Search results for: industrial structure optimization

Authors: Abu Harera Nadeem, Kingsley Donkor

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Tea is a popular beverage due to its flavour, aroma and antioxidant properties—with the most consumed varieties being green and black tea. Antioxidants in tea can lower the risk of Alzheimer’s and heart disease and obesity. However, these teas contain heavy metals such as Hg, Cd, or Pb, which can cause autoimmune diseases like Graves disease. In this study, 11 heavy metals in various commercial green, black, and oolong tea samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Two methods of sample preparation were compared for accuracy and precision, which were microwave-assisted digestion and ultrasonic-assisted extraction. The developed method was further validated by detection limit, precision, and accuracy. Results showed that the proposed method was highly sensitive with detection limits within parts-per-billion levels. Reasonable method accuracy was obtained by spiked experiments. The findings of this study can be used to delve into the link between tea consumption and disease and to provide information for future studies on metal determination in tea.

Keywords: ICP-MS, green tea, black tea, microwave-assisted acid digestion, ultrasound-assisted extraction

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Authors: Harish Kumar Ponnappan, Joseph C. Chen

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The main objective of this research is to optimize the surface roughness of a milling operation on AISI 1018 steel using live tooling on a HAAS ST-20 lathe. In this study, Taguchi analysis is used to optimize the milling process by investigating the effect of different machining parameters on surface roughness. The L₉ orthogonal array is designed with four controllable factors with three different levels each and an uncontrollable factor, resulting in 18 experimental runs. The optimal parameters determined from Taguchi analysis were feed rate – 76.2 mm/min, spindle speed 1150 rpm, depth of cut – 0.762 mm and 2-flute TiN coated high-speed steel as tool material. The process capability Cp and process capability index Cpk values were improved from 0.62 and -0.44 to 1.39 and 1.24 respectively. The average surface roughness values from the confirmation runs were 1.30 µ, decreasing the defect rate from 87.72% to 0.01%. The purpose of this study is to efficiently utilize the Taguchi design to optimize the surface roughness in a milling operation using live tooling.

Keywords: live tooling, surface roughness, taguchi analysis, CNC milling operation, CNC turning operation

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Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy

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The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.

Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling

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Authors: Yusuf Ziya Ayık, Ferhat Kahveci

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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.

Keywords: cost of query, database management systems, materialized view, query performance

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Authors: Yasith Mindula Saipath Wickramasinghe

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Augmented reality applications require a high processing power to load, render and live stream high-definition AR models and virtual scenes; it also requires device sensors to work excessively to coordinate with internal hardware, OS and give the expected outcome in advance features like object detection, real time tracking, as well as voice and text recognition. Excessive thermal generation due to these advanced functionalities has become a major research problem as it is unbearable for smaller mobile devices to manage such heat increment and battery drainage as it causes physical harm to the devices in the long term. Therefore, effective thermal management is one of the major requirements in Augmented Reality application development. As this paper discusses major causes for this issue, it also provides possible solutions in the means of operating system adaptations as well as further research on best coding practises to optimize the application performance that reduces thermal excessive thermal generation.

Keywords: augmented reality, device thermal management, GPU, operating systems, device I/O, overheating

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Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

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Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

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Authors: Elionai Moura, José A. Cunha, César Analide

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This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

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Authors: Rossella Marzullo

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Family plays a central role in the Calabrian criminal organization, which draws its strength from blood ties and gender stereotypes that still impose a strong verticalization of intra-family relationships for the benefit of men. However, female figures are of great importance in the organizational structure of the 'Ndrangheta families, despite the fact that they appear to be formally suffocated by the culture of gender subordination still strongly present in the archaic world of criminal organizations. And this is so much true that over time, the women of the 'Ndrangheta have added to the function of ‘internal containment’, the increasingly explicit function of intermediaries in the ‘external’ activities of the clan. But what happens in the 'Ndrangheta if women break the bond and decide to speak? The results are shocking. When a woman starts talking to ask the institutions for help, the system ‘goes crazy’, because the woman is considered the means of consolidating and transmitting family codes: she educates, forges, holds the structure together. If a woman from the 'Ndrangheta decides to speak out and get out of the family bottlenecks of the clan, she does not exclusively destroy the family; she destroys the system. This happens because, while not playing the same roles as men within organizations, women carry out support activities as intermediaries for the circulation of communications, thus ensuring the operability of the gang in practice and on a daily basis. Crossing the border means breaking the bonds of belonging, thus questioning one's own identity and reconstructing it according to other points of reference. How much these disruptive choices are feared by the men of the 'Ndrangheta has been seen in the dramatic stories of Lea Garofalo and Maria Concetta Cacciola: the fear of the breaking of the family pact, of the earthquake that arises from within, has marked their fate of death, useful both to stop the judicial action and to recompose the organization's estate under the aegis of terror. With physical, psychological violence, underhanded torture, and moral blackmail, the men of the mafia family tried to heal the shock caused by the voices of women, relying on violence and yet another attempt to subordinate them. This proves that the 'Ndrangheta is really afraid of them. The female voices of the 'Ndrangheta, who have shaken a consolidated and considered intangible system, represent the anti-'ndrangheta par excellence; in their choices, there is an even stronger desire to break with the mafia world.

