Showing papers by "National Institute of Technology, Karnataka published in 2016"

Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin

Abstract: Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation (RUSLE) integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km 2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm·ha − 1 hr − 1 /year, 0.10 to 0.44 t ha − 1 ·MJ − 1 ·mm − 1 , 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002–2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin.

Fabrication of polydopamine functionalized halloysite nanotube/polyetherimide membranes for heavy metal removal

Abstract: Polydopamine modified halloysite nanotubes (HNTs) were synthesised through a one step facile procedure and employed as a well dispersed hydrophilic additive to enhance the filtration properties of polyetherimide (PEI) membranes. The nanocomposite membranes were prepared by an immersion precipitation method with different amounts of modified HNTs (MHNTs) in the casting solution. The good dispersion of MHNTs throughout the membrane matrix was confirmed by elemental mapping analysis. The prepared nanocomposite membranes were extensively studied in terms of their porosity, morphology, membrane hydraulic resistance and hydrophilicity. The permeation experiments showed that the modified membranes exhibited higher water flux than a pristine PEI membrane. The antifouling and anti-biofouling behaviour of the modified membranes was investigated in detail. The results revealed that a membrane with a 3 wt% MHNT dosage showed a higher Fouling Resistance Ratio (FRR) of 74.5% with reversible membrane fouling of 64.3%. Moreover, the membrane showed excellent resistance to microbial growth on the membrane surface. The well performing membrane was subjected to heavy metal ion rejection. Results indicated that membranes had the capacity to adsorb Pb2+ and Cd2+. Overall, PEI–MHNTs nanocomposite membranes could have great potential to improve antifouling, anti-biofouling and filtration properties.

An efficient cuckoo search algorithm based multilevel thresholding for segmentation of satellite images using different objective functions

Abstract: This paper proposes a computationally efficient optimization algorithm for segmenting colour satellite images.CS algorithm incorporating Mantegna's and McCulloch's method for modeling levy flight is presented.PSO, DPSO, ABC and CS algorithms are compared with the proposed algorithm.All these optimization algorithms are exploited using three different objective functions.Performance assessment metrics demonstrated the improvement in the efficiency of the proposed algorithm. Satellite image segmentation is challenging due to the presence of weakly correlated and ambiguous multiple regions of interest. Several bio-inspired algorithms were developed to generate optimum threshold values for segmenting such images efficiently. Their exhaustive search nature makes them computationally expensive when extended to multilevel thresholding. In this paper, we propose a computationally efficient image segmentation algorithm, called CSMcCulloch, incorporating McCulloch's method for l e ? v y flight generation in Cuckoo Search (CS) algorithm. We have also investigated the impact of Mantegna's method for l e ? v y flight generation in CS algorithm (CSMantegna) by comparing it with the conventional CS algorithm which uses the simplified version of the same. CSMantegna algorithm resulted in improved segmentation quality with an expense of computational time. The performance of the proposed CSMcCulloch algorithm is compared with other bio-inspired algorithms such as Particle Swarm Optimization (PSO) algorithm, Darwinian Particle Swarm Optimization (DPSO) algorithm, Artificial Bee Colony (ABC) algorithm, Cuckoo Search (CS) algorithm and CSMantegna algorithm using Otsu's method, Kapur entropy and Tsallis entropy as objective functions. Experimental results were validated by measuring PSNR, MSE, FSIM and CPU running time for all the cases investigated. The proposed CSMcCulloch algorithm evolved to be most promising, and computationally efficient for segmenting satellite images. Convergence rate analysis also reveals that the proposed algorithm outperforms others in attaining stable global optimum thresholds. The experiments results encourages related researches in computer vision, remote sensing and image processing applications.

Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings

Abstract: Named Entity Recognition is a well established information extraction task with many state of the art systems existing for a variety of languages. Most systems rely on language specific resources, large annotated corpora, gazetteers and feature engineering to perform well monolingually. In this paper, we introduce an attentional neural model which only uses language universal phonological character representations with word embeddings to achieve state of the art performance in a monolingual setting using supervision and which can quickly adapt to a new language with minimal or no data. We demonstrate that phonological character representations facilitate cross-lingual transfer, outperform orthographic representations and incorporating both attention and phonological features improves statistical efficiency of the model in 0-shot and low data transfer settings with no task specific feature engineering in the source or target language.

PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors

Abstract: This paper contributes to a growing body of evidence that—when coupled with appropriate machine-learning techniques–linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data. In particular, we show that phonological features outperform character-based models. PanPhon is a database relating over 5,000 IPA segments to 21 subsegmental articulatory features. We show that this database boosts performance in various NER-related tasks. Phonologically aware, neural CRF models built on PanPhon features are able to perform better on monolingual Spanish and Turkish NER tasks that character-based models. They have also been shown to work well in transfer models (as between Uzbek and Turkish). PanPhon features also contribute measurably to Orthography-to-IPA conversion tasks.

Securing web applications from injection and logic vulnerabilities

Abstract: Context: Web applications are trusted by billions of users for performing day-to-day activities. Accessibility, availability and omnipresence of web applications have made them a prime target for attackers. A simple implementation flaw in the application could allow an attacker to steal sensitive information and perform adversary actions, and hence it is important to secure web applications from attacks. Defensive mechanisms for securing web applications from the flaws have received attention from both academia and industry.Objective: The objective of this literature review is to summarize the current state of the art for securing web applications from major flaws such as injection and logic flaws. Though different kinds of injection flaws exist, the scope is restricted to SQL Injection (SQLI) and Cross-site scripting (XSS), since they are rated as the top most threats by different security consortiums.Method: The relevant articles recently published are identified from well-known digital libraries, and a total of 86 primary studies are considered. A total of 17 articles related to SQLI, 35 related to XSS and 34 related to logic flaws are discussed.Results: The articles are categorized based on the phase of software development life cycle where the defense mechanism is put into place. Most of the articles focus on detecting the flaws and preventing the attacks against web applications.Conclusion: Even though various approaches are available for securing web applications from SQLI and XSS, they are still prevalent due to their impact and severity. Logic flaws are gaining attention of the researchers since they violate the business specifications of applications. There is no single solution to mitigate all the flaws. More research is needed in the area of fixing flaws in the source code of applications.

Dynamic mechanical analysis and free vibration behavior of intra-ply woven natural fiber hybrid polymer composite:

Abstract: Influence of nature of weaving pattern and intra-ply hybridization of natural fibers on dynamic mechanical and free vibration characteristics of woven banana/jute polyester composite has been inves...

Effect of particle surface treatment and blending method on flexural properties of injection-molded cenosphere/HDPE syntactic foams

Abstract: The present work on cenosphere/high-density polyethylene (HDPE) syntactic foams aims at understanding the effect of surface treatment of cenospheres and functionalization of HDPE on flexural properties. Cenospheres are treated with silane, and HDPE is functionalized with 10 % dibutyl maleate. Effects of mechanical and Brabender mixing methods are also studied. Flexural test specimens are cast with 20, 40, and 60 wt% of cenospheres using injection molding. The flexural modulus and strength are found to increase with increasing cenosphere content. Particle breakage increases with the cenosphere content, and the measured properties show increased dependence on processing method. Brabender mixing resulted in 70 and 41 % higher modulus and strength for 60 wt% cenospheres than HDPE. Modulus of syntactic foams is predicted by two theoretical models. Bardella–Genna model provides close estimates for syntactic foams having 20 and 40 wt% cenospheres, while predictions are higher for higher cenosphere content, likely due to particle breakage during processing. The uncertainty in the properties of cenospheres due to defects contributes to the variation in the predicted values.

Microbial synthesis of chalcogenide semiconductor nanoparticles: a review

Abstract: Chalcogenide semiconductor quantum dots are emerging as promising nanomaterials due to their size tunable optoelectronic properties. The commercial synthesis and their subsequent integration for practical uses have, however, been contorted largely due to the toxicity and cost issues associated with the present chemical synthesis protocols. Accordingly, there is an immediate need to develop alternative environment-friendly synthesis procedures. Microbial factories hold immense potential to achieve this objective. Over the past few years, bacteria, fungi and yeasts have been experimented with as eco-friendly and cost-effective tools for the biosynthesis of semiconductor quantum dots. This review provides a detailed overview about the production of chalcogen-based semiconductor quantum particles using the inherent microbial machinery.

