Search results for: weighted routing algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4219

Search results for: weighted routing algorithm

1729 Microbiota Associated With the Larval Culture of Red Cusk Eel Genipterus Chilensis in Chile

Authors: Luz Hurtado, Rodrigo Rojas, Jaime Romero, Christopher Concha

Abstract:

The culture of the marine fish red cusk eel Genypterus chilensis is currently considered a priority for Chilean aquaculture which is a Chilean native species of high gastronomic demand and market value. The microbiota was analyzed in terms of diversity and structure using massive Illumina sequencing. The analysis of alpha diversity was performed in samples of G. chilensis larvae of 6, 18 and 32 dph (days post-hatching) and it was observed that there were significant differences (P = 0.05) between the days of culture for the Chao1 index, being the larvae of 18 dph the one with the highest index followed by the larvae of 6 dph, The lowest value for this index was presented in larvae of 32 dph. There were no significant differences in larvae between the days of culture for the Shannon (P=0.0857) and Simpson (P=0.0714) indices. In general, the larvae of G. chilensis have high rates of diversity. When analyzing the beta diversity, a differentiation between the bacterial communities is observed depending on the day of the culture of the larvae. Considering the PCoA elaborated from the unweighted UniFrac statistic, the explained variance was 46.2% (PC1 29.2% and PC2 17.0%) and in the case of the PCoA elaborated with the weighted UniFrac statistic; the explained variance was 65.5% (PC1 41.8% and PC2 23.7%) these differences were significant based on the Permanova statistical analysis (P= 0.002 and 0.037 respectively). When analyzing the taxonomic composition of the microbiota of the larvae in the different days of culture it was observed that at the phyla level the most abundant in the larvae of 6 dph were Proteobacteria (57%) Verrucomicrobia (24%) and Firmicutes (14%), for the larvae of 18 dph the predominant phyla were Proteobacteria (90%), Dependientiae (5%), Actinobacteria (2%) and Plactomyces (2%), for the larvae of 32 dph the phyla that presented the highest relative abundance were Proteobacteria (57%), Firmicutes (29%), Verrucomicrobia (5%) and Actinobacteria (5%), when comparing the larvae between the days it was observed that the phylum Proteobacteria was the most abundant in the samples of larvae of 6, 18 and 32 dph being the larvae of 18 dph those that present the highest relative abundance, the larvae of 6 dph were those that presented the highest relative abundance for the phylum Verrucomicrobia and in the larvae of 32 dph was observed greater abundance of the phylum Firmicutes compared to the other days of larval culture. At the level of genera, those with the highest relative abundance in larvae of 6 dph were Rubritalea (30%), Psychrobacter (28%), staphylococcus (17%) and Ralstonia (10%), for the larvae of 18 dph the genera with the highest abundance were Psychrobacter (47%), Litoreibacter (13%), Nautella (9%) and Cohesibacter (8%), for the larvae of 32 dph the most abundant genera were Alloiococcus (25%), Dialister (14%), Neptunomonas (13%) and Piscirickettsia (11%). When observing the taxonomic composition of the larvae between the days of larval culture, it is observed that there are differences between them.

Keywords: microbiota, diversity, G. Chilensis, larvae

Procedia PDF Downloads 69
1728 Numerical Study of a Nanofluid in a Truncated Cone

Authors: B. Mahfoud, A. Bendjaghlouli

Abstract:

Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

Procedia PDF Downloads 305
1727 Evaluation of Different Waste Management Planning Strategies in an Industrial City

Authors: Leila H. Khiabani, Mohammadreza Vafaee, Farshad Hashemzadeh

Abstract:

