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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. -
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. -
A Flexible HfO2 Nanofilm deposition on activated carbon fiber using atomic layer deposition method for Uric acid Detection
Flexible devices are in demand for the future development of electronic products. This study introduces a method where a uniform HfO2 thin nanofilm (10 nm) is deposited on flexible carbon cloth (CC) using atomic layer deposition (ALD). This electrode replaces traditional glassy carbon electrodes and other metal electrodes used in sensor fabrication. The ALD technique is employed for the first time in the fabrication of nanomaterials for non-enzymatic uric acid detection, offering advantages such as a solvent-free, binder-free, and low-chemical synthesis process. Synergistic effect of CC and HfO2 active sites contributes to its benchmark performance as a uric-acid sensors. HfO2 structure can supply more reaction sites and ion diffusion pathways. ALD-derived HfO2 exhibit a significant number of oxygen vacancies due to the suboxide formation. These oxygen vacancies or defects act as charge-trapping sites, and when biomolecules are introduced, the film electrical conductivity is altered. The presence of a uniformly distributed, grainy porous structure explains the successful immobilization of uric acid on HfO?. The highly rough surface and large surface area of 200-HfO?/CC boost uric acid sensitivity by more than five times compared with cleaned CC. This research work confirmed that the sensor possesses high selectivity and good reproducibility, suggesting its ability for practical application. HfO2 with a nanofilm structure was chosen for the selective detection of uric acid for the first time, with higher stability and lower detection level (10 nM) (less than reported literature). Herein, this study presents a promising electrocatalyst for nonenzymatic uric acid detection and real-time monitoring of uric acid in human serum and urine for disease prevention. 2026 Elsevier B.V. -
A Fog-Based Retrieval of Real-Time Data for Health Applications
Fog computing is an emerging technology that offers high-quality cloud services by providing high bandwidth, low latency, and efficient computational power and storage capacity. Although cloud computing is an efficient solution so far to store and retrieve the huge data of IoT devices, it is expected to limit its performance due to low latency and storage capacity. Fog computing addresses these limitations by extending its services to the cloud at the edge of the network. In this paper, we use a fog computing network approach for efficiently retrieving the real-time patient data. The performance of our proposed approach has been compared with the cloud computing approach in terms of retrieval time of real-time data. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A formative measurement model and development of quality of work-life scale based on two-factor theory: evidence from Indian private industries
Purpose: This study examines the quality of work-life (QoWL) as a formative construct and validates the scale in an Indian context. Taking a cue from the two-factor (Herzberg) theory, the study developed and validated a formative assessment model of QoWL in the current scenario. Design/methodology/approach: Cross-sectional data and a self-administered questionnaire were used to analyze the QoWL scale based on a sample of 841 respondents from IT/ITES, BFSI, CPG and manufacturing sectors. Indicators/items of QoWL were considered a first-order reflective construct, and factors of QoWL were considered second-order formative construct in the study. Embedded two-stage approach was used to assess the antecedent construct in the model in which QoWL was measured with seven formative indicators in stage one, and all the constructs of the QoWL are measured with a single item (Global_QWL, i.e. the essence of all constructs) in stage two. Findings: The study found QoWL as a formative construct with seven significant dimensions; namely, hygiene factors included fairness in compensation (FC), job security (JS), interpersonal relationship (IR), health and wellbeing (HWB), where motivational factors had rewards and career growth (RG), work-life balance (WLB) and learning and development (LD). The study also indicated the strong association of a single item (global_QWL) with all constructs of QoWL. The study findings conceptualize a QoWL as a formative construct within the mentioned sector and can be generalized and extended to other sectors of the economy as well. Research limitations/implications: Future researchers can take guidance to deal with the formative construct in the development and validation of scale in various topics in the field of HRM. Future researchers can extend the study across cities and different sectors. Practical implications: In this VUCA world, employees have to be constantly on their toes to ensure their organization remains relevant. In this context, the least organization can do for their employees is to offer a conducive environment and favorable QoWL. This study aims to assist the key decision-makers in applying the QoWL index as a formative construct and aiding them in improving the quality of their decisions. Social implications: Researcher believes that applying the QoWL index as a formative construct can aid decision-makers in improving the quality of their decisions by equipping them with relevant inputs and knowledge. Government can focus on the employees' welfare and introduce the current motivational and hygiene factors in the area of quality of life of the Indians. Originality/value: Formative assessment measurement of QoWL model was validated with the two-factor theory to understand the work environment of India in the private sector across different sectors. The unique finding of the study was a single item (global_QWL) to conclude the QoWL index as a formative construct by redundancy analysis. 2022, Emerald Publishing Limited. -
