Search results for: Wiebe Combustion Model (WCM)
4456 Fragility Assessment for Vertically Irregular Buildings with Soft Storey
Authors: N. Akhavan, Sh. Tavousi Tafreshi, A. Ghasemi
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Seismic behavior of irregular structures through the past decades indicate that the stated buildings do not have appropriate performance. Among these subjects, the current paper has investigated the behavior of special steel moment frame with different configuration of soft storey vertically. The analyzing procedure has been evaluated with respect to incremental dynamic analysis (IDA), and numeric process was carried out by OpenSees finite element analysis package. To this end, nine 2D steel frames, with different numbers of stories and irregularity positions, which were subjected to seven pairs of ground motion records orthogonally with respect to Ibarra-Krawinkler deterioration model, have been investigated. This paper aims at evaluating the response of two-dimensional buildings incorporating soft storey which subjected to bi-directional seismic excitation. The IDAs were implemented for different stages of PGA with various ground motion records, in order to determine maximum inter-storey drift ratio. According to statistical elements and fracture range (standard deviation), the vulnerability or exceedance from above-mentioned cases has been examined. For this reason, fragility curves for different placement of soft storey in the first, middle and the last floor for 4, 8, and 16 storey buildings have been generated and compared properly.Keywords: special steel moment frame, soft storey, incremental dynamic analysis, fragility curve
Procedia PDF Downloads 3424455 Study of Launch Recovery Control Dynamics of Retro Propulsive Reusable Rockets
Authors: Pratyush Agnihotri
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The space missions are very costly because the transportation to the space is highly expensive and therefore there is the need to achieve complete re-usability in our launch vehicles to make the missions highly economic by cost cutting of the material recovered. Launcher reusability is the most efficient approach to decreasing admittance to space access economy, however stays an incredible specialized hurdle for the aerospace industry. Major concern of the difficulties lies in guidance and control procedure and calculations, specifically for those of the controlled landing stage, which should empower an exact landing with low fuel edges. Although cutting edge ways for navigation and control are present viz hybrid navigation and robust control. But for powered descent and landing of first stage of launch vehicle the guidance control is need to enable on board optimization. At first the CAD model of the launch vehicle I.e. space x falcon 9 rocket is presented for better understanding of the architecture that needs to be identified for the guidance and control solution for the recovery of the launcher. The focus is on providing the landing phase guidance scheme for recovery and re usability of first stage using retro propulsion. After reviewing various GNC solutions, to achieve accuracy in pre requisite landing online convex and successive optimization are explored as the guidance schemes.Keywords: guidance, navigation, control, retro propulsion, reusable rockets
Procedia PDF Downloads 834454 Financing from Customers for SMEs and Managing Financial Risks: The Role of Customer Relationships
Authors: Yongsheng Guo, Mengyu Lu
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This study investigates how Chinese SMEs manage financial risks in financing from customers from the perspectives of ethics and national culture. A grounded theory approach is adopted to identify the causal conditions, actions/interactions, and consequences. 32 interviews were conducted, and systematic coding methods were used to identify themes and categories. This study found that Chinese ethical principles, including integrity, friendship, and reciprocity, and cultural traits, including collectivism, acquaintance society, and long-term orientation, provide conditions for financing from customers. The SMEs establish trust-based relationships with customers through personal communications and social networks and reduce financial risk through diversification, frequent operations, and enterprise reputations. Both customers and SMEs can get benefits like financial resources and customer experiences. This study creates a theoretical framework that connects the causal conditions, processes, and outcomes, providing a deeper understanding of financing from customers. A resource and process capability theory of SMEs and a customer capital and customer value model are proposed to connect accounting and finance concepts. Suggestions are proposed for the authorities as more guidance and regulations are needed for this informal finance.Keywords: CRM, culture, ethics, SME, risk management
Procedia PDF Downloads 384453 Enhanced Peroxidase Production by Raoultella Species
Authors: Ayodeji O. Falade, Leonard V. Mabinya, Uchechukwu U. Nwodo, Anthony I. Okoh