Industrial waste management regulates different stages of production, storage, transfer, recycling and waste disposal. There are several common practices for industrial waste management. However, due to various local health, economic, social, environmental and aesthetic considerations, the most optimal principles and measures often vary at each specific industrial zone. In addition, waste management strategies are heavily impacted by local administrative, legal, and financial regulations. In this study, a hybrid qualitative and quantitative research methodology has been designed for waste management planning in an industrial city. Firstly, following a qualitative research methodology, the most relevant waste management strategies for the specific industrial city were identified through interviews with environmental planning and waste management experts. Forty experts participated in this study. Alborz industrial city in Iran, which hosts more than one thousand industrial units in nine hundred acres, was chosen as the sample industrial city in this study. The findings from the expert interviews at the first phase were then used to design a quantitative questionnaire for the second phase of the study. The aim of the questionnaire was to quantify the relative impact of different waste management strategies in the sample industrial city. Eight waste management strategies and three implementation policies were included in the questionnaire. The experts were asked to rank the relative effectiveness of each strategy for environmental planning of the sample industrial city. They were also asked to rank the relative effectiveness of each planning policy on each of the waste management strategies. In the end, the weighted average of all the responses was calculated to identify the most effective waste management strategy and planning policies for the sample industrial city. The results suggested that among the eight suggested waste management strategies, industrial composting is the most effective (31%) strategy based on the collective evaluation of the local expert. Additionally, the results suggested that the most effective policy (58%) in the city’s environmental planning is to reduce waste generation by prolonging the effective life of industrial products using higher quality and recyclable materials. These findings can provide useful expert guidelines for prioritization between different waste management strategies in the city’s overall environmental planning roadmap. The findings may also be applicable to similar industrial cities. In addition, a similar methodology can be utilized in the environmental planning of other industrial cities.

Keywords: environmental planning, industrial city, quantitative research, waste management

Procedia PDF Downloads 129
1726 Policy Guidelines to Enhance the Mathematics Teachers’ Association of the Philippines (MTAP) Saturday Class Program

Authors: Roselyn Alejandro-Ymana

Abstract:

The study was an attempt to assess the MTAP Saturday Class Program along its eight components namely, modules, instructional materials, scheduling, trainer-teachers, supervisory support, administrative support, financial support and educational facilities, the results of which served as bases in developing policy guidelines to enhance the MTAP Saturday Class Program. Using a descriptive development method of research, this study involved the participation of twenty-eight (28) schools with MTAP Saturday Class Program in the Division of Dasmarinas City where twenty-eight school heads, one hundred twenty-five (125) teacher-trainer, one hundred twenty-five (125) pupil program participants, and their corresponding one hundred twenty-five (125) parents were purposively drawn to constitute the study’s respondent. A self-made validated survey questionnaire together with Pre and Post-Test Assessment Test in Mathematics for pupils participating in the program, and an unstructured interview guide was used to gather the data needed in the study. Data obtained from the instruments administered was organized and analyzed through the use of statistical tools that included the Mean, Weighted Mean, Relative Frequency, Standard Deviation, F-Test or One-Way ANOVA and the T-Test. Results of the study revealed that all the eight domains involved in the MTAP Saturday Class Program were practiced with the areas of 'trainer-teachers', 'educational facilities', and 'supervisory support' identified as the program’s strongest components while the areas of 'financial support', 'modules' and 'scheduling' as being the weakest program’s components. Moreover, the study revealed based on F-Test, that there was a significant difference in the assessment made by the respondents in each of the eight (8) domains. It was found out that the parents deviated significantly from the assessment of either the school heads or the teachers on the indicators of the program. There is much to be desired when it comes to the quality of the implementation of the MTAP Saturday Class Program. With most of the indicators of each component of the program, having received overall average ratings that were at least 0.5 point away from the ideal rating 5 for total quality, school heads, teachers, and supervisors need to work harder for total quality of the implementation of the MTAP Saturday Class Program in the division.

Keywords: mathematics achievement, MTAP program, policy guidelines, program assessment

Procedia PDF Downloads 209
1725 RAPD Analysis of Genetic Diversity of Castor Bean

Authors: M. Vivodík, Ž. Balážová, Z. Gálová

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The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.

Keywords: dendrogram, polymorphism, RAPD technique, Ricinus communis L.

Procedia PDF Downloads 467
1724 Multi Objective Near-Optimal Trajectory Planning of Mobile Robot

Authors: Amar Khoukhi, Mohamed Shahab

Abstract:

This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

Procedia PDF Downloads 364
1723 Compensatory Neuro-Fuzzy Inference (CNFI) Controller for Bilateral Teleoperation

Authors: R. Mellah, R. Toumi

Abstract:

This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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1722 Design of a Drift Assist Control System Applied to Remote Control Car

Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

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1721 RNA-Seq Analysis of Coronaviridae Family and SARS-Cov-2 Prediction Using Proposed ANN

Authors: Busra Mutlu Ipek, Merve Mutlu, Ahmet Mutlu

Abstract:

Novel coronavirus COVID-19, which has recently influenced the world, poses a great threat to humanity. In order to overcome this challenging situation, scientists are working on developing effective vaccine against coronavirus. Many experts and researchers have also produced articles and done studies on this highly important subject. In this direction, this special topic was chosen for article to make a contribution to this area. The purpose of this article is to perform RNA sequence analysis of selected virus forms in the Coronaviridae family and predict/classify SARS-CoV-2 (COVID-19) from other selected complete genomes in coronaviridae family using proposed Artificial Neural Network(ANN) algorithm.

