Search results for: optimization methods

Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

Procedia PDF Downloads 334

Authors: Mehmet Alpaslan Köroğlu, Musa Hakan Arslan, Muslu Kazım Körez

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Basic objective of this study is to create a regression analysis method that can estimate the length of a plastic hinge which is an important design parameter, by making use of the outcomes of (lateral load-lateral displacement hysteretic curves) the experimental studies conducted for the reinforced square concrete columns. For this aim, 170 different square reinforced concrete column tests results have been collected from the existing literature. The parameters which are thought affecting the plastic hinge length such as cross-section properties, features of material used, axial loading level, confinement of the column, longitudinal reinforcement bars in the columns etc. have been obtained from these 170 different square reinforced concrete column tests. In the study, when determining the length of plastic hinge, using the experimental test results, a regression analysis have been separately tested and compared with each other. In addition, the outcome of mentioned methods on determination of plastic hinge length of the reinforced concrete columns has been compared to other methods available in the literature.

Keywords: columns, plastic hinge length, regression analysis, reinforced concrete

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Authors: Muhammad Rizwan Tabassum, Ao Xia, Jerry D. Murphy

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The aim of this work is to provide an overview of macroalgae as an alternative feedstock for gaseous fuel production and key innovative technologies. Climate change and continuously depleting resources are the key driving forces to think for alternative sources of energy. Macroalgae can be favored over land based energy crops because they are not in direct competition with food crops. However, some drawbacks, such as high moisture content, seasonal variation in chemical composition and process inhibition limit the economic practicability. Macroalgae, like brown seaweed can be converted into gaseous and liquid fuel by different conversion technologies. Biomethane via anaerobic digestion is the appealing technology due to its dual advantage of a commercially applicable and environment friendly technology. Other technologies like biodiesel and bioethanol conversion technologies from seaweed are still under progress. Screening of high yielding macroalgae species, peak harvesting season and process optimization make the technology economically feasible for alternative source of feedstock for biofuel production in future.

Keywords: anaerobic digestion, biofuels, bio-methane, advanced conversion technologies, macroalgae

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Authors: Kartik Gupta, Umar Khan, Mayur Parab, Dhiraj Chaudhari, Afzal Ansari

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The report focuses on the study related to the Design and Simulation of a stabilator (an all-movable horizontal stabilizer) for a fixed-wing aircraft. The project involves the development of a computerized direct optimization procedure for designing an aircraft all-movable stabilator. This procedure evaluates various design variables to synthesize an optimal stabilator that meets specific requirements, including performance, control, stability, strength, and flutter velocity constraints. The work signifies the CFD (Computational Fluid Dynamics) analysis of the airfoils used in the stabilator along with the CFD analysis of the Stabilizer and Stabilator of an aircraft named Thorp- T18 in software like XFLR5 and ANSYS-Fluent. A comparative analysis between a Stabilizer and Stabilator of equal surface area and under the same environmental conditions was done, and the percentage of drag reduced by the Stabilator for the same amount of lift generated as the Stabilizer was also calculated lastly, Wind tunnel testing was performed on a scale down model of the Stabilizer and Stabilator and the results of the Wind tunnel testing were compared with the results of CFD.

Keywords: wind tunnel testing, CFD, stabilizer, stabilator

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Authors: F. V. Matta, C. M. Donnelly, M. B. Jaafar, N. I. Ward

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‘Yerba Mate’ (Ilex paraguariensis) is a native plant from South America with the main producers being Argentina and Brazil. ‘Mate’ is widely consumed in Argentina, Brazil, Uruguay and Paraguay. The most popular format is as an infusion made from dried leaves of a traditional cup, roasted material in tea bags or iced tea infusions. There are many alleged health benefits resulted from mate consumption, even though there is a lack of conclusive research published in the international literature. The main objective of this study was to develop and evaluate the sample preparation and instrumental analysis stages involved in the determination of trace elements in yerba mate using inductively coupled plasma mass spectrometry (ICP-MS). Specific details on the methods of sample digestion, validation of the ICP-MS analysis especially for polyatomic ion correction and matrix effects associated with the complex medium of mate will be presented. More importantly, mate produced in Brazil and Argentina, is subject to different soil conditions, methods of cultivation and production, especially for loose leaves and tea bags. The highest concentrations for loose mate leaf were for (mg/kg, dry weight): aluminium (253.6 – 506.9 for Brazil (Bra), 230.0 – 541.8 for Argentina (Arg), respectively), manganese (378.3 – 762.6 Bra; 440.8 – 879.9 Arg), iron (32.5 – 85.7 Bra; 28.2 – 132.9 Arg), zinc (28.2 – 91.1 Bra; 39.1 – 92.3 Arg), nickel (2.2 – 4.3 Bra; 2.9 – 10.8 Arg) and copper (4.8 – 9.1 Bra; 4.3 – 9.2 Arg), with lower levels of chromium, cobalt, selenium, molybdenum, cadmium, lead and arsenic. Elemental levels of mate leaf consumed in tea bags were found to be higher, mainly due to only using leaf material (as opposed to leaf and twig for loose packed product). Further implications of the way of consuming yerba mate will be presented, including different infusion methods in Brazil and Argentina. This research provides for the first time an extensive evaluation of mate products from both countries and the possible implications of specific trace elements, especially Mn, Fe, Se, Cu and Zn and the various health claims of consuming yerba mate.

