Category Archives: Uncategorized

The Impact of Solar Energy System on Environmental and Social Sustainability

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Authors: Abdul Waris Farid, Mohammad Naser Rasuli, Ghulam Hussain.R

Abstract: Energy production and technical efficiency are important aspects of energy systems, they should not be used to determine their sustainability of solar energy systems. The study combines environmental aspects of solar PV systems' life cycles with social aspects to explore their environmental and social sustainability impacts. Three different PV technologies—monocrystalline silicon, multicrystalline silicon, cadmium telluride—are analyzed, and the energy yield, module efficiency, greenhouse-gas emissions, energy payback time, and social aspects like employment, energy access, community benefits, and social acceptance are considered. An AHP-based framework is still maintained to highlight that on how the various sustainability dimensions can be incorporated into the PV assessment. The illustrative results show that PV technologies have various electrical and environmental features, and social outcomes are highly sensitive to project site settings and deployment environment, as well as community context. The paper emphasizes on the importance of integrated assessment for environmental and social sustainability in the planning of solar energy systems.

DOI: https://doi.org/10.5281/zenodo.23180622

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Machine Learning- Assigned Numerical Optimization For Complex Nonlinear Systems

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Authors: Pushpendra Kumar Sharma, J. Indra Kumari

Abstract: Finding missing persons is a challenging task that often requires significant time, manual investigation, and coordination between authorities and the public. This paper presents an AI-assisted missing-person identification system that uses face recognition and machine learning to support the search and identification process. The proposed system allows authorized personnel to register missing-person cases by storing details such as name, age, contact information, location, and photographs in a centralized database. The system also provides a user interface through which the public can submit photographs of unidentified or potentially missing persons along with relevant information. The submitted images are processed and compared with the registered missing-person photographs using facial feature matching techniques. When a suitable match is identified, the system provides the corresponding case information and supports notification to the concerned user or authority. The application is implemented using Python, PyQt5, PostgreSQL, and machine learning-based face recognition techniques, providing an integrated platform for case management, image matching, and search assistance. The proposed system aims to reduce manual effort, improve the speed of image-based identification, and support police and public participation in locating missing persons.

DOI: http://doi.org/10.5281/zenodo.23157635

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A Study On The Effectiveness Of Recruitment Metrics In The IT Sector In Delhi NCR

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Authors: Monika Jaiswal

Abstract: The present study examines the effectiveness of recruitment metrics in the IT sector in Delhi NCR, focusing on their role in improving hiring efficiency, recruitment decisions, quality of hire, consistent recruitment practices, and employee retention. Recruitment metrics such as time to recruit, quality of recruitment, cost per recruitment, offer acceptance ratio, and employee retention provide organisations with measurable information for evaluating recruitment performance. A quantitative research approach was adopted using a descriptive and analytical research design. Primary data were collected through a structured questionnaire using a five-point Likert scale from 450 respondents associated with the IT sector in Delhi NCR. The collected data were analysed using SPSS and Microsoft Excel through frequency, percentage, mean, standard deviation, ANOVA, regression coefficients, Spearman’s rho, and Chi-square analysis. The findings indicate that quality of recruitment was considered the most important recruitment metric by 153 respondents, followed by time to recruit with 117 respondents. Hiring efficiency recorded the highest mean score of 3.97, while quality-of-hire recorded a mean of 3.94. The ANOVA results showed a statistically significant model (F = 26.393, p = 0.002), and all four examined predictors demonstrated significant positive relationships with recruitment effectiveness. The study concludes that systematic application of recruitment metrics can strengthen recruitment efficiency, quality, consistency, and employee retention in the IT sector in Delhi NCR

DOI: http://doi.org/10.5281/zenodo.23121148

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A Hybrid Autoencoder–XGBoost Framework for Proactive Cloud Security and Vulnerability Detection

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Authors: Karupothu Bharath, Assistant Professor T Swapna Sridevi

Abstract: Cloud computing has become a fundamental part of modern digital infrastructure, enabling organizations to deploy applications, store data, and deliver services across highly distributed environments. However, the dynamic nature of cloud systems also creates complex security challenges, including abnormal network activity, unauthorized access, misconfigurations, and emerging vulnerabilities. Traditional security mechanisms often depend on predefined rules and known attack patterns, making them less effective when dealing with previously unseen or continuously evolving threats. This paper presents a machine learning-based approach for strengthening cloud security by combining anomaly detection and vulnerability classification. The proposed framework uses an Autoencoder to identify unusual patterns in cloud-related data and XGBoost to classify detected security events and potential vulnerabilities. The system processes security-relevant information such as network traffic, system logs, user activity, and historical vulnerability records through data preprocessing and feature extraction stages before applying the machine learning models. By combining unsupervised anomaly detection with supervised classification, the framework is designed to provide a more adaptive approach to identifying both familiar and potentially unknown security threats. The proposed solution is implemented as a web-based security framework using Python and Django, providing mechanisms for data management, model evaluation, prediction, and security monitoring. It is intended to reduce dependence on manual analysis while supporting faster identification of suspicious activities and potential vulnerabilities. The framework also provides a foundation for continuous model improvement as new security data becomes available. Overall, the proposed approach demonstrates how machine learning can be integrated into cloud security workflows to support proactive vulnerability detection and improve the adaptability of security monitoring in distributed environments.

