Search results for: gradient training method

Authors: Xiaodong Gao, Pingchuan Dong, Qichao Gao

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There has been lots of published work focused on asphaltene deposited on the smooth pipe under steady conditions, while particle deposition on the blockage wellbores under transient conditions has not been well elucidated. This work attempts to predict the deposition rate of asphaltene particles in blockage tube through CFD simulation. The Euler-Lagrange equation has been applied during the flow of crude oil and asphaltene particles. The net gravitational force, virtual mass, pressure gradient, saffman lift, and drag forces are incorporated in the simulations process. Validation of CFD simulation results is compared to the benchmark experiments from the previous literature. Furthermore, the effect of blockage location, blockage length, and blockage thickness on deposition rate are also analyzed. The simulation results indicate that the maximum deposition rate of asphaltene occurs in the blocked tube section, and the greater the deposition thickness, the greater the deposition rate. Moreover, the deposition amount and maximum deposition rate along the length of the tube have the same trend. Results of this study are in the ability to better understand the deposition of asphaltene particles in production and help achieve to deal with the asphaltene challenges.

Keywords: asphaltene deposition rate, blockage length, blockage thickness, blockage diameter, transient condition

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Authors: Yun-Hsiang Lee

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Cancer is the main cause of death worldwide. With advances in medical technology, immunotherapy, which is a newly developed advanced treatment, is currently a crucial cancer treatment option. For better quality cancer care, the ability to communicate and critical thinking plays a central role in clinical oncology settings. However, few studies have explored the impact of communication skills on immunotherapy-related issues and their related factors. This study was to (i) explore the current status of communication skill ability for immunotherapy-related issues, self-efficacy for immunotherapy-related care, and critical thinking ability; and (ii) identify factors related to communication skill ability. This is a cross-sectional study. Oncology nurses were recruited from the Taiwan Oncology Nursing Society, in which nurses came from different hospitals distributed across four major geographic regions (North, Center, South, East) of Taiwan. A total of 123 oncology nurses participated in this study. A set of questionnaires were used for collecting data. Communication skill ability for immunotherapy issues, self-efficacy for immunotherapy-related care, critical thinking ability, and background information were assessed in this survey. Independent T-test and one-way ANOVA were used to examine different levels of communication skill ability based on nurses having done oncology courses (yes vs. no) and education years (< 1 year, 1-3 years, and > 3 years), respectively. Spearman correlation was conducted to understand the relationships between communication skill ability and other variables. Among the 123 oncology nurses in the current study, the majority of them were female (98.4%), and most of them were employed at a hospital in the North (46.8%) of Taiwan. Most of them possessed a university degree (78.9%) and had at least 3 years of prior work experience (71.7%). Forty-three of the oncology nurses indicated in the survey that they had not received oncology nurses-related training. Those oncology nurses reported moderate to high levels of communication skill ability for immunotherapy issues (mean=4.24, SD=0.7, range 1-5). Nurses reported moderate levels of self-efficacy for immunotherapy-related care (mean=5.20, SD=1.98, range 0-10) and also had high levels of critical thinking ability (mean=4.76, SD=0.60, range 1-6). Oncology nurses who had received oncology training courses had significantly better communication skill ability than those who had not received oncology training. Oncology nurses who had higher work experience (1-3 years, or > 3 years) had significantly higher levels of communication skill ability for immunotherapy-related issues than those with lower work experience (<1 year). When those nurses reported better communication skill ability, they also had significantly better self-efficacy (r=.42, p<.01) and better critical thinking ability (r=.47, p<.01). Taken altogether, courses designed to improve communication skill ability for immunotherapy-related issues can make a significant impact in clinical settings. Communication skill ability for oncology nurses is the major factor associated with self-efficacy and critical thinking, especially for those with lower work experience (< 1 year).

