Search results for: and coal mining industry

Authors: Rafat Rob, Khaled Alotaibi, Dana Nour, Abdullah Albadrani, Abdulmohsen Mulhim

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Power systems digitization solutions provides a comprehensive smart, cohesive, interconnected network, extensive connectivity between digital assets, physical power plants, and resources to form digital economies. However, digitization has exposed the classical air gapped power plants to the rapid spread of cyber threats and attacks in the process delaying and forcing many organizations to rethink their cyber security policies and standards before they can augment their operation the new advanced digital devices. Cyber Security requirements for power systems (and industry control systems therein) demand a new approach, unique methodology, and design process that is completely different to Cyber Security measures designed for the IT systems. In practice, Cyber Security strategy, as applied to power systems, tends to be closely aligned to those measures applied for IT system purposes. The differentiator for Cyber Security in terms of power systems are the physical assets and applications used, alongside the ever-growing rate of expansion within the industry controls sector (in comparison to the relatively saturated growth observed for corporate IT systems). These factors increase the magnitude of the cyber security risk within such systems. The introduction of smart devices and sensors along the grid initiate vulnerable entry points to the systems. Every installed Smart Meter is a target; the way these devices communicate with each other may instigate a Denial of Service (DoS) and Distributed Denial of Service (DDoS) attack. Attacking one sensor or meter has the potential to propagate itself throughout the power grid reaching the IT network, where it may manifest itself as a malware infiltration.

Keywords: supply chain, cybersecurity, maturity model, risk, smart grid

Procedia PDF Downloads 114

Authors: Mohammed Fathima Shahanaaz, Shaik Fayazuddin, M. Uday Kiran

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Groundwater quality is deteriorating day by day in different parts of the world due to various reasons, toxic chemicals are being discharged without proper treatment into inland water bodies and land which in turn add pollutants to the groundwater. In this kind of situation, the rural communities which do not have municipal drinking water have to rely on groundwater though it is polluted for various uses. Tannery industry is one of the major industry which provides economy and employment to India. Since most of the developed countries stopped using chemicals which are toxic, the tanning industry which uses chromium as its major element are being shifted towards developing countries. Most of the tanning industries in India can be found in clusters concentrated mainly in states of Tamilnadu, West Bengal, Uttar Pradesh and limited places of Punjab. Limited work is present in the case of tanneries of Warangal. There exists 18 group of tanneries in Desaipet, Enamamula region of Warangal, out of which 4 are involved in dry process and are low responsible for groundwater pollution. These units of tanneries are discharging their effluents after treatment into Sai Cheruvu. Though the treatment effluents are being discharged, the Sai Cheruvu is turned in to Pink colour, with higher levels of BOD, COD, chromium, chlorides, total hardness, TDS and sulphates. An attempt was made to analyse the groundwater samples around this polluted Sai Cheruvu region since literature shows that a single tannery can pollute groundwater to a radius of 7-8 kms from the point of disposal. Sample are collected from 6 different locations around Sai Cheruvu. Analysis was performed for determining various constituents in groundwater such as pH, EC, TDS, TH, Ca+2, Mg+2, HCO3-, Na+, K+, Cl-, SO42-, NO3-, F and Cr+6. The analysis of these constitutes gave values greater than permissible limits. Even chromium is also present in groundwater samples which is exceeding permissible limits People in Paidepally and Sardharpeta villages already stopped the usage of groundwater. They are buying bottle water for drinking purpose. Though they are not using groundwater for drinking purpose complaints are made about using this water for washing also. So treatment process should be adopted for groundwater which should be simple and efficient. In this study rice husk silica (RHS) is used to treat pollutants in groundwater with varying dosages of RHS and contact time. Rice husk is treated, dried and place in a muffle furnace for 6 hours at 650°C. Reduction is observed in total hardness, chlorides and chromium levels are observed after the application RHS. Pollutants reached permissible limits for 27.5mg/l and 50 mg/l of dosage for a contact time of 130 min at constant pH and temperature.

