Volume 13 | Issue 4

 Abstract

Fraudulent job ads have grown to be a major problem in online recruiting due to the quick expansion of online employment platforms. We suggest an improved job categorisation system that uses cutting-edge deep learning algorithms to identify fake job ads in order to address this issue. We use a Convolutional Neural Network (CNN2D) to enhance feature extraction and maximise classification performance, building on the usage of transformer-based models such as BERT and RoBERTa. By employing 2D convolutional layers, the CNN2D model efficiently and accurately detects fraudulent job ads by capturing intricate patterns in the dataset. Furthermore, the system's user-friendly interface, which makes use of the Flask framework, allows for easy job posting administration and real-time fraud detection. This enhancement increases the accuracy and expediency of the process of identifying fraudulent job postings.

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 Keywords

Fraudulent Job Postings, Convolutional Neural Network (Cnn2d), Feature Extraction, Real-Time Fraud Detection.

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Early detection and classification of cataracts are crucial for timely medical intervention and vision preservation. Traditional diagnostic methods, such as slit-lamp examinations and fundus imaging, rely heavily on ophthalmologists' expertise, making the process subjective, time-consuming, and resource- intensive. To address these limitations, deep learning-based techniques have emerged as powerful tools for automated cataract detection. In this study, we explore the use of the Inception V3 convolutional neural network (CNN) classifier for cataract detection from fundus images. Inception V3, known for its multi-scale feature extraction capabilities, optimized architecture, and high accuracy in image classification tasks, is trained on a dataset of labeled cataract images. The model undergoes transfer learning and fine-tuning to improve performance on medical image datasets. Experimental results demonstrate that Inception V3 achieves high classification accuracy, outperforming traditional machine learning approaches and other CNN architectures. Furthermore, we analyze the effectiveness of ensemble learning, hybrid CNN- LSTM models, and transfer learning techniques to enhance model robustness and generalizability. The integration of transfer learning, ensemble learning, and hybrid architectures has further improved the effectiveness of cataract classification. While challenges remain in terms of data quality, interpretability, and deployment, ongoing advancements in AI and cloud computing hold the potential to make automated cataract screening accessible globally. The study also highlights challenges such as dataset limitations, image quality variations, and the need for explainable AI in medical applications. Future research directions include the integration of attention mechanisms, real-time deployment in mobile screening applications, and collaboration with clinical experts to refine AI- driven diagnostic systems

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 Keywords

Cataract Detection, Inception V3, Convolution Neural Network, DeepLearning

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This research explores the effect of social media on investment decisions in the stock market, with specific reference to the influence of Facebook and Instagram on investor behavior. Investors have become more dependent on social media, as it has become a go-to source of real-time data, market sentiment, and trends. The research draws on data from surveys undertaken with different respondents to gain a better insight into the connection between social media usage and investment behavior. Implications of the findings are expected to shed light on the influence of social media on investors' decision-making process, specifically regarding risk perception, trust, and the tempo of investment behavior. Through the examination of these dynamics, the study hopes to inform policymakers, educators, and investors on how to best leverage social media to create well-informed and responsible investing behavior. Overall, this study illustrates the increasing importance of digital communication in financial markets and how it may increase and complicate the investment environment.

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 Keywords

Social Media, Stock Market, Investor Behavior, Financial Decision-Making, Online Platforms.

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The old age is an integral part of human life. It is the evening of life. It is unavoidable, undesirable, unwelcome and problem ridden phase of life. But it is really interesting to note that everybody likes to live a long life, but not to be old. It is ironical that however undesirable the old age that is bound to life. Reminiscence therapy for depression consists of recollecting of past life experiences which implicates the principles of cognitive therapy. However there are inherent difficulties in assuming from these studies that reminiscence therapy for depression is an effective treatment with the general adult population. The research design adopted for the study was quasi experimental non-equivalent control group design. The study was conducted at selected Geriatric home, Madurai. The samples selected were 60, of which 30 samples were allotted in the experimental group and the remaining 30 were in the control group. The samples were recognized based on the inclusion criteria and picked up with Non probability - purposive sampling technique. Yesavage geriatric depression scale was used as a tool for data collection after confirming the validity and reliability. Reminiscence therapy was demonstrated to the experimental group only for 21 days in both morning and evening. The data obtained were analysed and interpreted using descriptive and inferential statistics. The comparison of mean post test score of level of depression among geriatrics between experimental and control group using unpaired 't' test revealed that the 't' value was 22.25 which showed a statistical significance at p<0.001 level. It was inferred that the reminiscence therapy was significantly effective to decrease the level of depression among elderly in experimental group. The chi square test revealed that there was significant association between pretest level of depression among elderly with the selected demographic variables like gender(p=0.0102), marital status(p=0.0051) and any medical illness (p=0.0012) in experimental group and control group and remaining was not associated with demographic variables at p < 0.05 level.

