Search results for: critical diagnostic distinctions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6193

Search results for: critical diagnostic distinctions

2293 Dissection of the Impact of Diabetes Type on Heart Failure across Age Groups: A Systematic Review of Publication Patterns on PubMed

Authors: Nazanin Ahmadi Daryakenari

Abstract:

Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

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2292 Sustainable Management Practices of International Construction Joint Ventures: A Conceptual Model for Managing Barriers and Risks

Authors: Mershack O. Tetteh, Albert P. C. Chan, Amos Darko, Gabriel Nani

Abstract:

International construction joint ventures (ICJVs) have evolved as an effective approach to sustainable development, given their myriad socio-economic and environmental benefits. Yet, they are not free of barriers and risks. In many studies, it is termed as risks for convenience’s sake. While the barriers and risks continue to affect the success of ICJVs, a systematic and reliable approach for managing them has yet to be developed. This study aims to identify and classify the barriers and risks factors affecting ICJVs through a systematic literature review. Based on a critical review of 54 papers published in peer-reviewed journals from 1990 to 2019, a conceptual framework was proposed for managing the barriers and risks in ICJV operations. The review showed that the barriers can be grouped into six including inter-organizational differences, lack of expertise and confidence, lack of effective planning and strategies, lack of knowledge of ICJV’s fundamentals, conflicts among ICJV entities, and management difficulties. The risks were also categorized into six: policy and political risks, legal risks, financial risks, management risks, project and technical risks, and market risks. The developed model would help practitioners achieve more efficient resource allocation and bring new perspectives for managerial practices in ICJVs. Moreover, it is positioned to alleviate the negligence of previous studies that combined the barriers and risks factors as one checklist.

Keywords: barriers, construction, international construction joint venture, risks, sustainable development

Procedia PDF Downloads 241
2291 Factors Influencing Soil Organic Carbon Storage Estimation in Agricultural Soils: A Machine Learning Approach Using Remote Sensing Data Integration

Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

Abstract:

The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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2290 A Collective Intelligence Approach to Safe Artificial General Intelligence

Authors: Craig A. Kaplan

Abstract:

If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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2289 Dispersions of Carbon Black in Microemulsions

Authors: Mohamed Youssry, Dominique Guyomard, Bernard Lestriez

Abstract:

In order to enhance the energy and power densities of electrodes for energy storage systems, the formulation and processing of electrode slurries proved to be a critical issue in determining the electrode performance. In this study, we introduce novel approach to formulate carbon black slurries based on microemulsion and lyotropic liquid crystalline phases (namely, lamellar phase) composed of non-ionic surfactant (Triton X100), decanol and water. Simultaneous measurements of electrical properties of slurries under shear flow (rheology) have been conducted to elucidate the microstructure evolution with the surfactant concentration and decanol/water ratio at rest, as well as, the structural transition under steady-shear which has been confirmed by rheo-microscopy. Interestingly, the carbon black slurries at low decanol/water ratio are weak-gel (flowable) with higher electrical conductivity than those at higher ratio which behave strong-gel viscoelastic response. In addition, the slurries show recoverable electrical behaviour under shear flow in tandem with the viscosity trend. It is likely that oil-in-water microemulsion enhances slurries’ stability without affecting on the percolating network of carbon black. On the other hand, the oil-in-water analogous and bilayer structure of lamellar phase cause the slurries less conductive as a consequence of losing the network percolation. These findings are encouraging to formulate microemulsion-based electrodes for energy storage system (lithium-ion batteries).