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Given the high-utility of peroxidase, its production in large amount is of utmost importance. Over the years, actinomycetes have been the major peroxidase-producing bacteria. Consequently, other classes of bacteria with peroxidase production potentials are underexplored. This study, therefore, sought to enhance peroxidase production by a Raoultella species, a new ligninolytic proteobacteria strain, by determining the optimum culture conditions (initial pH, incubation temperature and agitation speed) for peroxidase production under submerged fermentation using the classical process of one variable at a time and supplementing the fermentation medium with some lignin model and inorganic nitrogen compounds. Subsequently, the time-course assay was carried out under optimized conditions. Then, some agricultural residues were valorized for peroxidase production under solid state fermentation. Peroxidase production was optimal at initial pH 5, incubation temperature of 35 °C and agitation speed of 150 rpm with guaiacol and ammonium chloride as the best inducer and nitrogen supplement respectively. Peroxidase production by the Raoultella species was optimal at 72 h with specific productivity of 16.48 ± 0.89 U mg⁻¹. A simultaneous production of a non-peroxide dependent extracellular enzyme which suggests probable laccase production was observed with specific productivity of 13.63 ± 0.45 U mg⁻¹ while sawdust gave the best peroxidase yield under solid state fermentation. In conclusion, peroxidase production by the Raoultella species was increased by 3.40-fold.Keywords: enzyme production, ligninolytic bacteria, peroxidase, proteobacteria
Procedia PDF Downloads 2654452 Modeling User Departure Time Choice for Work Trips in High Traffic Suburban Roads
Authors: Saeed Sayyad Hagh Shomar
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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning
Procedia PDF Downloads 2944451 Effects of Handheld Video Games on Interpersonal Relationships: A Two-Wave Panel Study on Elementary School Students
Authors: Kanae Suzuki
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Handheld video games are popular communication tools among Japanese elementary school students today. This study aims to examine the effects of the use of handheld video games on interpersonal relationships of the students in real and virtual worlds. A two-wave panel survey was conducted for students of ten elementary schools at an interval of approximately six months. The survey questionnaire included questions about the average amount of time spent playing a handheld video game during the past one month, the frequency of communication with players during game play, and the interpersonal relationships, such as the number of real and virtual friends the students have. A multiple regression model was constructed for 324 students to examine causal relationships. The results indicated that the more frequently the students communicated with other players while playing games, the number of the real friends tended to increase. In contrast, no significant effect of the total time spent playing games was found on interpersonal relationships. The findings suggested that communication during game play is an important factor for improving interpersonal relationships of this age group.Keywords: communication, real friend, social adjustment, virtual friend
Procedia PDF Downloads 4874450 Shear Behavior of Ultra High Strength Concrete Beams
Authors: Ghada Diaa, Enas A. Khattab
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Ultra High Strength Concrete (UHSC) is a new advanced concrete that is being transferred from laboratory researches to practicable applications. In addition to its excellent durability properties, UHSC has high compressive and tensile strengths, and high modulus of elasticity. Despite of this low degree of hydration, ultra high strength values can be achieved by controlling the mixture proportions. In this research, an experimental program was carried out to investigate the shear behavior of ultra high strength concrete beams. A total of nine beams were tested to determine the effect of different parameters on the shear behavior of UHSC beams. The parameters include concrete strength, steel fiber volume, shear span to depth ratio, and web reinforcement ratio. The results demonstrated that nominal shear stress at cracking load and at ultimate load increased with the increase of concrete strength or the decrease in shear span-depth ratio. Using steel fibers or shear reinforcement increases the ultimate shear strength and makes the shear behavior more ductile. In this study, a simplified analytical model to calculate the shear strength of UHSC beams is introduced. Shear strength estimated according to the proposed method in this research is in good agreement with the experimental results.Keywords: ultra high strength, shear strength, diagonal, cracking, steel fibers
Procedia PDF Downloads 6114449 Quasi-Static Analysis of End Plate Beam-to-Column Connections
Authors: A. Al-Rifaie, Z. W. Guan, S. W. Jones
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This paper presents a method for modelling and analysing end plate beam-to-column connections to obtain the quasi-static behaviour using non-linear dynamic explicit integration. In addition to its importance to study the static behaviour of a structural member, quasi-static behaviour is largely needed to be compared with the dynamic behaviour of such members in order to investigate the dynamic effect by proposing dynamic increase factors (DIFs). The beam-to-column bolted connections contain various contact surfaces at which the implicit procedure may have difficulties converging, resulting in a large number of iterations. Contrary, explicit procedure could deal effectively with complex contacts without converging problems. Hence, finite element modelling using ABAQUS/explicit is used in this study to address the dynamic effect may be produced using explicit procedure. Also, the effect of loading rate and mass scaling are discussed to investigate their effect on the time of analysis. The results show that the explicit procedure is valuable to model the end plate beam-to-column connections in terms of failure mode, load-displacement relationships. Also, it is concluded that loading rate and mass scaling should be carefully selected to avoid the dynamic effect in the solution.Keywords: quasi-static, end plate, finite elements, connections
