Search results for: streamline upwind petrov-galerkin
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 134

Search results for: streamline upwind petrov-galerkin

44 Sports Preference Intervention as a Predictor of Sustainable Participation at Risk Teenagers in Ibadan Metropolis, Ibadan Nigerian

Authors: Felix Olajide Ibikunle

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Introductory Statement: Sustainable participation of teenagers in sports requires deliberate and concerted plans and managerial policy rooted in the “philosophy of catch them young.” At risk, teenagers need proper integration into societal aspiration: This direction will go a long way to streamline them into security breaches and attractive nuisance free lifestyles. Basic Methodology: The population consists of children between 13-19 years old. A proportionate sampling size technique of 60% was adopted to select seven zones out of 11 geo-political zones in the Ibadan metropolis. Qualitative information and interview were used to collect needed information. The majority of the teenagers were out of school, street hawkers, motor pack touts and unserious vocation apprentices. These groups have the potential for security breaches in the metropolis and beyond. Five hundred and thirty-four (534) respondents were used for the study. They were drawn from Ojoo, Akingbile and Moniya axis = 72; Agbowo, Ajibode and Apete axis = 74; Akobo, Basorun and Idi-ape axis 79; Wofun, Monatan and Iyana-Church axis = 78; Molete, Oke-ado and Oke-Bola axis = 75; Beere, Odinjo, Elekuro axis = 77; Eleyele, Ologuneru and Alesinloye axis = 79. Major Findings: Multiple regression was used to analyze the independent variables and percentages. The respondents' average age was 15.6 years old, and 100% were male. The instrument (questionnaire) used yielded; sport preference (r = 0.72), intervention (r = 0.68), and sustainable participation (r = 0.70). The relative contributions of sport preference on the participation of at risk teenagers was (F-ratio = 1.067); Intervention contribution of sport on the participation of at risk teenagers = produced (F-ratio of 12.095) was significant while, sustainable participation of at risk teenagers produced (F-ratio = 1.062) was significant. Closing Statement: The respondents’ sport preference stimulated their participation in sports. The intervention exposed at risk-teenagers to coaching, which activated their interest and participation in sports. At the same time, sustainable participation contributed positively to evolving at risk teenagers' participation in their preferred sport.

Keywords: sport, preference, intervention, teenagers, sustainable, participation and risk teenagers

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43 Applications of Hyperspectral Remote Sensing: A Commercial Perspective

Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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42 Viewers’ Reactions to Excessive Ritual Themes in Nigerian Home Videos: A Portharcourt City Survey

Authors: Godwin Bassey Okon

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The need to streamline viewers’ disposition towards the predominant portrayal of rituals, in most Nigerian home videos, as a way of life in the southern part of Nigeria necessitated this study. The focus however was on ascertaining if such portrayals dovetail within the framework of construction of social reality or misconstruction of social reality. In other words, do the people of the southern part of Nigeria engage in rituals as a means of acquiring wealth or do they merely have proclivity for diabolism, as frequently portrayed in home videos subsumed in their socio-cultural settings? The method of study was survey with the questionnaire as the predominant instrument. The questionnaire was used to elicit responses from Portharcourt city residents on their views and reactions in the light of ritual themes in Nigerian home videos. The choice of Portharcourt was informed by the fact that it is a foremost cosmopolitan city in the south. A Sample size of 400 was drawn from a population of 1,382,392 using Taro Yamane’s formula. Actual respondents were reached using a multi-stage cluster sampling technique. The reliability of the instrument as ascertained through Pearson’s Product Moment Correlation stood at 0.89. Findings however revealed that ritual themes, as used in Nigerian home videos, did not significantly reflect the cultural heritage of the people of southern Nigeria. Findings further showed that their excessive use in Nigerian home videos served only to create frills and thrills in plots. A synthesis of the foregoing, however, revealed that viewers are not favourably disposed towards the excessive use of ritual themes since they inadvertently portray the cultural heritage of the people of the south in the negative. To this end, it was recommended that producers of Nigerian home videos should focus more on themes that serve to construct social reality while projecting favorably the rich cultural heritage of the people. In terms of contribution to knowledge, the findings of this study tend to reinforce the notion of film as a conveyor belt in cognitive constructs.

Keywords: disposition, home videos, ritual, social reality, themes

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41 Enhancing Operational Efficiency and Patient Care at Johns Hopkins Aramco Healthcare through a Business Intelligence Framework

Authors: Muneera Mohammed Al-Dossary, Fatimah Mohammed Al-Dossary, Mashael Al-Shahrani, Amal Al-Tammemi

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Johns Hopkins Aramco Healthcare (JAHA), a joint venture between Saudi Aramco and Johns Hopkins Medicine, delivers comprehensive healthcare services to a diverse patient population. Despite achieving high patient satisfaction rates and surpassing several operational targets, JAHA faces challenges such as appointment delays and resource inefficiencies. These issues highlight the need for an advanced, integrated approach to operational management. This paper proposes a Business Intelligence (BI) framework to address these challenges, leveraging tools such as Epic electronic health records and Tableau dashboards. The framework focuses on data integration, real-time monitoring, and predictive analytics to streamline operations and enhance decision-making. Key outcomes include reduced wait times (e.g., a 23% reduction in specialty clinic wait times) and improved operating room efficiency (from 95.83% to 98% completion rates). These advancements align with JAHA’s strategic objectives of optimizing resource utilization and delivering superior patient care. The findings underscore the transformative potential of BI in healthcare, enabling a shift from reactive to proactive operations management. The success of this implementation lays the foundation for future innovations, including machine learning models for more precise demand forecasting and resource allocation.