Keywords: families, gender, ‘Ndrangheta, stereotypes

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Authors: Wen Cai Ng, Saman Ilankoon, Meng Nan Chong

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The vast increase in global energy demand, coupled with the growing concerns on environmental issues, has triggered the search for cleaner alternative energy sources. In view of this, the photoelectrochemical (PEC) water splitting offers a sustainable hydrogen (H2) production route that only requires solar energy, water, and PEC system operating in an ambient environment. However, the current advancement of PEC water splitting technologies is still far from the commercialization benchmark indicated by the solar-to-H2 (STH) efficiency of at least 10 %. This is largely due to the shortcomings of photoelectrodes used in the PEC system, such as the rapid recombination of photogenerated charge carriers and limited photo-responsiveness in the visible-light spectrum. Silver orthophosphate (Ag3PO4) possesses many desirable intrinsic properties for the fabrication into photoanode used in PEC systems, such as narrow bandgap of 2.4 eV and low valence band (VB) position. Hence, in this study, a highly efficient Ag3PO4-based photoanode was synthesized and characterized. The surface of the Ag foil substrate was directly oxidized to fabricate a top layer composed of {111}-bound Ag3PO4 tetrahedrons layer with a porous structure, forming the dual-layer Ag/Ag3PO4 photoanode. Furthermore, the key synthesis parameters were systematically investigated by varying the concentration ratio of capping agent-to-precursor (R), the volume ratio of hydrogen peroxide (H2O2)-to-water, and reaction period. Results showed that the optimized dual-layer Ag/Ag3PO4 photoanode achieved a photocurrent density as high as 4.19 mA/cm2 at 1 V vs. Ag/AgCl for the R-value of 4, the volume ratio of H2O2-to-water of 3:5 and 20 h reaction period. The current work provides a solid foundation for further nanoarchitecture modification strategies on Ag3PO4-based photoanodes for more efficient PEC water splitting applications. This piece of information needs to be backed up by evidence; therefore, you need to provide a reference. As the abstract should be self-contained, all information requiring a reference should be removed. This is a fact known to the area of research, and not necessarily required a reference to support.

Keywords: solar-to-hydrogen fuel, photoelectrochemical water splitting, photoelectrode, silver orthophosphate

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Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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Authors: Zahra Khan

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Hydrogels are a macromolecular network of hydrophilic copolymers with physical or chemical cross-linking structures with significant water uptake capabilities. They are a promising substrate for surface-enhanced Raman spectroscopy (SERS) as they are both flexible and biocompatible materials. Conventional SERS-active substrates suffer from limitations such as instability and inflexibility, which restricts their use in broader applications. Gelatin-based hydrogels have been synthesised in a facile and relatively quick method without the use of any toxic cross-linking agents. Composite gel material was formed by combining the gelatin with simple polymers to enhance the functional properties of the gel. Gold nanoparticles prepared by a reproducible seed-mediated growth method were combined into the bulk material during gel synthesis. After gel formation, the gel was submerged in the analyte solution overnight. SERS spectra were then collected from the gel using a standard Raman spectrometer. A wide range of analytes was successfully detected on these hydrogels showing potential for further optimization and use as SERS substrates for biomedical applications.

Keywords: gelatin, hydrogels, flexible materials, SERS

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Authors: Pejman Hosseiniun, Rose Shayeghi, Alireza Farzaneh, Abolghasem Ghasempour

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Using LED lamps as lighting resources with new technology in designing lighting systems has been studied in this article. In this respect a history of LED emergence, its different manufacturing methods and technologies were revised, then their structure, light production line, its application and benefits in lighting industry has been evaluated. Finally, there is a comparison between these lamps and ordinary lamps to assess light parameters as well as energy consumption using DIALux software. Considering the results of analogies LED lamps have lower consumption and more lighting yield, therefore they are more economically feasible. Color variety, longer usage lap (circa 10 years) and compatibility with DC voltages are other LED lamps perquisites.

