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Growth and characterization of glycine potassium nitrate NLO crystals
Single crystals of glycine potassium nitrate were grown using slow evaporation technique. The solutions were prepared mixing glycine with potassium nitrate in different ratios stirring continuously for an hour to get a saturated solution. It was then kept at room temperature for controlled evaporation. Optically clear and well shaped crystals were obtained and these were characterized by (FTIR) studies, EDAX and X-ray powder diffraction. 2011 American Institute of Physics. -
Structural characterization of paraffin wax soot and carbon black by XRD
From past few decades, an exponential increase in the research related to carbon nanomaterials and their excellent applications has been witnessed. Realizing the need for new potential precursors and cost effective production methods, we have investigated two precursors-paraffin wax soot (CS) and carbon black (CB). Structural and morphological features of the samples are analyzed by various techniques such as X-ray diffraction, high resolution scanning electron microscopy and electron dispersive spectroscopy. The lateral size of the aromatic lamellae, stacking height, the average spacing of the (002) crystallographic planes (d002) and aromaticity are found to be 15.12 44.30 3.57 0.912 and 15.26 43.23 3.68 0.986 respectively for paraffin wax soot and carbon black. Very low ? and ? band intensity ratio shows a low amount of disorder in the samples. SEM micrographs of the samples reveal non-uniform carbon nanospheres of particle sizes 26-94 nm. Asian Journal of Chemistry 2013. -
Revisiting psychotherapeutic practices in Karnataka, India: Lessons from indigenous healing methods
Psychotherapeutic practices in India observes a paradigm shift with the current focus on the indigenous movement which has hit the discipline of Psychology like any other stream in Social Sciences and Humanities. The professional challenges and issues faced by the mental health professionals in this country has always revolved around on the 'uncanny' realm of myths, beliefs and religions as far as mental illness is concerned (Prasadarao & Sudhir, 2001). Efforts have been initiated in exploring the cultural and social roots of the health-illness constructs as well as debating on the possibility of 'integration' of these different philosophies. This paper is designed to understand the various therapeutic forms and processes in indigenous healing practices and to analyse the negotiation between indigenous healing practices and psychotherapy with special reference to Karnataka, one of the States situated in the Southern part of India. The study approaches the cultural landscape of Karnataka state based on a qualitative research design wherein in-depth unstructured interview of healers and mental health practitioners and systematic observation of some indigenous healing forms are adopted as methods of data collection. The paper concludes by looking at the challenges of constructing ethnospecific interventions in psychotherapy and the need to develop more cultural-specific theories taking into account the cultural history of the community. -
Evolutionary algorithm based feature extraction for enhanced recommendations
A major challenge to Collaborative Filtering systems is high dimensional and sparse data which they have to deal with. Feature selection techniques partly address this problem by reducing the feature space and retaining only a representative subset of features. However these techniques do not address the sparsity problem which affects both quality and quantity of recommendations. A more promising direction would be to construct/extract new features which are low dimensional, dense and have more discriminative power. Content based construction of features has been explored in the past. This work proposes a evolutionary algorithm based feature extraction techniques which discover hidden features with high discriminative capacity. Such an approach offers the advantage of discovering features even in the absence of additional information such as item contents etc. The proposed approach is contrasted with content based feature extraction techniques through experiments and the ability of the new approach in discovering interesting and useful features is established. -
An autonomic computing architecture for business applications
Though the vision of autonomic computing (AC) is highly ambitious, an objective analysis of autonomic computing and its growth in the last decade throw more incisive and decisive insights on its birth deformities and growth pains. Predominantly software-based solutions are being preferred to make IT infrastructures and platforms, adaptive and autonomic in their offerings, outputs, and outlooks. However the autonomic journey has not been as promising as originally envisaged by industry leaders and luminaries, and there are several reasons being quoted by professionals and pundits for that gap. Precisely speaking, there is a kind of slackness in articulating its unique characteristics, and the enormous potentials in business and IT acceleration. There are not many real-world applications to popularize the autonomic concept among the development community. Though, some inroads has been made into infrastructure areas like networking, load balancing etc., very few attempts has been exercised in application areas like ERP, SCM, or CRM. In this paper, we would like to dig and dive deeper to extract and explain where the pioneering and path-breaking autonomic computing stands today, and the varied opportunities and possibilities, which insists hot pursuit of the autonomic idea. A simplistic architecture for deployment of autonomic business applications is introduced and a sample implementation in an existing CRM system is described. This should form the basis of new start and ubiquitous application of AC concepts for business applications. 2012 IEEE. -
