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Daily Archives: August 21, 2026

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The Impact of Artificial Intelligence on Branding Strategies

Authors: Prachi Prakash Gupta

Abstract: Artificial Intelligence (AI) has emerged as a transformative force in modern marketing and branding. Businesses are increasingly using AI-driven technologies to understand consumer behaviour, personalize brand communication, automate customer interactions, analyse market trends, and strengthen customer relationships. The integration of AI into branding strategies has enabled organizations to create more personalized, efficient, and data-driven brand experiences. This research paper examines the impact of Artificial Intelligence on branding strategies and explores how AI influences brand awareness, customer engagement, personalization, brand loyalty, and consumer perception. The study also highlights the challenges and ethical concerns associated with the use of AI in branding, including data privacy, authenticity, transparency, algorithmic bias, and over-dependence on technology. The paper concludes that AI has the potential to strengthen branding when technological efficiency is balanced with human creativity, ethical responsibility, and consumer trust.

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The Role of Artificial Intelligence in Personalized Marketing: Transforming Customer Experiences in the Digital Age

Authors: Assistant Professor Ms. Pooja Jagatnarayan Dixit

Abstract: The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed the way businesses interact with consumers. In an increasingly competitive marketplace, organizations are shifting from mass marketing approaches to personalized marketing strategies that cater to individual customer preferences, behaviors, and needs. AI technologies such as machine learning, predictive analytics, natural language processing, and recommendation systems have enabled businesses to analyze vast amounts of consumer data and deliver highly customized experiences in real time. This paper explores the role of Artificial Intelligence in personalized marketing, examining its applications, benefits, challenges, and future implications. The study argues that AI-driven personalization not only enhances customer satisfaction and engagement but also reshapes the relationship between brands and consumers by making marketing more relevant, efficient, and customer-centric.

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Challenges and Strategies for Learner Support and Remediation in the Context of Free Education and the Competency-Based Curriculum in Selected Secondary Schools in Chirundu District

Authors: Ephraim Mapiki

Abstract: This study investigated the challenges and strategies for learner support and remediation in the context of Free Education and the Competency-Based Curriculum (CBC) in selected secondary schools in Chirundu District, Zambia. The study was guided by three objectives: to identify challenges schools face in providing learner support and remediation; to examine how Free Education and CBC affect the provision of learner support and remediation; and to determine strategies for addressing the identified challenges. A qualitative research approach and descriptive research design were employed. The study involved three selected secondary schools, with three headteachers, thirty teachers and fifteen learners participating. Data were collected through headteacher interviews and structured questionnaires administered to teachers and learners, and were analysed thematically and descriptively. The findings revealed that learner support and remediation were being provided through remedial and extra lessons, continuous assessment, peer support, group work, additional explanations and follow-up of learners experiencing difficulties. However, their effectiveness was constrained by large class sizes, inadequate classroom space, shortages of textbooks and other teaching and learning materials, limited computers and practical equipment, heavy teacher workloads, limited instructional time and inadequate professional support. Learners particularly reported difficulties caused by classroom noise and overcrowding, while also highlighting shortages of textbooks, computers and practical materials. At the same time, learners appreciated teachers' efforts to provide extra lessons and simplify explanations. The study further found that Free Education had significantly increased access to secondary education, particularly for learners from financially disadvantaged families. However, increased enrolment had placed additional pressure on teachers, classrooms and learning resources, thereby reducing opportunities for individualised learner support and making remediation and continuous assessment more difficult. The study concludes that expanding access without proportionately expanding school capacity can undermine the effectiveness of learner support and the attainment of CBC competencies. The study recommends increased provision of teachers, classrooms, textbooks, ICT and practical resources; strengthened continuous professional development; structured remedial programs; effective assessment and monitoring; supportive supervision; and stronger parental and community involvement. The study concludes that the effective implementation of Free Education and CBC requires not only increased access to education but also adequate resources and systematic learner support to ensure that all learners have meaningful opportunities to achieve the expected competencies.

DOI: https://doi.org/10.5281/zenodo.22044534

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Multi-Objective Topology Optimization and Mechanical Characterization of Additively Manufactured Triply Periodic Minimal Surface (TPMS) Structures

Authors: Gaurav Gugale

Abstract: Lightweight porous structures have gained significant attention across aerospace, biomedical, and automotive applications due to their exceptional specific energy absorption (SEA) and strength-to-weight ratios. Triply Periodic Minimal Surfaces (TPMS), specifically Gyroid and Diamond sheet-based architectures, offer superior stress distribution and high permeability over traditional strut-based lattice systems. This study investigates the elastoplastic compressive behavior of 316L stainless steel TPMS lattices fabricated via Laser Powder Bed Fusion (LPBF). Non-linear Finite Element Analysis (FEA) incorporating Johnson-Cook plasticity and ductile damage models was conducted and benchmarked against experimental uniaxial quasi-static compression tests. The results demonstrate that sheet-Gyroid architectures exhibit stable, progressive collapse modes with a 28.4% increase in SEA compared to Diamond lattices at an equivalent relative density of ρ* = 0.30. Furthermore, a Gibson-Ashby scaling relationship was established to predict the effective modulus and plateau stress across relative densities from 0.15 to 0.45.