Keywords: communication skills, critical thinking, immunotherapy, oncology nurses, self-efficacy

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Authors: Badryah Alshehri, Kevin Gormley, Gillian Prue, Karen McCutcheon

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In a disaster event, sharing patient information between the pre-hospital Emergency Medical Services (EMS) and Emergency Department (ED) hospitals is a complex process during which important information may be altered or lost due to poor communication. The aim of this study was to critically discuss the current evidence base in relation to communication between pre- EMS hospital and ED hospital professionals by the use of Information and Communication Systems (ICT). This study followed the systematic approach; six electronic databases were searched: CINAHL, Medline, Embase, PubMed, Web of Science, and IEEE Xplore Digital Library were comprehensively searched in January 2018 and a second search was completed in April 2020 to capture more recent publications. The study selection process was undertaken independently by the study authors. Both qualitative and quantitative studies were chosen that focused on factors that are positively or negatively associated with coordinated communication between pre-hospital EMS and ED teams in a disaster event. These studies were assessed for quality, and the data were analyzed according to the key screening themes which emerged from the literature search. Twenty-two studies were included. Eleven studies employed quantitative methods, seven studies used qualitative methods, and four studies used mixed methods. Four themes emerged on communication between EMTs (pre-hospital EMS and ED staff) in a disaster event using the ICT. (1) Disaster preparedness plans and coordination. This theme reported that disaster plans are in place in hospitals, and in some cases, there are interagency agreements with pre-hospital and relevant stakeholders. However, the findings showed that the disaster plans highlighted in these studies lacked information regarding coordinated communications within and between the pre-hospital and hospital. (2) Communication systems used in the disaster. This theme highlighted that although various communication systems are used between and within hospitals and pre-hospitals, technical issues have influenced communication between teams during disasters. (3) Integrated information management systems. This theme suggested the need for an integrated health information system that can help pre-hospital and hospital staff to record patient data and ensure the data is shared. (4) Disaster training and drills. While some studies analyzed disaster drills and training, the majority of these studies were focused on hospital departments other than EMTs. These studies suggest the need for simulation disaster training and drills, including EMTs. This review demonstrates that considerable gaps remain in the understanding of the communication between the EMS and ED hospital staff in relation to response in disasters. The review shows that although different types of ICTs are used, various issues remain which affect coordinated communication among the relevant professionals.

Keywords: emergency medical teams, communication, information and communication technologies, disaster

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Authors: Xijun Yu, Zhenzhen Li, Zupeng Jia

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This paper presents a new cell-centered Lagrangian scheme for two-dimensional compressible flow. The new scheme uses a semi-Lagrangian form of the Euler equations. The system of equations is discretized by Discontinuous Galerkin (DG) method using the Taylor basis in Eulerian space. The vertex velocities and the numerical fluxes through the cell interfaces are computed consistently by a nodal solver. The mesh moves with the fluid flow. The time marching is implemented by a class of the Runge-Kutta (RK) methods. A WENO reconstruction is used as a limiter for the RKDG method. The scheme is conservative for the mass, momentum and total energy. The scheme maintains second-order accuracy and has free parameters. Results of some numerical tests are presented to demonstrate the accuracy and the robustness of the scheme.

Keywords: cell-centered Lagrangian scheme, compressible Euler equations, RKDG method

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Authors: Abdul Halim Abdul, Wan Ismail Wan Yusoff

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The geological formation at Limau Manis Besar area, are consist of low grade metamorphic rock and undulating mountaineers, rugged terrain and the quite steeply 45 degree slope gradient. The objectives of this paper are present the methods and devices used in measurement of P-wave velocity to estimate the initial Shear Modulus (Go) in steady state and critical state soil consolidation. The relationship between SPT-N values and the Shear Modulus (Go) at very small strain is widely considered to be evaluated. Based on the seismic reflection survey, the constant (K) poroelastic theory, mean effectives stress and primer wave velocity (Vs) increase as the soil depth increase. The steady state and critical state, Degree of Soil Consolidation(U) concept is used to interpret the behavior of Shear Modulus (Go). The relationship between Consolidation Test and Seismic Reflection Survey is also discussed.

