Search results for: strain approach
7495 Study on Discontinuity Properties of Phased-Array Ultrasound Transducer Affecting to Sound Pressure Fields Pattern
Authors: Tran Trong Thang, Nguyen Phan Kien, Trinh Quang Duc
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The phased-array ultrasound transducer types are utilities for medical ultrasonography as well as optical imaging. However, their discontinuity characteristic limits the applications due to the artifacts contaminated into the reconstructed images. Because of the effects of the ultrasound pressure field pattern to the echo ultrasonic waves as well as the optical modulated signal, the side lobes of the focused ultrasound beam induced by discontinuity of the phased-array ultrasound transducer might the reason of the artifacts. In this paper, a simple method in approach of numerical simulation was used to investigate the limitation of discontinuity of the elements in phased-array ultrasound transducer and their effects to the ultrasound pressure field. Take into account the change of ultrasound pressure field patterns in the conditions of variation of the pitches between elements of the phased-array ultrasound transducer, the appropriated parameters for phased-array ultrasound transducer design were asserted quantitatively.Keywords: phased-array ultrasound transducer, sound pressure pattern, discontinuous sound field, numerical visualization
Procedia PDF Downloads 4977494 Predicting Global Solar Radiation Using Recurrent Neural Networks and Climatological Parameters
Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar
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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error
Procedia PDF Downloads 4357493 A Review on Water Models of Surface Water Environment
Authors: Shahbaz G. Hassan
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Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.Keywords: empirical models, mathematical, statistical, water quality
Procedia PDF Downloads 2537492 Industrial Ecology Perspectives of Food Supply Chains: A Framework of Analysis
Authors: Luciano Batista, Sylvia Saes, Nuno Fouto, Liam Fassam
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This paper introduces the theoretical and methodological basis of an analytical framework conceived with the purpose of bringing industrial ecology perspectives into the core of the underlying disciplines supporting analyses in studies concerned with environmental sustainability aspects beyond the product cycle in a supply chain. Given the pressing challenges faced by the food sector, the framework focuses upon waste minimization through industrial linkages in food supply chains. The combination of industrial ecology practice with basic LCA elements, the waste hierarchy model, and the spatial scale of industrial symbiosis allows the standardization of qualitative analyses and associated outcomes. Such standardization enables comparative analysis not only between different stages of a supply chain, but also between different supply chains. The analytical approach proposed contributes more coherently to the wider circular economy aspiration of optimizing the flow of goods to get the most out of raw materials and cuts wastes to a minimum.Keywords: by-product synergy, food supply chain, industrial ecology, industrial symbiosis
Procedia PDF Downloads 4127491 Determination of Water Pollution and Water Quality with Decision Trees
Authors: Çiğdem Bakır, Mecit Yüzkat
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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.Keywords: decision tree, water quality, water pollution, machine learning
Procedia PDF Downloads 767490 On the Bootstrap P-Value Method in Identifying out of Control Signals in Multivariate Control Chart
Authors: O. Ikpotokin
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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics
Procedia PDF Downloads 3427489 Estimation of the Upper Tail Dependence Coefficient for Insurance Loss Data Using an Empirical Copula-Based Approach
Authors: Adrian O'Hagan, Robert McLoughlin
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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient
Procedia PDF Downloads 2807488 Modeling Electrical Properties of Hetero-Junction-Graphene/Pentacene and Gold/Pentacene
Authors: V. K. Lamba, Abhinandan Bharti
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We investigate the electronic transport properties across the graphene/ pentacene and gold/pentacene interface. Further, we studied the effect of ripples/bends in pentacene using NEGF-DFT approach. Current transport across the pentacene/graphene interface is found to be remarkably different from transport across pentacene/Gold interfaces. We found that current across these interfaces could be accurately modeled by a combination of thermionic and Poole–Frenkel emission. Further, the degree of bend or degrees of the curve formed during ripple formation strongly change the optimized geometric structures, charge distributions, energy bands, and DOS. The misorientation and hybridization of carbon orbitals are associated with a variation in bond lengths and carrier densities, and are the causes of the dramatic changes in the electronic structure during ripple formation. The electrical conductivity decreases with increase in curvature during ripple formation or due to bending of pentacene molecule and a decrease in conductivity is directly proportional to the increase in curvature angle and given by quadratic relation.Keywords: hetero-junction, grapheme, NEGF-DFT, pentacene, gold/pentacene