Keywords: business intelligence, operational efficiency, healthcare management, predictive analytics, patient care improvement, data integration, real-time monitoring, resource optimization, Johns Hopkins Aramco Healthcare, electronic health records, Tableau dashboards, predictive modeling, efficiency metrics, resource utilization, patient satisfaction

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40 Exploratory Analysis and Development of Sustainable Lean Six Sigma Methodologies Integration for Effective Operation and Risk Mitigation in Manufacturing Sectors

Authors: Chukwumeka Daniel Ezeliora

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The Nigerian manufacturing sector plays a pivotal role in the country's economic growth and development. However, it faces numerous challenges, including operational inefficiencies and inherent risks that hinder its sustainable growth. This research aims to address these challenges by exploring the integration of Lean and Six Sigma methodologies into the manufacturing processes, ultimately enhancing operational effectiveness and risk mitigation. The core of this research involves the development of a sustainable Lean Six Sigma framework tailored to the specific needs and challenges of Nigeria's manufacturing environment. This framework aims to streamline processes, reduce waste, improve product quality, and enhance overall operational efficiency. It incorporates principles of sustainability to ensure that the proposed methodologies align with environmental and social responsibility goals. To validate the effectiveness of the integrated Lean Six Sigma approach, case studies and real-world applications within select manufacturing companies in Nigeria will be conducted. Data were collected to measure the impact of the integration on key performance indicators, such as production efficiency, defect reduction, and risk mitigation. The findings from this research provide valuable insights and practical recommendations for selected manufacturing companies in South East Nigeria. By adopting sustainable Lean Six Sigma methodologies, these organizations can optimize their operations, reduce operational risks, improve product quality, and enhance their competitiveness in the global market. In conclusion, this research aims to bridge the gap between theory and practice by developing a comprehensive framework for the integration of Lean and Six Sigma methodologies in Nigeria's manufacturing sector. This integration is envisioned to contribute significantly to the sector's sustainable growth, improved operational efficiency, and effective risk mitigation strategies, ultimately benefiting the Nigerian economy as a whole.

Keywords: lean six sigma, manufacturing, risk mitigation, sustainability, operational efficiency

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39 Computational Team Dynamics in Student New Product Development Teams

Authors: Shankaran Sitarama

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Teamwork is an extremely effective pedagogical tool in engineering education. New Product Development (NPD) has been an effective strategy of companies to streamline and bring innovative products and solutions to customers. Thus, Engineering curriculum in many schools, some collaboratively with business schools, have brought NPD into the curriculum at the graduate level. Teamwork is invariably used during instruction, where students work in teams to come up with new products and solutions. There is a significant emphasis of grade on the semester long teamwork for it to be taken seriously by students. As the students work in teams and go through this process to develop the new product prototypes, their effectiveness and learning to a great extent depends on how they function as a team and go through the creative process, come together, and work towards the common goal. A core attribute of a successful NPD team is their creativity and innovation. The team needs to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas resulting in a POC (proof-of-concept) implementation or a prototype of the product. The simultaneous requirement of teams to be creative and at the same time also converge and work together imposes different types of tensions in their team interactions. These ideational tensions / conflicts and sometimes relational tensions / conflicts are inevitable. Effective teams will have to deal with the Team dynamics and manage it to be resilient enough and yet be creative. This research paper provides a computational analysis of the teams’ communication that is reflective of the team dynamics, and through a superimposition of latent semantic analysis with social network analysis, provides a computational methodology of arriving at patterns of visual interaction. These team interaction patterns have clear correlations to the team dynamics and provide insights into the functioning and thus the effectiveness of the teams. 23 student NPD teams over 2 years of a course on Managing NPD that has a blend of engineering and business school students is considered, and the results are presented. It is also correlated with the teams’ detailed and tailored individual and group feedback and self-reflection and evaluation questionnaire.

Keywords: team dynamics, social network analysis, team interaction patterns, new product development teamwork, NPD teams

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38 Bridging Healthcare Information Systems and Customer Relationship Management for Effective Pandemic Response

Authors: Sharda Kumari

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As the Covid-19 pandemic continues to leave its mark on the global business landscape, companies have had to adapt to new realities and find ways to sustain their operations amid social distancing measures, government restrictions, and heightened public health concerns. This unprecedented situation has placed considerable stress on both employees and employers, underscoring the need for innovative approaches to manage the risks associated with Covid-19 transmission in the workplace. In response to these challenges, the pandemic has accelerated the adoption of digital technologies, with an increasing preference for remote interactions and virtual collaboration. Customer relationship management (CRM) systems have risen to prominence as a vital resource for organizations navigating the post-pandemic world, providing a range of benefits that include acquiring new customers, generating insightful consumer data, enhancing customer relationships, and growing market share. In the context of pandemic management, CRM systems offer three primary advantages: (1) integration features that streamline operations and reduce the need for multiple, costly software systems; (2) worldwide accessibility from any internet-enabled device, facilitating efficient remote workforce management during a pandemic; and (3) the capacity for rapid adaptation to changing business conditions, given that most CRM platforms boast a wide array of remotely deployable business growth solutions, a critical attribute when dealing with a dispersed workforce in a pandemic-impacted environment. These advantages highlight the pivotal role of CRM systems in helping organizations remain resilient and adaptive in the face of ongoing global challenges.