Keywords: geological setting, shear modulus, poroelastic theory, steady state and none steady state degree of soil consolidation, consolidation test

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Authors: Badr A. Al-Jehani

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Nowadays, contractor selection is a critical activity of the project owner. Selecting the right contractor is essential to the project manager for the success of the project, and this cab happens by using the proper selecting method. Traditionally, the contractor is being selected based on his offered bid price. This approach focuses only on the price factor and forgetting other essential factors for the success of the project. In this research paper, the Analytic Network Process (ANP) method is used as a decision tool model to select the most appropriate contractor. This decision-making method can help the clients who work in the construction industry to identify contractors who are capable of delivering satisfactory outcomes. Moreover, this research paper provides a case study of selecting the proper contractor among three contractors by using ANP method. The case study identifies and computes the relative weight of the eight criteria and eleven sub-criteria using a questionnaire.

Keywords: contractor selection, project management, decision-making, bidding

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Authors: A. Fakhri Makram, Marwa S. Alwazni, Al-Douri Yarub, Evan T. Salim, Hashim Uda, Chin C. Woei

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Lithium niobate (LiNbO₃) nanostructures are prepared on quartz substrate by the sol-gel method. They have been deposited with different molarity concentration and annealed at 500°C. These samples are characterized and analyzed by X-ray diffraction (XRD), Scanning Electron Microscope (SEM) and Atomic Force Microscopy (AFM). The measured results showed an importance increasing in molarity concentrations that indicate the structure starts to become crystal, regular, homogeneous, well crystal distributed, which made it more suitable for optical waveguide application.

Keywords: lithium niobate, morphological properties, thin film, pechini method, XRD

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Authors: Mamoona Rasheed, Salman Iqbal, Muhammad Abdullah

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Organizational capability, in terms of employees’ knowledge is valuable, and difficult to reproduce; and help to build sustainable competitive advantages. Knowledge capability is linked with human resource (HR) practices of an organization. This paper investigates the relationship between HR practices, knowledge management and organization capability. In an organization, employees play key role for the effective organizational performance by sharing their knowledge with management and co-workers that contributes towards organization capability. Pakistan being a developing country has different HR practices and culture. The business opportunities give rise to the discussion about the effect of HR practices on knowledge management and organization capability as innovation performance. An empirical study is conducted through questionnaires form the employees in private banks of Lahore, Pakistan. The data is collected via structured questionnaire with a sample of 120 cases. Data is analyzed using Structure Equation Modeling (SEM), and results are depicted using AMOS software. Results of this study are tabulated, interpreted and crosschecked with other studies. Findings suggest that there is a positive relationship of training & development along with incentives on knowledge management. On the other hand, employee’s participation has insignificant association with knowledge management. In addition, knowledge management has also positive association with organization capability. In line with the previous research, it is suggested that knowledge management is important for improving the organizational capability such as innovation performance and knowledge capacity of firm. Organization capability may improve significantly once specific HR practices are properly established and implemented by HR managers. This Study has key implications for knowledge management and innovation fields theoretically and practically.

Keywords: employee participation, incentives, knowledge management, organization capability, training and development

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Authors: M. Saeedi, R. Wuchner, K.-U. Bletzinger

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In order to study the aerodynamic performance of a semi-flexible membrane wing, Fluid-Structure Interaction simulations have been performed. The fluid problem has been modeled using two different approaches which are the numerical solution of the Navier-Stokes equations and the vortex panel method. Nonlinear analysis of the structural problem is performed using the Finite Element Method. Comparison between the two fluid solvers has been made. Aerodynamic performance of the wing is discussed regarding its lift and drag coefficients and they are compared with those of the equivalent rigid wing.