Keywords: electrode slurries, microemulsion, microstructure transition, rheo-electrical properties

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2288 Optimization of the Mechanical Performance of Fused Filament Fabrication Parts

Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

Abstract:

Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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2287 Optimization of Fused Deposition Modeling 3D Printing Process via Preprocess Calibration Routine Using Low-Cost Thermal Sensing

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

Abstract:

This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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2286 Probabilistic Models to Evaluate Seismic Liquefaction In Gravelly Soil Using Dynamic Penetration Test and Shear Wave Velocity

Authors: Nima Pirhadi, Shao Yong Bo, Xusheng Wan, Jianguo Lu, Jilei Hu

Abstract:

Although gravels and gravelly soils are assumed to be non-liquefiable because of high conductivity and small modulus; however, the occurrence of this phenomenon in some historical earthquakes, especially recently earthquakes during 2008 Wenchuan, Mw= 7.9, 2014 Cephalonia, Greece, Mw= 6.1 and 2016, Kaikoura, New Zealand, Mw = 7.8, has been promoted the essential consideration to evaluate risk assessment and hazard analysis of seismic gravelly soil liquefaction. Due to the limitation in sampling and laboratory testing of this type of soil, in situ tests and site exploration of case histories are the most accepted procedures. Of all in situ tests, dynamic penetration test (DPT), Which is well known as the Chinese dynamic penetration test, and shear wave velocity (Vs) test, have been demonstrated high performance to evaluate seismic gravelly soil liquefaction. However, the lack of a sufficient number of case histories provides an essential limitation for developing new models. This study at first investigates recent earthquakes that caused liquefaction in gravelly soils to collect new data. Then, it adds these data to the available literature’s dataset to extend them and finally develops new models to assess seismic gravelly soil liquefaction. To validate the presented models, their results are compared to extra available models. The results show the reasonable performance of the proposed models and the critical effect of gravel content (GC)% on the assessment.

Keywords: liquefaction, gravel, dynamic penetration test, shear wave velocity

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2285 Ranking of the Main Criteria for Contractor Selection Procedures on Major Construction Projects in Libya Using the Delphi Method

Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

Abstract:

The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organizations and is central to the success of any construction project. Contractor selection (CS) is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. However, this paper evaluates the current state of knowledge in relation to contractor selection process and demonstrates the findings from the analysis of the data collected from the Delphi questionnaire survey. The survey was conducted with a group of 12 experts working in the Libyan construction industry (LCI). The paper starts by briefly explaining the general outline of the questionnaire including the survey participation rate, the different fields the experts came from, and the business titles of the participants. Then, the paper describes the tests used to determine when the experts had reached consensus. The paper is based on research which aims to develop rank contractor selection criteria with specific application to make construction projects in the Libyan context. The findings of this study will be utilized to establish the scope of work that will be used as part of a PhD research.

Keywords: contractor selection, Libyan construction industry, decision experts, Delphi technique

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2284 Breaking the Barrier of Service Hostility: A Lean Approach to Achieve Operational Excellence

Authors: Mofizul Islam Awwal

Abstract:

Due to globalization, industries are rapidly growing throughout the world which leads to many manufacturing organizations. But recently, service industries are beginning to emerge in large numbers almost in all parts of the world including some developing countries. In this context, organizations need to have strong competitive advantage over their rivals to achieve their strategic business goals. Manufacturing industries are adopting many methods and techniques in order to achieve such competitive edge. Over the last decades, manufacturing industries have been successfully practicing lean concept to optimize their production lines. Due to its huge success in manufacturing context, lean has made its way into the service industry. Very little importance has been addressed to service in the area of operations management. Service industries are far behind than manufacturing industries in terms of operations improvement. It will be a hectic job to transfer the lean concept from production floor to service back/front office which will obviously yield possible improvement. Service processes are not as visible as production processes and can be very complex. Lack of research in this area made it quite difficult for service industries as there are no standardized frameworks for successfully implementing lean concept in service organization. The purpose of this research paper is to capture the present scenario of service industry in terms of lean implementation. Thorough analysis of past literature will be done on the applicability and understanding of lean in service structure. Classification of research papers will be done and critical factors will be unveiled for implementing lean in service industry to achieve operational excellence.

