Search results for: model based engineering MBE
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 38984

Search results for: model based engineering MBE

30044 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 84
30043 Multi-Agent System Based Distributed Voltage Control in Distribution Systems

Authors: A. Arshad, M. Lehtonen. M. Humayun

Abstract:

With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

Procedia PDF Downloads 309
30042 Self-Organization-Based Approach for Embedded Real-Time System Design

Authors: S. S. Bendib, L. W. Mouss, S. Kalla

Abstract:

This paper proposes a self-organization-based approach for real-time systems design. The addressed issue is the mapping of an application onto an architecture of heterogeneous processors while optimizing both makespan and reliability. Since this problem is NP-hard, a heuristic algorithm is used to obtain efficiently approximate solutions. The proposed approach takes into consideration the quality as well as the diversity of solutions. Indeed, an alternate treatment of the two objectives allows to produce solutions of good quality while a self-organization approach based on the neighborhood structure is used to reorganize solutions and consequently to enhance their diversity. Produced solutions make different compromises between the makespan and the reliability giving the user the possibility to select the solution suited to his (her) needs.

Keywords: embedded real-time systems design, makespan, reliability, self-organization, compromises

Procedia PDF Downloads 131
30041 Mitigation Strategies in the Urban Context of Sydney, Australia

Authors: Hamed Reza Heshmat Mohajer, Lan Ding, Mattheos Santamouris

Abstract:

One of the worst environmental dangers for people who live in cities is the Urban Heat Island (UHI) impact which is anticipated to become stronger in the coming years as a result of climate change. Accordingly, the key aim of this paper is to study the interaction between the urban configuration and mitigation strategies including increasing albedo of the urban environment (reflective material), implementation of Urban Green Infrastructure (UGI) and/or a combination thereof. To analyse the microclimate models of different urban categories in the metropolis of Sydney, this study will assess meteorological parameters using a 3D model simulation tool of computational fluid dynamics (CFD) named ENVI-met. In this study, four main parameters are taken into consideration while assessing the effectiveness of UHI mitigation strategies: ambient air temperature, wind speed/direction, and outdoor thermal comfort. Layouts with present condition simulation studies from the basic model (scenario one) are taken as the benchmark. A base model is used to calculate the relative percentage variations between each scenario. The findings showed that maximum cooling potential across different urban layouts can be decreased by 2.15 °C degrees by combining high-albedo material with flora; besides layouts with open arrangements(OT1) present a highly remarkable improvement in ambient air temperature and outdoor thermal comfort when mitigation technologies applied compare to compact counterparts. Besides all layouts present a higher intensity on the maximum ambient air temperature reduction rather than the minimum ambient air temperature. On the other hand, Scenarios associated with an increase in greeneries are anticipated to have a slight cooling effect, especially on high-rise layouts.

Keywords: sustainable urban development, urban green infrastructure, high-albedo materials, heat island effect

Procedia PDF Downloads 90
30040 Prioritizing Temporary Shelter Areas for Disaster Affected People Using Hybrid Decision Support Model

Authors: Ashish Trivedi, Amol Singh

Abstract:

In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

Procedia PDF Downloads 197
30039 Analyzing Success Factors of Canadian Play-Based Intervention Programs for Children with Different Abilities: A Comparative Study

Authors: Shuaa A. Mutawally, Budor H. Saigh, Ebtehal A. Mutawally

Abstract:

This study aims to analyze and compare the success factors of play-based intervention programs for children with different abilities in Canada. Children with disabilities often face limited participation in play and physical activities, leading to increased health risks. Understanding the specific features of these interventions that contribute to positive outcomes is crucial to promoting holistic development in these children. A comparative case study approach was used, selecting three similar successful intervention programs through purposive sampling. Data were collected through interviews and program documents, with 40 participants purposively chosen. Thematic analysis was conducted to identify key themes, including Quality Program, Meeting the Needs of Participants, and Lessons Learned from Experts and Practitioners. These programs play a vital role in addressing the gap in community programming for children with different abilities. The results of this study contribute to the generalization of success factors derived from best practices in play-based intervention programs for children with different abilities.