Mesoporous iron aluminophosphate: An efficient catalyst for one pot synthesis of amides by ester-amide exchange reaction
A series of metal aluminophosphates (MAlP: M = V, Fe, Co, Ni & Cu) were prepared by co-precipitation method. All the materials were characterized by various physico-chemical techniques. The materials were found to be mesoporous and moderately acidic. The catalytic activity of the materials was investigated in the synthesis of benzamides in a single pot reaction under solvent free refluxing conditions from methyl benzoate and different amines. Iron aluminophosphate was found to be the most effective catalyst for the synthesis of benzamides with 100% selectivity. The isolated yield of benzamide varied from 46% to 100% depending on the nature of amine. A possible reaction mechanism has been proposed which correlates the surface acidity and catalytic activity of the catalyst. The catalyst could be recycled for about three times without any appreciable loss in activity, thus making the method ecofriendly and economical. -
Growth and characterization of chalcogenide crystals by vapour method
A horizontal linear gradient two zone furnace was designed and employed to grow single crystals of indium telluride by Physical Vapour Deposition (PVD) method. It was calibrated for various trials including, series and parallel combinations of coils, and set temperatures. Systematic growth runs for chalcogenide crystals were performed by varying the source and growth temperatures. Crystals of different sizes and morphologies were obtained. The morphology and chemical analysis of the grown crystals were investigated by Scanning Electron Microscope (SEM) and Energy Dispersive Analysis using X-rays (EDAX). The hardness of the crystals was estimated using a Vickers microhardness tester. 2011 American Institute of Physics. -
Usage of online educational courses by undergraduate engineering students in Karnataka
Increasing availability of low-cost technology has enabled many students to use online courses to supplement their studies. The emergence of MOOCs (Massively Open Online Courses) has also brought about a great revolution in the teaching and learning methods. In case of Indian students, since most of the online courses available are not customized according to the syllabus, the students do not find them completely useful. In this case, Massively Empowered Classrooms (MEC) provides curriculum based video lectures and quizzes to students free of cost. The students are able to gain a good understanding of the subject and also score well in exams. This paper is based on an exploratory study conducted to analyze the usage of online courses and MEC by the undergraduate engineering students in Karnataka, India. The paper also describes some expectations from students and teachers to improve the reach and impact of online education. 2013 IEEE. -
Occupancy improvement in serviced apartments: Customer profiling
Sustaining and improving higher occupancy and generating steady revenue by bringing the experience of 'Home away from Home'for the Customers is the business model of ServicedApartments Industry. Serviced Apartment Industry has to be highly competitive. Its performance is governed by many factors such as competition, technology, social factors and lastly Customers themselves. This study focuses only on Customer profile. To achieve results, the Serviced Apartment Owners/Managers will need to study Customers' profile and their needs. Customer satisfaction and retention lead to better customer loyalty, occupancy rates, and revenue. In this paper a methodological framework to analyze and profile Serviced Apartment Customers is discussed, focusing on the factors and particularly the Customer information which could help in increasing the Occupancy. There is a trend that would normally go unnoticed if analysis of data is taken at the aggregate level but looking at them individually, it provides interesting information. 2012 Taylor & Francis Group. -
Prominent label identification and multi-label classification for cancer prognosis prediction
Cancer prognosis prediction improves the quality of treatment and increases the survivability of the patients. Conventional methods of cancer prediction deal with single class by limiting the prognosis prediction to one response variable. The SEER Public Use cancer database has more prominent variables that support better prediction approach. The objective of this paper is to find the prominent labels from cancer databases and use them in a multi-class environment. The implementation consist of three phases namely, pre-processing, prominent label identification and multi-label classification. Breast, Colorectal and Respiratory Cancer Data sets have been used for the experimentation. Also random samples from all three data sets are generated to form a mixed cancer data. Patient survival, number of primaries and age at diagnosis are the prominent labels identified from others using the Decision tree, Nae Bayes and KNN algorithms. The three prominent labels have been tested using multi-label RAkEL algorithm to find the relations between them. The results of the empirical study are comparatively better than the traditional way of cancer prediction. 2012 IEEE. -
X -ray diffraction and microhardness studies of tin monoselenide
Tin Monoselenide (SnSe) crystals have been grown by the Physical Vapour Deposition (PVD) method. X-ray diffraction studies were carried out on the as grown crystals and the lattice parameters were found to be a=11.506 b=4.149and c=4.447 The values were found to be comparable with that reported in the PDF card for SnSe. The microhardness of the crystals has been determined by using Vickers microhardness indenter. 2011 American Institute of Physics. -