Keywords: lean service, lean literature classification, lean implementation, service industry, service excellence

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2283 Military Orchestrated Leadership Change in Zimbabwe and the Quest for Political Transition

Authors: Patrick Dzimiri

Abstract:

This chapter discusses the military-orchestrated leadership change in Zimbabwe that transpired in November 2017. Fundamentally, the chapter provides a critical examination of military interference in the country's politics and its implications for a political transition in the post-Mugabe dispensation. This chapter offers insight into Zimbabwe's political crises propelled by the lack of a succession plan. It emerged that the succession battle within ZANU-PF got complicated by the militarisation of factionalism. The chapter builds from an extensive review of primary and secondary data sources on political developments before and post-Mugabe era. Vilfredo Pareto's (1848-18923) theory on elite circulation is deployed herein to explain the absence of a succession mechanism within ZANU-PF and the militarisation of socio-politics life Zimbabwe. The chapter argues that what transpired in Zimbabwe’s power wrangle within the ZANU-PF political elites was triggered by a lack of a clear succession policy. Building from insights offered by Pareto's theory of elite circulation, it is averred that the removal of Mugabe by the military did not herald any form of political transition but rather a mere power play of one elite replacing another. In addition, it is argued that the lack of political reform by the Mnangagwa government affirms the position that political elites seek power for personal self-actualisation and not the public good. The chapter concludes that Mnangagwa's rise to power is nothing but a new elite displacing the old elite structure and does not herald a positive transition and transformation in the politics of Zimbabwe.

Keywords: military, politics, zimbabwe, governance, political transition

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2282 Partnership Oriented Innovation Alliance Strategy Based on Market Feedback

Authors: Victor Romanov, Daria Efimenko

Abstract:

The focus on innovation in modern economy is the main factor in surviving business in a competitive environment. The innovations are based on the search and use of knowledge in a global context. Nowadays consumers and market demand are the main innovation drivers. This leads to build a business as a system with feedback, promptly restructuring production and innovation implementation in response to market demands. In modern knowledge economy, because of speed of technical progress, the product's lifecycle became much shorter, what makes more stringent requirements for innovation implementation on the enterprises of and therefore the possibility for enterprise for receiving extra income is decreasing. This circumstance imposes additional requirements for the replacement of obsolete products and the prompt release of innovative products to the market. The development of information technologies has led to the fact that only in the conditions of partnership and knowledge sharing with partners it is possible to update products quickly for innovative products. Many companies pay attention to updating innovations through the search for new partners, but the task of finding new partners presents some difficulties. The search for a suitable one includes several stages such as: determining the moment of innovation-critical, introducing a search, identifying search criteria, justifying and deciding on the choice of a partner. No less important is the question of how to manage an innovative product in response to a changing market. The article considers the problems of information support for the search for the source of innovation and partnership to decrease the time for implementation of novelty products.

Keywords: partnership, novelty, market feedback, alliance

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2281 Springback Prediction for Sheet Metal Cold Stamping Using Convolutional Neural Networks

Authors: Lei Zhu, Nan Li

Abstract:

Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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2280 A Systematic Mapping of the Use of Information and Communication Technology (ICT)-Based Remote Agricultural Extension for Women Smallholders

Authors: Busiswa Madikazi

Abstract:

This systematic mapping study explores the underrepresentation of women's contributions to farming in the Global South within the development of Information and Communication Technologies (ICT)-based extension methods. Despite women farmers constituting 70% of the agricultural labour force, their productivity is hindered by various constraints, including illiteracy, household commitments, and limited access to credit and markets. A systematic mapping approach was employed with the aim of identifying evidence gaps in existing ICT extension for women farmers. The data collection protocol follows a structured approach, incorporating key criteria for inclusion, exclusion, search strategy, and coding and the PICO strategy (Population, Intervention, Comparator, and Outcome). The results yielded 119 articles that qualified for inclusion. The findings highlight that mobile phone apps (WhatsApp) and radio/television programming are the primary extension methods employed while integrating ICT with training, field visits, and demonstrations are underutilized. Notably, the study emphasizes the inadequate attention to critical issues such as food security, gender equality, and attracting youth to farming within ICT extension efforts. These findings indicate a significant policy and practice gap, neglecting community-driven approaches that cater to women's specific needs and enhance their agricultural production. Map highlights the importance of refocusing ICT extension efforts to address women farmers’ unique challenges, thereby contributing to their empowerment and improving agricultural practices.

