Search results for: capacity performance

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: S. Zouari, H. Ghorbel, H. Liao, R. Elleuch

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Research is increasingly moving towards the use of surface treatment processes to limit environmental effects. Electrolytic plating has traditionally been seen as a way to protect brass products, especially faucets, from mechanical and chemical damage. However, this method was not effective industrially, economically and ecologically. The aim of this work is to develop non-usual polymer coatings for brass faucets in order to improve the performance of brass and to replace electrolytic chromium coatings, thereby reducing environmental impact. Fluorinated-Ethylene-Propylene polymer (FEP) was chosen for its excellent mechanical and chemical properties and its good environmental performance. This coating was developed by spraying (painting) process onto brass substrates. The coatings obtained were characterized using a scanning electron microscope to evaluate the morphology of the deposits and their porosity rate. Grid adhesion, surface energy and corrosion tests (salt spray) were also performed to evaluate the mechanical and chemical behavior of these coatings properly. The results show that the deposits obtained have a homogeneous microstructure with a very low porosity rate. The results of the grid adhesion test prove the conformity of the test according to the NF077 standard. The coatings have a hydrophobic character following the low values of surface energy obtained and a very good resistance to corrosion. These results are interesting and may represent real technological issues in the industrial field.

Keywords: FEP coatings, spraying process, brass, adhesion, surface energy, corrosion resistance

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Authors: Chinedu Ejike

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The United States is now energy self-sufficient due to the production of shale oil reserves. With more than half of it being tapped daily in the United States, these unconventional reserves are massive and provide immense potential for future energy demands. Drilling horizontal wells and fracking are the primary methods for developing these reserves. Regrettably, recovery efficiency is rarely greater than 10%. As a result, optimizing recuperation offers a significant benefit. Huff and puff gas flooding and cyclic gas injection have all been demonstrated to be more successful than tapping the remaining oil in place. Methane, nitrogen, and carbon (IV) oxide, among other high-pressure gases, can be injected. Operators use Darcy's law to assess a reservoir's productive capacity, but they are unaware that the law may not apply to shale oil reserves. This is due to the fact that, unlike pressure differences alone, diffusion, concentration, and gas selection all play a role in the flow of gas injected into the wellbore. The reservoir drainage and oil sweep efficiency rates are determined by the transport method. This research assesses the parameters that influence the gas injection transport mechanism. Understanding the process causing these factors could accelerate recovery by two to three times, according to peer-reviewed studies and effective field testing.

Keywords: enhanced oil recovery, gas injection, shale oil, transport mechanism, unconventional reserve

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Authors: Nila Febri Wilujeng, Helda Risman

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Enjoying stable security within its region for the last 50 years, ASEAN nowadays contends with the global context emerging dynamically, which brings about multidimensional challenges and threats such as terrorism, radicalism, armed rebellion, hijacking, and other non-traditional threats. Dealing with these circumstances, ASEAN member states tighten its capacity by enhancing regional cooperation and strategic information exchange among ASEAN member states so-called ASEAN Our Eyes. This initiative adopted for the sake of forestalling any possible threat posed by violent extremism, radicalization, and terrorism through timely strategic information exchange among ASEAN member states. By using qualitative method, this paper will utilize regional security complex and international cooperation theories in analyzing the process to examine ASEAN Our Eyes based on its terms of reference. As a result, it portrays that ASEAN Our Eyes is able to undermine the gaps in the realm of strategic information exchange in monitoring the movement of violent extremism, radicalism, foreign terrorist fighters, and crime-terror nexus. However, it remains premature as a strategic measure to encounter those threats in the years to come.

