Search results for: Atanu Rakshit
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8

Search results for: Atanu Rakshit

8 Recognizing Customer Preferences Using Review Documents: A Hybrid Text and Data Mining Approach

Authors: Oshin Anand, Atanu Rakshit

Abstract:

The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

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7 Drone Classification Using Classification Methods Using Conventional Model With Embedded Audio-Visual Features

Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

Abstract:

This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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6 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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5 Study of Structure and Properties of Polyester/Carbon Blends for Technical Applications

Authors: Manisha A. Hira, Arup Rakshit

Abstract:

Textile substrates are endowed with flexibility and ease of making–up, but are non-conductors of electricity. Conductive materials like carbon can be incorporated into textile structures to make flexible conductive materials. Such conductive textiles find applications as electrostatic discharge materials, electromagnetic shielding materials and flexible materials to carry current or signals. This work focuses on use of carbon fiber as conductor of electricity. Carbon fibers in staple or tow form can be incorporated in textile yarn structure to conduct electricity. The paper highlights the process for development of these conductive yarns of polyester/carbon using Friction spinning (DREF) as well as ring spinning. The optimized process parameters for processing hybrid structure of polyester with carbon tow on DREF spinning and polyester with carbon staple fiber using ring spinning have been presented. The studies have been linked to highlight the electrical conductivity of the developed yarns. Further, the developed yarns have been incorporated as weft in fabric and their electrical conductivity has been evaluated. The paper demonstrates the structure and properties of fabrics developed from such polyester/carbon blend yarns and their suitability as electrically dissipative fabrics.

Keywords: carbon fiber, conductive textiles, electrostatic dissipative materials, hybrid yarns

Procedia PDF Downloads 271
4 The Nexus Between the Rise of Autocratisation and the Deeper Level of BRI Engagement

Authors: Dishari Rakshit, Mitchell Gallagher

Abstract:

The global landscape is witnessing a disconcerting surge in democratic backsliding, engendering concerns over the rise of autocratisation. This research demonstrates the intricate relationship between a nation's domestic propensity for autocratic governance and its trade relations with China. Giving prominence to Belt and Road Initiative (BRI) investments, this study adopts a rigorous neorealist framework to discern the complexities of nations' economic interests amidst an anarchic milieu and how these interests may transcend steadfast adherence to democratic principles. The burgeoning bipolarity in the international political setting serves as a backdrop to our inquiry. To operationalise our hypothesis, we conduct a large-scale 'N' study, encompassing a comprehensive global dataset comprising countries' democracy indicators, total trade volume with China, and cumulative Chinese BRI investments over a substantial temporal expanse. By meticulously examining BRI signatories’, we aim to ascertain the potential accentuation of democratic backsliding among these nations. To test our empirical underpinning, we will validate our findings through cogent case studies. Our analysis adds to the scholarship on multifaceted interactions between trade dynamics and democratic governance within the fabric of the international political landscape. In its culmination, the paper addresses the question- has the erstwhile grandeur of bipolarity resurfaced in the contemporary global panorama? Concurrently, we explore the nexus between the ascendant wave of autocratisation as a by-product of the Beijing Consensus? Pertinent to policymakers, our discoveries stand poised to furnish a comprehensive grasp of the manifold implications arising from the deepening entanglements with China under the auspices of the BRI.

Keywords: democracy, autocracy, china, belt road initiative, international political economy

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3 Formation of the Water Assisted Supramolecular Assembly in the Transition Structure of Organocatalytic Asymmetric Aldol Reaction: A DFT Study

Authors: Kuheli Chakrabarty, Animesh Ghosh, Atanu Roy, Gourab Kanti Das

Abstract:

