Search results for: industry skills

Authors: Pisut Boonkaew, Jatuporn Thongsri

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In hard disk drive manufacturing industry, the process of reducing an unnecessary part and qualifying the quality of part before assembling is important. Thus, clamp was designed and fabricated as a fixture for holding in testing process. Basically, testing by trial and error consumes a long time to improve. Consequently, the simulation was brought to improve the part and reduce the time taken. The problem is the present clamp has a low life expectancy because of the critical stress that occurred. Hence, the simulation was brought to study the behavior of stress and compressive force to improve the clamp expectancy with all probability of designs which are present up to 27 designs, which excluding the repeated designs. The probability was calculated followed by the full fractional rules of six sigma methodology which was provided correctly. The six sigma methodology is a well-structured method for improving quality level by detecting and reducing the variability of the process. Therefore, the defective will be decreased while the process capability increasing. This research focuses on the methodology of stress and fatigue reduction while compressive force still remains in the acceptable range that has been set by the company. In the simulation, ANSYS simulates the 3D CAD with the same condition during the experiment. Then the force at each distance started from 0.01 to 0.1 mm will be recorded. The setting in ANSYS was verified by mesh convergence methodology and compared the percentage error with the experimental result; the error must not exceed the acceptable range. Therefore, the improved process focuses on degree, radius, and length that will reduce stress and still remain in the acceptable force number. Therefore, the fatigue analysis will be brought as the next process in order to guarantee that the lifetime will be extended by simulating through ANSYS simulation program. Not only to simulate it, but also to confirm the setting by comparing with the actual clamp in order to observe the different of fatigue between both designs. This brings the life time improvement up to 57% compared with the actual clamp in the manufacturing. This study provides a precise and trustable setting enough to be set as a reference methodology for the future design. Because of the combination and adaptation from the six sigma method, finite element, fatigue and linear regressive analysis that lead to accurate calculation, this project will able to save up to 60 million dollars annually.

Keywords: clamp, finite element analysis, structural, six sigma, linear regressive analysis, fatigue analysis, probability

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Authors: Surinder Pal, Ajay Gupta, Johny Khajuria

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Casting simulation helps visualize mold filling and casting solidification; predict related defects like cold shut, shrinkage porosity and hard spots; and optimize the casting design to achieve the desired quality with high yield. Flow and solidification of molten metals are, however, a very complex phenomenon that is difficult to simulate correctly by conventional computational techniques, especially when the part geometry is intricate and the required inputs (like thermo-physical properties and heat transfer coefficients) are not available. Simulation software is based on the process of modeling a real phenomenon with a set of mathematical formulas. It is, essentially, a program that allows the user to observe an operation through simulation without actually performing that operation. Simulation software is used widely to design equipment so that the final product will be as close to design specs as possible without expensive in process modification. Simulation software with real-time response is often used in gaming, but it also has important industrial applications. When the penalty for improper operation is costly, such as airplane pilots, nuclear power plant operators, or chemical plant operators, a mockup of the actual control panel is connected to a real-time simulation of the physical response, giving valuable training experience without fear of a disastrous outcome. The all casting simulation software has own requirements, like magma cast has only best for crack simulation. The latest generation software Auto CAST developed at IIT Bombay provides a host of functions to support method engineers, including part thickness visualization, core design, multi-cavity mold design with common gating and feeding, application of various feed aids (feeder sleeves, chills, padding, etc.), simulation of mold filling and casting solidification, automatic optimization of feeders and gating driven by the desired quality level, and what-if cost analysis. IIT Bombay has developed a set of applications for the foundry industry to improve casting yield and quality. Casting simulation is a fast and efficient solution for process for advanced tool which is the result of more than 20 years of collaboration with major industrial partners and academic institutions around the world. In this paper the process of casting simulation is studied.

Keywords: casting simulation software’s, simulation technique’s, casting simulation, processes

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Authors: Paolo Guzzini, Emad Samuel M. Ebeid

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Bridges and Railways are critical infrastructures. Ensuring safety for transports using such assets is a primary goal as it directly impacts the lives of people. By the way, improving safety could require increased investments in O&M, and therefore optimizing resource usage for asset maintenance becomes crucial. Drones4Safety (D4S), a European project funded under the H2020 Research and Innovation Action (RIA) program, aims to increase the safety of the European civil transport by building a system that relies on 3 main pillars: • Drones operating autonomously in swarm mode; • Drones able to recharge themselves using inductive phenomena produced by transmission lines in the nearby of bridges and railways assets to be inspected; • Data acquired that are analyzed with AI-empowered algorithms for defect detection This paper describes the business model behind this disruptive project. The Business Model is structured in 2 parts: • The first part is focused on the design of the business model Canvas, to explain the value provided by the Drone4safety project; • The second part aims at defining a detailed financial analysis, with the target of calculating the IRR (Internal Return rate) and the NPV (Net Present Value) of the investment in a 7 years plan (2 years to run the project + 5 years post-implementation). As to the financial analysis 2 different points of view are assumed: • Point of view of the Drones4safety company in charge of designing, producing, and selling the new system; • Point of view of the Utility company that will adopt the new system in its O&M practices; Assuming the point of view of the Drones4safety company 3 scenarios were considered: • Selling the drones > revenues will be produced by the drones’ sales; • Renting the drones > revenues will be produced by the rental of the drones (with a time-based model); • Selling the data acquisition service > revenues will be produced by the sales of pictures acquired by drones; Assuming the point of view of a utility adopting the D4S system, a 4th scenario was analyzed taking into account the decremental costs related to the change of operation and maintenance practices. The paper will show, for both companies, what are the key parameters affecting most of the business model and which are the sustainable scenarios.

Keywords: a swarm of drones, AI, bridges, railways, drones4safety company, utility companies

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Authors: Younis Elhaddad, Alfonso Ortega

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Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.

