Search results for: intra prediction

Authors: Ena Arora, Rong Fan, Aleksandr Fuks, Kolawole Felix Akinnawonu

Abstract:

Introduction: Leiomyomas are benign tumors that are derived from the overgrowth of uterine smooth muscle cells. Women with symptomatic leiomyomas who desire future fertility, myomectomy should be the standard surgical treatment. Perioperative hemorrhage is a common complication in myomectomy. We performed the study to investigate blood transfusion rate in abdominal myomectomies, risk factors influencing blood loss and modalities to improve perioperative blood loss. Methods: Retrospective chart review was done for patients who underwent myomectomy from 2016 to 2022 at Queens hospital center, New York. We looked at preoperative patient demographics, clinical characteristics, intraoperative variables, and postoperative outcomes. Mann-Whitney U test were used for parametric and non-parametric continuous variable comparisons, respectively. Results: A total of 159 myomectomies were performed between 2016 and 2022, including 1 laparoscopic, 65 vaginal and 93 abdominal. 44 patients received blood transfusion during or within 72 hours of abdominal myomectomy. The blood transfusion rate was 47.3%. Blood transfusion rate was found to be twice higher than the average documented rate in literature which is 20%. Risk factors identified were black race, preoperative hematocrit<30%, preoperative blood transfusion within 72 hours, large fibroid burden, prolonged surgical time, and abdominal approach. Conclusion: Preoperative optimization with iron supplements or GnRH agonists is important for patients undergoing myomectomy. Interventions to decrease intra operative blood loss should include cell saver, tourniquet, vasopressin, misoprostol, tranexamic acid and gelatin-thrombin matrix hemostatic sealant.

Keywords: myomectomy, perioperative blood loss, cell saver, tranexamic acid

Procedia PDF Downloads 82

Authors: Mahesh Chudasama, Harit Raval

Abstract:

Conical sections and shells of metal plates manufactured by 3-roller conical bending process are widely used in the industries. The process is completed by first bending the metal plates statically and then dynamic roller bending sequentially. It is required to have an analytical model to get maximum bending force, for optimum design of the machine, for static bending stage. Analytical models assuming various stress conditions are considered and these analytical models are compared considering various parameters and reported in this paper. It is concluded from the study that for higher bottom roller inclination, the shear stress affects greatly to the static bending force whereas for lower bottom roller inclination it can be neglected.

Keywords: roller-bending, static-bending, stress-conditions, analytical-modeling

Procedia PDF Downloads 248

Authors: İsmail İnce

Abstract:

The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

Procedia PDF Downloads 469

Authors: Naseem Uddin

Abstract:

Impinging jets are used in variety of engineering and industrial applications. This paper is based on numerical simulations of heat transfer by turbulent impinging jet with velocity field excitations using different Reynolds Averaged Navier-Stokes Equations models. Also Detached Eddy Simulations are conducted to investigate the differences in the prediction capabilities of these two simulation approaches. In this paper the excited jet is simulated in non-commercial CFD code OpenFOAM with the goal to understand the influence of dynamics of impinging jet on heat transfer. The jet’s frequencies are altered keeping in view the preferred mode of the jet. The Reynolds number based on mean velocity and diameter is 23,000 and jet’s outlet-to-target wall distance is 2. It is found that heat transfer at the target wall can be influenced by judicious selection of amplitude and frequencies.

Keywords: excitation, impinging jet, natural frequency, turbulence models

Procedia PDF Downloads 268

Authors: Y. Galerkin, A. Rekstin, K. Soldatova

Abstract:

Universal modeling method well proven for industrial compressors was applied for design of the high flow rate supersonic stage. Results were checked by ANSYS CFX and NUMECA Fine Turbo calculations. The impeller appeared to be very effective at transonic flow velocities. Stator elements efficiency is acceptable at design Mach numbers too. Their loss coefficient versus inlet flow angle performances correlates well with Universal modeling prediction. The impeller demonstrated ability of satisfactory operation at design flow rate. Supersonic flow behavior in the impeller inducer at the shroud blade to blade surface Φdes deserves additional study.