Secure multi-party computation protocol using asymmetric encryption
Privacy preservation is very essential in various real life applications such as medical science and financial analysis. This paper focuses on implementation of an asymmetric secure multi-party computation protocol using anonymization and public-key encryption where all parties have access to trusted third party (TTP) who (1) doesn't add any contribution to computation (2) doesn't know who is the owner of the input received (3) has large number of resources (4) decryption key is known to trusted third party (TTP) to get the actual input for computation of final result. In this environment, concern is to design a protocol which deploys TTP for computation. It is proposed that the protocol is very proficient (in terms of secure computation and individual privacy) for the parties than the other available protocols. The solution incorporates protocol using asymmetric encryption scheme where any party can encrypt a message with the public key but decryption can be done by only the possessor of the decryption key (private key). As the protocol works on asymmetric encryption and packetization it ensures following: (1) Confidentiality (Anonymity) (2) Security (3) Privacy (Data). 2014 IEEE. -
Computationally efficient wavelet domain solver for florescence diffuse optical tomography
Estrogen induced proliferation of mutant cells is a growth signal hallmark of breast cancer. Fluorescent molecule that can tag Estrogen Receptor (ER) can be effectively used for detecting cancerous tissue at an early stage. A novel targetspecific NIRf dye conjugate aimed at measuring ER status was synthesized by ester formation between 17-? estradiol and a hydrophilic derivative of ICG, cyanine dye, bis-1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. In-vitro studies provided specific binding on ER+ve [MCF-7] cells clearly indicating nuclear localization of the dye for ER+ve as compared to plasma level staining for MDAMB-231. Furthermore, cancer prone cells showed 4.5-fold increase in fluorescence signal intensity compared to control.; A model of breast phantom was simulated to study the in-vivo efficiency of dye with the parameters of dye obtained from photo-physical and in-vitro studies. The excitation (754 nm) and emission (787 nm) equation are solved independently using parallel processing strategies. The results were obtained by carrying out wavelet transformation on forward and the inverse data sets. An improvisation of the Information content of system matrix was suggested in wavelet domain. The inverse problem was addressed using LevenbergMarquardt (LM) procedure with the minimization of objective function using Tikhonov approach. The multi resolution property of wavelet transform was explored in reducing error and increasing computational efficiency. Our results were compared with the single resolution approach on various parameters like computational time, error function, and Normalized Root Mean Square (NRMS) error. A model with background absorption coefficient of 0.01 mm-1 with anomalies of 0.02 mm-1 with constant reduced scattering of 2.0 mm for different concentration of dye was compared in the result. The reconstructed optical properties were in concurrence with the tissue property at 787 nm. We intend our future plans on in-vivo study on developing a complete instrumentation for imaging a target specific lipophilic dye. Springer International Publishing Switzerland 2014. -
Verification and validation of MapReduce program model for parallel K-means algorithm on Hadoop cluster
With the development of information technology, a large volume of data is growing and getting stored electronically. Thus, the data volumes processing by many applications will routinely cross the petabyte threshold range, in that case it would increase the computational requirements. Efficient processing algorithms and implementation techniques are the key in meeting the scalability and performance requirements in such scientific data analyses. So for the same here, we have p analyzed the various MapReduce Programs and a parallel clustering algorithm (PKMeans) on Hadoop cluster, using the Concept of MapReduce. Here, in this experiment we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Means Clustering Algorithm. We have found that as the number of nodes increases the execution time decreases, but also some of the interesting cases has been found during the experiment and recorded the various performance change and drawn different performance graphs. This experiment is basically a research study of above MapReduce applications and also to verify and validate the MapReduce Program model for Parallel K-Means algorithm on Hadoop Cluster having four nodes. 2013 IEEE. -
A distributed randomization framework for privacy preservation in big data
The privacy preservation is a big challenge for data generated from various sources such as social networking sites, online transaction, weather forecast to name a few. Due to the socialization of the internet and cloud computing pica bytes of unstructured data is generated online with intrinsic values. The inflow of big data and the requirement to move this information throughout an organization has become a new target for hackers. This data is subject to privacy laws and should be protected. The proposed protocol is one step toward the security in case of above circumstances where data is coming from multiple participants and all are concerned about individual privacy and confidentiality. 2014 IEEE. -
Message efficient ring leader election in distributed systems
