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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. -
A Document Clustering Approach Using Shared Nearest Neighbour Affinity, TF-IDF and Angular Similarity
Quantum of data is increasing in an exponential order. Clustering is a major task in many text mining applications. Organizing text documents automatically, extracting topics from documents, retrieval of information and information filtering are considered as the applications of clustering. This task reveals identical patterns from a collection of documents. Understanding of the documents, representation of them and categorization of documents require various techniques. Text clustering process requires both natural language processing and machine learning techniques. An unsupervised spatial pattern identification approach is proposed for text data. A new algorithm for finding coherent patterns from a huge collection of text data is proposed, which is based on the shared nearest neighbour. The implementation followed by validation confirms that the proposed algorithm can cluster the text data for the identification of coherent patterns. The results are visualized using a graph. The results show the methodology works well for different text datasets. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Dual Step Strategy for Retinal Thin Vessel Enhancement/Extraction
Blood vessel extraction from retinal images is a challenging and fundamental step in pathological analysis. Most of the vessel extraction algorithms face difficulty in the extraction of thin vessels. In this paper, a dual step strategy for retinal thin vessel enhancement/extraction is proposed. Since thin vessel pixels have intensities closer to the background non-vessel pixels, the first level enhancement algorithms usually suffers in its accurate extraction. This led to explore a novel idea of eliminating the effects of thick vessel pixels in a reference image, via replacing it with neighboring non-vessel pixels. By applying second level enhancement on the vessel subtracted image, thin vessels are projected and improvement in extraction is attained subjectively as well as objectively. 2019 IEEE. -
A dual-functional rhodamine B and azo-salicylaldehyde derivative for the simultaneous detection of copper and hypochlorite: synthesis, biological applications and theoretical insights
A multifunctional rhodamine derivative containing azo-salicylaldehyde (BBS) was designed and synthesized as a colorimetric and fluorescence turn-on probe for the selective detection of copper cations (Cu2+) and hypochlorite anions (OCl?) in aqueous media. In the presence of Cu2+, the probe BBS exhibited turn-on absorption and fluorescence change at 554 nm and 585 nm, respectively. The binding mechanism of BBS with Cu2+ induces the opening of a spirolactam ring in the rhodamine moiety by the formation of a metal-ligand complex, achieving 10-fold enhancement in fluorescence and quantum yield, along with a binding constant of 1 104 M?1 and a detection limit of 2.61 ?M. Addition of OCl? enhanced the absorbance and fluorescence intensities at 520 nm and 575 nm, respectively. The probe BBS underwent hypochlorite-mediated oxidation, followed by hydrolysis, resulting in the formation of rhodamine B itself, which is detectable by the naked eye via the color and fluorescence enhancement by 11-fold with a high quantum yield and a detection limit of 1.96 ?M. For practical applications, sensor BBS can be used to detect Cu2+ in water samples and on cotton swabs. For biological applications, the interaction of the BBS-Cu(ii) complex with transport proteins such as bovine serum albumin (BSA) and ct-DNA was investigated through UV-vis and fluorescence titration experiments. Additionally, the structural optimization of BBS and the BBS-Cu(ii) complex was demonstrated using DFT, and the interactions of the BBS-Cu(ii) complex with BSA and ct-DNA were analysed through theoretical docking studies. Bioimaging studies were conducted by capturing fluorescence images of BBS with Cu2+ and OCl? in a physiological medium containing living plant tissue using green gram seeds. 2024 The Royal Society of Chemistry. -
A Dynamic Anomaly Detection Approach for Fault Detection on Fire Alarm System Based on Fuzzy-PSO-CNN Approach
