Volume 14 | Issue 3 |

 Abstract

Buddhism includes an analysis of human psychology, emotion, cognition, behavior and motivation along with therapeutic practices. Buddhist psychology is embedded within the greater Buddhist ethical and philosophical system, and its psychological terminology is colored by ethical overtones. Buddhist psychology has two therapeutic goals: the healthy and virtuous life of a householder (samacariya, "harmonious living") and the ultimate goal of nirvana, the total cessation of dissatisfaction and suffering (dukkha). A central feature of Buddhist psychology is its methodology which is based on personal experience through introspection and phenomenological self-observation. According to the Buddha while initially unreliable, one's mind can be trained, calmed and cultivated so as to make introspection a refined and reliable method. This methodology is the foundation for the personal insight into the nature of the mind which Buddha said to have achieved. While introspection is a key aspect of the Buddhist method; observation of a person's behaviour is also important. Finally, In the Buddhist psychological view, looking carefully into one's own heart will reveal the source of pain. The experiential process can understand the changes of every human moment. According to the Buddhist psychology, we can distinguish the relation between the inner and outer self, to abandon fantasy and the delusion, and to see reality with purified mind.

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 Keywords

psychology, cognition, therapeutic, phenomenology, introspection.

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Road accidents caused by potholes, debris, stalled vehicles and unmarked speed breakers remain a significant challenge for road safety worldwide. Traditional navigation systems mainly depend on manual reporting and do not provide automated hazard detection in real time. This paper presents RoadWatch, an AI-driven road hazard detection and real-time alert system implemented through a web-based application. The proposed system uses computer vision techniques to analyze video streams captured from vehicle dashcams or connected cameras to automatically detect road hazards such as potholes, debris and stalled vehicles. Deep learning models such as YOLOv8 are used for object detection while OpenCV is used for frame preprocessing and feature extraction. The system integrates GPS and sensor data to accurately identify the geographic location of hazards and display them on an interactive web dashboard. To ensure user privacy, the platform automatically blurs faces and vehicle license plates before storing or transmitting visual data. Hazard information is securely uploaded to cloud servers and visualized through the web application, where drivers, authorities and vehicle companies can monitor hazard alerts, heatmaps and safety analytics. Experimental evaluation shows that the system achieves approximately 85% detection accuracy, enabling efficient real-time hazard alerts and improved road safety monitoring. The proposed web-based platform creates a unified ecosystem that connects drivers, vehicles and authorities to support safer and smarter transportation infrastructure.

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 Keywords

Road Hazard Detection, Computer Vision, YOLOv8, Edge AI, Web Application, Road Safety

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Students spend more time online because social media sites use algorithms to show them content that is relevant to them. This study examines the impact of algorithm-driven media exposure on academic self-regulation and psychological well-being among students aged 18 to 25 in Navi Mumbai. The survey, which was done with Google Forms, had about 100-110 students take part. The study found that students who use social media sites like YouTube and Instagram more often have mood swings, put things off, and get distracted. Many students concurred that using social media excessively interferes with their ability to focus and study. The research indicates that algorithm-driven content significantly affects students' academic concentration and mental well-being. To keep up with academic discipline and emotional health, it's important to use social media in a balanced and responsible way.

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 Keywords

Addiction to social media, bad use of social media, content driven by algorithms, mental health, anxiety and depression, digital literacy, and teenage health.

