Search results for: driven piles

Authors: Monique de Ritter, Annemieke Roobeek

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This study takes a holistic multi-layered systems approach on entrepreneurship, innovation, and sustainability. Concretely we looked how mission driven entrepreneurs (level 1) employ new business models and launch innovative products and/or ideas in their enterprises, which are (level 2) operating in entrepreneurial ecosystems (level 3), and how these in turn may generate higher level sustainable change (level 4). We employed a qualitative grounded research approach in which our aim is to contribute to theory. Fourteen in-depth semi-structured interviews were conducted with mission driven entrepreneurs in the Netherlands in which their individual drives, business models, and ecosystems were discussed. Interview transcripts were systematically coded and analysed and the ecosystems were visually mapped. Most important patterns include 1) entrepreneurs have a clear sustainable mission and regard this mission as de raison d’être of their enterprise; 2) entrepreneurs employ new business models with a focus on collaboration for innovation; the business model supports or enhances the sustainable mission of the enterprise, 3) entrepreneurs collaborate in ecosystems in which a) they also regard suppliers as partners for innovation and clients as ambassadors for the sustainable mission, b) would like to improve their relationships with financial institutions as they are in the entrepreneurs’ perspective often lagging behind with their innovative ideas and models, c) they collaborate for knowledge and innovation with several parties, d) personal informal connections are very important, and e) in which the higher sustainable mission is not a point of competition but of collaboration.

Keywords: sustainability, entrepreneurship, innovation, ecosystem, business models

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Authors: Kwaku Damoah

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This study presents a comprehensive data-driven analysis to understand the evolution of adverse events (AEs) in pharmacovigilance. Utilizing data from the FDA Adverse Event Reporting System (FAERS), we employed three analytical methods: rank-based, frequency-based, and percentage change analyses. These methods assessed temporal trends and patterns in AE reporting, focusing on various drug-active ingredients and patient demographics. Our findings reveal significant trends in AE occurrences, with both increasing and decreasing patterns from 2000 to 2023. This research highlights the importance of continuous monitoring and advanced analysis in pharmacovigilance, offering valuable insights for healthcare professionals and policymakers to enhance drug safety.

Keywords: event analysis, FDA adverse event reporting system, pharmacovigilance, temporal trend analysis

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Authors: Beatrice Eyram Afi Ziorklui, Norihisa Shima

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Community Driven Development (CDD) is now a widely recommended and accepted development strategy for informal communities across the continent. Centered on the utilization of social capital through community structures, different informal settlements have different structures and different levels of social capital, which affect the implementation and ability to overcome CDD challenges. Although known to be very successful, there are few perspectives on the implementation of CDD initiatives in different informal settlements. This study assesses the implementation of CDD initiatives in migrant and indigenous informal settlements and their ability to navigate challenges. The case study research design was adopted in this research, and respondents were chosen through simple random sampling. Using the Statistical Package for social scientists (SPSS) for data analysis, the study found that migrant informal settlements implement CDD projects through the network of hierarchical structures based on government systems, whereas indigenous informal settlements implement through the hierarchical social structure based on traditions and culture. The study also found that, with the exception of the challenge of land accessibility in migrant informal settlements, all other challenges, such as participation, resource mobilization, and maintenance, have a significant relationship with social capital, although indigenous informal settlements have higher levels of social capital than migrant informal settlements. The study recommends a framework that incorporates community characteristics and the underlying social capital to facilitate upgrading strategies in informal in Ghana.

Keywords: community driven development, informal settlements, social capital, upgrading

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Authors: Martin Bugeja, Helen Spiropolos

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Using a sample of U.S. firms during the period 1993-2015, this study examines whether mergers and acquisitions (M&A) impact the compensation of the Chief Financial Officer (CFO) in the bidding and integration phases of M&As. The study finds that after controlling for CEO power, CFOs’ total compensation is higher during M&A years and is driven by higher equity incentives. These results are robust to controlling for self-selection. Furthermore, CFOs receive a greater bonus during the year of acquisition and the year prior. The study also investigates if CFO compensation during M&A years is driven by M&A characteristics and finds that deal size and diversification are positively related to total compensation while completion time is negatively related. The results are robust to a number of sensitivity tests and additional analyses.