Procedia PDF Downloads 2277487 The Role of the Internal Audit Unit in Detecting and Preventing Fraud at Public Universities in West Java, Indonesia
Authors: Fury Khristianty Fitriyah
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This study aims to identify the extent of the role of the Satuan Pengawas Intern (Internal Audit Unit) in detecting and preventing fraud in public universities in West Java under the Ministry of Research, Technology and Higher Education. The research method applied was a qualitative case study approach, while the unit of analysis for this study is the Internal Audit Unit at each public university. Results of this study indicate that the Internal Audit Unit is able to detect and prevent fraud within a public university environment by means of red flags to mark accounting anomalies. These stem from inaccurate budget planning that prompts inappropriate use of funds, exacerbated by late disbursements of funds, which potentially lead to fictitious transactions, and discrepancies in recording state-owned assets into a state property management system (SIMAK BMN), which, if not conducted properly, potentially causes loss to the state.Keywords: governance, internal control, fraud, public university
Procedia PDF Downloads 2777486 Numerical Model for Investigation of Recombination Mechanisms in Graphene-Bonded Perovskite Solar Cells
Authors: Amir Sharifi Miavaghi
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It is believed recombination mechnisms in graphene-bonded perovskite solar cells based on numerical model in which doped-graphene structures are employed as anode/cathode bonding semiconductor. Moreover, the dark-light current density-voltage density-voltage curves are investigated by regression analysis. Loss mechanisms such as back contact barrier, deep surface defect in the adsorbent layer is determined by adapting the simulated cell performance to the measurements using the differential evolution of the global optimization algorithm. The performance of the cell in the connection process includes J-V curves that are examined at different temperatures and open circuit voltage (V) under different light intensities as a function of temperature. Based on the proposed numerical model and the acquired loss mechanisms, our approach can be used to improve the efficiency of the solar cell further. Due to the high demand for alternative energy sources, solar cells are good alternatives for energy storage using the photovoltaic phenomenon.Keywords: numerical model, recombination mechanism, graphen, perovskite solarcell
Procedia PDF Downloads 617485 An Overview of College English Writing Teaching Studies in China Between 2002 and 2022: Visualization Analysis Based on CiteSpace
Authors: Yang Yiting
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This paper employs CiteSpace to conduct a visualiazation analysis of literature on college English writing teaching researches published in core journals from the CNKI database and CSSCI journals between 2002 and 2022. It aims to explore the characteristics of researches and future directions on college English writing teaching. The present study yielded the following major findings: the field primarily focuses on innovative writing teaching models and methods, the integration of traditional classroom teaching and information technology, and instructional strategies to enhance students' writing skills. The future research is anticipated to involve a hybrid writing teaching approach combining online and offline teaching methods, leveraging the "Internet+" digital platform, aiming to elevate students' writing proficiency. This paper also presents a prospective outlook for college English writing teaching research in China.Keywords: citespace, college English, writing teaching, visualization analysis
Procedia PDF Downloads 647484 Comparative study of the technical efficiency of the cotton farms in the towns of Banikoara and Savalou
Authors: Boukari Abdou Wakilou
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Benin is one of West Africa's major cotton-producing countries. Cotton is the country's main source of foreign currency and employment. But it is also one of the sources of soil degradation. The search for good agricultural practices is therefore, a constant preoccupation. The aim of this study is to measure the technical efficiency of cotton growers by comparing those who constantly grow cotton on the same land with those who practice crop rotation. The one-step estimation approach of the stochastic production frontier, including determinants of technical inefficiency, was applied to a stratified random sample of 261 cotton producers. Overall, the growers had a high average technical efficiency level of 90%. However, there was no significant difference in the level of technical efficiency between the two groups of growers studied. All the factors linked to compliance with the technical production itinerary had a positive influence on the growers' level of efficiency. It is, therefore, important to continue raising awareness of the importance of respecting the technical production itinerary and of integrated soil fertility management techniques.Keywords: technical efficiency, soil fertility, cotton, crop rotation, benin