Keywords: healthcare, CRM, customer relationship management, customer experience, digital transformation, pandemic response, patient monitoring, patient management, healthcare automation, electronic health record, patient billing, healthcare information systems, remote workforce, virtual collaboration, resilience, adaptable business models, integration features, CRM in healthcare, telehealth, pandemic management

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37 Computational Pipeline for Lynch Syndrome Detection: Integrating Alignment, Variant Calling, and Annotations

Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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36 Numerical Investigation of Turbulent Flow Control by Suction and Injection on a Subsonic NACA23012 Airfoil by Proper Orthogonal Decomposition Analysis and Perturbed Reynolds Averaged Navier‐Stokes Equations

Authors: Azam Zare

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Separation flow control for performance enhancement over airfoils at high incidence angle has become an increasingly important topic. This work details the characteristics of an efficient feedback control of the turbulent subsonic flow over NACA23012 airfoil using forced reduced‐order model based on the proper orthogonal decomposition/Galerkin projection and perturbation method on the compressible Reynolds Averaged Navier‐Stokes equations. The forced reduced‐order model is used in the optimal control of the turbulent separated flow over a NACA23012 airfoil at Mach number of 0.2, Reynolds number of 5×106, and high incidence angle of 24° using blowing/suction controlling jets. The Spallart-Almaras turbulence model is implemented for high Reynolds number calculations. The main shortcoming of the POD/Galerkin projection on flow equations for controlling purposes is that the blowing/suction controlling jet velocity does not show up explicitly in the resulting reduced order model. Combining perturbation method and POD/Galerkin projection on flow equations introduce a forced reduced‐order model that can predict the time-varying influence of the blowing/suction controlling jet velocity. An optimal control theory based on forced reduced‐order system is used to design a control law for a nonlinear reduced‐order model, which attempts to minimize the vorticity content in the turbulent flow field over NACA23012 airfoil. Numerical simulations were performed to help understand the behavior of the controlled suction jet at 12% to 18% chord from leading edge and a pair of blowing/suction jets at 15% to 18% and 24% to 30% chord from leading edge, respectively. Analysis of streamline profiles indicates that the blowing/suction jets are efficient in removing separation bubbles and increasing the lift coefficient up to 22%, while the perturbation method can predict the flow field in an accurate Manner.

Keywords: flow control, POD, Galerkin projection, separation

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35 Navigating Disruption: Key Principles and Innovations in Modern Management for Organizational Success

Authors: Ahmad Haidar

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This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

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34 Web Development in Information Technology with Javascript, Machine Learning and Artificial Intelligence

Authors: Abdul Basit Kiani, Maryam Kiani

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Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

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33 The Pore–Scale Darcy–Brinkman–Stokes Model for the Description of Advection–Diffusion–Precipitation Using Level Set Method

Authors: Jiahui You, Kyung Jae Lee

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Hydraulic fracturing fluid (HFF) is widely used in shale reservoir productions. HFF contains diverse chemical additives, which result in the dissolution and precipitation of minerals through multiple chemical reactions. In this study, a new pore-scale Darcy–Brinkman–Stokes (DBS) model coupled with Level Set Method (LSM) is developed to address the microscopic phenomena occurring during the iron–HFF interaction, by numerically describing mass transport, chemical reactions, and pore structure evolution. The new model is developed based on OpenFOAM, which is an open-source platform for computational fluid dynamics. Here, the DBS momentum equation is used to solve for velocity by accounting for the fluid-solid mass transfer; an advection-diffusion equation is used to compute the distribution of injected HFF and iron. The reaction–induced pore evolution is captured by applying the LSM, where the solid-liquid interface is updated by solving the level set distance function and reinitialized to a signed distance function. Then, a smoothened Heaviside function gives a smoothed solid-liquid interface over a narrow band with a fixed thickness. The stated equations are discretized by the finite volume method, while the re-initialized equation is discretized by the central difference method. Gauss linear upwind scheme is used to solve the level set distance function, and the Pressure–Implicit with Splitting of Operators (PISO) method is used to solve the momentum equation. The numerical result is compared with 1–D analytical solution of fluid-solid interface for reaction-diffusion problems. Sensitivity analysis is conducted with various Damkohler number (DaII) and Peclet number (Pe). We categorize the Fe (III) precipitation into three patterns as a function of DaII and Pe: symmetrical smoothed growth, unsymmetrical growth, and dendritic growth. Pe and DaII significantly affect the location of precipitation, which is critical in determining the injection parameters of hydraulic fracturing. When DaII<1, the precipitation uniformly occurs on the solid surface both in upstream and downstream directions. When DaII>1, the precipitation mainly occurs on the solid surface in an upstream direction. When Pe>1, Fe (II) transported deeply into and precipitated inside the pores. When Pe<1, the precipitation of Fe (III) occurs mainly on the solid surface in an upstream direction, and they are easily precipitated inside the small pore structures. The porosity–permeability relationship is subsequently presented. This pore-scale model allows high confidence in the description of Fe (II) dissolution, transport, and Fe (III) precipitation. The model shows fast convergence and requires a low computational load. The results can provide reliable guidance for injecting HFF in shale reservoirs to avoid clogging and wellbore pollution. Understanding Fe (III) precipitation, and Fe (II) release and transport behaviors give rise to a highly efficient hydraulic fracture project.

Keywords: reactive-transport , Shale, Kerogen, precipitation

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32 Numerical Analysis of Charge Exchange in an Opposed-Piston Engine

Authors: Zbigniew Czyż, Adam Majczak, Lukasz Grabowski

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The paper presents a description of geometric models, computational algorithms, and results of numerical analyses of charge exchange in a two-stroke opposed-piston engine. The research engine was a newly designed internal Diesel engine. The unit is characterized by three cylinders in which three pairs of opposed-pistons operate. The engine will generate a power output equal to 100 kW at a crankshaft rotation speed of 3800-4000 rpm. The numerical investigations were carried out using ANSYS FLUENT solver. Numerical research, in contrast to experimental research, allows us to validate project assumptions and avoid costly prototype preparation for experimental tests. This makes it possible to optimize the geometrical model in countless variants with no production costs. The geometrical model includes an intake manifold, a cylinder, and an outlet manifold. The study was conducted for a series of modifications of manifolds and intake and exhaust ports to optimize the charge exchange process in the engine. The calculations specified a swirl coefficient obtained under stationary conditions for a full opening of intake and exhaust ports as well as a CA value of 280° for all cylinders. In addition, mass flow rates were identified separately in all of the intake and exhaust ports to achieve the best possible uniformity of flow in the individual cylinders. For the models under consideration, velocity, pressure and streamline contours were generated in important cross sections. The developed models are designed primarily to minimize the flow drag through the intake and exhaust ports while the mass flow rate increases. Firstly, in order to calculate the swirl ratio [-], tangential velocity v [m/s] and then angular velocity ω [rad / s] with respect to the charge as the mean of each element were calculated. The paper contains comparative analyses of all the intake and exhaust manifolds of the designed engine. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: computational fluid dynamics, engine swirl, fluid mechanics, mass flow rates, numerical analysis, opposed-piston engine