Keywords: evolutionary automatic programming, gas lift, genetic algorithms, oil production

Procedia PDF Downloads 159

Authors: Matthew J. I. Woolley, Gemma J. M. Read, Paul M. Salmon, Natassia Goode

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The significance of high consequence, workplace failures within construction continues to resonate with a combined average of 12 fatal incidents occurring daily throughout Australia, the United Kingdom, and the United States. Within the Australian construction domain, more than 35 serious, compensable injury incidents are reported daily. These alarming figures, in conjunction with the continued occurrence of fatal and serious, occupational injury incidents globally suggest existing approaches to incident analysis may not be achieving required injury prevention outcomes. One reason may be that, incident analysis methods used in construction have not kept pace with advances in the field of safety science and are not uncovering the full range system-wide contributory factors that are required to achieve optimal levels of construction safety performance. Another reason underpinning this global issue may also be the absence of information surrounding the construction operating and project delivery system. For example, it is not clear who shares the responsibility for construction safety in different contexts. To respond to this issue, to the author’s best knowledge, a first of its kind, control structure model of the construction industry is presented and then used to analyse a fatal construction incident. The model was developed by applying and extending the Systems Theoretic and Incident Model and Process method to hierarchically represent the actors, constraints, feedback mechanisms, and relationships that are involved in managing construction safety performance. The Causal Analysis based on Systems Theory (CAST) method was then used to identify the control and feedback failures involved in the fatal incident. The conclusions from the Coronial investigation into the event are compared with the findings stemming from the CAST analysis. The CAST analysis highlighted additional issues across the construction system that were not identified in the coroner’s recommendations, suggested there is a potential benefit in applying a systems theory approach to incident analysis in construction. The findings demonstrate the utility applying systems theory-based methods to the analysis of construction incidents. Specifically, this study shows the utility of the construction control structure and the potential benefits for project leaders, construction entities, regulators, and construction clients in controlling construction performance.

Keywords: construction project management, construction performance, incident analysis, systems thinking

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Authors: Carlos Y. Soto, Camila A. Lota, G. Astrid Garzón

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Bacterial biofilms cause an ongoing problem for food safety. They are formed when microorganisms aggregate to form a community that attaches to solid surfaces. Biofilms increase the resistance of pathogens to cleaning, disinfection and antibacterial products. This resistance gives rise to problems for human health, industry, and agriculture. At present, plant extracts rich in polyphenolics are being investigated as natural alternatives to degrade bacterial biofilms. The pomace of the tropical Berry Vaccinium meridionale S. contains high amounts of phenolic compounds. Therefore, in the current study, the antimicrobial and antibiofilm effects of extracts from the pomace of Vaccinium meridionale S. were tested on three foodborne pathogens: Enterohaemorrhagic Escherichia coli O157:H7 (ATCC®700728TM), Staphylococcus aureus subsp. aureus (ATCC® 6538TM), and Salmonella enterica serovar Enteritidis (ATCC® 13076TM). Microwave-assisted extraction was used to extract polyphenols with aqueous methanol (80% v/v) at a solid to solvent ratio of 1:10 (w/v) for 20 min. The magnetic stirring was set at 400 rpm, and the microwave power was adjusted to 400 W. The antimicrobial effect of the extract was assessed by determining the half maximal inhibitory concentration (IC50) against the three food poisoning pathogens at concentrations ranging from 50 to 2,850 μg gallic acid equivalents (GAE)/mL of the extract. Biofilm inhibition was assessed using a crystal violet assay applying the same range of concentration. Three replications of the experiments were carried out, and all analyses were run in triplicate. IC50 values were determined using the GraphPad Prism8® program. Significant differences (P<0.05) among means were identified using one-factor analysis of variance (ANOVA) and the post-hoc least significant difference (LSD) test using the Statgraphics plus program, version 2.1.There was significant difference among the mean IC50 values for the tested bacteria. The IC50 for S. aureus was 48 ± 9 μg GAE/mL, followed by 123 ± 49 μg GAE/mL for Salmonella and 376 ± 32 μg GAE/mL for E. coli. The percent inhibition of the extract on biofilm formation was significantly higher for S. aureus (85.8  0.3), followed by E. coli (74.5  1.0) and Salmonella (53.6  9.7). These findings suggest that polyphenolic extracts obtained from the pomace of V. meridionale S. might be used as natural antimicrobial and anti-biofilm natural agents, effective against S. aureus, E. coli and Salmonella enterica.

Keywords: antibiofilm, antimicrobial, E. coli, S. aureus, salmonella, IC50, pomace, V. meridionale

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Authors: A. Gonzalez Aguna, J. M. Santamaria Garcia, J. L. Gomez Gonzalez, R. Barchino Plata, M. Fernandez Batalla, S. Herrero Jaen

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Background: Computer Science is a field that transcends other disciplines of knowledge because it allows to support all kinds of physical and mental tasks. Health centres have a greater number and complexity of technological devices and the population consume and demand services derived from technology. Also, nursing education plans have included competencies related to and, even, courses about new technologies are offered to health professionals. However, nurses still limit their performance to the use and evaluation of products previously built. Objective: Develop a teaching-learning methodology for acquiring skills on designing applications for care. Methodology: Blended learning teaching with a group of graduate nurses through official training within a Master's Degree. The study sample was selected by intentional sampling without exclusion criteria. The study covers from 2015 to 2017. The teaching sessions included a four-hour face-to-face class and between one and three tutorials. The assessment was carried out by written test consisting of the preparation of an IEEE 830 Standard Specification document where the subject chosen by the student had to be a problem in the area of care. Results: The sample is made up of 30 students: 10 men and 20 women. Nine students had a degree in nursing, 20 diploma in nursing and one had a degree in Computer Engineering. Two students had a degree in nursing specialty through residence and two in equivalent recognition by exceptional way. Except for the engineer, no subject had previously received training in this regard. All the sample enrolled in the course received the classroom teaching session, had access to the teaching material through a virtual area and maintained at least one tutoring. The maximum of tutorials were three with an hour in total. Among the material available for consultation was an example of a document drawn up based on the IEEE Standard with an issue not related to care. The test to measure competence was completed by the whole group and evaluated by a multidisciplinary teaching team of two computer engineers and two nurses. Engineers evaluated the correctness of the characteristics of the document and the degree of comprehension in the elaboration of the problem and solution elaborated nurses assessed the relevance of the chosen problem statement, the foundation, originality and correctness of the proposed solution and the validity of the application for clinical practice in care. The results were of an average grade of 8.1 over 10 points, a range between 6 and 10. The selected topic barely coincided among the students. Examples of care areas selected are care plans, family and community health, delivery care, administration and even robotics for care. Conclusion: The applied methodology of learning-teaching for the design of technologies demonstrates the success in the training of nursing professionals. The role of expert is essential to create applications that satisfy the needs of end users. Nursing has the possibility, the competence and the duty to participate in the process of construction of technological tools that are going to impact in care of people, family and community.