Early detection is crucial due to the catastrophic threats to life and property that are involved with fires. Sensory systems used in fire alarms are prone to false alerts and breakdowns, endangering lives and property. Therefore, it is essential to check the functionality of smoke detectors often. Traditional plans for such systems have included periodic maintenance; however, because they don't account for the condition of the fire alarm sensors, they are sometimes carried out not when necessary but rather on a predefined conservative timeframe. They describe a data-driven online anomaly detection of smoke detectors, which analyzes the behavior of these devices over time and looks for aberrant patterns that may imply a failure, to aid in the development of a predictive maintenance approach. The suggested procedure begins with three steps: preprocessing, segmentation, and model training. A pre-processing unit can enhance data quality by compensating for sensor drifts, sample-to-sample volatility, and disturbances (noise). The proposed approach normalizes the data in preparation. The smoke source can be detected by using segmentation to differentiate it from the background. Following segmentation, Fuzzy-PSO-CNN is used to train the models. CNN and PSO, two of the most used alternatives, are both outperformed by the proposed method. 2023 IEEE. -
A facile and economic electrochemical sensor for methylmalonic acid: A potential biomarker for vitamin B12 deficiency
A facile and cost-effective method based on a modified pencil graphite electrode (PGE) has been developed for the sensing of methylmalonic acid (MMA). The electrode (Ag-PEDOT/PGE) was designed by the electrodeposition of Ag nanoparticles (NPs) on carbon fibre paper (CFP) coated with poly(3,4-ethylenedioxythiophene) (PEDOT). Field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), and other electroanalytical techniques were used to characterize the modified electrodes. The fabricated sensor showcased a wide linear dynamic range (0.50 pM-55 nM) and a low detection limit (0.16 pM). A sharp increase in anodic peak current shows the excellent rate of electron transfer arising from Ag-PEDOT and PGE. The developed electrode was effectively utilized towards electrochemical MMA determination in urine and human blood serum samples. The results obtained certainly indicate that the sensor has high selectivity, ensures rapid detection, is reproducible, and has high stability towards the quantification of MMA in real samples. This journal is The Royal Society of Chemistry and the Centre National de la Recherche Scientifique. -
A Facile One-Pot Solvent-Free Synthesis, in Vitro and in Silico Studies of a Series of Tetrahydropyridine Derivatives as Breast Cancer Inhibitors
Ammonium trifluoroacetate (ATA) catalysed synthesis of 1,2,5,6-tetrahydropyridine (THP) derivatives, under eco-friendly conditions via a facile one-pot strategy. We have synthesized fifteen THP derivatives, and docked into the crystal structure of Phosphatase and Tensin Homolog deleted on Chromosome 10 (PTEN) tumour suppressor protein (PDB ID: 1D5R) based on drug-likeness prediction and pharmacokinetic properties. Molecular docking simulation studies reveal that four of our synthesised compounds are potential hit candidates because they bound to the receptor through 57 conventional hydrogen bonds with ?9.7 to ?8.6 kcal/mol of binding energy. The compounds were evaluated using the in vitro inhibitory activity of MCF-7 breast cancer cell lines. Identified hit compounds showed moderate inhibition at (160320 ?g/mL) and inhibitory concentration IC50 values in the low micromolar range of 171.062, 189.803, 195.469 and 181.272 ?g/mL respectively. The results obtained are very promising; therefore fine-tuning the substituents of hit molecules with appropriate bioisosteres can lead to the development of potential leads. 2023 Wiley-VCH GmbH. -
A facile one-step microwave synthesis of Pt deposited on N & P co-doped graphene intercalated carbon black - An efficient cathode electrocatalyst for PEM fuel cell
A facile, single step microwave assisted polyol route for simultaneously depositing platinum as well as co-doping graphene oxide, is herein proposed. However, low durability and full cell performance of Pt/NPG (platinum deposited on nitrogen phosphorous co-doped graphene) was observed due to restacking of graphene layers. This issue was addressed by intercalating CB into the graphene layers as spacers during the synthesis (in-situ addition of spacers - Pt/(NPG + S)). Moreover, to study the influence of spacers, external addition of spacers (ex-situ - Pt/(NPG) + S) were also examined. Results from our study indicate that in-situ addition of spacers- Pt/(NPG + S) enhanced the full cell performance (405 mW cm?2) and exhibited <40% ECSA loss (37.47%), thereby attaining DoE target. Thus, emerging as a durable cathode electrocatalyst (Pt/(NPG + S)) for PEM fuel cells. 2022 Hydrogen Energy Publications LLC -
