Search results for: velocity prediction program

Authors: Sumaira Zafar, Arjumand Zaidi, Muhammad Arslan Hafeez

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Indus Basin Irrigation System (IBIS) is the largest contiguous irrigation system of the world comprising Indus River and its tributaries, canals, distributaries, and watercourses. A big challenge faced by IBIS is transmission losses through seepage and leaks that account to 41 percent of the total water derived from the river and about 40 percent of that is through watercourses. Irrigation system rehabilitation programs in Pakistan are focused on improvement of canal system at the watercourse level (tertiary channels). Under these irrigation system management programs more than 22,800 watercourses have been improved or lined out of 43,000 (12,900 Kilometers) watercourses. The evaluation of the improvement work is required at this stage to testify the success of the programs. In this paper, emerging technologies of GIS and satellite remote sensing are used for impact assessment of watercourse rehabilitation work in Sindh. To evaluate the efficiency of the improved watercourses, few parameters are selected like soil moisture along watercourses, availability of water at tail end and changes in cultivable command areas. Improved watercourses details and maps are acquired from National Program for Improvement of Watercourses (NPIW) and Space and Upper Atmospheric Research Commission (SUPARCO). High resolution satellite images of Google Earth for the year of 2004 to 2013 are used for digitizing command areas. Temporal maps of cultivable command areas show a noticeable increase in the cultivable land served by improved watercourses. Field visits are conducted to validate the results. Interviews with farmers and landowners also reveal their overall satisfaction in terms of availability of water at the tail end and increased crop production.

Keywords: geospatial, impact assessment, watercourses, GIS, remote sensing, seepage, canal lining

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Authors: Erinetta P. Anjani, Karina Mariz, Rifqi K. Fathianto

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While Islam teaches its’ followers to be mindful of God’s creation, including the environment, Indonesia as one of the world’s largest Muslim country, is now also world’s second-largest plastic waste contributor. The problem of waste is a complicated matter in Indonesia and is worsening because many landfills are now on verge of overcapacity. The causes of this problem are at least due to two things. First is Indonesia’s bad waste management. Second, people’s low of eco-literacy, as can be seen in massive use of non-degradable materials, low rate of waste separation, low rate of recycling and up cycling, whereas households are the largest source of waste in Indonesia. Mostly dealing with patriarchal culture, women in Indonesia play big and important role in their households, from family matter to household management (including waste management), to economic matter. Uniquely, the majority of Muslim women in Indonesia are engaged in -arisan- women social gathering or in -majelis ta’lim- women community in Islamic prayer, which serves as a social mechanism. As many NGOs are working on tackling environmental issues by raising awareness in order for the people to adapt a more environmentally-friendly household management practices, the problem of waste in Indonesia is meeting a bright light. Using qualitative data and descriptive analysis, the following is a proposal for a program intended to spread eco-literacy for waste management to women in Indonesia through their social gathering in order for them to gain awareness and start implementing eco-actions in their households. We attempt Waste4Change, a social company which provides environmentally-friendly waste management services, to reach women with modules that consist of environmental education, trainings, and workshops. We will then monitor and counsel the women to make sure if the lesson is going to be fully applied in their houses. The program will take place nearby University of Indonesia, Depok, West Java.

Keywords: eco-literacy, environmental education, household waste management, Muslim women social gathering, Waste4Change

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Authors: Yuki Matsumoto, Yuma Ishimoto