Keywords: care, learning, nursing, technology

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Authors: Marco Camilli

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This article examines the impact of the pandemic outbreak of COVID-19 in the tourism sector in Italy, analyzing the current scenario, the government decisions and the private company reaction for the summer season 2020. The framework of the data analyzed shows how massive it’s the impact of the pandemic outbreak in the tourism revenue, and the weaknesses of the measures proposed. Keywords Travel &Tourism, Transportation, Sustainability, COVID-19, Businesses Introduction The current COVID-19 scenario shows a shocking situation for the tourism and transportation sectors: it could be the most affected by the Coronavirus in Italy. According to forecasts, depending on the duration of the epidemic outbreak and the lockdown strategy applied by the Government, businesses in the supply chain could lose between 24 and 66 billion in turnover in the period of 2020-21, with huge diversified impacts at the national and regional level. Many tourist companies are on the verge of survival and if there are no massive measures by the government they risk closure. Data analysis The tourism and transport sector could be among the sectors most damaged by Covid-19 in Italy. Considering the two-year period 2020-21, companies operating in the travel & tourism sector (Tour operator, Travel Agencies, Hotel, Guides, Bus Company, etc..) could in suffer losses in revenues of 24 to 64 billion euros, especially in the sectors such as the travel agencies, hotel and rental. According to Statista Research Department, from April 2020 estimated that the coronavirus (COVID-19) pandemic will have a significant impact on revenues of the tourism industry in Italy. Revenues are expected to decrease by over 40 billion euros in the first semester of 2020, compared to the same period of the previous year. According to the study, hotel and non-hotel accommodations will experience the highest loss. Revenues of this sector are expected to decrease by 13 billion euros compared to the first semester of 2019 when accommodations registered revenues for about 17 billion euros. According to Statista.com, in 2020, Italy is expected to register a decrease of roughly 28.5 million tourist arrivals due to the impact of coronavirus (COVID-19) on the country's tourist sector. According to the estimate, the region of Veneto will record the highest drop with a decrease of roughly 4.61 million arrivals. Similarly, Lombardy is expected to register a decrease of about 3.87 million arrivals in 2020.

Keywords: travel and tourism, sustainability, COVID-19, businesses, transportation

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Authors: Samuel Holder

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Mass incarceration in the United States is a human rights issue, not merely a civil rights problem. It is a human rights problem not only because the United States has a high rate of incarceration, but more importantly because of who is jailed, for what purpose they are jailed and, ultimately, the manner in which they are jailed. To sustain the scale of the criminal justice system, one of the darker policies involves a multi-tiered strategy of fee- and fine-collection, targeting, usually, the most vulnerable and poor, many of whom run into the law via small offenses that do not rise to the level of felonies. This paper advances the notion that this debt collection-to-incarceration pipeline is tantamount to a modern-day debtors’ prison system. This article seeks to confront the thorny issue of incarceration via criminal justice debt from a human rights and cause-lawyering position. It will argue that a two-pronged cause-lawyering strategy: the first focused on traditional litigation along constitutional grounds, and the second, an advocacy approach rooted in grassroots campaigns, designed to shift the normative operation and understanding of the rights of marginalized and racialized offenders. Ultimately, the argument suggests that this approach will be effective in combatting the (often highly privatized) criminal justice debt system and bring the roles of 'incapacitation, rehabilitation, deterrence, and retribution' back into the criminal justice legal conversation. Part I contextualizes and historicizes the role of fees, penalties, and fines in American criminal justice. Part II examines the emergence of private industry in the criminal justice system, and its role in the acceleration of profit-driven criminal justice debt collection and incarceration. Part III addresses the failures of the federal and state law and legislation in combatting predatory incarceration and debt collection in the criminal justice system, particularly as waged against the indigent and/or ethnically or racially marginalized. Part IV examines the potential for traditional cause-lawyering litigation along constitutional grounds, using case studies across contexts for illustration. Finally, Part V will review the radical cause-lawyer’s role in the normative struggle in redefining prisoners’ rights and the rights of the marginalized (and racialized) as they intersect at the crossroads of criminal justice debt. This paper will conclude with recommendations for litigation and advocacy, drawing on hypotheses advanced, and informed by case studies from a variety of both national and international jurisdictions.

Keywords: cause-lawyering, criminal justice debt, human rights, judicial fees

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Authors: M. F. Perez, Ysmael Verde, B. Escobar, R. Barbosa, J. C. Cruz

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Reinforced concrete is one of the most important materials in the construction industry. However, in recent years the durability of concrete structures has been a worrying problem, mainly due to corrosion of reinforcing steel; the consequences of corrosion in all cases lead to shortening of the life of the structure and decrease in quality of service. Since the emergence of this problem, they have implemented different methods or techniques to reduce damage by corrosion of reinforcing steel in concrete structures; as the use of polymeric materials as coatings for the steel rod, spiked inhibitors of concrete during mixing, among others, presenting different limitations in the application of these methods. Because of this, it has been used a method that has proved effective, cathodic protection. That is why due to the properties attributed to carbon nanotubes (CNT), these could act as cathodic corrosion protection. Mounting a three-electrode electrochemical cell, carbon steel as working electrode, saturated calomel electrode (SCE) as the reference electrode, and a graphite rod as a counter electrode to close the system is performed. Samples made were subjected to a cycling process in order to compare the results in the corrosion performance of a coating composed of CNT and the others based on an anticorrosive commercial painting. The samples were tested at room temperature using an electrolyte consisting NaCl and NaOH simulating the typical pH of concrete, ranging from 12.6 to 13.9. Three test samples were made of steel rod, white, with commercial anticorrosive paint and CNT based coating; delimiting the work area to a section of 0.71 cm2. Tests cyclic voltammetry and linear voltammetry electrochemical spectroscopy each impedance of the three samples were made with a window of potential vs SCE 0.7 -1.7 a scan rate of 50 mV / s and 100 mV / s. The impedance values were obtained by applying a sine wave of amplitude 50 mV in a frequency range of 100 kHz to 100 MHz. The results obtained in this study show that the CNT based coating applied to the steel rod considerably decreased the corrosion rate compared to the commercial coating of anticorrosive paint, because the Ecorr was passed increase as the cycling process. The samples tested in all three cases were observed by light microscopy throughout the cycling process and micrographic analysis was performed using scanning electron microscopy (SEM). Results from electrochemical measurements show that the application of the coating containing carbon nanotubes on the surface of the steel rod greatly increases the corrosion resistance, compared to commercial anticorrosive coating.