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31 Logistics and Supply Chain Management Using Smart Contracts on Blockchain

Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

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30 Predicting Daily Patient Hospital Visits Using Machine Learning

Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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29 Numerical Model of Crude Glycerol Autothermal Reforming to Hydrogen-Rich Syngas

Authors: A. Odoom, A. Salama, H. Ibrahim

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Hydrogen is a clean source of energy for power production and transportation. The main source of hydrogen in this research is biodiesel. Glycerol also called glycerine is a by-product of biodiesel production by transesterification of vegetable oils and methanol. This is a reliable and environmentally-friendly source of hydrogen production than fossil fuels. A typical composition of crude glycerol comprises of glycerol, water, organic and inorganic salts, soap, methanol and small amounts of glycerides. Crude glycerol has limited industrial application due to its low purity thus, the usage of crude glycerol can significantly enhance the sustainability and production of biodiesel. Reforming techniques is an approach for hydrogen production mainly Steam Reforming (SR), Autothermal Reforming (ATR) and Partial Oxidation Reforming (POR). SR produces high hydrogen conversions and yield but is highly endothermic whereas POR is exothermic. On the downside, PO yields lower hydrogen as well as large amount of side reactions. ATR which is a fusion of partial oxidation reforming and steam reforming is thermally neutral because net reactor heat duty is zero. It has relatively high hydrogen yield, selectivity as well as limits coke formation. The complex chemical processes that take place during the production phases makes it relatively difficult to construct a reliable and robust numerical model. Numerical model is a tool to mimic reality and provide insight into the influence of the parameters. In this work, we introduce a finite volume numerical study for an 'in-house' lab-scale experiment of ATR. Previous numerical studies on this process have considered either using Comsol or nodal finite difference analysis. Since Comsol is a commercial package which is not readily available everywhere and lab-scale experiment can be considered well mixed in the radial direction. One spatial dimension suffices to capture the essential feature of ATR, in this work, we consider developing our own numerical approach using MATLAB. A continuum fixed bed reactor is modelled using MATLAB with both pseudo homogeneous and heterogeneous models. The drawback of nodal finite difference formulation is that it is not locally conservative which means that materials and momenta can be generated inside the domain as an artifact of the discretization. Control volume, on the other hand, is locally conservative and suites very well problems where materials are generated and consumed inside the domain. In this work, species mass balance, Darcy’s equation and energy equations are solved using operator splitting technique. Therefore, diffusion-like terms are discretized implicitly while advection-like terms are discretized explicitly. An upwind scheme is adapted for the advection term to ensure accuracy and positivity. Comparisons with the experimental data show very good agreements which build confidence in our modeling approach. The models obtained were validated and optimized for better results.

Keywords: autothermal reforming, crude glycerol, hydrogen, numerical model

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28 Elevating Healthcare Social Work: Implementing and Evaluating the (Introduction, Subjective, Objective, Assessment, Plan, Summary) Documentation Model

Authors: Shir Daphna-Tekoah, Nurit Eitan-Gutman, Uri Balla

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Background: Systemic documentation is essential in social work practice. Collaboration between an institution of higher education and social work health care services enabled adaptation of the medical documentation model of SOAP in the field of social work, by creating the ISOAPS model (Introduction, Subjective, Objective, Assessment, Plan, Summary) model. Aims: The article describes the ISOAPS model and its implementation in the field of social work, as a tool for standardization of documentation and the enhancement of multidisciplinary collaboration. Methods: We examined the changes in standardization using a mixed methods study, both before and after implementation of the model. A review of social workers’ documentation was carried out by medical staff and social workers in the Clalit Healthcare Services, the largest provider of public and semi-private health services in Israel. After implementation of the model, semi-structured qualitative interviews were undertaken. Main findings: The percentage of reviewers who evaluated their documentation as correct increased from 46%, prior to implementation, to 61% after implementation. After implementation, 81% of the social workers noted that their documentation had become standardized. The training process prepared them for the change in documentation and most of them (83%) started using the model on a regular basis. The qualitative data indicate that the use of the ISOAPS model creates uniform documentation, improves standards and is important to teach social work students. Conclusions: The ISOAPS model standardizes documentation and promotes communication between social workers and medical staffs. Implications for practice: In the intricate realm of healthcare, efficient documentation systems are pivotal to ensuring coherent interdisciplinary communication and patient care. The ISOAPS model emerges as a quintessential instrument, meticulously tailored to the nuances of social work documentation. While it extends its utility across the broad spectrum of social work, its specificity is most pronounced in the medical domain. This model not only exemplifies rigorous academic and professional standards but also serves as a testament to the potential of contextualized documentation systems in elevating the overall stature of social work within healthcare. Such a strategic documentation tool can not only streamline the intricate processes inherent in medical social work but also underscore the indispensable role that social workers play in the broader healthcare ecosystem.