Keywords: agricultural extension, ICT, women farmers, smallholders

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2279 The Factors Constitute the Interaction between Teachers and Students: An Empirical Study at the Notion of Framing

Authors: Tien-Hui Chiang

Abstract:

The code theory, proposed by Basil Bernstein, indicates that framing can be viewed as the core element in constituting the phenomenon of cultural reproduction because it is able to regulate the transmission of pedagogical information. Strong framing increases the social relation boundary between a teacher and pupils, which obstructs information transmission, so that in order to improve underachieving students’ academic performances, teachers need to reduce to strength of framing. Weak framing enables them to transform academic knowledge into commonsense knowledge in daily life language. This study posits that most teachers would deliver strong framing due to their belief mainly confined within the aspect of instrumental rationality that deprives their critical minds. This situation could make them view the normal distribution bell curve of students’ academic performances as a natural outcome. In order to examine the interplay between framing, instrumental rationality and pedagogical action, questionnaires were completed by over 5,000 primary school teachers in Henan province, China, who were stratified sample. The statistical results show that most teachers employed psychological concepts to measure students’ academic performances and, in turn, educational inequity was legitimatized as a natural outcome in the efficiency-led approach. Such efficiency-led minds made them perform as the agent practicing the mechanism of social control and in turn sustaining the phenomenon of cultural reproduction.

Keywords: code, cultural reproduction, framing, instrumental rationality, social relation and interaction

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2278 Advantages of Multispectral Imaging for Accurate Gas Temperature Profile Retrieval from Fire Combustion Reactions

Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

Abstract:

Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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2277 Pre-Cancerigene Injuries Related to Human Papillomavirus: Importance of Cervicography as a Complementary Diagnosis Method

Authors: Denise De Fátima Fernandes Barbosa, Tyane Mayara Ferreira Oliveira, Diego Jorge Maia Lima, Paula Renata Amorim Lessa, Ana Karina Bezerra Pinheiro, Cintia Gondim Pereira Calou, Glauberto Da Silva Quirino, Hellen Lívia Oliveira Catunda, Tatiana Gomes Guedes, Nicolau Da Costa

Abstract:

The aim of this study is to evaluate the use of Digital Cervicography (DC) in the diagnosis of precancerous lesions related to Human Papillomavirus (HPV). Cross-sectional study with a quantitative approach, of evaluative type, held in a health unit linked to the Pro Dean of Extension of the Federal University of Ceará, in the period of July to August 2015 with a sample of 33 women. Data collecting was conducted through interviews with enforcement tool. Franco (2005) standardized the technique used for DC. Polymerase Chain Reaction (PCR) was performed to identify high-risk HPV genotypes. DC were evaluated and classified by 3 judges. The results of DC and PCR were classified as positive, negative or inconclusive. The data of the collecting instruments were compiled and analyzed by the software Statistical Package for Social Sciences (SPSS) with descriptive statistics and cross-references. Sociodemographic, sexual and reproductive variables were analyzed through absolute frequencies (N) and their respective percentage (%). Kappa coefficient (κ) was applied to determine the existence of agreement between the DC of reports among evaluators with PCR and also among the judges about the DC results. The Pearson's chi-square test was used for analysis of sociodemographic, sexual and reproductive variables with the PCR reports. It was considered statistically significant (p<0.05). Ethical aspects of research involving human beings were respected, according to 466/2012 Resolution. Regarding the socio-demographic profile, the most prevalent ages and equally were those belonging to the groups 21-30 and 41-50 years old (24.2%). The brown color was reported in excess (84.8%) and 96.9% out of them had completed primary and secondary school or studying. 51.5% were married, 72.7% Catholic, 54.5% employed and 48.5% with income between one and two minimum wages. As for the sexual and reproductive characteristics, prevailed heterosexual (93.9%) who did not use condoms during sexual intercourse (72.7%). 51.5% had a previous history of Sexually Transmitted Infection (STI), and HPV the most prevalent STI (76.5%). 57.6% did not use contraception, 78.8% underwent examination Cancer Prevention Uterus (PCCU) with shorter time interval or equal to one year, 72.7% had no cases of Cervical Cancer in the family, 63.6% were multiparous and 97% were not vaccinated against HPV. DC identified good level of agreement between raters (κ=0.542), had a specificity of 77.8% and sensitivity of 25% when compared their results with PCR. Only the variable race showed a statistically significant association with CRP (p=0.042). DC had 100% acceptance amongst women in the sample, revealing the possibility of other experiments in using this method so that it proves as a viable technique. The DC positivity criteria were developed by nurses and these professionals also perform PCCU in Brazil, which means that DC can be an important complementary diagnostic method for the appreciation of these professional’s quality of examinations.