Keywords: children with different abilities, physical activity, play, play-based intervention programs

Procedia PDF Downloads 71
30038 The Differential Impacts of Shame and Guilt on Father Involvement in Families with Special Needs Children

Authors: Lo Kai Chung

Abstract:

Fathers in the family of disabled children play a crucial role in fostering child development. Previous studies addressing emotions of father involvement in rearing children with special needs have been rare. With reference to the cultural orientation and masculine idea of Chinese fathers, shame and guilt are probable causal emotions that affect fathers’ psycho-behavioral reactions and, thus, father involvement. Based on the findings of our earlier qualitative studies, the current study aims to develop and validate a multi-item scale of guilt or shame and explore their relations with and fatherhood in families with children with special needs. A model is proposed to understand the roles that shame and guilt play in affecting fathers’ involvement in their family system. The severity and type of the child’s special needs are regarded as independent variables affecting the father’s emotional responses – shame and guilt. It is hypothesized that shame and guilt, under the influence of masculinity, lead to avoidance and compensation, respectively, which subsequently decrease and increase father involvement with children with special needs. A cross-sectional online questionnaire survey of fathers with children with special needs recruited by convenience sampling was conducted. Potential participants were reached by bulk emails, related groups on the Internet and education/social services providers. Totally 537 valid sets of online questionnaires were collected from fathers of children with special needs. EFA on the items pool of shame and guilt was performed, resulting in an x-item single-factor solution and y-item single-factor solution, respectively. Further path model analysis revealed that shame and guilt, under the influence of masculinity, showed differential avoidance and compensation responses and resulted in a decrease and increase in father involvement with special needs children. Demographic and key confounding variables were controlled in the analysis. The shame and guilt scales developed show good psychometric properties. Furthermore, they showed significant differential impacts, under the influence of masculinity, on avoidance and compensation behaviours, consequently resulting in a decrease/increase in father involvement in the expected directions. The findings have important theoretical and practical implications. At the community and policy level, the findings inform the design of strategies for strengthening the role of men in families with special needs children.

Keywords: emotions, father involvement, guilt, shame, special needs

Procedia PDF Downloads 63
30037 Electrical Properties of Cement-Based Piezoelectric Nanoparticles

Authors: Moustafa Shawkey, Ahmed G. El-Deen, H. M. Mahmoud, M. M. Rashad

Abstract:

Piezoelectric based cement nanocomposite is a promising technology for generating an electric charge upon mechanical stress of concrete structure. Moreover, piezoelectric nanomaterials play a vital role for providing accurate system of structural health monitoring (SHM) of the concrete structure. In light of increasing awareness of environmental protection and energy crises, generating renewable and green energy form cement based on piezoelectric nanomaterials attracts the attention of the researchers. Herein, we introduce a facial synthesis for bismuth ferrite nanoparticles (BiFeO3 NPs) as piezoelectric nanomaterial via sol gel strategy. The fabricated piezoelectric nanoparticles are uniformly distributed to cement-based nanomaterials with different ratios. The morphological shape was characterized by field emission scanning electron microscopy (FESEM) and high-resolution transmission electron microscopy (HR-TEM) as well as the crystal structure has been confirmed using X-ray diffraction (XRD). The ferroelectric and magnetic behaviours of BiFeO3 NPs have been investigated. Then, dielectric constant for the prepared cement samples nanocomposites (εr) is calculated. Intercalating BiFeO3 NPs into cement materials achieved remarkable results as piezoelectric cement materials, distinct enhancement in ferroelectric and magnetic properties. Overall, this present study introduces an effective approach to improve the electrical properties based cement applications.