Keywords: Coronaviridae family, COVID-19, RNA sequencing, ANN, neural network

Procedia PDF Downloads 141
1720 A Clinician’s Perspective on Electroencephalography Annotation and Analysis for Driver Drowsiness Estimation

Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

Abstract:

Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

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1719 Residual Life Prediction for a System Subject to Condition Monitoring and Two Failure Modes

Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

Procedia PDF Downloads 412
1718 Bayesian Analysis of Change Point Problems Using Conditionally Specified Priors

Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

Procedia PDF Downloads 184
1717 Identification and Optimisation of South Africa's Basic Access Road Network

Authors: Diogo Prosdocimi, Don Ross, Matthew Townshend

Abstract:

Road authorities are mandated within limited budgets to both deliver improved access to basic services and facilitate economic growth. This responsibility is further complicated if maintenance backlogs and funding shortfalls exist, as evident in many countries including South Africa. These conditions require authorities to make difficult prioritisation decisions, with the effect that Road Asset Management Systems with a one-dimensional focus on traffic volumes may overlook the maintenance of low-volume roads that provide isolated communities with vital access to basic services. Given these challenges, this paper overlays the full South African road network with geo-referenced information for population, primary and secondary schools, and healthcare facilities to identify the network of connective roads between communities and basic service centres. This connective network is then rationalised according to the Gross Value Added and number of jobs per mesozone, administrative and functional road classifications, speed limit, and road length, location, and name to estimate the Basic Access Road Network. A two-step floating catchment area (2SFCA) method, capturing a weighted assessment of drive-time to service centres and the ratio of people within a catchment area to teachers and healthcare workers, is subsequently applied to generate a Multivariate Road Index. This Index is used to assign higher maintenance priority to roads within the Basic Access Road Network that provide more people with better access to services. The relatively limited incidence of Basic Access Roads indicates that authorities could maintain the entire estimated network without exhausting the available road budget before practical economic considerations get any purchase. Despite this fact, a final case study modelling exercise is performed for the Namakwa District Municipality to demonstrate the extent to which optimal relocation of schools and healthcare facilities could minimise the Basic Access Road Network and thereby release budget for investment in roads that best promote GDP growth.

Keywords: basic access roads, multivariate road index, road prioritisation, two-step floating catchment area method

Procedia PDF Downloads 225
1716 Characterization and Modelling of Aerosol Droplet in Absorption Columns

Authors: Hammad Majeed, Hanna Knuutila, Magne Hillestad, Hallvard F. Svendsen

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Formation of aerosols can cause serious complications in industrial exhaust gas CO2 capture processes. SO3 present in the flue gas can cause aerosol formation in an absorption based capture process. Small mist droplets and fog formed can normally not be removed in conventional demisting equipment because their submicron size allows the particles or droplets to follow the gas flow. As a consequence of this aerosol based emissions in the order of grams per Nm3 have been identified from PCCC plants. In absorption processes aerosols are generated by spontaneous condensation or desublimation processes in supersaturated gas phases. Undesired aerosol development may lead to amine emissions many times larger than what would be encountered in a mist free gas phase in PCCC development. It is thus of crucial importance to understand the formation and build-up of these aerosols in order to mitigate the problem. Rigorous modelling of aerosol dynamics leads to a system of partial differential equations. In order to understand mechanics of a particle entering an absorber an implementation of the model is created in Matlab. The model predicts the droplet size, the droplet internal variable profiles and the mass transfer fluxes as function of position in the absorber. The Matlab model is based on a subclass method of weighted residuals for boundary value problems named, orthogonal collocation method. The model comprises a set of mass transfer equations for transferring components and the essential diffusion reaction equations to describe the droplet internal profiles for all relevant constituents. Also included is heat transfer across the interface and inside the droplet. This paper presents results describing the basic simulation tool for the characterization of aerosols formed in CO2 absorption columns and gives examples as to how various entering droplets grow or shrink through an absorber and how their composition changes with respect to time. Below are given some preliminary simulation results for an aerosol droplet composition and temperature profiles.