Keywords: LED, lighting efficiency, lighting intensity, luminance

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Authors: Istvan Szilagyi, Marko Pavlovic, Paul Rouster

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Antioxidant enzymes are the most efficient defense systems against reactive oxygen species, which cause severe damage in living organisms and industrial products. However, their supplementation is problematic due to their high sensitivity to the environmental conditions. Immobilization on carrier nanoparticles is a promising research direction towards the improvement of their functional and colloidal stability. In that way, their applications in biomedical treatments and manufacturing processes in the food, textile and cosmetic industry can be extended. The main goal of the present research was to prepare and formulate antioxidant bionanocomposites composed of superoxide dismutase (SOD) enzyme, anionic clay (layered double hydroxide, LDH) nanoparticle and heparin (HEP) polyelectrolyte. To characterize the structure and the colloidal stability of the obtained compounds in suspension and solid state, electrophoresis, dynamic light scattering, transmission electron microscopy, spectrophotometry, thermogravimetry, X-ray diffraction, infrared and fluorescence spectroscopy were used as experimental techniques. LDH-SOD composite was synthesized by enzyme immobilization on the clay particles via electrostatic and hydrophobic interactions, which resulted in a strong adsorption of the SOD on the LDH surface, i.e., no enzyme leakage was observed once the material was suspended in aqueous solutions. However, the LDH-SOD showed only limited resistance against salt-induced aggregation and large irregularly shaped clusters formed during short term interval even at lower ionic strengths. Since sufficiently high colloidal stability is a key requirement in most of the applications mentioned above, the nanocomposite was coated with HEP polyelectrolyte to develop highly stable suspensions of primary LDH-SOD-HEP particles. HEP is a natural anticoagulant with one of the highest negative line charge density among the known macromolecules. The experimental results indicated that it strongly adsorbed on the oppositely charged LDH-SOD surface leading to charge inversion and to the formation of negatively charged LDH-SOD-HEP. The obtained hybrid materials formed stable suspension even under extreme conditions, where classical colloid chemistry theories predict rapid aggregation of the particles and unstable suspensions. Such a stabilization effect originated from electrostatic repulsion between the particles of the same sign of charge as well as from steric repulsion due to the osmotic pressure raised during the overlap of the polyelectrolyte chains adsorbed on the surface. In addition, the SOD enzyme kept its structural and functional integrity during the immobilization and coating processes and hence, the LDH-SOD-HEP bionanocomposite possessed excellent activity in decomposition of superoxide radical anions, as revealed in biochemical test reactions. In conclusion, due to the improved colloidal stability and the good efficiency in scavenging superoxide radical ions, the developed enzymatic system is a promising antioxidant candidate for biomedical or other manufacturing processes, wherever the aim is to decompose reactive oxygen species in suspensions.

Keywords: clay, enzyme, polyelectrolyte, formulation

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Authors: Chung Hyun Goh, Armin Yazdanshenas, X. Neil Dong, Yong Tai Wang

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Physical rehabilitation is a necessary step in regaining lower body function after a partial paralysis caused by a spinal cord injury or a stroke. The purpose of this paper is to present the development and optimization of a training device that accurately recreates the motions in a gait cycle with the goal of rehabilitation for individuals with incomplete spinal cord injuries or who are victims of a stroke. A functional electrical stimulator was used in conjunction with the training device to stimulate muscle groups pertaining to rehabilitative walking. The feasibility and reliability of the design are presented. To validate the design functionality, motion analyses of the knee and ankle gait paths were made using motion capture systems. Key results indicate that the robotic walking training device provides a viable mode of physical rehabilitation.

Keywords: functional electrical stimulation, rehabilitative walking, robotic walking training device, spinal cord injuries

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Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

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Authors: Venkataramana Sovenahalli Badigar, B. M. Suryakanth, Akshar Prasanna, Karthik Veeramalai, Vishwak Ram Vishwak Ram

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Technological advances have led to widespread autonomy in vehicles. Empowering these autonomous with the intelligence to cooperate amongst themselves leads to a more efficient use of the resources available to them. This paper proposes a demonstration of a swarm algorithm implemented on a group of autonomous vehicles. The demonstration involves two ground bots and an aerial drone which cooperate amongst them to locate an object of interest. The object of interest is modelled using a high-intensity light source which acts as a beacon. The ground bots are light sensitive and move towards the beacon. The ground bots and the drone traverse in random paths and jointly locate the beacon. This finds application in various scenarios in where human interference is difficult such as search and rescue during natural disasters, delivering crucial packages in perilous situations, etc. Experimental results show that the modified swarm algorithm implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.