Keywords: piezoelectric nanomaterials, cement technology, bismuth ferrite nanoparticles, dielectric

Procedia PDF Downloads 245
30036 Geo-Additive Modeling of Family Size in Nigeria

Authors: Oluwayemisi O. Alaba, John O. Olaomi

Abstract:

The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

Procedia PDF Downloads 535
30035 Relating Interface Properties with Crack Propagation in Composite Laminates

Authors: Tao Qu, Chandra Prakash, Vikas Tomar

Abstract:

The interfaces between organic and inorganic phases in natural materials have been shown to be a key factor contributing to their high performance. This work analyzes crack propagation in a 2-ply laminate subjected to uniaxial tensile mode-I crack propagation loading that has laminate properties derived based on biological material constituents (marine exoskeleton- chitin and calcite). Interfaces in such laminates are explicitly modeled based on earlier molecular simulations performed by authors. Extended finite element method and cohesive zone modeling based simulations coupled with theoretical analysis are used to analyze crack propagation. Analyses explicitly quantify the effect that interface mechanical property variation has on the delamination as well as the transverse crack propagation in examined 2-ply laminates.

Keywords: chitin, composites, interfaces, fracture

Procedia PDF Downloads 376
30034 Modeling of an Insulin Mircopump

Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

Abstract:

Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

Procedia PDF Downloads 339
30033 The Importance of Analysis of Internal Quality Management Systems and Self-Examination Processes in Engineering Accreditation Processes

Authors: Wilfred Fritz

Abstract:

The accreditation process of engineering degree programmes is based on various reports evaluated by the relevant governing bodies of the institution of higher education. One of the aforementioned reports for the accreditation process is a self-assessment report which is to be completed by the applying institution. This paper seeks to emphasise the importance of analysis of internal quality management systems and self-examination processes in the engineering accreditation processes. A description of how the programme fulfils the criteria should be given. Relevant stakeholders all need to contribute in the writing and structuring of the self-assessment report. The last step is to gather evidence in the form of supporting documentation. In conclusion, the paper also identifies learning outcomes in a case study in seeking accreditation from an international relevant professional body.

Keywords: accreditation, governing bodies, self-assessment report, quality management

Procedia PDF Downloads 117
30032 Material Properties Evolution Affecting Demisability for Space Debris Mitigation

Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

Abstract:

The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence numerous studies have come up with technologies for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. Since the demisability of spacecraft depends on evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. Therefore, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: demisability, emissivity, lightweight, re-entry, survivability

Procedia PDF Downloads 109
30031 Unsteady Characteristics Investigation on the Precessing Vortex Breakdown and Energy Separation in a Vortex Tube

Authors: Xiangji Guo, Bo Zhang

Abstract:

In this paper, the phenomenon of vortex breakdown in a vortex tube was analyzed within the scope of unsteady character in swirl flows. A 3-D Unsteady Reynolds-averaged Navier–Stokes (URANS) closed by the Reynolds Stress Model (RSM) was adopted to simulate the large-scale vortex structure in vortex tube, and the numerical model was verified by the steady results. The swirl number was calculated for the vortex tube and the flow field was classed as strong swirl flow. According to the results, a time-dependent spiral flow field gyrates around a central recirculation zone which is precessing around the axis of the tube, and manifests the flow structure is the spiral type (S-type) vortex breakdown. The vortex breakdown is crucial for the formation of the central recirculation zone (CRZ), a further discussion was about the affection on CRZ with the different external conditions of vortex tube, the study on the unsteady characters was expected to hope to design of vortex tube and analyze the energy separation effect.

Keywords: vortex tube, vortex breakdown, central recirculation zone, unsteady, energy separation

Procedia PDF Downloads 311
30030 The Science of Health Care Delivery: Improving Patient-Centered Care through an Innovative Education Model

Authors: Alison C. Essary, Victor Trastek

Abstract:

