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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 Abstract

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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 Abstract

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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 Keywords

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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 Keywords

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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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