Keywords: anticorrosive, carbon nanotubes, corrosion, steel

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Authors: Joy Chadwick

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There is no doubt that classrooms of today are more complex and diverse than ever before. Preparing teacher candidates to meet these challenges is essential to ensure the retention of teachers within the profession and to ensure that graduates begin their teaching careers with the knowledge and understanding of how to effectively meet the diversity of students they will encounter. Creating inclusive classrooms requires teachers to have a repertoire of effective instructional skills and strategies. Teachers must also have the mindset to embrace diversity and value the uniqueness of individual students in their care. This qualitative study analyzed teacher candidates' experiences as they completed a fourteen-week teaching practicum while simultaneously completing a university course focused on inclusive pedagogy. The research investigated the challenges and successes teacher candidates had in navigating the translation of theory related to inclusive pedagogy into their teaching practice. Applying threshold concept theory as a framework, the research explored the troublesome concepts, liminal spaces, and transformative experiences as connected to inclusive practices. Threshold concept theory suggests that within all disciplinary fields, there exists particular threshold concepts that serve as gateways or portals into previously inaccessible ways of thinking and practicing. It is in these liminal spaces that conceptual shifts in thinking and understanding and deep learning can occur. The threshold concept framework provided a lens to examine teacher candidate struggles and successes with the inclusive education course content and the application of this content to their practicum experiences. A qualitative research approach was used, which included analyzing twenty-nine course reflective journals and six follow up one-to-one semi structured interviews. The journals and interview transcripts were coded and themed using NVivo software. Threshold concept theory was then applied to the data to uncover the liminal or stuck spaces of learning and the ways in which the teacher candidates navigated those challenging places of teaching. The research also sought to uncover potential transformative shifts in teacher candidate understanding as connected to teaching in an inclusive classroom. The findings suggested that teacher candidates experienced difficulties when they did not feel they had the knowledge, skill, or time to meet the needs of the students in the way they envisioned they should. To navigate the frustration of this thwarted vision, they relied on present and previous course content and experiences, collaborative work with other teacher candidates and their mentor teachers, and a proactive approach to planning for students. Transformational shifts were most evident in their ability to reframe their perceptions of children from a deficit or disability lens to a strength-based belief in the potential of students. It was evident that through their course work and practicum experiences, their beliefs regarding struggling students shifted as they saw the value of embracing neurodiversity, the importance of relationships, and planning for and teaching through a strength-based approach. Research findings have implications for teacher education programs and for understanding threshold concepts theory as connected to practice-based learning experiences.

Keywords: inclusion, inclusive education, liminal space, teacher education, threshold concepts, troublesome knowledge

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Authors: Selisha A. Sooklal, Phelelani Mpangase, Shaun Aron, Karl Rumbold

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Organically bound fluorine (C-F bond) is extremely rare in nature. Despite this, the first fluorinated secondary metabolite, fluoroacetate, was isolated from the plant Dichapetalum cymosum (commonly known as Gifblaar). However, the enzyme responsible for fluorination (fluorinase) in Gifblaar was never isolated and very little progress has been achieved in understanding this process in higher plants. Fluorinated compounds have vast applications in the pharmaceutical, agrochemical and fine chemicals industries. Consequently, an enzyme capable of catalysing a C-F bond has great potential as a biocatalyst in the industry considering that the field of fluorination is virtually synthetic. As with any biocatalyst, a range of these enzymes are required. Therefore, it is imperative to expand the exploration for novel fluorinases. This study aimed to gain molecular insights into secondary metabolite biosynthesis in Gifblaar using a high-throughput sequencing-based approach. Mechanical wounding studies were performed using Gifblaar leaf tissue in order to induce expression of the fluorinase. The transcriptome of the wounded and unwounded plant was then sequenced on the Illumina HiSeq platform. A total of 26.4 million short sequence reads were assembled into 77 845 transcripts using Trinity. Overall, 68.6 % of transcripts were annotated with gene identities using public databases (SwissProt, TrEMBL, GO, COG, Pfam, EC) with an E-value threshold of 1E-05. Sequences exhibited the greatest homology to the model plant, Arabidopsis thaliana (27 %). A total of 244 annotated transcripts were found to be differentially expressed between the wounded and unwounded plant. In addition, secondary metabolic pathways present in Gifblaar were successfully reconstructed using Pathway tools. Due to lack of genetic information for plant fluorinases, a transcript failed to be annotated as a fluorinating enzyme. Thus, a local database containing the 5 existing bacterial fluorinases was created. Fifteen transcripts having homology to partial regions of existing fluorinases were found. In efforts to obtain the full coding sequence of the Gifblaar fluorinase, primers were designed targeting the regions of homology and genome walking will be performed to amplify the unknown regions. This is the first genetic data available for Gifblaar. It has provided novel insights into the mechanisms of metabolite biosynthesis and will allow for the discovery of the first eukaryotic fluorinase.

Keywords: biocatalyst, fluorinase, gifblaar, transcriptome

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Authors: Mario Hanna Louis Hanna

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The use of CAD (pc Aided layout) generation is ubiquitous inside the structure, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of structure faculties in Nigeria as an important part of the training module. This newsletter examines the moral troubles involved in implementing CAD (pc Aided layout) content into the architectural training curriculum. Using current literature, this study begins with the advantages of integrating CAD into architectural education and the responsibilities of various stakeholders in the implementation process. It also examines issues related to the terrible use of records generation and the perceived bad effect of CAD use on design creativity. The use of a survey technique, information from the architecture department of Chukwuemeka Odumegwu Ojukwu Uli college changed into accumulated to serve as a case observe on how the problems raised have been being addressed. The object draws conclusions on what guarantees a hit moral implementation. Tens of millions of human beings around the sector suffer from hepatitis C, one of the international's deadliest sicknesses. Interferon (IFN) is a remedy alternative for patients with hepatitis C, but these treatments have their aspect outcomes. Our research targeted growing an oral small molecule drug that goals hepatitis C virus (HCV) proteins and has fewer facet effects. Our contemporary study targets to broaden a drug primarily based on a small molecule antiviral drug precise for the hepatitis C virus (HCV). Drug improvement and the use of laboratory experiments isn't always best high-priced, however also time-eating to behavior those experiments. instead, on this in silicon have a look at, we used computational strategies to recommend a particular antiviral drug for the protein domain names of discovered in the hepatitis C virus. This examines used homology modeling and abs initio modeling to generate the 3-D shape of the proteins, then figuring out pockets within the proteins. Proper lagans for pocket pills were advanced the usage of the de novo drug design method. Pocket geometry is taken into consideration while designing ligands. A few of the various lagans generated, a different for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, Hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication.