Keywords: regional cooperation, counter-terrorism, ASEAN our eyes, strategic information exchange

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Authors: Mamert Mbonimpa, Ousseynou Kanteye, Élysée Tshibangu Ngabu, Rachid Amrou, Abdelkabir Maqsoud, Tikou Belem

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The management of mine wastes (waste rocks and tailings) containing sulphide minerals such as pyrite and pyrrhotite represents the main environmental challenge for the mining industry. Indeed, acid mine drainage (AMD) can be generated when these wastes are exposed to water and air. AMD is characterized by low pH and high concentrations of heavy metals, which are toxic to plants, animals, and humans. It affects the quality of the ecosystem through water and soil pollution. Different techniques involving soil materials can be used to control AMD generation, including impermeable covers (compacted clays) and oxygen barriers. The latter group includes covers with capillary barrier effects (CCBE), a multilayered cover that include the moisture retention layer playing the role of an oxygen barrier. Once AMD is produced at a mine site, it must be treated so that the final effluent at the mine site complies with regulations and can be discharged into the environment. Active neutralization with lime is one of the treatment methods used. This treatment produces sludge that is usually stored in sedimentation ponds. Other sludge management alternatives have been examined in recent years, including sludge co-disposal with tailings or waste rocks, disposal in underground mine excavations, and storage in technical landfill sites. Considering the ability of AMD neutralization sludge to maintain an alkaline to neutral pH for decades or even centuries, due to the excess alkalinity induced by residual lime within the sludge, valorization of sludge in specific applications could be an interesting management option. If done efficiently, the reuse of sludge could free up storage ponds and thus reduce the environmental impact. It should be noted that mixtures of sludge and soils could potentially constitute usable materials in CCBE for the rehabilitation of acid-generating mine sites, while sludge alone is not suitable for this purpose. The high sludge water content (up to 300%), even after sedimentation, can, however, constitute a geotechnical challenge. Adding lime to the mixtures can reduce the water content and improve the geotechnical properties. The objective of this paper is to investigate the impact of the sludge content (30, 40 and 50%) in sand-sludge mixtures (SSM) on their hydrogeotechnical properties (compaction, shrinkage behaviour, saturated hydraulic conductivity, and water retention curve). The impact of lime addition (dosages from 2% to 6%) on the moisture content, dry density after compaction and saturated hydraulic conductivity of SSM was also investigated. Results showed that sludge adding to sand significantly improves the saturated hydraulic conductivity and water retention capacity, but the shrinkage increased with sludge content. The dry density after compaction of lime-treated SSM increases with the lime dosage but remains lower than the optimal dry density of the untreated mixtures. The saturated hydraulic conductivity of lime-treated SSM after 24 hours of cure decreases by 3 orders of magnitude. Considering the hydrogeotechnical properties obtained with these mixtures, it would be possible to design CCBE whose moisture retention layer is made of SSM. Physical laboratory models confirmed the performance of such CCBE.

Keywords: mine waste, AMD neutralization sludge, sand-sludge mixture, hydrogeotechnical properties, mine site reclamation, CCBE

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Authors: Mohammad Ahmad Ahmad Odah

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Aging is a complex biological process characterized by the progressive decline of physiological functions and increased vulnerability to age-related diseases. Epigenetic changes, particularly DNA methylation alterations, play a critical role in the aging process by influencing gene expression and genomic stability. This study explores the potential of epigenetic reprogramming as a strategy to reverse aging phenotypes in human fibroblasts. Using CRISPR-Cas9 gene editing and small molecule inhibitors targeting DNA methylation and histone acetylation, we successfully induced significant changes in DNA methylation and gene expression profiles. Our results demonstrate a global reduction in DNA methylation levels and the identification of differentially methylated regions (DMRs) associated with cellular senescence and DNA repair. Additionally, treated fibroblasts exhibited enhanced proliferative capacity, reduced cellular senescence, and improved differentiation potential. These findings suggest that epigenetic reprogramming could be a promising approach for regenerative medicine, offering potential therapeutic strategies to counteract age-related decline and extend healthy lifespan.