Keywords: chief financial officer, compensation, mergers, acquisitions

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Authors: P. K. Purohit, Azad A. Mansoori, Parvaiz A. Khan, Purushottam Bhawre, Sharad C. Tripathi, A. M. Aslam, Malik A. Waheed, Shivangi Bhardwaj, A. K. Gwal

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The geomagnetic storm represents the most outstanding example of solar wind-magnetospheric interaction, which causes global disturbances in the geomagnetic field as well as the trigger ionospheric disturbances. We study the behaviour of ionospheric Total Electron Content (TEC) during the geomagnetic storms. For the present investigation we have selected 47 intense geomagnetic storms (Dst ≤ -100nT) that were observed during the solar cycle 23 i.e. during 1998-2006. We then categorized these storms into four categories depending upon their solar sources like Magnetic Cloud (MC), Co-rotating Interaction Region (CIR), SH+ICME and SH+MC. We then studied the behaviour of ionospheric TEC at a mid latitude station Usuda (36.13N, 138.36E), Japan during these storm events produced by four different solar sources. During our study we found that the smooth variations in TEC are replaced by rapid fluctuations and the value of TEC is strongly enhanced during the time of these storms belonging to all the four categories. However, the greatest enhancements in TEC are produced during those geomagnetic storms which are either caused by sheath driven magnetic cloud (SH+MC) or sheath driven ICME (SH+ICME). We also derived the correlation between the TEC enhancements produced during storms of each category with the minimum Dst. We found the strongest correlation exists for the SH+ICME category followed by SH+MC, MC and finally CIR. Since the most intense storms were either caused by SH+ICME or SH+MC while the least intense storms were caused by CIR, consequently the correlation was the strongest with SH+ICME and SH+MC and least with CIR.

Keywords: GPS, TEC, geomagnetic storm, sheath driven magnetic cloud

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Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

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Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

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Authors: Navid P Roodaki, Rochelle Abila, Daisy Evangeline Garcia

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Background and Objective: Respiratory Distress Syndrome (RDS) among premature infants is a major causes of neonatal death. The use of Continuous Positive Airway Pressure (CPAP) has become a standard of care for preterm newborns with RDS hence cost-effective innovations are needed. This study compared a novel low-cost Bubble CPAP (bCPAP) device to ventilator driven CPAP in the treatment of RDS. Methods: This is a single-blind, randomized controlled trial done on May 2022 to October 2022 in a Level III Neonatal Intensive Care Unit in the Philippines. Preterm newborns (<36 weeks) with RDS were randomized to receive Vayu bCPAP device or Ventilator-derived CPAP. Arterial Blood Gases, Oxygen Saturation, administration of surfactant, and CPAP failure rates were measured. Results: Seventy preterm newborns were included. No differences were observed between the Ventilator driven CPAP and Vayu bCPAP on the PaO2 (97.51mmHg vs 97.37mmHg), So2 (97.08% vs 95.60%) levels, amount of surfactant administered between groups. There were no observed differences in CPAP failure rates between Vayu bPCAP (x̄ 3.23 days) and ventilator-driven CPAP (x̄ 2.98 days). However, a significant difference was noted on the CO2 level (40.32mmHg vs 50.70mmHg), which was higher among those hooked to Ventilator-driven CPAP (p 0.004). Conclusion: This study has shown that the novel low-cost bubble CPAP (Vayu bCPAP) can be used as an efficacious alternate non invasive oxygen therapy among preterm neonates with RDS, although the CO2 levels were higher among those hooked to ventilator driven CPAP, other outcome parameters measured showed that both devices are comparable. Recommendation: A multi-center or national study to account for geographic region, which may alter the outcomes of patients connected to different ventilatory support. Cost comparison between devices is also suggested. A mixed-method research assessing the experiences of health care professionals in assembling and utilizing the gadget is a second consideration.