Keywords: ISOAPS, professional documentation, medial social-work, social work

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27 Virtual Screening and in Silico Toxicity Property Prediction of Compounds against Mycobacterium tuberculosis Lipoate Protein Ligase B (LipB)

Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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26 Liability of AI in Workplace: A Comparative Approach Between Shari’ah and Common Law

Authors: Barakat Adebisi Raji

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In the workplace, Artificial Intelligence has, in recent years, emerged as a transformative technology that revolutionizes how organizations operate and perform tasks. It is a technology that has a significant impact on transportation, manufacturing, education, cyber security, robotics, agriculture, healthcare, and so many other organizations. By harnessing AI technology, workplaces can enhance productivity, streamline processes, and make more informed decisions. Given the potential of AI to change the way we work and its impact on the labor market in years to come, employers understand that it entails legal challenges and risks despite the advantages inherent in it. Therefore, as AI continues to integrate into various aspects of the workplace, understanding the legal and ethical implications becomes paramount. Also central to this study is the question of who is held liable where AI makes any defaults; the person (company) who created the AI, the person who programmed the AI algorithm or the person who uses the AI? Thus, the aim of this paper is to provide a detailed overview of how AI-related liabilities are addressed under each legal tradition and shed light on potential areas of accord and divergence between the two legal cultures. The objectives of this paper are to (i) examine the ability of Common law and Islamic law to accommodate the issues and damage caused by AI in the workplace and the legality of compensation for such injury sustained; (ii) to discuss the extent to which AI can be described as a legal personality to bear responsibility: (iii) examine the similarities and disparities between Common Law and Islamic Jurisprudence on the liability of AI in the workplace. The methodology adopted in this work was qualitative, and the method was purely a doctrinal research method where information is gathered from the primary and secondary sources of law, such as comprehensive materials found in journal articles, expert-authored books and online news sources. Comparative legal method was also used to juxtapose the approach of Islam and Common Law. The paper concludes that since AI, in its current legal state, is not recognized as a legal entity, operators or manufacturers of AI should be held liable for any damage that arises, and the determination of who bears the responsibility should be dependent on the circumstances surrounding each scenario. The study recommends the granting of legal personality to AI systems, the establishment of legal rights and liabilities for AI, the establishment of a holistic Islamic virtue-based AI ethics framework, and the consideration of Islamic ethics.

Keywords: AI, health- care, agriculture, cyber security, common law, Shari'ah

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25 Assessing the Competence of Oral Surgery Trainees: A Systematic Review

Authors: Chana Pavneet

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Background: In more recent years in dentistry, a greater emphasis has been placed on competency-based education (CBE) programmes. Undergraduate and postgraduate curriculums have been reformed to reflect these changes, and adopting a CBE approach has shown to be beneficial to trainees and places an emphasis on continuous lifelong learning. The literature is vast; however, very little work has been done specifically to the assessment of competence in dentistry and even less so in oral surgery. The majority of the literature tends to opinion pieces. Some small-scale studies have been undertaken in this area researching assessment tools which can be used to assess competence in oral surgery. However, there is a lack of general consensus on the preferable assessment methods. The aim of this review is to identify the assessment methods available and their usefulness. Methods: Electronic databases (Medline, Embase, and the Cochrane Database of systematic reviews) were searched. PRISMA guidelines were followed to identify relevant papers. Abstracts of studies were reviewed, and if they met the inclusion criteria, they were included in the review. Papers were reviewed against the critical appraisal skills programme (CASP) checklist and medical education research quality instrument (MERQSI) to assess their quality and identify any bias in a systematic manner. The validity and reliability of each assessment method or tool were assessed. Results: A number of assessment methods were identified, including self-assessment, peer assessment, and direct observation of skills by someone senior. Senior assessment tended to be the preferred method, followed by self-assessment and, finally, peer assessment. The level of training was shown to affect the preferred assessment method, with one study finding peer assessment more useful in postgraduate trainees as opposed to undergraduate trainees. Numerous tools for assessment were identified, including a checklist scale and a global rating scale. Both had their strengths and weaknesses, but the evidence was more favourable for global rating scales in terms of reliability, applicability to more clinical situations, and easier to use for examiners. Studies also looked into trainees’ opinions on assessment tools. Logbooks were not found to be significant in measuring the competence of trainees. Conclusion: There is limited literature exploring the methods and tools which assess the competence of oral surgery trainees. Current evidence shows that the most favourable assessment method and tool may differ depending on the stage of training. More research is required in this area to streamline assessment methods and tools.

Keywords: competence, oral surgery, assessment, trainees, education

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24 Lean Implementation in a Nurse Practitioner Led Pediatric Primary Care Clinic: A Case Study

Authors: Lily Farris, Chantel E. Canessa, Rena Heathcote, Susan Shumay, Suzanna V. McRae, Alissa Collingridge, Minna K. Miller

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Objective: To describe how the Lean approach can be applied to improve access, quality and safety of care in an ambulatory pediatric primary care setting. Background: Lean was originally developed by Toyota manufacturing in Japan, and subsequently adapted for use in the healthcare sector. Lean is a systematic approach, focused on identifying and reducing waste within organizational processes, improving patient-centered care and efficiency. Limited literature is available on the implementation of the Lean methodologies in a pediatric ambulatory care setting. Methods: A strategic continuous improvement event or Rapid Process Improvement Workshop (RPIW) was launched with the aim evaluating and structurally supporting clinic workflow, capacity building, sustainability, and ultimately improving access to care and enhancing the patient experience. The Lean process consists of five specific activities: Current state/process assessment (value stream map); development of a future state map (value stream map after waste reduction); identification, quantification and prioritization of the process improvement opportunities; implementation and evaluation of process changes; and audits to sustain the gains. Staff engagement is a critical component of the Lean process. Results: Through the implementation of the RPIW and shifting workload among the administrative team, four hours of wasted time moving between desks and doing work was eliminated from the Administrative Clerks role. To streamline clinic flow, the Nursing Assistants completed patient measurements and vitals for Nurse Practitioners, reducing patient wait times and adding value to the patients visit with the Nurse Practitioners. Additionally, through the Nurse Practitioners engagement in the Lean processes a need was recognized to articulate clinic vision, mission and the alignment of NP role and scope of practice with the agency and Ministry of Health strategic plan. Conclusions: Continuous improvement work in the Pediatric Primary Care NP Clinic has provided a unique opportunity to improve the quality of care delivered and has facilitated further alignment of the daily continuous improvement work with the strategic priorities of the Ministry of Health.

