We present an empirical and theoretical comparative analysis of the structural causal model (SCM) and the potential outcome (PO) frameworks under the presence of biases of confounding and selection in the dataset. We used the Early Grade Reading Assessment (EGRA) dataset tagged “Strengthening Education in Northeast (SENSE) Nigeria, - an educational intervention program of the American University of Nigeria under the sponsorship of the United States Agency for International Development (USAID).
In open-air settings, low magnetic fields of 0.0𝑚𝑇, 0.0215𝑚𝑇, 0.0373𝑚𝑇, and 0.646𝑚𝑇 are applied throughout the sprout length growth phase following germination and post-germination of gram seeds (Cicer arietinum). When magnetic fields increase, the sprout length reduces and non-linear changes are seen in the graphs. As a result, the sprout length elongation of seeds is negatively impacted by these magnetic fields.
The addition of additives and changes in the quantity of certain materials and additions have an impact on the properties of molding sands. These additives include coal dust, clays, and corn flours; the materials mentioned are binders and water. The source of the natural molding sand was at Potiskum town, which is in the Potiskum Local Government Area of Yobe State, North Eastern Nigeria.
The rise in the failure of mechanical components, some of which are attributable to poor weld joints has given rise to research study on the optimization of weld joint strengths. Irrespective of the welding process, the need for the right combination of input process parameters cannot be over emphasized. To achieve a desired weld quality, a weld mechanical property such as the Chip Removal Rate was examined and related to weld input parameters such as depth of cut, cutting speed and feed rate. The Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict and optimize the Chip Removal Rate of a required to enhance the tool life of some Selected Material.
Nigeria, a developing nation, has abundant natural gas resources, which are abundant in terms of energy when combined with the known crude oil reserves of the nation. Nigeria is also becoming into a hub for natural gas, with long-term economic growth and development promising long-term environmental benefits. And for good reason—natural gas is the most economical, cleanest, and ecologically benign energy source available to consumers.
Project management is essential for achieving organizational goals, especially in today's dynamic business environment. As projects become more intricate, the demand for intelligent tools to aid project managers in decision-making and resource allocation has grown. Generative Artificial Intelligence (AI) holds promise in transforming project management by automating tasks, generating insights, and facilitating decision-making.
In this paper, we conduct a systematic literature review of present-day orchestration frameworks. This kind of demand has been compulsory and necessary for the sustainable growth of the digital economy in the present and future world markets as the need for scalable, flexible and reliable system design has increased tremendously. This becomes apparent today when organizations have top-level goals of deploying massive applications at scale while maintaining optimal control measures, which are offered by technologies like containers and container orchestration, namely docker and Kubernetes.
This study explores the integration of machine learning into Salesforce workflows to enhance automation and optimize operational efficiency. The research addresses the limitations of traditional Salesforce automation, which often falls short in managing the increasing complexity of data and workflows. The study employed a range of machine learning algorithms, including Logistic Regression, Decision Trees, Random Forests, and Gradient Boosting, applied to Salesforce data to assess their impact on task completion times, error rates, and user satisfaction.
With its decentralized structure and unchangeable record-keeping system, blockchain technology has gained widespread acceptance in a number of industries, including supply chain management, healthcare, and finance. However, there are issues with scalability, security, and efficiency with its conventional implementation.
With data exponential in nature, data management strategies have evolved in modern enterprises to embrace the exponential growth of data and AI acts as a transformative enabler for this. This paper explores how AI-driven data lakes and data warehouses converge to improve data science practices. Compared to data lakes, which can give scalable and inexpensive storage to unstructured and semi-structured data, the use case of data warehouses is to give a stable querying ability and performance for structured data. AI-driven frameworks integrate these paradigms and help in intelligent data discovery, automated transformations, and faster analytics. Experimental results show that these systems overcome traditional bottlenecks, optimize ETL processes, and enable real-time decision-making. However, governance, data quality, and ethical AI usage have persisted.
Cyber-Physical Systems (CPS) represent the convergence of physical processes and computational control, enabling enhanced automation and monitoring in industrial environments. CPS plays a pivotal role in ensuring operational efficiency, precision, and real-time decision-making in sectors such as manufacturing, energy systems, and smart grids. However, the growing interconnectivity and integration of CPS expose these systems to significant security threats, including cyberattacks, unauthorized access, and operational disruptions.