Keywords: CFD, FSI, Membrane wing, Vortex panel method

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Christine Lassen, Elizabeth Leonard, Matthew Oliver

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The management of trauma is often complex and outcomes dependent on clinical expertise, effective teamwork, and a supported trauma system. The implementation of a statewide trauma education program should be accessible to all clinicians who manage trauma, but this can be challenging due to diverse individual needs, trauma service needs and geography. The NSW Institute of Trauma and Injury Management (ITIM) is a government funded body, responsible for coordinating and supporting the NSW Trauma System. The aim of this presentation is to describe how education initiatives have been implemented across the state. Simulation: In 2006, ITIM developed a Trauma Team Training Course - aimed to educate clinicians on the technical and non-technical skills required to manage trauma. The course is now independently coordinated by trauma services across the state at major trauma centres as well as in regional and rural hospitals. ITIM is currently in the process of re-evaluating and updating the Trauma Team Training Course to allow for the development of new resources and simulation scenarios. Trauma Education Evenings: In 2013, ITIM supported major trauma services to develop trauma education evenings which allowed the provision of free education to staff within the area health service and local area. The success of these local events expanded to regional hospitals. A total of 75 trauma education evenings have been conducted within NSW, with over 10,000 attendees. Wed-Based Resources: Recently, ITIM commenced free live streaming of the trauma education evenings which have now had over 3000 live views. The Trauma App developed in 2015 provides trauma clinicians with a centralised portal for trauma information and works on smartphones and tablets that integrate with the ITIM website. This supports pre-hospital and bedside clinical decisions and allows for trauma care to be more standardised, evidence-based, timely, and appropriate. Online e-Learning modules have been developed to assist clinicians, reduce unwarranted clinical variation and provide up to date evidence based education. The modules incorporate clinically focused education content with summative and formative assessments. Conclusion: Since 2005, ITIM has helped to facilitate the development of trauma education programs for doctors, nurses, pre-hospital and allied health clinicians. ITIM has been actively involved in more than 100 specialized trauma education programs, seminars and clinical workshops - attended by over 12,000 staff. The provision of state-wide trauma education is a challenging task requiring collaboration amongst numerous agencies working towards a common goal – to provide easily accessible trauma education.

Keywords: education, simulation, team-training, trauma

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Authors: Mitra Savabi-Esfahani, Fariba Taleghani, Mahnaz Noroozi, Maryam Tabatabaeian, Elsebeth Lynge

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Breast cancer is a health concern in worldwide. All women have not adequate information about breast cancer, resulting in undetected some tumors until advanced stages. Therefore awareness of people was recommended as a strategy to control that. The aim of this study was to assess the effect of an educational intervention on women's knowledge and attitude about breast cancer and screening. This study was conducted in 2016 on 191 women. All women living in one of big cities were invited to enroll in training classes. Inclusion criteria consisted women who were 20 - 69 years and not participated in any educational intervention. The lecture with group discussion was used as educational methods. Data collection tool was a structured questionnaire which filled out before and after intervention. The reliability of the questionnaire was determined by Cronbach's alpha. The data were analyzed using SPSS software. The average age was 44/4 ± 11.5 and 42.6% of the women had obtained high school. Of the 191 women, 70(36.6%) and 76(39.8%) had low and medium level of knowledge respectively and half of them, 95(50%) had medium level of attitude in before intervention. There was significant difference between mean scores of knowledge and attitude before and after the intervention by Paired T test (p < 0/001). It seems applying effective educational interventions can increase knowledge and attitude women about breast cancer particularly in community that they have insufficient levels. Moreover, the lecture method along with group discussion can be proposed as effective and conventional methods for this purpose.

Keywords: attitude, breast cancer, educational intervention, knowledge

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Authors: Xinglu Nie, Feifei Tang, Chuntao Wei, Zhimin Ruan, Qianhong Zhu

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Current method of manual-style inspection can not fully meet the requirement of the urban rail transit security in China. In this paper, an intelligent inspection method using unmanned aerial vehicle (UAV) is utilized. A series of orthophoto of rail transit monitored area was collected by UAV, image correction and registration were operated among multi-phase images, then the change detection was used to detect the changes, judging the engineering activities and human activities that may become potential threats to the security of urban rail. Not only qualitative judgment, but also quantitative judgment of changes in the security control area can be provided by this method, which improves the objectives and efficiency of the patrol results. The No.6 line of Chongqing Municipality was taken as an example to verify the validation of this method.