Keywords: epigenetic reprogramming, aging, regenerative medicine, DNA methylation, cellular rejuvenation, CRISPR-Cas9, senescence

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Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Blair Arthur Agero Jr., Lucia Garcia Heras

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The triangular fibrocartilage complex (TFCC) is one of the crucial stabilizing ligaments of the wrist. The TFCC is also subject to excessive stress amongst performance athletes and enthusiasts. The excessive loading of the TFCC may lead to a partial or complete rupture that requires surgery. The recovery from an open TFCC surgical repair may take several months. Immobilization of the repaired wrist for a given period is part of all the current protocols in the post-surgical treatment. The immobilization to prevent the rotation of the forearm can last from six weeks to eight weeks with the wrist held in a neutral position. In all protocols reviewed, the pronosupination is only initiated between the 6th week and 8th week or even later after the cast is removed. The prolonged immobilization can cause stiffness of the wrist and hand. Furthermore, the entire period of post-surgical hand therapy has its economic impact, especially for performing athletes. However, delayed mobilization, specifically rotation of the wrist, is necessary to allow ligament healing. This study aims to report the effects of early mobilization of the wrist in athletes who had an open surgical repair of the TFCC. The surgery was done by the co-author, and the hand therapy was implemented by the main author. The cases documented spans from 2014 to 2019 and were all performed in Dubai, United Arab Emirates. All selected participants in this case study were provided with a follow-up questionnaire to ascertain their current condition since their surgery. The respondents reported high satisfaction in the results of their treatment and have verified zero re-rupture of their TFCC despite mobilizing and rotating the wrist at the third-week post-surgery during their hand therapy. There is also a negligible number of respondents who reported a limitation in their ranges of pronosupination. This case study suggests that early mobilization of the wrist after an open TFCC surgical repair can be more beneficial to the patient as opposed to the traditional treatment of prolonged immobilization. However, it should be considered that the patients selected in this case study are professional performance athletes and advanced fitness enthusiasts. Athletes are known to withstand vigorous physical stress in their training that may correlate to their ability to better cope with the progressive stress that was implemented during their hand therapy. Nevertheless, this approach has its merits, and application of it may be adjusted for patients with a similar injury and surgical procedure.

Keywords: hand therapy, performance athlete, TFCC repair, wrist ligament

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Authors: Salah E. El-Metwally, Marwan Abdo, Basem Abdel Wahed

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Fiber-reinforced polymer (FRP) bars have been proposed as an alternative to conventional steel bars; hence, the use of these non-corrosive and nonmetallic reinforcing bars has increased in various concrete projects. This concrete material is lightweight, has a long lifespan, and needs minor maintenance; however, its non-ductile nature and weak bond with the surrounding concrete create a significant challenge. The behavior of concrete elements reinforced with FRP bars has been the subject of several experimental investigations, even with their high cost. This study aims to numerically assess the viability of using FRP bars, as longitudinal reinforcement, in comparison with traditional steel bars, and also as prestressing tendons instead of the traditional prestressing steel. The nonlinear finite element analysis has been utilized to carry out the current study. Numerical models have been developed to examine the behavior of concrete beams reinforced with FRP bars or tendons against similar models reinforced with either conventional steel or prestressing steel. These numerical models were verified by experimental test results available in the literature. The obtained results revealed that concrete beams reinforced with FRP bars, as passive reinforcement, exhibited less ductility and less stiffness than similar beams reinforced with steel bars. On the other hand, when FRP tendons are employed in prestressing concrete beams, the results show that the performance of these beams is similar to those beams prestressed by conventional active reinforcement but with a difference caused by the two tendon materials’ moduli of elasticity.

Keywords: reinforced concrete, prestressed concrete, nonlinear finite element analysis, fiber-reinforced polymer, ductility

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Authors: Bambang Wispriyono, Satria Pratama, Haryoto Kusnoputranto, Faisal Yunus, Meliana Sari

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Introduction/objective: The impact of the development of motor vehicles is increasing the number of pollutants in the air. One of the substances that cause serious health problems is NO2. The health impacts arising from exposure to NO2 include pulmonary function impairment. The purpose of this study was to determine the relationship of NO2 exposure on the incidence of pulmonary function impairment. Methods: We are using a cross-sectional study design with 110 traffic police who were divided into two groups: exposed (police officers working on the highway) and the unexposed group (police officers working in the office). Election subject convenient sampling carried out in each group to the minimum number of samples met. Results: The results showed that the average NO2 in the exposed group was 18.72 ppb and unexposed group is 4.14 ppb. Pulmonary dysfunction on exposed and unexposed groups showed that FVC (Forced Vital Capacity) value are 88.68 and 90.27. And FEV1 (Forced Expiratory Volume in One) value are 94.9 and 95.16. Some variables like waist circumference, Body Mass Index, Visceral Fat, and Fat has associated with the incidence of Pulmonary Dysfunction (p < 0.05). Conclusion: Health monitoring is needed to decreasing health risk in Policeman.