Keywords: absorption columns, aerosol formation, amine emissions, internal droplet profiles, monoethanolamine (MEA), post combustion CO2 capture, simulation

Procedia PDF Downloads 244
1715 Pareto Optimal Material Allocation Mechanism

Authors: Peter Egri, Tamas Kis

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Scheduling problems have been studied by the algorithmic mechanism design research from the beginning. This paper is focusing on a practically important, but theoretically rather neglected field: the project scheduling problem where the jobs connected by precedence constraints compete for various nonrenewable resources, such as materials. Although the centralized problem can be solved in polynomial-time by applying the algorithm of Carlier and Rinnooy Kan from the Eighties, obtaining materials in a decentralized environment is usually far from optimal. It can be observed in practical production scheduling situations that project managers tend to cache the required materials as soon as possible in order to avoid later delays due to material shortages. This greedy practice usually leads both to excess stocks for some projects and materials, and simultaneously, to shortages for others. The aim of this study is to develop a model for the material allocation problem of a production plant, where a central decision maker—the inventory—should assign the resources arriving at different points in time to the jobs. Since the actual due dates are not known by the inventory, the mechanism design approach is applied with the projects as the self-interested agents. The goal of the mechanism is to elicit the required information and allocate the available materials such that it minimizes the maximal tardiness among the projects. It is assumed that except the due dates, the inventory is familiar with every other parameters of the problem. A further requirement is that due to practical considerations monetary transfer is not allowed. Therefore a mechanism without money is sought which excludes some widely applied solutions such as the Vickrey–Clarke–Groves scheme. In this work, a type of Serial Dictatorship Mechanism (SDM) is presented for the studied problem, including a polynomial-time algorithm for computing the material allocation. The resulted mechanism is both truthful and Pareto optimal. Thus the randomization over the possible priority orderings of the projects results in a universally truthful and Pareto optimal randomized mechanism. However, it is shown that in contrast to problems like the many-to-many matching market, not every Pareto optimal solution can be generated with an SDM. In addition, no performance guarantee can be given compared to the optimal solution, therefore this approximation characteristic is investigated with experimental study. All in all, the current work studies a practically relevant scheduling problem and presents a novel truthful material allocation mechanism which eliminates the potential benefit of the greedy behavior that negatively influences the outcome. The resulted allocation is also shown to be Pareto optimal, which is the most widely used criteria describing a necessary condition for a reasonable solution.

Keywords: material allocation, mechanism without money, polynomial-time mechanism, project scheduling

Procedia PDF Downloads 328
1714 Contextual Sentiment Analysis with Untrained Annotators

Authors: Lucas A. Silva, Carla R. Aguiar

Abstract:

This work presents a proposal to perform contextual sentiment analysis using a supervised learning algorithm and disregarding the extensive training of annotators. To achieve this goal, a web platform was developed to perform the entire procedure outlined in this paper. The main contribution of the pipeline described in this article is to simplify and automate the annotation process through a system of analysis of congruence between the notes. This ensured satisfactory results even without using specialized annotators in the context of the research, avoiding the generation of biased training data for the classifiers. For this, a case study was conducted in a blog of entrepreneurship. The experimental results were consistent with the literature related annotation using formalized process with experts.

Keywords: sentiment analysis, untrained annotators, naive bayes, entrepreneurship, contextualized classifier

Procedia PDF Downloads 391
1713 Credit Risk Prediction Based on Bayesian Estimation of Logistic Regression Model with Random Effects

Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

Procedia PDF Downloads 537
1712 Emergency Physician Performance for Hydronephrosis Diagnosis and Grading Compared with Radiologist Assessment in Renal Colic: The EPHyDRA Study

Authors: Sameer A. Pathan, Biswadev Mitra, Salman Mirza, Umais Momin, Zahoor Ahmed, Lubna G. Andraous, Dharmesh Shukla, Mohammed Y. Shariff, Magid M. Makki, Tinsy T. George, Saad S. Khan, Stephen H. Thomas, Peter A. Cameron

Abstract:

Study objective: Emergency physician’s (EP) ability to identify hydronephrosis on point-of-care ultrasound (POCUS) has been assessed in the past using CT scan as the reference standard. We aimed to assess EP interpretation of POCUS to identify and grade the hydronephrosis in a direct comparison with the consensus-interpretation of POCUS by radiologists, and also to compare the EP and radiologist performance using CT scan as the criterion standard. Methods: Using data from a POCUS databank, a prospective interpretation study was conducted at an urban academic emergency department. All POCUS exams were performed on patients presenting with renal colic to the ED. Institutional approval was obtained for conducting this study. All the analyses were performed using Stata MP 14.0 (Stata Corp, College Station, Texas). Results: A total of 651 patients were included, with paired sets of renal POCUS video clips and the CT scan performed at the same ED visit. Hydronephrosis was reported in 69.6% of POCUS exams by radiologists and 72.7% of CT scans (p=0.22). The κ for consensus interpretation of POCUS between the radiologists to detect hydronephrosis was 0.77 (0.72 to 0.82) and weighted κ for grading the hydronephrosis was 0.82 (0.72 to 0.90), interpreted as good to very good. Using CT scan findings as the criterion standard, Eps had an overall sensitivity of 81.1% (95% CI: 79.6% to 82.5%), specificity of 59.4% (95% CI: 56.4% to 62.5%), PPV of 84.3% (95% CI: 82.9% to 85.7%), and NPV of 53.8% (95% CI: 50.8% to 56.7%); compared to radiologist sensitivity of 85.0% (95% CI: 82.5% to 87.2%), specificity of 79.7% (95% CI: 75.1% to 83.7%), PPV of 91.8% (95% CI: 89.8% to 93.5%), and NPV of 66.5% (95% CI: 61.8% to 71.0%). Testing for a report of moderate or high degree of hydronephrosis, specificity of EP was 94.6% (95% CI: 93.7% to 95.4%) and to 99.2% (95% CI: 98.9% to 99.5%) for identifying severe hydronephrosis alone. Conclusion: EP POCUS interpretations were comparable to the radiologists for identifying moderate to severe hydronephrosis using CT scan results as the criterion standard. Among patients with moderate or high pre-test probability of ureteric calculi, as calculated by the STONE-score, the presence of moderate to severe (+LR 6.3 and –LR 0.69) or severe hydronephrosis (+LR 54.4 and –LR 0.57) was highly diagnostic of the stone disease. Low dose CT is indicated in such patients for evaluation of stone size and location.

Keywords: renal colic, point-of-care, ultrasound, bedside, emergency physician

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1711 Development of Modular Shortest Path Navigation System

Authors: Nalinee Sophatsathit

Abstract:

This paper presents a variation of navigation systems which tallies every node along the shortest path from start to destination nodes. The underlying technique rests on the well-established Dijkstra Algorithm. The ultimate goal is to serve as a user navigation guide that furnishes stop over cost of every node along this shortest path, whereby users can decide whether or not to visit any specific nodes. The output is an implementable module that can be further refined to run on the Internet and smartphone technology. This will benefit large organizations having physical installations spreaded over wide area such as hospitals, universities, etc. The savings on service personnel, let alone lost time and unproductive work, are attributive to innovative navigation system management.

Keywords: navigation systems, shortest path, smartphone technology, user navigation guide

Procedia PDF Downloads 331
1710 Characterization of Aerosol Particles in Ilorin, Nigeria: Ground-Based Measurement Approach

Authors: Razaq A. Olaitan, Ayansina Ayanlade

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Understanding aerosol properties is the main goal of global research in order to lower the uncertainty associated with climate change in the trends and magnitude of aerosol particles. In order to identify aerosol particle types, optical properties, and the relationship between aerosol properties and particle concentration between 2019 and 2021, a study conducted in Ilorin, Nigeria, examined the aerosol robotic network's ground-based sun/sky scanning radiometer. The AERONET algorithm version 2 was utilized to retrieve monthly data on aerosol optical depth and angstrom exponent. The version 3 algorithm, which is an almucantar level 2 inversion, was employed to retrieve daily data on single scattering albedo and aerosol size distribution. Excel 2016 was used to analyze the data's monthly, seasonal, and annual mean averages. The distribution of different types of aerosols was analyzed using scatterplots, and the optical properties of the aerosol were investigated using pertinent mathematical theorems. To comprehend the relationships between particle concentration and properties, correlation statistics were employed. Based on the premise that aerosol characteristics must remain constant in both magnitude and trend across time and space, the study's findings indicate that the types of aerosols identified between 2019 and 2021 are as follows: 29.22% urban industrial (UI) aerosol type, 37.08% desert (D) aerosol type, 10.67% biomass burning (BB), and 23.03% urban mix (Um) aerosol type. Convective wind systems, which frequently carry particles as they blow over long distances in the atmosphere, have been responsible for the peak-of-the-columnar aerosol loadings, which were observed during August of the study period. The study has shown that while coarse mode particles dominate, fine particles are increasing in seasonal and annual trends. Burning biomass and human activities in the city are linked to these trends. The study found that the majority of particles are highly absorbing black carbon, with the fine mode having a volume median radius of 0.08 to 0.12 meters. The investigation also revealed that there is a positive coefficient of correlation (r = 0.57) between changes in aerosol particle concentration and changes in aerosol properties. Human activity is rapidly increasing in Ilorin, causing changes in aerosol properties, indicating potential health risks from climate change and human influence on geological and environmental systems.