Procedia PDF Downloads 3044448 B Spline Finite Element Method for Drifted Space Fractional Tempered Diffusion Equation
Authors: Ayan Chakraborty, BV. Rathish Kumar
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Off-late many models in viscoelasticity, signal processing or anomalous diffusion equations are formulated in fractional calculus. Tempered fractional calculus is the generalization of fractional calculus and in the last few years several important partial differential equations occurring in the different field of science have been reconsidered in this term like diffusion wave equations, Schr$\ddot{o}$dinger equation and so on. In the present paper, a time-dependent tempered fractional diffusion equation of order $\gamma \in (0,1)$ with forcing function is considered. Existence, uniqueness, stability, and regularity of the solution has been proved. Crank-Nicolson discretization is used in the time direction. B spline finite element approximation is implemented. Generally, B-splines basis are useful for representing the geometry of a finite element model, interfacing a finite element analysis program. By utilizing this technique a priori space-time estimate in finite element analysis has been derived and we proved that the convergent order is $\mathcal{O}(h²+T²)$ where $h$ is the space step size and $T$ is the time. A couple of numerical examples have been presented to confirm the accuracy of theoretical results. Finally, we conclude that the studied method is useful for solving tempered fractional diffusion equations.Keywords: B-spline finite element, error estimates, Gronwall's lemma, stability, tempered fractional
Procedia PDF Downloads 1834447 Predictive Analytics of Student Performance Determinants
Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi
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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.Keywords: student performance, supervised machine learning, classification, cross-validation, prediction
Procedia PDF Downloads 1184446 Optimisation of a Dragonfly-Inspired Flapping Wing-Actuation System
Authors: Jia-Ming Kok, Javaan Chahl
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An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.Keywords: flapping wing, optimisation, quasi-steady model, dragonfly
Procedia PDF Downloads 3544445 Developing Digital Twins of Steel Hull Processes
Authors: V. Ložar, N. Hadžić, T. Opetuk, R. Keser
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The development of digital twins strongly depends on efficient algorithms and their capability to mirror real-life processes. Nowadays, such efforts are required to establish factories of the future faced with new demands of custom-made production. The ship hull processes face these challenges too. Therefore, it is important to implement design and evaluation approaches based on production system engineering. In this study, the recently developed finite state method is employed to describe the stell hull process as a platform for the implementation of digital twinning technology. The application is justified by comparing the finite state method with the analytical approach. This method is employed to rebuild a model of a real shipyard ship hull process using a combination of serial and splitting lines. The key performance indicators such as the production rate, work in process, probability of starvation, and blockade are calculated and compared to the corresponding results obtained through a simulation approach using the software tool Enterprise dynamics. This study confirms that the finite state method is a suitable tool for digital twinning applications. The conclusion highlights the advantages and disadvantages of methods employed in this context.Keywords: digital twin, finite state method, production system engineering, shipyard
Procedia PDF Downloads 924444 Capacity Loss at Midblock Sections of Urban Arterials Due to Pedestrian Crossings
Authors: Ashish Dhamaniya, Satish Chandra
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Pedestrian crossings at grade in India are very common and pedestrian cross the carriageway at undesignated locations where they found the path to access the residential and commercial areas. Present paper aims to determine capacity loss on 4-lane urban arterials due to such crossings. Base capacity which is defined as the capacity without any influencing factor is determined on 4-lane roads by collecting speed-flow data in the field. It is observed that base capacity is varying from 1636 pcu/hr/lane to 2043 pcu/hr/lane which is attributed to the different operating conditions at different sections. The variation in base capacity is related with the operating speed on the road sections. Free flow speed of standard car is measured in the field and 85th percentile of this speed is reported as operating speed. Capacity of the 4-lane road sections with different pedestrian cross-flow is also determined and compared with the capacity of base section. The difference in capacity values is reported as capacity loss due to the average number of pedestrian crossings in one hour. It has been observed that capacity of 4-lane road section reduces from 18 to 30 percent with pedestrian cross-flow of 800 to 1550 peds/hr. A model is proposed between capacity loss and pedestrian cross-flow from the observed data.Keywords: capacity, free flow speed, pedestrian, urban arterial, transport
Procedia PDF Downloads 4434443 Transportation Mode Classification Using GPS Coordinates and Recurrent Neural Networks
Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem
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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.Keywords: classification, gated recurrent unit, recurrent neural network, transportation
Procedia PDF Downloads 1284442 A Method of Representing Knowledge of Toolkits in a Pervasive Toolroom Maintenance System
Authors: A. Mohamed Mydeen, Pallapa Venkataram
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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.Keywords: knowledge representation, pervasive computing, agent technology, ECA rules
Procedia PDF Downloads 3264441 Family Homicide: A Comparison of Rural and Urban Communities in California
Authors: Bohsiu Wu
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This study compares the differences in social dynamics between rural and urban areas in California to explain homicides involving family members. It is hypothesized that rural homicides are better explained by social isolation and lack of intervention resources, whereas urban homicides are attributed to social disadvantage factors. Several critical social dynamics including social isolation, social disadvantages, acculturation, and intervention resources were entered in a hierarchical linear model (HLM) to examine whether county-level factors affect how each specific dynamic performs at the ZIP code level, a proxy measure for communities. Homicide data are from the Supplementary Homicide Report for all 58 counties in California from 1997 to 1999. Predictors at both the county and ZIP code levels are derived from the 2000 US census. Preliminary results from a HLM analysis show that social isolation is a significant but moderate predictor to explain rural family homicide and various social disadvantage factors are significant factors accounting for urban family homicide. Acculturation has little impact. Rurality and urbanity appear to interact with various social dynamics in explaining family homicide. The implications for prevention at both the county and community level as well as directions for future study on the differences between rural and urban locales are explored in the paper.Keywords: communities, family, HLM, homicide, rural, urban
Procedia PDF Downloads 3214440 Brain Tumor Detection and Classification Using Pre-Trained Deep Learning Models
Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri
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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation
Procedia PDF Downloads 674439 Process Integration of Natural Gas Hydrate Production by CH₄-CO₂/H₂ Replacement Coupling Steam Methane Reforming
Authors: Mengying Wang, Xiaohui Wang, Chun Deng, Bei Liu, Changyu Sun, Guangjin Chen, Mahmoud El-Halwagi
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Significant amounts of natural gas hydrates (NGHs) are considered potential new sustainable energy resources in the future. However, common used methods for methane gas recovery from hydrate sediments require high investment but with low gas production efficiency, and may cause potential environment and security problems. Therefore, there is a need for effective gas production from hydrates. The natural gas hydrate production method by CO₂/H₂ replacement coupling steam methane reforming can improve the replacement effect and reduce the cost of gas separation. This paper develops a simulation model of the gas production process integrated with steam reforming and membrane separation. The process parameters (i.e., reactor temperature, pressure, H₂O/CH₄ ratio) and the composition of CO₂ and H₂ in the feed gas are analyzed. Energy analysis is also conducted. Two design scenarios with different composition of CO₂ and H₂ in the feed gas are proposed and evaluated to assess the energy efficiency of the novel system. Results show that when the composition of CO₂ in the feed gas is between 43 % and 72 %, there is a certain composition that can meet the requirement that the flow rate of recycled gas is equal to that of feed gas, so as to ensure that the subsequent production process does not need to add feed gas or discharge recycled gas. The energy efficiency of the CO₂ in feed gas at 43 % and 72 % is greater than 1, and the energy efficiency is relatively higher when the CO₂ mole fraction in feed gas is 72 %.Keywords: Gas production, hydrate, process integration, steam reforming
Procedia PDF Downloads 1764438 Effect of Fluidized Granular Activated Carbon for the Mitigation of Membrane Fouling in Wastewater Treatment
Authors: Jingwei Wang, Anthony G. Fane, Jia Wei Chew
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The use of fluidized Granular Activated Carbon (GAC) as a means of mitigation membrane fouling in membrane bioreactors (MBRs) has received much attention in recent years, especially in anaerobic fluidized bed membrane bioreactors (AFMBRs). It has been affirmed that the unsteady-state tangential shear conferred by GAC fluidization on membrane surface suppressed the extent of membrane fouling with energy consumption much lower than that of bubbling (i.e., air sparging). In a previous work, the hydrodynamics of the fluidized GAC particles were correlated with membrane fouling mitigation effectiveness. Results verified that the momentum transfer from particle to membrane held a key in fouling mitigation. The goal of the current work is to understand the effect of fluidized GAC on membrane critical flux. Membrane critical flux values were measured by a vertical Direct Observation Through the Membrane (DOTM) setup. The polystyrene particles (known as latex particles) with the particle size of 5 µm were used as model foulant thus to give the number of the foulant on the membrane surface. Our results shed light on the positive effect of fluidized GAC enhancing the critical membrane flux by an order-of-magnitude as compared to that of liquid shear alone. Membrane fouling mitigation was benefitted by the increasing of power input.Keywords: membrane fouling mitigation, liquid-solid fluidization, critical flux, energy input