Introduction: The current state of the health care system in the U.S. is characterized by an unprecedented number of people living with multiple chronic conditions, unsustainable rise in health care costs, inadequate access to care, and wide variation in health outcomes throughout the country. An estimated two-thirds of Americans are living with two or more chronic conditions, contributing to 75% of all health care spending. In 2013, the School for the Science of Health Care Delivery (SHCD) was charged with redesigning the health care system through education and research. Faculty in business, law, and public policy, and thought leaders in health care delivery, administration, public health and health IT created undergraduate, graduate, and executive academic programs to address this pressing need. Faculty and students work across disciplines, and with community partners and employers to improve care delivery and increase value for patients. Methods: Curricula apply content in health care administration and operations within the clinical context. Graduate modules are team-taught by faculty across academic units to model team-based practice. Seminars, team-based assignments, faculty mentoring, and applied projects are integral to student success. Cohort-driven models enhance networking and collaboration. This observational study evaluated two years of admissions data, and one year of graduate data to assess program outcomes and inform the current graduate-level curricula. Descriptive statistics includes means, percentages. Results: Fall 2013, the program received 51 applications. The mean GPA of the entering class of 37 students was 3.38. Ninety-seven percent of the fall 2013 cohort successfully completed the program (n=35). Sixty-six percent are currently employed in the health care industry (n=23). Of the remaining 12 graduates, two successfully matriculated to medical school; one works in the original field of study; four await results on the MCAT or DAT, and five were lost to follow up. Attrition of one student was attributed to non-academic reasons. Fall 2014, the program expanded to include both on-ground and online cohorts. Applications were evenly distributed between on-ground (n=70) and online (n=68). Thirty-eight students enrolled in the on-ground program. The mean GPA was 3.95. Ninety-five percent of students successfully completed the program (n=36). Thirty-six students enrolled in the online program. The mean GPA was 3.85. Graduate outcomes are pending. Discussion: Challenges include demographic variability between online and on-ground students; yet, both profiles are similar in that students intend to become change agents in the health care system. In the past two years, on-ground applications increased by 31%, persistence to graduation is > 95%, mean GPA is 3.67, graduates report admission to six U.S. medical schools, the Mayo Medical School integrates SHCD content within their curricula, and there is national interest in collaborating on industry and academic partnerships. This places SHCD at the forefront of developing innovative curricula in order to improve high-value, patient-centered care.

Keywords: delivery science, education, health care delivery, high-value care, innovation in education, patient-centered

Procedia PDF Downloads 278
30029 Play-Based Early Education and Teachers’ Professional Development: Impact on Vulnerable Children

Authors: Chirine Dannaoui, Maya Antoun

Abstract:

This paper explores the intricate dynamics of play-based early childhood education (ECE) and the impact of professional development on teachers implementing play-based pedagogy, particularly in the context of vulnerable Syrian refugee children in Lebanon. By utilizing qualitative methodologies, including classroom observations and in-depth interviews with five early childhood educators and a field manager, this study delves into the challenges and transformations experienced by teachers in adopting play-based learning strategies. The research unveils the critical role of continuous and context-specific professional development in empowering teachers to implement play-based pedagogies effectively. When appropriately supported, it emphasizes how such educational approaches significantly enhance children's cognitive, social, and emotional development in crisis-affected environments. Key findings indicate that despite diverse educational backgrounds, teachers show considerable growth in their pedagogical skills through targeted professional development. This growth is vital for fostering a learning environment where vulnerable children can thrive, particularly in humanitarian settings. The paper also addresses educators' challenges, including adapting to play-based methodologies, resource limitations, and balancing curricular requirements with the need for holistic child development. This study contributes to the discourse on early childhood education in crisis contexts, emphasizing the need for sustainable, well-structured professional development programs. It underscores the potential of play-based learning to bridge educational gaps and contribute to the healing process of children facing calamity. The study highlights significant implications for policymakers, educators, schools, and not-for-profit organizations engaged in early childhood education in humanitarian contexts, stressing the importance of investing in teacher capacity and curriculum reform to enhance the quality of education for children in general and vulnerable ones in particular.