Keywords: centrifugal compressor stage, supersonic impeller, inlet flow angle, loss coefficient, return channel, shock wave, vane diffuser

Procedia PDF Downloads 465

Authors: Tayeb Aissaoui, Inas M. AlNashef

Abstract:

In recent years, green solvents named deep eutectic solvents (DESs) have been found to possess significant properties and to be applicable in several technologies. Choline chloride (ChCl) mixed with urea at a ratio of 1:2 and 80 °C was the first discovered DES. In this article, chemical structure and combination mechanism of ChCl: urea based DES were investigated. Moreover, the implementation of this DES in water removal from natural gas was reported. Dehydration of natural gas by ChCl:urea shows significant absorption efficiency compared to triethylene glycol. All above operations were retrieved from COSMOthermX software. This article confirms the potential application of DESs in gas industry.

Keywords: COSMO-RS, deep eutectic solvents, dehydration, natural gas, structure, organic salt

Procedia PDF Downloads 288

Authors: Maryam Amiri, Leyli Mohammad-Khanli

Abstract:

Cloud computing is becoming increasingly popular and more business applications are moving to cloud. In this regard, services that provide similar functional properties are increasing. So, the ability to select a service with the best non-functional properties, corresponding to the user preference, is necessary for the user. This paper presents an Evaluation Framework of Service Trustworthiness (EFST) that evaluates the trustworthiness of equivalent services without need to additional invocations of them. EFST extracts user preference automatically. Then, it assesses trustworthiness of services in two dimensions of qualitative and quantitative metrics based on the experiences of past usage of services. Finally, EFST determines the overall trustworthiness of services using Fuzzy Inference System (FIS). The results of experiments and simulations show that EFST is able to predict the missing values of Quality of Service (QoS) better than other competing approaches. Also, it propels users to select the most appropriate services.

Keywords: user preference, cloud service, trustworthiness, QoS metrics, prediction

Procedia PDF Downloads 285

Authors: Tarek Litim, Ouahiba Taamallah

Abstract:

The present paper is an investigation of the effect of burnishing on the surface integrity of a component made of 15NiCr6 steel. This work shows a statistical study based on regression, and Taguchi's design has allowed the development of mathematical models to predict the output responses as a function of the technological parameters studied. The response surface methodology (RSM) showed a simultaneous influence of the burnishing parameters and observe the optimal processing parameters. ANOVA analysis of the results resulted in the validation of the prediction model with a determination coefficient R=90.60% and 92.41% for roughness and hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=10kgf, i=3passes, and f=0.074mm/rev, which favours minimum roughness and maximum hardness. The result was validated by the desirability of D= (0.99 and 0.95) for roughness and hardness, respectively.

Keywords: 15NiCr6 steel, burnishing, surface integrity, Taguchi, RSM, ANOVA

Procedia PDF Downloads 188

Authors: Muhammad Anjum Aqueel, Muhammad Jaffar Hussain, Abu Bakar Muhammad Raza

Abstract:

Diaeretiella rapae (M’Intosh) attack most of the aphid species. However, it is specialized in feeding on crucifer aphid, Brevicoryne brassicae. Biological potential of parasitoid is its density-dependency due to sharing of limited resources in few cases. The present study was carried out to check the biotic potential of D. rapae at its different densities (1, 2, 4, 8 and 10 pairs) on fixed number of B. brassicae (100 in number) as a host. The present study was performed under laboratory conditions (25 ± 2 ºC temperature and 65-70 % R.H.). Different biological parameters for parasitoid (e.g. percent parasitism, adult emergence, adult longevity and per pair parasitism) were evaluated to check its biotic potential. The present findings showed that maximum parasitism (43.09 % ± 0.63) was observed in highest density (10 pairs) and minimum parasitism (16.59 % ± 1.28) in lowest density (1 pair) of the parasitoid. Maximum adult emergence (80.31 % ± 1.33) was observed in highest density (10 pairs) and minimum parasitism (45.99 % ± 1.27) in lowest density (1 pair) of the parasitoid. In the case of adult longevity, highest (8.2 days ± 0.38) and lowest (6 days ± 0.32) longevity were observed in lowest (1 pair) and highest (10 pairs) densities of parasitoids respectively. However, per pair parasitism rate decreased with the increase in parasitoid densities due to intra-specific competition, developed between the parasitoids for parasitism. The positive but close relationship was observed between percent parasitism and adult emergence. The increase in parasitoid densities increased the percent parasitism and adult emergence of the parasitoid. So, we conclude that an inter-specific competition negatively affected the efficacy of parasitoids and may reduce the fitness of the emerging parasitoid.

Keywords: Diaeretiella rapae, Parasitoid densities, Percent parasitism, adult emergence

Procedia PDF Downloads 231

Authors: Tariq Mansoor, Lubos Hes, Vladimir Bajzik

Abstract:

Socks comfort has great significance in our daily life. This significance even increased when we have undergone a work of low or high activity. It causes the sweating of our body with different rates. In this study, plain socks with differential fibre composition were wetted to saturated level. Then after successive intervals of conditioning, these socks are characterized by thermal resistance in dry and wet states. Theoretical thermal resistance is predicted by using combined filling coefficients and thermal conductivity of wet polymers instead of dry polymer (fibre) in different models. By this modification, different mathematical models could predict thermal resistance at different moisture levels. Furthermore, predicted thermal resistance by different models has reasonable correlation range between (0.84 -0.98) with experimental results in both dry (lab conditions moisture) and wet states. "This work is supported by Technical University of Liberec under SGC-2019. Project number is 21314".

Keywords: thermal resistance, mathematical model, plain socks, moisture loss rate

Procedia PDF Downloads 195

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 122

Authors: Dilek Saritas Atalar, Cansu Alsancak Akbulut, İrem Metin Orta, Feyza Yön, Zeynep Yenen, Joan Grusec

Abstract:

Objective: The aim of this study was to develop semi-structured Domains of Socialization Interview and its coding manual and to test their psychometric properties. Domains of Socialization Interview was designed to assess maternal awareness regarding effective parenting in five socialization domains (protection, mutual reciprocity, control, guided learning, and group participation) within the framework of the domains-of-socialization approach. Method: A series of two studies were conducted to develop and validate the interview and its coding manual. The pilot study, sampled 13 mothers of preschool-aged children, was conducted to develop the assessment tools and to test their function and clarity. Participants of the main study were 82 Turkish mothers (Xage = 34.25, SD = 3.53) who have children aged between 35-76 months (Xage = 50.75, SD = 11.24). Mothers filled in a questionnaire package including Coping with Children’s Negative Emotions Questionnaire, Social Competence and Behavior Evaluation-30, Child Rearing Questionnaire, and Two Dimensional Social Desirability Questionnaire. Afterward, interviews were conducted online by a single interviewer. Interviews were rated independently by two graduate students based on the coding manual. Results: The relationships of the awareness of effective parenting scores to the other measures demonstrate convergent, discriminant, and predictive validity of the coding manual. Intra-class correlation coefficient estimates were ranged between 0.82 and 0.90, showing high interrater reliability of the coding manual. Conclusion: Taken as a whole, the results of these studies demonstrate the validity and reliability of a new and useful interview to measure maternal awareness regarding effective parenting within the framework of the domains-of-socialization approach.