Keywords: bubble CPAP, ventilator-derived CPAP; infant, premature, respiratory distress syndrome

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Authors: Muhammad Tariq Chaudhary

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Bridges constitute a vital link in a transportation system and their functionality after an earthquake is critical in reducing disruption to social and economic activities of the society. Bridges supported on pile foundations are commonly used in many earthquake-prone regions. In order to properly design or investigate the performance of such structures, it is imperative that the effect of soil-foundation-structure interaction be properly taken into account. This study focused on the influence of soil and seismic ground motion variability on the dynamic impedance of pile-group foundations typically used for medium-span (about 30 m) urban viaduct bridges. Soil profiles corresponding to various AASHTO soil classes were selected from actual data of such bridges and / or from the literature. The selected soil profiles were subjected to 1-D wave propagation analysis to determine effective values of soil shear modulus and damping ratio for a suite of properly selected actual seismic ground motions varying in PGA from 0.01g to 0.64g, and having variable velocity and frequency content. The effective values of the soil parameters were then employed to determine the dynamic impedance of pile groups in horizontal, vertical and rocking modes in various soil profiles. Pile diameter was kept constant for bridges in various soil profiles while pile length and number of piles were changed based on AASHTO design requirements for various soil profiles and earthquake ground motions. Conclusions were drawn regarding variability in effective soil shear modulus, soil damping, shear wave velocity and pile group impedance for various soil profiles and ground motions and its implications for design and evaluation of pile-supported bridges. It was found that even though the effective soil parameters underwent drastic variation with increasing PGA, the pile group impedance was not affected much in properly designed pile foundations due to the corresponding increase in pile length or increase in a number of piles or both when subjected to increasing PGA or founded in weaker soil profiles.

Keywords: bridge, pile foundation, dynamic foundation impedance, soil profile, shear wave velocity, seismic ground motion, seismic wave propagation

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Authors: Badiy Elmabrouk, Abdelhamid Boujarif, Zhiguo Zeng, Stephane Borrel, Robert Heidsieck

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In an era where sustainability is paramount, this paper introduces a machine learning-driven testing protocol to accurately predict diode failures, merging reliability engineering with failure physics to enhance repair operations efficiency. Our approach refines the burn-in process, significantly curtailing its duration, which not only conserves energy but also elevates productivity and mitigates component wear. A case study from GE HealthCare’s repair center vividly demonstrates the method’s effectiveness, recording a high prediction of diode failures and a substantial decrease in energy consumption that translates to an annual reduction of 6.5 Tons of CO2 emissions. This advancement sets a benchmark for environmentally conscious practices in the electronics repair sector.

Keywords: maintenance, burn-in, failure physics, reliability testing

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Glebert C. Dadol, Camila Flor Y. Lobarbio, Noel Peter B. Tan

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Water scarcity is a global problem. One of the promising solutions to this challenge is the use of membrane-based desalination technologies. In this study, a passive solar-driven membrane (PSDM) distillation was employed to test its desalination performance. The PSDM was fabricated using a TiNOX sheet solar absorber, cellulose-based hydrophilic top and bottom layers, and a middle layer. The effects of the middle layer material and thickness on the desalination performance in terms of distillate flow rate, productivity, and salinity were investigated. An air-gap screen mesh (2 mm, 4 mm, 6 mm thickness) and a hydrophobic PTFE membrane (0.3 mm thickness) were used as middle-layer materials. Saltwater input (35 g/L NaCl) was used for the PSDM distiller on a rooftop setting at the University of San Carlos, Cebu City, Philippines. The highest distillate flow rate and productivity of 1.08 L/m²-h and 1.47 L/kWh, respectively, were achieved using a 2 mm air-gap middle layer, but it also resulted in a high salinity of 25.20 g/L. Increasing the air gap lowered the salinity but also decreased the flow rate and productivity. The lowest salinity of 1.07 g/L was achieved using 6 mm air gap, but the flow rate and productivity were reduced to 0.08 L/m²-h and 0.17 L/kWh, respectively. The use of a hydrophobic PTFE membrane, on the other hand, did not offer a significant improvement in its performance. A PDSM distiller with a thick air gap as the middle layer can deliver a distillate with low salinity and is preferred over a thin hydrophobic PTFE membrane. Various modifications and optimizations to the distiller can be done to improve its performance further.

Keywords: desalination, membrane distillation, passive solar-driven membrane distiller, solar distillation

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Authors: Jackeline Kafie-Martinez, Peter B. Keating

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A three-dimensional finite element model is developed to capture the stress field generated in connected plates during the installation of hot-driven rivets. Clamping stress is generated when a steel rivet heated to approximately 1000 °C comes in contact with the material to be fastened at ambient temperature. As the rivet cools, thermal contraction subjects the rivet into tensile stress, while the material being fastened is subjected to compressive stress. Model characteristics and assumptions, as well as steel properties variation with respect to temperature are discussed. The thermal stresses developed around the rivet hole are assessed and reported. Results from the analysis are utilized to detect possible regions for fatigue crack propagation under cyclic loads.