Keywords: play-based learning, professional development, vulnerable children, early childhood education

Procedia PDF Downloads 55
30028 Cybersecurity Protective Behavior in Industrial Revolution 4.0 Era: A Conceptual Framework

Authors: Saif Hussein Abdallah Alghazo, Norshima Humaidi

Abstract:

Adopting cybersecurity protective behaviour among the employees is seriously considered in the organization, especially when the Internet of Things (IoT) is widely used in Industrial Revolution 4.0 (IR 4.0) era. Cybersecurity issues arise due to weaknesses of employees’ behaviour such as carelessness and failure to adopt good practices of information security behaviour. Therefore, this study aims to explore the dimensions that might influence employees’ behaviour to adopt good cybersecurity practices and to develop a new holistic model related to this concept. The study proposed this by reviewing the existing works of literature related to this field extensively, especially by focusing on the existing theory such as Protection Motivation Theory (PMT). Moreover, this study has also explored the role of cybersecurity competency among the security manager in the organization since this construct is essential to enhance the protective behaviour towards cybersecurity among the employees in the organization. The proposed research model is important to be quantitatively tested in the future as the findings will serve as the input to the act that will enhance employee’s cybersecurity protective behaviour in the IR 4.0 environment.

Keywords: cybersecurity protective behaviour, protection motivation theory, IR 4.0, cybersecurity competency

Procedia PDF Downloads 146
30027 Analysis of Correlation Between Manufacturing Parameters and Mechanical Strength Followed by Uncertainty Propagation of Geometric Defects in Lattice Structures

Authors: Chetra Mang, Ahmadali Tahmasebimoradi, Xavier Lorang

Abstract:

Lattice structures are widely used in various applications, especially in aeronautic, aerospace, and medical applications because of their high performance properties. Thanks to advancement of the additive manufacturing technology, the lattice structures can be manufactured by different methods such as laser beam melting technology. However, the presence of geometric defects in the lattice structures is inevitable due to the manufacturing process. The geometric defects may have high impact on the mechanical strength of the structures. This work analyzes the correlation between the manufacturing parameters and the mechanical strengths of the lattice structures. To do that, two types of the lattice structures; body-centered cubic with z-struts (BCCZ) structures made of Inconel718, and body-centered cubic (BCC) structures made of Scalmalloy, are manufactured by laser melting beam machine using Taguchi design of experiment. Each structure is placed on the substrate with a specific position and orientation regarding the roller direction of deposed metal powder. The position and orientation are considered as the manufacturing parameters. The geometric defects of each beam in the lattice are characterized and used to build the geometric model in order to perform simulations. Then, the mechanical strengths are defined by the homogeneous response as Young's modulus and yield strength. The distribution of mechanical strengths is observed as a function of manufacturing parameters. The mechanical response of the BCCZ structure is stretch-dominated, i.e., the mechanical strengths are directly dependent on the strengths of the vertical beams. As the geometric defects of vertical beams are slightly changed based on their position/orientation on the manufacturing substrate, the mechanical strengths are less dispersed. The manufacturing parameters are less influenced on the mechanical strengths of the structure BCCZ. The mechanical response of the BCC structure is bending-dominated. The geometric defects of inclined beam are highly dispersed within a structure and also based on their position/orientation on the manufacturing substrate. For different position/orientation on the substrate, the mechanical responses are highly dispersed as well. This shows that the mechanical strengths are directly impacted by manufacturing parameters. In addition, this work is carried out to study the uncertainty propagation of the geometric defects on the mechanical strength of the BCC lattice structure made of Scalmalloy. To do that, we observe the distribution of mechanical strengths of the lattice according to the distribution of the geometric defects. A probability density law is determined based on a statistical hypothesis corresponding to the geometric defects of the inclined beams. The samples of inclined beams are then randomly drawn from the density law to build the lattice structure samples. The lattice samples are then used for simulation to characterize the mechanical strengths. The results reveal that the distribution of mechanical strengths of the structures with the same manufacturing parameters is less dispersed than one of the structures with different manufacturing parameters. Nevertheless, the dispersion of mechanical strengths due to the structures with the same manufacturing parameters are unneglectable.

