 1012 and 1 1013 ions/cm2. FTIR and UV–vis–NIR measurements were carried out on the pristine and Si ion irradiated polyaniline thin films for structural evaluation and optical band gap determination. The effect of swift heavy ions on the structural and optical properties of plasma-polymerised aniline thin film is investigated. Their properties are compared with that of the pristine sample. The FTIR spectrum indicates that the structure of the irradiated sample is altered. The optical studies show that the band gap of irradiated thin film has been considerably modified. This has been attributed to the rearrangement in the ring structure and the formation of CRC terminals. This results in extended conjugated structure causing reduction in optical band gap

The synthesis of high coercivity cobalt-in-carbon nanotube hybrid structures and their optical limiting properties

Magnetic heterostructures with carbon nanotubes having multiple functionalities are fascinating materials which can be manipulated by means of an external magnetic field. In this paper we report our investigations on the synthesis and optical limiting properties of pristine cobalt nanotubes and high coercivity cobalt-in-carbon nanotubes (a new nanosystem where carbon nanotubes are filled with cobalt nanotubes). A general mobility assisted growth mechanism for the formation of one-dimensional nanostructures inside nanopores is verified in the case of carbon nanotubes. The open-aperture z-scan technique is employed for the optical limiting measurements in which nanosecond laser pulses at 532 nm have been used for optical excitation. Compared to the benchmark pristine carbon nanotubes these materials show an enhanced nonlinear optical absorption, and the nonlinear optical parameters calculated from the data show that these materials are efficient optical limiters. To the best of our knowledge this is the first report where the optical limiting properties of metal nanotubes are compared to those of carbon nanotubes

On structural, optical and dielectric properties of zinc aluminate nanoparticles

Zinc aluminate nanoparticles with average particle size of 40 nm were synthesized using a sol–gel combustion method. X-ray diffractometry result was analysed by Rietveld refinement method to establish the phase purity of the material. Different stages of phase formation of the material during the synthesis were investigated using differential scanning calorimetry and differential thermogravimetric analysis. Particle size was determined with transmission electron microscopy and the optical bandgap of the nanoparticles was determined by absorption spectroscopy in the ultraviolet-visible range. Dielectric permittivity and a.c. conductivity of the material were measured for frequencies from 100 kHz to 8 MHz in the temperature range of 30–120◦C. The presence of Maxwell– Wagner type interfacial polarization was found to exist in the material and hopping of electron by means of quantum mechanical tunneling is attributed as the reason for the observed a.c. conductivity

Nonlinear and magneto-optical transmission studies on magnetic nanofluids of non-interacting metallic nickel nanoparticles

Oxide free stable metallic nanofluids have the potential for various applications such as in thermal management and inkjet printing apart from being a candidate system for fundamental studies. A stable suspension of nickel nanoparticles of ∼5 nm size has been realized by a modified two-step synthesis route. Structural characterization by x-ray diffraction and transmission electron microscopy shows that the nanoparticles are metallic and are phase pure. The nanoparticles exhibited superparamagnetic properties. The magneto-optical transmission properties of the nickel nanofluid (Ni-F) were investigated by linear optical dichroism measurements. The magnetic field dependent light transmission studies exhibited a polarization dependent optical absorption, known as optical dichroism, indicating that the nanoparticles suspended in the fluid are non-interacting and superparamagnetic in nature. The nonlinear optical limiting properties of Ni-F under high input optical fluence were then analyzed by an open aperture z-scan technique. The Ni-F exhibits a saturable absorption at moderate laser intensities while effective two-photon absorption is evident at higher intensities. The Ni-F appears to be a unique material for various optical devices such as field modulated gratings and optical switches which can be controlled by an external magnetic field