Keywords: clamping stress, fatigue, finite elements, rivet, riveted railroad bridges

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Authors: Carlos Olave Lopez de Ayala

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The concept of purpose has generated a remarkable interest as a subject of study by the scientific community in recent years. However, most authors have studied it from an organizational point of view. Concepts such as purpose-driven organization and purpose management have been the focal point of numerous research studies, as well as of empirical implementation in some organizations. On the other hand, theories of motivation have been traditionally focused on the purpose of an individual and have been used to refer to personal motivation. This paper aims to study the influence of organizational purpose on the dimensions of human motivations, involving the meaning that each individual gives to his/her work. The results show that the person’s alignment with the organizational purpose is connected with the meaning of work as a career, a calling, and a higher calling. This research adds to the knowledge of the impact of the organizational purpose and its influence on individuals.

Keywords: human motivations, meaningful work, organizational purpose, purpose management, purpose-driven organization

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Authors: Zhao Pengcheng, Yin Siyuan

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Fintech is the new hot topic of the 21st century, a discipline that combines financial theory with computer modelling. It can provide both digital analysis methods for investment banks and investment decisions for users. Given the variety of services available, it is necessary to provide a superior method of requirements elicitation to ensure that users' needs are addressed in the software development process. The accuracy of traditional software requirements elicitation methods is not sufficient, so this study attempts to use a multi-perspective based requirements heuristic framework. Methods such as interview and questionnaire combination, card sorting, and model driven are proposed. The collection results from PCA show that the new methods can better help with requirements elicitation. However, the method has some limitations and, there are some efficiency issues. However, the research in this paper provides a good theoretical extension that can provide researchers with some new research methods and perspectives viewpoints.

Keywords: requirement elicitation, FinTech, mobile application, survey, interview, model-driven

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Akshay S. Dalvi, Hazim El-Mounayri

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The internal and the external interactions between the complex structural and behavioral characteristics of the complex energy system result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex energy systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering (MBSE). This paper mainly presents a MBSE driven approach to define and handle the complexity that arises due to emergent behaviors. The approach provides guidelines for developing system architecture that leverages in predicting the complexity index of the system at different levels of abstraction. A framework that integrates indefinite and definite modeling aspects is developed to determine the complexity that arises during the development phase of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. A system architecture for a district cooling plant is presented, which demonstrates the ability to predict the complexity index. The result suggests that complex energy systems like district cooling plant can be defined in an elegant manner using the unconventional modified MBSE driven approach that helps in estimating development time and cost.

Keywords: district cooling plant, energy systems, framework, MBSE

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Authors: Shiwei Deng, Yang Bao

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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: dependence analysis, EFSM model, greedy algorithm, regression test

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Authors: Bruno Coelho Lima, Joao F.A. Martos, Paulo G. P. Toro, Israel S. Rego

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The shock tube is a ground-facility widely used in aerospace and aeronautics science and technology for studies on gas dynamic and chemical-physical processes in gases at high-temperature, explosions and dynamic calibration of pressure sensors. A shock tube in its simplest form is comprised of two separate tubes of equal cross-section by a diaphragm. The diaphragm function is to separate the two reservoirs at different pressures. The reservoir containing high pressure is called the Driver, the low pressure reservoir is called Driven. When the diaphragm is broken by pressure difference, a normal shock wave and non-stationary (named Incident Shock Wave) will be formed in the same place of diaphragm and will get around toward the closed end of Driven. When this shock wave reaches the closer end of the Driven section will be completely reflected. Now, the shock wave will interact with the boundary layer that was created by the induced flow by incident shock wave passage. The interaction between boundary layer and shock wave force the separation of the boundary layer. The aim of this paper is to make an analysis of influences of separation of the boundary layer in the reservoir pressure in the shock tube. A comparison among CDF (Computational Fluids Dynamics), experiments test and analytical analysis were performed. For the analytical analysis, some routines in Python was created, in the numerical simulations (Computational Fluids Dynamics) was used the Ansys Fluent, and the experimental tests were used T1 shock tube located in IEAv (Institute of Advanced Studies).