DOI: http://doi.org/10.61137/ijsret.vol.12.issue5.153

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AI-Driven Facial Image Matching Framework for Missing Person Identification and Search Assistance

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Authors: Pilli Satya Sri, M Sujana Priya Darshini

Abstract: Finding missing persons is a challenging task that often requires significant time, manual investigation, and coordination between authorities and the public. This paper presents an AI-assisted missing-person identification system that uses face recognition and machine learning to support the search and identification process. The proposed system allows authorized personnel to register missing-person cases by storing details such as name, age, contact information, location, and photographs in a centralized database. The system also provides a user interface through which the public can submit photographs of unidentified or potentially missing persons along with relevant information. The submitted images are processed and compared with the registered missing-person photographs using facial feature matching techniques. When a suitable match is identified, the system provides the corresponding case information and supports notification to the concerned user or authority. The application is implemented using Python, PyQt5, PostgreSQL, and machine learning-based face recognition techniques, providing an integrated platform for case management, image matching, and search assistance. The proposed system aims to reduce manual effort, improve the speed of image-based identification, and support police and public participation in locating missing persons.

DOI: http://doi.org/10.61137/ijsret.vol.12.issue5.152

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Understanding The Climate Sensitive Vernacular Architecture Of Palle Chuwdu Middelu In Ramanapalle-village In Kadapa Division A.P, India

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Authors: Prof. Eswara Rao. P, Dr. Viswanadh Kumar. G

Abstract: Vernacular architecture and climate are engaged in a happy marriage in any indigenously developed settlement. We documented and analyzed a vernacular Palle or village settlement such as Ramanapalli, Chennur which are located in tropical zone of hot and semi-arid climatic Kadapa region of Andhra Pradesh. Palle is a rural settlement in Kadapa district of Rayalaseema, India. It is particularly significant for architectural studies because it has been documented as an example of climate-sensitive vernacular architecture in the Rayalaseema region. The Palle form and structure come from many years of evolution and sharing knowledge. This shows how different physical and non-physical forces like weather, land, religion, culture, money, old building methods, and how people organize themselves have shaped them. These are made up of small groups of homes with thick walls, heavy roofs, small windows, and narrow streets. In villages like Chennur, Ramanapalle, and Rachinayapalle, there are different types of houses, known locally as ‘Chowda or Dante Middelu’. The designs of these houses are usually rectangular or square, built using traditional methods that take into account the local climate. They are well suited to meet the everyday needs of the people living there. The people living in these houses adjust their daily activities to fit the natural qualities of the space around them. The house is designed and built in a way that responds to the hot and dry climate. This type of design is a form of passive architecture that uses local materials, thick walls, small windows, traditional flat roof with high thermal mass, and small vents near the roof but below it. These thick walls and heavy roof help absorb and slow down the transfer of heat. The small windows are placed carefully to reduce the amount of direct sunlight entering. However, the 'House form of Chowda Middelu' in Kadapa district is vanishing because of various reasons in recent years. Previously, this type of architecture and the way people lived were very responsive to the climate. But now, these traditional designs and habits are slowly changing into ones that don't take the climate or local surroundings into account. This research suggests the need for a set of guidelines that can help balance modern development with the traditional building methods used in the area.

DOI: http://doi.org/10.5281/zenodo.23118495

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Coventry University Students’ Perceptions of Factors That Influenced Them to Make Healthy or Unhealthy Dietary Choices

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Authors: Mayanja Shafique

Abstract: The study aimed at exploring Coventry University students’ perceptions of factors that influenced them to make healthy or unhealthy dietary choices. A qualitative approach was used to explore students’ perceptions of factors that influenced their dietary choices. Methods and Analysis- Five participants all Coventry University students were recruited for this study using purposive sampling method. One to one semi-structured interviews were conducted to explore students’ perceptions of factors influencing their dietary choices. Students were interviewed using open-ended questions to capture a broader perspective of the phenomena of interest. Interviews were manually transcribed, and an inductive thematic analytical method was used to analyse data which lead to the identification of three major themes. Results- The results indicate that three major themes emerged which included concept and perspectives of healthy and unhealthy dietary choices, perceptions of factors influencing students’ dietary choices and solutions to healthier choices. Concepts and perspectives indicated that students understood the meaning of healthy and unhealthy dietary choices as well as expressing how they understood the concepts. The students also expressed their perceptions of factors that influenced them to make dietary choices which includes socio-economic, lifestyle factors, social and community networks and environmental factors. These include among cost, Time, knowledge, health, Availability, Accessibility, location and weather changes. However, the most influential factors were cost, time, family and health. Possible recommendations were suggested to promote healthier choices including proper planning, advertisement of healthier foods, Eating when necessary and personal responsibility.