A facile, green synthesis of carbon quantum dots from Polyalthia longifolia and its application for the selective detection of cadmium
Carbon quantum dots (CQDs) has received world-wide recognition for their outstanding physicochemical properties that have the ability to substitute the semiconductor quantum dots. Herein, we have developed a strategy to determine the presence of Cd2+ using CQDs as a fluorescence probe. The CQDs were synthesized from the leaves of Polyalthia longifolia (a natural source) through a one-step hydrothermal method. The CQDs obtained from Polyalthia longifolia (p-CQDs) was characterized using XRD, TEM, FTIR, Raman Spectroscopy, XPS Studies, UVVisible spectroscopy and PL Spectroscopy. The p-CQDs displayed bright red fluorescence under the UV light, with good water solubility, and appreciable photostability and a quantum yield of 22%. The p-CQDs had a quasi-spherical morphology with an average particle size of 3.33 nm. The p-CQDs showed high selectivity and sensitivity for the detection of Cd2+ with a low limit of detection of 2.4 nM and a wide linear range of 7.3 nM12 ?M. The PL intensity of the p-CQDs showed a quenching effect in presence of Cd2+ and the mechanism of quenching was validated via fluorescence lifetime decay studies. We have also studied the effectiveness of the fluorescent probe developed for Cd2+ sensing in real samples of ground water and industrial effluents. 2022 Elsevier Ltd -
A facile, green synthesis of carbon quantum dots from Polyalthia longifolia and its application for the selective detection of cadmium /
Dyes and Pigments, Vol.210, ISSN No: 0143-7208.
Carbon quantum dots (CQDs) has received world-wide recognition for their outstanding physicochemical properties that have the ability to substitute the semiconductor quantum dots. Herein, we have developed a strategy to determine the presence of Cd<sup>2+</sup> using CQDs as a fluorescence probe. The CQDs were synthesized from the leaves of <em>Polyalthia longifolia</em> (a natural source) through a one-step hydrothermal method. The CQDs obtained from <em>Polyalthia longifolia</em> (p-CQDs) was characterized using XRD, TEM, FTIR, Raman Spectroscopy, XPS Studies, UV–Visible spectroscopy and PL Spectroscopy. The p-CQDs displayed bright red fluorescence under the UV light, with good water solubility, and appreciable photostability and a quantum yield of 22%. The p-CQDs had a quasi-spherical morphology with an average particle size of 3.33 nm. -
A FAMILY OF CONGRUENCES FOR (2, ?)?REGULAR BIPARTITIONS
The congruence of certain restricted partition functions known as regular bipartition is discussed in this paper. We particularly investigate the (2, ?)-regular bipartitions of n, denoted by B2,? (n), and establish certain congruences for B2,? (n) when ? ? 3. We derive infinite families of congruences modulo 4 for the (2, 3)-regular bipartition. We also obtain a generalisation of the regular bipartition for modulo p and p2. Indian Mathematical Society, 2022. -
A Family of Mexican Hat Wavelet Stieltjes Transform for Unbounded Non-decreasing Functions
In the present article, we examine the characteristics of the Mexican hat wavelet Stieltjes transform (MHWST) for a specific set of functions belonging to one of the sub-class of bounded variation functions. The subset comprises functions that are unbounded and non-decreasing. Further, a unified approach is applied to establish a uniqueness theorem and subsequently derive a representation theorem for the MHWST. The Author(s), under exclusive licence to The National Academy of Sciences, India 2024. -
A fast survey on recent developments in designing colorimetric and fluorescent sensors for the selective detection of essential amino acids