Keywords: chromium, groundwater, rice husk silica, tanning industries

Procedia PDF Downloads 202

Authors: Krish Batra

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The advent of open banking has revolutionized the financial services industry by fostering innovation, enhancing customer experience, and promoting competition. However, this paradigm shift towards more open and interconnected banking ecosystems has introduced complex cybersecurity challenges. This research paper delves into the multifaceted cybersecurity landscape of open banking, highlighting the vulnerabilities and threats inherent in sharing financial data across a network of banks and third-party providers. Through a detailed analysis of recent data breaches, phishing attacks, and other cyber incidents, the paper assesses the current state of cybersecurity within the open banking framework. It examines the effectiveness of existing security measures, such as encryption, API security protocols, and authentication mechanisms, in protecting sensitive financial information. Furthermore, the paper explores the regulatory response to these challenges, including the implementation of standards such as PSD2 in Europe and similar initiatives globally. By identifying gaps in current cybersecurity practices, the research aims to propose a set of robust, forward-looking strategies that can enhance the security and resilience of open banking systems. This includes recommendations for banks, third-party providers, regulators, and consumers on how to mitigate risks and ensure a secure open banking environment. The ultimate goal is to provide stakeholders with a comprehensive understanding of the cybersecurity implications of open banking and to outline actionable steps for safeguarding the financial ecosystem in an increasingly interconnected world.

Keywords: open banking, financial services industry, cybersecurity challenges, data breaches, phishing attacks, encryption, API security protocols, authentication mechanisms, regulatory response, PSD2, cybersecurity practices

Procedia PDF Downloads 60

Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

Procedia PDF Downloads 119

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Sipho Mbatha, Anne Mastament-Mason

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The Multi-Fibre Arrangement (MFA) which regulated all trade in the Apparel Manufacturing Industries (AMI) for four decades was dissolved in 2005. Since 2005, the Apparel Manufacturing Industry of South Africa (AMISA) has been battling to adjust to an environment of liberalised trade, mainly due to strategic, infrastructural and skills factors. In developing competitive advantage strategy for the AMISA, the study aimed to do the following (1) to apply Porter’s diamond model’s determinant “Factor Condition” as framework to develop competitive advantage strategies. (2) Examine the effectiveness of government policy Industrial Policy Action Plan (IPAP 2007) in supporting AMISA. (3) Examine chance events that could be used as bases for competitive advantage strategies for the AMISA. This study found that the lack of advanced skills and poor infrastructure are affecting the competitive advantage of AMISA. The then Clothing, Textiles, Leather and Footwear Sector Education and Training Authority (CTLF-SETA) has also fallen short of addressing the skills gap within the apparel manufacturing industries. The only time that AMISA have shown signs of competitive advantage was when they made use of government grants and incentives available to only compliant AMISA. The findings have shown that the apparel retail groups have shown support for the AMISA by shouldering raw material costs, making it easier to manufacture the required apparel at acceptable lead times. AMISA can compete in low end apparel, provided quick response is intensified, the development of local textiles and raw materials is expedited.

Keywords: compliance rule, apparel manufacturing idustry, factor conditions, advance skills, industrial policy action plan of South Africa

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Authors: Iman Atighi, Jalal Soleimannejad, Ahmad Akbarinasab, Saeid Moradpour

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In the past, we could increase profit by increasing product prices. But in the new decade, a competitive market does not let us to increase profit with increase prices. Therefore, the only way to increase profit will be reduce costs. A significant percentage of production costs are the maintenance costs, and analysis of these costs could achieve more profit. Most maintenance strategies such as RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance), PM (Preventive Maintenance) etc., are trying to reduce maintenance costs. In this paper, decreasing the maintenance costs of Concentration Plant of Golgohar Company (GEG) was examined by using of MTBF (Mean Time between Failures) and MTTR (Mean Time to Repair) analyses. These analyses showed that instead of buying new machines and increasing costs in order to promote capacity, the improving of MTBF and MTTR indexes would solve capacity problems in the best way and decrease costs.

Keywords: Golgohar Iron Ore Mining and Industrial Company, maintainability, maintenance costs, reliability-center-maintenance

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Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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Authors: Hadjer Didouh, Izzaddine Sameut Bouhaik, Mohammed Hadj Meliani