Keywords: beverage analysis, ICP-MS, trace elements, yerba mate

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Authors: Zahia Kabouche, Ouissem Gherboudj, Naima Boutaghane, Ahmed Kabouche, Laurence Voutquenne-Nazabadioko

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Chrysanthemum herbs (Asteraceae) are extensively used as food additives and in folk medicine. Anti-cancer, anti-human immunodeficiency virus type 1 (HIV-1), anti-inflammatory, antinociceptive and antiproliferative activities as well as antioxidant effects have been reported for Chrysanthemum species. We report the isolation and identification of flavonoids and new and known terpenoids from the endemic species, C. macrocarpum and C. deserticolum “guertoufa”, used in Algerian Sahara as tea drinks and in “couscous” and soups “Chorba”. Structures of the isolated compounds were established by 1-D and 2-D homo and hetero-nuclear NMR (1H, 13C, COSY, HSQC, HMBC, and NOESY), mass spectrometry, UV and comparison with literature data. C. deserticolum extracts were tested by four methods to identify the antioxidant activity namely, ABTS•+, DPPH• scavenging, CUPRAC and ferrous-ions chelating activity methods. Anti-inflammatory, antinociceptive, antiproliferative and antioxidant activities of C. macrocarpum extracts and isolated compounds are also reported here.

Keywords: Chrysanthemum macrocarpum, C. deserticolum, flavonoids, terpenoids, antioxidant, anti-inflammatory, anti-proliferative

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: Obsi Terfasa, Bhanupriya Das, Shiao-Shing Chen

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Converting coal fly ash (CFA) waste into ceramic membranes presents a promising alternative to traditional disposal methods, offering potential economic and environmental advantages that warrant further investigation. This research focuses on the creation of ceramic membranes exclusively from CFA using a uniaxial compaction technique. The membranes' properties were examined through various analytical methods: Scanning Electron Microscopy (SEM) revealed a porous and flawless membrane surface, X-Ray Diffraction (XRD) identified mullite and quartz crystalline structures, and Fourier-Transform Infrared Spectroscopy (FTIR) characterized the membrane's functional groups. Thermogravimetric analysis (TGA) determined the ideal sintering temperature to be 800°C. To evaluate its separation capabilities, the synthesized membrane was tested on wastewater from denim jeans production at 0.2 bar pressure. The results were impressive, with 97.42% removal of Chemical Oxygen Demand (COD), 95% color elimination, and a pure water flux of 4.5 Lm⁻²h⁻¹bar⁻¹. These findings suggest that CFA, a byproduct of thermal power plants, can be effectively repurposed to produce ultrafiltration membranes suitable for various industrial purification and separations.

Keywords: wastewater treatment, separator, coal fly ash, ceramic membrane, ultrafiltration

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Authors: Brandtner-Hafner Martin

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Adhesives are increasingly being used in the construction sector. On the one hand, this concerns dowel reinforcements using chemical anchors. On the other hand, the sealing and repair of cracks in structural concrete components are still on the rise. In the field of bonding, the interface between the joined materials is the most critical area. Therefore, it is of immense importance to characterize and investigate this section sufficiently by fracture analysis. Since standardized mechanical test methods are not sufficiently capable of doing this, recourse is made to an innovative concept based on fracture energy. Therefore, a series of experimental tests were performed using the so-called GF-principle to study the interface bonding safety of adhesively bonded concrete joints. Several different structural adhesive systems based on epoxy, CA/A hybrid, PUR, MS polymer, dispersion, and acrylate were selected for bonding concrete substrates. The results show that stable crack propagation and prevention of uncontrolled failure in bonded concrete joints depend very much on the adhesive system used, and only fracture analytical evaluation methods can provide empirical information on this.