Keywords: NO2, pulmonary dysfunction, police traffic, Jakarta

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Authors: Catherine Oluyemo

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In Africa, patriarchy has manifested itself in the socio-cultural, political, economic and legal institutions. The decree of the father as the male head of the family has contributed to the powerlessness of women in African nations. To buttress this perception, in his work Meno, Plato made a declaration in the platonic dialogue that the desirable quality of a man should be the capacity to administer the state, and in the administration of it to benefit his friends and harm his enemies; and he must also be careful not to suffer harm himself. Furthermore, he said: a woman's good worth may also be easily described as ordering her house, keep what is indoors, and obey her husband. The works of Aristotle portrayed women as morally, intellectually, and physically inferior to men; they saw women as the property of men; claimed that women's role in society was to reproduce and serve men in the household; and saw male domination of women as natural and virtuous. This has been sustained for ages and is incessantly impinging on the involvement of women in African leadership positions. The purpose of this paper is to make sense of the concept of patriarchy in relations to women participation in Africa leadership, and its challenges in the participation of women in the leadership positions of Africa. It seeks to discover what women should do to make their voices heard, to participate in leadership arrangements so as to actualize their potentials in contributing to the development of Africa.

Keywords: women, leadership, patriarchy, development, actualize, potentials

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: C. R. Danielle, S. Erik, T. Patrick, M. Hugh

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In the last decade there has been an increase in demand for fine grinding due to the depletion of coarse-grained orebodies and an increase of processing fine disseminated minerals and complex orebodies. These ores have provided new challenges in concentrator design because fine and ultra-fine grinding is required to achieve acceptable recovery rates. Therefore, the correct design of a grinding circuit is important for minimizing unit costs and increasing product quality. The use of ball mills for grinding in fine size ranges is inefficient and, therefore, vertical stirred grinding mills are becoming increasingly popular in the mineral processing industry due to its already known high energy efficiency. This work presents a hypothesis of a methodology to predict the product size distribution of a vertical stirred mill using a Bond ball mill. The Population Balance Model (PBM) was used to empirically analyze the performance of a vertical mill and a Bond ball mill. The breakage parameters obtained for both grinding mills are compared to determine the possibility of predicting the product size distribution of a vertical mill based on the results obtained from the Bond ball mill. The biggest advantage of this methodology is that most of the minerals processing laboratories already have a Bond ball mill to perform the tests suggested in this study. Preliminary results show the possibility of predicting the performance of a laboratory vertical stirred mill using a Bond ball mill.

Keywords: bond ball mill, population balance model, product size distribution, vertical stirred mill

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Authors: James Andrew Fitzjohn

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This paper intends to discuss and explore the practical aspects of cracking encrypted messages with quantum computers. The theory of this process has been shown and well described both in academic papers and headline-grabbing news articles, but with all theory and hyperbole, we must be careful to assess the practicalities of these claims. Therefore, we will use real-world devices and proof of concept code to prove or disprove the notion that quantum computers will render the encryption technologies used by many websites unfit for purpose. It is time to discuss and implement the practical aspects of the process as many advances in quantum computing hardware/software have recently been made. This paper will set expectations regarding the useful lifespan of RSA and cipher lengths and propose alternative encryption technologies. We will set out comprehensive roadmaps describing when and how encryption schemes can be used, including when they can no longer be trusted. The cost will also be factored into our investigation; for example, it would make little financial sense to spend millions of dollars on a quantum computer to factor a private key in seconds when a commodity GPU could perform the same task in hours. It is hoped that the real-world results depicted in this paper will help influence the owners of websites who can take appropriate actions to improve the security of their provisions.