Procedia PDF Downloads 527483 Synthesis of Silver Nanoparticle: An Analytical Method Based Approach for the Quantitative Assessment of Drug
Authors: Zeid A. Alothman
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Silver nanoparticle (AgNP) has been synthesized using adrenaline. Adrenaline readily undergoes an autoxidation reaction in an alkaline medium with the dissolved oxygen to form adrenochrome, thus behaving as a mild reducing agent for the dissolved oxygen. This reducing behavior of adrenaline when employed to reduce Ag(+) ions yielded a large enhancement in the intensity of absorbance in the visible region. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) studies have been performed to confirm the surface morphology of AgNPs. Further, the metallic nanoparticles with size greater than 2 nm caused a strong and broad absorption band in the UV-visible spectrum called surface plasmon band or Mie resonance. The formation of AgNPs caused the large enhancement in the absorbance values with λmax at 436 nm through the excitation of the surface plasmon band. The formation of AgNPs was adapted to for the quantitative assessment of adrenaline using spectrophotometry with lower detection limit and higher precision values.Keywords: silver nanoparticle, adrenaline, XRD, TEM, analysis
Procedia PDF Downloads 2047482 Micro-Study of Dissimilar Welded Materials
Authors: Ezzeddin Anawa, Abdol-Ghane Olabi
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The dissimilar joint between aluminum /titanium alloys (Al 6082 and Ti G2) alloys were successfully achieved by CO2 laser welding with a single pass and without filler material using the overlap joint design. Laser welding parameters ranges combinations were experimentally determined using Taguchi approach with the objective of producing welded joint with acceptable welding profile and high quality of mechanical properties. In this study a joining of dissimilar Al 6082 / Ti G2 was result in three distinct regions fusion area (FA), heat-affected zone (HAZ), and the unaffected base metal (BM) in the weldment. These regions are studied in terms of its microstructural characteristics and microhardness which are directly affecting the welding quality. The weld metal was mainly composed of martensite alpha prime. In two different metals in the two different sides of joint HAZ, grain growth was detected. The microhardness of the joint distribution also has shown microhardness increasing in the HAZ of two base metals and a varying microhardness in fusion zone.Keywords: microharness , microstructure, laser welding and dissimilar jointed materials.
Procedia PDF Downloads 3727481 Innovative Textile Design Using in-situ Ag NPs incorporation into Natural Fabric Matrix
Authors: M. Rehan, H. Mashaly, H. Emam, A. Abou El-Kheir, S. Mowafi
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In this work, we will study a simple highly efficient technique to impart multi functional properties to different fabric substrates by in situ Ag NPs incorporation into fabric matrix. Ag NPs as a coloration and antimicrobial agent were prepared in situ incorporation into fabric matrix (Cotton and Wool) by using trisodium citrate as reducing and stabilizing agent. The Ag NPs treated fabric (Cotton and Wool) showed different color because of localized surface Plasmon resonance (LSPR) property of Ag NPs. The formation of Ag NPs was confirmed by UV/Vis spectra for the supernatant solutions and The Ag NPs treated fabric (Cotton and Wool) were characterized by scanning electron microscopy (SEM) and X-ray photo electron spectroscopy (XPS). The dependence of color properties characterized by colorimetric, fastness and antibacterial properties evaluated by Escherichia coli using counting method and the reaction parameters were studied. The results indicate that, the in situ Ag NPs incorporation into fabric matrix approach can simultaneously impart colorant and antimicrobial properties into different fabric substrates.Keywords: Ag NPs, coloration, antibacterial, wool, cotton fabric
Procedia PDF Downloads 3527480 Spectral Anomaly Detection and Clustering in Radiological Search
Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk
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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.Keywords: radiological search, radiological mapping, radioactivity, radiation protection
Procedia PDF Downloads 6887479 Optimization of Perfusion Distribution in Custom Vascular Stent-Grafts Through Patient-Specific CFD Models
Authors: Scott M. Black, Craig Maclean, Pauline Hall Barrientos, Konstantinos Ritos, Asimina Kazakidi
