Search results for: school based support program
14907 Optimization of Mechanical Properties of Alginate Hydrogel for 3D Bio-Printing Self-Standing Scaffold Architecture for Tissue Engineering Applications
Authors: Ibtisam A. Abbas Al-Darkazly
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In this study, the mechanical properties of alginate hydrogel material for self-standing 3D scaffold architecture with proper shape fidelity are investigated. In-lab built 3D bio-printer extrusion-based technology is utilized to fabricate 3D alginate scaffold constructs. The pressure, needle speed and stage speed are varied using a computer-controlled system. The experimental result indicates that the concentration of alginate solution, calcium chloride (CaCl2) cross-linking concentration and cross-linking ratios lead to the formation of alginate hydrogel with various gelation states. Besides, the gelling conditions, such as cross-linking reaction time and temperature also have a significant effect on the mechanical properties of alginate hydrogel. Various experimental tests such as the material gelation, the material spreading and the printability test for filament collapse as well as the swelling test were conducted to evaluate the fabricated 3D scaffold constructs. The result indicates that the fabricated 3D scaffold from composition of 3.5% wt alginate solution, that is prepared in DI water and 1% wt CaCl2 solution with cross-linking ratios of 7:3 show good printability and sustain good shape fidelity for more than 20 days, compared to alginate hydrogel that is prepared in a phosphate buffered saline (PBS). The fabricated self-standing 3D scaffold constructs measured 30 mm × 30 mm and consisted of 4 layers (n = 4) show good pore geometry and clear grid structure after printing. In addition, the percentage change of swelling degree exhibits high swelling capability with respect to time. The swelling test shows that the geometry of 3D alginate-scaffold construct and of the macro-pore are rarely changed, which indicates the capability of holding the shape fidelity during the incubation period. This study demonstrated that the mechanical and physical properties of alginate hydrogel could be tuned for a 3D bio-printing extrusion-based system to fabricate self-standing 3D scaffold soft structures. This 3D bioengineered scaffold provides a natural microenvironment present in the extracellular matrix of the tissue, which could be seeded with the biological cells to generate the desired 3D live tissue model for in vitro and in vivo tissue engineering applications.Keywords: biomaterial, calcium chloride, 3D bio-printing, extrusion, scaffold, sodium alginate, tissue engineering
Procedia PDF Downloads 10614906 Follower Upward Influence Tactics: A Review of Quantitative Studies
Authors: Najla Alshenaifi, Nicholas Clarke
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Interest in how followers may influence their leaders in order to achieve their goals can be traced to studies in the late 1970s. The last major review of the literature was published over a decade ago in 2002. It would seem timely then to take stock of the literature and consider what we have learned since then. In so doing, our aim is to derive an empirically-based framework for understanding the effects of upward influence tactics to underpin future research in the field. Many factors are identified as having a major effect on upward influence processes including goals of influence, culture, gender, leadership style and the outcome of influence. A key conclusion from our review is that although upward influence tactics can result in positive outcomes for followers, the results from many studies are more often than inconclusive.Keywords: upward influence tactics, influence tactics, influence strategies, followership
Procedia PDF Downloads 38014905 Distinct Patterns of Resilience Identified Using Smartphone Mobile Experience Sampling Method (M-ESM) and a Dual Model of Mental Health
Authors: Hussain-Abdulah Arjmand, Nikki S. Rickard
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The response to stress can be highly heterogenous, and may be influenced by methodological factors. The integrity of data will be optimized by measuring both positive and negative affective responses to an event, by measuring responses in real time as close to the stressful event as possible, and by utilizing data collection methods that do not interfere with naturalistic behaviours. The aim of the current study was to explore short term prototypical responses to major stressor events on outcome measures encompassing both positive and negative indicators of psychological functioning. A novel mobile experience sampling methodology (m-ESM) was utilized to monitor both effective responses to stressors in real time. A smartphone mental health app (‘Moodprism’) which prompts users daily to report both their positive and negative mood, as well as whether any significant event had occurred in the past 24 hours, was developed for this purpose. A sample of 142 participants was recruited as part of the promotion of this app. Participants’ daily reported experience of stressor events, levels of depressive symptoms and