Owing to the biological significance of various amino acids, developing accurate and cost-effective sensing techniques for the selective detection of amino acids has recently attracted growing interest. This review discusses the recent advancements of chemosensors in the selective detection of only essential amino acids out of a total of twenty amino acids, which have been applied in chemosensing research, and the mechanism of their action. The focus is directed towards the detection of the most important essential amino acids, like leucine, threonine, lysine, histidine, tryptophan and methionine, since isoleucine and valine are yet to be explored in regard to chemosensing. According to their chemical and fluorescence properties, different sensing techniques, such as the reaction-based approach, DNA-based sensors, nanoparticle formation, coordination ligand binding, host-guest chemistry, the fluorescence indicator displacement (FID) approach, electrochemical sensors, carbon dot-based sensors, MOF-based sensors and metal-based techniques, have been described. 2023 The Royal Society of Chemistry. -
A Feature Selection Study on the Bot-IoT Dataset Using Ensemble Classification Techniques
IoT is an emerging giant in the field of technol- ogy, taking over traditional systems, providing interconnected- ness, convenience, efficiency, and automation, making our lives unimaginably better. However, security for these IoT systems is challenging, especially due to their interconnectedness, making them vulnerable to various cyber threats. The rising tide of IoT botnets, especially, presents a unique challenge. This has urgently increased the need for Intrusion Detection research. Modern Intrusion Detection approaches often employ Machine Learning for effective results. Feature Selection is extremely important while creating Machine Learning Classification models to avoid overfitting and poor performance. This paper focuses on running a Feature Selection study on the Bot-IoT dataset provided by UNSW to increase the accuracy of a ML model. The paper tests 5 types of Feature Selection methods, from Filter- based, Wrapper-based and Embedded methods, combined with two distinct ensemble classifiers: Random Forest + Adaboost and XGBoost. Each combination is tested with the dataset, and the accuracy is compared to find the most effective and versatile feature selection method that can assist both Stacking and Voting- type Ensemble classifiers. The results show that Karl Pearson can provide the best accuracy when applied to both Ensemble Classifiers. 2024 IEEE. -
A feminist interrogation of gender and class representation in specific detergent advertisements /
Women have been stereotyped by society at large to be caretakers in the domestic front. Advertisement is a tool used to influence people and stereotypes have often been included in advertisements to target a specific audience. Washing clothes has been stereotyped as a women’s job in society across the globe. The concept of Feminism is to bring about equality of both genders in all spheres if life. -
A Feminist Perspective on the Food and Gender based Marketing Narrative
Nutrition to the body is a basic element for sustenance and growth biologically, provided through food. This paper aims to understand why there is a difference between foods that are marketed gender-specifically to males and females separately. There have been a lot of participative changes in the household kitchen activities since the birth of the concept. However, certain things have continued to remain the same either as a result of tradition, preference, or systemic societal loop. This paper aims to categorically understand this patterned behaviour behind gender based food marketing and the consequent consumptions so as to find a more sustainable and inclusive approach for food marketing for the firms of this industry. The aim is also to shed light on the impact of such practices on the psychological level of the individual buyer that stems to form a pattern, creating a recurring practice out of habit, over internal choice. The Electrochemical Society -
A feminist study of food in select culinary narratives
An academic study of food entails a study of food at the intersection of individual experience, socio-cultural significance and global politics of food. A study of the emerging genre of culinary narratives, therefore, is a study of women’s experience of food, shaped by the socio-cultural context she occupies and its interaction with the world food scenario. This research titled “A Feminist Study of Food in Select Culinary Narratives” studies Indian immigrant women’s relationship with food in the twenty-first century globalised, capitalist, multicultural, American society. The research places itself within the broader framework of literature, cultural and women’s studies and focuses on the emerging genre of South-Asian diasporic culinary narratives. It, therefore, adds to the limited scholarship on the genre of diasporic culinary narratives by looking at the works of Shoba Narayan’s Monsoon Diary: A Memoir with Recipes (2003),Amulya Malladi’s
