Category Archives: Uncategorized

Authors: Gurnam Toor

Abstract: Enterprises today demand uninterrupted customer engagement, especially as Salesforce Service Cloud integrates artificial intelligence (AI) to power predictive case routing, chatbots, and intelligent support workflows. However, delivering these services at scale requires robust, fault-tolerant infrastructures capable of ensuring high availability and disaster recovery. This review explores how Veritas Cluster Server (VCS) strengthens hybrid Unix infrastructures to support AI-powered Salesforce Service Cloud operations. The paper examines VCS’s architecture, including its cluster-based design, service groups, and monitoring agents that automate failover and ensure business continuity. It further discusses the integration of VCS with Salesforce workflows, highlighting how resilience at the infrastructure level enables continuous availability of customer-facing AI processes. Industry case studies from financial services, healthcare, telecommunications, and the public sector illustrate real-world benefits, while challenges such as deployment complexity, interoperability, and cost considerations are critically assessed. Finally, the review identifies future research opportunities, including AI-driven cluster management, deeper integration with cloud-native architectures, compliance automation, and sustainability-focused clustering strategies. By linking technical resilience with business value, this article emphasizes the transformative potential of combining VCS with Salesforce Service Cloud to meet modern demands for reliability, compliance, and enhanced customer experience

DOI: http://doi.org/10.5281/zenodo.17365601

Published by: vikaspatanker

Authors: Harnoor Gill

Abstract: As Salesforce CRM increasingly drives enterprise customer engagement, securing sensitive workflows across hybrid multi-cloud Unix infrastructures has become critical. This review explores the integration of Tripwire, Tivoli, and artificial intelligence (AI) to create a comprehensive security monitoring framework for Salesforce CRM environments. Tripwire provides continuous file integrity monitoring and change detection, while Tivoli ensures system performance, event correlation, and compliance management. AI enhances these tools by enabling anomaly detection, predictive threat analysis, and automated remediation, transforming traditional monitoring into a proactive, intelligent security system. The article examines architectural frameworks, workflow automation, incident response orchestration, and regulatory compliance considerations. Industry case studies from financial services, healthcare, retail, and government illustrate real-world applications and benefits. Challenges such as integration complexity, scalability, cost, and AI tuning are discussed, alongside future research directions, including cloud-native monitoring, zero-trust architectures, and self-healing security frameworks. This review emphasizes how combining Tripwire, Tivoli, and AI empowers enterprises to maintain secure, resilient, and compliant Salesforce CRM workflows in complex hybrid multi-cloud environments.

DOI: http://doi.org/10.5281/zenodo.17365580

Published by: vikaspatanker

Authors: Tejinder Grewal

Abstract: Salesforce CRM has become a mission-critical platform for enterprises, supporting customer engagement, sales operations, and service delivery. With growing reliance on hybrid Unix infrastructures and multi-cloud environments, ensuring disaster recovery (DR) and business continuity has become increasingly complex. This review explores the role of Commvault, Veritas Cluster Server (VCS), and Unix-native tools in building a resilient DR framework for Salesforce CRM. Commvault provides comprehensive data backup, replication, and granular recovery; VCS delivers clustering and automated failover for high availability; and Unix tools ensure system-level reliability and orchestration. Together, these solutions create a layered, complementary approach that minimizes downtime, protects data integrity, and supports compliance with regulatory requirements. Case studies from finance, healthcare, and telecommunications industries demonstrate the effectiveness of multi-cloud DR strategies in maintaining seamless operations. The article also discusses challenges such as orchestration complexity, compliance concerns, and skill shortages, while highlighting future trends including AI-driven predictive recovery, Disaster Recovery as a Service (DRaaS), and blockchain-based validation. By integrating enterprise DR tools with hybrid Unix infrastructure, organizations can achieve robust resilience, ensuring Salesforce CRM remains reliable in dynamic and unpredictable IT environments.