Keywords: domains of socialization, parenting, interview, assessment

Procedia PDF Downloads 184

Authors: Gabrielle O'Donoghue

Abstract:

Background: Pre-operative radiographs facilitate assessment and treatment planning in minor oral surgery. Quality assurance for dental radiography advocates the As Low As Reasonably Achievable (ALARA) principle in collecting accurate diagnostic information. Aims: To audit the quality of digital intraoral periapicals (IOPAs) taken prior to dental extractions in a metropolitan general dental practice setting. Standards: The National Radiological Protection Board (NRPB) guidance outlines three grades of radiograph quality: excellent (Grade 1 > 70% of total exposures), diagnostically acceptable (Grade 2 <20%), and unacceptable (Grade 3 <10%). Methodology: A study of pre-operative radiographs taken prior to dental extractions across 12 private general dental practices in a large metropolitan area by 44 practitioners. A total of 725 extractions were assessed, allowing 258 IOPAs to be reviewed in one audit cycle. Results: First cycle: Of 258 IOPAs: 223(86.4%) scored Grade 1, 27(10.5%) Grade 2, and 8(3.1%) Grade 3. The standard was met. 35 dental extractions were performed without an available pre-operative radiograph. Action Plan & Recommendations: Results were distributed to all staff and a continuous professional development evening organized to outline recommendations to improve image quality. A second audit cycle is proposed at a six-month interval to review the recommendations and appraise results. Conclusion: The overall standard of radiographs met the published guidelines. A significant improvement in the number of procedures undertaken without pre-operative imaging is expected at a six-month interval period. An investigation into undiagnostic imaging and associated adverse patient outcomes is being considered. Maintenance of the standards achieved is predicted in the second audit cycle to ensure consistent high quality imaging.

Keywords: audit, oral radiology, oral surgery, periapical radiographs, quality assurance

Procedia PDF Downloads 163

Authors: Damiaa Saad Khudor

Abstract:

The paper describes an investigation for the thermal design of a fluidized bed cooler and prediction of heat transfer rate among the media categories. It is devoted to the thermal design of such equipment and their application in the industrial fields. It outlines the strategy for the fluidization heat transfer mode and its implementation in industry. The thermal design for fluidized bed cooler is used to furnish a complete design for a fluidized bed cooler of Sodium Bicarbonate. The total thermal load distribution between the air-solid and water-solid along the cooler is calculated according to the thermal equilibrium. The step by step technique was used to accomplish the thermal design of the fluidized bed cooler. It predicts the load, air, solid and water temperature along the trough. The thermal design for fluidized bed cooler revealed to the installation of a heat exchanger consists of (65) horizontal tubes with (33.4) mm diameter and (4) m length inside the bed trough.

Keywords: fluidization, powder technology, thermal design, heat exchangers

Procedia PDF Downloads 509

Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu

Abstract:

The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.

Keywords: artificial neural network (ANN), finite element method (FEM), perforated sections, thin-walled Steel, ultimate load

Procedia PDF Downloads 348

Authors: Fangting Gao

Abstract:

With the accelerated pace of industrialization and urbanization, the economic level has been significantly improved, and at the same time, the air quality situation has also become a focus of attention, which not only affects people's health but also has certain impacts on the economy and ecology. As the capital city of China, the air quality situation in Beijing has attracted much attention. In this paper, based on the day-by-day PM2.5, PM10, CO, NO₂, SO₂ and O₃ conditions in Beijing from 2018 to 2022, the characterization of pollutants is launched, and the seasonal decomposition and prediction of the main pollutants, PM2.5, PM10 and O3, are performed in STL. The results of the study show that (1) the overall air quality of Beijing has significantly improved from 2018 to 2022, and the main pollutants are PM2.5, PM10, and O₃; (2) the seasonal intensities of the main pollutants are higher, and they are influenced by seasonal factors; and (3) it is predicted that the O₃ concentration will have a trend of slowly increasing from 2023 to 2026, and the PM10 and PM2.5 pollution situation slowly improves.