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This research delves into the intricate dynamics of biofilm adhesion on surfaces, particularly focusing on the widely employed X52 surface in oil and gas industry pipelines. Biofilms, characterized by microorganisms within a self-produced matrix, pose significant challenges due to their detrimental impact on surfaces. Our study integrates advanced molecular techniques and cutting-edge microscopy, such as scanning electron microscopy (SEM), to identify microbial communities and visually assess biofilm adhesion. Simultaneously, we concentrate on the X52 surface, utilizing impedance spectroscopy and potentiodynamic polarization to gather electrochemical responses under various conditions. In conjunction with the broader investigation, we propose a novel approach to mitigate biofilm-induced corrosion challenges. This involves environmentally friendly inhibitors derived from plants, offering a sustainable alternative to conventional chemical treatments. Our inquiry screens and selects inhibitors based on their efficacy in hindering biofilm formation and reducing corrosion rates on the X52 surface. This study contributes valuable insights into the interplay between electrochemical processes and biofilm attachment on the X52 surface. Furthermore, the outcomes of this research have broader implications for the oil and gas industry, where biofilm-related corrosion is a persistent concern. The exploration of eco-friendly inhibitors not only holds promise for corrosion control but also aligns with environmental considerations and sustainability goals. The comprehensive nature of this research aims to enhance our understanding of biofilm dynamics, provide effective strategies for corrosion mitigation, and contribute to sustainable practices in pipeline management within the oil and gas sector.

Keywords: bio-corrosion, biofilm, attachment, X52, metal/bacteria interface

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Authors: Michal Friedrich

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Cross-border investment has never been easier than in today’s global economy. Despite recent initiatives tightening the international tax landscape, profit shifting and tax optimization by multinational entities (MNEs) in the context of cross-border M&A remain persistent and complex phenomena that warrant in-depth exploration. By synthesizing the outcomes of existing research, this study aims to first provide a methodological framework for identifying MNEs’ profit-shifting behavior and quantifying its fiscal impacts via various macroeconomic and microeconomic approaches. The study also proposes additional methods and qualitative/quantitative measures for extracting insight into the profit shifting behavior of MNEs in the context of their M&A activities at industry and entity levels. To develop the proposed methods, this study applies the knowledge of international tax laws and known profit shifting conduits (incl. dividends, interest, and royalties) on several model cases/types of cross-border acquisitions and post-acquisition integration activities by MNEs and highlights important factors that encourage or discourage tax optimization. Follow-up research is envisaged to apply the methods outlined in this study on published data on real-world M&A transactions to gain practical country-by-country, industry and entity-level insights. In conclusion, this study seeks to contribute to the ongoing discourse on profit shifting by providing a methodological toolkit for exploring profit shifting tendencies MNEs in connection with their M&A activities and to serve as a backbone for further research. The study is expected to provide valuable insight to policymakers, tax authorities, and tax professionals alike.

Keywords: BEPS, cross-border M&A, international taxation, profit shifting, tax optimization

Procedia PDF Downloads 69

Authors: Hadjer Didouh, Mohamed Hadj Meliani, Izzeddine Sameut Bouhaik

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As global demand for natural gas intensifies, Algeria is increasing its production to meet this rising need, placing significant strain on the nation's extensive pipeline infrastructure. Sonatrach, Algeria's national oil and gas company, faces persistent challenges from metal corrosion, particularly microbiologically influenced corrosion (MIC), leading to substantial economic losses. This study investigates the corrosion-inhibiting properties of Calotropis procera extracts, known as karanka, as a sustainable alternative to conventional inhibitors, which often pose environmental risks. The Calotropis procera extracts were evaluated for their efficacy on carbon steel API 5L X52 through electrochemical techniques, including potentiodynamic polarization and electrochemical impedance spectroscopy (EIS), under simulated operational conditions at varying concentrations, particularly at 10%, and elevated temperatures up to 60°C. The results demonstrated remarkable inhibition efficiency, achieving 96.73% at 60°C, attributed to the formation of a stable protective film on the metal surface that suppressed anodic and cathodic corrosion reactions. Scanning electron microscopy (SEM) confirmed the stability and adherence of these protective films, while EIS analysis indicated a significant increase in charge transfer resistance, highlighting the extract's effectiveness in enhancing corrosion resistance. The abundant availability of Calotropis procera in Algeria and its low-cost extraction processes present a promising opportunity for sustainable biocorrosion management strategies in the oil and gas industry, reinforcing the potential of plant-based extracts as viable alternatives to synthetic inhibitors for environmentally friendly corrosion control.