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Authors: Emma Van Schie

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The purpose of this study is to use mixed methods research to create typologies of the performance of firms in the cotton-to-clothing value chain in Zimbabwe, and to use these typologies to achieve the objective of adding to the small pool of studies on Sub-Saharan African value chains performing in the context of economic liberalisation and achieving development. The uptake of economic liberalisation measures across Sub-Saharan Africa has led to the restructuring of many value chains. While this action has resulted in some African economies positively reintegrating into global commodity chains, it has also been deeply problematic for the development impacts of the majority of others. Over and above this, these nations have been placed at a disadvantage due to the fact that there is little scholarly and policy research on approaches for managing economic liberalisation and value chain development in the unique African context. As such, the central question facing these less successful cases is how they can integrate into the world economy whilst still fostering their development. This paper draws from quantitative questionnaires and qualitative interviews with 28 stakeholders in the cotton-to-clothing value chain in Zimbabwe. This paper examines the performance of firms in the value chain, and the subsequent local socio-economic development impacts that are affected by the revival of the cotton-to-clothing value chain following its collapse in the wake of Zimbabwe’s uptake of economic liberalisation measures. Firstly, the paper finds the relatively undocumented characteristics and structures of firms in the value chain in the post-economic liberalisation era. As well as this, it finds typologies of the status of firms as either being in operation, closed down, or being placed under judicial management and the common characteristics that these typologies hold. The key findings show how a mixture of macro and local level aspects, such as value chain governance and the management structure of a business, leads to the most successful typology that is able to add value to the chain in the context of economic liberalisation, and thus unlock its socioeconomic development potential. These typologies are used in making industry and policy recommendations on achieving this balance between the macro and the local level, as well as recommendations for further academic research for more typologies and models on the case of cotton value chains in Sub-Saharan Africa. In doing so, this study adds to the small collection of academic evidence and policy recommendations for the challenges that African nations face when trying to incorporate into global commodity chains in attempts to benefit from their associated socioeconomic development opportunities.

Keywords: cotton-to-clothing value chain, economic liberalisation, restructuring value chain, typologies of firms, value chain governance, Zimbabwe

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Authors: Nils Haglund, Svenolof Dahlgren, Maria Rastam, Peik Gustafsson, Karin Kalien

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In Sweden, like in most developed countries, there is a substantial increase of children diagnosed with autism and other conditions within the autism spectrum (ASD). The rapid increase of ASD rates stresses the importance of developing care programs to provide support and comprehensive interventions for affected families. The current observational study was conducted in order to evaluate an ongoing Comprehensive Intensive Early Intervention (CIEI) program for children with autism in southern Sweden. The change in autism symptoms among children participating in CIEI (intervention group, n=67) was compared with children who received traditional habilitation services only (comparison group, n=27). Children of parents who accepted the offered CIEI-program, constituted the intervention group, whereas children, whose parents (for some reason) were not interested in the offered CIEI-program, constituted the comparison group. The CIEI-program was individualized to each child by experienced applied behavior analysis (ABA) specialists with different backgrounds as psychologists, speech pathologists or special education teachers, in cooperation with parents and preschool staff. Due to the individualization, the intervention could vary in intensity and techniques. The intensity was calculated to 15-25 hours each week at home and the preschool altogether. Each child was assigned one 'trainer', who was often employed as a preschool teacher but could have another educational background. An agreement between supervisor- parents and preschool staff was reached to confirm the intensity and content of the CIEI- program over an approximately two-year intervention period. Symptom changes were measured as evaluation-ADOS-2-scores, total- and severity-scores, minus the corresponding baseline-scores, divided by the time between baseline and evaluation. The difference between the study-groups regarding change of ADOS-2-scores was estimated using ANCOVA. In the current study, children in the CIEI-group improved their ADOS-2-total scores between baseline and evaluation (-0.8 scores per year; 95%CI: -1.2 to -0.4), whereas no such improvement was detected in the comparison group (+0.1 scores per year; 95%CI: -0.7 to +0.9). The change difference (change in the CIEI-group vs. change in the comparison group) was statistically significant, both crude and after adjusting for possible confounders (-1.1; 95%CI -1.9 to -0.4). Children in the CIEI-group also significantly improved their ADOS-calibrated severity scores, but not significantly differently so from the comparison group. The results from the current study indicate that the CIEI program significantly improves social and communicative skills among children with autism and that children with developmental delay could benefit to a similar degree as other children. The results support earlier studies reporting on the improvement of autism symptoms after early intensive interventions. The results from observational studies are difficult to interpret, but it is nevertheless of uttermost importance to evaluate costly autism intervention programs. Such results may be of immediate importance to healthcare organizations when allocating the already strained resources to different patient groups. Albeit the obvious limitation of the current naturalistic study, the results support previous positive studies and indicate that children with autism benefit from participating in early comprehensive, intensive programs and that investments in these programs may be highly justifiable.