Keywords: gynecological examination, human papillomavirus, nursing, papillomavirus infections, uterine lasmsneop

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2276 Enhancing Quality Management Systems through Automated Controls and Neural Networks

Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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2275 Global Low Carbon Transitions in the Power Sector: A Machine Learning Archetypical Clustering Approach

Authors: Abdullah Alotaiq, David Wallom, Malcolm McCulloch

Abstract:

This study presents an archetype-based approach to designing effective strategies for low-carbon transitions in the power sector. To achieve global energy transition goals, a renewable energy transition is critical, and understanding diverse energy landscapes across different countries is essential to design effective renewable energy policies and strategies. Using a clustering approach, this study identifies 12 energy archetypes based on the electricity mix, socio-economic indicators, and renewable energy contribution potential of 187 UN countries. Each archetype is characterized by distinct challenges and opportunities, ranging from high dependence on fossil fuels to low electricity access, low economic growth, and insufficient contribution potential of renewables. Archetype A, for instance, consists of countries with low electricity access, high poverty rates, and limited power infrastructure, while Archetype J comprises developed countries with high electricity demand and installed renewables. The study findings have significant implications for renewable energy policymaking and investment decisions, with policymakers and investors able to use the archetype approach to identify suitable renewable energy policies and measures and assess renewable energy potential and risks. Overall, the archetype approach provides a comprehensive framework for understanding diverse energy landscapes and accelerating decarbonisation of the power sector.

Keywords: fossil fuels, power plants, energy transition, renewable energy, archetypes

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2274 Study of the Persian Gulf’s and Oman Sea’s Numerical Tidal Currents

Authors: Fatemeh Sadat Sharifi

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In this research, a barotropic model was employed to consider the tidal studies in the Persian Gulf and Oman Sea, where the only sufficient force was the tidal force. To do that, a finite-difference, free-surface model called Regional Ocean Modeling System (ROMS), was employed on the data over the Persian Gulf and Oman Sea. To analyze flow patterns of the region, the results of limited size model of The Finite Volume Community Ocean Model (FVCOM) were appropriated. The two points were determined since both are one of the most critical water body in case of the economy, biology, fishery, Shipping, navigation, and petroleum extraction. The OSU Tidal Prediction Software (OTPS) tide and observation data validated the modeled result. Next, tidal elevation and speed, and tidal analysis were interpreted. Preliminary results determine a significant accuracy in the tidal height compared with observation and OTPS data, declaring that tidal currents are highest in Hormuz Strait and the narrow and shallow region between Iranian coasts and Islands. Furthermore, tidal analysis clarifies that the M_2 component has the most significant value. Finally, the Persian Gulf tidal currents are divided into two branches: the first branch converts from south to Qatar and via United Arab Emirate rotates to Hormuz Strait. The secondary branch, in north and west, extends up to the highest point in the Persian Gulf and in the head of Gulf turns counterclockwise.

Keywords: numerical model, barotropic tide, tidal currents, OSU tidal prediction software, OTPS

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2273 How Reverse Logistics Can Improve the Sustainability Performance of a Business?

