Volume 14 | Issue 3

 Abstract

This study assesses the hydrochemical characteristics and irrigation suitability of groundwater in Akola Tehsil, Maharashtra. A total of 20 groundwater samples were analyzed for 19 physico-chemical parameters using standard analytical methods. Hydrogeochemical tools such as Piper and Gibbs diagrams were used to interpret water types and geochemical processes, while Wilcox and USSL diagrams evaluated the water's suitability for irrigation. Most samples fall within the "good to permissible" range, with a few showing elevated salinity and sodium hazards. The results highlight the influence of rock-water interaction and agricultural activities on groundwater quality, providing a basis for sustainable irrigation planning in the region.

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Groundwater Irrigation suitability, hydrogeochemistry.

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Web applications remain the most exploited entry point in modern cyber attacks, with industry reports attributing nearly one in four data breaches to vulnerabilities in web-facing software. Web Application Firewalls (WAFs) have emerged as a critical defense layer, inspecting HTTP traffic to identify and block malicious requests before they reach the application. This survey provides a comprehensive review of WAF technologies spanning signature-based, anomaly-based, and machine learning-driven detection methods. We examine the evolution of WAFs from early rule-matching systems such as Snort and ModSecurity through modern cloud-native solutions offered by AWS, Cloudflare, and Azure, and into the emerging class of AI-powered next-generation firewalls. We present a structured taxonomy of web application attacks aligned with the OWASP Top 10 (2021) and their corresponding Common Weakness Enumerations (CWEs), and we systematically compare how different WAF approaches address each category. Our analysis covers deployment architectures (reverse-proxy, embedded, cloud-based, and hybrid), real-time monitoring and alerting mechanisms, and the trade-offs among detection accuracy, latency overhead, and operational complexity. We consolidate findings from over 40 studies published between 2003 and 2025, identify seven persistent research gaps--including the shortage of public evaluation benchmarks, the opacity of commercial solutions, and the difficulty of detecting novel zero day payloads--and outline promising future directions such as federated learning for distributed WAF deployments and explainable AI for security decision-making.

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Web Application Firewall, Survey, Intrusion Detection, SQL Injection, Cross-Site Scripting, DDoS Mitigation, Machine Learning, Anomaly Detection, Real-Time Monitoring, OWASP Top 10

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The rapid growth of social media has significantly transformed modern marketing practices and consumer purchasing patterns. Social media platforms such as Facebook, Instagram, YouTube, and Twitter have become powerful tools for businesses to promote products and interact with consumers. This study examines the impact of social media marketing on the buying behavior of college students with special reference to Keonjhar District. The primary objective of the study is to analyse how social media influences students' awareness, preferences, and purchasing decisions. The research is based on primary data collected from college students through structured questionnaires. The study explores various factors such as online advertisements, influencer recommendations, product reviews, brand promotions, and peer opinions that affect consumer buying behavior on social media platforms. It also examines the frequency of social media usage among students and their level of trust in online marketing content. The findings indicate that social media plays a significant role in shaping the buying decisions of college students. Attractive advertisements, promotional offers, influencer marketing, and positive online reviews strongly influence students' purchasing intentions. Moreover, social media platforms provide easy access to product information, price comparisons, and user feedback, which further guide consumers in making informed decisions. The study concludes that social media marketing has become an effective and influential marketing strategy for businesses targeting young consumers. Understanding the behavior of college students in Keonjhar District can help marketers design more effective promotional strategies and improve customer engagement. The research also highlights the growing importance of digital marketing in shaping consumer behavior in the modern marketplace.

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Influencer, Recommendation, Promotional, Advertising, Significant

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The work patterns in India are experiencing a great change, and co-working places are being identified as a significant alternative to the traditional office set-ups. This paper discusses the concepts of co-working spaces in India and their influence on the traditional office market. The research design that was used was a mixed-method approach that incorporated secondary data (through industry reports and research articles) and primary data from a structured survey of 79 respondents across six major cities in India (Bengaluru, Delhi-NCR, Mumbai, Hyderabad, Pune and Chennai). The results show that there is a clear shift in preference to co-working and hybrid work set-ups, which is mainly driven by cost savings and flexibility, as well as the acceleration of hybrid work post-COVID-19. It is worth noting that co-working's share of total office absorption reached 30% in 2024, while the gross leasing volume in the flexible workspace industry reached an all-time high of 12.4 million sq. ft. in 2024. In the meantime, big corporations and industries like BFSI and Legal still favor the use of traditional offices because of privacy, operational control, and brand image reasons. The findings affirm that co-working is not a transient trend but it is structurally redefining the Indian office market. The paper concludes with recommendations to co-working operators, conventional office developers, corporates and policymakers, and identifies directions for future research.