DOI: https://doi.org/10.5281/zenodo.23117855

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Impact Of Exercise Interventions On Clinical Outcomes In Patients With Comorbid Chronic Obstructive Pulmonary Disease And Type 2 Diabetes Mellitus: A Systematic Review

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Authors: Dr. B.R. Shaalini, Dr. K. Raja Senthil, Dr. E. Prema

Abstract: Background-Chronic Obstructive Pulmonary Disease (COPD) and Type 2 Diabetes Mellitus (T2DM) frequently coexist because of shared risk factors, including ageing, smoking, obesity, physical inactivity, and systemic inflammation. Their coexistence contributes to impaired pulmonary function, poor glycaemic control, reduced exercise capacity, diminished quality of life, and increased morbidity. Although exercise rehabilitation is recommended for both conditions individually, evidence regarding its effectiveness in patients with both COPD and T2DM has not been comprehensively synthesised. Objective- To systematically evaluate the effects of exercise interventions on clinical outcomes in adults with comorbid COPD and Type 2 Diabetes Mellitus. Methods- This systematic review was conducted according to the PRISMA 2020 guidelines. Electronic databases including PubMed/MEDLINE, Scopus, Embase, Web of Science, Cochrane Library-PEDro, and Google Scholar were searched for studies published between January 2015 and June 2026. Randomized controlled trials, controlled clinical trials, and prospective cohort studies evaluating structured exercise interventions in adults with comorbid COPD and T2DM were included. Methodological quality was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool and ROBINS-I. Due to clinical and methodological heterogeneity, a narrative synthesis was performed. Results- Twenty-five studies met the eligibility criteria. Exercise interventions, including aerobic training, resistance training, combined aerobic-resistance exercise, pulmonary rehabilitation, inspiratory muscle training, and high-intensity interval training, demonstrated consistent improvements in exercise capacity, pulmonary function, glycaemic control, respiratory muscle strength, dyspnoea, inflammatory markers, and health-related quality of life. Combined aerobic and resistance exercise delivered within pulmonary rehabilitation programmes showed the most consistent overall clinical benefits. Exercise interventions were generally safe and well tolerated, with no serious exercise-related adverse events reported. Conclusion- Current evidence supports structured exercise rehabilitation as a safe and effective non- pharmacological intervention for individuals with comorbid COPD and T2DM. Combined aerobic and resistance exercise within pulmonary rehabilitation appears to provide the greatest clinical benefit. However, larger multicentre randomized controlled trials with standardized exercise protocols and longer follow-up are needed to strengthen the evidence base.

DOI: http://doi.org/10.5281/zenodo.23102859

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Performance Analysis and Optimization of Augmented Reality Applications on Mobile Platforms Using Flutter

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Authors: Harsh Sharma, Dr. Akshya Bhardwaj

Abstract: Delivering responsive augmented reality (AR) experiences on mobile devices requires maintaining high rendering performance while operating within the constraints of limited processing power, memory, and battery resources. This study introduces a benchmarking framework developed with Flutter that evaluates the runtime performance of AR applications using Google ARCore on a physical Android device. The proposed framework continuously records important runtime metrics, including frame rate, frame time, CPU utilisation, memory consumption, estimated power usage, and motion-to-photon (MTP) latency during live AR sessions. Six optimisation techniques—distance-based level of detail, visibility control for distant objects, adaptive rendering quality, lazy asset loading, background-isolate data export, and batched platform metric collection—can be enabled independently to examine their individual and combined impact through controlled A/B experiments. Performance evaluation was conducted on a Realme RMX5070 smartphone running Android 16 under identical environmental conditions using a Release build. Experimental results demonstrate that enabling all optimisation strategies increased the average frame rate from 92.94 FPS to 103.27 FPS, representing an improvement of approximately 11.1%. Average memory usage decreased from 286.5 MB to 267.7 MB, while mean UI frame time was reduced by 9.4%. Among the evaluated techniques, adaptive quality adjustment produced the largest individual improvement in rendering performance. CPU utilisation remained consistently close to full capacity throughout all experiments, whereas GPU utilisation metrics were unavailable because of platform restrictions. The proposed benchmarking framework offers a reproducible methodology for analysing Flutter-based mobile AR applications and provides a practical foundation for future optimisation research across different devices and AR platforms.

DOI: https://doi.org/10.5281/zenodo.23102184

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Gender-Based Comparison Of Perceived Stress Among Employees Of Different Departments In An Engineering College

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Authors: Dr. Richa Ojha, Dr. Kamla Tiwari

Abstract: The purpose of the study was to compare the stress levels of male and female among different departments of an engineering college. A total number of 179 employees both male and female in which 28 from polytechnic (18 male and 10 female). 63 from engineering (36 male and 27 female), 52 from management (27 male and 25 female), and 36 from science & technology (7 male and 29 female) have been included in the study. All males and females who were selected for the study were in the age group of 20 years to 60 years. The results of the study shows that no significant difference can be found conclusively in perceived stress levels found across gender or college type. Although minor variations were observed, particularly a slightly higher vulnerability among female teachers, however, the overall pattern indicates a uniformly moderate level of stress among teachers

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