A Fractional Atmospheric Circulation System under the Influence of a Sliding Mode Controller
The earths surface is heated by the large-scale movement of air known as atmospheric circulation, which works in conjunction with ocean circulation. More than (Formula presented.) variables are involved in the complexity of the weather system. In this work, we analyze the dynamical behavior and chaos control of an atmospheric circulation model known as the Hadley circulation model, in the frame of Caputo and CaputoFabrizio fractional derivatives. The fundamental novelty of this paper is the application of the Caputo derivative with equal dimensionality to models that includes memory. A sliding mode controller (SMC) is developed to control chaos in this fractional-order atmospheric circulation system with uncertain dynamics. The proposed controller is applied to both commensurate and non-commensurate fractional-order systems. To demonstrate the intricacy of the models, we plot some graphs of various fractional orders with appropriate parameter values. We have observed the influence of thermal forcing on the dynamics of the system. The outcome of the analytical exercises is validated using numerical simulations. 2022 by the authors. -
A Frame Work For Continous Indian Sign Language Recognition Using Computer Vision
Sign language is a non-vocal, visually oriented natural language used by the hearing newlineimpaired and the hard-for-hearing part of society. It combines multiple modalities newlinelike hand movements, facial expressions and body poses. Static gestures involve basic finger movements such as numbers and alphabets, dynamic signs include words, and a sign sentence consists of grammatically connected and meaningful dynamic words. Sign Language Translation (SLT) models have been an actively evolving research topic under computer vision. One of the most challenging aspects in earlier iterations of SLTs was accurately capturing the intricate and constantly changing hand movements and facial expressions characteristic of sign language. newlineHowever, the advent of deep learning models has facilitated significant advancements in the field, particularly in the realm of continuous sign language translation. newlineThe research endeavours to develop a lightweight deep-learning framework newlinespecifically tailored for the translation of Indian Sign Language (ISL) into text and newlineaudio. The proposed framework introduces two collaborative deep-learning components that extract and classify features synergistically. The ISL video sequence serves as the input, which undergoes feature extraction utilizing the Inception V3 architecture, enabling the extraction of features from each frame. Classification models tend to be bulky and intricate, consuming substantial memory space and requiring extended training periods. This challenge has been addressed by introducing a lightweight LSTM model, which effectively utilizes the feature map generated by the Inception model for accurate classification. It is important to note that each sign possesses unique characteristics yet exhibits similar feature maps. The performance of the framework is assessed based on the speed and accuracy achieved in converting the input video into text and audio formats. -
A Framework for Digital Forensics Using Blockchain to Secure Digital Data
Digital forensics (DF) requires evidence integrity and provenance across boundaries of jurisdiction, and blockchain technology is ideal for ensuring that. As part of this paper, we discussed a digital forensic framework designed to help prevent duplication of data and secure digital data. In order to accomplish such forensic capabilities, we provide a block-based forensics framework. Using it, examinations are validated, irreversible, traceable, robust, and demonstrate high levels of confidence among examiners and evidence entities. 2022 IEEE. -
A Framework for Dress Code Monitoring System using Transfer Learning from Pre-Trained YOLOv4 Model
Maintaining a proper dress code in organizations or any environment is very important. It not only imbibes a sense of discipline but also reflects the personality and qualities of people as individuals. To follow this practice, some organizations like educational institutions and a few corporations have made it mandatory for the personnel to maintain proper attire as per their regulations. Manual checks are performed to adhere to the organizations' regulations which becomes tedious and erroneous most of the times. Having an automated system not only saves time but also there is very little scope of mistakes and errors. Taking this into context, the main aim and idea behind the project is to propose a model for detecting the dress code in such workplaces and educational institutions where the attire needs to be regularly monitored. The model detects Business Formals (Blazer, Shirt & Pants) worn by the personnel, for which CNN has been considered, along with YOLOv4, for performing the detection, due to its nature of giving the highest accuracy in comparison to the other object-detection models. Providing the Mean Average Precision of around 81%, it becomes evident that the model performs quite well in performing the detections. 2023 IEEE. -
A Framework for Enhancing Classification in BrainComputer Interface