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Co-working spaces, flexible workspace, traditional office market, commercial real estate, India, hybrid work, office leasing, post-COVID-19, workspace preferences, mixedmethod research

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Monkeypox is an infectious disease caused by the monkeypox virus (MPXV) that primarily affects animals but can be transmitted to humans, resulting in serious health implications. Early detection and accurate diagnosis of the disease are crucial for effective containment and treatment. Controlling the rapid transmission of the disease necessitates timely and accurate diagnosis, but the availability of traditional confirmatory tests, such as Polymerase Chain Reaction (PCR), remains limited. In this challenging scenario, by leveraging advanced technology, this approach can present a valuable alternative to conventional testing methods. To address this issue, we present a novel web application developed using Python's Flask framework, employing deep learning techniques for monkeypox disease detection. In this project, we develop a novel approach for the detection of Monkeypox disease using Deep Learning, specifically leveraging the ResNet50V2 architecture. The core of our approach relies on the ResNet50V2 architecture, which has demonstrated impressive performance in medical image analysis tasks. The model was trained on the Monkeypox Skin Lesion Dataset (MSLD), consisting of 1428 images labelled as 'Monkeypox' and 1764 images labelled as 'Others,' encompassing various skin lesion types. Through rigorous training and validation, our deep learning model achieved remarkable results, with a training accuracy of 93.00% and a validation accuracy of 92.00%. The easy-to-use web application allows users to upload skin lesion images, which are then analysed by our trained model to provide rapid identification of monkeypox. By providing a consumer-level software solution, our project aims to empower individuals and healthcare practitioners with a reliable tool for early detection of monkeypox, facilitating prompt action and containment efforts. This system can play a pivotal role in mitigating the impact of the ongoing monkeypox outbreak and enhancing global public health preparedness in the face of infectious diseases.

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Linear discriminant analysis, MLP Classifier, Adaboost , ML techniques, evaluation.

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Abstract Background: Breast cancer is one of the most common cancers affecting women worldwide. Early detection of breast cancer can significantly improve treatment outcomes and survival rates. Breast Self-Examination (BSE) is a simple, low-cost, and effective method for early detection of breast abnormalities. However, lack of knowledge and awareness about BSE among women remains a major barrier to early detection. Objectives: 1. To assess the knowledge regarding breast self-examination among women in a selected community area. 2. To assess the attitude toward breast self-examination among women. 3. To find the association between knowledge and attitude with selected demographic variables. 4. To develop an informational pamphlet regarding breast self-examination. Methods: A descriptive research design was used for the study. The study was conducted in a selected community area of Chhattisgarh. A total of 100 women were selected using a non-probability convenient sampling technique. Data were collected using a structured knowledge questionnaire and a Likert attitude scale. Descriptive and inferential statistics were used to analyze the data. Results: The findings revealed that a majority of respondents had moderate knowledge regarding breast self-examination, while some had inadequate knowledge. The attitude toward breast self-examination was found to be moderately favorable among many women. Educational status and previous exposure to health information were significantly associated with the knowledge level of the respondents. Conclusion: The study highlights the importance of health education programs to improve knowledge and encourage positive attitudes toward breast self-examination. Educational pamphlets and awareness programs can help women detect breast abnormalities early and improve health outcomes.

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Keywords: Breast Self-Examination, Knowledge, Attitude, Breast Cancer, Women's Health, Early Detection.

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Abstract Today, a new trend is observed. That is "taking private tuition". And it is increasing day by day. The present study is undertaken with the objective to study the nature of private tuition and to explore the reasons of taking private tuition. The study deals with 100 samples comprising male (25), female (25), Govt. Aided school students(25) and private school students(25) of class IX. Data tool included a questionnaire which is composed with two parts- part I( General information schedule), part- II( Nature of private tuition), .The findings revealed that Maximum students state that their private tutor's help is more beneficial than school teacher's help for their study. It is seen that the reasons of taking private tuitions are their parents want that they have a great career from their children (irrespective of boy and girls, private and Govt. aided school); large classroom so that teachers cannot give them personal attention, short time of period, tough curriculum, so they need external support; high societal competition, getting good job, getting excellent marks to get a chance in a good school tough job marketing competition; they have to do better than their friends, their desire of acquiring knowledge, aspiration of building a great career, enjoyment and engagement the time with friends in tuition. Maximum Govt. aided school students agree that they enjoy their peers company in coaching and private tutoring help them to obtain good grades in examination, private tutors make them satisfy by providing lessons, private tutors always listen to their problems, private tuition improves their results; they believe if they have one or more than one private tutor on a particular subject then they can achieve good mark.