In the modern financial sector, data plays a pivotal role in decision-making, compliance, and operational efficiency. However, managing financial data streams effectively remains a significant challenge due to the diversity of data sources, volume, and the need for real-time processing. Traditional methods for updating and consuming data in financial systems are fraught with latency, inconsistency, and scalability issues.
Stroke is still only one of the major causes of disability, affecting motor function and mobility in particular. Applying evidence from previous studies, physical therapy has been shown to have promising possibilities of regaining mobility for the affected person. The physiotherapy approaches covered in this paper are task-oriented training, CIMT, and robotic-assisted interventions, supported by literature. Neuroplasticity principles are incorporated alongside other progressive practices, together with new technologies, in determining the best outcomes. Such findings also emphasize the significance of immediate treatment, individualized treatment strategy, and strict compliance with the aftercare program.
Modern enterprises are under constant pressure to evolve and innovate while maintaining reliability and compliance. Legacy IT systems, while robust and deeply integrated into organizational operations, are often ill-suited for the agility required in today’s digital environment.
Causal Inference Estimates with Backdoor Adjustment Condition vs. the Unconfoundedness Assumption: A Comparative
Analysis Study of the Structural Causal Model and the Potential Outcome FrameworksGabriel Terna Ayem, Ozcan Asilkan,
Aamo Iorliam, Rabiu Ibrahim, Salu George Thandekkattu
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We present an empirical and theoretical comparative analysis of the structural causal model (SCM) and the potential outcome (PO) frameworks under the presence of biases of confounding and selection in the dataset. We used the Early Grade Reading Assessment (EGRA) dataset tagged “Strengthening Education in Northeast (SENSE) Nigeria, - an educational intervention program of the American University of Nigeria under the sponsorship of the United States Agency for International Development (USAID).
Response to a Low Magnetic Field during the Growth of Sprout Length of Gram SeedsAmitava Ghorai
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In open-air settings, low magnetic fields of 0.0𝑚𝑇, 0.0215𝑚𝑇, 0.0373𝑚𝑇, and 0.646𝑚𝑇 are applied throughout the sprout length growth phase following germination and post-germination of gram seeds (Cicer arietinum). When magnetic fields increase, the sprout length reduces and non-linear changes are seen in the graphs. As a result, the sprout length elongation of seeds is negatively impacted by these magnetic fields.
Evaluation of Potiskum Natural Sand's Acceptability as Foundry Moulding MaterialMahmoud Lawan Umar, Fabiyi Mustapha Olawale,
Isheni Yakubu, Majidadi Solomon Tibidawe
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The addition of additives and changes in the quantity of certain materials and additions have an impact on the properties of molding sands. These additives include coal dust, clays, and corn flours; the materials mentioned are binders and water. The source of the natural molding sand was at Potiskum town, which is in the Potiskum Local Government Area of Yobe State, North Eastern Nigeria.
Prediction and Optimization of Chip Removal Rate Required to enhance the Weld’s Tool Life using Response Surface Methodology
(RSM) and Artificial Neural Network (ANN)Eyituoyo Amorighoye Lucky, Achebo Joseph, Obahiagbon Kessington, Uwoghiren Frank Omos
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The rise in the failure of mechanical components, some of which are attributable to poor weld joints has given rise to research study on the optimization of weld joint strengths. Irrespective of the welding process, the need for the right combination of input process parameters cannot be over emphasized. To achieve a desired weld quality, a weld mechanical property such as the Chip Removal Rate was examined and related to weld input parameters such as depth of cut, cutting speed and feed rate. The Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict and optimize the Chip Removal Rate of a required to enhance the tool life of some Selected Material.
Natural Gas Utilization: The Opportunities and Limitations militating Developing EconomiesOnwuamaeze, Ikechukwu Patrick,
Mohammed Bello Ahmed, Enakireru Emmanuel Ese
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Nigeria, a developing nation, has abundant natural gas resources, which are abundant in terms of energy when combined with the known crude oil reserves of the nation. Nigeria is also becoming into a hub for natural gas, with long-term economic growth and development promising long-term environmental benefits. And for good reason—natural gas is the most economical, cleanest, and ecologically benign energy source available to consumers.
Revolutionizing Project Management with Generative AIAmit Mangal
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Project management is essential for achieving organizational goals, especially in today's dynamic business environment. As projects become more intricate, the demand for intelligent tools to aid project managers in decision-making and resource allocation has grown. Generative Artificial Intelligence (AI) holds promise in transforming project management by automating tasks, generating insights, and facilitating decision-making.