Authors: Taknaz Banihashemi, Jiangang Fei, Peggy Shu-Ling Chen

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Reverse logistics (RL) is a part of the logistics of companies and its aim is to reclaim value from the returned products in an environmentally friendly manner. In recent years, RL has attracted significant attention among both practitioners and academics due to environmental directives and governmental legislation, consumer concerns and social responsibilities for environment, awareness of the limits of natural resources and economic potential. Sustainability development is considered as a critical goal for organisations due to its impact on competitive advantage. With growing environmental concerns and legal regulations related to green and sustainability issues, product disposition through RL can be considered as an environmental, economic and social sound way to achieve sustainable development. When employed properly, RL can help firms to improve their sustainability performance. The aim of this paper is to investigate the sustainability issues in the context of RL in the perspective of the triple-bottom-line approach. Content analysis was used to collect the information. The findings show that there is a research gap to investigate the relationship between RL and sustainability performance. Most of the studies have focused on performance evaluation of RL by considering the factors related to economic and environmental performance. RL can have significant effects on social issues along with economic and environmental issues. The inclusion of the social aspect in the sustainability performance will provide a complete and holistic picture of how RL may impact on the sustainability performance of firms. Generally, there is a lack of research on investigating the relationship between RL and sustainability by integrating the three pillars of triple-bottom-line sustainability performance. This paper provides academics and researchers a broad view of the correlations between RL and sustainability performance.

Keywords: verse Logistics, review, sustainability, sustainability performance

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2272 Ipsilateral Heterotopic Ossification in the Knee and Shoulder Post Long COVID-19

Authors: Raheel Shakoor Siddiqui, Calvin Mathias, Manikandar Srinivas Cheruvu, Bobin Varghese

Abstract:

A 58 year old gentleman presented to accident and emergency at the district general hospital with worsening shortness of breath and a non-productive cough over a period of five days. He was initially admitted under the medical team for suspicion of SARS-CoV-2 (COVID-19) pneumonitis. Subsequently, upon deterioration of observations and a positive COVID-19 PCR, he was taken to intensive care for invasive mechanical ventilation. He required frequent proning, inotropic support and was intubated for thirty-three days. After successful extubation, he developed myopathy with a limited range of motion to his right knee and right shoulder. Plain film imaging of these limbs demonstrated an unusual formation of heterotopic ossification without any precipitating trauma or surgery. Current literature demonstrates limited case series portraying heterotopic ossification post-COVID-19. There has been negligible evidence of heterotopic ossification in the ipsilateral knee and shoulder post-prolonged immobility secondary to a critical illness. Physiotherapy and rehabilitation are post-intensive care can be prolonged due to the formation of heterotopic ossification around joints. Prolonged hospital stays may lead to a higher risk of developing infections of the chest, urine and pressure sores. This raises the question of whether a severe systemic inflammatory immune response from the SARS-CoV-2 virus results in histopathological processes leading to the formation of heterotopic ossification not previously seen, requiring prolonged physiotherapy.

Keywords: orthopaedics, rehabilitation, physiotherapy, heterotopic ossification, COVID-19

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2271 Revolutionizing Financial Forecasts: Enhancing Predictions with Graph Convolutional Networks (GCN) - Long Short-Term Memory (LSTM) Fusion

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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2270 Opportunities for Precision Feed in Apiculture

Authors: John Michael Russo

Abstract:

Honeybees are important to our food system and continue to suffer from high rates of colony loss. Precision feed has brought many benefits to livestock cultivation and these should transfer to apiculture. However, apiculture has unique challenges. The objective of this research is to understand how principles of precision agriculture, applied to apiculture and feed specifically, might effectively improve state-of-the-art cultivation. The methodology surveys apicultural practice to build a model for assessment. First, a review of apicultural motivators is made. Feed method is then evaluated. Finally, precision feed methods are examined as accelerants with potential to advance the effectiveness of feed practice. Six important motivators emerge: colony loss, disease, climate change, site variance, operational costs, and competition. Feed practice itself is used to compensate for environmental variables. The research finds that the current state-of-the-art in apiculture feed focuses on critical challenges in the management of feed schedules which satisfy requirements of the bees, preserve potency, optimize environmental variables, and manage costs. Many of the challenges are most acute when feed is used to dispense medication. Technology such as RNA treatments have even more rigorous demands. Precision feed solutions focus on strategies which accommodate specific needs of individual livestock. A major component is data; they integrate precise data with methods that respond to individual needs. There is enormous opportunity for precision feed to improve apiculture through the integration of precision data with policies to translate data into optimized action in the apiary, particularly through automation.