Keywords: aerosol loading, aerosol types, health risks, optical properties

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1709 Comparison between Photogrammetric and Structure from Motion Techniques in Processing Unmanned Aerial Vehicles Imageries

Authors: Ahmed Elaksher

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Over the last few years, significant progresses have been made and new approaches have been proposed for efficient collection of 3D spatial data from Unmanned aerial vehicles (UAVs) with reduced costs compared to imagery from satellite or manned aircraft. In these systems, a low-cost GPS unit provides the position, velocity of the vehicle, a low-quality inertial measurement unit (IMU) determines its orientation, and off-the-shelf cameras capture the images. Structure from Motion (SfM) and photogrammetry are the main tools for 3D surface reconstruction from images collected by these systems. Unlike traditional techniques, SfM allows the computation of calibration parameters using point correspondences across images without performing a rigorous laboratory or field calibration process and it is more flexible in that it does not require consistent image overlap or same rotation angles between successive photos. These benefits make SfM ideal for UAVs aerial mapping. In this paper, a direct comparison between SfM Digital Elevation Models (DEM) and those generated through traditional photogrammetric techniques was performed. Data was collected by a 3DR IRIS+ Quadcopter with a Canon PowerShot S100 digital camera. Twenty ground control points were randomly distributed on the ground and surveyed with a total station in a local coordinate system. Images were collected from an altitude of 30 meters with a ground resolution of nine mm/pixel. Data was processed with PhotoScan, VisualSFM, Imagine Photogrammetry, and a photogrammetric algorithm developed by the author. The algorithm starts with performing a laboratory camera calibration then the acquired imagery undergoes an orientation procedure to determine the cameras’ positions and orientations. After the orientation is attained, correlation based image matching is conducted to automatically generate three-dimensional surface models followed by a refining step using sub-pixel image information for high matching accuracy. Tests with different number and configurations of the control points were conducted. Camera calibration parameters estimated from commercial software and those obtained with laboratory procedures were comparable. Exposure station positions were within less than few centimeters and insignificant differences, within less than three seconds, among orientation angles were found. DEM differencing was performed between generated DEMs and few centimeters vertical shifts were found.

Keywords: UAV, photogrammetry, SfM, DEM

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1708 Reliability Based Topology Optimization: An Efficient Method for Material Uncertainty

Authors: Mehdi Jalalpour, Mazdak Tootkaboni

Abstract:

We present a computationally efficient method for reliability-based topology optimization under material properties uncertainty, which is assumed to be lognormally distributed and correlated within the domain. Computational efficiency is achieved through estimating the response statistics with stochastic perturbation of second order, using these statistics to fit an appropriate distribution that follows the empirical distribution of the response, and employing an efficient gradient-based optimizer. The proposed algorithm is utilized for design of new structures and the changes in the optimized topology is discussed for various levels of target reliability and correlation strength. Predictions were verified thorough comparison with results obtained using Monte Carlo simulation.