The Role of Containers and Orchestration in Scalable System DesignGaurav Shekhar
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In this paper, we conduct a systematic literature review of present-day orchestration frameworks. This kind of demand has been compulsory and necessary for the sustainable growth of the digital economy in the present and future world markets as the need for scalable, flexible and reliable system design has increased tremendously. This becomes apparent today when organizations have top-level goals of deploying massive applications at scale while maintaining optimal control measures, which are offered by technologies like containers and container orchestration, namely docker and Kubernetes.
Enhancing Salesforce with Machine Learning: Predictive Analytics for Optimized Workflow AutomationNagaraj Mandaloju,
Vinod kumar Karne, Noone Srinivas, Siddhartha Varma Nadimpalli
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This study explores the integration of machine learning into Salesforce workflows to enhance automation and optimize operational efficiency. The research addresses the limitations of traditional Salesforce automation, which often falls short in managing the increasing complexity of data and workflows. The study employed a range of machine learning algorithms, including Logistic Regression, Decision Trees, Random Forests, and Gradient Boosting, applied to Salesforce data to assess their impact on task completion times, error rates, and user satisfaction.
AI-Driven Smart Contracts for Blockchain NetworksGaurav Kashyap
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With its decentralized structure and unchangeable record-keeping system, blockchain technology has gained widespread acceptance in a number of industries, including supply chain management, healthcare, and finance. However, there are issues with scalability, security, and efficiency with its conventional implementation.
AI-Powered Data Lakes and Warehouses: The Synergy that is Changing Data Science ForeverPrem Tamanam
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With data exponential in nature, data management strategies have evolved in modern enterprises to embrace the exponential growth of data and AI acts as a transformative enabler for this. This paper explores how AI-driven data lakes and data warehouses converge to improve data science practices. Compared to data lakes, which can give scalable and inexpensive storage to unstructured and semi-structured data, the use case of data warehouses is to give a stable querying ability and performance for structured data. AI-driven frameworks integrate these paradigms and help in intelligent data discovery, automated transformations, and faster analytics. Experimental results show that these systems overcome traditional bottlenecks, optimize ETL processes, and enable real-time decision-making. However, governance, data quality, and ethical AI usage have persisted.
Cyber-Physical Systems: Enhancing Security and Reliability in Industrial AutomationJyothsna Devi Dontha
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Cyber-Physical Systems (CPS) represent the convergence of physical processes and computational control, enabling enhanced automation and monitoring in industrial environments. CPS plays a pivotal role in ensuring operational efficiency, precision, and real-time decision-making in sectors such as manufacturing, energy systems, and smart grids. However, the growing interconnectivity and integration of CPS expose these systems to significant security threats, including cyberattacks, unauthorized access, and operational disruptions.
Implementing Seamless Financial Data Injection Into Data Lakes Using KafkaGomathi Shirdi Botla
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In the modern financial sector, data plays a pivotal role in decision-making, compliance, and operational efficiency. However, managing financial data streams effectively remains a significant challenge due to the diversity of data sources, volume, and the need for real-time processing. Traditional methods for updating and consuming data in financial systems are fraught with latency, inconsistency, and scalability issues.
Optimizing Recovery Post-Stroke: Evidence-Based Physical Therapy Interventions for Motor Function Restoration and
Long-Term Mobility ImprovementsLaljibhai Makwana
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Stroke is still only one of the major causes of disability, affecting motor function and mobility in particular. Applying evidence from previous studies, physical therapy has been shown to have promising possibilities of regaining mobility for the affected person. The physiotherapy approaches covered in this paper are task-oriented training, CIMT, and robotic-assisted interventions, supported by literature. Neuroplasticity principles are incorporated alongside other progressive practices, together with new technologies, in determining the best outcomes. Such findings also emphasize the significance of immediate treatment, individualized treatment strategy, and strict compliance with the aftercare program.
The Role of Cloud in Digital Transformation: Strategies for Legacy ModernizationSantosh Pashikanti
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Modern enterprises are under constant pressure to evolve and innovate while maintaining reliability and compliance. Legacy IT systems, while robust and deeply integrated into organizational operations, are often ill-suited for the agility required in today’s digital environment.