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The purpose of the present investigation was to find out the effects of ladder training on agility, explosive power and speed among college men. To achieve the purpose of this study, twenty-four men students studying in St. Johns College, Palayamkottai, Tirunelveli were selected randomly as participants. The participants were divided into two groups namely ladder training (experimental) group and control group of twelve (n=12) participants each. The experimental group underwent ladder training for six weeks of three sessions per week. The second group acted as control, which was not engaged in any special activities other than their regular curricular activities during the period of training. Among the physical variables the following variables was selected as criterion variables namely agility, and explosive power. All the participants were tested on selected criterion variables prior to and immediately after the training period. Agility, explosive power and speed test was assessed by seconds and coordination was assess by in number. The collected data were analyzed statistically by using dependent 't' test to determine the differences if any among the group prior to and immediately after the training period on selected criterion variables separately. Analysis of covariance (ANCOVA) was used to determine the differences, if any among the adjusted posttest means on selected dependent variables separately. The level of significance was fixed at 0.05 level of confidence, which was considered as appropriate. The experimental group namely the ladder training group has achieved significant improvement on agility and explosive power. Significant differences were found among ladder training group towards improving the selected criterion variables such as agility, and explosive power.

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 Keywords

Agility, Explosive Power, Ladder Training

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 Abstract

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 Keywords

Humanism, Spiritual Humanism, Man-making Education, Freedom, Religion, Vedanta.

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India has a diverse tribal population, among which the Particularly Vulnerable Tribal Groups (PVTGs) represent some of the most socio-economically marginalized communities. In Tamil Nadu, the Irula tribe is recognized as one of the six PVTGs and has historically depended on traditional livelihood practices such as hunting, gathering, subsistence agriculture, and small-scale livestock rearing. However, environmental changes, deforestation, and socio-economic transformations have significantly altered these traditional livelihood systems. The present study examines the livelihood patterns and socio-economic conditions of the Irula community with a focus on their access to institutional support and sustainable livelihood opportunities. The research adopted a descriptive research design and collected primary data from 104 respondents belonging to the Irula community in the Nilgiris region of Tamil Nadu using a self-structured questionnaire. The study analyzed various aspects such as demographic characteristics, income sources, awareness of government welfare schemes, access to institutional support, and satisfaction with healthcare facilities. Descriptive statistical tools such as frequency and percentage analysis were used to interpret the data. The findings reveal that the livelihood of the Irula community is largely dependent on seasonal migration, wage employment, livestock rearing, and agricultural labour, reflecting economic vulnerability and limited land ownership. The study also indicates moderate awareness of government schemes such as the Tamil Nadu Rural Transformation Project (TNRTP) and Large Sized Adivasi Multipurpose Societies (LAMPS), while a significant proportion of respondents reported inadequate institutional support in preserving indigenous knowledge and improving livelihood opportunities. Furthermore, dissatisfaction with healthcare services highlights the persistent infrastructural challenges in tribal areas. The study concludes that although institutional initiatives and welfare schemes exist to support tribal development, their reach and effectiveness remain limited. Strengthening awareness programs, improving service accessibility, and promoting community participation are essential to enhance sustainable livelihood opportunities and improve the overall socio-economic well-being of the Irula tribal community.

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Irula Tribes, Socio- Economic, Nilgiris District

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Human machine interface technologies have significantly advanced the development of assistive robotic systems. This paper presents the design and implementation of a hybrid control system for a robotic arm using electromyography (EMG) signals combined with voice commands. Surface EMG sensors are used to capture electrical signals generated by muscle contractions from the user's forearm. These signals represent the user's muscle activity and intention to perform certain movements. The EMG signals obtained from the electrodes are very weak and susceptible to noise. Therefore, they are first amplified and filtered using an EMG sensor module before being processed by an Arduino Nano microcontroller. The processed signals are analyzed to detect muscle contraction levels, which are then translated into commands to control the movements of the robotic fingers. However, relying solely on EMG signals can lead to limitations due to signal variability, muscle fatigue, and differences in electrode placement. To enhance system flexibility and usability, a smartphone-based voice command interface is integrated into the system. Voice commands are transmitted through a Bluetooth communication module (HC-05), allowing the user to control additional robotic movements through speech.The robotic arm consists of five servo motors that simulate the motion of human fingers. The Arduino Nano processes both EMG signals and voice commands to generate appropriate control signals for the motors. Experimental results demonstrate that the proposed hybrid control approach improves interaction efficiency, response time, and usability .This system provides a low-cost assistive solution that can be beneficial for individuals with upper-limb disabilities, rehabilitation therapy, and human-machine interaction research.

