Journal of Scientific Research and Technology

Public-Private Partnership On National Highways In Karnataka: Opportunities And Challenges

2025-08-01T17:11:08+00:00

Public-Private Partnerships (PPPs) have transformed infrastructure development in India, particularly for National Highways in Karnataka, a state with 4,491 km of critical highway networks. This study evaluates the efficacy of PPP models in enhancing Karnataka’s National Highways under the National Highways Development Project (NHDP), focusing on projects like NH-48 and NH-44. Using a mixed-methods approach, the research analyzes NHAI reports, Karnataka PWD data, and case studies to assess performance metrics such as cost efficiency, completion timelines, traffic flow, and safety improvements. Findings reveal that PPPs have reduced project delays by 20% and improved road quality, but challenges like funding disputes and risk allocation persist. The study proposes a framework for optimizing PPP contracts, emphasizing stakeholder collaboration and innovative financing. By addressing these challenges, PPPs can enhance connectivity, reduce congestion, and align with India’s infrastructure goals. This research offers actionable insights for policymakers and stakeholders to strengthen PPP frameworks, ensuring sustainable and safe highway development in Karnataka.

Detecting Mental Disorders In Social Media Through Emotional Patterns: The Case Of Anorexia And Depression

2025-08-01T17:32:28+00:00

In forensic science, managing evidence is crucial. The evidence recovered from a crime scene is essential to wrapping up the case and making sure the victims get justice. For this reason, it's imperative to protect these bits of evidence from manipulation of any type. The procedure that guarantees the evidence's preservation is the Chain of Custody. If the chain of custody is broken, the evidence may not be allowed to be used in court, which could lead to the case being dropped.

Because forensic evidence management systems are environmentally friendly, it is becoming more and more important to digitize them. These are digital ledgers that are split into blocks and made available to all users on the network. They cryptographically record transactions in a chronological manner. The Linux Foundation created the Hyperledger Fabric, a framework mainly intended for use in corporate applications. The current study aims to create a framework and suggest an algorithm for the digitalization of forensic evidence management systems and the upkeep of the Chain of Custody, drawing on the concepts of Hyperledger Fabric.

Design A Cryptosystem Based Healthcare Cyber Security Model, Contributing With Key Distribution For Different Attack

2025-08-02T07:01:58+00:00

In today's digital era, the healthcare industry is increasingly reliant on electronic systems for storing, transmitting, and processing sensitive patient data. This dependency makes healthcare networks a prime target for various cyber-attacks such as eavesdropping, man-in-the- middle, replay, and unauthorized access. This project presents the design and implementation of a cryptosystem-based healthcare cyber security model that enhances data security through robust encryption techniques combined with a secure key distribution mechanism. The proposed model introduces a dynamic key generation and exchange protocol to protect medical data from different types of attacks, ensuring confidentiality, integrity, and availability. The system leverages both symmetric and asymmetric cryptographic algorithms to provide a hybrid encryption framework that adapts to various network threats. Experimental evaluations demonstrate the effectiveness of the proposed model in preventing common security breaches in healthcare data transmission. The research contributes to the growing field of medical cyber security by offering a scalable and practical solution for protecting sensitive health information in real-time environments.

Critical Insights Of Central Pontine Myelinolysis: Development Of Hypothetical Co-Relation With Hyperparathyroidism, Its Comorbidity

2025-08-04T19:50:37+00:00

Central Pontine Myelinolysis (CPM) is severe demyelinating disorder traditionally linked to rapid correction of hyponatremia. Recent insights recommend as metabolic and endocrine disturbances may also contribute to its development. This review explores the established comorbidities of CPM — including alcoholism, liver disease, and electrolyte imbalances and proposes a hypothetical correlation with hyperparathyroidism. We suggest that CNS injury-induced stress may elevate cortisol levels, disrupting calcium-phosphate balance and stimulating parathyroid hormone (PTH) secretion. This neuroendocrine-inflammatory cascade could exacerbate osmotic stress on pontine tissue and increased secretion of parathyroid hormone increasing the risk of demyelination and hyperparathyroidsm. Understanding this possible link emphasizes the need for broader metabolic monitoring in patients vulnerable to CPM along with hyperparathyrodism. Further studies are warranted to validate this novel hypothesis and to redefine the systemic approach toward CPM prevention and management.

AI Empowered Health Insurance Fraud Detection

2025-08-04T20:09:54+00:00

The project titled aims to develop an advanced system for identifying and preventing fraudulent activities within the health insurance sector. By leveraging the power of artificial intelligence and machine learning algorithms, this system is designed to analyse vast amounts of data from insurance claims, detecting patterns and anomalies indicative of fraudulent behavior. The proposed solution focuses on enhancing the accuracy and efficiency of fraud detection processes, minimizing false positives, and significantly reducing the financial losses incurred by insurance companies. The system also provides a robust framework for continuous learning and adaptation to emerging fraud tactics, ensuring long-term reliability and effectiveness in safeguarding the integrity of health insurance claims.