Keywords: geometric defects, lattice structure, mechanical strength, uncertainty propagation

Procedia PDF Downloads 121
30026 Structural Parameter Identification of Old Steel Truss Bridges

Authors: A. Bogdanovic, M. Vitanova, J. Bojadjieva, Z. Rakicevic, V. Sesov, K. Edip, N. Naumovski, F. Manojlovski, A.Popovska, A. Shoklarovski, T. Kitanovski, D. Ivanovski, I. Markovski, D. Filipovski

Abstract:

The conditions of existing structures change in the course of time and can hardly be characterized particularly if a bridge has long been in function and there is no design documentation related to it. To define the real conditions of a structure, detailed static and dynamic analysis of the structure has to be carried out and its modal parameters have to be defined accurately. Modal analysis enables a quite accurate identification of the natural frequencies and mode shapes. Presented in this paper are the results from the performed detailed analyses of a steel truss bridge that has been in use for more than 7 decades by the military services of R.N. Macedonia and for which there is no documentation at all. Static and dynamic investigations and ambient vibration measurements were performed. The acquired data were used to identify the mode shapes that were used for comparison with the numerical model. Dynamic tests were performed to define the bridge behaviour and the damping index. Finally, based on all the conducted detailed analyses and investigations, conclusions on the conditions of the bridge structure were drawn.

Keywords: ambient vibrations, dynamic identification, in-situ measurement, steel truss bridge

Procedia PDF Downloads 86
30025 Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program

Authors: Ming Wen, Nasim Nezamoddini

Abstract:

Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

Procedia PDF Downloads 107
30024 Neural Network Approach to Classifying Truck Traffic

Authors: Ren Moses

Abstract:

The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

Procedia PDF Downloads 306
30023 Finite Element Simulation of Four Point Bending of Laminated Veneer Lumber (LVL) Arch

Authors: Eliska Smidova, Petr Kabele

Abstract:

This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

Procedia PDF Downloads 284
30022 Bimetallic MOFs Based Membrane for the Removal of Heavy Metal Ions from the Industrial Wastewater

Authors: Muhammad Umar Mushtaq, Muhammad Bilal Khan Niazi, Nouman Ahmad, Dooa Arif

Abstract:

Apart from organic dyes, heavy metals such as Pb, Ni, Cr, and Cu are present in textile effluent and pose a threat to humans and the environment. Many studies on removing heavy metallic ions from textile wastewater have been conducted in recent decades using metal-organic frameworks (MOFs). In this study new polyether sulfone ultrafiltration membrane, modified with Cu/Co and Cu/Zn-based bimetal-organic frameworks (MOFs), was produced. Phase inversion was used to produce the membrane, and atomic force microscopy (AFM), scanning electron microscopy (SEM) were used to characterize it. The bimetallic MOFs-based membrane structure is complex and can be comprehended using characterization techniques. The bimetallic MOF-based filtration membranes are designed to selectively adsorb specific contaminants while allowing the passage of water molecules, improving the ultrafiltration efficiency. MOFs' adsorption capacity and selectivity are enhanced by functionalizing them with particular chemical groups or incorporating them into composite membranes with other materials, such as polymers. The morphology and performance of the bimetallic MOF-based membrane were investigated regarding pure water flux and metal ion rejection. The advantages of developed bimetallic MOFs based membranes for wastewater treatment include enhanced adsorption capacity because of the presence of two metals in their structure, which provides additional binding sites for contaminants, leading to a higher adsorption capacity and more efficient removal of pollutants from wastewater. Based on the experimental findings, bimetallic MOF-based membranes are more capable of rejecting metal ions from industrial wastewater than conventional membranes that have already been developed. Furthermore, the difficulties associated with operational parameters, including pressure gradients and velocity profiles, are simulated using Ansys Fluent software. The simulation results obtained for the operating parameters are in complete agreement with the experimental results.

Keywords: bimetallic MOFs, heavy metal ions, industrial wastewater treatment, ultrafiltration.