Keywords: corrosion inhibition, calotropis procera, microbiologically influenced corrosion, eco-friendly inhibitor

Procedia PDF Downloads 26

Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

Procedia PDF Downloads 198

Authors: Lin Meng, Xi Lu, Haibo Wang, Yong Song, Lili Cao, Wenfang Song, Yong Hu

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China has abundant heavy oil resources, and thermal recovery is the main recovery method for heavy oil reservoirs. However, high energy consumption, high carbon emission and high production costs make heavy oil thermal recovery unsustainable. It is urgent to explore a replacement for developing technology. A low Carbon and cost technology of heavy oil recovery, chemical viscosity-reduction in layer (CVRL), is developed by the petroleum exploration and development research institute of Sinopec via investigated mechanisms, synthesized products, and improved oil production technologies, as follows: (1) Proposed a cascade viscous mechanism of heavy oil. Asphaltene and resin grow from free molecules to associative structures further to bulk aggregations by π - π stacking and hydrogen bonding, which causes the high viscosity of heavy oil. (2) Aimed at breaking the π - π stacking and hydrogen bond of heavy oil, the copolymer of N-(3,4-dihydroxyphenethyl) acryl amide and 2-Acrylamido-2-methylpropane sulfonic acid was synthesized as a viscosity reducer. It achieves a viscosity reduction rate of>80% without shearing for heavy oil (viscosity < 50000 mPa‧s), of which fluidity is evidently improved in the layer. (3) Synthesized hydroxymethyl acrylamide-maleic acid-decanol ternary copolymer self-assembly plugging agent. The particle size is 0.1 μm-2 mm adjustable, and the volume is 10-500 times controllable, which can achieve the efficient transportation of viscosity reducer to enriched oil areas. CVRL has applied 400 wells until now, increasing oil production by 470000 tons, saving 81000 tons of standard coal, reducing CO2 emissions by 174000 tons, and reducing production costs by 60%. It promotes the transformation of heavy oil towards low energy consumption, low carbon emissions, and low-cost development.

Keywords: heavy oil, chemical viscosity-reduction, low carbon, viscosity reducer, plugging agent

Procedia PDF Downloads 73

Authors: Vesna Pungercar, Florian Musso

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Identifying materials that can substitute rare or expensive natural resources is one of the key challenges for improving resource efficiency in the building sector. With a growing world population and rising living standards, more and more salt is produced as waste through seawater desalination and potash mining processes. Unfortunately, most of the salt is directly disposed of into nature, where it causes environmental pollution. On the other hand, salt is affordable, is used therapeutically in various respiratory treatments, and can store humidity and heat. It was, therefore, necessary to determine salt materials already in use in building construction and their hygrothermal properties. This research aims to identify salt materials from different scientific branches and historically, to investigate their properties and prioritize the most promising salt materials for indoor applications in a thermal envelope. This was realized through literature review and classification of salt materials into three groups (raw salt materials, composite salt materials, and processed salt materials). The outcome of this research shows that salt has already been used as a building material for centuries and has a potential for future applications due to its hygrothermal properties in a thermal envelope.

Keywords: salt, building material, hygrothermal properties, environment

Procedia PDF Downloads 169

Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

Procedia PDF Downloads 293

Authors: Natalia Ortega

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Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.

Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety

Procedia PDF Downloads 80

Authors: Silvania M. P. Silva, Ricardo A. Mazaro, Gemilde M. Queiroz, Josefa Barbosa, Lucas S. Victorino, Grasiela J. Silva

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The Minas Gerais sweets have a remarkable personality, perceived on the original usage of fruits, sweets, and cheeses in the Brazilian gastronomic landscape, as a unique representation of Minas Gerais. This memory-related and feeling-oriented food is one of the treasures common to all Brazilians. It is mandatory to mention its Portuguese roots for the use of honey, as well as sugar cane and its countless possibilities. This work will show that this heritage is predominantly Portuguese, born in Portuguese convents and that it crossed the Atlantic. Through a historical survey, visits to mining towns known for their sweet culture and material collected in these places, we present the protagonists of this journey of flavors: the Portuguese cake makers (boleiras), who brought the knowledge, ingredients, and the dream of a better life in the crowded mines of gold and opportunities, helping to form a new Minas Gerais knowledge with their delicacies.

Keywords: sweets from portugal, convent sweets, minas gerais, brazil

Procedia PDF Downloads 170

Authors: Anja Jutraz, Tadeja Zupancic

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This article explores urban laboratory, which presents a combination of different physical and digital methods and tools for public participation in urban design. The city consists of built and unbuilt environments, which can be defined as a community of people, who live there. Communities should have the option to express opinions and decide about the future of their city, from the early stages of the design process onwards. In this paper, we presented the possibility of involving community into renewal of Banska Štiavnica in Slovakia (more exactly the old mining shaft and lake Michal Štolna) and the methods to promote the community building. As a case study we presented the eTHNo project, Education about Technical, Historical and Natural opportunities of Michal Štolna. Moreover, we discussed the possibility of using virtual digital tools for public participation in urban design, where we especially focused on Virtual Urban Laboratory, VuLab.