Keywords: ambulatory care, lean, pediatric primary care, system efficiency

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23 Integrating Machine Learning and Rule-Based Decision Models for Enhanced B2B Sales Forecasting and Customer Prioritization

Authors: Wenqi Liu, Reginald Bailey

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This study proposes a comprehensive and effective approach to business-to-business (B2B) sales forecasting by integrating advanced machine learning models with a rule-based decision-making framework. The methodology addresses the critical challenge of optimizing sales pipeline performance and improving conversion rates through predictive analytics and actionable insights. The first component involves developing a classification model to predict the likelihood of conversion, aiming to outperform traditional methods such as logistic regression in terms of accuracy, precision, recall, and F1 score. Feature importance analysis highlights key predictive factors, such as client revenue size and sales velocity, providing valuable insights into conversion dynamics. The second component focuses on forecasting sales value using a regression model, designed to achieve superior performance compared to linear regression by minimizing mean absolute error (MAE), mean squared error (MSE), and maximizing R-squared metrics. The regression analysis identifies primary drivers of sales value, further informing data-driven strategies. To bridge the gap between predictive modeling and actionable outcomes, a rule-based decision framework is introduced. This model categorizes leads into high, medium, and low priorities based on thresholds for conversion probability and predicted sales value. By combining classification and regression outputs, this framework enables sales teams to allocate resources effectively, focus on high-value opportunities, and streamline lead management processes. The integrated approach significantly enhances lead prioritization, increases conversion rates, and drives revenue generation, offering a robust solution to the declining pipeline conversion rates faced by many B2B organizations. Our findings demonstrate the practical benefits of blending machine learning with decision-making frameworks, providing a scalable, data-driven solution for strategic sales optimization. This study underscores the potential of predictive analytics to transform B2B sales operations, enabling more informed decision-making and improved organizational outcomes in competitive markets.

Keywords: machine learning, XGBoost, regression, decision making framework, system engineering

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22 Evolution of Web Development Progress in Modern Information Technology

Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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21 Semi-Autonomous Surgical Robot for Pedicle Screw Insertion on ex vivo Bovine Bone: Improved Workflow and Real-Time Process Monitoring

Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang

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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.

Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow

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20 Criteria to Access Justice in Remote Criminal Trial Implementation

Authors: Inga Žukovaitė

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This work aims to present postdoc research on remote criminal proceedings in court in order to streamline the proceedings and, at the same time, ensure the effective participation of the parties in criminal proceedings and the court's obligation to administer substantive and procedural justice. This study tests the hypothesis that remote criminal proceedings do not in themselves violate the fundamental principles of criminal procedure; however, their implementation must ensure the right of the parties to effective legal remedies and a fair trial and, only then, must address the issues of procedural economy, speed and flexibility/functionality of the application of technologies. In order to ensure that changes in the regulation of criminal proceedings are in line with fair trial standards, this research will provide answers to the questions of what conditions -first of all, legal and only then organisational- are required for remote criminal proceedings to ensure respect for the parties and enable their effective participation in public proceedings, to create conditions for quality legal defence and its accessibility, to give a correct impression to the party that they are heard and that the court is impartial and fair. It also seeks to present the results of empirical research in the courts of Lithuania that was made by using the interview method. The research will serve as a basis for developing a theoretical model for remote criminal proceedings in the EU to ensure a balance between the intention to have innovative, cost-effective, and flexible criminal proceedings and the positive obligation of the State to ensure the rights of participants in proceedings to just and fair criminal proceedings. Moreover, developments in criminal proceedings also keep changing the image of the court itself; therefore, in the paper will create preconditions for future research on the impact of remote criminal proceedings on the trust in courts. The study aims at laying down the fundamentals for theoretical models of a remote hearing in criminal proceedings and at making recommendations for the safeguarding of human rights, in particular the rights of the accused, in such proceedings. The following criteria are relevant for the remote form of criminal proceedings: the purpose of judicial instance, the legal position of participants in proceedings, their vulnerability, and the nature of required legal protection. The content of the study consists of: 1. Identification of the factual and legal prerequisites for a decision to organise the entire criminal proceedings by remote means or to carry out one or several procedural actions by remote means 2. After analysing the legal regulation and practice concerning the application of the elements of remote criminal proceedings, distinguish the main legal safeguards for protection of the rights of the accused to ensure: (a) the right of effective participation in a court hearing; (b) the right of confidential consultation with the defence counsel; (c) the right of participation in the examination of evidence, in particular material evidence, as well as the right to question witnesses; and (d) the right to a public trial.

Keywords: remote criminal proceedings, fair trial, right to defence, technology progress

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19 Smart Contracts: Bridging the Divide Between Code and Law

