Volume 13 | Issue 2 |

 Abstract

Bankruptcy prediction is a critical task in financial risk management, aiding businesses and investors in making informed decisions. This survey explores recent advancements in bankruptcy prediction models using deep learning techniques. Traditional financial models often struggle with high-dimensional, nonlinear financial data, whereas deep learning methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer-based architectures, offer improved accuracy and robustness. We analyze various datasets, feature selection methods, and performance metrics used in bankruptcy prediction studies. The survey highlights key challenges such as data imbalance, feature interpretability, and model generalization. Additionally, we discuss the effectiveness of hybrid approaches that combine deep learning with traditional statistical models for enhanced predictive capabilities. Our findings suggest that deep learning significantly improves bankruptcy prediction accuracy, making it a valuable tool for financial forecasting. Future research directions include explainable AI, transfer learning, and real-time bankruptcy risk assessment.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bankruptcy, Bankruptcy prediction system Classification, machine learning techniques, Credit Card Fraud Detection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India has a long-standing tradition of utilizing medicinal and aromatic plants for treating various ailments, including fever (pyrexia), a common condition characterized by an elevated body temperature and associated symptoms such as lethargy, anorexia, and shivering. Although conventional antipyretic drugs help in temperature regulation, the rise of antibiotic resistance necessitates alternative approaches. Herbal antipyretics offer a promising solution, leveraging natural bioactive compounds to combat fever and associated infections effectively. This review explores the pharmacological potential of medicinal plants such as Neem (Azadirachta indica), Tulsi (Ocimum tenuiflorum), Amla (Phyllanthus emblica), Nirgundi, Ginger (Zingiber officinale), and Baheda (Terminalia bellirica), highlighting their antipyretic, antimicrobial, and immunomodulatory properties. The bioactive constituents, including flavonoids, alkaloids, terpenoids, and polyphenols, play crucial roles in fever reduction through mechanisms such as prostaglandin inhibition, immune modulation, and anti-inflammatory effects. Clinical studies indicate the efficacy of these herbal remedies, demonstrating their potential as safe and cost-effective alternatives to synthetic drugs. Despite their advantages, considerations regarding dosage standardization, herb-drug interactions, and long-term safety remain vital. Future research should focus on elucidating molecular pathways, optimizing formulations, and integrating herbal antipyretics into mainstream healthcare. This study underscores the relevance of traditional herbal medicine in contemporary fever management and its potential to offer sustainable and effective treatment options.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Antipyretics, Anorexia, Aromatic plants, Prostaglandin inhibition, Zingiber officinale

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An Open and Accessible Auction Platform Auction is an innovative mobile application designed to provide a transparent and user-friendly platform for online auctions. It aims to create an accessible marketplace where users can easily buy and sell diverse items using a secure and engaging bidding system. Unlike traditional auction platforms, Auction leverages modern technologies to enhance the user experience. It features a streamlined interface built with Kotlin Compose, ensuring compatibility across a wide range of Android devices. The app utilizes Firebase for its backend infrastructure, providing real-time updates, secure data storage, and robust transaction handling through Firebase Functions. Auction introduces Radianite, a virtual currency for in-app transactions, offering a convenient and secure payment method for bidding and purchasing items. The app also integrates with a real-time currency API to provide accurate dollar values for Radianite, ensuring transparency and familiarity for users. Furthermore, Auction has the potential to incorporate advanced features such as a Geminipowered chatbot for user support and guidance. This would further enhance the user experience and provide a more interactive platform for buyers and sellers. It empowers users to participate in auctions from anywhere, anytime, fostering a vibrant and inclusive online marketplace. The app's scalable architecture and potential for feature expansion position it as a leading platform in the online auction space.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Auction System, Online Bidding, Java Android Development, Firebase Integration, User Authentication, Auction Management, Admin Controls, Wallet System, User-Friendly UI, Auction Item Listing, Real-time Database, Bid Management, Fragment-based Design, E-commerce Auction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the contemporary world, the dilemma of climate change has deeply affected the lives of many individuals. It has evolved as a global menace. Often the terms Climate Change, Climate Crisis, Climate Breakdown, or Global Warming are used interchangeably. According to the United Nations, climate change refers to long-term shifts in temperatures and weather patterns. It is the continuing rise in the global average temperature. Climate change exerts different effects on different regions based on various factors including geographical and territorial formation. Climate Change is massively demolishing the lives and societies, leaving behind the loads of destruction that is unavoidable. Fertile grasslands that once accommodated millions of population are transforming into wastelands The torment of climate change has substantially deteriorated the present environment leading to the expansion of deserts, rise in sea levels, ocean acidification, melting of glaciers etc. These implications of Climate change have largely disrupted the ecological balance causing natural disasters such as droughts, floods, earthquakes, hurricanes and other extreme weather conditions. The outcomes of Climate Change are not only ecological but are largely socio-economic as it poses drastic Human Rights Challenges. One of the profound instances of such challenges is the Climate Induced Migration. This paper is a generous attempt to highlight the misery of climate-induced migration and it's associated human rights violations

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Climate Change , climate-induced, migration