Keywords: rail transit, control of protected areas, intelligent inspection, UAV, change detection

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Authors: Mondher Yahyaoui

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A generalized vortex lattice method for complex lifting surfaces with flap and aileron deflection is formulated. The method is not restricted by the linearized theory assumption and accounts for all standard geometric lifting surface parameters: camber, taper, sweep, washout, dihedral, in addition to flap and aileron deflection. Thickness is not accounted for since the physical lifting body is replaced by a lattice of panels located on the mean camber surface. This panel lattice setup and the treatment of different wake geometries is what distinguish the present work form the overwhelming majority of previous solutions based on the vortex lattice method. A MATLAB code implementing the proposed formulation is developed and validated by comparing our results to existing experimental and numerical ones and good agreement is demonstrated. It is then used to study the accuracy of the widely used classical vortex-lattice method. It is shown that the classical approach gives good agreement in the clean configuration but is off by as much as 30% when a flap or aileron deflection of 30° is imposed. This discrepancy is mainly due the linearized theory assumption associated with the conventional method. A comparison of the effect of four different wake geometries on the values of aerodynamic coefficients was also carried out and it is found that the choice of the wake shape had very little effect on the results.

Keywords: aileron deflection, camber-surface-bound vortices, classical VLM, generalized VLM, flap deflection

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Authors: Francis Zerd, Brian E. Moore, Atuganile E. Malango, Patrick W. Hosokawa, Kevin O. Lillehei, Laurence Lemery Mchome, D. Ryan Ormond

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Introduction: Since neuropathologic diagnosis in the developing world is hampered by limitations in technical infrastructure, trained laboratory personnel, and subspecialty-trained pathologists, the use of telepathology for diagnostic support, second-opinion consultations, and ongoing training holds promise as a means of addressing these challenges. This research aims to assess the utility of static teleneuropathology in improving neuropathologic diagnoses in low- and middle-income countries. Methods: Consecutive neurosurgical biopsy and resection specimens obtained at Muhimbili National Hospital in Tanzania between July 1, 2018, and June 30, 2019, were selected for retrospective, blinded static-image neuropathologic review followed by on-site review by an expert neuropathologist. Results: A total of 75 neuropathologic cases were reviewed. The agreement of static images and on-site glass diagnosis was 71% with strict criteria and 88% with less stringent criteria. This represents an overall improvement in diagnostic accuracy from 36% by general pathologists to 71% by a neuropathologist using static telepathology (or 76% to 88% with less stringent criteria). Conclusions: Telepathology offers a suitable means of providing diagnostic support, second-opinion consultations, and ongoing training to pathologists practicing in resource-limited countries. Moreover, static digital teleneuropathology is an uncomplicated, cost-effective, and reliable way to achieve these goals.

Keywords: neuropathology, resource-limited settings, static image, Tanzania, teleneuropathology

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Authors: Chong Wang, Kellem M. Soares, Luis E. Kosteski

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The problem of toughening in brittle materials reinforced by fibers is complex, involving all the mechanical properties of fibers, matrix, the fiber/matrix interface, as well as the geometry of the fiber. An appropriate method applicable to the simulation and analysis of toughening is essential. In this work, we performed simulations and analysis of toughening in brittle matrix reinforced by randomly distributed fibers by means of the discrete elements method. At first, we put forward a mechanical model of the contribution of random fibers to the toughening of composite. Then with numerical programming, we investigated the stress, damage and bridging force in the composite material when a crack appeared in the brittle matrix. From the results obtained, we conclude that: (i) fibers with high strength and low elasticity modulus benefit toughening; (ii) fibers with relatively high elastic modulus compared to the matrix may result in considerable matrix damage (spalling effect); (iii) employment of high-strength synthetic fiber is a good option. The present work makes it possible to optimize the parameters in order to produce advanced ceramic with desired performance. We believe combination of the discrete element method (DEM) with the finite element method (FEM) can increase the versatility and efficiency of the software developed.