Keywords: community building, digital tools, public participation, urban design

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

Procedia PDF Downloads 148

Authors: Jin Woo Hwang, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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As greenhouse effect has been recognized as serious environmental problem of the world, interests in carbon dioxide (CO₂) emission which comprises major part of greenhouse gas (GHG) emissions have been increased recently. Since construction industry takes a relatively large portion of total CO₂ emissions of the world, extensive studies about reducing CO₂ emissions in construction and operation of building have been carried out after the 2000s. Also, performance based design (PBD) methodology based on nonlinear analysis has been robustly developed after Northridge Earthquake in 1994 to assure and assess seismic performance of building more exactly because structural engineers recognized that prescriptive code based design approach cannot address inelastic earthquake responses directly and assure performance of building exactly. Although CO₂ emissions and PBD approach are recent rising issues on construction industry and structural engineering, there were few or no researches considering these two issues simultaneously. Thus, the objective of this study is to minimize the CO₂ emissions and cost of building designed by PBD approach in structural design stage considering structural materials. 4 story and 4 span reinforced concrete building optimally designed to minimize CO₂ emissions and cost of building and to satisfy specific seismic performance (collapse prevention in maximum considered earthquake) of building satisfying prescriptive code regulations using non-dominated sorting genetic algorithm-II (NSGA-II). Optimized design result showed that minimized CO₂ emissions and cost of building were acquired satisfying specific seismic performance. Therefore, the methodology proposed in this paper can be used to reduce both CO₂ emissions and cost of building designed by PBD approach.

Keywords: CO2 emissions, performance based design, optimization, sustainable design

Procedia PDF Downloads 406

Authors: Hsuan Yu Lai, Hsuan Hsuan Chang

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The consumer decision process steps through problems by weighing evidence, examining alternatives, and choosing a decision path. Currently, the COVID 19 made the tourism industry encounter a huge challenge and suffer the biggest amount of economic loss. It would be very important to reexamine the decision-making process model, especially after the pandemic, and consider the differences among different generations. The tourism industry has been significantly impacted by the global outbreak of COVID-19, but as the pandemic subsides, the sector is recovering. This study addresses the scarcity of research on travel decision-making patterns among generations in Taiwan. Specifically targeting individuals who frequently traveled abroad before the pandemic, the study explores differences in decision-making at different stages post-outbreak. So this study investigates differences in travel decision-making among individuals from different generations during/after the COVID-19 pandemic and examines the moderating effects of social media usage and individuals' perception of health risks. The study hypotheses are “there are significant differences in the decision-making process including travel motivation, information searching preferences, and criteria for decision-making” and that social-media usage and health-risk perception would moderate the results of the previous study hypothesis. The X, Y, and Z generations are defined and categorized based on a literature review. The survey collected data including their social-economic background, travel behaviors, motivations, considerations for destinations, travel information searching preferences, and decision-making criteria before/after the pandemic based on the reviews of previous studies. Data from 656 online questionnaires were collected between January to May 2023 and from Taiwanese travel consumers who used to travel at least one time abroad before Covid-19. SPSS is used to analyze the data with One-Way ANOVA and Two-Way ANOVA. The analysis includes demand perception, information gathering, alternative comparison, purchase behavior, and post-travel experience sharing. Social media influence and perception of health risks are examined as moderating factors. The findings show that before the pandemic, the Y Generation preferred natural environments, while the X Generation favored historical and cultural sites compared to the Z Generation. However, after the outbreak, the Z Generation displayed a significant preference for entertainment activities. This study contributes to understanding changes in travel decision-making patterns following COVID-19 and the influence of social media and health risks. The findings have practical implications for the tourism industry.