Procedia PDF Downloads 4014437 Explanation Conceptual Model of the Architectural Form Effect on Structures in Building Aesthetics
Authors: Fatemeh Nejati, Farah Habib, Sayeh Goudarzi
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Architecture and structure have always been closely interrelated so that they should be integrated into a unified, coherent and beautiful universe, while in the contemporary era, both structures and architecture proceed separately. The purpose of architecture is the art of creating form and space and order for human service, and the goal of the structural engineer is the transfer of loads to the structure, too. This research seeks to achieve the goal by looking at the relationship between the form of architecture and structure from its inception to the present day to the Global Identification and Management Plan. Finally, by identifying the main components of the design of the structure in interaction with the architectural form, an effective step is conducted in the Professional training direction and solutions to professionals. Therefore, after reviewing the evolution of structural and architectural coordination in various historical periods as well as how to reach the form of the structure in different times and places, components are required to test the components and present the final theory that one hundred to be tested in this regard. Finally, this research indicates the fact that the form of architecture and structure has an aesthetic link, which is influenced by a number of components that could be edited and has a regular order throughout history that could be regular. The research methodology is analytic, and it is comparative using analytical and matrix diagrams and diagrams and tools for conducting library research and interviewing.Keywords: architecture, structural form, structural and architectural coordination, effective components, aesthetics
Procedia PDF Downloads 2104436 TQM Framework Using Notable Authors Comparative
Authors: Redha M. Elhuni
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This paper presents an analysis of the essential characteristics of the TQM philosophy by comparing the work of five notable authors in the field. A framework is produced which gather the identified TQM enablers under the well-known operations management dimensions of process, business and people. These enablers are linked with sustainable development via balance scorecard type economic and non-economic measures. In order to capture a picture of Libyan Company’s efforts to implement the TQM, a questionnaire survey is designed and implemented. Results of the survey are presented showing the main differentiating factors between the sample companies, and a way of assessing the difference between the theoretical underpinning and the practitioners’ undertakings. Survey results indicate that companies are experiencing much difficulty in translating TQM theory into practice. Only a few companies have successfully adopted a holistic approach to TQM philosophy, and most of these put relatively high emphasis on hard elements compared with soft issues of TQM. However, where companies can realize the economic outputs, non- economic benefits such as workflow management, skills development and team learning are not realized. In addition, overall, non-economic measures have secured low weightings compared with the economic measures. We believe that the framework presented in this paper can help a company to concentrate its TQM implementation efforts in terms of process, system and people management dimensions.Keywords: TQM, balance scorecard, EFQM excellence model, oil sector, Libya
Procedia PDF Downloads 3964435 A New Intelligent, Dynamic and Real Time Management System of Sewerage
Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem
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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.Keywords: automation, optimization, paradigm, RTC
Procedia PDF Downloads 2934434 Development of a Vacuum System for Orthopedic Drilling Processes and Determination of Optimal Processing Parameters for Temperature Control
Authors: Kadir Gök
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In this study, a vacuum system was developed for orthopedic drilling processes, and the most efficient processing parameters were determined using statistical analysis of temperature rise. A reverse engineering technique was used to obtain a 3D model of the chip vacuum system, and the obtained point cloud data was transferred to Solidworks software in STL format. An experimental design method was performed by selecting different parameters and their levels, such as RPM, feed rate, and drill bit diameter, to determine the most efficient processing parameters in temperature rise using ANOVA. Additionally, the bone chip-vacuum device was developed and performed successfully to collect the whole chips and fragments in the bone drilling experimental tests, and the chip-collecting device was found to be useful in removing overheating from the drilling zone. The effects of processing parameters on the temperature levels during the chip-vacuuming were determined, and it was found that bone chips and fractures can be used as autograft and allograft for tissue engineering. Overall, this study provides significant insights into the development of a vacuum system for orthopedic drilling processes and the use of bone chips and fractures in tissue engineering applications.Keywords: vacuum system, orthopedic drilling, temperature rise, bone chips