positive affect were collected across a 30 day period as they used the app. For each participant, major stressor events were identified on the subjective severity of the event rated by the user. Depression and positive affect ratings were extracted for the three days following the event. Responses to the event were scaled relative to their general reactivity across the remainder of the 30 day period. Participants were first clustered into groups based on initial reactivity and subsequent recovery following a stressor event. This revealed distinct patterns of responding along depressive symptomatology and positive affect. Participants were then grouped based on allocations to clusters in each outcome variable. A highly individualised nature in which participants respond to stressor events, in symptoms of depression and levels of positive affect, was observed. A complete description of the novel profiles identified will be presented at the conference. These findings suggest that real-time measurement of both positive and negative functioning to stressors yields a more complex set of responses than previously observed with retrospective reporting. The use of smartphone technology to measure individualized responding also proved to shed significant insight.Keywords: depression, experience sampling methodology, positive functioning, resilience
Procedia PDF Downloads 23414904 Applications of Probabilistic Interpolation via Orthogonal Matrices
Authors: Dariusz Jacek Jakóbczak
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Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation
Procedia PDF Downloads 52014903 A Prediction Method of Pollutants Distribution Pattern: Flare Motion Using Computational Fluid Dynamics (CFD) Fluent Model with Weather Research Forecast Input Model during Transition Season
Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada
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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model
Procedia PDF Downloads 54114902 The Use of Artificial Intelligence in Digital Forensics and Incident Response in a Constrained Environment
Authors: Dipo Dunsin, Mohamed C. Ghanem, Karim Ouazzane
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Digital investigators often have a hard time spotting evidence in digital information. It has become hard to determine which source of proof relates to a specific investigation. A growing concern is that the various processes, technology, and specific procedures used in the digital investigation are not keeping up with criminal developments. Therefore, criminals are taking advantage of these weaknesses to commit further crimes. In digital forensics investigations, artificial intelligence is invaluable in identifying crime. It has been observed that an algorithm based on artificial intelligence (AI) is highly effective in detecting risks, preventing criminal activity, and forecasting illegal activity. Providing objective data and conducting an assessment is the goal of digital forensics and digital investigation, which will assist in developing a plausible theory that can be presented as evidence in court. Researchers and other authorities have used the available data as evidence in court to convict a person. This research paper aims at developing a multiagent framework for digital investigations using specific intelligent software agents (ISA). The agents communicate to address particular tasks jointly and keep the same objectives in mind during each task. The rules and knowledge contained within each agent are dependent on the investigation type. A criminal investigation is classified quickly and efficiently using the case-based reasoning (CBR) technique. The MADIK is implemented using the Java Agent Development Framework and implemented using Eclipse, Postgres repository, and a rule engine for agent reasoning. The proposed framework was tested using the Lone Wolf image files and datasets. Experiments were conducted using various sets of ISA and VMs. There was a significant reduction in the time taken for the Hash Set Agent to execute. As a result of loading the agents, 5 percent of the time was lost, as the File Path Agent prescribed deleting 1,510, while the Timeline Agent found multiple executable files. In comparison, the integrity check carried out on the Lone Wolf image file using a digital forensic tool kit took approximately 48 minutes (2,880 ms), whereas the MADIK framework accomplished this in 16 minutes (960 ms). The framework is integrated with Python, allowing for further integration of other digital forensic tools, such as AccessData Forensic Toolkit (FTK), Wireshark, Volatility, and Scapy.Keywords: artificial intelligence, computer science, criminal investigation, digital forensics
Procedia PDF Downloads 20114901 Automatic and High Precise Modeling for System Optimization
Authors: Stephanie Chen, Mitja Echim, Christof Büskens
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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization
Procedia PDF Downloads 40014900 Development of Coastal Inundation–Inland and River Flow Interface Module Based on 2D Hydrodynamic Model
Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han