Keywords: precision agriculture, precision feed, apiculture, honeybees

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2269 Algerian EFL Students' Perceptions towards the Development of Writing through Weblog Storytelling

Authors: Nawel Mansouri

Abstract:

Weblog as a form of internet-based resources has become popular as an authentic and constructive learning tool, especially in the language classroom. This research explores the use of weblog storytelling as a pedagogical tool to develop Algerian EFL students’ creative writing. This study aims to investigate the effectiveness of weblog- writing and the attitudes of both Algerian EFL students and teachers towards weblog storytelling. It also seeks to explore the potential benefits and problems that may affect the use of weblog and investigate the possible solutions to overcome the problems encountered. The research work relies on a mixed-method approach which combines both qualitative and quantitative methods. A questionnaire will be applied to both EFL teachers and students as a means to obtain preliminary data. Interviews will be integrated in accordance with the primary data that will be gathered from the questionnaire with the aim of validating its accuracy or as a strategy to follow up any unexpected results. An intervention will take place on the integration of weblog- writing among 15 Algerian EFL students for a period of two months where students are required to write five narrative essays about their personal experiences, give feedback through the use of a rubric to two or three of their peers, and edit their work based on the feedback. After completion, questionnaires and interviews will also take place as a medium to obtain both the students’ perspectives towards the use of weblog as an innovative teaching approach. This study is interesting because weblog storytelling has recently been emerged as a new form of digital communication and it is a new concept within Algerian context. Furthermore, the students will not just develop their writing skill through weblog storytelling but it can also serve as a tool to develop students’ critical thinking, creativity, and autonomy.

Keywords: Weblog writing, EFL writing, EFL learners' attitudes, EFL teachers' views

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2268 A Controlled Natural Language Assisted Approach for the Design and Automated Processing of Service Level Agreements

Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

Abstract:

The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

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2267 The Misuse of Social Media in Order to Exploit "Generation Y"; The Tactics of IS

Authors: Ali Riza Perçin, Eser Bingül

Abstract:

Internet technologies have created opportunities with which people share their ideologies, thoughts and products. This virtual world, named social media has given the chance of gathering individual users and people from the world's remote locations and establishing an interaction between them. However, to an increasingly higher degree terrorist organizations today use the internet and most notably social-network media to create the effects they desire through a series of on-line activities. These activities, designed to support their activities, include information collection (intelligence), target selection, propaganda, fundraising and recruitment to name a few. Meanwhile, these have been used as the most important tool for recruitment especially from the different region of the world, especially disenfranchised youth, in the West in order to mobilize support and recruit “foreign fighters.” The recruits have obtained the statue, which is not accessible in their society and have preferred the style of life that is offered by the terrorist organizations instead of their current life. Like other terrorist groups, for a while now the terrorist organization Islamic State (IS) in Iraq and Syria has employed a social-media strategy in order to advance their strategic objectives. At the moment, however, IS seems to be more successful in their on-line activities than other similar organizations. IS uses social media strategically as part of its armed activities and for the sustainability of their military presence in Syria and Iraq. In this context, “Generation Y”, which could exist at the critical position and undertake active role, has been examined. Additionally, the explained characteristics of “Generation Y” have been put forward and the duties of families and society have been stated as well.

Keywords: social media, "generation Y", terrorist organization, islamic state IS

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2266 Analysis of Iran-Turkey Relations Based on Environmental Geopolitics

Authors: Farid Abbasi

Abstract:

Geographical spaces have different relations with each other, and especially neighboring geographical spaces have more relations than other spaces due to their proximity. Meanwhile, various parameters affect the relationships between these spaces, such as environmental parameters. These parameters have become important in recent decades, affecting the political relations of the actors in neighboring spaces. The Islamic Republic of Iran and the Republic of Turkey, as two actors in the region, political relations seem to have been affected to some extent by environmental issues. Based on this, the present study tries to examine and analyze the political relations between the two countries from an environmental, and geopolitical perspective. The method of this research is descriptive-analytical. The method of data analysis is based on library and field information (questionnaire) in the form of content analysis and statistics through the Mick Mac software system and Scenario Wizard. The results of studies and analysis of theories show that 35 indicators, directly and indirectly, affect Iran-Turkey relations from an environmental, and geopolitical perspective, which are in the form of five dimensions (water resources, soil resources, Vegetation, climate, living species). Using the Mick Mac method, 9 factors were extracted as key factors affecting Iran-Turkey relations, and in the process of analyzing research scenarios, 10100 possible situations were presented by scenario wizard software. 9 strong scenarios with 3 scenarios of favorable and very favorable situations, 3 scenarios with moderate situations and also 3 scenarios with critical situations and catastrophes according to Iran-Turkey relations from the environmental aspect are presented.

Keywords: geopolitics, relations, Iran, Turkey, environment

Procedia PDF Downloads 141
2265 Reorientation of Anisotropic Particles in Free Liquid Microjets

Authors: Mathias Schlenk, Susanne Seibt, Sabine Rosenfeldt, Josef Breu, Stephan Foerster

Abstract:

Thin liquid jets on micrometer scale play an important role in processing such as in fiber fabrication, inkjet printing, but also for sample delivery in modern synchrotron X-ray devices. In all these cases the liquid jets contain solvents and dissolved materials such as polymers, nanoparticles, fibers pigments or proteins. As liquid flow in liquid jets differs significantly from flow in capillaries and microchannels, particle localization and orientation will also be different. This is of critical importance for applications, which depend on well-defined homogeneous particle and fiber distribution and orientation in liquid jets. Investigations of particle orientation in liquid microjets of diluted solutions have been rare, despite their importance. With the arise of micro-focused X-ray beams it has become possible to scan across samples with micrometer resolution to locally analyse structure and orientation of the samples. In the present work, we used this method to scan across liquid microjets to determine the local distribution and orientation of anisotropic particles. The compromise wormlike block copolymer micelles as an example of long flexible fibrous structures, hectorite materials as a model of extended nanosheet structures, and gold nanorods as an illustration of short stiff cylinders to comprise all relevant anisotropic geometries. We find that due to the different velocity profile in the liquid jet, which resembles plug flow, the orientation of the particles which was generated in the capillary is lost or changed into non-oriented or bi-axially orientations depending on the geometrical shape of the particle.

Keywords: anisotropic particles, liquid microjets, reorientation, SAXS

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2264 Modelling Exchange-Rate Pass-Through: A Model of Oil Prices and Asymmetric Exchange Rate Fluctuations in Selected African Countries

Authors: Fajana Sola Isaac

Abstract:

In the last two decades, we have witnessed an increased interest in exchange rate pass-through (ERPT) in developing economies and emerging markets. This is perhaps due to the acknowledged significance of the pattern of exchange rate pass-through as a key instrument in monetary policy design, principally in retort to a shock in exchange rate in literature. This paper analyzed Exchange Rate Pass-Through by A Model of Oil Prices and Asymmetric Exchange Rate Fluctuations in Selected African Countries. The study adopted A Non-Linear Autoregressive Distributed Lag approach using yearly data on Algeria, Burundi, Nigeria and South Africa from 1986 to 2022. The paper found asymmetry in exchange rate pass-through in net oil-importing and net oil-exporting countries in the short run during the period under review. An ERPT exhibited a complete pass-through in the short run in the case of net oil-importing countries but an incomplete pass-through in the case of the net oil-exporting countries that were examined. An extended result revealed a significant impact of oil price shock on exchange rate pass-through to domestic price in the long run only for net oil importing countries. The Wald restriction test also confirms the evidence of asymmetric with the role of oil price acting as an accelerator to exchange rate pass-through to domestic price in the countries examined. The study found the outcome to be very useful for gaining expansive knowledge on the external shock impact on ERPT and could be of critical value for national monetary policy decisions on inflation targeting, especially for countries examined and other developing net oil importers and exporters.

Keywords: pass through, exchange rate, ARDL, monetary policy

Procedia PDF Downloads 63