Authors: Abeeb Abiodun Bakare

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The advent of blockchain technology has birthed a revolutionary innovation: smart contracts. These self-executing contracts, encoded within the immutable ledger of a blockchain, hold the potential to transform the landscape of traditional contractual agreements. This research paper embarks on a comprehensive exploration of the legal implications surrounding smart contracts, delving into their enforceability and their profound impact on traditional contract law. The first section of this paper delves into the foundational principles of smart contracts, elucidating their underlying mechanisms and technological intricacies. By harnessing the power of blockchain technology, smart contracts automate the execution of contractual terms, eliminating the need for intermediaries and enhancing efficiency in commercial transactions. However, this technological marvel raises fundamental questions regarding legal enforceability and compliance with traditional legal frameworks. Moving beyond the realm of technology, the paper proceeds to analyze the legal validity of smart contracts within the context of traditional contract law. Drawing upon established legal principles, such as offer, acceptance, and consideration, we examine the extent to which smart contracts satisfy the requirements for forming a legally binding agreement. Furthermore, we explore the challenges posed by jurisdictional issues as smart contracts transcend physical boundaries and operate within a decentralized network. Central to this analysis is the examination of the role of arbitration and dispute resolution mechanisms in the context of smart contracts. While smart contracts offer unparalleled efficiency and transparency in executing contractual terms, disputes inevitably arise, necessitating mechanisms for resolution. We investigate the feasibility of integrating arbitration clauses within smart contracts, exploring the potential for decentralized arbitration platforms to streamline dispute resolution processes. Moreover, this paper explores the implications of smart contracts for traditional legal intermediaries, such as lawyers and judges. As smart contracts automate the execution of contractual terms, the role of legal professionals in contract drafting and interpretation may undergo significant transformation. We assess the implications of this paradigm shift for legal practice and the broader legal profession. In conclusion, this research paper provides a comprehensive analysis of the legal implications surrounding smart contracts, illuminating the intricate interplay between code and law. While smart contracts offer unprecedented efficiency and transparency in commercial transactions, their legal validity remains subject to scrutiny within traditional legal frameworks. By navigating the complex landscape of smart contract law, we aim to provide insights into the transformative potential of this groundbreaking technology.

Keywords: smart-contracts, law, blockchain, legal, technology

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18 Poster for Sickle Cell Disease and Barriers to Care in South Yorkshire from 2017 to 2023

Authors: Amardass Dhami, Clare Samuelson

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Background: Sickle cell disease (SCD) is a complex, multisystem condition that significantly impacts patients' quality of life, characterized by acute illness episodes, progressive organ damage, and reduced life expectancy. In the UK, over 13,000 individuals are affected, with South Yorkshire having the fifth highest prevalence, including approximately 800 patients. Retinal complications in SCD can manifest as either proliferative or non-proliferative disease, with proliferative changes being more prevalent. These retinal issues can cause significant morbidity, including visual loss and increased care requirements, underscoring the need for regular monitoring. An integrated approach was applied to ensure timely interventions, ultimately enhancing patient outcomes and reduce ‘did not attend’ rates. Aim: To assess the factors which may influence attendance to Haematology and Ophthalmology Clinics with attention towards levels of deprivation towards non-attendance. Method : A retrospective study on 84 eligible patients, from the regional tertiary Centre for Sickle Cell Care (Sheffield Teaching Hospital) from 2017 to 2023. The study focused on the incidence of sickle cell eye disease, specifically examining the outcomes of patients who attended the combined haematology and ophthalmology clinics. Patients who did not attend either clinic were excluded from the analysis to ensure a clear understanding of the combined clinic's impact. This data was then compared with the United Kingdom’s Index of Multiple Deprivation (IMD) datasets to assess if inequalities of care affected this population. Results: The study concluded that the effectiveness of combining haematology and ophthalmology clinics was reduced following the intervention. The DNA rates increased to 40% for the haematology clinic. Additionally, a significant proportion of the cohort was classified as residing in areas of deprivation, suggesting a possible link between socioeconomic factors and non-attendance rates Conclusion: These findings underscore the challenges of integrating care for SCD patients, particularly in relation to socioeconomic barriers. Despite the intent to streamline care and improve patient outcomes, the increase in DNA rates points to the need for further investigation into the underlying causes of non-attendance. Addressing these issues, especially in deprived areas, could enhance the effectiveness of combined clinics and ensure that patients receive the necessary monitoring and interventions for their eye health and overall well-being. Future strategies may need to focus on improving accessibility, outreach, and support for patients to mitigate the impact of socioeconomic factors on healthcare attendance.

Keywords: south yorkshire, sickle cell anemia, deprivation, factors, haematology

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17 The Strategic Gas Aggregator: A Key Legal Intervention in an Evolving Nigerian Natural Gas Sector

Authors: Olanrewaju Aladeitan, Obiageli Phina Anaghara-Uzor

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Despite the abundance of natural gas deposits in Nigeria and the immense potential, this presents both for the domestic and export oriented revenue, there exists an imbalance in the preference for export as against the development and optimal utilization of natural gas for the domestic industry. Considerable amounts of gas are still being wasted by flaring in the country to this day. Although the government has set in place initiatives to harness gas at the flare and thereby reduce volumes flared, the gas producers would rather direct the gas produced to the export market whereas gas apportioned to the domestic market is often marred by the low domestic gas price which is often discouraging to the gas producers. The exported fraction of gas production no doubt yields healthy revenues for the government and an encouraging return on investment for the gas producers and for this reason export sales remain enticing and preferable to the domestic sale of gas. This export pull impacts negatively if left unchecked, on the domestic market which is in no position to match the price at the international markets. The issue of gas price remains critical to the optimal development of the domestic gas industry, in that it comprises the basis for investment decisions of the producers on the allocation of their scarce resources and to what project to channel their output in order to maximize profit. In order then to rebalance the domestic industry and streamline the market for gas, the Gas Aggregation Company of Nigeria, also known as the Strategic Aggregator was proposed under the Nigerian Gas Master Plan of 2008 and then established pursuant to the National Gas Supply and Pricing Regulations of 2008 to implement the domestic gas supply obligation which focuses on ramping-up gas volumes for domestic utilization by mandatorily requiring each gas producer to dedicate a portion of its gas production for domestic utilization before having recourse to the export market. The 2008 Regulations further stipulate penalties in the event of non-compliance. This study, in the main, assesses the adequacy of the legal framework for the Nigerian Gas Industry, given that the operational laws are structured more for oil than its gas counterpart; examine the legal basis for the Strategic Aggregator in the light of the Domestic Gas Supply and Pricing Policy 2008 and the National Domestic Gas Supply and Pricing Regulations 2008 and makes a case for a review of the pivotal role of the Aggregator in the Nigerian Gas market. In undertaking this assessment, the doctrinal research methodology was adopted. Findings from research conducted reveal the reawakening of the Federal Government to the immense potential of its gas industry as a critical sector of its economy and the need for a sustainable domestic natural gas market. A case for the review of the ownership structure of the Aggregator to comprise a balanced mix of the Federal Government, gas producers and other key stakeholders in order to ensure the effective implementation of the domestic supply obligations becomes all the more imperative.