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Reminiscence therapy, Effectiveness, Depression, Elderly, Old-age home

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This research paper explores the historical institution of matriliny among the Nairs of the Malabar region in Kerala, India. The Nair Tharavad (matrilineal joint family) system stands as a unique socio-cultural structure that redefined gender roles, property rights, and power dynamics within a patriarchal Indian context. This study examines the origins, development, and eventual decline of the system, offering insights into how gender and power were negotiated and performed in a matrilineal framework. Through archival sources, colonial records, and oral histories, the paper critically analyses the intersection of gender and kinship and its implications for contemporary debates on family, inheritance, and women's agency.

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Nair, Tharavad, Matriliny, Gender, Power, Malabar, Kinship, Inheritance, Colonialism, Marumakkathayam

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Numerous multipurpose perovskite materials have been prepared in recent years as a result of the remarkable versatility of perovskite structure in accommodating various dopant ions. By doping divalent Zr4+ ions into the octahedral positions of lead zirconate-titanate perovskite, we hope to create stable and extremely high dielectric constant lead-based materials for supercapacitors. Due to its intriguing ferroelectric, dielectric, piezoelectric, and other electrical properties, lead titanate based materials have attracted a lot of attention from material scientists.Here in this study, we report synthesis of PbZr0.01Ti0.99O3 material by high temperature solid synthesis technique. The Rietveld refinement of the sample confirms the pure phase of tetragonal structure with space group of P4mm.William son-Hall analysis of the XRD data revels the size of crystallite to be about 50nm and the strain arising from the high firing and intense grinding effect to be 8.54*10-3. The electrical impedance and electrical modulus as a function of ac field was investigated to emphasize on the conduction mechanism in the sample.

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Crystal Structure, Rietveld Refinement, Williamson-Hall Method, Conduction Mechanism.

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Climate change is no longer just about the environment, it has become a serious threat to global peace and security. This article examines how increased temperatures, natural disasters, and loss of resources such as water and land can result in conflict, migration, and instability. Climate change aggravates existing issues in the world, particularly among nations that are already politically unstable, or are facing other challenges. Through the use of actual examples in regions such as the Sahel region, Lake Chad, and Syria, this article shows how environment related problems may result in violence and unrest in the global arena. The article also discusses the way international organizations like the United Nations, African Union, and European Union are starting to think of climate change as a matter of security. Treaties like the Paris Agreement and steps taken by certain nations are instances of this increasing consciousness. Furthermore, this article is particularly concerned with how these issues impact the Global South the most. It demands global action to lower climate threats, promote peace-building, and sustain development. To address these issues, we need to consider climate security as a vital component of international peace efforts.

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climate change, environmental degradation, international security, migration, UN, Global South, security threat

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In educational institutions, traditional communication methods like notice boards and disorganized emails often result in missed opportunities and low event participation. To overcome these limitations, a Centralized Event Management Website is proposed to streamline communication and provide personalized access to event details. This platform uses secure login and responsive design to ensure accessibility across devices, while tailoring event information based on users' academic year, department, and interests. By consolidating updates in a single interface, it improves information dissemination, increases engagement, and reduces communication gaps.