Procedia PDF Downloads 864433 Conceptualizing the Cyber Insecurity Risk in the Ethics of Automated Warfare
Authors: Otto Kakhidze, Hoda Alkhzaimi, Adam Ramey, Nasir Memon
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This paper provides an alternative, cyber security based a conceptual framework for the ethics of automated warfare. The large body of work produced on fully or partially autonomous warfare systems tends to overlook malicious security factors as in the possibility of technical attacks on these systems when it comes to the moral and legal decision-making. The argument provides a risk-oriented justification to why technical malicious risks cannot be dismissed in legal, ethical and policy considerations when warfare models are being implemented and deployed. The assumptions of the paper are supported by providing a broader model that contains the perspective of technological vulnerabilities through the lenses of the Game Theory, Just War Theory as well as standard and non-standard defense ethics. The paper argues that a conventional risk-benefit analysis without considering ethical factors is insufficient for making legal and policy decisions on automated warfare. This approach will provide the substructure for security and defense experts as well as legal scholars, ethicists and decision theorists to work towards common justificatory grounds that will accommodate the technical security concerns that have been overlooked in the current legal and policy models.Keywords: automated warfare, ethics of automation, inherent hijacking, security vulnerabilities, risk, uncertainty
Procedia PDF Downloads 3534432 Predicting Timely Delivery of Humanitarian Supplies Using Machine Learning Techniques
Authors: Mohammad Alshehri, Fahd Alfarsi
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Efficient supply chains play an essential role in delivering humanitarian supplies and directly impact the success of public aid initiatives globally. Predicting the delivery status of these essential supplies in a timely manner is crucial. Therefore, this study explores the application of various machine learning approaches to predict whether humanitarian deliveries will be made on time, using a comprehensive case-study dataset provided by one of the largest international supplying organisations. We employed several machine learning methods such as regression-based (e.g., logistics regression), tree-based (e.g., decision trees) and ensemble-based (e.g., AdaBoost, XGBoost, and Gradient Boosting) to develop our predictive model. Our findings demonstrate that ensemble algorithms achieved promising results, with F1 scores ranging from 0.90 to 0.98. These high accuracy levels indicate the robustness of ensemble-learning techniques in forecasting delivery status, potentially enabling more proactive and efficient supply chain management in global aid initiatives. The implications of this study suggest that integrating advanced predictive analytics can significantly enhance the reliability of supply chains, ensuring the timely delivery of critical commodities to those in need.Keywords: humanitarian aids, supply chains, machine learning, delivery status
Procedia PDF Downloads 174431 Overall Stability of Welded Q460GJ Steel Box Columns: Experimental Study and Numerical Simulations
Authors: Zhou Xiong, Kang Shao Bo, Yang Bo
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To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.Keywords: axial compression, box columns, global buckling, numerical simulations, Q460GJ steel
Procedia PDF Downloads 3984430 Smart Textiles Integration for Monitoring Real-time Air Pollution
Authors: Akshay Dirisala
Abstract:
Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models
Procedia PDF Downloads 1044429 A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test
Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany
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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution
Procedia PDF Downloads 1604428 A Case Study on the Collapse Assessment of the Steel Moment-Frame Setback High-Rise Tower
Authors: Marzie Shahini, Rasoul Mirghaderi
Abstract:
This paper describes collapse assessments of a steel moment-frame high-rise tower with setback irregularity, designed per the 2010 ASCE7 code, under spectral-matched ground motion records. To estimate a safety margin against life-threatening collapse, an analytical model of the tower is subjected to a suite of ground motions with incremental intensities from maximum considered earthquake hazard level to the incipient collapse level. Capability of the structural system to collapse prevention is evaluated based on the similar methodology reported in FEMA P695. Structural performance parameters in terms of maximum/mean inter-story drift ratios, residual drift ratios, and maximum plastic hinge rotations are also compared to the acceptance criteria recommended by the TBI Guidelines. The results demonstrate that the structural system satisfactorily safeguards the building against collapse. Moreover, for this tower, the code-specified requirements in ASCE7-10 are reasonably adequate to satisfy seismic performance criteria developed in the TBI Guidelines for the maximum considered earthquake hazard level.Keywords: high-rise buildings, set back, residual drift, seismic performance
Procedia PDF Downloads 2564427 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification
Authors: Bing Li, Zhi Li, Yilong Yang
Abstract:
Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery
Procedia PDF Downloads 132