Aldol reaction is an important class of carbon-carbon bond forming reactions. One of the popular ways to impose asymmetry in aldol reaction is the introduction of chiral auxiliary that binds the approaching reactants and create dissymmetry in the reaction environment, which finally evolves to enantiomeric excess in the aldol products. The last decade witnesses the usage of natural amino acids as chiral auxiliary to control the stereoselectivity in various carbon-carbon bond forming processes. In this context, L-proline was found to be an effective organocatalyst in asymmetric aldol additions. In last few decades the use of water as solvent or co-solvent in asymmetric organocatalytic reaction is increased sharply. Simple amino acids like L-proline does not catalyze asymmetric aldol reaction in aqueous medium not only that, In organic solvent medium high catalytic loading (~30 mol%) is required to achieve moderate to high asymmetric induction. In this context, huge efforts have been made to modify L-proline and 4-hydroxy-L-proline to prepare organocatalyst for aqueous medium asymmetric aldol reaction. Here, we report the result of our DFT calculations on asymmetric aldol reaction of benzaldehyde, p-NO2 benzaldehyde and t-butyraldehyde with a number of ketones using L-proline hydrazide as organocatalyst in wet solvent free condition. Gaussian 09 program package and Gauss View program were used for the present work. Geometry optimizations were performed using B3LYP hybrid functional and 6-31G(d,p) basis set. Transition structures were confirmed by hessian calculation and IRC calculation. As the reactions were carried out in solvent free condition, No solvent effect were studied theoretically. Present study has revealed for the first time, the direct involvement of two water molecules in the aldol transition structures. In the TS, the enamine and the aldehyde is connected through hydrogen bonding by the assistance of two intervening water molecules forming a supramolecular network. Formation of this type of supramolecular assembly is possible due to the presence of protonated -NH2 group in the L-proline hydrazide moiety, which is responsible for the favorable entropy contribution to the aldol reaction. It is also revealed from the present study that, water assisted TS is energetically more favorable than the TS without involving any water molecule. It can be concluded from this study that, insertion of polar group capable of hydrogen bond formation in the L-proline skeleton can lead to a favorable aldol reaction with significantly high enantiomeric excess in wet solvent free condition by reducing the activation barrier of this reaction.

Keywords: aldol reaction, DFT, organocatalysis, transition structure

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2 Development of Mesoporous Gel Based Nonwoven Structure for Thermal Barrier Application

Authors: R. P. Naik, A. K. Rakshit

Abstract:

In recent years, with the rapid development in science and technology, people have increasing requirements on uses of clothing for new functions, which contributes to opportunities for further development and incorporation of new technologies along with novel materials. In this context, textiles are of fast decalescence or fast heat radiation media as per as comfort accountability of textile articles are concern. The microstructure and texture of textiles play a vital role in determining the heat-moisture comfort level of the human body because clothing serves as a barrier to the outside environment and a transporter of heat and moisture from the body to the surrounding environment to keep thermal balance between body heat produced and body heat loss. The main bottleneck which is associated with textile materials to be successful as thermal insulation materials can be enumerated as; firstly, high loft or bulkiness of material so as to provide predetermined amount of insulation by ensuring sufficient trapping of air. Secondly, the insulation depends on forced convection; such convective heat loss cannot be prevented by textile material. Third is that the textile alone cannot reach the level of thermal conductivity lower than 0.025 W/ m.k of air. Perhaps, nano-fibers can do so, but still, mass production and cost-effectiveness is a problem. Finally, such high loft materials for thermal insulation becomes heavier and uneasy to manage especially when required to carry over a body. The proposed works aim at developing lightweight effective thermal insulation textiles in combination with nanoporous silica-gel which provides the fundamental basis for the optimization of material properties to achieve good performance of the clothing system. This flexible nonwoven silica-gel composites fabric in intact monolith was successfully developed by reinforcing SiO2-gel in thermal bonded nonwoven fabric via sol-gel processing. Ambient Pressure Drying method is opted for silica gel preparation for cost-effective manufacturing. The formed structure of the nonwoven / SiO₂ -gel composites were analyzed, and the transfer properties were measured. The effects of structure and fibre on the thermal properties of the SiO₂-gel composites were evaluated. Samples are then tested against untreated samples of same GSM in order to study the effect of SiO₂-gel application on various properties of nonwoven fabric. The nonwoven fabric composites reinforced with aerogel showed intact monolith structure were also analyzed for their surface structure, functional group present, microscopic images. Developed product reveals a significant reduction in pores' size and air permeability than the conventional nonwoven fabric. Composite made from polyester fibre with lower GSM shows lowest thermal conductivity. Results obtained were statistically analyzed by using STATISTICA-6 software for their level of significance. Univariate tests of significance for various parameters are practiced which gives the P value for analyzing significance level along with that regression summary for dependent variable are also studied to obtain correlation coefficient.