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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model
Procedia PDF Downloads 35414899 Early Initiation of Breastfeeding and Its Determinants among Non-Caesarean Deliveries at Primary and Secondary Health Facilities: A Case Observational Study
Authors: Farhana Karim, Abdullah N. S. Khan, Mohiuddin A. K. Chowdhury, Nabila Zaka, Alexander Manu, Shams El Arifeen, Sk Masum Billah
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Breastfeeding, an integral part of newborn care, can reduce 55-87% of all-cause neonatal mortality and morbidity. Early initiation of breastfeeding within 1 hour of birth can avert 22% of newborn mortality. Only 45% of world’s newborns and 42% of newborns in South-Asia are put to the breast within one hour of birth. In Bangladesh, only a half of the mothers practice early initiation of breastfeeding which is less likely to be practiced if the baby is born in a health facility. This study aims to generate strong evidence for early initiation of breastfeeding practices in the government health facilities and to explore the associated factors influencing the practice. The study was conducted in selected health facilities in three neighbouring districts of Northern Bangladesh. Total 249 normal vaginal delivery cases were observed for 24 hours since the time of birth. The outcome variable was initiation of breastfeeding within 1 hour while the explanatory variables included type of health facility, privacy, presence of support person, stage of labour at admission, need for augmentation of labour, complications during delivery, need for episiotomy, spontaneous cry of the newborn, skin-to-skin contact with mother, post-natal contact with the service provider, receiving a post-natal examination and counselling on breastfeeding during postnatal contact. The simple descriptive statistics were employed to see the distribution of samples according to socio-demographic characteristics. Kruskal-Wallis test was carried out for testing the equality of medians among two or more categories of each variable and P-value is reported. A series of simple logistic regressions were conducted with all the potential explanatory variables to identify the determining factors for breastfeeding within 1 hour in a health facility. Finally, multiple logistic regression was conducted including the variables found significant at bi-variate analyses. Almost 90% participants initiated breastfeeding at the health facility and median time to initiate breastfeeding was 38 minutes. However, delivering in a sub-district hospital significantly delayed the breastfeeding initiation in comparison to delivering in a district hospital. Maintenance of adequate privacy and presence of separate staff for taking care of newborn significantly reduced the time in early breastfeeding initiation. Initiation time was found longer if the mother had an augmented labour, obstetric complications, and the newborn needed resuscitation. However, the initiation time was significantly early if the baby was put skin-to-skin on mother’s abdomen and received a postnatal examination by a provider. After controlling for the potential confounders, the odds of initiating breastfeeding within one hour of birth is higher if mother gives birth in a district hospital (AOR 3.0: 95% CI 1.5, 6.2), privacy is well-maintained (AOR 2.3: 95% CI 1.1, 4.5), babies cry spontaneously (AOR 7.7: 95% CI 3.3, 17.8), babies are put to skin-to-skin contact with mother (AOR 4.6: 95% CI 1.9, 11.2) and if the baby is examined by a provider in the facility (AOR 4.4: 95% CI 1.4, 14.2). The evidence generated by this study will hopefully direct the policymakers to identify and prioritize the scopes for creating and supporting early initiation of breastfeeding in the health facilities.Keywords: Bangladesh, early initiation of breastfeeding, health facility, normal vaginal delivery, skin to skin contact
Procedia PDF Downloads 14714898 Application of Sub-health Diagnosis and Reasoning Method for Avionics
Authors: Weiran An, Junyou Shi
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Health management has become one of the design goals in the research and development of new generation avionics systems, and is an important complement and development for the testability and fault diagnosis technology. Currently, the research and application for avionics system health dividing and diagnosis technology is still at the starting stage, lack of related technologies and methods reserve. In this paper, based on the health three-state dividing of avionics products, state lateral transfer coupling modeling and diagnosis reasoning method considering sub-health are researched. With the study of typical case application, the feasibility and correctness of the method and the software are verified.Keywords: sub-health, diagnosis reasoning, three-valued coupled logic, extended dependency model, avionics
Procedia PDF Downloads 32614897 An Iterative Family for Solution of System of Nonlinear Equations
Authors: Sonia Sonia