Keywords: autism symptoms, ADOS-scores, evaluation, intervention program

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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As natural prebiotic (non-digestible) carbohydrates stimulate the growth of colon microflora and contribute to maintain the health of the host, analytical studies aiming at revealing the chemical behavior of these beneficial food components came to the forefront of interest. Food processing (especially baking) may lead to a significant conversion of the parent compounds, hence it is of utmost importance to characterize the transformation patterns and the plausible decomposition products formed by thermal degradation. The relevance of this work is confirmed by the wide-spread use of these carbohydrates (fructo-oligosaccharides, cyclodextrins, raffinose and resistant starch) in the food industry. More and more functional foodstuffs are being developed based on prebiotics as bioactive components. 12 different types of oligosaccharides have been investigated in order to reveal their thermal degradation characteristics. Different carbohydrate derivatives (D-fructose and D-glucose oligomers and polymers) have been exposed to elevated temperatures (150 °C 170 °C, 190 °C, 210 °C, and 220 °C) for 10 min. An advanced HPLC method was developed and used to identify the decomposition products of carbohydrates formed as a consequence of thermal treatment. Gradient elution was applied with binary solvent elution (acetonitrile, water) through amine based carbohydrate column. Evaporative light scattering (ELS) proved to be suitable for the reliable detection of the UV/VIS inactive carbohydrate degradation products. These experimental conditions and applied advanced techniques made it possible to survey all the formed intermediers. Change in oligomer distribution was established in cases of all studied prebiotics throughout the thermal treatments. The obtained results indicate increased extent of chain degradation of the carbohydrate moiety at elevated temperatures. Prevalence of oligomers with shorter chain length and even the formation of monomer sugars (D-glucose and D-fructose) might be observed at higher temperatures. Unique oligomer distributions, which have not been described previously are revealed in the case of each studied, specific carbohydrate, which might result in various prebiotic activities. Resistant starches exhibited high stability when being thermal treated. The degradation process has been modeled by a plausible reaction mechanism, in which proton catalyzed degradation and chain cleavage take place.

Keywords: prebiotics, thermal degradation, fructo-oligosaccharide, HPLC, ELS detection

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Authors: Vidya Nimkar Tayade

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Introduction: Intellectual capital of an organization is a key factor to success. Many companies invest a huge amount in their Research and development activities. Any innovation is helpful not only to that particular company but also to many other companies, industry and mankind as a whole. Companies undertake innovative changes for increasing their capital profitability and indirectly increase in pay packages of their employees. The quality of human capital can also improve due to such positive changes. Employees become more skilled and experienced due to such innovations and inventions. For increasing intangible capital, the author has referred to a couple of books and referred case studies to come to a conclusion. Different charts and tables are also referred to by the author. Case studies are more important because they are proven and established techniques. They enable students to apply theoretical concepts in real-world situations. It gives solutions to an open-ended problem with multiple potential solutions. There are three different strategies for undertaking intellectual capital increase. They are: Research push strategy/ Technology pushed approach, Market pull strategy/ approach and Open innovation strategy/approach. Research push strategy, In this strategy, research is undertaken and innovation is achieved on its own. After invention inventor company protects such invention and finds buyers for such invention. In this way, the invention is pushed into the market. In this method, research and development are undertaken first and the outcome of this research is commercialized. Market pull strategy, In this strategy, commercial opportunities are identified first and our research is concentrated in that particular area. For solving a particular problem, research is undertaken. It becomes easier to commercialize this type of invention. Because what is the problem is identified first and in that direction, research and development activities are carried on. Open invention strategy, In this type of research, more than one company enters into an agreement of research. The benefits of the outcome of this research will be shared by both companies. Internal and external ideas and technologies are involved. These ideas are coordinated and then they are commercialized. Due to globalization, people from the outside company are also invited to undertake research and development activities. Remuneration of employees of both the companies can increase and the benefit of commercialization of such invention is also shared by both the companies. Conclusion: In modern days, not only can tangible assets be commercialized, but also intangible assets can also be commercialized. The benefits of such an invention can be shared by more than one company. Competition can become more meaningful. Pay packages of employees can improve. It Is a need for time to adopt such strategies to benefit employees, competitors, stakeholders.

Keywords: innovation, protection, management, commercialization

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Authors: Antonio Piga

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This study explores the correlation between Systemic Functional Linguistics (SFL) and Critical Discourse Analysis (CDA) as tools for analysing the evolution of rhetoric in the communicative strategies adopted in a company’s Reports on social and environmental responsibility. In more specific terms, transitivity and ergativity- concepts from Systemic Functional Linguistics (SFL) - through the lenses of CDA, are employed as a theoretical means for the analysis of a longitudinal study in the communicative strategies employed by Saras SpA pre- and during the Covid-19 pandemic crisis. Saras is an Italian joint-stock company operating in oil refining and power generation. The qualitative and quantitative linguistic analysis carried out through the use of Sketch Engine software aims to identify and explain how rhetoric - and ideology - is constructed and presented through language use in Saras SpA Sustainability Reports. Specific focus is given to communication strategies to local and global communities and stakeholders in the years immediately before and during the Covid-19 pandemic. The rationale behind the study lies in the fact that 2020 and 2021 have been among the most difficult years since the end of World War II. Lives were abruptly turned upside down by the pandemic, which had grave negative effects on people’s health and on the economy. The result has been a threefold crisis involving health, the economy and social tension, with the refining sector being one of the hardest hit, since the oil refining industry was one of the most affected industries due to the general reduction in mobility and oil consumption brought about by the virus-fighting measures. Emphasis is placed on the construction of rhetorical strategies pre- and during the pandemic crisis using the representational process of transitivity and ergativity (SFL), thus revealing the close relationship between the use language in terms of Social Actors and semantic roles of syntactic transformation on the one hand, and ideological assumptions on the other. The results show that linguistic decisions regarding transitivity and ergativity choices play a crucial role in how effective writing achieves its rhetorical objectives in terms of spreading and maintaining dominant and implicit ideologies and underlying persuasive actions, and that some ideological motivation is perpetuated – if not actually overtly or subtly strengthened - in social-environmental Reports issued in the midst of the Covid-19 pandemic crisis.

Keywords: systemic functional linguistics, sustainability, critical discourse analysis, transitivity, ergativity

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

Procedia PDF Downloads 541

Authors: Ross J. Maestas

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Biofuels are derived from multiple renewable bioenergy feedstocks including animal fats, wood, starchy grains, and oil seeds. Transportation agencies have considered growing the latter two on underutilized and nontraditional lands that they manage, such as in the Right of Way (ROW), abandoned weigh stations, and at maintenance yards. These crops provide the opportunity to generate revenue or supplement fuel once converted and offer a solution to increasing fuel costs and instability by creating a ‘home-grown’ alternative. Biofuels are non-toxic, biodegradable, and emit less Green House Gasses (GHG) than fossil fuels, therefore allowing agencies to meet sustainability goals and regulations. Furthermore, they enable land managers to achieve soil erosion and roadside aesthetic strategies. The research sought to understand if the cultivation of a biofuel feedstock within the Arkansas State Highway Transportation Department’s (AHTD) managed and marginalized lands is feasible by identifying potential land areas and crops. To determine potential plots the parcel data was downloaded from Arkansas’s GIS office. ArcGIS was used to query the data for all variations of the names of property owned by AHTD and a KML file was created that identifies the queried parcel data in Google Earth. Furthermore, biofuel refineries in the state were identified to optimize the harvest to transesterification process. Agricultural data was collected from federal and state agencies and universities to assess various oil seed crops suitable for conversion and suited to grow in Arkansas’s climate and ROW conditions. Research data determined that soybean is the best adapted biofuel feedstock for Arkansas with camelina and canola showing possibilities as well. Agriculture is Arkansas’s largest industry and soybean is grown in over half of the state’s counties. Successful cultivation of a feedstock in the aforementioned areas could potentially offer significant employment opportunity for which the skilled farmers already exist. Based on compiled data, AHTD manages 21,489 acres of marginalized land. The result of the feasibility assessment offer suggestions and guidance should AHTD decide to further investigate this type of initiative.