Keywords: air pollutants, Beijing, characteristic analysis, STL

Procedia PDF Downloads 13

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

Abstract:

The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

Procedia PDF Downloads 130

Authors: A. Hocine, A. Ghouaoula, S. M. Medjdoub, M. Cherifi

Abstract:

The present paper proposed a meso–macro model describing the mechanical behaviour composite laminates of staking sequence [+θ/-θ]s under tensil loading. The behaviour of a layer is ex-pressed through elasticity coupled to damage. The elastic strain is due to the elasticity of the layer and can be modeled by using the classical laminate theory, and the laminate is considered as an orthotropic material. This means that no coupling effect between strain and curvature is considered. In the present work, the damage is associated to cracking of the matrix and parallel to the fibers and it being taken into account by the changes in the stiffness of the layers. The anisotropic damage is completely described by a single scalar variable and its evolution law is specified from the principle of maximum dissipation. The stress/strain relationship is investigated in plane stress loading.

Keywords: damage, behavior modeling, meso-macro model, composite laminate, membrane loading

Procedia PDF Downloads 472

Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

Abstract:

Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

Procedia PDF Downloads 41

Authors: Kais A. Kadhim

Abstract:

This paper is a semantic analysis of the English modals in Obama’s speech. The main objective of this study is to analyze selected modal auxiliaries identified in selected speeches of Obama’s campaign based on Coates’ (1983) semantic clusters. A total of fifteen speeches of Obama’s campaign were selected as the primary data and the modal auxiliaries selected for analysis include will, would, can, could, should, must, ought, shall, may and might. All the modal auxiliaries taken from the speeches of Barack Obama were analyzed based on the framework of Coates’ semantic clusters. Such analytical framework was carried out to examine how modal auxiliaries are used in the context of persuading people in Obama’s campaign speeches. The findings reveal that modals of intention, prediction, futurity and modals of possibility, ability, permission are mostly used in Obama’s campaign speeches.

Keywords: modals, meaning, persuasion, speech

Procedia PDF Downloads 402

Authors: Sara Javanmardi, Sepehr Aziziz, Baharak Divband, Masoumeh Firouzamandi

Abstract:

Post-operative adhesions are the most common cause of intestinal obstruction, female infertility and chronic abdominal pain. We developed a novel approach for preventing post-operative peritoneal adhesions using a biodegradable and thermosensitive curcumin hydrogel in rats. Thirteen male Sprague-Dawley rats were assigned randomly into five groups of six animals each: In SHAM group, the cecum was exteriorized, gently manipulated and sent back into the abdomen. In CONTROL group, the surgical abrasion was performed with no further treatment. In Hydrogel group, surgical abrasion was performed with local application of blank hydrogel (1 mL). In Curcumin group, surgical abrasion was performed with local application of curcumin (1 mL). In CUR/HGEL group, surgical abrasion was performed with local application of curcumin hydrogel (1 mL). On day 10, adhesions were assessed using a standardized scale (Evans model), and samples were collected for the Real-time PCR. Real-time PCR was performed to determine mRNA levels of VCAM-1, ICAM-1 and GAPDH. The macroscopic adhesion intensity showed statistically significant differences between the CUR/HGEL and other groups (P=0.0005). The findings of the present study revealed there were statistically significant differences between the groups regarding adhesion band length and numbers (P<0.0001). The protein and mRNA expression of VCAM-1 and ICAM-1 in secal tissues were significantly down regulated due to curcumin-hydrogel application in CUR/HGEL compared to other groups (p<0.05). The thermosensitive hydrogel could reduce the severity and even prevent formation of intra-abdominal adhesion. Curcumin hydrogel could serve as a potential barrier agent to prevent post-operative peritoneal adhesion in rats.