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This paper presents a family of iterative scheme for solving nonlinear systems of equations which have wide application in sciences and engineering. The proposed iterative family is based upon some parameters which generates many different iterative schemes. This family is completely derivative free and uses first of divided difference operator. Moreover some numerical experiments are performed and compared with existing methods. Analysis of convergence shows that the presented family has fourth-order of convergence. The dynamical behaviour of proposed family and local convergence have also been discussed. The numerical performance and convergence region comparison demonstrates that proposed family is efficient.Keywords: convergence, divided difference operator, nonlinear system, Newton's method
Procedia PDF Downloads 22814896 Accurate HLA Typing at High-Digit Resolution from NGS Data
Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang
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Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.Keywords: human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing
Procedia PDF Downloads 65514895 Enabling Wire Arc Additive Manufacturing in Aircraft Landing Gear Production and Its Benefits
Authors: Jun Wang, Chenglei Diao, Emanuele Pagone, Jialuo Ding, Stewart Williams
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As a crucial component in aircraft, landing gear systems are responsible for supporting the plane during parking, taxiing, takeoff, and landing. Given the need for high load-bearing capacity over extended periods, 300M ultra-high strength steel (UHSS) is often the material of choice for crafting these systems due to its exceptional strength, toughness, and fatigue resistance. In the quest for cost-effective and sustainable manufacturing solutions, Wire Arc Additive Manufacturing (WAAM) emerges as a promising alternative for fabricating 300M UHSS landing gears. This is due to its advantages in near-net-shape forming of large components, cost-efficiency, and reduced lead times. Cranfield University has conducted an extensive preliminary study on WAAM 300M UHSS, covering feature deposition, interface analysis, and post-heat treatment. Both Gas Metal Arc (GMA) and Plasma Transferred Arc (PTA)-based WAAM methods were explored, revealing their feasibility for defect-free manufacturing. However, as-deposited 300M features showed lower strength but higher ductility compared to their forged counterparts. Subsequent post-heat treatments were effective in normalising the microstructure and mechanical properties, meeting qualification standards. A 300M UHSS landing gear demonstrator was successfully created using PTA-based WAAM, showcasing the method's precision and cost-effectiveness. The demonstrator, measuring Ф200mm x 700mm, was completed in 16 hours, using 7 kg of material at a deposition rate of 1.3kg/hr. This resulted in a significant reduction in the Buy-to-Fly (BTF) ratio compared to traditional manufacturing methods, further validating WAAM's potential for this application. A "cradle-to-gate" environmental impact assessment, which considers the cumulative effects from raw material extraction to customer shipment, has revealed promising outcomes. Utilising Wire Arc Additive Manufacturing (WAAM) for landing gear components significantly reduces the need for raw material extraction and refinement compared to traditional subtractive methods. This, in turn, lessens the burden on subsequent manufacturing processes, including heat treatment, machining, and transportation. Our estimates indicate that the carbon footprint of the component could be halved when switching from traditional machining to WAAM. Similar reductions are observed in embodied energy consumption and other environmental impact indicators, such as emissions to air, water, and land. Additionally, WAAM offers the unique advantage of part repair by redepositing only the necessary material, a capability not available through conventional methods. Our research shows that WAAM-based repairs can drastically reduce environmental impact, even when accounting for additional transportation for repairs. Consequently, WAAM emerges as a pivotal technology for reducing environmental impact in manufacturing, aiding the industry in its crucial and ambitious journey towards Net Zero. This study paves the way for transformative benefits across the aerospace industry, as we integrate manufacturing into a hybrid solution that offers substantial savings and access to more sustainable technologies for critical component production.Keywords: WAAM, aircraft landing gear, microstructure, mechanical performance, life cycle assessment
Procedia PDF Downloads 15314894 An Integrated Tailoring Method for Thermal Cycling Tests of Spacecraft Electronics
Authors: Xin-Yan Ji, Jing Wang, Chang Liu, Yan-Qiang Bi, Zhong-Xu Xu, Xi-Yuan Li
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Thermal tests of electronic units are critically important for the reliability validation and performance demonstration of the spacecraft hard-wares. The tailoring equation in MIL-STD-1540 is based on fatigue of solder date. In the present paper, a new test condition tailoring expression is proposed to fit different thermo-mechanical fatigue and different subsystems, by introducing an integrated evaluating method for the fatigue acceleration exponent. The validate test has been accomplished and the data has been analyzed and compared with that from the MIL-STD-1540 tailoring equations. The results are encouraging and reasonable.Keywords: thermal cycling test, thermal fatigue, tailoring equation, test condition planning