Procedia PDF Downloads 86
30021 Lean Comic GAN (LC-GAN): a Light-Weight GAN Architecture Leveraging Factorized Convolution and Teacher Forcing Distillation Style Loss Aimed to Capture Two Dimensional Animated Filtered Still Shots Using Mobile Phone Camera and Edge Devices

Authors: Kaustav Mukherjee

Abstract:

In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

Procedia PDF Downloads 130
30020 Machine Learning-Driven Prediction of Cardiovascular Diseases: A Supervised Approach

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

Procedia PDF Downloads 33
30019 Submicron Size of Alumina/Titania Tubes for CO2-CH4 Conversion

Authors: Chien-Wan Hun, Shao-Fu Chang, Jheng-En Yang, Chien-Chon Chen, Wern-Dare Jheng

Abstract:

This research provides a systematic way to study and better understand double nano-tubular structure of alunina (Al2O3) and titania (TiO2). The TiO2 NT was prepared by immersing Al2O3 template in 0.02 M titanium fluoride (TiF4) solution (pH=3) at 25 °C for 120 min, followed by annealing at 450 °C for 1 h to obtain anatase TiO2 NT in the Al2O3 template. Large-scale development of film for nanotube-based CO2 capture and conversion can potentially result in more efficient energy harvesting. In addition, the production process will be relatively environmentally friendly. The knowledge generated by this research will significantly advance research in the area of Al2O3, TiO2, CaO, and Ca2O3 nano-structure film fabrication and applications for CO2 capture and conversion. This green energy source will potentially reduce reliance on carbon-based energy resources and increase interest in science and engineering careers.

Keywords: alumina, titania, nano-tubular, film, CO2

Procedia PDF Downloads 390
30018 Formulation of Optimal Shifting Sequence for Multi-Speed Automatic Transmission

Authors: Sireesha Tamada, Debraj Bhattacharjee, Pranab K. Dan, Prabha Bhola

Abstract:

The most important component in an automotive transmission system is the gearbox which controls the speed of the vehicle. In an automatic transmission, the right positioning of actuators ensures efficient transmission mechanism embodiment, wherein the challenge lies in formulating the number of actuators associated with modelling a gearbox. Data with respect to actuation and gear shifting sequence has been retrieved from the available literature, including patent documents, and has been used in this proposed heuristics based methodology for modelling actuation sequence in a gear box. This paper presents a methodological approach in designing a gearbox for the purpose of obtaining an optimal shifting sequence. The computational model considers factors namely, the number of stages and gear teeth as input parameters since these two are the determinants of the gear ratios in an epicyclic gear train. The proposed transmission schematic or stick diagram aids in developing the gearbox layout design. The number of iterations and development time required to design a gearbox layout is reduced by using this approach.

Keywords: automatic transmission, gear-shifting, multi-stage planetary gearbox, rank ordered clustering

Procedia PDF Downloads 321
30017 Development of a Real Time Axial Force Measurement System and IoT-Based Monitoring for Smart Bearing

Authors: Hassam Ahmed, Yuanzhi Liu, Yassine Selami, Wei Tao, Hui Zhao

Abstract:

The purpose of this research is to develop a real time axial force measurement system for a smart bearing through the use of strain-gauges, whereby the data acquisition is performed by an Arduino microcontroller due to its easy manipulation and low-cost. The measured signal is acquired and then discretized using a Wheatstone Bridge and an Analog-Digital Converter (ADC) respectively. For bearing monitoring, a real time monitoring system based on Internet of things (IoT) and Bluetooth were developed. Experimental tests were performed on a bearing within a force range up to 600 kN. The experimental results show that there is a proportional linear relationship between the applied force and the output voltage, and the error R squared is within 0.9878 based on the regression analysis.

Keywords: bearing, force measurement, IoT, strain gauge

Procedia PDF Downloads 138
30016 Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles

Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane

Abstract:

In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.

Keywords: autonomous vehicles, convoy, non-linear control, non-linear observer, sliding mode

Procedia PDF Downloads 136
30015 A U-Net Based Architecture for Fast and Accurate Diagram Extraction

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

Abstract:

In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 132