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 Keywords

Event Management, Centralized Communication, Web Portal, Responsive Design, User Authentication, Academic Engagement

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Dry Hand Washing Machine represents an innovative approach to hand hygiene, utilizing a fog-based disinfection system to significantly minimize water consumption while ensuring effective cleaning. This system integrates a water reservoir containing a safe herbal disinfectant, which is transformed into fine fog using a specialized fogging mechanism. The mist uniformly covers the entire surface of the hands within seconds, helping dissolve soap and remove contaminants thoroughly. Compared to traditional hand washing methods, this approach dramatically reduces water usage, making it a more sustainable and eco-conscious solution for hygiene in public and private settings. The machine operates on an Atmega-based controller that enables manual adjustments, including setting the duration of fog exposure for each user. Additionally, the incorporation of solar power enhances energy efficiency and supports autonomous operation. IoT integration allows real-time monitoring and tracking of sanitizer levels and system performance. This smart, water-efficient disinfection method promotes environmental sustainability while improving hygiene standards and public health outcomes.

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Dry Hand Washing, Fog Dispersion, Water Conservation, Hand Hygiene, IoT, Solar Power, Eco-Friendly, Automated Sanitization.

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This project presentation the design, development, and implementation of "AUTONOMOUS RETAIL CART WITH SMART BILLING AND FOLLOW ME FUNCTIONLITY"equipped with IoT capabilities for enhanced control and functionality. The primary objective of the proposed system is to create interaction between humans and robots, facilitating effortless item retrieval while adapting to dynamic environmental conditions. The robot's architecture comprises state-of-the-art hardware components including sensors, actuators, and processing units, seamlessly integrated with IoT modules for real-time communication and control. Advanced computer vision algorithms enable the robot to recognize and track human movements, ensuring precise following behavior even in crowded or complex environments. The IoT integration enables remote control and monitoring of the robot's operations, providing users with the flexibility to initiate and customize item retrieval tasks through web or mobile interfaces. Additionally, the system incorporates machine learning techniques for personalized item recommendations based on user preferences and historical data. Furthermore, the paper discusses the implementation challenges and the strategies employed to overcome them, including sensor fusion techniques for robust perception, efficient path planning algorithms for obstacle avoidance, and secure communication protocols for IoT connectivity. Through experimental validation in real-world scenarios, the effectiveness and reliability of the proposed human-following robot system are demonstrated.

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Microcontroller: This acts as the brain of the system and processes the data received from the sensor. You can program the microcontroller to carry out specific functionalities. The most commonly used microcontrollers are Arduino, Uno & Raspberry Pi Sensors: These are electrical devices that can monitor specific values real- time. For example, DHT (Digital Humidity and Temperature) sensor tracks the temperature and humidity differences in the environment real time and send the data to t

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The stability of a system is basically regionalized networks, also known as micro grids, must be able to operate independently by cutting off their connection to the main grid in order for a system to stay stable. Customers' reliability can be raised by providing a more robust power supply. Due to reversed energy flow from distributed generator units, regional fluctuations, temporary micro grid modes, significant frequency discrepancies in electrically isolated mode operation, as well as financial and supply demand uncertainties, consistency, dependability, and security are in fact with micro grids In order for a system to remain stable, regionalized networks known as micro grids must be able to function independently by cutting off their connection to the main grid. By offering a stronger power supply, the dependability of consumers can be increased.

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interlinking converter ,distributed generators, bidirectional power flow, and hybrid micro grids (HMGs),and some related terms

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Wireless Power Transfer (WPT) has proven to be a revolutionary technology for electric vehicle (EV) charging, allowing contactless and efficient energy transfer. This paper reports the design and development of a better WPT system using a high-frequency inverter and resonant inductive coupling to deliver higher power transfer efficiency. A MATLAB/Simulink model is created using source-side and vehicle-side compensation networks, rectifiers, and battery charging logic. Performance of the system is analyzed over a range of different coil separations by varying mutual inductance values while holding coil parameters steady. Contrary to traditional anticipation that power transmission drops off as distance increases, simulation yields only a slight gain in transmitted power at larger separations. This aberrant behavior can be ascribed to the intrinsic characteristic of the resonant inductive coupling circuit that dynamically varies its operation as per variations in coupling strength while providing high energy transfer via tuned resonance at high frequency. The simulated model of this design reveals trustworthy performance, stable SOC process, and high efficiency, hence qualifies as an excellent candidate for practical EV wireless charging applications.