Keywords: interface bonding safety, adhesively bonded concrete joints, GF-principle, fracture analysis

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Authors: Amine Ganibardi, Cherif Arab Ali

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This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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Authors: Dipak Sonawane, Sudarshan Daga, Somesh Gupta

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Quantitative risk assessment (QRA) is a very precise and consistent approach to defining the likelihood, consequence and severity of a major incident/accident. A variety of hazardous cargoes in bulk, such as hydrocarbons and flammable/toxic chemicals, are handled at various ports. It is well known that most of the operations are hazardous, having the potential of damaging property, causing injury/loss of life and, in some cases, the threat of environmental damage. In order to ensure adequate safety towards life, environment and property, the application of scientific methods such as QRA is inevitable. By means of these methods, comprehensive hazard identification, risk assessment and appropriate implementation of Risk Control measures can be carried out. In this paper, the authors, based on their extensive experience in Risk Analysis for ports and harbors, have exhibited how QRA can be used in practice to minimize and contain risk to tolerable levels. A specific case involving the operation for unloading of hydrocarbon at a port is presented. The exercise provides confidence that the method of QRA, as proposed by the authors, can be used appropriately for the identification of hazards and risk assessment of Ports and Terminals.

Keywords: quantitative risk assessment, hazard assessment, consequence analysis, individual risk, societal risk

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Authors: Nigel Q. Kelly, Zaid Siddiqi, Jin W. Lee

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It is known that using Coanda aerosurfaces can drastically augment the lift forces when applied to an Unmanned Aerial Vehicle (UAV) platform. However, Coanda saucer UAVs, which commonly use a dish-like, radially-extending structure, have shown no significant increases in thrust/lift force and therefore have never been commercially successful: the additional thrust/lift generated by the Coanda surface diminishes since the airstreams emerging from the rotor compartment expand radially causing serious loss of momentums and therefore a net loss of total thrust/lift. To overcome this technical weakness, we propose to examine a Coanda surface of straight, cylindrical design and optimize its geometry for highest thrust/lift utilizing computational fluid dynamics software ANSYS Fluent®. The results of this study reveal that a Coanda UAV configured with 4 sides of straight, cylindrical Coanda surface achieve an overall 45% increase in lift compared to conventional Coanda Saucer UAV configurations. This venture integrates with an ongoing research project where a Coanda prototype is being assembled. Additionally, a custom thrust-stand has been constructed for thrust/lift measurement.

Keywords: CFD, Coanda, lift, UAV

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Authors: Talar Agopian

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Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: active learning, constructivism, learner engagement, student-centered strategies

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

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This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

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Authors: Michael Okeke, Andrew Blyth

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Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection.

Keywords: industrial control system (ics, no-trust-zone (ntz), particle swarm optimisation (pso), supervisory control and data acquisition (scada), swarm intelligence (SI)

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Authors: Hasan Türe, Kader Terzioglu, Evren Tunca

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Contamination of aqueous environment by heavy metal ions is a serious and complex problem, owing to their hazards to human being and ecological systems. The treatment methods utilized for removing metal ions from aqueous solution include membrane separation, ion exchange and chemical precipitation. However, these methods are limited by high operational cost. Recently, biobased beads are considered as promising biosorbent to remove heavy metal ions from water. The aim of present study was to characterize the alginate/perlite composite beads and to investigate the adsorption performance of obtained beads for removing Pb (II) from aqueous solution. Alginate beads were synthesized by ionic gelation methods and different amount of perlite (aljinate:perlite=1, 2, 3, 4, 5 wt./wt.) was incorporated into alginate beads. Samples were characterized by means of X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM). The effects of perlite level, the initial concentration of Pb (II), initial pH value of Pb(II) solution and effect of contact time on the adsorption capacity of beads were investigated by using batch method. XRD analysis indicated that perlite includes silicon or silicon and aluminum bearing crystalline phase. The diffraction pattern of perlite containing beads is similar to that of that perlite powder with reduced intensity. SEM analysis revealed that perlite was embedded into alginate polymer and SEM-EDX (Energy-Dispersive X-ray) showed that composite beads (aljinate:perlite=1) composed of C (41.93 wt.%,), O (43.64 wt.%), Na (10.20 wt.%), Al (0.74 wt.%), Si (2.72 wt.%) ve K (0.77 wt.%). According to TGA analysis, incorporation of perlite into beads significantly improved the thermal stability of the samples. Batch experiment indicated that optimum pH value for Pb (II) adsorption was found at pH=7 with 1 hour contact time. It was also found that the adsorption capacity of beads decreased with increases in perlite concentration. The results implied that alginate/perlite composite beads could be used as promising adsorbents for the removal of Pb (II) from wastewater. Acknowledgement: This study was supported by TUBITAK (Project No: 214Z146).