Keywords: peritoneal adhesion, hydrogel, curcumijn, ICAM-1, VCAM-1

Procedia PDF Downloads 83

Authors: Mabrouka Morri, Amel Soualmia, Philippe Belleudy

Abstract:

Vegetation affects the mean and turbulent flow structure. It may increase flood risks and sediment transport. Therefore, it is important to develop analytical approaches for the bed shear stress on vegetated bed, to predict resistance caused by vegetation. In the recent years, experimental and numerical models have both been developed to model the effects of submerged vegetation on open-channel flow. In this paper, different analytic models are compared and tested using the criteria of deviation, to explore their capacity for predicting the mean velocity and select the suitable one that will be applied in real case of rivers. The comparison between the measured data in vegetated flume and simulated mean velocities indicated, a good performance, in the case of rigid vegetation, whereas, Huthoff model shows the best agreement with a high coefficient of determination (R2=80%) and the smallest error in the prediction of the average velocities.

Keywords: analytic models, comparison, mean velocity, vegetation

Procedia PDF Downloads 272

Authors: Quoc Ngoc Phan, Hieu Van Nguyen, Minh Hong Nguyen

Abstract:

This study presents an integrated approach using Mercury Injection Capillary Pressure (MICP) and petrographic analysis to assess the seal quality of the inter-bedded shale formations which are considered the intra-formation top seals of hydrocarbon bearing zones in Green Dragon structure. Based on the hydrocarbon column height (HCH) at leak point derived from capillary pressure data, four seal types were identified. Furthermore, the results of scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were interpreted to clarify the influence of clay minerals on seal capacity. The result of the study indicated that the inter-bedded shale formations are the good sealing quality with a majority of analyzed samples ranked type A and B seals in the sample set. Both seal types occurred mainly in mudstones with pore radius estimated less than 0.251 µm. Overall, type A and B seals contained a large amount of authigenic clay minerals such as illite, chlorite which showed the complexity of morphological arrangement in pore space. Conversely, the least common seal type C and D were presented in moderately compacted sandstones with more open pore radius. It is noticeable that there was a reduction of illite and chlorite in clay mineral fraction of these seal type. It is expected that the integrated analysis approach using Mercury Injection Capillary Pressure and petrographic data employed in this study can be applied to assess the sealing quality of future well sites in Green Dragon or other structures.

Keywords: seal capacity, hydrocarbon height column, seal type, SEM, XRD

Procedia PDF Downloads 158

Authors: Gianna Zou

Abstract:

Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

Procedia PDF Downloads 141

Authors: Ziyad S. Haidar

Abstract:

Millions of teeth are removed annually, and dental extraction is one of the most commonly performed surgical procedures globally. Whether due to caries, periodontal disease or trauma, exodontia and the ensuing wound healing and bone remodeling processes of the resultant socket (hole in the jaw bone) usually result in serious deformities of the residual alveolar osseous ridge and surrounding soft tissues (reduced height/width). Such voluminous changes render the placement of a proper conventional bridge, denture or even an implant-supported prosthesis extremely challenging. Further, most extractions continue to be performed with no regard for preventing the onset of alveolar osteitis (also known as dry socket, a painful and difficult-to-treat/-manage condition post-exodontia). Hence, such serious resorptive morphological changes often result in significant facial deformities and a negative impact on the overall Quality of Life (QoL) of patients (and oral health-related QoL), alarming, particularly for the geriatric with compromised healing and in light of the thriving longevity statistics. Opportunity: Despite advances in tissue/wound grafting, serious limitations continue to exist, including efficacy and clinical outcome predictability, cost, treatment time, expertise and risk of immune reactions. For cases of dry sockets, specifically, the commercially-available and often-prescribed home remedies are highly lacking. Indeed, most are not recommended for use anymore. Alveogyl is a fine example. Hence, there is a great market demand and need for alternative solutions. Solution: Herein, SockGEL/PLUG (patent pending), an all-natural, drug-free and injectable stimuli-responsive hydrogel, was designed, formulated, characterized and evaluated as an osteogenic, angiogenic, anti-microbial and pain-soothing suture-free intra-alveolar dressing, safe and efficacious for use in several oro-dental and cranio-maxillo-facial interventional applications; for example: in fresh dental extraction sockets, immediately post-exodontia. It is composed of FDA-approved, biocompatible and biodegradable polymers, self-assembled electro-statically to formulate a scaffolding matrix to (a) prevent the onset of alveolar osteitis via securing the fibrin-clot in situ and protecting/sealing the socket from contamination/infection; and (b) endogenously promote/accelerate wound healing and bone remodeling to preserve the volume of the alveolus. Findings: The intrinsic properties of the SockGEL/PLUG hydrogel were evaluated physico-chemico-mechanically for safety (cell viability), viscosity, rheology, bio-distribution and essentially, capacity to induce wound healing and osteogenesis (small defect, in vivo) without any signaling cues from exogenous cells, growth factors or drugs. The performed animal model of cranial critical-sized and non-vascularized bone defects shall provide vitally critical insights into the role and mechanism of the employed natural bio-polymer blend and gel product in endogenous reparative regeneration of soft tissues and bone morphogenesis. Alongside, the fine-tuning of our modified formulation method will further tackle appropriateness, reproducibility, scalability, ease and speed in producing stable, biodegradable and sterilizable stimuli (thermo-sensitive and photo-responsive) matrices (3-dimensional interpenetrating yet porous polymeric network) suitable for an intra-socket application, and beyond. Conclusions and Perspective: Findings are anticipated to provide sufficient evidence to translate into pilot clinical trials and validate the bionanomaterial before engaging the market for feasibility, acceptance and cost-effectiveness studies. The SockGEL/PLUG platform is patent pending: SockGEL is a bio-inspired drug-free hydrogel; SockPLUG is a drug-loaded hydrogel designed for complex indications.

Keywords: hydrogel, injectable, dentistry, craniomaxillofacial complex, bioinspired, nanobiotechnology, biopolymer, sol-gel, stimuli-responsive, matrix, tissue engineering, regenerative medicine

Procedia PDF Downloads 68

Authors: Daniel Afolayan, Christina Olawepo, Francis Olowookanga, Nguhemen Tingir, Olawale Fadare, John Oko

Abstract:

In Nigeria, traditional birth attendants (TBAs) can play an important role in the prevention of mother-to-child transmission of HIV. However, their role in improving access to antiretroviral therapy (ART) is unclear. Catholic Caritas Foundation of Nigeria (Caritas Nigeria) is an implementing agency supporting increased access to HIV testing and treatment services in Lagos state through health facilities including Mother Theresa Hospital. Despite intra-facility testing and community outreaches, ART uptake at Mother Theresa Hospital, Lagos was low with 6 individuals on antiretroviral drugs 3 months post-activation. This study explored improving access to ART through linkages with TBAs for ART uptake at the facility. Plan-Do-Study-Act model was used. The goal was to improve uptake of ART from 6 to 80 in 5 months (end of project year). Scanning revealed a network of 15 TBAs with potential as satellites for HIV testing. Caritas Nigeria linked the facility with 15 TBAs who were provided with HIV test kits and trained on HIV testing services for provider-initiated testing and outreaches. Weekly reports and referrals of positives were received, tracked and feedback given on testing yield. These TBAs serve individuals of various age and gender at their trado-medical centres. At the end of 5 months, HIV testing increased by 10,575 (78% from TBAs) and HIV positives obtained improved by 77 (44.2% from TBAs). 55 new individuals were enrolled and commenced on ART (61.8% from TBAs). There was a successful linkage of all clients with escort services due to incentives. Total uptake of ART was 61 (76.3% of target). Structured partnerships between TBAs and HIV care and treatment centers should be strengthened to improve access to ART.