Keywords: consumer decision-making, generation study, health risk perception, post-pandemic era, social media

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Authors: Z. Bouattou, R. Laurini, H. Belbachir

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This paper describes a new approach for the automatic generation of the visual summaries dealing with cartographic visualization methods and sensors real time data modeling. Hence, the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet (1980) as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, issue has been discussed in this paper. Our approach is based on spatial analysis by interpolating the values recorded at the same time, by sensors available, so we have a number of distributed observations on study areas and used spatial interpolation methods to find the concentration fields, from these fields and by using some spatial data mining procedures on the fly, it is possible to extract important patterns as geographic rules. Then, those patterns are visualized as chorems.

Keywords: geovisualization, spatial analytics, real-time, geographic data streams, sensors, chorems

Procedia PDF Downloads 401

Authors: R. Saravanakumar, A. Siva, R. Banupriya, K. Balasubramanian

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Slurry infiltrated fibrous concrete (SIFCON) is one of the recently developed construction material that can be considered as a special type of high performance fibre reinforced concrete (HPFRC) with higher fibre content. Fibre reinforced concrete is essentially a composite material in which fibres out of waste having higher modulus of elasticity. SIFCON is a special type of high fibrous concrete and it is having a high cementious content and sand. The matrix usually consists of cement-sand slurry or fluent mortar. The construction industry is in need of finding cost effective materials for increasing the strength of concrete structures hence an endeavour has been made in the present investigations to study the influence of addition of waste material like Lathe waste from workshop at different dosages to the total weight of concrete. The waste of steel scrap material which is available from the lathe is used as a steel fibre for innovative construction industry. To get sustainable and environmental benefits, lathe scrap as recycled fibres with concrete are likely to be used. An experimental program was carried out to investigate the flexural behavior of Slurry infiltrated fibrous concrete (SIFCON) in which the fibres having an aspect ratio of 100 is used. The investigations were done using M25 mix and tests were carried out as per recommended procedures by appropriate codes. SIFCON specimens with 8%, 10% and 12% volume of fraction fibres are used in this study. Test results were presented in comparison of SIFCON with and without conventional steel reinforcement. The load carrying capacity of SIFCON specimen is higher than conventional concrete and it also reduced crack width. In the SIFCON specimen less number of cracks as compared with conventional concrete.

Keywords: SIFCON, lathe waste, RCC, fibre volume, flexural behaviour

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Authors: Jeferson Gomes Dos Santos, Mirelle Cristina De Abreu Quintela

Abstract:

Considering that after the 1988 Constitution, in Brazil, municipalities have acquired new roles in the face of a financial reality that jeopardizes more substantial actions, the Public Budget is essential for the establishment of guidelines for action, within each budgetary reality. Within this, the present work sought to understand the budget profile of the mining municipality of Ataleia, with a view to identifying its budget composition, in relation to the main sources of revenue and expenditure. To achieve the purposes of the study, information was collected on the municipality's finances, from the years 2000 to 2016, visualizing the progress of its revenues in terms of funding and origin, and expenses in terms of nature and purpose. It was evidenced that the municipality, having its budget revenue in the period, still shows great dependence on intergovernmental transfers, as the own collection was relatively low. The budget expenditure of the period was mainly influenced by social expenditures, but it must be said that the municipality complied with the limits of spending, minimum and maximum, established by law.

Keywords: expenses, municipal budget, planning, revenue

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

Procedia PDF Downloads 247

Authors: Maico R. Severino, Laura G. Caixeta, Nadine M. Costa, Raísa L. T. Napoleão, Éverton F. V. Valle, Diego D. Calixto, Danielle Oliveira