Keywords: alginate, adsorption, beads, perlite

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Authors: Xiaoci Li, Yonghua Huang, Hui Lin

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Optimization of the concentration of components in mixed refrigerants leads to potential improvement of either thermodynamic cycle performance or safety performance of heat pumps and refrigerators. R32+R1234yf and R125+R290 are two promising binary mixed refrigerants for the application of heat pumps working in the cold areas. The p-ρ-T data of these mixtures are one of the fundamental and necessary properties for design and evaluation of the performance of the heat pumps. Although the property data of mixtures can be predicted by the mixing models based on the pure substances incorporated in programs such as the NIST database Refprop, direct property measurement will still be helpful to reveal the true state behaviors and verify the models. Densities of the mixtures of R32+R1234yf an d R125+R290 are measured by an Anton Paar U shape oscillating tube digital densimeter DMA-4500 in the range of temperatures from 0°C to 100 °C and pressures up to 10 MPa. The accuracy of the measurement reaches 0.00005 g/cm³. The experimental data are compared with the predictions by Refprop in the corresponding range of pressure and temperature.

Keywords: mixed refrigerant, density measurement, densimeter, thermodynamic property

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak

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In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.

Keywords: unmanned aerial vehicles, morphing, autopilots, autonomous performance

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Authors: Milad Nooshadi, Alessandro Manzardo

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CO₂ emissions in the atmosphere continue to rise, mostly as a result of the combustion of fossil fuels. CO₂ injection into the oceans and geological formation as a process of physical carbon capture are two of the most promising emerging strategies for mitigating climate change and global warming. The purpose of this research is to evaluate the two mentioned methods of CO₂ sequestration and to assess information on previous and current advancements, limitations, and uncertainties associated with carbon sequestration in order to identify possible prospects for ensuring the timely implementation of the technology, such as determining how governments and companies can gain a better understanding of CO₂ storage in terms of which media have the most applicable capacity, which type of injection has the fewer environmental impact, and how much carbon sequestration and storage will cost. The behavior of several forms is characterized as a near field, a far field, and a see-floor in ocean storage, and three medias in geological formations as an oil and gas reservoir, a saline aquifer, and a coal bed. To determine the capacity of various forms of media, an analysis of some models and practical experiments are necessary. Additionally, as a major component of sequestration, the various injection methods into diverse media and their monitoring are associated with a variety of environmental impacts and financial consequences.

Keywords: carbon sequestration, ocean storage, geologic storage, carbon transportation

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Authors: Samuel Ahamefula

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Turbulent motion is a highly nonlinear and complex phenomenon, and its modelling is still very challenging. In this study, we developed a hybrid computational approach to accurately simulate fluid turbulence phenomenon. The focus is coupling and transitioning between Direct Numerical Simulation (DNS) and Large Eddy Simulating Wall Models (LES-WM) regions. In the framework, high-order fidelity fluid dynamical methods are utilized to simulate the unsteady compressible Navier-Stokes equations in the Eulerian format on the unstructured moving grids. The coupling and transitioning of DNS and LES-WM are conducted through the linearly staggered Dirichlet-Neumann coupling scheme. The high-fidelity framework is verified and validated based on namely, DNS ability for capture full range of turbulent scales, giving accurate results and LES-WM efficiency in simulating near-wall turbulent boundary layer by using wall models.