Keywords: access improvement, antiretroviral therapy, traditional birth attendants, uptake

Procedia PDF Downloads 451

Authors: I. Goual, M. S. Goual, M. K. Gueddouda, Taïbi Saïd, Abou-Bekr Nabil, A. Ferhat

Abstract:

This paper presents the study of hydro mechanical behavior of this optimal mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying- wetting behavior of the optimal mixture was carried out on slurry samples and compacted samples at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behavior of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

Keywords: tuff, sandy calcareous, road engineering, hydro mechanical behaviour, suction

Procedia PDF Downloads 503

Authors: Pei-Chann Chang, Jhen-Fu Liao, Chin-Hung Teng, Meng-Hui Chen

Abstract:

This research combines artificial immune system with user and item based collaborative filtering to create an efficient and accurate recommendation system. By applying the characteristic of antibodies and antigens in the artificial immune system and using Pearson correlation coefficient as the affinity threshold to cluster the data, our collaborative filtering can effectively find useful users and items for rating prediction. This research uses MovieLens dataset as our testing target to evaluate the effectiveness of the algorithm developed in this study. The experimental results show that the algorithm can effectively and accurately predict the movie ratings. Compared to some state of the art collaborative filtering systems, our system outperforms them in terms of the mean absolute error on the MovieLens dataset.

Keywords: artificial immune system, collaborative filtering, recommendation system, similarity

Procedia PDF Downloads 532

Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

Procedia PDF Downloads 148

Authors: Maria F. Seran

Abstract:

In second language interaction, an EFL student always carries his knowledge of targeted language and sometimes gets influenced by his first language cultures which makes him transfer his utterances from the first language to the second language. The influence of L1 cultures somehow can lead to face-threatening act when it comes to responding on speech act, for instance, compliment. A speaker praises a compliment to show gratitude, and in return, he expects for compliment respond uttered by the hearer. While Western people use more acceptance continuum on compliment response, Indonesians utter more denial continuum which can somehow put the speakers into a face-threating situation and offense. This study investigated compliment response employed by EFL students and English native speakers. The study was distinct as none compliment response studies had been conducted to compare the compliment response between English native speakers and two different Indonesian EFL proficiency groups in which this research sought to meet this need. This study was significant for EFL teachers because it gave insight on cross-cultural understanding and brought pedagogical implication on explicit pragmatic instruction. Two research questions were set, 1. How do Indonesian EFL students and English native speakers respond compliments? 2. Is there any correlation between Indonesia EFL students’ proficiency and their compliment response use in English? The study involved three groups of participants; 5 English native speakers, 10 high-proficiency and 10 low-proficiency Indonesian EFL university students. The research instruments used in this study were as follows, an online TOEFL prediction test, focusing on grammar skill which was modified from Barron TOEFL exercise test, and a discourse completion task (DCT), consisting of 10 compliment respond items. Based on the research invitation, 20 second-year university students majoring in English education at Widya Mandira Catholic University, Kupang, East Nusa Tenggara, Indonesia who willingly participated in the research took the TOEFL prediction test online from the link provided. Students who achieved score 75-100 in test were categorized as high-proficiency students, while, students who attained score below 74 were considered as low-proficiency students. Then, the DCT survey was administered to these EFL groups and the native speaker group. Participants’ responses were coded and analyzed using categories of compliment response framework proposed by Tran. The study found out that 5 native speakers applied more compliment upgrades and appreciation token in compliment response, whereas, Indonesian EFL students combined some compliment response strategies in their utterance, such as, appreciation token, return and compliment downgrade. There is no correlation between students’ proficiency level and their CR responds as most EFL students in both groups produced less varied compliment responses and only 4 Indonesian high-proficiency students uttered more varied and were similar to the native speakers. The combination strategies used by EFL students can be explained as the influence of pragmatic transfer from L1 to L2; therefore, EFL teachers should explicitly teach more compliment response strategies to raise students’ awareness on English culture and elaborate their speaking to be more competence as close to native speakers as possible.

Keywords: compliment response, English native speakers, Indonesian EFL students, speech acts

Procedia PDF Downloads 145