Procedia PDF Downloads 44414893 Preliminary Seismic Vulnerability Assessment of Existing Historic Masonry Building in Pristina, Kosovo
Authors: Florim Grajcevci, Flamur Grajcevci, Fatos Tahiri, Hamdi Kurteshi
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The territory of Kosova is actually included in one of the most seismic-prone regions in Europe. Therefore, the earthquakes are not so rare in Kosova; and when they occurred, the consequences have been rather destructive. The importance of assessing the seismic resistance of existing masonry structures has drawn strong and growing interest in the recent years. Engineering included those of Vulnerability, Loss of Buildings and Risk assessment, are also of a particular interest. This is due to the fact that this rapidly developing field is related to great impact of earthquakes on the socioeconomic life in seismic-prone areas, as Kosova and Prishtina are, too. Such work paper for Prishtina city may serve as a real basis for possible interventions in historic buildings as are museums, mosques, old residential buildings, in order to adequately strengthen and/or repair them, by reducing the seismic risk within acceptable limits. The procedures of the vulnerability assessment of building structures have concentrated on structural system, capacity, and the shape of layout and response parameters. These parameters will provide expected performance of the very important existing building structures on the vulnerability and the overall behavior during the earthquake excitations. The structural systems of existing historical buildings in Pristina, Kosovo, are dominantly unreinforced brick or stone masonry with very high risk potential from the expected earthquakes in the region. Therefore, statistical analysis based on the observed damage-deformation, cracks, deflections and critical building elements, would provide more reliable and accurate results for the regional assessments. The analytical technique was used to develop a preliminary evaluation methodology for assessing seismic vulnerability of the respective structures. One of the main objectives is also to identify the buildings that are highly vulnerable to damage caused from inadequate seismic performance-response. Hence, the damage scores obtained from the derived vulnerability functions will be used to categorize the evaluated buildings as “stabile”, “intermediate”, and “unstable”. The vulnerability functions are generated based on the basic damage inducing parameters, namely number of stories (S), lateral stiffness (LS), capacity curve of total building structure (CCBS), interstory drift (IS) and overhang ratio (OR).Keywords: vulnerability, ductility, seismic microzone, ductility, energy efficiency
Procedia PDF Downloads 40014892 Diagnosis of Static Eccentricity in 400 kW Induction Machine Based on the Analysis of Stator Currents
Authors: Saleh Elawgali
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Current spectrums of a four pole-pair, 400 kW induction machine were calculated for the cases of full symmetry and static eccentricity. The calculations involve integration of 93 electrical plus four mechanical ordinary differential equations. Electrical equations account for variable inductances affected by slotting and eccentricities. The calculations were followed by Fourier analysis of the stator currents in steady state operation. Zooms of the current spectrums, around the 50 Hz fundamental harmonic as well as of the main slot harmonic zone, were included. The spectrums included refer to both calculated and measured currents.Keywords: diagnostic, harmonic, induction machine, spectrum
Procedia PDF Downloads 51714891 Spatial Resilience of the Ageing Population in the Romanian Functional Urban Areas
Authors: Marinela Istrate, Ionel Muntele, Alexandru Bănică
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The authors propose the identification, analysis and prognosis of the quantitative and qualitative evolution of the elderly population in the functional urban areas. The present paper takes into account the analysis of some representative indicators (the weight of the elderly population, ageing index, dynamic index of economic ageing of productive population etc.) and the elaboration of an integrated indicator that would help differentiate the population ageing forms in the 48 functional urban areas that were defined based on demographic and social-economic criteria for all large and medium cities in Romania.Keywords: ageing, demographic transition, functional urban areas, spatial resilience
Procedia PDF Downloads 34714890 Department of Social Development/Japan International Cooperation Agency's Journey from South African Community to Southern African Region
Authors: Daisuke Sagiya, Ren Kamioka