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Aortic aneurysms and dissections are leading causes of death in cardiovascular disease. Both inevitably lead to hemodynamic instability without surgical intervention in the form of vascular stent-graft deployment. An accurate description of the aortic geometry and blood flow in patient-specific cases is vital for treatment planning and long-term success of such grafts, as they must generate physiological branch perfusion and in-stent hemodynamics. The aim of this study was to create patient-specific computational fluid dynamics (CFD) models through a multi-modality, multi-dimensional approach with boundary condition optimization to predict branch flow rates and in-stent hemodynamics in custom stent-graft configurations. Three-dimensional (3D) thoracoabdominal aortae were reconstructed from four-dimensional flow-magnetic resonance imaging (4D Flow-MRI) and computed tomography (CT) medical images. The former employed a novel approach to generate and enhance vessel lumen contrast via through-plane velocity at discrete, user defined cardiac time steps post-hoc. To produce patient-specific boundary conditions (BCs), the aortic geometry was reduced to a one-dimensional (1D) model. Thereafter, a zero-dimensional (0D) 3-Element Windkessel model (3EWM) was coupled to each terminal branch to represent the distal vasculature. In this coupled 0D-1D model, the 3EWM parameters were optimized to yield branch flow waveforms which are representative of the 4D Flow-MRI-derived in-vivo data. Thereafter, a 0D-3D CFD model was created, utilizing the optimized 3EWM BCs and a 4D Flow-MRI-obtained inlet velocity profile. A sensitivity analysis on the effects of stent-graft configuration and BC parameters was then undertaken using multiple stent-graft configurations and a range of distal vasculature conditions. 4D Flow-MRI granted unparalleled visualization of blood flow throughout the cardiac cycle in both the pre- and postsurgical states. Segmentation and reconstruction of healthy and stented regions from retrospective 4D Flow-MRI images also generated 3D models with geometries which were successfully validated against their CT-derived counterparts. 0D-1D coupling efficiently captured branch flow and pressure waveforms, while 0D-3D models also enabled 3D flow visualization and quantification of clinically relevant hemodynamic parameters for in-stent thrombosis and graft limb occlusion. It was apparent that changes in 3EWM BC parameters had a pronounced effect on perfusion distribution and near-wall hemodynamics. Results show that the 3EWM parameters could be iteratively changed to simulate a range of graft limb diameters and distal vasculature conditions for a given stent-graft to determine the optimal configuration prior to surgery. To conclude, this study outlined a methodology to aid in the prediction post-surgical branch perfusion and in-stent hemodynamics in patient specific cases for the implementation of custom stent-grafts.Keywords: 4D flow-MRI, computational fluid dynamics, vascular stent-grafts, windkessel
Procedia PDF Downloads 1697478 Uncertainty Estimation in Neural Networks through Transfer Learning
Authors: Ashish James, Anusha James
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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.Keywords: uncertainty estimation, neural networks, transfer learning, regression
Procedia PDF Downloads 1237477 Knowledge Management Challenges within Traditional Procurement System
Authors: M. Takhtravanchi, C. Pathirage
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In the construction industry, project members are conveyor of project knowledge which is, often, not managed properly to be used in future projects. As construction projects are temporary and unique, project members are willing to be recruited once a project is completed. Therefore, poor management of knowledge across construction projects will lead to a considerable amount of knowledge loss; the ignoring of which would be detrimental to project performance. This issue is more prominent in projects undertaken through the traditional procurement system, as this system does not incentives project members for integration. Thus, disputes exist between the design and construction phases based on the poor management of knowledge between those two phases. This paper aims to highlight the challenges of the knowledge management that exists within the traditional procurement system. Expert interviews were conducted and challenges were identified and analysed by the Interpretive Structural Modelling (ISM) approach in order to summarise the relationships among them. Two identified key challenges are the Culture of an Organisation and Knowledge Management Policies. A knowledge of the challenges and their relationships will help project manager and stakeholders to have a better understanding of the importance of knowledge management.Keywords: challenges, construction industry, knowledge management, traditional procurement system
Procedia PDF Downloads 4247476 An Improved Amplified Sway Method for Semi-Rigidly Jointed Sway Frames
Authors: Abdul Hakim Chikho
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A simple method of calculating satisfactory of the effect of instability on the distribution of in-plane bending moments in unbraced semi-rigidly multistory steel framed structures is presented in this paper. This method, which is a modified form of the current amplified sway method of BS5950: part1:2000, uses an approximate load factor at elastic instability in each storey of a frame which in turn dependent up on the axial loads acting in the columns. The calculated factors are then used to represent the geometrical deformations due to the presence of axial loads, acting in that storey. Only a first order elastic analysis is required to accomplish the calculation. Comparison of the prediction of the proposed method and the current BS5950 amplified sway method with an accurate second order elastic computation shows that the proposed method leads to predictions which are markedly more accurate than the current approach of BS5950.Keywords: improved amplified sway method, steel frames, semi-rigid connections, secondary effects
