Volume 14 | Issue 4 |

 Abstract

The current study sought to investigate the correlation between birth order and aggression in young adults aged 18 to 30 years. A total of 140 participants were chosen through convenience sampling and subsequently divided into two groups, each comprising 70 participants, categorised by first-born birth order and other birth order. The Buss-Perry Aggression Questionnaire was used to measure aggression. It looks at physical aggression, anger, verbal aggression, and hostility. We used Jamovi statistical software to analyse the data we got from an online Google Form. Descriptive statistics revealed that first-born participants exhibited marginally elevated scores across all dimensions of aggression in comparison to participants of other birth orders. Nonetheless, independent samples t-tests indicated that these differences were not statistically significant across any of the subscales or total aggression scores. The findings suggest that birth order does not significantly influence aggression levels among young adults. Although minor variations were observed, they were not statistically significant enough to establish a strong relationship. The study highlights that aggression is likely influenced by broader environmental and social factors rather than birth order alone. Further research is recommended to explore additional variables such as family dynamics and parenting styles.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Birth Order, first born and other birth order (second, third, only), Aggression.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Women's participation in formal financial markets is a key indicator of economic empowerment and inclusive growth. Women have historically been excluded from the investment ecosystem in India due to socio-cultural norms, limited financial literacy, risk aversion, and a lack of financial autonomy. This research paper conducts an in-depth empirical investigation into the multidimensional factors that influence women's investment behaviour in the National Capital Region. This study uses both quantitative and qualitative research methods to examine how social, economic, demographic, and psychological factors interact to influence women's investment decisions. The findings show that, while education and income are important enablers, deeply ingrained cultural norms, family dynamics, and a lack of financial literacy continue to undermine women's confidence in navigating complex financial markets. The study emphasises the interconnectedness of these factors and discusses strategies for policymakers, educators, and financial institutions to promote greater financial inclusion for women. This paper adds to the conversation about gender and finance by providing actionable insights for closing the gender gap in investment behaviour.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women investors, financial literacy, investment behaviour, socio-demographic characteristics, risk aversion, and financial capability

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hybrid Renewable Energy, Solar Power, Wind Energy, Off-Grid Charging System, Portable Power Supply, Arduino Nano, Battery Storage System, Inverter Circuit, Smart Charging Control, Password Protection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The synthetic voice generation technology has reached new heights because of artificial intelligence which has developed at an exceptional pace. The new technology for creating voices helps virtual assistants and accessibility tools work better. It also brings big security risks from two main sources: fake voice recordings and deepfake audio attacks. Scammers can now make realistic voice recordings that sound like real people. This makes it harder to tell if audio content is real or fake. The threats are especially bad for Europe in areas like transactions, identity verification and social engineering. Detection systems currently look at the audio recording to decide if it's real or fake. They work well in some situations. Can't catch fake parts when only some of the audio is changed. This makes traditional systems less reliable in forensic investigations. The reason is that they often don't have real audio to work with. This paper introduces a solution: the Segment Level Synthetic Voice Manipulation Detection system. It looks at signals in short intervals. The system breaks down the audio into parts and checks each one separately using deep learning. It uses Mel-Frequency Cepstral Coefficients and other features, which are then processed by a Convolutional Neural Network model. This produces probability results that show the chance of manipulation.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Segment-Level Detection, Synthetic Voice Detection, Deep Learning, Convolutional Neural Network, Mel-Frequency Cepstral Coefficients, Audio Forensics, Deepfake Audio, Signal Processing, Fraud Detection, Security Monitoring