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This comprehensive paper presents an advanced approach to visual identity verification utilizing AlexNet, a pioneering convolutional neural network architecture. We propose a robust system that leverages deep learning techniques for accurate personal authentication through visual data, incorporating multiple innovative improvements to the original architecture. The implementation demonstrates significant improvements in verification accuracy compared to traditional methods, achieving an accuracy rate of 95.8% on our diverse test dataset. Our approach addresses key challenges in identity verification including varying lighting conditions, pose variations, partial occlusions, and presentation attacks. The system's architecture incorporates modified AlexNet layers optimized for identity verification tasks, with enhanced feature extraction capabilities specifically designed for biometric applications. Additionally, we present novel techniques for data augmentation, network optimization, and real-time processing that significantly improve the system's practical applicability. Furthermore, we introduce comprehensive analyses of network architecture variations, investigating the impact of different layer configurations and activation functions on verification performance. Our study encompasses extensive experimentation with various optimization techniques, including adaptive learning rate methods and custom loss functions designed specifically for identity verification tasks. We also present detailed analyses of system performance across diverse demographic groups and environmental conditions, supported by extensive statistical validation. The implementation incorporates advanced security features including liveness detection and anti-spoofing mechanisms, making it suitable for highsecurity applications. Our experimental results, conducted across multiple datasets and environmental conditions, demonstrate the robustness and reliability of our approach in real-world scenarios. Our work also addresses practical deployment considerations including scalability, maintenance requirements, and integration with existing security infrastructure.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AlexNet, Deep Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In contemporary society, the demand for cosmetics has surged, with individuals increasingly utilizing various products to enhance their appearance and maintain a youthful demeanor. The significance of cosmetics in daily life is undeniable, particularly as consumers gravitate towards herbal options, which are perceived to offer reduced side effects and enhanced safety. Among the various aspects of personal care, hair, as an essential component of the human body, serves not only a protective function but also contributes to an individual's aesthetic appeal. This study aims to develop an herbal hair serum suitable for daily application, utilizing a blend of various herbs. The research focuses on evaluating the properties of the cosmetic serum to identify the optimal formulation. Three distinct serum formulations (F1,F2&F3) each varying in excipient concentrations, were created. Comprehensive assessments were conducted, encompassing physical appearance, pH level, homogeneity, viscosity, spreadability, and antifungal activity. Results indicated that the F1 formulation met established standards, exhibiting satisfactory characteristics. The findings of this research underscore the effectiveness of herbal formulation F1 in enhancing hair quality and consistency, suggesting promising avenues for future development in herbal cosmetic products.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Herbal cosmetics, hair serum, formulation, safety, efficacy, daily use

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bryophyllum pinnatum, a medicinal plant found in tropical regions, contains alkaloids, flavonoids, and other bioactive compounds. It is used in traditional medicine for wound healing, hemostasis, and various therapeutic applications, including anti-inflammatory, anticancer, antidiabetic, hepatoprotective, and neuroprotective effects. This review highlights its chemical composition and medicinal benefits.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Scientific Classification, Macroscopical Character, Microscopical Character, Chemical Constituents, Potential Uses Of Bryophyllum Pinnatum, Pharmacological Activity , Nutritional Value Of Bryophyllum Pinnatum, Side Effects, Marketed Formulations.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Human examination of security elements involves a recurring process: creating and implementing a plan and then monitoring and assessing outcomes. These steps try to determine the authenticity of the thing. These activities necessitate knowledge stored either internally (memorized) or externally (supplied by the object). Some claim that the world's knowledge is best suited for thorough examination of primary security elements. Knowledge stored in the mind is not dependable without consistent standardization. Five relevant questions arise from the action cycle. a) How readily can the user discern and comprehend the device's function? b) What actions can be taken? c) Perform the actions? d) Should we examine the outcomes? e) Compare the actual results with the anticipated results. Generic design guidelines are established based on the device's function, strategy implementation, and result assessment. Several initial security aspects are assessed from a human factors perspective. The features include substrate embedded elements such as watermarks and windowed threads, ink additives like iridescent pigments, printed characteristics like intaglio and tiny letters, see-through devices, latent pictures, and post-printed features like iridescent foils. Many current security features are found to not adhere to fundamental ergonomic design principles. Iridescent optically variable devices can meet these needs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Security Document, Inspection lineup, Security authentication devices, Security feature's Design, Ergonomics for Design

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The current study has been undertaken to assess knowledge score regarding Bronchial Asthma and Health-Related Quality of Life among peoples by advanced teaching programme in Gram Mangliya, Indore. The research design used for study was pre- experimental in nature. The tool for study was self-structured knowledge questionnaire which consists of 2 parts-PART- I consisted questions related to Socio-demographic data, PART-II consisted of self -structured knowledge questionnaire to assess knowledge score regarding Bronchial Asthma and Health-Related Quality of Life among peoples. The data was analyzed by using descriptive & inferential statistical methods. The most significant finding was that 29.4% of peoples were having average knowledge regarding Bronchial Asthma and Health-Related Quality of Life whereas 70.6% had fair knowledge after post-test. It was suggested that nurses must educate peoples regarding Bronchial Asthma and Health-Related Quality of Life

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Impact, advanced teaching programme, knowledge & Bronchial Asthma and Health-Related Quality of Life

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper delves into the heart-wrenching narrative of Pecola Breedlove, the eleven-year-old protagonist of Toni Morrison's seminal novel, 'The Bluest Eye'. Set against the backdrop of a racist and oppressive society, Morrison's work masterfully exposes the devastating consequences of internalized racism, family abuse, and communal trauma on the psyche of a young African American girl. Through a critical lens, this research examines the cluster of traumatic experiences that Pecola endures, including relentless ridicule and torment for her appearance, familial abuse, and the suffocating grip of societal expectations. This study argues that these experiences culminate in Pecola's debilitating depression, crippling inferiority complex, and ultimately, her destruction. Morrison's powerful narrative serves as a scathing indictment of the racist and patriarchal systems that perpetuate oppression, stifling the freedom and equality of African Americans. By analyzing Pecola's tragic story, this research sheds light on the long-lasting impact of trauma, the corrosive nature of internalized racism, and the urgent need for collective healing and liberation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

African American, slavery, freedom, equality, identity, sexual abuse, importance of family,

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Creative Commons Attribution 4.0 and The Open Definition