Keywords: domestic supply obligations, natural gas, Nigerian gas sector, strategic gas aggregator

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16 Process Safety Management Digitalization via SHEQTool based on Occupational Safety and Health Administration and Center for Chemical Process Safety, a Case Study in Petrochemical Companies

Authors: Saeed Nazari, Masoom Nazari, Ali Hejazi, Siamak Sanoobari Ghazi Jahani, Mohammad Dehghani, Javad Vakili

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More than ever, digitization is an imperative for businesses to keep their competitive advantages, foster innovation and reduce paperwork. To design and successfully implement digital transformation initiatives within process safety management system, employees need to be equipped with the right tool, frameworks, and best practices. we developed a unique full stack application so-called SHEQTool which is entirely dynamic based on our extensive expertise, experience, and client feedback to help business processes particularly operations safety management. We use our best knowledge and scientific methodologies published by CCPS and OSHA Guidelines to streamline operations and integrated them into task management within Petrochemical Companies. We digitalize their main process safety management system elements and their sub elements such as hazard identification and risk management, training and communication, inspection and audit, critical changes management, contractor management, permit to work, pre-start-up safety review, incident reporting and investigation, emergency response plan, personal protective equipment, occupational health, and action management in a fully customizable manner with no programming needs for users. We review the feedback from main actors within petrochemical plant which highlights improving their business performance and productivity as well as keep tracking their functions’ key performance indicators (KPIs) because it; 1) saves time, resources, and costs of all paperwork on our businesses (by Digitalization); 2) reduces errors and improve performance within management system by covering most of daily software needs of the organization and reduce complexity and associated costs of numerous tools and their required training (One Tool Approach); 3) focuses on management systems and integrate functions and put them into traceable task management (RASCI and Flowcharting); 4) helps the entire enterprise be resilient to any change of your processes, technologies, assets with minimum costs (through Organizational Resilience); 5) reduces significantly incidents and errors via world class safety management programs and elements (by Simplification); 6) gives the companies a systematic, traceable, risk based, process based, and science based integrated management system (via proper Methodologies); 7) helps business processes complies with ISO 9001, ISO 14001, ISO 45001, ISO 31000, best practices as well as legal regulations by PDCA approach (Compliance).

Keywords: process, safety, digitalization, management, risk, incident, SHEQTool, OSHA, CCPS

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15 Progress Towards Optimizing and Standardizing Fiducial Placement Geometry in Prostate, Renal, and Pancreatic Cancer

Authors: Shiva Naidoo, Kristena Yossef, Grimm Jimm, Mirza Wasique, Eric Kemmerer, Joshua Obuch, Anand Mahadevan

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Background: Fiducial markers effectively enhance tumor target visibility prior to Stereotactic Body Radiation Therapy or Proton therapy. To streamline clinical practice, fiducial placement guidelines from a robotic radiosurgery vendor were examined with the goals of optimizing and standardizing feasible geometries for each treatment indication. Clinical examples of prostate, renal, and pancreatic cases are presented. Methods: Vendor guidelines (Accuray, Sunnyvale, Ca) suggest implantation of 4–6 fiducials at least 20 mm apart, with at least a 15-degree angular difference between fiducials, within 50 mm or less from the target centroid, to ensure that any potential fiducial motion (e.g., from respiration or abdominal/pelvic pressures) will mimic target motion. Also recommended is that all fiducials can be seen in 45-degree oblique views with no overlap to coincide with the robotic radiosurgery imaging planes. For the prostate, a standardized geometry that meets all these objectives is a 2 cm-by-2 cm square in the coronal plane. The transperineal implant of two pairs of preloaded tandem fiducials makes the 2 cm-by-2 cm square geometry clinically feasible. This technique may be applied for renal cancer, except repositioned in a sagittal plane, with the retroperitoneal placement of the fiducials into the tumor. Pancreatic fiducial placement via endoscopic ultrasound (EUS) is technically more challenging, as fiducial placement is operator-dependent, and lesion access may be limited by adjacent vasculature, tumor location, or restricted mobility of the EUS probe in the duodenum. Fluoroscopically assisted fiducial placement during EUS can help ensure fiducial markers are deployed with optimal geometry and visualization. Results: Among the first 22 fiducial cases on a newly installed robotic radiosurgery system, live x-ray images for all nine prostatic cases had excellent fiducial visualization at the treatment console. Renal and pancreatic fiducials were not as clearly visible due to difficult target access and smaller caliber insertion needle/fiducial usage. The geometry of the first prostate case was used to ensure accurate geometric marker placement for the remaining 8 cases. Initially, some of the renal and pancreatic fiducials were closer than the 20 mm recommendation, and interactive feedback with the proceduralists led to subsequent fiducials being too far to the edge of the tumor. Further feedback and discussion of all cases are being used to help guide standardized geometries and achieve ideal fiducial placement. Conclusion: The ideal tradeoffs of fiducial visibility versus the thinnest possible gauge needle to avoid complications needs to be systematically optimized among all patients, particularly in regards to body habitus. Multidisciplinary collaboration among proceduralists and radiation oncologists can lead to improved outcomes.

Keywords: fiducial, prostate cancer, renal cancer, pancreatic cancer, radiotherapy

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