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Cognitive Behavior Therapy (CBT) with children has shown effective application to various problems such as anxiety and depression. Although there are barriers to access to mental health services including lack of professional services in communities and parental concerns about stigma, school has a significant role to address children’s health problems. Schools are regarded as a suitable arena for prevention and early intervention of mental health problems. In this line, CBT can be adaptable to school education and useful to enhance students’ social and emotional skills. However, Japanese school curriculum is rigorous so as to limit available time for implementation of CBT in schools. This paper describes Brief Cognitive Behavior Therapy (BCBT) with children in a Japanese school setting. The program has been developed in order to facilitate acceptability of CBT in schools and aimed to enhance students’ skills to manage anxiety and difficult behaviors. The present research used a single arm design in which 30 students aged 9-10 years old participated. The authors provided teachers a CBT training workshop (two hours) at two primary schools in Tokyo metropolitan area and recruited participants in the research. A homeroom teacher voluntarily delivered a 6-session BCBT program (15 minutes each) in classroom periods which is called as Kaerinokai, a meeting before leaving school. Students completed a questionnaire sheet at pre- and post-periods under the supervision of the teacher. The sheet included the Spence Child Anxiety Scale (SCAS), the Depression Self-Rating Scale for Children (DSRS), and the Strengths and Difficulties Questionnaire (SDQ). The teacher was asked for feedback after the completion. Significant positive changes were found in the total and five of six sub-scales of the SCAS and the total difficulty scale of the SDQ. However, no significant changes were seen in Physical Injury Fear sub-scale of the SCAS, in the DSRS or the Prosocial sub-scale of the SDQ. The effect sizes are mostly between small and medium. The teacher commented that the program was easy to use and found positive changes in classroom activities and personal relationships. This preliminary research showed the feasibility of the BCBT in a school setting. The results suggest that the BCBT offers effective treatment for reduction in anxiety and in difficult behaviors. There is a good prospect of the BCBT suggesting that BCBT may be easier to be delivered than CBT by Japanese teachers to promote child mental health. The study has limitations including no control group, small sample size, or a short teacher training. Future research should address these limitations.

Keywords: brief cognitive behavior therapy, cognitive behavior therapy, mental health services in schools, teacher training workshop

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Authors: Hamad M. Alhajeri

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Swirling chamber is a promising cooling method for heavily thermally loaded parts like turbine blades due to the additional circumferential velocity and therefore improved turbulent mixing of the fluid. This paper investigates numerically the effect of turbulence model on the heat convection of the swirling chamber. Grid independence analysis is conducted to obtain the proper grid dimension. The work validated with experimental data available in the literature. Flow analysis using improved delayed detached eddy simulation turbulence model and Reynolds averaged Navier-Stokes k-ɛ turbulence model is carried. The flow characteristic near the exit is reformed when improved delayed detached eddy simulation model used.

Keywords: gas turbine, Nusselt number, flow characteristics, heat transfer

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Authors: Wei Qu, Cassandra Agius, Nikki Varvazovsky, Angela Meade

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The goals of the case study are to address the importance of early diagnosis of osmotic demyelination syndrome (ODS) and to analyse the types, duration, and intensities of the rehabilitation program to promote neurological and functional recovery. It can be associated with biphasic course of disease and severe neurological and neuropsychiatric symptoms. Although a few treatment modalities, such as plasmapheresis, immunoglobulin therapy, steroid, and thyrotrophin-releasing hormone, have been suggested, there is no effective treatment for ODS. The overall prognosis of established ODS is generally poor. A high proportion of patients have a severe permanent disability, which has led to social, economic, and emotional burdens to carers and societies. In this case, a 69-year-old retired pensioner with chronic alcoholism was admitted to the hospital with a reduced level of consciousness and tonic-clonic seizure. He had severe hyponatraemia (serum sodium 118 mmol/L) and hypokalemia (serum potassium 2.8 mmol/L). He was treated with anticonvulsants, 150ml 3% hypertonic saline over one hour, and 40 mmol potassium chloride over one hour, and his sodium was increased by 11 mmol/L in the first 24 hours. However, he had worsened neurological symptoms with quadriplegia, dysphagia, anarthria, and confusion, and the radiological features suggested the diagnosis of ODS. He had minimal neurological recovery during the first four weeks of hospital admission. He was treated with seven weeks of a multi-disciplinary intensive rehabilitation program. On discharge, he had made a significant cognitive and functional recovery and could mobilize independently without a walking aid. In conclusion, ODS can still occur despite correcting sodium following the current clinical guidelines. Patients with severe neurological deficits in the context of osmotic demyelination syndrome would benefit from intensive rehabilitation to facilitate their functional improvement and to promote their quality of life.