Keywords: bridging stress, discrete element method, fiber reinforced composites, toughening

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Authors: Anneke Van Biljon

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Background: Exercise is a primary form of preventing and improving cardiometabolic disease risk factors; however specific exercise variables and their associated health benefits in children are inconclusive. A preliminary study revealed that different exercise variables may improve particular cardiometabolic health benefits. Objectives: This study further investigated the specific cardiometabolic health benefits associated with three isocaloric exercise interventions set at different intensities. Methods: Hundred-and-twenty (n = 120) participants between the ages of 10 – 14 years old were assigned to four different study groups 1. High intensity interval training (HIIT) at > 80% MHR 2. Moderate intensity continuous training (MICT) at 65% – 70% MHR 3. Alternative intensities (ALT) of HIIT and MICT 4. Control group. Exercise interventions were designed to generate isocaloric workloads of ~154.77 kcal per session, three times per week for five weeks. The one-way ANOVA test established comparisons between group means. Post hoc tests were calculated to determine specific group differences. Results: Although, all exercise groups improved cardiometabolic health, the MICT group showed greater improvements in fasting glucose (-9.30%), whereas cardiorespiratory fitness increased most by 31.33% (p = 0.000) within the HIIT group. Finally, ALT group recorded overall superior and additional cardiometabolic health benefits compared with both MICT and HIIT groups. Conclusion: The findings of this study indicate that superior benefits may be elicited when combining and alternating MICT and HIIT. These results provide specific exercise recommendations for achieving optimal and substantial cardiometabolic health benefits in children which will contribute towards achieving the health-related Sustainable Development Goals for 2030.

Keywords: cardiometabolic disease risk factors, exercise, pediatrics, interventions

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Morteza Giti

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As online shopping is becoming increasingly popular, computing customer lifetime value for better knowing the customers is also gaining more importance. Two distinct factors that can affect the value of a customer in the context of online shopping is the number of returned orders and payment method. Returned orders are those which have been shipped but not collected by the customer and are returned to the store. Payment method refers to the way that customers choose to pay for the price of the order which are usually two: Pre-pay and Cash-on-delivery. In this paper, a novel model called RFMSP is presented to calculated the customer lifetime value, taking these two parameters into account. The RFMSP model is based on the common RFM model while adding two extra parameter. The S represents the order status and the P indicates the payment method. As a case study for this model, the purchase history of customers in an online shop is used to compute the customer lifetime value over a period of twenty months.

Keywords: RFMSP model, AHP, customer lifetime value, k-means clustering, e-commerce

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

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A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml^-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 10³ l mol^-1cm^-1 and 0.0125 μg cm^-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: solvent extraction, PMPT, Palladium (II), spectrophotometry

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Ntokozo Dennis Ndwandwe

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The aim of the study was to explore the barriers facing the implementation of peace education as a strategy to combat violence in selected secondary schools in the Western Cape Province of South Africa. The problem that motivated this enquiry was the absence of stable peace and the increase of incidents of violence in schools. A qualitative approach was followed when conducting the study, and small samples of three case studies of secondary schools were used. Method used in collecting data consisted of semi-structured interviews; focus group interviews and observation. The participants consisted of the program manager for Quaker for Peace Centre (QPC), three principals, nine teachers, and fifteen learners. Data were analysed by transcribing, organising, marking by hand and coding that produced labels that allowed key points to be highlighted. Findings revealed that the effective implementation of peace education was being constrained by factors such as financial constraints, inadequate time allocated, lack of parental involvement, over work-loaded teachers, negative attitude and other societal influences. It is recommended that teachers should receive an ongoing training for peace education. Therefore, the government should prioritise and provide funds for peace education. In addition, parental involvement should be improved in order to enhance the implementation of peace education in selected secondary schools.