Keywords: quantum computing, encryption, RSA, roadmap, real world

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Authors: Chitresh Prasad, Arvind Ramesh, Aditya Virkar, Karan Dholkaria, Vinayak Malhotra

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Solid Propellant Rocket is a rocket that utilises a combination of a solid Oxidizer and a solid Fuel. Success in Solid Rocket Motor design and development depends significantly on knowledge of burning rate behaviour of the selected solid propellant under all motor operating conditions and design limit conditions. Most Solid Motor Rockets consist of the Main Engine, along with multiple Boosters that provide an additional thrust to the space-bound vehicle. Though widely used, they have been eclipsed by Liquid Propellant Rockets, because of their better performance characteristics. The addition of a catalyst such as Iron Oxide, on the other hand, can drastically enhance the performance of a Solid Rocket. This scientific investigation tries to emulate the working of a Solid Rocket using Sparklers and Energized Candles, with a central Energized Candle acting as the Main Engine and surrounding Sparklers acting as the Booster. The Energized Candle is made of Paraffin Wax, with Magnesium filings embedded in it’s wick. The Sparkler is made up of 45% Barium Nitrate, 35% Iron, 9% Aluminium, 10% Dextrin and the remaining composition consists of Boric Acid. The Magnesium in the Energized Candle, and the combination of Iron and Aluminium in the Sparkler, act as catalysts and enhance the burn rates of both materials. This combustion of Metallized Propellants has an influence over the regression rate of the subject candle. The experimental parameters explored here are Separation Distance, Systematically varying Configuration and Layout Symmetry. The major performance parameter under observation is the Regression Rate of the Energized Candle. The rate of regression is significantly affected by the orientation and configuration of the sparklers, which usually act as heat sources for the energized candle. The Overall Efficiency of any engine is factorised by the thermal and propulsive efficiencies. Numerous efforts have been made to improve one or the other. This investigation focuses on the Orientation of Rocket Motor Design to maximize their Overall Efficiency. The primary objective is to analyse the Flame Spread Rate variations of the energized candle, which resembles the solid rocket propellant used in the first stage of rocket operation thereby affecting the Specific Impulse values in a Rocket, which in turn have a deciding impact on their Time of Flight. Another objective of this research venture is to determine the effectiveness of the key controlling parameters explored. This investigation also emulates the exhaust gas interactions of the Solid Rocket through concurrent ignition of the Energized Candle and Sparklers, and their behaviour is analysed. Modern space programmes intend to explore the universe outside our solar system. To accomplish these goals, it is necessary to design a launch vehicle which is capable of providing incessant propulsion along with better efficiency for vast durations. The main motivation of this study is to enhance Rocket performance and their Overall Efficiency through better designing and optimization techniques, which will play a crucial role in this human conquest for knowledge.

Keywords: design modifications, improving overall efficiency, metallized combustion, regression rate variations

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Authors: Nyeng P. Gyang

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Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

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Authors: Andrzej Kesiak

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Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

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Authors: R. S. Quintal, J. L. Tesch Santos, M. D. Davis, E. C. de Santana, M. de F. Bandeira dos Santos

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The objective is to identify the contributions from the introduction of the computerized system deal within the Accounting Department of Brazilian Navy Financial Directorship and its possible effects on the budgetary and financial harvest of Brazilian Navy. The relevance lies in the fact that the management process is responsible for the continuous improvement of organizational performance through higher levels of quality in their activities. Improvements in organizational processes have direct effects on crops cost, quality, reliability, flexibility and speed. The method of study of this research is the case study. The choice of case study attended, among other demands, a need for greater flexibility to study processes related to a computerized system. The sources of evidence were used literature, documentary and direct observation. Direct observation was made by monitoring the implementation of the computerized system in the Division of Management Analysis. The main findings of the study point to the fact that the computerized system may contribute significantly to the standardization of information. There was improvement of internal processes in the division of management analysis, made possible the consolidation of a standard management and performance analysis that contribute to global homogeneity in the treatment of information essential to the process of decision making. This study has limitations related to the fact the search result be subject exclusively to the case studied, and it is impossible to generalize to other organs of government.