Keywords: osmotic demyelination syndrome, hyponatremia, central pontine and extrapontine myelinolysis, rehabilitation

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Authors: Kholod Hajo

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In this study COMSOL Multiphysics was used to design lateral flow biosensors (LFBs) which provide advantages in low cost, simplicity, rapidity, stability and portability thus making LFBs popular in biomedical, agriculture, food and environmental sciences. This study was focused on simulation model of biosensor based on gold nanoparticles (GNPs) designed using software package (COMSOL Multiphysics), the magnitude of the laminar velocity field in the flow cell, concentration distribution in the analyte stream and surface coverage of adsorbed species and average fractional surface coverage of adsorbed analyte were discussed from the model and couples of suggestion was given in order to functionalize GNPs and to increase the accuracy of the biosensor design, all above were obtained acceptable results.

Keywords: model, gold nanoparticles, biosensor, COMSOL Multiphysics

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Authors: Motahar Reza, Rajni Chahal, Neha Sharma

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This article addresses the boundary layer flow and heat transfer of Casson fluid over a nonlinearly permeable stretching surface with chemical reaction in the presence of variable magnetic field. The effect of thermal radiation is considered to control the rate of heat transfer at the surface. Using similarity transformations, the governing partial differential equations of this problem are reduced into a set of non-linear ordinary differential equations which are solved by finite difference method. It is observed that the velocity at fixed point decreases with increasing the nonlinear stretching parameter but the temperature increases with nonlinear stretching parameter.

Keywords: boundary layer flow, nonlinear stretching, Casson fluid, heat transfer, radiation

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Authors: Manana Lobzhanidze, Marine Kobalava, Lali Chikviladze

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The global pandemic crisis has had a significant impact on educational migration, substantially limiting young people’s access to education abroad. Therefore, it became necessary to study the economic, demographic, social, cultural and other factors associated with educational migration, to identify the economic and political challenges of educational migration and to develop recommendations. The aim of the research is to study the effects of the atypical crisis on educational migration and to make recommendations on effective migration opportunities based on the identification of economic and policy challenges in this area. Bibliographic research is used to assess the effects of the impact of the atypical crisis on educational migration presented in the papers of various scholars. Against the background of the restrictions imposed during the COVID19 pandemic, migration rates have been analyzed, endogenous and exogenous factors affecting educational migration have been identified. Quantitative and qualitative research of students and graduates of TSU Economics and Business Faculty is conducted, the results have been processed by SPSS program, the factors hindering educational migration and the challenges have been identified. The Internet and digital technologies have been shown to play a vital role in alleviating the challenges posed by the COVID-19 pandemic, however, lack of Internet access and limited financial resources have played a disruptive role in the educational migration process. The analysis of quantitative research materials revealed the problems of educational migration caused by the atypical crisis, while some issues were clarified during the focus group meetings. The following theoretical-methodological approaches were used during the research: a bibliographic research, analysis, synthesis, comparison, selection-grouping are used; Quantitative and qualitative research has been carried out, the results have been processed by SPSS program. The article presents the consequences of the atypical crisis for educational migration, identifies the main economic and policy challenges in the field of educational migration, and develops appropriate recommendations to overcome them.

Keywords: educational migration, atypical crisis, economic-political challenges, educational migration factors

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Authors: Jerome Nyameh

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The most valuable asset in the existence of organization is the employees and their ability in maintain appreciable level of performance which support the goal of the organization and the ability to do that depend largely on the organizational culture and culture has been considered most currently as the factor that relate positively to organizational excellence and sustainable employee’s performance over the period of time An employee engagement program will not go far without first establishing the organizational culture that is required to support sustainability. This means integrating sustainability into the overall employee’s performance, with clear vision, goals and metrics. It means having strong culture and a collaborative governance structure that has been develop as a ways of doing things in the organization for decision making and resource allocation. It requires a rewards and recognition program to support and reinforce sustainability behaviors. With such a culture in place, organization will be able to develop a strategy that fully engages employees, while fully realizing the benefits of their contributions. The study investigated empirically the role of organizational culture building sustainable employee’s performance using Zenith bank PLC a model where organizational culture will build sustainable employees performance strategy for a lasting actualization of organizational was developed. In order to achieve the research objectives of (i) to assess how organizational culture can build sustainable employee’s performance (ii) to analyze the gap that exists between organizational culture and sustainable employee’s performance in the organization, a survey questionnaires of 20 items was administered to sixty respondents. The findings of this study have practical implications for organizational leaders, managers and employees, and their organizations, particularly commercial banks in Nigeria, besides offering scope for further research in the area of organizational culture and sustainable employee’s performance. It will also show a significance and positive relationship that exist between organizational culture and sustainable employee’s performance, as means of building viable organization with cultural uniqueness and excellence performance in the world of competition.