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 Keywords

Electric Vehicles(EV),Inductive Coupling, Wireless Charging, Efficiency, Wireless Power Transfer(WPT) ,MATLAB

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 Abstract

Effect of earthquake can be very hazardous to the structure influenced by these forces. There are many traditional methods for protection of structure against earthquake effects. But there are some disadvantages in these methods. Increasing strength and stiffness are some of the traditional methods. But they lead to higher sections and result in uneconomic design. To overcome these disadvantages associated with the traditional method, many vibration-control measures, called structural control, have been studied and remarkable advances in this respect have been made over recent years. This paper describes the effect of use of steel bracing, dampers, base isolator (lead rubber bearing), combination of steel bracing with dampers and the combination of base isolator with steel bracing in a structure subjected to earthquake motion. The structure is designed in ETABS 2016 and then bracings, dampers, base isolator and some combinations are applied respectively in 6 different models and results are compared. Force of ground motion that is earthquake force is applied to structure by using seismic coefficient method. Base isolated structure gives improved performance against seismic vibrations than conventional structure. The essential characteristics of base isolation system are isolation, energy dissipation, and restoring mechanism. It is shown that under design conditions, all base isolators can significantly reduce the acceleration transmitted to superstructure. Bracing and dampers are also useful reduction of storey drift and base shear.

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RCC, Bracings, Dampers, Base Isolators, Seismic Coefficient Method, Storey Displacement, Storey Drift, Base Shear, Lead Rubber Bearing, Time Period.

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Retail businesses increasingly require real-time, digital solutions to manage inventory, sales, and customer interactions efficiently. This paper introduces Smart Shop Tracker, an advanced retail shop management application developed using Flutter and Supabase. The system provides features such as inventory control, sales tracking, billing generation, and real-time data updates. With Supabase's scalable backend and Flutter's cross-platform capabilities, the application offers an efficient and modern approach to shop management for small and medium-sized businesses.

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Flutter, Supabase, Smart Shop Tracker, Retail Management System, Cross-Platform App, Real-Time Sync, Backend-as-a-Service, Inventory System.

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Goods and Services Tax (GST) has been one of the most groundbreaking tax reforms implemented in India to simplify and introduce consolidation in the Indian indirect tax regime. The present study was aimed at analyzing consumers' awareness, consumers' attitudes, and consumer satisfaction levels towards GST among consumers located in Coimbatore. By using systematic questionnaires and statistical instruments such as percentages, Likert scale, and rank analysis, the research sets the level of consumer awareness, issues confronted by them, and the effects of GST on their buying decision and cost of living.

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GST, Consumer Awareness, Tax Perception, Indirect Tax, Coimbatore.

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This literature survey explores the evolution of credit information sharing, credit information bureaus in contemporary financial systems that support well-informed lending choices and improve credit market efficiency, and their effects on borrowers. The research looks at credit information exchange and credit bureaus in India and other nations. The results demonstrate the growing significance of credit information bureaus as a result of the widespread use of credit reports. Employers use it to find information about a candidate's credit history, and insurance companies, car manufacturers, landlords, and employers use it to assess a client's credit worthiness. Therefore, it is evident that the current financial system depends on the exchange of credit information. The results show that for high-quality borrowers, exchanging credit information lowers loan duration and the interest rate spread. It was discovered that credit information bureaus had a favourable and substantial effect on banks' credit performance, globally.

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Credit Information Bureaus, Credit Information Sharing, Credit Score, Banks