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South Africa has ratified the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) on 30th November 2007. In line with this, the Department of Social Development (DSD) revised the White Paper on the Rights of Persons with Disabilities (WPRPD), and the Cabinet approved it on 9th December 2015. The South African government is striving towards the elimination of poverty and inequality in line with UNCRPD and WPRPD. However, there are minimal programmes and services that have been provided to persons with disabilities in the rural community. In order to address current discriminative practices, disunity and limited self-representation in rural community, DSD in cooperation with the Japan International Cooperation Agency (JICA) is implementing the 'Project for the Promotion of Empowerment of Persons with Disabilities and Disability Mainstreaming' from May 2016 to May 2020. The project is targeting rural community as the project sites, namely 1) Collins Chabane municipality, Vhembe district, Limpopo and 2) Maluti-a-Phofung municipality, Thabo Mofutsanyana district, Free State. The project aims at developing good practices on Community-Based Inclusive Development (CBID) at the project sites which will be documented as a guideline and applied in other provinces in South Africa and neighbouring countries (Lesotho, Swaziland, Botswana, Namibia, Zimbabwe, and Mozambique). In cooperation with provincial and district DSD and local government, the project is currently implementing various community activities, for example: Establishment of Self-Help Group (SHG) of persons with disabilities and Peer Counselling in the villages, and will conduct Disability Equality Training (DET) and accessibility workshop in order to enhance the CBID in the project sites. In order to universalise good practices on CBID, the authors will explain lessons learned from the project by utilising the theories of disability and development studies and community psychology such as social model of disability, twin-track approach, empowerment theory, sense of community, helper therapy principle, etc. And the authors conclude that in order to realise social participation of persons with disabilities in rural community, CBID is a strong tool and persons with disabilities must play central roles in all spheres of CBID activities.Keywords: community-based inclusive development, disability mainstreaming, empowerment of persons with disabilities, self-help group
Procedia PDF Downloads 22814889 Dielectric Properties of MWCNT-Muscovite/Epoxy Hybrid Composites
Authors: Nur Suraya Anis Ahmad Bakhtiar, Hazizan Md Akil
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In the present work, the dielectric properties of Epoxy/MWCNTs-muscovite HYBRID and MIXED composites based on ratio 30:70 were studies. The multi-wall carbon nanotubes (MWCNTs) were prepared by two method; (a) muscovite-MWCNTs hybrids were synthesized by chemical vapor deposition (CVD) and (b) physically mixing of muscovite with MWCNTs. The effect of different preparations of the composites and filler loading was evaluated. It is revealed that the dielectric constants of HYBRID epoxy composites are slightly higher compared to MIXED epoxy composites. It is also indicated that the dielectric constant increased by increases the MWCNTs filler loading.Keywords: muscovite, epoxy, dielectric properties, hybrid composite
Procedia PDF Downloads 64514888 Detonating Culture, Statistics and Development in Imo State of Nigeria
Authors: Ugiri Ejikeme
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In an executive summary, UNESCO describes Framework for Cultural Statistics as a tool for organizing cultural statistics both nationally and internationally. This is based on conceptual foundation and a common understanding of culture that will enable the measurement of a wide range of cultural expressions. This means therefore that cultural expression in whatever guise has the potentiality of contributing reasonably to the development of a given society. The paper looked into the various tangible and intangible cultures in Imo State of Nigeria. Due to government’s insensitivity, there is need to remind ourselves of the need to pay adequate attention to the cultural heritage bequeathed to us by our forefathers for the sake of posterity. Documenting this information in written form therefore becomes imperative. The study concludes that culture if developed, could reasonably contribute to economic and social growth of the society.Keywords: detonating culture, statistics and development, Imo State, Nigeria
Procedia PDF Downloads 47914887 Innovative Preparation Techniques: Boosting Oral Bioavailability of Phenylbutyric Acid Through Choline Salt-Based API-Ionic Liquids and Therapeutic Deep Eutectic Systems
Authors: Lin Po-Hsi, Sheu Ming-Thau