Procedia PDF Downloads 837475 A Reliable Multi-Type Vehicle Classification System
Authors: Ghada S. Moussa
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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm
Procedia PDF Downloads 3507474 Deployed Confidence: The Testing in Production
Authors: Shreya Asthana
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Testers know that the feature they tested on stage is working perfectly in production only after release went live. Sometimes something breaks in production and testers get to know through the end user’s bug raised. The panic mode starts when your staging test results do not reflect current production behavior. And you started doubting your testing skills when finally the user reported a bug to you. Testers can deploy their confidence on release day by testing on production. Once you start doing testing in production, you will see test result accuracy because it will be running on real time data and execution will be a little faster as compared to staging one due to elimination of bad data. Feature flagging, canary releases, and data cleanup can help to achieve this technique of testing. By this paper it will be easier to understand the steps to achieve production testing before making your feature live, and to modify IT company’s testing procedure, so testers can provide the bug free experience to the end users. This study is beneficial because too many people think that testing should be done in staging but not in production and now this is high time to pull out people from their old mindset of testing into a new testing world. At the end of the day, it all just matters if the features are working in production or not.Keywords: bug free production, new testing mindset, testing strategy, testing approach
Procedia PDF Downloads 657473 Network Connectivity Knowledge Graph Using Dwave Quantum Hybrid Solvers
Authors: Nivedha Rajaram
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Hybrid Quantum solvers have been given prime focus in recent days by computation problem-solving domain industrial applications. D’Wave Quantum Computers are one such paragon of systems built using quantum annealing mechanism. Discrete Quadratic Models is a hybrid quantum computing model class supplied by D’Wave Ocean SDK - a real-time software platform for hybrid quantum solvers. These hybrid quantum computing modellers can be employed to solve classic problems. One such problem that we consider in this paper is finding a network connectivity knowledge hub in a huge network of systems. Using this quantum solver, we try to find out the prime system hub, which acts as a supreme connection point for the set of connected computers in a large network. This paper establishes an innovative problem approach to generate a connectivity system hub plot for a set of systems using DWave ocean SDK hybrid quantum solvers.Keywords: quantum computing, hybrid quantum solver, DWave annealing, network knowledge graph
Procedia PDF Downloads 1187472 Systematic Review of Quantitative Risk Assessment Tools and Their Effect on Racial Disproportionality in Child Welfare Systems
Authors: Bronwen Wade
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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality
Procedia PDF Downloads 467471 A Thermal Analysis Based Approach to Obtain High Carbonaceous Fibers from Chicken Feathers
Authors: Y. Okumuş, A. Tuna, A. T. Seyhan, H. Çelebi
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Useful carbon fibers were derived from chicken feathers (PCFs) based on a two-step pyrolysis method. The collected PCFs were cleaned and categorized as black, white and brown. Differential scanning calorimeter (DSC) and thermo-gravimetric analyzer (TGA) were systemically used to design the pyrolysis steps. Depending on colors, feathers exhibit different glass transition (Tg) temperatures. Long-time heat treatment applied to the feathers emerged influential on the surface quality of the resulting carbon fibers. Fourier Transformation Infrared (FTIR) examination revealed that the extent of disulfide bond cleavage is highly associated with the feather melting stability. Scanning electron microscopy (SEM) examinations were employed to evaluate the morphological changes of feathers after pyrolysis. Of all, brown feathers were found to be the most promising to turn into useful carbon fibers without any trace of melting and shape distortion when pyrolysis was carried out at 230°C for 24 hours and at 450°C for 1 hour.Keywords: poultry chicken feather, keratin protein fiber, pyrolysis, high carbonaceous fibers
Procedia PDF Downloads 3227470 Recruitment Strategies and Migration Regulations for International Students in the United States and Canada: A Comparative Study
Authors: Aynur Charkasova