Keywords: computational methods, turbulence modelling, turbulence entropy, navier-stokes equations

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Authors: Abdulaziz Fageeh

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This study investigates the integration of artificial intelligence (AI) within the landscape of language learning and teaching, exploring its potential benefits and challenges. Employing a mixed-methods approach, the research draws upon a comprehensive literature review, case studies, user reviews, and in-depth interviews with educators and students. Findings demonstrate that AI tools, including language learning apps and writing assistants, can enhance personalization, improve writing skills, and increase accessibility to language learning resources. However, the study also highlights concerns regarding over-reliance on AI, potential accuracy and reliability issues, and ethical implications such as data privacy and potential bias. User and educator perspectives emphasize the importance of balancing AI with traditional teaching methods, fostering critical thinking skills, and addressing potential misuse. The study concludes by underscoring the need for ongoing research and development to ensure responsible AI integration in language learning, focusing on pedagogical strategies, ethical frameworks, and the long-term impact of AI on learning outcomes.

Keywords: artificial intelligence, language learning, education, technology, ethical considerations, user perceptions

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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

Abstract:

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

Procedia PDF Downloads 238

Authors: Yusuf Ziya Ayık, Ferhat Kahveci

Abstract:

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

Procedia PDF Downloads 280

Authors: Sandeep Vasaikar, Lary Obi

Abstract:

Rapid and discriminative genotyping methods are useful for determining the clonality of the isolates in nosocomial or household outbreaks. Multilocus sequence typing (MLST) is a nucleotide sequence-based approach for characterising bacterial isolates. The genetic diversity and the clinical relevance of the drug-resistant Klebsiella isolates from Mthatha are largely unknown. For this reason, prospective, experimental study of the molecular epidemiology of Klebsiella isolates from patients being treated in Mthatha over a three-year period was analysed. Methodology: PCR amplification and sequencing of the drug-resistance-associated genes, and multilocus sequence typing (MLST) using 7 housekeeping genes mdh, pgi, infB, FusAR, phoE, gapA and rpoB were conducted. A total of 32 isolates were analysed. Results: The percentages of multidrug-resistant (MDR), extensively drug-resistance (XDR) and pandrug-resistant (PDR) isolates were; MDR 65.6 % (21) and XDR and PDR with 0 % each. In this study, K. pneumoniae was 19/32 (59.4 %). MLST results showed 22 sequence types (STs) were identified, which were further separated by Maximum Parsimony into 10 clonal complexes and 12 singletons. The most dominant group was Klebsiella pneumoniae with 23/32 (71.8 %) isolates, Klebsiella oxytoca as a second group with 2/32 (6.25 %) isolates, and a single (3.1 %) K. varricola as a third group while 6 isolates were of unknown sequences. Conclusions/significance: A phylogenetic analysis of the concatenated sequences of the 7 housekeeping genes showed that strains of K. pneumoniae form a distinct lineage within the genus Klebsiella, with K. oxytoca and K. varricola its nearest phylogenetic neighbours. With the analysis of 7 genes were determined 1 K. variicola, which was mistakenly identified as K. pneumoniae by phenotypic methods. Two misidentifications of K. oxytoca were found when phenotypic methods were used. No significant differences were observed between ESBL blaCTX-M, blaTEM and blaSHV groups in the distribution of Sequence types (STs) or Clonal complexes (CCs).

Keywords: phylogenetic analysis, phylogeny, klebsiella phylogenetic, klebsiella

Procedia PDF Downloads 373

Authors: Hongyu Chen, Li Jiang

Abstract:

Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

Procedia PDF Downloads 129

Authors: Yasith Mindula Saipath Wickramasinghe

Abstract:

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

Procedia PDF Downloads 118

Authors: Kaycee Bills

Abstract:

This study will determine if students with disabilities have higher student loan debt payments than other student populations. The hypothesis was that students with disabilities would have significantly higher student loan debt payments than other students due to the length of time they spend in school. Using the Bachelorette and Beyond Study Wave 2015/017 dataset, quantitative methods were employed. These data analysis methods included linear regression and a correlation matrix. Due to the exploratory nature of the study, the significance levels for the overall model and each variable were set at .05. The correlation matrix demonstrated that students with certain types of disabilities are more likely to fall under higher student loan payment brackets than students without disabilities. These results also varied among the different types of disabilities. The result of the overall linear regression model was statistically significant (p = .04). Despite the overall model being statistically significant, the majority of the significance values for the different types of disabilities were null. However, several other variables had statistically significant results, such as veterans, people of minority races, and people who attended private schools. Implications for how this impacts the economy, capitalism, and financial wellbeing of various students are discussed.

Keywords: disability, student loan debt, higher education, social work

Procedia PDF Downloads 168