DOI: http://doi.org/10.5281/zenodo.17365534

Published by: vikaspatanker

Authors: Ravinder Virk

Abstract: The rapid expansion of AI-powered customer relationship management systems has created new demands for efficient, scalable, and resilient deployment strategies within hybrid infrastructures. This review examines how the integration of Salesforce Flows and Red Hat Kickstart can accelerate CRM automation by linking application-level workflows with system-level provisioning. Salesforce Flows provides a declarative approach to automating CRM processes, while Red Hat Kickstart delivers reliable Unix/Linux provisioning at scale. Together, they enable end-to-end automation pipelines that reduce deployment times, enhance consistency, and align infrastructure resources with dynamic business needs. The article explores the evolution of CRM automation, the role of hybrid infrastructures, and the benefits and challenges of integrating workflow and provisioning tools. Case studies from industries such as finance, healthcare, and retail illustrate the practical applications of this approach. The review also discusses key challenges, including interoperability, security, and organizational readiness, while highlighting emerging trends such as Infrastructure as Code, AI-driven orchestration, and autonomous deployment pipelines. Ultimately, the convergence of Salesforce Flows and Red Hat Kickstart demonstrates a pathway toward intelligent and resilient CRM deployment strategies, positioning enterprises to thrive in an era of digital transformation

DOI: http://doi.org/10.5281/zenodo.17365471

Published by: vikaspatanker

Authors: Gaganjot Bajwa

Abstract: The increasing demand for seamless and personalized customer experiences has driven enterprises to adopt omni-channel engagement strategies that unify communication across digital, mobile, and traditional platforms. Salesforce has emerged as a leading enabler of such strategies, particularly with the integration of artificial intelligence through its Einstein platform. These AI-driven capabilities enhance omni-channel operations by enabling predictive insights, intelligent routing, conversational AI, and real-time personalization. However, the success of such systems depends on the underlying IT infrastructure. Hybrid environments that combine on-premises Unix/Linux systems with private and public cloud platforms provide the scalability, reliability, and flexibility required to support AI-enhanced customer engagement. This review examines the integration of Salesforce AI-driven omni-channel features with hybrid Unix/Linux infrastructures, highlighting frameworks, automation, and security considerations that enable seamless interoperability. Case studies from industries such as finance, healthcare, and retail illustrate the tangible benefits of this integration, while also identifying challenges related to complexity, compliance, and operational costs. Future trends point toward advancements in generative AI, edge computing, and zero-trust security frameworks, which will further enhance resilience and responsiveness in omni-channel CRM. The findings underscore the importance of aligning AI-powered Salesforce capabilities with robust hybrid infrastructures to achieve customer-centric operations that are scalable, secure, and adaptive to evolving enterprise needs

DOI: http://doi.org/10.5281/zenodo.17365436

Published by: vikaspatanker

Authors: Kanwarpal Sekhon

Abstract: The rapid adoption of Salesforce CRM across industries has transformed how organizations manage customer data, streamline business processes, and enhance operational efficiency. However, when deployed within hybrid Unix cloud infrastructures, Salesforce CRM faces significant security and compliance challenges due to data fragmentation, complex integrations, and diverse regulatory requirements. This review article explores the role of IBM Tivoli and Tripwire as complementary tools for addressing these challenges. Tivoli strengthens identity and access management by unifying authentication and authorization across Salesforce and Unix/Linux systems, while Tripwire provides continuous file integrity monitoring, vulnerability detection, and automated compliance reporting. Together, these platforms create a comprehensive security and compliance framework capable of safeguarding sensitive CRM data in distributed environments. The article also examines real-world applications across industries such as financial services, healthcare, retail, and government, highlighting how integrated deployments improve regulatory adherence and resilience. Furthermore, it discusses future directions in security automation, including the integration of AI-driven threat detection, Zero Trust architectures, and cloud-native security enhancements. By combining Salesforce CRM with Tivoli and Tripwire, enterprises can establish a proactive, scalable, and audit-ready compliance strategy, ensuring customer trust and long-term digital sustainability.

DOI: http://doi.org/10.5281/zenodo.17365413

Published by: vikaspatanker

Authors: Swati V, Ms. S. Madhu Sangeetha, Dr. B. Lalitha

Abstract: Automatic Teller Machine (ATM) are widely available for users and procedure the ability to carry-out financial transactions and Banking functions in continuous time basis at any time. It made banking transactions effortless for customers current ATM’s have access card and pin authentication for unique information. This explains ATMs to lot of financial theft like card theft, pin theft and stealing account holders’ information. So this project will make the multilevel high end security to find the authorized user in the ATM machine and make secured and more safety transaction and withdrawal money in ATM. High level security mechanism is provided by the consecutive actions after proceeding with pin number such as initially system use Open CV library to analyze the person authorized identification by capturing the human face initially it begins with the entering the pin number if the entered pin is correct then the process continues with the face recognition. If the entered pin is wrong then it sends OTP to the registered Outlook mail. If the entered OTP is correct then the process continues or else the transaction is declined. If the person is authorized it continues if the person is unauthorized, it sends the alert mail and alert SMS to the registered user by using the fast2sms messaging platform. After the completion of transaction, it provides persons image which was captured at the Time of withdrawal in the ATM has to be sent to the registered user mail.