Keywords: process management, management control, business intelligence, Brazilian Navy

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Andrew Rylance, Anna Spenceley

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An evaluation was undertaken to understand opportunities for stimulating local enterprise development within the tourism supply chain, linked to a private game reserve in South Africa, the Sabi Sand Game Reserve, which neighbors the Kruger National Park. The study focused on understanding the market demand for local products and services from commercial lodges, and the current local supply from enterprises and entrepreneurs in local communities. This article quantifies the value of current procurement spend by lodges on local products and services and estimates their potential future expenditure. The study matches these responses with the availability of products and services in the neighboring communities. It also provides insights into relationships between private lodges, game reserves and local communities in South Africa. It concurs with previous research on tourism supply chains in rural South Africa, and also makes recommendations for the development of local businesses with higher technical capacity development.

Keywords: tourism, communities, business development, South Africa, Sabi Sand Game Reserve, market study, supply study

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Authors: Sayantan Saha, Sambit Supriya Dash, Vinayak Malhotra

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Efficient propulsive systems development is an area of major interest and concern in aerospace industry. Combustion forms the most reliable and basic form of propulsion for ground and space applications. The generation of large amount of energy from a small volume relates mostly to the flaming combustion. This study deals with instabilities associated with flaming combustion. Combustion is always accompanied by acoustics be it external or internal. Chemical propulsion oriented rockets and space systems are well known to encounter acoustic instabilities. Acoustic brings in changes in inter-energy conversion and alter the reaction rates. The modified heat fluxes, owing to wall temperature, reaction rates, and non-linear heat transfer are observed. The thermoacoustic instabilities significantly result in reduced combustion efficiency leading to uncontrolled liquid rocket engine performance, serious hazards to systems, assisted testing facilities, enormous loss of resources and every year a substantial amount of money is spent to prevent them. Present work attempts to fundamentally understand the mechanisms governing the thermoacoustic combustion in liquid rocket engine using a simplified experimental setup comprising a butane cylinder and an impinging acoustic source. Rocket engine produces sound pressure level in excess of 153 Db. The RL-10 engine generates noise of 180 Db at its base. Systematic studies are carried out for varying fuel flow rates, acoustic levels and observations are made on the flames. The work is expected to yield a good physical insight into the development of acoustic devices that when coupled with the present propulsive devices could effectively enhance combustion efficiency leading to better and safer missions. The results would be utilized to develop impinging acoustic devices that impinge sound on the combustion chambers leading to stable combustion thus, improving specific fuel consumption, specific impulse, reducing emissions, enhanced performance and fire safety. The results can be effectively applied to terrestrial and space application.

Keywords: combustion instability, fire safety, improved performance, liquid rocket engines, thermoacoustics

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Authors: Daniel Ferreira, José M. Marques Oliveira, Filipe Oliveira

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Wear phenomena is critical in injection moulding processes, causing failure of the components, and making the parts more expensive with an additional wasting time. When very abrasive materials are being injected inside the steel mould’s cavities, such as polymers reinforced with abrasive fibres, the consequences of the wear are more evident. Maraging steel (1.2709) is commonly employed in moulding components to resist in very aggressive injection conditions. In this work, the wear performance of the SLM produced 1.2709 maraging steel reinforced by ultrafine titanium and tungsten carbide (TiC-WC), was investigated using a pin-on-disk testing apparatus. A polypropylene reinforced with 40 wt.% fibreglass (PP40) disk, was used as the counterpart material. The wear tests were performed at 40 N constant load and 0.4 ms-1 sliding speed at room temperature and humidity conditions. The experimental results demonstrated that the wear rate in the 18Ni300-TiC-WC composite is lower than the unreinforced 18Ni300 matrix. The morphology and chemical composition of the worn surfaces was observed by 3D optical profilometry and scanning electron microscopy (SEM), respectively. The resulting debris, caused by friction, were also analysed by SEM and energy dispersive X-ray spectroscopy (EDS). Their morphology showed distinct shapes and sizes, which indicated that the wear mechanisms, may be different in maraging steel produced by casting and SLM. The coefficient of friction (COF) was recorded during the tests, which helped to elucidate the wear mechanisms involved.