Over the past twenty years, the various merits of braincomputer interface (BCI) have garnered much recognition in the industry and scientific institutes. An increase in the quality of life is the key benefit of BCI utilization. The majority of the published works are associated with the examination and assessment of classification algorithms due to the ever-increasing interest in electroencephalography-based (EEG) BCIs. Yet, another objective is to offer guidelines that aid the reader in picking the best-suited classification algorithm for a given BCI experiment. For a given BCI system, selecting the best-suited classifier essentially requires an understanding of the features to be utilized, their properties, and their practical uses. As a feature extraction method, the common spatial pattern (CSP) will project multichannel EEG signals into a subspace to highlight the variations between the classes and minimize the similarities. This work has evaluated the efficacy of various classification algorithms like Naive Bayes, k-nearest neighbor classifier, classification and regression tree (CART), and AdaBoost for the BCI framework. Furthermore, the work has offered the proposal for channel selection with recursive feature elimination. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A framework for information security assurance using DNA cryptography
Molecular biology is a branch of life science which plays a pivot role in improving the quality of life whereas Information security is another aspect for social edification, which human beings will never compromise. Both are subjects of high relevance and inevitable for humanity. Thus, an amalgamation of these subjects turns up as an innovation which is beneficial for Information security and storage. The secure transfer of information was of significant concern from ancient civilizations. Various techniques have been proposed from time immemorial to maintain the security of data so that only intended recipient should be able to receive the message other than the sender. newlineThe Information security aspects became prominent with the introduction of the newlineInternet. Regardless of the type of information which varies from a single newlinecharacter to the much-discussed Big Data , it is necessary to ensure secure storage and protection which is a matter of concern.Cryptography is an art by newlineitself and the science of secrecy which protects information from unauthorized newlineaccess. Various techniques have evolved through years of information protection newlinewhich includes Ciphers, Cryptography, Steganography, Biometrics and the most newlinerecent Nano-Cryptography comprising of Quantum Cryptography and DNA Cryptography. newlineDNA cryptography is an emerging and promising field of Information security. Dr. Leonard Adleman s experiment to solve the Hamiltonian Path Problem, which is an NP-complete problem using computational properties of DNA, has newlineredefined the word computing. The emergence of DNA computing marked the beginning of DNA Cryptography.It was a leap forward in the field of security to use biomolecular concepts and the later research followed on DNA encryption gives us new hope of unbreakable algorithms. DNA based encryption schemes work on the principles of DNA computing techniques.Cryptosystems based on DNA got relevance due to bio-computational properties of DNA. -
A framework for integrating nested queries in natural language interfaces to databases
To translate Natural Language (NL) statements into Structured Query Language
(SQL) queries, different methods and systems were proposed in the past. This work presents a framework for automating the translation of Data Requirement
Specifications (DRS) given by enterprise Business Users in NL into SQL queries,
focusing on requirements that result in the generation of nested SQLs. The framework takes the business user’s DRS given in English as input and generates an initial query sketch by employing semantic parsing. This initial sketch is further refined and completed into a well-formed SQL by consulting the Database Schema. It performs the translation by combining NL processing techniques with Query Sketch generation methods and refines it by employing Repair techniques or extends it further. The framework suggests using Lambda expressions for intermediate representation and employs standard operations of Lambda Calculus for performing the required transformations needed for translation. Lambda Context Calculus (LCC) provides the operational semantics and the relevant methods needed in transforming NL statements into SQL, preserving the integrity and compositionality24 of expressions in every step of the translation. Though Lambda Calculus is found to be effective in representing the intermediate expressions and assists in performing the transformations that are needed for translating specific predicates into SQL, its inflexibility in combining parallel computations is a constraint. To represent clauses that are in parallel or are in
pipeline, and to perform the required transformations on the intermediate expressions involving these, more advanced programming constructs are needed. It also adopts functional programming techniques to deal with complex scenarios involving nested queries. This work recommends the use of some advanced language constructs, the Fixed-point Combinators11 and Monad Comprehensions20 for performing the required transformation at the intermediate language level and adopts functional programming techniques for the required syntactic sugar. -
A Framework for Integrating Nested Queries in Natural Language Interfaces to Databases