From Theory To Practice A Study On The Skills Gap In Management Graduates

2025-08-08T17:58:10+00:00

The persistent gap between academic training and industry expectations in management education continues to challenge graduate employability worldwide. While business schools often emphasize theoretical knowledge, employers increasingly demand graduates equipped with practical competencies—particularly in aptitude and reasoning skills such as analytical thinking, problem-solving, and data interpretation. This study investigates the nature and causes of this skills mismatch, cognitive dimensions of employability. Drawing on literature, industry insights, and academic perspectives, the research examines the extent to which current curricula address reasoning-related capabilities and explores industry-academia collaboration in enhancing them.
Using a mixed-methods approach, a study incorporates qualitative interviews with faculty and industry professionals, as well survey data from management students and recent graduates. Findings reveal that aptitude and reasoning are critical yet underdeveloped areas in traditional management programs, largely due to insufficient experiential learning and limited exposure to real-world problem-solving scenarios. The study highlights successful models of collaboration—such as internships, case-based learning, and co-designed curricula—that effectively bridge the skills gap.
The paper concludes by recommending integrative strategies to embed aptitude development within academic frameworks, suggesting that sustainable, structured engagement between academia and industry is essential to produce graduates who is not only knowledgeable, but also reasoning-capable and job-ready.

Water Quality Classification Using SVM And XGboost Method Machine Learning

2025-08-12T14:21:35+00:00

Various pollutants have been endangering water quality over the past decades. As a result, predicting and modeling
water quality have become essential to minimizing water pollution. This research has developed a classification
algorithm to predict the water quality classification (WQC). The WQC is classified based on the water quality index
(WQI) from 7 parameters in a dataset using Support Vector Machine (SVM) and Extreme Gradient Boosting
(XGBoost). The results from the proposed model can accurately classify the water quality based on their features.
The research outcome demonstrated that the XGBoost model performed better, with an accuracy of 94%, compared
to the SVM model, with only a 67% accuracy. Even better, the XGBoost resulted in only 6% misclassification error
compared to SVM, which had 33%. On top of that, XGBoost also obtained consistent superior results from 5-fold
validation with an average accuracy of 90%, while SVM with an average accuracy of 64%. Considering the enhanced
performance, XGBoost is concluded to be better at water quality classification.

Dual Band Microstrip Patch Antenna For Wireless Communication Applications

2025-08-18T07:21:40+00:00

The proposed work investigates the design of dual band microstrip patch antenna for the wireless communication applications. The performance of the proposed antenna is planned to design on a low-cost FR-4substrate material. The designed antenna is expected to be operating at dual frequency bands. The antenna parameters like resonance frequency, return loss, bandwidth, gain and radiation patterns are going to be studied. Simulation and experimental results are going to be analyzed using the 3DEM Mentor Graphics simulation software. The proposed antenna expected to be suitable element for wireless communication applications.

Characterization of Bio-Medical Waste in Kalaburagi City

2025-08-18T09:00:28+00:00

The waste generated in healthcare units and hospital are refer to as Bio- Medical waste it includes waste from operation theatres, surgical waste, syringes, needles, cotton pieces for dressings etc. in the presence study ESIC hospital, Jayadeva Hospital GIMS Hospital. Has been considered as study area in order to characterize the bio-medical waste. To conducted in hospital to quantify the waste, segregate the waste as Red, Yellow, Blue, White. To study the method of handling and ultimate disposal of waste. The study is conducted for three months in 3 hospitals (May, June July) during this period the average quantity of red, yellow, blue, white in ESIC Hospital in 71.51%, 41.13%, 24.73%, 2.08%. Jayadeva Hospital in 30.51%, 14.63% 6.23%, 6.4%. GIMS Hospital in 23.06%, 14.41%, 6.87%, 1.47%. The waste generated in three Hospital in ESIC Hospital in 140-160kg/day in red category, 90-110kg/day in yellow category, 70-90 kg/ day in blue category, 10-15 kg/day in white category. Jayadeva Hospital in 60-80 kg/day in red category, 30-40 kg/day in yellow category, 20-30 kg/day in blue category ,3-5 kg/day in white category. GIMS Hospital in 50-60 kg/day in red category, 40-50 kg/day in yellow category, 30-40 kg/day in blue category, 5-10 kg/day in white category.It is observed that health care, housekeeping personal were not effectively using personal protective wears.

Noise Pollution Monitoring Of Residential Areas In Kalaburagi City

2025-08-18T09:33:56+00:00

Traffic noise is a major problem in the urban and developed cities leading to health and hazardous pollution in the environment. To overcome the characteristic problem of noise pollution, measure of the noise pollution are crucial. Importance should be given to areas like bus stands, business areas (commercial), residential areas, and hospitals zones. The purpose of this research was to investigate the current state of noise pollution in the surrounding environment. Sound levels in Kalaburagi city were found at an avg of 56 dB, which is in the allowable limit, according to the study. This paper represents the participatory sensing and real time monitoring and analysis of noise pollution the kalaburagi city.