Keywords: Arkansas highways, biofuels, renewable energy initiative, marginalized lands

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Authors: Thea Werkhoven, Wayne Cotton

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Adult and childhood rates of obesity in Australia are health concerns of high national priority, retaining epidemic status in the populations affected. Attempts to prevent further increases in prevalence of childhood obesity in the population aged below eighteen years have had varied success. A multidisciplinary approach has been used, employing strategies in schools, through established health care system usage and public health campaigns. Over the last decade a plateau in prevalence has been reached in the youth population afflicted by obesity and interest has peaked in school based strategies to prevent and treat overweight and obesity. Of interest to this study is the importance of the tertiary training of future health educators or health professionals destined to be involved in obesity prevention and treatment strategies. Health educators and health professionals are considered instrumental to the success of prevention and treatment strategies, required to possess sufficient and accurate knowledge in order to be effective in their positions. A common influence on the success of school based health promoting activities are the weight based attitudes possessed by health educators, known to be negative and biased towards overweight or obese children during training and practice. Whilst the tertiary training of future health professionals includes minimal nutrition education, there is no mandatory training in health education or nutrition for pre-service health educators in Australian tertiary institutions. This study aimed to assess the impact of a pedagogical intervention on pre-service health educators and health professionals enrolled in a health and wellbeing elective. The intervention aimed to increase nutrition knowledge and decrease weight bias and was embedded in the twelve week elective. Participants (n=98) were tertiary students at a major Australian University who were enrolled in health (47%) and non-health related degrees (53%). A quantitative survey using four valid and reliable instruments was conducted to measured nutrition knowledge, antifat attitudes and weight stereotyping attitudes at baseline and post-intervention. Scores on each instrument were compared between time points to check if they had significantly changed and to determine the effect of the intervention on attitudes and knowledge. Antifat attitudes at baseline were considered low and decreased further over the course of the intervention. Scores representing weight bias did decrease but the change was not significant. Fat stereotyping attitudes became stronger over the course of the intervention and this change was significant. Nutrition knowledge significantly improved from baseline to post-intervention. The design of the nutrition knowledge and attitude amelioration content of the intervention was semi-successful in achieving its outcomes. While the level of nutrition knowledge was improved over the course of the intervention, an unintentional increase was observed in weight based prejudice which is known to occur in interventions that employ stigma reduction methodologies. Further research is required into a structured methodology that increases level of nutrition knowledge and ameliorates weight bias at the tertiary level. In this way training provided would help prepare future health educators with the knowledge, skills and attitudes required to be effective and bias free in their practice.

Keywords: education, intervention, nutrition, obesity

Procedia PDF Downloads 199

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

Procedia PDF Downloads 400

Authors: Amelia Faotusia

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The blue economy concept was coined by Pacific nations in recognition of the importance of sustainably managing their extensive marine territories. This is especially important for major ocean-based economic sectors of Pacific economies, such as coastal tourism. There is an absence of research, however, on the key ways in which the blue economy concept has emerged in discourse and public policy in Pacific countries, as well as how it articulates with coastal tourism. This research helps to fill such a gap with a specific focus on Tonga through the application of a post-positivist research approach to conduct a desktop study of relevant national documents and qualitative interviews with relevant government staff, civil society organizations, and tourism operators. The findings of the research reflect the importance of institutional integration and partnerships for a successful blue economy transition and are presented in the form of two case studies corresponding to two sub-sectors of Tonga’s coastal tourism sector: (i) the whale-watching and swimming industry, and (ii) beach resorts and restaurants. A thematic analysis applied to the interview data of both cases then enabled the identification of key areas and issues for socio-economic policy intervention and recommendations in support of blue economy transitions in Tonga’s coastal tourism sector. Examples of the relevant areas and issues that emerged included the importance of foreign direct investment, local market access, community-based special management areas, as well as the need to address the anthropogenic impacts of tropical cyclones, whale tourism, plastic litter on coastal assets, and ecosystems. Policy and practical interventions in support of addressing such issues include a proposed restructuring of the whale-watching and swimming licensing system; integration of climate resilience, adaptation, and capacity building as priorities of local blue economy interventions; as well as strengthening of the economic sustainability dimension of blue economy policies. Finally, this research also revealed the need for further specificity and research on the influence and value of local Tongan culture and traditional knowledge, particularly within existing customary marine tenure systems, on Tonga’s national and sectoral blue economy policies and transitions.

Keywords: blue economy, coastal tourism, integrated ocean management, ecosystem resilience