Leader Election Algorithm, not only in distributed systems but in any communication network, is an essential matter for discussion. Tremendous amount of work are happening in the research community on election as network protocols are in need of co-ordinator process for the smooth running of the system. These so called Coordinator processes are responsible for the synchronization of the system otherwise, the system loses its reliability. Furthermore, if the leader process crashes, the new leader process should take the charge as early as possible. New leader is one among the currently running processes with the highest process id. In this paper we have presented a modified version of ring algorithm. Our work involves substantial modifications of the existing ring election algorithm and the comparison of message complexity with the original algorithm. Simulation results show that our algorithm minimizes the number of messages even in worst case scenario. 2013 Springer Science+Business Media. -
Mapping extinction using GALEX and SDSS photometric observations
The primary objective of this work is to create an all sky extinction map of the Milky Way galaxy. We have cross-matched the Sloan Digital Sky Survey (SDSS data release 8) photometric observations with that of Galaxy Evolution Explorer (GALEX data release 6). This provides a wide range of wavelength coverage from Far Ultra-Violet through the optical spectrum and gives one unique SDSS source for every GALEX source. We discuss a sample of ?32000 objects in the north galactic pole (?75 latitude) from this combined database. The Castelli and Kurucz Atlas was fit to the photometric observations of each star, best fit being determined using a chi-square test. Best fit parameters provide the spectral type and extinction towards each of the objects. The shift in magnitude obtained during the best-fit can be used to determine the distance to each of the stars. With this data, a comprehensive extinction map can be made for the high-latitude objects and later extended to all-sky. 2013 AIP Publishing LLC. -
Verification and validation of Parallel Support Vector Machine algorithm based on MapReduce Program model on Hadoop cluster
From the recent years the large volume of data is growing bigger and bigger. It is difficult to measure the total volume of structured and unstructured data that require machine-based systems and technologies in order to be fully analyzed. Efficient implementation techniques are the key to meeting the scalability and performance requirements entailed in such scientific data analysis. So for the same in this paper the Sequential Support Vector Machine in WEKA and various MapReduce Programs including Parallel Support Vector Machine on Hadoop cluster is analyzed and thus, in this way Algorithms are Verified and Validated on Hadoop Cluster using the Concept of MapReduce. In this paper, the performance of above applications has been shown with respect to execution time/training time and number of nodes. Experimental Results shows that as the number of nodes increases the execution time decreases. This experiment is basically a research study of above MapReduce applications. 2013 IEEE. -
User profiling based on keyword clusters for improved recommendations
Recommender Systems (RS) have risen in popularity over the years, and their ability to ease decision-making for the user in various domains has made them ubiquitous. However, the sparsity of data continues to be one of the biggest shortcomings of the suggestions offered. Recommendation algorithms typically model user preferences in the form of a profile, which is then used to match user preferences to items of their interest. Consequently, the quality of recommendations is directly related to the level of detail contained in these profiles. Several attempts at enriching the user profiles leveraging both user preference data and item content details have been explored in the past. We propose a method of constructing a user profile, specifically for the movie domain, based on user preference for keyword clusters, which indirectly captures preferences for various narrative styles. These profiles are then utilized to perform both content-based (CB) filtering as well as collaborative filtering (CF). The proposed approach scores over the direct keyword-matching, genre-based user profiling and the traditional CF methods under sparse data scenarios as established by various experiments. It has the advantage of a compact user model representation, while at the same time capturing the essence of the styles or genres preferred by the user. The identification of implicit genres is captured effectively through clustering without requiring labeled data for training. 2014 Springer International Publishing Switzerland. -
An ettective dynamic scheduler tor reconfigurable high speed computing system
High Speed Computing is a promising technology that meets ever increasing real-time computational demands through leveraging of flexibility and parallelism. This paper introduces a reconfigurable fabric named Reconfigurable High Speed Computing System (RHSCS) and offers high degree of flexibility and parallelism. RHSCS contains Field Programmable Gate Array (FPGA) as a Processing Element (PE). Thus, RHSCS made to share the FPGA resources among the tasks within single application. In this paper an efficient dynamic scheduler is proposed to get full advantage of hardware utilization and also to speed up the application execution. The addressed scheduler distributes the tasks of an application to the resources of RHSCS platform based on the cost function called Minimum Laxity First (MLF). Finally, comparative study has been made for designed scheduling technique with the existing techniques. The proposed platform RHSCS and scheduler with Minimum Laxity First (MLF) as cost function, enhances the speed of an application up to 80.30%. 2014 IEEE.