Authors: Nagaraju Goshikonda

Abstract: The digitalization of critical infrastructure sectors of the U.S. economy such as energy, transportation, healthcare, and defense has expanded the cyber-attack surface at a rapid pace. The old models of perimeter-based security are no longer effective against complex attacks, like advanced persistent attacks (APTs), insider attacks and AI-assisted cyber-attacks. This paper will suggest AI-based Zero Trust Security Architecture (ZTSA) adapted to secure the critical infrastructure in the United States. The framework incorporates behavioral analytics, federated learning, and adaptive risk scoring, that allow one to continue verification and intelligent response to threats. The predictive and generative AI models are utilized to simulate the attack scenario, improve anomaly detection, and automate policy enforcement. Experimental assessment based on simulated critical infrastructure datasets is shown to have a higher detection rate of 95.8 and a 30% lower rate of false positives than traditional zero-trust systems. The outcomes show that AI-enhanced zero-trust models will be capable of mitigating critical infrastructure in the US to a considerably greater extent in terms of resilience, scalability, and mitigation of threats in real-time.

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Published by: vikaspatanker

Authors: Dipak Kadve, Vaishali Suryawanshi, Aditi Choure, Pratibha Ghodake

Abstract: In recent years, digital streaming platforms have become an integral part of students’ daily routines. Among various forms of online entertainment, anime has gained significant popularity among college students in urban Indian cities, including Pune. While entertainment media can provide relaxation and emotional engagement, concerns are often raised regarding excessive viewing habits and their potential academic implications. The present study explores the relationship between anime consumption patterns and academic productivity among college students in Pune. A structured online questionnaire was administered to 150 respondents across different academic disciplines. The study examined variables such as daily viewing duration, binge-watching behavior, late-night streaming habits, sleep duration, study hours, and self-reported academic performance. The findings suggest that moderate anime consumption does not significantly affect academic productivity. However, extended late-night viewing and frequent binge-watching were associated with reduced study hours and irregular sleep patterns. The study highlights the importance of balanced digital engagement and responsible time management among students.

 

 

Published by: vikaspatanker

Authors: Dr. Snehal Godse, Mr. Prathameshsingh U. Rajput, Prof. Apurva Shende

Abstract: Artificial Intelligence (AI) has evolved from task specific systems to increasingly adaptive and socially responsive agents. As research advances toward Artificial General Intelligence (AGI), a transformative shift is anticipated not only in computational capability but also in human–machine relationships. This study explores the dual nature of AGI—conceptualized as “Syrup and Sword”—wherein emotionally intelligent systems may deepen human closeness while simultaneously introducing existential and psychological risks. Drawing upon attachment theory, alignment research, and human–computer interaction (HCI) scholarship, this paper develops an integrative conceptual framework linking AI capability progression with attachment intensity and societal outcomes. A mixed-method research design is proposed, combining qualitative thematic analysis and quantitative experimental surveys to examine emotional scaling from Narrow AI to AGI-level systems. The study identifies key drivers of attachment such as empathy simulation, memory continuity, adaptive responsiveness, and perceived moral agency. It further analyzes risks including emotional dependency, anthropomorphic projection, manipulation, and value misalignment. The proposed “Syrup vs. Sword Framework” offers a structured lens to evaluate how increasing cognitive and affective sophistication in AGI could produce both enhanced well-being and destabilizing consequences. The findings contribute to interdisciplinary discourse by bridging psychological, ethical, and technical perspectives, emphasizing the necessity of emotionally aware governance in future AGI development. Index Terms—Artificial General Intelligence (AGI), Human–AI Attachment, AI Ethics, Alignment Problem, Emotional AI, Existential Risk, Human–Computer Interaction.

 

 

Published by: vikaspatanker

Authors: Nagalakshmi.S, Kuvvarapu rasmitha, Anbarasan. P

Abstract: Electrical distribution conditions that feed inducting appliances like induction motors and responding industrial devices often have poor power factor due to slow response time to the supply voltage. These conditions of operation cause a high conduction loss, a low stability of the voltage, and a low capacity utilization and energy waste. To help avoid such inefficiencies, a Automatic Power Factor Monitoring and Correction System based on Sequential Load Balancing is introduced as an autonomous driven real-time compensation structure.The suggested research structure incorporates an embedded controller based on Arduino to monitor the acquisition of voltage and current under the control of calibrated sensing modules. Phase difference testing on sensed waves can be used to compute power factor correctly as well as to estimate the amount of reactive compensation that is necessary. Relay-controlled capacitor stages are switched in in sequence when it is detected that there is deviation from target operating limits and hence, the reactive power injection is in an incremental fashion but not abrupt transiently. These simulated balancing ensure that overcompensation is prevented and operational stability is maintained at different loading conditions of variable loads.The measured electrical quantities such as the magnitude of voltage, current level, and post-corrected power factor are displayed on a liquid crystal interface whereas remote monitoring is also facilitated via wireless communication modules which are connected to the serial protocols. This is proved by experimental validation of a correction accuracy of 96.8, and the values of power factor are kept in the range of 0.95 or more after implementation under dynamic load variation. Measured data prove the significant decrease of the line losses and the increase of the voltage regulation. The derived implementation confirms its appropriateness in the industrial and domestic power distribution setting that needs affordable, high quality power factor improvement.