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The scientific and economic contributions of international students cannot be underestimated. International education continues to be a competitive global industry, and many countries are seeking to recruit the best and the brightest to reinforce scientific innovations, boost intercultural learning, and bring more funding to universities and colleges. Substantial changes in international educational policies and migration regulations have been made in the hopes of recruiting global talent. This paper explores and compares recruitment strategies, employment opportunities, and a legal path to permanent residency policies related to international students in the United States of America and Canada. This study will utilize the legal information available from the government websites of both countries and peer-reviewed scholarly articles and will highlight which approach promises a better path in recruiting and retention of international students. The findings from the study will be discussed and recommendations will be provided.Keywords: International students, current immigration policies, STEM, employability, visa reforms for international students, Canadian recruitment policy
Procedia PDF Downloads 707469 An AFM Approach of RBC Micro and Nanoscale Topographic Features During Storage
Authors: K. Santacruz-Gomez, E. Silva-Campa, S. Álvarez-García, V. Mata-Haro, D. Soto-Puebla, M. Pedroza-Montero
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Blood gamma irradiation is the only available method to prevent transfusion-associated graft versus host disease (TA-GVHD). However, when blood is irradiated, determine blood shelf time is crucial. Non-irradiated blood has a self-time from 21 to 35 days when is preserved with an anticoagulated solution and stored at 4°C. During their storage, red blood cells (RBC) undergo a series of biochemical, biomechanical and molecular changes involving what is known as storage lesion (SL). SL include loss of structural integrity of RBC, a decrease of 2,3-diphosphatidylglyceric acid levels, and an increase of both ion potassium concentration and hemoglobin (Hb). On the other hand, Atomic force Microscopy (AFM) represents a versatile tool for a nano-scale high-resolution topographic analysis in biological systems. In order to evaluate SL in irradiated and non-irradiated blood, RBC topography and morphometric parameters were obtained from an AFM XE-BIO system. Cell viability was followed using flow cytometry. Our results showed that early markers as nanoscale roughness, allow us to evaluate blood quality since another perspective.Keywords: AFM, blood γ-irradiation, roughness, storage lesion
Procedia PDF Downloads 5257468 Uncertainty Analysis of a Hardware in Loop Setup for Testing Products Related to Building Technology
Authors: Balasundaram Prasaant, Ploix Stephane, Delinchant Benoit, Muresan Cristian
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Hardware in Loop (HIL) testing is done to test and validate a particular product especially in building technology. When it comes to building technology, it is more important to test the products for their efficiency. The test rig in the HIL simulator may contribute to some uncertainties on measured efficiency. The uncertainties include physical uncertainties and scenario-based uncertainties. In this paper, a simple uncertainty analysis framework for an HIL setup is shown considering only the physical uncertainties. The entire modeling of the HIL setup is done in Dymola. The uncertain sources are considered based on available knowledge of the components and also on expert knowledge. For the propagation of uncertainty, Monte Carlo Simulation is used since it is the most reliable and easy to use. In this article it is shown how an HIL setup can be modeled and how uncertainty propagation can be performed on it. Such an approach is not common in building energy analysis.Keywords: energy in buildings, hardware in loop testing, modelica modelling, Monte Carlo simulation, uncertainty propagation
Procedia PDF Downloads 1287467 Eco-City Planning and Urban Design in Lagos, Nigeria: Recent Innovations, Trends, Concerns, Challenges, and Solutions
Authors: Dahunsi Michael Oluseyi
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This paper aims to extensively examine eco-city planning and urban design in Lagos, Nigeria. It will delve into the city's developments, challenges, and potential solutions to offer insights for sustainable urban growth within the rapidly expanding urban landscape. The research will scrutinize recent innovations, emerging trends, and practical remedies to promote ecological sustainability within an urban framework. It will encompass a more in-depth review of current literature, case studies, and qualitative analyses, thereby augmenting the depth and breadth of the research. The objectives are to assess the current eco-city planning initiatives and urban design trends in Lagos, Nigeria, considering the city's unique characteristics and challenges. To identify and analyze the challenges encountered during the implementation of eco-friendly urban developments in Lagos, to explore and evaluate the innovative and practical solutions that are implemented to promote sustainability within the city, to provide comprehensive insights and actionable recommendations for policymakers, urban planners, and other stakeholders involved in sustainable urban development in Lagos, the rapid urbanization of Lagos has brought forth a myriad of challenges, including a burgeoning population, inadequate infrastructure, waste