Keywords: swarm algorithm, object localization, ground bots, drone, beacon

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

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Authors: Shiraz M. Mammadov, Elvin M. Aliyev, Adil A. Garibov

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The role of the disulfochloride benzene in unsaturated rubbers (SKIN, SKN-26) which is in the systems of SKIN+disulfochloride benzene and SKN-26+disulfochloride benzene was studied by the radiation exposure. By the usage of physical, chemical and spectral methods the changes in the molecular structure of the rubber were shown after irradiation by y-rays at 300 kGy. The outputs and the emergence of the crosslinking in the elastomers for each system depending on absorbed dose were defined. It is suggested that the mechanism of radiation occurs by the heterogeneous transformation of elastomers in the presence of disulfochloride benzene.

Keywords: acrylonitrile-butadiene rubber, crosslinking, polyfunctional monomers, radiation, sensitizier, vulcanization

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Authors: Verónica Diaz Quezada

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This research examines the teaching models used by secondary math teachers when teaching logarithmic, quadratic and exponential functions. For this, descriptive case studies have been carried out on 5 secondary teachers. These teachers have been chosen from 3 scientific-humanistic and technical schools, in Chile. Data have been obtained through non-participant class observation and the application of a questionnaire and a rubric to teachers. According to the results, the didactic model that prevails is the one that starts with an interactive strategy, moves to a more content-based structure, and ends with a reinforcement stage. Nonetheless, there is always influence from teachers, their methods, and the group of students.

Keywords: teaching models, math teachers, functions, secondary education

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Authors: Mardin Abdalqadir, Paul Adzakro, Tannaz Pak, Sina Rezaei Gomari

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Climate change and global warming recently became significant concerns due to the massive emissions of greenhouse gases into the atmosphere, predominantly CO2 gases. Therefore, it is necessary to find sustainable and inexpensive methods to capture the greenhouse gasses and protect the environment for live species. The application of naturally available and cheap adsorbents of carbon such as clay minerals became a great interest. However, the minerals prone to low storage capacity despite their high affinity to adsorb carbon. This paper aims to explore ways to improve the pore volume and surface area of two selected clay minerals, ‘montmorillonite and kaolinite’ by acid treatment to overcome their low storage capacity. Montmorillonite and kaolinite samples were treated with different sulfuric acid concentrations (0.5, 1.2 and 2.5 M) at 40 °C for 8 hours to achieve the above aim. The grain size distribution and morphology of clay minerals before and after acid treatment were explored with Scanning Electron Microscope to evaluate surface area improvement. The ImageJ software was used to find the porosity and pore volume of treated and untreated clay samples. The structure of the clay minerals was also analyzed using an X-ray Diffraction machine. The results showed that the pore volume and surface area were increased substantially through acid treatment, which speeded up the rate of carbon dioxide adsorption. XRD pattern of kaolinite did not change after sulfuric acid treatment, which indicates that acid treatment would not affect the structure of kaolinite. It was also discovered that kaolinite had a higher pore volume and porosity than montmorillonite before and after acid treatment. For example, the pore volume of untreated kaolinite was equal to 30.498 um3 with a porosity of 23.49%. Raising the concentration of acid from 0.5 M to 2.5 M in 8 hours’ time reaction led to increased pore volume from 30.498 um3 to 34.73 um3. The pore volume of raw montmorillonite was equal to 15.610 um3 with a porosity of 12.7%. When the acid concentration was raised from 0.5 M to 2.5 M for the same reaction time, pore volume also increased from 15.610 um3 to 20.538 um3. However, montmorillonite had a higher specific surface area than kaolinite. This study concludes that clay minerals are inexpensive and available material sources to model the realistic conditions and apply the results of carbon capture to prevent global warming, which is one of the most critical and urgent problems in the world.

Keywords: acid treatment, kaolinite, montmorillonite, pore volume, porosity, surface area

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Authors: U. M. Swamy

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A compact Hausdorff and totally disconnected topological space are known as Boolean space in view of the stone duality between Boolean algebras and such topological spaces. A sheaf over X is a triple (S, p, X) where S and X are topological spaces and p is a local homeomorphism of S onto X (that is, for each element s in S, there exist open sets U and G containing s and p(s) in S and X respectively such that the restriction of p to U is a homeomorphism of U onto G). Here we mainly concern on sheaves over Boolean spaces. From a given sheaf over a Boolean space, we obtain an algebraic structure in such a way that there is a one-to-one correspondence between these algebraic structures and sheaves over Boolean spaces.