 

Published by: vikaspatanker

Authors: Glecemae Rubino, Adriann R. Dela Peña, Reymark M. Petecio, Allana C. Dimarao, Hearth B. Musketer

Abstract: This study investigated the potential of overripe tomato waste as a sustainable bioenergy source through the use of a Microbial Fuel Cell (MFC) system for electricity generation. An experimental quantitative research design was employed to evaluate the electrical performance of an overripe tomato-based MFC in comparison with a mud-based MFC used as a positive control. Key parameters measured included voltage output, current production, and power density, along with microbial activity indicators such as bacterial growth rate, electron transfer efficiency, and biofilm formation. A total of ten trials were conducted under controlled conditions to ensure data reliability and consistency. Statistical analyses, including frequency distribution, mean computation, and independent sample t-tests at a 0.05 level of significance, were used to determine differences in electricity generation between substrates. Results of the study aim to demonstrate the feasibility of converting organic tomato waste into bioelectricity, supporting sustainable energy development, waste reduction, and low-cost renewable energy solutions, particularly for urban communities such as Davao City.

DOI: https://doi.org/10.5281/zenodo.18875721

Published by: vikaspatanker

Authors: Annie Threse Edwis

Abstract: A CPW antenna with overall dimensions of 30 mm × 25 mm × 2 mm is designed using FR4 as the substrate material. Two rectangular ground planes, each having dimensions of 12 mm × 9.5 mm, are printed on the top surface of the substrate. A signal strip of width 5 mm is used to excite the antenna, and the gap between the signal strip and the ground planes is maintained at 0.5 mm. The proposed antenna structure consists of an elliptical patch connected to the central signal strip along with two rectangular CPW ground planes on the top side of the FR4 substrate. The elliptical patch, which is united with the signal strip, resonates at 6.25 GHz. The designed antenna operates over several wireless communication bands, including 5.15–5.35 GHz (5.2 GHz WLAN), 5.725–5.825 GHz (5.8 GHz WLAN), 5.25–5.85 GHz (5.5 GHz WiMAX), 5.725–5.875 GHz (ISM band), and 5.15–5.85 GHz (5.5 GHz Wi-Fi). The impedance (Z) and VSWR characteristics demonstrate good radiation performance at the resonant frequency of 6.25 GHz. Furthermore, the gain plot of the CPW radiator indicates efficient radiation across various wireless bands. The co-polarization level is significantly higher than the cross-polarization level at 6.25 GHz, confirming that the proposed antenna is suitable for multiple wireless communication applications.

 

 

Published by: vikaspatanker

Authors: Professor Yash Deshmukh, Aishwarya Bhalekar, Vaibhav Dhok, Atharva Gaikwad, Epshita Gaikwad

Abstract: Industrial machines require continuous monitoring to avoid damage due to overcurrent, overheating, or abnormal voltage conditions. This paper presents a GSM-based machine protection system that monitorsmachine parameters and sends real-time alerts to theoperator using SMS. A microcontroller continuously checks sensor values, and when unsafe conditions are detected, the system automatically shuts down the machine through a relay and informs the user remotely. This system improves safety, reduces maintenance cost, and enables remote monitoring of industrial equipment.

Published by: vikaspatanker

Authors: Om Vichare, Aniket Nale, Soham Deolalikar, Siddhant Kamble

Abstract: Maintaining optimal indoor humidity is essential for human comfort, health, and the safety of electronic devices. Conventional humidifiers lack intelligent monitoring and safety mechanisms, and typically require manual operation. This paper presents the design and implementation of a Smart Room Humidifier using the ESP32 microcontroller. The system continuously monitors ambient humidity using a DHT11 sensor and automatically controls a 5 V ultrasonic mist maker through a transistor-driven switching circuit. A water level sensor prevents dry operation, and a buzzer alerts the user when the water level is low. The ESP32’s built-in Wi-Fi module enables web- based remote ON/OFF control, while a 0.96-inch OLED display provides real-time readings of humidity, temperature, water level status, and system state. The system is powered by a 5 V buck converter; regulated 3.3 V for sensor modules is supplied directly by the ESP32. Experimental testing confirms reliable performance, safe operation, and effective humidity control. The system is low-cost and well-suited for indoor domestic applications.

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Published by: vikaspatanker

Authors: Kunal Vishwajit Uke, Shreyas Anil Sonwalkar, Abhishek Avinash Yadav, Krushna Ganesh Vibhute, Prof. Chetna Sharma

Abstract: Industrial automation demands efficient material handling and quality control mechanisms to enhance productivity and reduce operational costs. This paper presents the design and implementation of an automated colour-sorting machine using Arduino microcontroller technology integrated with optical colour sensors. The system employs a conveyor belt mechanism that transports objects through a detection zone where a TCS3200 colour sensor identifies the colour of each item. Based on the detected colour signature, the Arduino controller processes the sensor data and activates corresponding servo motors to divert items into designated collection bins. The proposed system achieves high-speed sorting with accuracy exceeding 95%, significantly reducing manual labour requirements and minimizing classification errors. Experimental results demonstrate the system's effectiveness in sorting multiple colours simultaneously with minimal delay. This automated solution finds applications in food processing, pharmaceutical packaging, recycling industries, and quality control operations where colour-based segregation is essential.

 

 

Published by: vikaspatanker

Authors: Saukhya, Santhosh, Sai Surya, Abdul Rahman Sharikh, Abhijit raj N

Abstract: Auto Go is a tech-enabled autorickshaw rental and fleet management platform designed to address the growing urban transportation challenges in Indian metropolitan cities, with an initial focus on Bengaluru. The project’s core objective is to facilitate affordable and flexible autorickshaw access for independent drivers and small businesses, thereby reducing the financial barrier posed by vehicle ownership and promoting economic opportunity. The service will provide a digital platform — including a website and mobile app — to enable customers to book autorickshaws under daily, weekly, or monthly rental agreements. Additionally, the platform will integrate payment processing, customer support, and vehicle tracking, improving transparency and operational efficiency.

 

 

Published by: vikaspatanker