Keywords: boundary layer separation, moving shock wave, shock tube, transient simulation

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: N. P. Yadav, Deepti Verma

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This paper focuses on the mathematical modeling for solidification of Al alloy in a cube mould cavity to study the solidification behavior of casting process. The parametric investigation of solidification process inside the cavity was performed by using computational solidification/melting model coupled with Volume of fluid (VOF) model. The implicit filling algorithm is used in this study to understand the overall process from the filling stage to solidification in a model metal casting process. The model is validated with past studied at same conditions. The solidification process are analyzed by including the effect of pouring velocity and temperature of liquid metal, effect of wall temperature as well natural convection from the wall and geometry of the cavity. These studies show the possibility of various defects during solidification process.

Keywords: buoyancy driven flow, natural convection driven flow, residual flow, secondary flow, volume of fluid

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Authors: Carole A. South-Winter

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Research-based learning gives students the opportunity to experience problems that require critical thinking and idea development. The skills they gain in working through these problems 'hands-on,' develop into attributes that benefit their careers in the professional field. The partnerships developed between students and industries give advantages to both sides. The students gain knowledge and skills that will increase their likelihood of success in the future and the industries are given research on new advancements that will give them a competitive advantage in their given field of work. The future of these partnerships is dependent on the success of current programs, enabling the enhancement and improvement of the research efforts. Once more students can complete research, there will be an increase in reliability of the results for each industry. The overall goal is to continue the support for research-based learning and the partnerships formed between students and industries.

Keywords: global healthcare, industry partnerships, research-driven decisions, short-term study abroad

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Authors: Olga Orynycz, Andrzej Wasiak

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Mathematical model describing energetic efficiency (defined as a ratio of energy obtained in the form of biofuel to the sum of energy inputs necessary to facilitate production) of agricultural subsystem as a function of technological parameters was developed. Production technology is characterized by parameters of machinery, topological characteristics of the plantation as well as transportation routes inside and outside of plantation. The relationship between the energetic efficiency of agricultural and industrial subsystems is also derived. Due to the assumed large area of the individual field, the operations last for several days increasing inter-fields routes because of several returns. The total distance driven outside of the fields is, however, small as compared to the distance driven inside of the fields. This results in small energy consumption during inter-fields transport that, however, causes a substantial decrease of the energetic effectiveness of the whole system.

Keywords: biofuel, energetic efficiency, EROEI, mathematical modelling, production system

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Authors: Soufiane Benoumhani, Nadia Saifi, Boubekeur Dokkar, Mohamed Cherif Benzid

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This work presents the design and simulation of electric equipment for a hybrid solar vehicle. The new drive train of this vehicle is a parallel hybrid system which means a vehicle driven by a great percentage of an internal combustion engine with 49.35 kW as maximal power and electric motor only as assistance when is needed. This assistance is carried out on the rear axle by a single electric motor of 7.22 kW as nominal power. The motor is driven by 12 batteries connecting in series, which are charged by three PV panels (300 W) installed on the roof and hood of the vehicle. The individual components are modeled and simulated by using the Matlab Simulink environment. The whole system is examined under different load conditions. The reduction of CO₂ emission is obtained by reducing fuel consumption. With the use of this hybrid system, fuel consumption can be reduced from 6.74 kg/h to 5.56 kg/h when the electric motor works at 100 % of its power. The net benefit of the system reaches 1.18 kg/h as fuel reduction at high values of power and torque.

Keywords: light car, hybrid system, PV panel, electric motor

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Authors: Seyed Abolhassan Naeini, Hamed Yekehdehghan

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Shallow foundations cannot be used when the bedding soil is soft. A suitable method for constructing foundations on soft soil is to employ pile groups to transfer the load to the bottom layers. The present research used results from tests carried out in northern Iran (Langarud) and the FLAC3D software to model a pile group for investigating the effects of various parameters on pile cap settlement under static and seismic conditions. According to the results, changes in the strength parameters of the soil, groundwater level, and the length of and distance between the piles affect settlement differently.

Keywords: FLACD 3D software, pile group, settlement, soil

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Authors: Andreas Jede, Frank Teuteberg

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Cloud computing (CC) has already gained overall appreciation in research and practice. Whereas the willingness to integrate cloud services in various IT environments is still unbroken, the previous CC procurement processes run mostly in an unorganized and non-standardized way. In practice, a sufficiently specific, yet applicable business process for the important acquisition phase is often lacking. And research does not appropriately remedy this deficiency yet. Therefore, this paper introduces a field-tested approach for CC procurement. Based on an extensive literature review and augmented by expert interviews, we designed a model that is validated and further refined through an in-depth real-life case study. For the detailed process description, we apply the event-driven process chain notation (EPC). The gained valuable insights into the case study may help CC research to shift to a more socio-technical area. For practice, next to giving useful organizational instructions we will provide extended checklists and lessons learned.