Keywords: Boolean algebra, Boolean space, sheaf, stone duality

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Authors: Eve S. A. Loiseau, Marion Frey, Yves Blickenstorfer, Fabian Niedermair, André R. Studart

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Porous microcapsules have a broad range of applications that require a robust shell. We propose a new method to produce macroporous polymer capsules with controlled size, shell thickness, porosity and mechanical properties using co-flow flow-focusing glass capillary devices. The porous structure was investigated through SEM and the permeability through confocal microscopy. Compression tests on single capsules were performed. We obtained microcapsules with tailored permeability from open to close pores structures and able to withstand loads up to 150 g.

Keywords: microcapsules, micromechanics, porosity, polymer shells

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Authors: Marine Segui, Simon Bezin, Ruxandra Mihaela Botez

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As part of a ‘Morphing-Wing’ idea, this study consists of measuring how a winglet, which is able to change its shape during the flight, is efficient. Conventionally, winglets are fixed-vertical platforms at the wingtips, optimized for a cruise condition that the airplane should use most of the time. However, during a cruise, an airplane flies through a lot of cruise conditions corresponding to altitudes variations from 30,000 to 45,000 ft. The fixed winglets are not optimized for these variations, and consequently, they are supposed to generate some drag, and thus to deteriorate aircraft fuel consumption. This research assumes that it exists a winglet position that reduces the fuel consumption for each cruise condition. In this way, the methodology aims to find these optimal winglet positions, and to further simulate, and thus estimate the fuel consumption of an aircraft wearing this type of adaptive winglet during several cruise conditions. The adaptive winglet is assumed to have degrees of freedom given by the various changes of following surfaces: the tip chord, the sweep and the dihedral angles. Finally, results obtained during cruise simulations are presented in this paper. These results show that an adaptive winglet can reduce, thus improve up to 2.12% the fuel consumption of an aircraft during a cruise.

Keywords: aerodynamic, Cessna, Citation X, optimization, winglet

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Authors: Mitchell J. Baum, Badin Gibbes, Greg Collecutt

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This study details a three-dimensional field-scale numerical investigation conducted for the Gold Coast Desalination Plant (GCDP) offshore multiport brine diffuser. Quantitative assessment of diffuser performance with regard to trajectory, dilution and mapping of seafloor concentration distributions was conducted for 100% plant operation. The quasi-steady Computational Fluid Dynamics (CFD) simulations were performed using the Reynolds averaged Navier-Stokes equations with a k-ω shear stress transport turbulence closure scheme. The study compliments a field investigation, which measured brine plume characteristics under similar conditions. CFD models used an iterative mesh in a domain with dimensions 400 m long, 200 m wide and an average depth of 24.2 m. Acoustic Doppler current profiler measurements conducted in the companion field study exhibited considerable variability over the water column. The effect of this vertical variability on simulated discharge outcomes was examined. Seafloor slope was also accommodated into the model. Ambient currents varied predominantly in the longshore direction – perpendicular to the diffuser structure. Under these conditions, the alternating port orientation of the GCDP diffuser resulted in simultaneous subjection to co-propagating and counter-propagating ambient regimes. Results from quiescent ambient simulations suggest broad agreement with empirical scaling arguments traditionally employed in design and regulatory assessments. Simulated dynamic ambient regimes showed the influence of ambient crossflow upon jet trajectory, dilution and seafloor concentration is significant. The effect of ambient flow structure and the subsequent influence on jet dynamics is discussed, along with the implications for using these different simulation approaches to inform regulatory decisions.