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Surrogacy represents a complex intersection of law, ethics, and human desire. As advancements in assisted reproductive technologies (ART) expand the possibilities of family creation, the practice of surrogacy continues to provoke profound questions about autonomy, consent, commodification, and trans-national justice. This paper explores the evolving legal landscapes and ethical controversies surrounding surrogacy, drawing on comparative perspectives from jurisdictions such as the United States, United Kingdom, India, and Ukraine. It examines the tension between commercial and altruistic models, the role of consent and economically asymmetrical arrangements, and the implications of cross-border surrogacy on citizenship, parentage, and regulation. Emphasising the need for coherent and rights based legal framework. The paper argues that ethical surrogacy must prioritise the dignity and agency of all parties involved - specially the surrogate and the child -while recognising the legitimacy of diverse family building aspirations. This paper delves into the various ethical and legal challenges surrounding surrogacy, with a focus on international and domestic perspective. It examines regulation of surrogacy, the ethical concerns it raises, the legal rights of all the parties involved, and the complexities in managing cross-border arrangements. Additionally, the research delves into the issue of exploitation, the commodification of reproduction and the need for international legal consistency that regulate surrogacy procedures. This paper has tried to examine surrogacy through a dual lens: a mechanism for reproductive empowerment and as a practice vulnerable to exploitation. It interrogates the normative framework that governments across different legal systems, evaluate the ethical implications of divergent regulatory models and considers the rights and interest of all stakeholders, including the surrogate intended parents and children. Thus, this paper seeks to illuminate the necessity for legal harmonisation and ethical clarity in the governance of surrogacy, specially in an era, defined by globalisation and technological advancements. The research ultimately advocates for internationally harmonised legal standards, grounded in reproductive justice, human rights, and informed consent. The study concludes with recommendations for reform in both ethical and legal frameworks that will make it safe and secure for the parties involved.

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 Keywords

'Surrogacy', 'Legal', 'Ethical', 'Cross-Border', 'Altruistic', 'Surrogate',

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Surface plasmon resonance (SPR) sensors offer a powerful tool for label-free and real-time monitoring of biomolecular interactions and to detect very low concentrations of chemical substances. Sensitivity of these sensors can be enhanced using thin metal films for the generation of surface plasmons. Based on the thickness and quality of the metal films, minute changes in the refractive index corresponding to biochemical events can be detected. Current study focuses on the biochemical sensitivity of glucose molecules on the thin film based SPR sensors. Copper was taken as the base metallic material for the preparation of thin film for generation of surface plasmons. The nature of SPR response of this metallic film was analysed by wavelength scanning method and for various thickness. Then its sensitivity to glucose molecule was studied by simulating a glucose solution environment above the metallic film. The SPR response was recorded for change in the refractive index of the order of 0.001. By optimizing the thickness and wavelength of excitation radiation, a very high sensitivity to glucose was obtained for copper thin film based SPR sensors.

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 Keywords

Sensitivity, Surface plasmon resonance, copper thin film, biochemical sensor

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Biomedical imaging is pivotal in diagnostics, treatment planning, and medical research. However, the quality of biomedical images is often compromised due to various sources of noise during acquisition. This paper proposes an AI-driven denoising framework aimed at enhancing biomedical image quality. Leveraging deep learning techniques, particularly convolutional neural networks (CNNs), the proposed method effectively suppresses noise while preserving structural details crucial for clinical interpretation. Experimental results demonstrate significant improvements in image quality metrics such as PSNR and SSIM, highlighting the framework's potential for integration into clinical workflows.

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Biomedical Image Denoising, Deep Learning, CNN, PSNR, SSIM, Medical Imaging, Flask Web App, RealESRGAN, Noise Classification.

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This paper explores the legal framework, applications, and challenges associated with electronic signatures (e-signatures) in India. It examines the provisions of the Information Technology Act, 2000, which grants legal recognition to e-signatures and discusses the role of Certifying Authorities in ensuring their security and authenticity. The paper highlights the different types of e-signatures, including simple electronic signatures (SES), digital signatures, and advanced electronic signatures (AES), and their use across various sectors such as government, finance, and healthcare. Additionally, the study compares India's e-signature laws with those of international jurisdictions like the United States and the European Union. The paper concludes with recommendations for improving infrastructure, streamlining regulations, expanding legal recognition, and promoting public awareness to enhance the adoption of e-signatures in India. With the growth of digital transactions, e-signatures are poised to become a crucial tool in the country's digital transformation.

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Creative Commons Attribution 4.0 and The Open Definition

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Electronic Signatures, Information Technology Act, Certifying Authorities, Digital Signatures, Legal

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Creative Commons Attribution 4.0 and The Open Definition