Keywords: organizational culture, sustainable employee’s performance, organizations, Zenith Bank PLC Nigeria

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Authors: Mohit Kumar

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Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

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With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han

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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.

Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model

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Authors: Zohreh Sheidaei, Farhad Sadegh Moghanlou, Rahim Vesal

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Diseases related to leg venous system are common worldwide. An incompetent vein with deformed wall and insufficient valves affects flow field of blood and disrupts the process of blood circulating system. Having enough knowledge about the flow field through veins will help find new ways to cure the related diseases. In the present study, blood flow around a leaflet valve of a perforating vein is investigated numerically by Finite Element Method. Flow behavior and vortexes, generated around the leaflet valves, are studied considering valve opening percentage. Obtained velocity and pressure fields show mechanical stresses on vein wall and these valves and consequently introduce the regions susceptible to deformation.

Keywords: fluid flow, leaflet valve, numerical investigation, perforating vein

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Authors: Raoudha Chaabane, Faouzi Askri, Sassi Ben Nasrallah

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A new numerical algorithm is developed to solve coupled convection-radiation heat transfer in a two dimensional enclosure. Radiative heat transfer in participating medium has been carried out using the control volume finite element method (CVFEM). The radiative transfer equations (RTE) are formulated for absorbing, emitting and scattering medium. The density, velocity and temperature fields are calculated using the two double population lattice Boltzmann equation (LBE). In order to test the efficiency of the developed method the Rayleigh Benard convection with and without radiative heat transfer is analyzed. The obtained results are validated against available works in literature and the proposed method is found to be efficient, accurate and numerically stable.

Keywords: participating media, LBM, CVFEM- radiation coupled with convection

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Authors: Md. Abud Darda

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Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability.

Keywords: diffusion models, energy forecast, natural gas, nonlinear production

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: Ana Maria Girotti Sperandio, Jussara Conceição Guarnieri, Lauro Luiz Francisco Filho, Ana Claudia Martins Alves, Adriana Aparecida Carneiro Rosa

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The urban planning of a city should contemplate the construction of healthy spaces to provide quality of life for people. In a Brazilian municipality located 180 km from the capital of São Paulo with around 27,000 thousand inhabitants, the federal government made possible a program that allows the improvement of the quality of life of the inhabitants through the practice of physical activity. To describe health promotion strategies in the city that collaborate in the reduction of chronic non-communicable diseases (CDNT) and the improvement the quality of its residents. Considering the CDNT as a fundamental public health concern in different countries, the methodology of this work considered the different actions of health promotion that occurred in the city for the implementation of the Polo Health Academy with the objective of increasing the population's access to places that could develop targeted physical activities. As an instrument, it used records of participants of this academy such as: assessment sheets, evolution, photos, filming and daily reports of physical activities. Results: The implantation and implementation process of the Polo Health Academy in the city of Conchal / SP / Brazil was in accordance with the principles and values of the National Health Promotion Policy (PNaPS) in Brazil and with the city statute, that provides improvement in the quality of life of the Brazilian population. An increase was observed in the number of participants in different hours practicing physical activities in the territory linked to one of the five Health Units, showing the program provides that happiness and well-being to the students. The Brazilian health promotion policy, combined with the city’s development policy, provides the population with access to programs that stimulate the reduction of CDNTs, confirming the urban planning of a healthy city.