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Urea cycle disorders (UCD) are rare genetic metabolic disorders that compromise the body's urea cycle. Sodium phenylbutyrate (SPB) is a medication commonly administered in tablet or powder form to lower ammonia levels. Nonetheless, its high sodium content poses risks to sodium-sensitive UCD patients. This necessitates the creation of an alternative drug formulation to mitigate sodium load and optimize drug delivery for UCD patients. This study focused on crafting a novel oral drug formulation for UCD, leveraging choline bicarbonate and phenylbutyric acid. The active pharmaceutical ingredient-ionic liquids (API-ILs) and therapeutic deep eutectic systems (THEDES) were formed by combining these with choline chloride. These systems display characteristics like maintaining a liquid state at room temperature and exhibiting enhanced solubility. This in turn amplifies drug dissolution rate, permeability, and ultimately oral bioavailability. Incorporating choline-based phenylbutyric acid as a substitute for traditional SPB can effectively curtail the sodium load in UCD patients. Our in vitro dissolution experiments revealed that the ILs and DESs, synthesized using choline bicarbonate and choline chloride with phenylbutyric acid, surpassed commercial tablets in dissolution speed. Pharmacokinetic evaluations in SD rats indicated a notable uptick in the oral bioavailability of phenylbutyric acid, underscoring the efficacy of choline salt ILs in augmenting its bioavailability. Additional in vitro intestinal permeability tests on SD rats authenticated that the ILs, formulated with choline bicarbonate and phenylbutyric acid, demonstrate superior permeability compared to their sodium and acid counterparts. To conclude, choline salt ILs developed from choline bicarbonate and phenylbutyric acid present a promising avenue for UCD treatment, with the added benefit of reduced sodium load. They also hold merit in formulation engineering. The sustained-release capabilities of DESs position them favorably for drug delivery, while the low toxicity and cost-effectiveness of choline chloride signal potential in formulation engineering. Overall, this drug formulation heralds a prospective therapeutic avenue for UCD patients.Keywords: phenylbutyric acid, sodium phenylbutyrate, choline salt, ionic liquids, deep eutectic systems, oral bioavailability
Procedia PDF Downloads 10714886 A Study on Unix Process Crash Based on Efficient Process Management Method
Authors: Guo Haonan, Chen Peiyu, Zhao Hanyu, Burra Venkata Durga Kumar
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Unix and Unix-like operating systems are widely used due to their high stability but are limited by the parent-child process structure, and the child process depends on the parent process, so the crash of a single process may cause the entire process group or even the entire system to fail. Another possibility of unexpected process termination is that the system administrator inadvertently closed the terminal or pseudo-terminal where the application was launched, causing the application process to terminate unexpectedly. This paper mainly analyzes the reasons for the problems and proposes two solutions.Keywords: process management, daemon, login-bash and non-login bash, process group
Procedia PDF Downloads 12614885 Robust Half-Metallicity and Magnetic Properties of Cubic PrMnO3 Perovskite
Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad, T. Lantri, A. Zitouni
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The purpose of this study was to investigate the structural,electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3. It includes our calculations based on the use of the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, The spin polarized electronic band structures and densities of states aswellas the integer value of the magnetic moment of the unit cell (6 μB) illustrate that PrMnO3 is half-metallic ferromagnetic. The study shows that the robust half-metallicity makes the cubic PrMnO3 a promising candidate for application in spintronics.Keywords: Perovskite, DFT, electronic properties, Magnetic moment, half-metallic
Procedia PDF Downloads 45014884 Market Index Trend Prediction using Deep Learning and Risk Analysis
Authors: Shervin Alaei, Reza Moradi
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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks
Procedia PDF Downloads 14114883 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: cost prediction, machine learning, project management, random forest, neural networks
Procedia PDF Downloads 3614882 A CFD Analysis of Flow through a High-Pressure Natural Gas Pipeline with an Undeformed and Deformed Orifice Plate
Authors: R. Kiš, M. Malcho, M. Janovcová
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This work aims to present a numerical analysis of the natural gas which flows through a high-pressure pipeline and an orifice plate, through the use of CFD methods. The paper contains CFD calculations for the flow of natural gas in a pipe with different geometry used for the orifice plates. One of them has a standard geometry and a shape without any deformation and the other is deformed by the action of the pressure differential. It shows the behaviour of natural gas in a pipeline using the velocity profiles and pressure fields of the gas in both models with their differences. The entire research is based on the elimination of any inaccuracy which should appear in the flow of the natural gas measured in the high-pressure pipelines of the gas industry and which is currently not given in the relevant standard.Keywords: orifice plate, high-pressure pipeline, natural gas, CFD analysis