Keywords: selective laser melting, nanocomposites, injection moulding, polypropylene with fibreglass

Procedia PDF Downloads 155

Authors: Metinee Kawsomboon, Thanchanok Tulaphol, Manit Nithitanakul, Jitima Preechawong

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PolyHIPE is a porous polymeric material from polymerization of high internal phase emulsion (HIPE) which contains 74% of internal phase (disperse phase) and 26 % of external phase (continues phase). Typically, polyHIPE was prepared from styrene (S) and divinylbenzene (DVB) and they were used in various kind of applications such as catalyst support, gas adsorption, separation membranes, and tissue engineering scaffolds due to high specific surface areas, high porousity, ability to adsorb large quantities of liquid. In this research, cellulose from water hyacinth (Eichornia Crassipes), an aquatic plant that grows and spread rapidly in rivers and waterways in Thailand was added into polyHIPE to increase mechanical property of polyHIPE. Addition of unmodified and modified cellulose to poly(S/DVB)HIPE resulting in a decrease in the surface area and thermal stability of the resulting materials. Mechanical properties of the resulting polyHIPEs filled with both unmodified and modified cellulose exhibited higher compressive strength and Young’s modulus by 146.3% and 162.5% respectively, compared to unfilled polyHIPEs. The water adsorption capacity of filled polyHIPE was also improved.

Keywords: porous polymer, PolyHIPE, cellulose, surface modification, water hyacinth

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

Abstract:

The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

Procedia PDF Downloads 76

Authors: V. Viliene, A. Raceviciute-Stupeliene, V. Sasyte, V. Slausgalvis, R. Gruzauskas, J. Al-Saifi

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Animal nutritionists and scientists have searched for alternative measures to improve the production. One of such alternative is use of organic acids as feed additive in animal nutrition. The study was conducted to investigate the impact of butyric acids, calcium formate, organic acids, and its salts (BCOS) additives on rabbit’s productive performance, carcass traits and meat quality. The study was conducted with 14 Californian breed rabbits. The rabbits were assigned to two treatment groups (seven rabbits per each treatment group). The dietary treatments were 1) control diet, 2) diet supplemented with a mixture BCOS - 2 kg/t of feed. Growth performance characteristics (body weight, daily weight gain, daily feed intake, feed conversion ratio, mortality) were evaluated. Rabbits were slaughtered; carcass characteristics and meat quality were evaluated. Samples loin and hind leg meat were analysed to determine carcass characteristics, pH and colour measurements, cholesterol, and malonyldialdehyde (MDA) content in loin and hind leg meat. Differences between treatments were significant for body weight (1.30 vs. 1.36 kg; P<0.05), daily weight gain (16.60 vs. 17.85 g; P<0.05), and daily feed intake (78.25 vs. 80.58 g; P<0.05) for control and experimental group respectively for the entire experimental period (from 28–77 days old). No significant differences were found in feed conversion ratio and mortality. The feed additives insertion in the diets did not significantly influence the carcass yield or the proportions of the various carcass parts and organs. Differences between treatments were significant for pH value after 48h in loin (5.86 vs. 5.74; P<0.05), hind leg meat (6.62 vs. 6.65; P<0.05), more intense colour b* of loin (5.57 vs. 6.06; P<0.05), less intense colour a* (14.99 vs. 13.15; P<0.05) in hind leg meat. Cholesterol content in hind leg meat decreased by 17.67 mg/100g compared to control group (P<0.05). After storage for three months, MDA concentration decreased in loin and hind leg meat by 0.3 μmol/kg and 0.26 μmol/kg respectively compared to that of the control group (P<0.05). The results of this study suggest that BCOS could potentially be used in rabbit nutrition with consequent benefits on the rabbits’ productivity and nutritional quality of rabbit meat for consumers.

Keywords: butyric acids, Ca formate, meat quality, organic acids salts, rabbits, productivity

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: Wajahat Ali, Shakeel Javaid

Abstract:

In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

Procedia PDF Downloads 83

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

Abstract:

Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

Procedia PDF Downloads 124