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One of the biggest barriers that companies find nowadays is the coordination of production flow in their Supply Chains (SC). In this study, coordination is understood as a mechanism for incorporating the entire production channel, with everyone involved focused on achieving the same goals. Sometimes, this coordination is attempted by the use of logistics practices or production plan and control methods. No papers were found in the literature that presented the combined use of logistics practices and production plan and control methods. The main objective of this paper is to propose solutions for six case studies combining logistics practices and Ordering Systems (OS). The methodology used in this study was a conceptual model of decision making. This model contains six phases: a) the analysis the types and characteristics of relationships in the SC; b) the choice of the OS; c) the choice of the logistics practices; d) the development of alternative proposals of combined use; e) the analysis of the consistency of the chosen alternative; f) the qualitative and quantitative assessment of the impact on the coordination of the production flow and the verification of applicability of the proposal in the real case. This study was conducted on six Brazilian SC of different sectors: footwear, food and beverages, garment, sugarcane, mineral and metal mechanical. The results from this study showed that there was improvement in the coordination of the production flow through the following proposals: a) for the footwear industry the use of Period Bath Control (PBC), Quick Response (QR) and Enterprise Resource Planning (ERP); b) for the food and beverage sector firstly the use of Electronic Data Interchange (EDI), ERP, Continuous Replenishment (CR) and Drum-Buffer-Rope Order (DBR) (for situations in which the plants of both companies are distant), and secondly EDI, ERP, Milk-Run and Review System Continues (for situations in which the plants of both companies are close); c) for the garment industry the use of Collaborative Planning, Forecasting, and Replenishment (CPFR) and Constant Work-In-Process (CONWIP) System; d) for the sugarcane sector the use of EDI, ERP and CONWIP System; e) for the mineral processes industry the use of Vendor Managed Inventory (VMI), EDI and MaxMin Control System; f) for the metal mechanical sector the use of CONWIP System and Continuous Replenishment (CR). It should be emphasized that the proposals are exclusively recommended for the relationship between client and supplier studied. Therefore, it cannot be generalized to other cases. However, what can be generalized is the methodology used to choose the best practices for each case. Based on the study, it can be concluded that the combined use of OS and logistics practices enable a better coordination of flow production on SC.

Keywords: supply chain management, production flow coordination, logistics practices, ordering systems

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Authors: M. Çevik, S. Sabancı, D. Tezcan, C. Çelebi, F. İçier

Abstract:

Ultrasound technology is the one of the non-thermal food processing method in recent years which has been used widely in the food industry. Ultrasound application in the food industry is divided into two groups: low and high intensity ultrasound application. While low intensity ultrasound is used to obtain information about physicochemical properties of foods, high intensity ultrasound is used to extract bioactive components and to inactivate microorganisms and enzymes. In this study, the ultrasound pre-treatment at a constant power (1500 W) and fixed frequency (20 kHz) was applied to the red beetroot slices having the dimension of 25×25×50 mm at the constant temperature (25°C) for different application times (0, 5, 10, 15 and 20 min). The red beet root slices pretreated with ultrasonication was squeezed immediately. The changes on rheological properties of red beet root juice depending on ultrasonication duration applied to slices were investigated. Rheological measurements were conducted by using Brookfield viscometer (LVDV-II Pro, USA). Shear stress-shear rate data was obtained from experimental measurements for 0-200 rpm range by using spindle 18. Rheological properties of juice were determined by fitting this data to some rheological models (Newtonian, Bingham, Power Law, Herschel Bulkley). It was investigated that the best model was Power Law model for both untreated red beet root juice (R2=0.991, χ2=0.0007, RMSE=0.0247) and red beetroot juice produced from ultrasonicated slices (R2=0.993, χ2=0.0006, RMSE=0.0216 for 20 min pre-treatment). k (consistency coefficient) and n (flow behavior index) values of red beetroot juices were not affected from the duration of ultrasonication applied to the slices. Ultrasound treatment does not result in any changes on the rheological properties of red beetroot juice. This can be explained by lack of ability to homogenize of the intensity of applied ultrasound.

Keywords: ultrasonication, rheology, red beet root slice, juice

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Authors: Nonso Ochinanwata, Patrick Oseloka Ezepue

Abstract:

This paper explores challenges and prospects in Nigerian higher education. The paper develops an integrated business model that aimed to innovate Nigeria higher education system. A survey and semi-structured interview among Nigerian higher education academics, students and graduates are used to explore the challenges and prospects. The study provides a comparison between lecturers, students and graduates opinions to evaluate challenges and prospects in Nigerian higher institutions. The study found to achieve efficient and effectiveness innovation in Nigerian higher education, there is a need for higher institutions to collaborate with industry professionals and other stakeholders such as company management, and government policy makers in designing higher education institutions curricula. The study found that the curriculum design and delivery need to blend theoretical understanding and real-life experience from industry, and with social cultural influences related to Nigerian environment. This will enable lecturers to organise their teaching and assessments such that students can learn around theoretical and practical study themes. The curriculum design and delivery need to link the core ideas to challenging problems in society, nationally and globally. Hence, this approach will support business start-ups and social entrepreneurship which resolve key societal problems. The study suggests that higher education executives, directors, deans, head of departments, and even individual academics need to emulate innovative business managers to create value-adding products and services from innovative research and academic work.

Keywords: higher education, curriculum innovation, business model innovation, teaching and research excellence, economic development

Procedia PDF Downloads 271