Procedia PDF Downloads 86

Authors: S. C. Lin, M. S. Wu

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Japanese Scholar Manabu Sato has been advocating the Learning Community, which changed Japanese fundamental education during the last three decades. It was also called a “Quiet Revolution.” Manabu Sato criticized that traditional education only focused on individual competition, exams, teacher-centered instruction, and memorization. The students lacked leaning motivation. Therefore, Manabu Sato proclaimed that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. For a long time, secondary school education in Taiwan has been focused on exams and emphasized reciting and memorizing. The incident of “giving up learning” happened to some students. Manabu Sato’s learning community program has been implemented very successfully in Japan. It is worth exploring if learning community can resolve the issue of “Escape from learning” phenomenon among secondary school students in Taiwan. This study was the first year of a two-year project. This project applied a program theory-driven approach to evaluating the impact of teachers’ professional development interventions on students’ learning by using a mix of methods, qualitative inquiry, and quasi-experimental design. The current study was to show the results of using the method of theory-driven approach to program planning to design and evaluate a teachers’ professional development program (TPDP). The Manabu Sato’s learning community theory was applied to structure all components of a 54-hour workshop. The participants consisted of seven secondary school science teachers from two schools. The research procedure was comprised of: 1) Defining the problem and assessing participants’ needs; 2) Selecting the Theoretical Framework; 3) Determining theory-based goals and objectives; 4) Designing the TPDP intervention; 5) Implementing the TPDP intervention; 6) Evaluating the TPDP intervention. Data was collected from a number of different sources, including TPDP checklist, activity responses of workshop, LC subject matter test, teachers’ e-portfolio, course design documents, and teachers’ belief survey. The major findings indicated that program design was suitable to participants. More than 70% of the participants were satisfied with program implementation. They revealed that TPDP was beneficial to their instruction and promoted their professional capacities. However, due to heavy teaching loadings during the project some participants were unable to attend all workshops. To resolve this problem, the author provided options to them by watching DVD or reading articles offered by the research team. This study also established a communication platform for participants to share their thoughts and learning experiences. The TPDP had marked impacts on participants’ teaching beliefs. They believe that learning should be a sustainable process of “constantly weaving the relationship and the meanings” by having dialogues with learning materials, with peers, and with oneself. Having learned from TPDP, they applied a “learner-centered” approach and instructional strategies to design their courses, such as learning by doing, collaborative learning, and reflective learning. To conclude, participants’ beliefs, knowledge, and skills were promoted by the program instructions.

Keywords: program theory-driven approach, learning community, teacher professional development program, program evaluation

Procedia PDF Downloads 306

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 81

Authors: Natalia Rudeli, Elisabeth Viles, Adrian Santilli

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Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.

Keywords: cluster analysis, construction management, earned value, schedule

Procedia PDF Downloads 253

Authors: M. Turmanauli, T. Todua, O. Gvaberidze, R. Javakhadze, N. Chkhaidze, N. Khatiashvili

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Background: Mining process has the significant influence on human health and quality of life. In recent years the events in Georgia were reflected on the industry working process, especially minimal requirements of labor safety, hygiene standards of workplace and the regime of work and rest are not observed. This situation is often caused by the lack of responsibility, awareness, and knowledge both of workers and employers. The control of working conditions and its protection has been worsened in many of industries. Materials and Methods: For evaluation of the current situation the prospective epidemiological study by face to face interview method was conducted at Georgian “Manganese Zestafoni Ferroalloy Plant” in 2011-2013. 65.7% of employees (1428 bulletin) were surveyed and the incidence rates of temporary disability days were studied. Results: The average length of a temporary disability single accident was studied taking into consideration as sex groups as well as the whole cohort. According to the classes of harmfulness the following results were received: Class 2.0-10.3%; 3.1-12.4%; 3.2-35.1%; 3.3-12.1%; 3.4-17.6%; 4.0-12.5%. Among the employees 47.5% and 83.1% were tobacco and alcohol consumers respectively. According to the age groups and years of work on the base of previous experience ≥50 ages and ≥21 years of work data prevalence respectively. The obtained data revealed increased morbidity rate according to age and years of work. It was found that the bone and articulate system and connective tissue diseases, aggravation of chronic respiratory diseases, ischemic heart diseases, hypertension and cerebral blood discirculation were the leading among the other diseases. High prevalence of morbidity observed in the workplace with not satisfactory labor conditions from the hygienic point of view. Conclusion: According to received data the causes of morbidity are the followings: unsafety labor conditions; incomplete of preventive medical examinations (preliminary and periodic); lack of access to appropriate health care services; derangement of gathering, recording, and analysis of morbidity data. This epidemiological study was conducted at the JSC “Manganese Ferro Alloy Plant” according to State program “ Prevention of Occupational Diseases” (Program code is 35 03 02 05).

Keywords: occupational health, mining process, morbidity level, cerebral blood discirculation

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Zena Tredinnick-Kirby, Anna Divinsky, Brendan Berthold, Nicole Cingolani

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Faculty members from The Pennsylvania State University, Zena Tredinnick-Kirby, Ph.D., and Anna Divinsky are at the forefront of an innovative educational approach to improve access in asynchronous online art courses. Their pioneering work weaves virtual reality (VR) technologies to construct a more equitable educational experience for students by transforming their learning and engagement. The significance of their study lies in the need to bridge the digital divide in online art courses, making them more inclusive and interactive for all distance learners. In an era where conventional classroom settings are no longer the sole means of instruction, Tredinnick-Kirby and Divinsky harness the power of instructional technologies to break down geographical barriers by incorporating an interactive VR experience that facilitates community building within an online environment transcending physical constraints. The methodology adopted by Tredinnick-Kirby, and Divinsky is centered around integrating 3D virtual spaces into their art courses. Spatial.io, a virtual world platform, enables students to develop digital avatars and engage in virtual art museums through a free browser-based program or an Oculus headset, where they can interact with other visitors and critique each other’s artwork. The goal is not only to provide students with an engaging and immersive learning experience but also to nourish them with a more profound understanding of the language of art criticism and technology. Furthermore, the study aims to cultivate critical thinking skills among students and foster a collaborative spirit. By leveraging cutting-edge VR technology, students are encouraged to explore the possibilities of their field, experimenting with innovative tools and techniques. This approach not only enriches their learning experience but also prepares them for a dynamic and ever-evolving art landscape in technology and education. One of the fundamental objectives of Tredinnick-Kirby and Divinsky is to remodel how feedback is derived through peer-to-peer art critique. Through the inclusion of 3D virtual spaces into the curriculum, students now have the opportunity to install their final artwork in a virtual gallery space and incorporate peer feedback, enabling students to exhibit their work opening the doors to a collaborative and interactive process. Students can provide constructive suggestions, engage in discussions, and integrate peer commentary into developing their ideas and praxis. This approach not only accelerates the learning process but also promotes a sense of community and growth. In summary, the study conducted by the Penn State faculty members Zena Tredinnick-Kirby, and Anna Divinsky represents innovative use of technology in their courses. By incorporating 3D virtual spaces, they are enriching the learners' experience. Through this inventive pedagogical technique, they nurture critical thinking, collaboration, and the practical application of cutting-edge technology in art. This research holds great promise for the future of online art education, transforming it into a dynamic, inclusive, and interactive experience that transcends the confines of distance learning.

Keywords: Art, community building, distance learning, virtual reality

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Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

Abstract:

Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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