Keywords: computational fluid dynamics, desalination, field-scale simulation, multiport brine diffuser, negatively buoyant jet

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Authors: Andre Peres Ramos, Franklin Cesar Flores

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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

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Authors: Mohamed Thani Ibouroi, Ali Cheha, Claudine Montgelard, Veronique Arnal, Dawiyat Massoudi, Guillelme Astruc, Said Ali Ousseni Dhurham, Aurelien Besnard

Abstract:

The Livingstone's flying fox (Pteropus livingstonii) and the Comorian fruit bat (P.seychellensis comorensis) are two endemic fruit bat species among the mostly threatened animals of the Comoros archipelagos. Despite their role as important ecosystem service providers like all flying fox species as pollinators and seed dispersers, little is known about their ecologies, population genetics and structures making difficult the development of evidence-based conservation strategies. In this study, we assess spatial distribution and ecological niche of both species using Species Distribution Modeling (SDM) based on the recent Ensemble of Small Models (ESMs) approach using presence-only data. Population structure and genetic diversity of the two species were assessed using both mitochondrial and microsatellite markers based on non-invasive genetic samples. Our ESMs highlight a clear niche partitioning of the two sympatric species. Livingstone’s flying fox has a very limited distribution, restricted on steep slope of natural forests at high elevation. On the contrary, the Comorian fruit bat has a relatively large geographic range spread over low elevations in farmlands and villages. Our genetic analysis shows a low genetic diversity for both fruit bats species. They also show that the Livingstone’s flying fox population of the two islands were genetically isolated while no evidence of genetic differentiation was detected for the Comorian fruit bats between islands. Our results support the idea that natural habitat loss, especially the natural forest loss and fragmentation are the important factors impacting the distribution of the Livingstone’s flying fox by limiting its foraging area and reducing its potential roosting sites. On the contrary, the Comorian fruit bats seem to be favored by human activities probably because its diets are less specialized. By this study, we concluded that the Livingstone’s flying fox species and its habitat are of high priority in term of conservation at the Comoros archipelagos scale.

Keywords: Comoros islands, ecological niche, habitat loss, population genetics, fruit bats, conservation biology

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 62

Authors: Guang Yang, Zhiwei Bai, Bo Sun

Abstract:

This paper analyzes the influence of failure mode and harmfulness of rotative machine according to FMECA (Failure Mode, Effects, and Criticality Analysis) method, and finds out the weak links that affect the reliability of this equipment. Also in this paper, fault tree analysis software is used for quantitative and qualitative analysis, pointing out the main factors of failure of this equipment. Based on the experimental results, this paper puts forward corresponding measures for prevention and improvement, and fundamentally improves the inherent reliability of this rotative machine, providing the basis for the formulation of technical conditions for the safe operation of industrial applications.

Keywords: rotative machine, reliability test, fault tree analysis, FMECA

Procedia PDF Downloads 142

Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

Abstract:

A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

Procedia PDF Downloads 357

Authors: M. Vadivel, R. Ramesh Babu

Abstract:

Spinel ferrite magnetic nanomaterials have received a great deal of attention in recent years due to their wide range of potential applications in various fields such as magnetic data storage and microwave device applications. Among the family of spinel ferrites, cobalt ferrite (CoFe2O4) has been widely used in the field of high-frequency applications because of its remarkable material qualities such as moderate saturation magnetization, high coercivity, large permeability at higher frequency and high electrical resistivity. For aforementioned applications, the materials should have an improved electrical property, especially enhancement in the dielectric properties. It is well known that the substitution of rare earth metal cations in Fe3+ site of CoFe2O4 nanoparticles leads to structural distortion and thus significantly influences the structural and morphological properties whereas greatly modifies the electrical and magnetic properties of a material. In the present investigation, we report on the influence of lanthanum (La3+) ion substitution on the structural, morphological, dielectric and magnetic properties of CoFe2O4 magnetic nanoparticles prepared by co-precipitation method. Powder X-ray diffraction patterns reveal the formation of inverse cubic spinel structure with the signature of LaFeO3 phase at higher La3+ ion concentrations. Raman and Fourier transform infrared spectral analysis also confirms the formation of inverse cubic spinel structure and Fe-O symmetrical stretching vibrations of CoFe2O4 nanoparticles, respectively. Transmission electron microscopy study reveals that the size of the particles gradually increases with increasing La3+ ion concentrations whereas the agglomeration gets slightly reduced for La3+ ion substituted CoFe2O4 nanoparticles than that of undoped CoFe2O4 nanoparticles. Dielectric properties such as dielectric constant and dielectric loss were recorded as a function of frequency and temperature which reveals that the dielectric constant gradually increases with increasing temperatures as well as La3+ ion concentrations. The increased dielectric constant might be the reason that the formation of LaFeO3 secondary phase at higher La3+ ion concentrations. Magnetic measurement demonstrates that the saturation magnetization gradually decreases from 61.45 to 25.13 emu/g with increasing La3+ ion concentrations which is due to the nonmagnetic nature of La3+ ions substitution.

Keywords: cobalt ferrite, co-precipitation, dielectric properties, saturation magnetization

Procedia PDF Downloads 303