Serving Crazy with Curry (2007), Bharti Kirchner’s Pastries: A Novel of Desserts and Discoveries (2009) and Sandeepa Mukherjee Datta’s Bong Mom’s Cookbook (2013).Consequently, the research examines the various roles performed by food, as the immigrant woman navigates her geographical and cultural displacement. In this context, the research views food as a means for immigrant women to articulate their sense of ‘self’ and critiquing the standardization of women’s relationship with food by the capitalist food industry. Moreover, critiques of capitalist notions of women’s relationship with food further enables the select texts to re-envision women’s relationship with the kitchen and domestic work. The research also highlights the difference in the first and second generation immigrant women’s use of food to navigate their displacement. -
A Feminist study of food in select culinary narratives
This research studies Indian immigrant women s relationship with food in the twenty-first century globalised, capitalist, multicultural, American society. It adds to the limited scholarship on the genre of diasporic culinary narratives by looking at the works of Shoba Narayan s Monsoon Diary: A Memoir with Recipes (2003),Amulya Malladi s Serving Crazy with Curry (2007), Bharti Kirchner s Pastries: A Novel of Desserts and Discoveries (2009) and Sandeepa Mukherjee Datta s Bong Mom s Cookbook (2013). The research thus views food as a means for immigrant women to articulate their sense of self and critique the standardization of women s relationship with food by the capitalist food industry. Moreover, critiques of capitalist notions of women s relationship with food further enables the select texts to re-envision women s relationship with the kitchen and domestic work. Finally, the study analyses select culinary narratives as paradoxical texts for its simultaneous critique of the commodification of ethnic culture and performance of cultural self-commodification -
A finger print recognition using CNN Model
The fundamental goal of this research is to improve the new identification accuracy for fingerprint acknowledgment by contrasting Convolutional Neural Networks (CNN) model frameworks for biometric safety in the cloud with Conventional inception models (TIM). Accuracy was computed and compared using a CNN model and standard Inception Models (N=10). The statistical significance was calculated using SPSS. Average and standard deviation for a 95% confidence interval, 0.05% G-power cutoff. The TIM and Convolutional Neural Networks performed an autonomous T-Test on the samples. CNN is more successful (93%) than TIM (61%). Based on a significant value of 0.048 for the comparison ratio (p0.05), there is a statistically significant difference between the CNN and the TIM transformation. According to the findings, the suggested CNN model is 93% accurate on the dataset, with no rejected samples. 2023 IEEE. -
A First Report of Docosahexaenoic Acid-Clocked Polymer Enveloped Gold Nanoparticles: A Way to Precision Breast Cancer and Triple Negative Breast Cancer Therapy and Its Apoptosis Induction
Functionalized gold nanoparticles (GNPs) are extensively utilized in various disciplines due to their excellent bioactivity, biocompatibility, and extended drug half-life, influenced by the ligands and size that are changed on surfaces. In this study, we successfully fabricated GNPs coated with ligands containing docosahexaenoic acid (DHA) and polyethylene glycol (PEG) clocked by a carboxyl group. These nanoparticles are referred to as MPA@GNPs-PEG-DHA. The cytotoxicity results demonstrate that MPA@GNPs-PEG-DHA exhibits superior cell selectivity, explicitly inhibiting the proliferation of breast cancerous cells than noncancerous cell lines. Apoptosis is involved in the reduction of cell proliferation by MPA@GNPs-PEG-DHA, as demonstrated clearly through many assays measuring apoptotic index, including AO/EB staining, DAPI, annexin V-FITC staining, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) measurement. The efficacy of MPA@GNPs-PEG-DHA in inducing apoptosis was demonstrated by its inhibition of mitochondrial dysfunction by ROS. MPA@GNPs-PEG-DHA has the potential to improve the induction of apoptosis in breast cancerous cells. 2024 Wiley Periodicals LLC.