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Keywords: Private tuition, Student, Secondary School, Government aided School, Private School.

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John Osborne's play Look Back in Anger (1956) is a significant work in British theatre after World War II. It is known for bringing social realism to the stage. This paper looks at how Osborne shows the real struggles of Britain's working and middle classes, especially through the main character, Jimmy Porter. By exploring the main ideas, characters, conversations, and setting, the paper shows how the play reflects the social conditions of Britain in the 1950s.

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Social realism, post-war drama, Look Back in Anger, John Osborne, class struggle, Angry Young Men

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Traditionally, the Indian criminal justice system has functioned through an offender-centric lens, focusing heavily on retributive justice and punishment. However, a progressive shift toward a restorative framework is emerging, which recognizes the victim not just as a witness, but as a primary stakeholder entitled to rights, rehabilitation, and reparation. The introduction of Section 357A in the CrPC (now Section 396 of the Bharatiya Nagarik Suraksha Sanhita, 2023) marked a significant legislative milestone, establishing State-funded victim compensation schemes. Despite these advancements, the implementation of these schemes is hampered by bureaucratic delays, inadequate funding, and a lack of uniformity across states. This paper analyses the current landscape of victim compensation in India and proposes reforms to create a truly victim-centric justice system also highlights the various laws on Victim compensation scheme.

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Victim compensation, Victim Compensation Scheme (VCS), Crime victim compensation, financial assistance to victims, Victim support, Section 357 CrPC (Code of Criminal Procedure), Section 357A CrPC, Bharatiya Nyaya Sanhita (BNSS) 2023 (new legal framework), Legal Services Authority (LSA) (e.g., DLSA/SLSA), Interim relief, Court-ordered compensation, Restitution, Reparation. Rehabilitation of victims, Victimology, Victims' rights, Criminal justice system, Monetary damages, Pecuniary assistance

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Aluminium 7075, Silicon Carbide, Stir Casting, Metal Matrix Composite, Hardness, Tensile

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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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psychology, cognition, therapeutic, phenomenology, introspection.

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Creative Commons Attribution 4.0 and The Open Definition

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

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Creative Commons Attribution 4.0 and The Open Definition

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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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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Agility, Explosive Power, Ladder Training

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 Abstract

??????????? ??????? ???? ????????? ?????? ????????? ??????????? ?????? ???? ?????? ??????? ? ????????? ?????????? ??????????? ????? ???????? ??????? ???? ??????? ????????? ??? ?????? ??? ???, ??????? ???????? ?? ???????? ??? ?????? ??? ????? ??????? ??? ?????? ?????? ???? ???? ??????? ????????? ??? ???? ?????????? ?????, ?????????? ???? ??????? ?????????? ??????? ????? ?????? ???????? ???????? ?? ??? ???? ??????? ???? ?????? ???? ?? ?? ??? ??????? ???????? ??????? ???? ????? ?????????? ?? ??? ??? ??????? ????? ???? ???????? ???? ?? ???????? ???? ????????, "???? ????? ??? ??? ??, ??? ?? ?????? ?????", ??? ???? - ?????? ???? ????? ????????? ????? ???? ??????? ????? ???? ????? ?????? ????? ??? ??????? ??? ???? ??????? ??? ??????? ??? ? ???? ?????? ????? ??????? ????? ???? ?????? ?????? ??????? ???? ?? ???? ???? ??? ??? ????? ??? ??????? ????? ????? ??????? ????? ???? ?????? ?????? ???? ???????? ?? ???????? ????? ????? ???????? ?? ??? ?????? ??????? ????? ????????? ??????????? ??? ????????? ?????????? ???????? ??, ????????? ???????????? ??? ????????, ?????????, ?????????, ?????-?? ??????? ??????????? ???? ????? ??? ???? ????? ?? ????? ???? ????????? ???? ?????? ?????? ???? ???? ???????? ??????, ???? ???? ????????? ??? ?????? ??? ???????? ????? ?????? ????? ????????? ??????????? ???????? ??? ??????? ?????? ??? ???????? ???? ???? ?????, ?????????, ?????????, ?????, ????????????, ????????? ??? ??? ???????????

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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

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Creative Commons Attribution 4.0 and The Open Definition