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The Right to Disconnect in India: Addressing Digital Overwork and Employee Well-Being

Authors: Muskan Gupta

Abstract: This article looks at the idea of the Right to Disconnect, which means employees should not be expected to work or respond to messages outside their official working hours. It focuses on workers in India’s IT and BPM sectors. Using a mix of data from Indian and international labour surveys and a survey of 300 professionals in five major cities, the study examines how Indian labour laws currently do not protect workers from after-hours digital work, and how this affects their health and well-being. Key findings show that 68% of IT workers regularly get work messages after hours, and 42% show signs of burnout. The article also looks at how countries like France, Portugal, Belgium, and Spain handle this issue to suggest solutions for India. The study concludes that while a single national law might be hard to implement, a tiered approach — tailored to different sectors and included within India’s Occupational Safety, Health and Working Conditions Code — could protect employees without hurting business operations. Overall, the article highlights the importance of protecting workers’ digital rights as India’s work environment evolves.

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Evaluation of Aeolian Soil – Bacillus Brevis Induced Calcite Precipitate for Wind Erosion Application Using Bacterial Foraging Optimisation Algorithm

Authors: A. M. Garba, M. Abubakar, K. J. Osinubi, O. Eberemu, T. S. Ijimdiya

Abstract: The potential of biotreated Aeolian soil using Bacillus brevis (B. brevis)-induced calcite precipitation for mitigating wind erosion was investigated through the application of the Bacterial Foraging Optimization Algorithm (BFOA). Laboratory experiments were conducted to generate the data required for the optimization analysis. Sediment flux (y) was considered the dependent variable, while B. brevis suspension density, pH, compactive effort, water content relative to optimum, and cementation conditions were considered independent variables influencing the wind-erodibility response of the treated soil. GeneXproTools 5.0 was employed to develop the fitness (objective) function describing the relationship between sediment flux and the selected independent variables. The resulting fitness function was subsequently incorporated into BFO codes developed in MATLAB 2016 to determine the combination of variables associated with minimum sediment flux. The optimization results demonstrated a strong relationship between the predicted and experimentally measured sediment-flux values, with a coefficient of determination (R²) of 0.912. This indicates that the developed optimization model provided a satisfactory representation of the experimentally observed wind-erodibility behaviour of the biotreated Aeolian soil. The optimization process further showed that sediment flux was strongly influenced by the selected independent variables. The minimum predicted sediment flux of approximately 3.91 × 10⁻³ kg/m²s was obtained after 50 iterations. Based on the optimization results, treatment of Aeolian soil with B. brevis suspension and 0.75 M cementation reagent demonstrated considerable potential for reducing wind-induced sediment transport. The findings indicate that BFOA can serve as an effective optimization tool for identifying suitable microbial treatment conditions for wind-erosion mitigation, particularly in arid and semi-arid environments.

DOI: https://doi.org/10.5281/zenodo.22042808

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Design and Implementation of an IoT-Based Smart Office Automation System

Authors: Anjali Savner, Assistant Professor Kapil Shah, Professor Kamlesh Patidar

Abstract: This paper presents the design and implementation of an Internet of Things (IoT)-based smart office automation system developed to improve energy efficiency, security, comfort, and real-time office monitoring. The proposed system integrates an ESP32 controller with IR, LDR, DHT11, MQ-2 and R307 fingerprint sensors, together with relay modules, an L298N motor driver, a DC motor, a 16×2 LCD and a P10 LED display. Occupancy information is used to automate lights and fans, while environmental information supports temperature, humidity, light and air-quality monitoring. Biometric authentication is used to update office availability, which is displayed outside the office. ESP-NOW/Wi-Fi communication supports wireless exchange of status information between controller and display modules. The supplied project report documents successful hardware and integration testing, including motion detection, environmental sensing, biometric authentication, appliance control, curtain operation, sensor integration and failure handling. The system provides a practical prototype for smart-office and future smart-campus applications.

DOI: https://doi.org/10.5281/zenodo.22042149

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