Keywords: silica-gel, heat insulation, nonwoven fabric, thermal barrier clothing

Procedia PDF Downloads 81
1 Impact of Anthropogenic Stresses on Plankton Biodiversity in Indian Sundarban Megadelta: An Approach towards Ecosystem Conservation and Sustainability

Authors: Dibyendu Rakshit, Santosh K. Sarkar

Abstract:

The study illustrates a comprehensive account of large-scale changes plankton community structure in relevance to water quality characteristics due to anthropogenic stresses, mainly concerned for Annual Gangasagar Festival (AGF) at the southern tip of Sagar Island of Indian Sundarban wetland for 3-year duration (2012-2014; n=36). This prograding, vulnerable and tide-dominated megadelta has been formed in the estuarine phase of the Hooghly Estuary infested by largest continuous tract of luxurious mangrove forest, enriched with high native flora and fauna. The sampling strategy was designed to characterize the changes in plankton community and water quality considering three diverse phases, namely during festival period (January) and its pre - (December) as well as post (February) events. Surface water samples were collected for estimation of different environmental variables as well as for phytoplankton and microzooplankton biodiversity measurement. The preservation and identification techniques of both biotic and abiotic parameters were carried out by standard chemical and biological methods. The intensive human activities lead to sharp ecological changes in the context of poor water quality index (WQI) due to high turbidity (14.02±2.34 NTU) coupled with low chlorophyll a (1.02±0.21 mg m-3) and dissolved oxygen (3.94±1.1 mg l-1), comparing to pre- and post-festival periods. Sharp reduction in abundance (4140 to 2997 cells l-1) and diversity (H′=2.72 to 1.33) of phytoplankton and microzooplankton tintinnids (450 to 328 ind l-1; H′=4.31 to 2.21) was very much pronounced. The small size tintinnid (average lorica length=29.4 µm; average LOD=10.5 µm) composed of Tintinnopsis minuta, T. lobiancoi, T. nucula, T. gracilis are predominant and reached some of the greatest abundances during the festival period. Results of ANOVA revealed a significant variation in different festival periods with phytoplankton (F= 1.77; p=0.006) and tintinnid abundance (F= 2.41; P=0.022). RELATE analyses revealed a significant correlation between the variations of planktonic communities with the environmental data (R= 0.107; p= 0.005). Three distinct groups were delineated from principal component analysis, in which a set of hydrological parameters acted as the causative factor(s) for maintaining diversity and distribution of the planktonic organisms. The pronounced adverse impact of anthropogenic stresses on plankton community could lead to environmental deterioration, disrupting the productivity of benthic and pelagic ecosystems as well as fishery potentialities which directly related to livelihood services. The festival can be considered as multiple drivers of changes in relevance to beach erosion, shoreline changes, pollution from discarded plastic and electronic wastes and destruction of natural habitats resulting loss of biodiversity. In addition, deterioration in water quality was also evident from immersion of idols, causing detrimental effects on aquatic biota. The authors strongly recommend for adopting integrated scientific and administrative strategies for resilience, sustainability and conservation of this megadelta.

Keywords: Gangasagar festival, phytoplankton, Sundarban megadelta, tintinnid

Procedia PDF Downloads 200