management issues, and environmental pollution. Eco-city planning has emerged as a promising approach to addressing these obstacles, striving to create urban spaces that are more habitable, resource-efficient, and environmentally friendly. This research holds substantial importance in exploring the application of eco-city planning principles within a megacity like Lagos. Analyzing recent innovations, trends, concerns, challenges, and solutions provides invaluable insights for policymakers, urban planners, and stakeholders dedicated to fostering sustainable urban development. The methodologies employed in this research are structured to embrace a multifaceted and intricate approach, aiming to facilitate a comprehensive understanding of the complexities inherent in eco-city planning and urban design in Lagos, Nigeria. This methodological framework is designed to encompass various diverse strategies and analytical tools to effectively capture the multidimensional aspects of sustainable urban development. It involves an in-depth analysis of academic publications, governmental reports, and urban planning documents to highlight global eco-city planning trends and gather Lagos-specific insights through a detailed exploration of eco-friendly initiatives and projects in Lagos to evaluate successes, challenges, and strategies for addressing environmental concerns by engaging key stakeholders, including urban planners, policymakers, environmental experts, and residents, to collect firsthand perspectives, concerns, and insights. Also, a thorough analysis will be carried out on data collected from literature reviews, case studies, interviews, and surveys used to extract prevalent patterns, challenges, and innovative solutions from diverse sources. This study aims to contribute to the discourse on sustainable urban development by offering a comprehensive analysis of eco-city planning in Lagos and providing practical recommendations for a more sustainable urban future.Keywords: eco-friendly, innovation, sustainability, stakeholders
Procedia PDF Downloads 547466 Bridging Minds, Building Success Beyond Metrics: Uncovering Human Influence on Project Performance: Case Study of University of Salford
Authors: David Oyewumi Oyekunle, David Preston, Florence Ibeh
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The paper provides an overview of the impacts of the human dimension in project management and team management on projects, which is increasingly affecting the performance of organizations. Recognizing its crucial significance, the research focuses on analyzing the psychological and interpersonal dynamics within project teams. This research is highly significant in the dynamic field of project management, as it addresses important gaps and offers vital insights that align with the constantly changing demands of the profession. A case study was conducted at the University of Salford to examine how human activity affects project management and performance. The study employed a mixed methodology to gain a deeper understanding of the real-world experiences of the subjects and project teams. Data analysis procedures to address the research objectives included the deductive approach, which involves testing a clear hypothesis or theory, as well as descriptive analysis and visualization. The survey comprised a sample size of 40 participants out of 110 project management professionals, including staff and final students in the Salford Business School, using a purposeful sampling method. To mitigate bias, the study ensured diversity in the sample by including both staff and final students. A smaller sample size allowed for more in-depth analysis and a focused exploration of the research objective. Conflicts, for example, are intricate occurrences shaped by a multitude of psychological stimuli and social interactions and may have either a deterrent perspective or a positive perspective on project performance and project management productivity. The study identified conflict elements, including culture, environment, personality, attitude, individual project knowledge, team relationships, leadership, and team dynamics among team members, as crucial human activities to minimize conflict. The findings are highly significant in the dynamic field of project management, as they address important gaps and offer vital insights that align with the constantly changing demands of the profession. It provided project professionals with valuable insights that can help them create a collaborative and high-performing project environment. Uncovering human influence on project performance, effective communication, optimal team synergy, and a keen understanding of project scope are necessary for the management of projects to attain exceptional performance and efficiency. For the research to achieve the aims of this study, it was acknowledged that the productive dynamics of teams and strong group cohesiveness are crucial for effectively managing conflicts in a beneficial and forward-thinking manner. Addressing the identified human influence will contribute to a more sustainable project management approach and offer opportunities for exploration and potential contributions to both academia and practical project management.Keywords: human dimension, project management, team dynamics, conflict resolution
Procedia PDF Downloads 88