Keywords: barriers, implementation, conflict, peace, peace education, conflict resolution, violence

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Authors: Laure Wiest, Barbara Giroud, Azziz Assoumani, Francois Lestremau, Emmanuelle Vulliet

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Due to their production at high tonnages and their extensive use, surfactants are contaminants among those determined at the highest concentrations in wastewater. However, analytical methods and data regarding their occurrence in river water are scarce and concern only a few families, mainly anionic surfactants. The objective of this study was to develop an analytical method to extract and analyze a wide variety of surfactants in a minimum of steps, with a sensitivity compatible with the detection of ultra-traces in surface waters. 27 substances, from 12 families of surfactants, anionic, cationic and non-ionic were selected for method optimization. Different retention mechanisms for the extraction by solid phase extraction (SPE) were tested and compared in order to improve their detection by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The best results were finally obtained with a C18 grafted silica LC column and a polymer cartridge with hydrophilic lipophilic balance (HLB), and the method developed allows the extraction of the three types of surfactants with satisfactory recoveries. The final analytical method comprised only one extraction and two LC injections. It was validated and applied for the quantification of surfactants in 36 river samples. The method's limits of quantification (LQ), intra- and inter-day precision and accuracy were evaluated, and good performances were obtained for the 27 substances. As these compounds have many areas of application, contaminations of instrument and method blanks were observed and considered for the determination of LQ. Nevertheless, with LQ between 15 and 485 ng/L, and accuracy of over 80%, this method was suitable for monitoring surfactants in surface waters. Application on French river samples revealed the presence of anionic, cationic and non-ionic surfactants with median concentrations ranging from 24 ng/L for octylphenol ethoxylates (OPEO) to 4.6 µg/L for linear alkylbenzenesulfonates (LAS). The analytical method developed in this work will therefore be useful for future monitoring of surfactants in waters. Moreover, this method, which shows good performances for anionic, non-ionic and cationic surfactants, may be easily adapted to other surfactants.

Keywords: anionic surfactant, cationic surfactant, LC-MS/MS, non-ionic surfactant, SPE, surface water

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Authors: Pranvera Shehaj

Abstract:

Unlike any prior analysis on the withholding tax rates negotiated in tax treaties, this study looks at the treaty heterogeneity content, by investigating the impact of the residence country’s double tax relief method and of tax-sparing agreements, on the difference between developing countries’ domestic withholding taxes on dividends on one side, and treaty negotiated withholding taxes at source on portfolio dividends on the other side. Using a dyadic panel dataset of asymmetric double tax treaties between 2005 and 2019, this study suggests first that the difference between domestic and negotiated WHTs on portfolio dividends is higher when the OECD member uses the credit method, as compared to when it uses the exemption method. Second, results suggest that the inclusion of tax-sparing provisions vanishes the positive effect of the credit method at home on the difference between domestic and negotiated WHTs on portfolio dividends, incentivizing developing countries to negotiate higher withholding taxes.

Keywords: double tax treaties, asymmetric investments, withholding tax, dividends, double tax relief method, tax sparing

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Authors: Aasaithambi Kalaiselvi, Michael Gabriel Paulraj, Ekambaram Nakkeeran

Abstract:

Emergences of mosquito vector-borne diseases are considered as a perpetual problem globally in tropical countries. The outbreak of several diseases such as chikungunya, zika virus infection and dengue fever has created a massive threat towards the living population. Frequent usage of synthetic insecticides like Dichloro Diphenyl Trichloroethane (DDT) eventually had its adverse harmful effects on humans as well as the environment. Since there are no perennial vaccines, prevention, treatment or drugs available for these pathogenic vectors, WHO is more concerned in eradicating their breeding sites effectively without any side effects on humans and environment by approaching plant-derived natural eco-friendly bio-insecticides. The aim of this study is to investigate the larvicidal potency of Cinnamomum verum essential oil (CEO) loaded niosomes. Cholesterol and surfactant variants of Span 20, 60 and 80 were used in synthesizing CEO loaded niosomes using Transmembrane pH gradient method. The synthesized CEO loaded niosomes were characterized by Zeta potential, particle size, Fourier Transform Infrared Spectroscopy (FT-IR), GC-MS and SEM analysis to evaluate charge, size, functional properties, the composition of secondary metabolites and morphology. The Z-average size of the formed niosomes was 1870.84 nm and had good stability with zeta potential -85.3 meV. The entrapment efficiency of the CEO loaded niosomes was determined by UV-Visible Spectrophotometry. The bio-potency of CEO loaded niosomes was treated and assessed against gram-positive (Bacillus subtilis) and gram-negative (Escherichia coli) bacteria and fungi (Aspergillus fumigatus and Candida albicans) at various concentrations. The larvicidal activity was evaluated against II to IV instar larvae of Aedes aegypti, Anopheles stephensi and Culex quinquefasciatus at various concentrations for 24 h. The mortality rate of LC₅₀ and LC₉₀ values were calculated. The results exhibited that CEO loaded niosomes have greater efficiency against mosquito larvicidal activity. The results suggest that niosomes could be used in various applications of biotechnology and drug delivery systems with greater stability by altering the drug of interest.

Keywords: Cinnamomum verum, niosomes, entrapment efficiency, bactericidal and fungicidal, mosquito larvicidal activity

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Authors: Payel Das, Gnaneshwar Nelakanti

Abstract:

In this paper we analyse the iterated discrete Legendre Galerkin method for Fredholm-Hammerstein integral equations with smooth kernel. Using sufficiently accurate numerical quadrature rule, we obtain superconvergence rates for the iterated discrete Legendre Galerkin solutions in both infinity and $L^2$-norm. Numerical examples are given to illustrate the theoretical results.

Keywords: hammerstein integral equations, spectral method, discrete galerkin, numerical quadrature, superconvergence

Procedia PDF Downloads 457

Authors: Eng. M. Ahmed, A. Ibrahim, M. Ashour

Abstract:

One of the major concerns facing dam is the repair of their structures to prevent the seepage under them. In previous years, many existing dams have been treated by grouting, but with varying degrees of success. One of the major reasons for this erratic performance is the unsuitable selection of the grouting materials to reduce the seepage. Grouting is an effective way to improve the engineering properties of the soil and strengthen of the permeability of the soil to reduce the seepage. The purpose of this paper is to focus on the efficiency of current available grouting materials and techniques from construction, environmental and economical point of view. The seepage reduction usually accomplished by either chemical grouting or cementious grouting using ultrafine cement. In addition, the study shows a comparison between grouting materials according to their degree of permeability reduction and cost. The application of seepage reduction is based on the permeation grouting using grout curtain installation. The computer program (SEEP/W) is employed to model a dam rested on sandy soil, using grout curtain to reduce seepage quantity and hydraulic gradient by different grouting materials. This study presents a relationship that takes into account the permeability of the soil, grout curtain spacing and a new performance parameter that can be used to predict the best selection of grouting materials for seepage reduction.

Keywords: seepage, sandy soil, grouting, permeability

Procedia PDF Downloads 349

Authors: Shubham Jaiswal

Abstract:

In this study, the numerical solution of two-dimensional solute transport system in a homogeneous porous medium of finite-length is obtained. The considered transport system have the terms accounting for advection, dispersion and first-order decay with first-type boundary conditions. Initially, the aquifer is considered solute free and a constant input-concentration is considered at inlet boundary. The solution is describing the solute concentration in rectangular inflow-region of the homogeneous porous media. The numerical solution is derived using a powerful method viz., spectral collocation method. The numerical computation and graphical presentations exhibit that the method is effective and reliable during solution of the physical model with complicated boundary conditions even in the presence of reaction term.

Keywords: two-dimensional solute transport system, spectral collocation method, Chebyshev polynomials, Chebyshev differentiation matrix

Procedia PDF Downloads 217