Driving Behaviors: Models and Challenges for Non-Lane Based Mixed Traffic

Abstract: Most published microscopic driving behavior models, such as car following and lane changing, were developed for homogeneous and lane-based settings. In the emerging and developing world, traffic is characterized by a wide mix of vehicle types (e.g., motorized and non-motorized, two, three and four wheelers) that differ substantially in their dimensions, performance capabilities and driver behavior and by a lack of lane discipline. This paper presents a review of current driving behavior models in the context of mixed traffic, discusses their limitations and the data and modeling challenges that need to be met in order to extend and improve their fidelity. The models discussed include those for longitudinal and lateral movements and gap acceptance. The review points out some of the limitations of current models. A main limitation of current models is that they have not explicitly considered the wider range of situations that drivers in mixed traffic may face compared to drivers in homogeneous lane-based traffic, and the strategies that they may choose in order to tackle these situations. In longitudinal movement, for example, such strategies include not only strict following, but also staggered following, following between two vehicles and squeezing. Furthermore, due to limited availability of trajectory data in mixed traffic, most of the models are not estimated rigorously. The outline of modeling framework for integrated driver behavior was discussed finally.

Pyrene–Oxadiazoles for Organic Light-Emitting Diodes: Triplet to Singlet Energy Transfer and Role of Hole-Injection/Hole-Blocking Materials

Abstract: Three pyrene–oxadiazole derivatives were synthesized and characterized by optical, electrochemical, thermal, and theoretical investigations to obtain efficient multifunctional organic light emitting diode (OLED) materials. Synthesized molecules were used as emitters and electron transporters in three different device configurations, involving hole-injection/hole-blocking materials that showed good current and power efficiencies. To understand the underlying mechanisms involved in the application of these molecules as emitters and transporters, a detailed photophysical characterization of molecules 4–6 was carried out. The absorption, steady-state fluorescence, phosphorescence, fluorescence lifetime, and phosphorescence lifetime measurements were carried out. The high quantum yield and efficient reverse intersystem crossing leading to delayed fluorescence emission makes the molecule a good emitter, and the charge delocalization properties leading to excimer formation make them efficient electron transporte...

Bovine serum albumin catalyzed one-pot, three-component synthesis of dihydropyrano[2,3-c]pyrazole derivatives in aqueous ethanol

Abstract: Bovine serum albumin (BSA) catalyzed synthesis of dihydropyrano[2,3-c]pyrazole derivatives via a one pot, three component reaction of an aldehyde/ketone/isatin, malononitrile and 3-methyl-1H-pyrazol-5-(4H)-one in H2O–EtOH (7 : 3) at ambient temperature was developed in this work. The catalyst was found to work efficiently for aldehydes, ketones and isatins to give the corresponding dihydropyrano[2,3-c]pyrazole and spiro[indoline-3,4′-pyrano[2,3-c]pyrazole] derivatives in high yields. BSA showed a broad range of catalytic promiscuity towards various aldehydes, aromatic/aliphatic ketones and substituted isatins. The use of an environmentally benign protocol, reusability of the catalyst, avoidance of hazardous solvents, excellent yields, easy work up and no byproduct formation make BSA an attractive candidate for further applications as a biocatalyst.

Analysis of variability and trends in rainfall over northern Ethiopia

Abstract: Rainfall is a key component of the hydrological cycle, and its spatiotemporal variability is essential from the both scientific and practical perspectives. This study is focused on analysis of temporal variability and trends in historical rainfall records for stations in the Geba River basin. The Geba catchment is surrounded by the Danakil basin in the east, by the Tekeze River basin in the south, and the Werie River basin in the west which is located in the northern Ethiopia regional state of Tigray between 38° 38′ E and 39° 48′ E and 13° 18′ N and 14° 15′ N. The climate over the basin is semi-arid and has large elevation differences varying from 926 to 3301 m above mean sea level. Daily rainfall data of 43 years measured at seven stations in the basin for the period of 1971 to 2013 for annual and seasonal rainfall trends have been processed and used for the analysis. The non-parametric Mann–Kendall test and the Sen’s slope estimator have been used to identify the existence of trends and slope magnitude in rainfall. Results revealed that although there was a mix of positive and negative trends, they were no statistically significant except at one station which showed an increasing trend in annual rainfall. Considering rainfall in different seasons, an increase in rainfall was observed in two stations in the wet season which, however, was not statistically significant. For the remaining stations, a weak decline in wet season rainfall (not statistically significant at 95 % confidence level) for four stations and absence of trend for one station were noticed. Furthermore, no statistically significant trend (positive or negative) was evident for the dry season rainfall. Results of this study may prove useful in the preparation of climate change mitigation and adaptation strategies in rainfed agricultural and water supply systems in the region.