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design, implementation, and experimental validation of a novel Solar-Based Dynamic Energy Transfer (DET) system for Electric Vehicles (EVs), addressing critical limitations inherent in conventional plug-in charging infrastructure, such as charging downtime, connector degradation, and grid dependency. The proposed system leverages solar energy as its primary power source, thereby enhancing environmental sustainability and reducing reliance on conventional electrical grids. A 12V, 10W solar panel captures solar irradiance, which is subsequently regulated by a solar charge controller and stored in a 12V lead-acid battery, forming a robust, off-grid power reservoir. The core of the DET infrastructure comprises multiple transmission coils embedded within a base station. An Arduino Nano microcontroller serves as the central control unit, orchestrating the sequential activation of these coils. Infrared (IR) sensor modules strategically positioned along the charging track detect the presence and precise location of an EV. Based on these positional inputs, the Arduino activates the corresponding transmission coils via a 4-channel relay module, utilizing high-power TTC5200 NPN transistors and power resistors to manage current demands. This controlled activation strategy optimizes energy transfer efficiency by ensuring power delivery only to the coil directly beneath the vehicle, thereby minimizing quiescent power losses.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dynamic Energy Transfer, Electric Vehicles, Wireless Charging, Solar Energy, Inductive Coupling, Arduino, Renewable Energy, Smart Transportation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Inventory Management, Demand Forecasting, Machine Learning, XGBoost, Retail Analytics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Introduction: Inguinal hernia is a commonly encountered surgical condition, but giant inguinal hernias are rare and usually seen in neglected cases. These hernias gradually increase in size and may extend into the scrotum, leading to discomfort, difficulty in daily activities, and risk of complications like obstruction or strangulation. Methods: We present a case of an elderly male who came with a long-standing swelling in the inguinal region that had progressively increased in size. Clinical examination and ultrasonography were performed to confirm the diagnosis. After routine evaluation, the patient was planned for surgical repair. Results: Examination showed a large inguinoscrotal swelling with partial reducibility and a positive cough impulse. Imaging revealed herniation of bowel loops and omentum. The patient underwent open mesh repair (Lichtenstein hernioplasty). The postoperative period was smooth, with good recovery, relief from symptoms, and no immediate complications. Discussion: Giant inguinal hernias can be challenging due to their size and long duration. Reduction of contents and restoration of abdominal domain require careful surgical planning. Mesh repair is considered the standard treatment due to its strength and low recurrence rate. Conclusion: Even large, long-standing inguinal hernias can be successfully treated with timely surgical intervention. Early diagnosis and proper management play a key role in preventing complications and improving patient quality of life.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Inguinal hernia, Giant hernia, Hernioplasty, Scrotal hernia, Surgical management

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This Paper Presents An Automated Parcel Sorting System Using ESP32, RFID Identification, Dual IR Sensing, And TCS3200 Color Detection To Categorize Parcels Accurately. A Servo-Based Diverter Sorts Items Into Bins, While LEDs And A Buzzer Provide Real-Time Feedback. The System Integrates IoT Monitoring Through Arduino IoT Cloud, Displaying Parcel Counts, Detected Colors, Mismatch Alerts, And System Messages. The Proposed Solution Aims To Improve Sorting Accuracy, Reduce Manual Labor, And Enhance Operational Efficiency In Logistics And Warehouse Environments.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ESP32, RFID, TCS3200, IoT, Color Sorting, Parcel Automation, Arduino IoT Cloud, Servo Motor, IR Sensor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Human-computer interaction has evolved significantly with the advancement of motion sensing technologies, enabling more intuitive and flexible control methods. Traditional computer mice require a flat surface and limit user mobility. This paper presents the design and implementation of a cost-effective air mouse system using an Arduino Leonardo and an MPU6050 motion sensor. The system continuously tracks hand movements by detecting changes in acceleration and orientation. When motion is detected, the Arduino processes the sensor data and translates it into cursor movement on the computer screen using built-in Human Interface Device (HID) functionality. Additional controls such as clicking actions can be implemented using buttons or gesture-based inputs. The system operates in real-time without the need for external drivers and provides a seamless user experience. The use of simple and affordable components makes the system easy to implement, portable, and energy efficient. The proposed system is reliable, low-cost, and suitable for applications such as presentations, gaming, and assistive technologies.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Arduino Leonardo, Bread Board, MPU6050, Buttons, Jumper wires ( male to male, male to female)

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Creative Commons Attribution 4.0 and The Open Definition