Procedia PDF Downloads 37414881 Turbulent Flow in Corrugated Pipes with Helical Grooves
Authors: P. Mendes, H. Stel, R. E. M. Morales
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This article presents a numerical and experimental study of turbulent flow in corrugated pipes with helically “d-type" grooves, for Reynolds numbers between 7500 and 100,000. The ANSYS-CFX software is used to solve the RANS equations with the BSL two equation turbulence model, through the element-based finite-volume method approach. Different groove widths and helix angles are considered. Numerical results are validated with experimental pressure drop measurements for the friction factor. A correlation for the friction factor is also proposed considering the geometric parameters and Reynolds numbers evaluated.Keywords: turbulent flow, corrugated pipe, helical, numerical, experimental, friction factor, correlation
Procedia PDF Downloads 47514880 Design and Implementation of Generative Models for Odor Classification Using Electronic Nose
Authors: Kumar Shashvat, Amol P. Bhondekar
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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.Keywords: odor classification, generative models, naive bayes, linear discriminant analysis
Procedia PDF Downloads 37814879 The Microstructural and Mechanical Characterization of Organo-Clay-Modified Bitumen, Calcareous Aggregate, and Organo-Clay Blends
Authors: A. Gürses, T. B. Barın, Ç. Doğar
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Bitumen has been widely used as the binder of aggregate in road pavement due to its good viscoelastic properties, as a viscous organic mixture with various chemical compositions. Bitumen is a liquid at high temperature and it becomes brittle at low temperatures, and this temperature-sensitivity can cause the rutting and cracking of the pavement and limit its application. Therefore, the properties of existing asphalt materials need to be enhanced. The pavement with polymer modified bitumen exhibits greater resistance to rutting and thermal cracking, decreased fatigue damage, as well as stripping and temperature susceptibility; however, they are expensive and their applications have disadvantages. Bituminous mixtures are composed of very irregular aggregates bound together with hydrocarbon-based asphalt, with a low volume fraction of voids dispersed within the matrix. Montmorillonite (MMT) is a layered silicate with low cost and abundance, which consists of layers of tetrahedral silicate and octahedral hydroxide sheets. Recently, the layered silicates have been widely used for the modification of polymers, as well as in many different fields. However, there are not too much studies related with the preparation of the modified asphalt with MMT, currently. In this study, organo-clay-modified bitumen, and calcareous aggregate and organo-clay blends were prepared by hot blending method with OMMT, which has been synthesized using a cationic surfactant (Cetyltrymethylammonium bromide, CTAB) and long chain hydrocarbon, and MMT. When the exchangeable cations in the interlayer region of pristine MMT were exchanged with hydrocarbon attached surfactant ions, the MMT becomes organophilic and more compatible with bitumen. The effects of the super hydrophobic OMMT onto the micro structural and mechanic properties (Marshall Stability and volumetric parameters) of the prepared blends were investigated. Stability and volumetric parameters of the blends prepared were measured using Marshall Test. Also, in order to investigate the morphological and micro structural properties of the organo-clay-modified bitumen and calcareous aggregate and organo-clay blends, their SEM and HRTEM images were taken. It was observed that the stability and volumetric parameters of the prepared mixtures improved significantly compared to the conventional hot mixes and even the stone matrix mixture. A micro structural analysis based on SEM images indicates that the organo-clay platelets dispersed in the bitumen have a dominant role in the increase of effectiveness of bitumen - aggregate interactions.Keywords: hot mix asphalt, stone matrix asphalt, organo clay, Marshall test, calcareous aggregate, modified bitumen
Procedia PDF Downloads 23414878 Design and Analysis of a New Dual-Band Microstrip Fractal Antenna
Authors: I. Zahraoui, J. Terhzaz, A. Errkik, El. H. Abdelmounim, A. Tajmouati, L. Abdellaoui, N. Ababssi, M. Latrach
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This paper presents a novel design of a microstrip fractal antenna based on the use of Sierpinski triangle shape, it’s designed and simulated by using FR4 substrate in the operating frequency bands (GPS, WiMAX), the design is a fractal antenna with a modified ground structure. The proposed antenna is simulated and validated by using CST Microwave Studio Software, the simulated results presents good performances in term of radiation pattern and matching input impedance.Keywords: dual-band antenna, fractal antenna, GPS band, modified ground structure, sierpinski triangle, WiMAX band
Procedia PDF Downloads 443