Keywords: material uncertainty, stochastic perturbation, structural reliability, topology optimization

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1707 A Fast and Robust Protocol for Reconstruction and Re-Enactment of Historical Sites

Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi

Abstract:

This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction

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1706 Cognitive SATP for Airborne Radar Based on Slow-Time Coding

Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: space-time adaptive processing (STAP), airborne radar, signal-to-clutter ratio, slow-time coding

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1705 Petrogenesis and Tectonic Implication of the Oligocene Na-Rich Granites from the North Sulawesi Arc, Indonesia

Authors: Xianghong Lu, Yuejun Wang, Chengshi Gan, Xin Qian

Abstract:

The North Sulawesi Arc, located on the east of Indonesia and to the south of the Celebes Sea, is the north part of the K-shape of Sulawesi Island and has a complex tectonic history since the Cenozoic due to the convergence of three plates (Eurasia, India-Australia and Pacific plates). Published rock records contain less precise chronology, mostly using K-Ar dating, and rare geochemistry data, which limit the understanding of the regional tectonic setting. This study presents detailed zircon U-Pb geochronological and Hf-O isotope and whole-rock geochemical analyses for the Na-rich granites from the North Sulawesi Arc. Zircon U-Pb geochronological analyses of three representative samples yield weighted mean ages of 30.4 ± 0.4 Ma, 29.5 ± 0.2 Ma, and 27.3 ± 0.4 Ma, respectively, revealing the Oligocene magmatism in the North Sulawesi Arc. The samples have high Na₂O and low K₂O contents with high Na₂O/K₂O ratios, belonging to Low-K tholeiitic Na-rich granites. The Na-rich granites are characterized by high SiO₂ contents (75.05-79.38 wt.%) and low MgO contents (0.07-0.91 wt.%) and show arc-like trace elemental signatures. They have low (⁸⁷Sr/⁸⁶Sr)i ratios (0.7044-0.7046), high εNd(t) values (from +5.1 to +6.6), high zircon εHf(t) values (from +10.1 to +18.8) and low zircon δ18O values (3.65-5.02). They show an Indian-Ocean affinity of Pb isotopic compositions with ²⁰⁶Pb/²⁰⁴Pb ratio of 18.16-18.37, ²⁰⁷Pb/²⁰⁴Pb ratio of 15.56-15.62, and ²⁰⁸Pb/²⁰⁴Pb ratio of 38.20-38.66. These geochemical signatures suggest that the Oligocene Na-rich granites from the North Sulawesi Arc formed by partial melting of the juvenile oceanic crust with sediment-derived fluid-related metasomatism in a subducting setting and support an intra-oceanic arc origin. Combined with the published study, the emergence of extensive calc-alkaline felsic arc magmatism can be traced back to the Early Oligocene period, subsequent to the Eocene back-arc basalts (BAB) that share similarity with the Celebes Sea basement. Since the opening of the Celebes Sea started from the Eocene (42~47 Ma) and stopped by the Early Oligocene (~32 Ma), the geodynamical mechanism of the formation of the Na-rich granites from the North Sulawesi Arc during the Oligocene might relate to the subduction of the Indian Ocean.

Keywords: North Sulawesi Arc, oligocene, Na-rich granites, in-situ zircon Hf–O analysis, intra-oceanic origin

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1704 Optimal Capacitor Placement in Distribution Systems

Authors: Sana Ansari, Sirus Mohammadi

Abstract:

In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. General Algebraic Modeling System (GAMS) has been used to solve the maximization modules using the MINOS optimization software with Linear Programming (LP). The proposed method is tested on 33 node distribution system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: power losses, voltage stability, radial distribution systems, capacitor

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1703 Video Stabilization Using Feature Point Matching

Authors: Shamsundar Kulkarni

Abstract:

Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper, an algorithm is proposed to stabilize jittery videos .A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video are identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.

Keywords: video stabilization, point feature matching, salient points, image quality measurement

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1702 The Convection Heater Numerical Simulation

Authors: Cristian Patrascioiu, Loredana Negoita

Abstract:

This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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1701 Implementation of a Low-Cost Driver Drowsiness Evaluation System Using a Thermal Camera

Authors: Isa Moazen, Ali Nahvi

Abstract:

Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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1700 Finite Element Analysis of a Dynamic Linear Crack Problem

Authors: Brian E. Usibe

Abstract:

This paper addresses the problem of a linear crack located in the middle of a homogeneous elastic media under normal tension-compression harmonic loading. The problem of deformation of the fractured media is solved using the direct finite element numerical procedure, including the analysis of the dynamic field variables of the problem. A finite element algorithm that satisfies the unilateral Signorini contact constraint is also presented for the solution of the contact interaction of the crack faces and how this accounts for the qualitative and quantitative changes in the solution when determining the dynamic fracture parameter.

Keywords: harmonic loading, linear crack, fracture parameter, wave number, FEA, contact interaction

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