Published by: vikaspatanker

Authors: Ese Lawrence Ekanem, Ogbede Oritsematosan Marian, Okorocha Cyrilgentle Ugochukwu, Odejobi Babajide Michael, Oluwadamisi Tayo-Ladega , Erienu Obruche Kennedy

Abstract: The research examined how health issues affect the eating habits of older adults in both rural and urban households, focusing on Badagry L.G.A in Lagos State. Four research questions were formulated to guide the study, along with one hypothesis that was tested at a significance level of 0.05. A correlational ex-post facto research design was employed for this investigation. According to the 2006 census, Badagry L.G.A had a population of 241,093. The study used a descriptive survey design with 100 participants. A stratified random sampling method, including simple random sampling, was applied to select the sample for this research. Data was gathered through a questionnaire titled "Influence of Health Challenges on Nutritional Lifestyle of the Elderly in Rural and Urban Households of Badagry L.G.A, Lagos State (IHCNLERUH)." The validity of the instruments was assessed for face, content, and construct. The reliability of the instruments was also checked, yielding an internal consistency reliability coefficient of 0.96. The collected data were analyzed using basic correlation and regression at a significance level of 0.05. Frequency, percentage, mean, and standard deviation were utilized to address the research questions, while Pearson coefficient correlation was employed to test the hypothesis. The findings indicated that the eating habits of older adults significantly influence their healthy lifestyle. Health challenges have a notable impact on the nutritional lifestyle of the elderly in both rural and urban settings. High alcohol consumption adversely affects the nutritional status of older individuals. Various factors hinder the nutritional lifestyle and health behaviors of the elderly in these areas. The study suggested that the government and other stakeholders should regularly monitor the health of older adults to identify those at risk, enabling timely interventions, and establish a social security system to support the income and welfare of the elderly people in the study area

DOI: http://doi.org/10.5281/zenodo.17366239

Published by: vikaspatanker

Authors: Kailash Kumar Mahto

Abstract: Recent advancements in power electronics have provided a strong platform for the development of various multilevel inverter (MLI) topologies. These MLI configurations offer several notable advantages, such as high-quality staircase sinusoidal output voltage, a reduced number of power switches, and the elimination of external filters. In this paper, a symmetrical sourced base multilevel inverter topology to generate 11-level of output is proposed to minimize the number of inverter components while achieving an enhanced voltage-step generation. The proposed structure is capable of producing a high-step, staircase-type of 11-level voltage output waveform that closely approximates a sinusoidal voltage without increasing the number of power semiconductor switches. A Carrier-Based Sinusoidal Pulse Width Modulation (CB-PWM) technique is implemented at a switching frequency of 3 kHz to control the inverter operation. The simulation is carried out using MATLAB/Simulink R2019b environment. The working principle of the proposed multilevel inverter (MLI) is explained in detail. This research focuses on the design of a novel single-phase multilevel inverter with a reduced component count. The proposed MLI configuration is structured to generate the maximum possible number of voltage levels in the output AC waveform while utilizing fewer power electronic devices. Furthermore, the output characteristics of the proposed inverter are analyzed for modulation index 1 for an RL load to examine its dynamic behavior and voltage-step generation capability.

DOI: https://doi.org/10.5281/zenodo.18846772

Published by: vikaspatanker

Authors: Samruddhi Ande, Professor S. V. Raut

Abstract: Millions of individuals worldwide suffer with diabetes, a dangerous medical condition. Serious problems can be avoided with early diabetes prediction. In this study, we predict diabetes in individuals based on a variety of health factors using machine learning approaches. Age, blood pressure, glucose level, BMI, and other medical characteristics are among the data in the dataset. To increase prediction accuracy, data preprocessing techniques such as normalization and handling missing values were used. A number of machine learning models were tested, such as Support Vector Machine, Random Forest, and Decision Tree. The accuracy, precision, recall, and F1-score of these models were used to compare their performances. The Random Forest model demonstrated its suitability for diabetes prediction by achieving the best accuracy. The findings show that machine learning may reliably support early diagnosis, assisting physicians and patients in making better health-related decisions. The significance of technology in healthcare and the potential for AI-based solutions to enhance patient outcomes are highlighted in this study.

Published by: vikaspatanker