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Keywords: Electromyography (EMG) Hybrid Control System Human Machine Interface (HMI) Robotic Arm Voice Command Control Arduino Nano HC-05 Bluetooth Module Servo

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Data integrity validation across heterogeneous database systems is a fundamental challenge in cloud migration, multi-cloud replication, and continuous deployment pipelines. Existing tooling addresses homogeneous environments well but provides no general solution for cross-paradigm comparison--for instance, validating that records migrated from an Oracle relational schema are faithfully represented in an Azure CosmosDB document store. This paper presents a pluggable, database-agnostic comparison framework that normalises records from fourteen distinct database technologies into a canonical intermediate representation and performs field-level deep diffing with configurable key-matching strategies. The framework implements the Adapter design pattern, allowing new database backends to be integrated by implementing a five-method interface. We describe the architecture, the canonical type normalisation pipeline, identity-key resolution strategies for heterogeneous cross-paradigm comparisons, and empirical performance results on datasets ranging from one million to fifty million records. Benchmark results demonstrate that the framework sustains comparison throughputs of approximately 5,500 record pairs per second on commodity hardware for the homogeneous case, falling to approximately 2,100 record pairs per second for the most demanding cross-paradigm workload. The framework is fully open source and integrates naturally into CI/CD pipelines via structured exit codes and JSON/HTML report output.

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database comparison; data integrity; heterogeneous databases; adapter pattern; CosmosDB; migration validation; CI/CD; NoSQL; deep diff.

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Artificial Intelligence (AI) has transformed the analysis of consumer behaviour through precise, data-powered revelations about buying habits. This study investigates the contributions of AI-powered analytics, machine learning models, and vast datasets to untangle customer tastes and actions. The research probes AI's function in forecasting models, opinion mining, and customized suggestions, revolutionizing marketing approaches and improving customer engagement. Through advanced AI methods, companies can foresee customer requirements, streamline choices, and develop highly focused promotional efforts. AI facilitates instant monitoring of buying patterns while delivering practical intelligence that helps firms customize offerings and solutions according to behavioural adaptation and marketplace needs.

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Key words: Artificial intelligence, marketing approaches, promotional efforts.

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India's maritime foreign policy has passed through several distinct phases over the past decade -- from the focused regionalism of the SAGAR doctrine (2015), through the globally framed Indo-Pacific Oceans Initiative (2019), to the ambitious multilateralism of MAHASAGAR (2025). Each phase represented not a repudiation of what came before but a deliberate broadening of strategic scope, driven by a changing geopolitical environment, India's own growing material capabilities, and the accumulated lessons of a decade of oceanic statecraft. This article traces that evolution in depth. Beginning with Prime Minister Modi's Mauritius address of 12 March 2015, it examines how SAGAR crystallised India's long-neglected maritime identity into a coherent five-point doctrine of regional security and cooperative development. It traces SAGAR's operational record across bilateral capacity-building partnerships, multilateral naval platforms, and humanitarian deployments, while interrogating the structural constraints -- around financing, institutional depth, and Chinese counter-positioning -- that limited its reach. The article then analyses the Indo-Pacific Oceans Initiative as a doctrinal bridge, before examining MAHASAGAR -- formally, Mutual and Holistic Advancement for Security and Growth Across Regions -- as a genuinely global reformulation of India's maritime purpose. Drawing on diplomatic analysis by serving and former ambassadors, the coverage of MILAN 2026, peer-reviewed scholarship, and primary policy documents, the article argues that the SAGAR-to-MAHASAGAR transition reflects a state learning to translate civilisational maritime heritage into durable twenty-first-century statecraft.

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SAGAR, MAHASAGAR, Indian Ocean Region, Indo-Pacific Oceans Initiative, maritime multilateralism, MILAN 2026, Colombo Security Conclave, blue economy, Global South, India's foreign policy

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