Keywords: cloud procurement process, IT-organization, event-driven process chain, in-depth case study

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Authors: Danni Cheng

Abstract:

Background: Preclinical and epidemiological studies have reported potential protective effects of low-density lipoprotein cholesterol (LDL-C) lowering drugs on head and neck squamous cell cancer (HNSCC) survival, but the causality was not consistent. Genetic variants associated with LDL-C lowering drug targets can predict the effects of their therapeutic inhibition on disease outcomes. Objective: We aimed to evaluate the causal association of genetically proxied cholesterol-lowering drug targets and circulating lipid traits with cancer survival in HNSCC patients stratified by human papillomavirus (HPV) status using two-sample Mendelian randomization (MR) analyses. Method: Single-nucleotide polymorphisms (SNPs) in gene region of LDL-C lowering drug targets (HMGCR, NPC1L1, CETP, PCSK9, and LDLR) associated with LDL-C levels in genome-wide association study (GWAS) from the Global Lipids Genetics Consortium (GLGC) were used to proxy LDL-C lowering drug action. SNPs proxy circulating lipids (LDL-C, HDL-C, total cholesterol, triglycerides, apoprotein A and apoprotein B) were also derived from the GLGC data. Genetic associations of these SNPs and cancer survivals were derived from 1,120 HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) and 2,570 non-HPV-driven HNSCC patients in VOYAGER program. We estimated the causal associations of LDL-C lowering drugs and circulating lipids with HNSCC survival using the inverse-variance weighted method. Results: Genetically proxied HMGCR inhibition was significantly associated with worse overall survival (OS) in non-HPV-drive HNSCC patients (inverse variance-weighted hazard ratio (HR IVW), 2.64[95%CI,1.28-5.43]; P = 0.01) but better OS in HPV-positive OPSCC patients (HR IVW,0.11[95%CI,0.02-0.56]; P = 0.01). Estimates for NPC1L1 were strongly associated with worse OS in both total HNSCC (HR IVW,4.17[95%CI,1.06-16.36]; P = 0.04) and non-HPV-driven HNSCC patients (HR IVW,7.33[95%CI,1.63-32.97]; P = 0.01). A similar result was found that genetically proxied PSCK9 inhibitors were significantly associated with poor OS in non-HPV-driven HNSCC (HR IVW,1.56[95%CI,1.02 to 2.39]). Conclusion: Genetically proxied long-term HMGCR inhibition was significantly associated with decreased OS in non-HPV-driven HNSCC and increased OS in HPV-positive OPSCC. While genetically proxied NPC1L1 and PCSK9 had associations with worse OS in total and non-HPV-driven HNSCC patients. Further research is needed to understand whether these drugs have consistent associations with head and neck tumor outcomes.

Keywords: Mendelian randomization analysis, head and neck cancer, cancer survival, cholesterol, statin

Procedia PDF Downloads 83

Authors: Lyndsey Kim

Abstract:

We utilized country-level data on suicide rates from 1985 through 2015 provided by the WHO to explore global trends as well as country-specific trends. First, we find that up until 1995, there was an increase in suicide rates globally, followed by a steep decline in deaths. This observation is largely driven by the data from Europe, where suicides are prominent but steadily declining. Second, men are more likely to commit suicide than women across the world over the years. Third, the older generation is more likely to commit suicide than youth and adults. Finally, we turn to Durkheim’s theory and use it as a lens to understand trends in suicide across time and countries and attempt to identify social and economic events that might explain patterns that we observe. For example, we discovered a drastically different pattern in suicide rates in the US, with a steep increase in suicides in the early 2000s. We hypothesize this might be driven by both the 9/11 attacks and the recession of 2008.

Keywords: suicide trends, current events, data analysis, world health organization, durkheim theory

Procedia PDF Downloads 75

Authors: Saad M. Darwish

Abstract:

Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

Procedia PDF Downloads 471

Authors: Saad M. Darwish

Abstract:

Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

Procedia PDF Downloads 506