To translate Natural Language (NL) statements into Structured Query Language (SQL) queries, different methods and systems were proposed in the past. This work presents a framework for automating the translation of Data Requirement Specifications (DRS) given by enterprise Business Users in NL into SQL queries, focusing on requirements that result in the generation of nested SQLs. The framework takes the business user s DRS given in English as input and generates an initial query sketch by employing semantic parsing. This initial sketch is further refined and newlinecompleted into a well-formed SQL by consulting the Database Schema. It performs newlinethe translation by combining NL processing techniques with Query Sketch generation newlinemethods and refines it by employing Repair techniques or extends it further. The newlineframework suggests using Lambda expressions for intermediate representation and newlineemploys standard operations of Lambda Calculus for performing the required newlinetransformations needed for translation. Lambda Context Calculus (LCC) provides the newlineoperational semantics and the relevant methods needed in transforming NL statements newlineinto SQL, preserving the integrity and compositionality24 of expressions in every step of the translation. Though Lambda Calculus is found to be effective in representing the intermediate expressions and assists in performing the transformations that are needed for translating specific predicates into SQL, its inflexibility in combining parallel computations is a constraint. To represent clauses that are in parallel or are in pipeline, and to perform the required transformations on the intermediate expressions involving these, more advanced programming constructs are needed. It also adopts functional programming techniques to deal with complex scenarios involving nested queries. -
A Framework for Integrating the Distributed Hash Table (DHT) with an Enhanced Blooms Filter in MANET
MANET, a self-organizing, infrastructure-less, wireless network is a fast-growing technology in day-to-day life. There is a rapid growth in the area of mobile computing due to the extent of economical and huge availability of wireless devices which leads to the extensive analysis of the mobile ad-hoc network. It consists of the collection of wireless dynamic nodes. Due to this dynamic nature, the routing of packets in the MANET is a complex one. The integration of distributed hash table (DHT) in MANET is performed to enhance the overlay of routing. The node status updating in the centralized hash table creates the storage overhead. The bloom filter is a data structure that is a space-effective randomized one but it allows the false-positive rates. However, this can be able to compensate for the issue of storage overhead in DHT (Distributed hash table). Hence, to overcome the storage overhead occurring in DHT, and reduce the false positives, the Bloom's filter is integrated with the DHT initially. Furthermore, the link stability is measured by the distance among mobile nodes. The optimal node selection should be done for the transmission of packets which is the lacking factor. If it fails to select the optimal path then the removal of malicious nodes may lead to the unwanted entry of nodes into the other clustering groups. Therefore, to solve this problem, the bloom's filter is modified for enhancing the link stability. The novelty of this proposed work is the integration of Bloom's filter with the Distributed Hash Table which provides good security on transmission data by removing false-positive errors and storage overhead 2022,International Journal of Advanced Computer Science and Applications.All Rights Reserved -
A framework for national-level prevention initiatives in Indian schools: A risk reduction approach
India's mental health policies predominantly prioritize treatment and rehabilitation. While acknowledging the significance of youth well-being, the initiatives undertaken are fragmented, lacking comprehensive data on reach and utilization. Mounting evidence supports the preventability of mental illnesses, highlighting the cost-effectiveness of prevention initiatives, particularly within school-based programs. This paper aims to delineate a preventive framework centered on schools, employing the six-step OrigAMI (Origins of Adult Mental Illnesses) model. This model targets modifiable risk factors to stop the development of mental illnesses. Each step of this model is dissected and examined within the context of the school environment, elucidating the unique and influential role that educational institutions can undertake in preventive initiatives in India. In the initial step, the paper identifies modifiable risk factors in children and adolescents that can be addressed within the school environment. The second and third steps involve pinpointing the target demographic and utilizing data from comprehensive reviews of mental health initiatives. The fourth and fifth steps delineate the workforce structure, advocating for task shifting to non-specialists, engaging school stakeholders and parents, and establishing a systematic workforce framework. The final step delves into policy implications, exploring the potential to reduce the prevalence of mental illness by focusing on risk factors with a high Population Attributable Fraction. This section also contrasts the proposed approach in terms of expenditure against the current budget allocations. The paper culminates with a recommendation to integrate these preventive programs into existing healthcare policies, positioning schools as central to these prevention efforts. The integration of prevention programs into healthcare policies aims to reduce prevalence rates and alleviate the burden on the healthcare system. 2024 Elsevier GmbH