Keywords: health city, health promotion, physical activity, urban planning

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Authors: Rajlakshmi Guha, Sajjad Ansari, Shazia Nasreen, Hirak Banerjee, Jiaul Paik

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Dyslexia is a neurocognitive disorder, affecting around fifteen percent of the Indian population. The symptoms include difficulty in reading alphabet, words, and sentences. This can be difficult at the phonemic or recognition level and may further affect lexical structures. Therapeutic intervention of dyslexic children post assessment is generally done by special educators and psychologists through one on one interaction. Considering the large number of children affected and the scarcity of experts, access to care is limited in India. Moreover, unavailability of resources and timely communication with caregivers add on to the problem of proper intervention. With the development of Educational Technology and its use in India, access to information and care has been improved in such a large and diverse country. In this context, this paper proposes an ICT enabled home-based intervention program for dyslexic children which would support the child, and provide an interactive interface between expert, parents, and students. The paper discusses the details of the database design and system layout of the program. Along with, it also highlights the development of different technical aids required to build out personalized android applications for the Indian dyslexic population. These technical aids include speech database creation for children, automatic speech recognition system, serious game development, and color coded fonts. The paper also emphasizes the games developed to assist the dyslexic child on cognitive training primarily for attention, working memory, and spatial reasoning. In addition, it talks about the specific elements of the interactive intervention tool that makes it effective for home based intervention of dyslexia.

Keywords: Android applications, cognitive training, dyslexia, intervention

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Authors: Abdelraheem M. Aly, Minh Tuan Nguyen, Sang-Wook Lee

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The incompressible smoothed particle hydrodynamics (ISPH) is used to simulate impact free surface flows. In the ISPH, pressure is evaluated by solving pressure Poisson equation using a semi-implicit algorithm based on the projection method. The current ISPH method is applied to simulate dam break flow over an inclined plane with different inclination angles. The effects of inclination angle in the velocity of wave front and pressure distribution is discussed. The impact of circular cylinder over water in tank has also been simulated using ISPH method. The computed pressures on the solid boundaries is studied and compared with the experimental results.

Keywords: incompressible smoothed particle hydrodynamics, free surface flow, inclined plane, water entry impact

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Authors: Lei Li, Ming M. Chai, Xiao X. Lu, Jia W. Wang

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The mixing process of two liquid layers in a cylindrical container includes the upper liquid with higher density rushing into the lower liquid with lighter density, the lower liquid rising into the upper liquid, meanwhile the two liquid layers having interactions with each other, forming vortices, spreading or dispersing in others, entraining or mixing with others. It is a complex process constituted of flow instability, turbulent mixing and other multiscale physical phenomena and having a fast evolution velocity. In order to explore the mechanism of the process and make further investigations, some experiments about the interfacial instability and mixing behavior between two liquid layers bounded in different volumes are carried out, applying the planar laser induced fluorescence (PLIF) and the high speed camera (HSC) techniques. According to the results, the evolution of interfacial instability between immiscible liquid develops faster than theoretical rate given by the Rayleigh-Taylor Instability (RTI) theory. It is reasonable to conjecture that some mechanisms except the RTI play key roles in the mixture process of two liquid layers. From the results, it is shown that the invading velocity of the upper liquid into the lower liquid does not depend on the upper liquid's volume (height). Comparing to the cases that the upper and lower containers are of identical diameter, in the case that the lower liquid volume increases to larger geometric space, the upper liquid spreads and expands into the lower liquid more quickly during the evolution of interfacial instability, indicating that the container wall has important influence on the mixing process. In the experiments of miscible liquid layers’ mixing, the diffusion time and pattern of the liquid interfacial mixing also does not depend on the upper liquid's volumes, and when the lower liquid volume increases to larger geometric space, the action of the bounded wall on the liquid falling and rising flow will decrease, and the liquid interfacial mixing effects will also attenuate. Therefore, it is also concluded that the volume weight of upper heavier liquid is not the reason of the fast interfacial instability evolution between the two liquid layers and the bounded wall action is limited to the unstable and mixing flow. The numerical simulations of the immiscible liquid layers’ interfacial instability flow using the VOF method show the typical flow pattern agree with the experiments. However the calculated instability development is much slower than the experimental measurement. The numerical simulation of the miscible liquids’ mixing, which applying Fick’s diffusion law to the components’ transport equation, shows a much faster mixing rate than the experiments on the liquids’ interface at the initial stage. It can be presumed that the interfacial tension plays an important role in the interfacial instability between the two liquid layers bounded in finite volume.

Keywords: interfacial instability and mixing, two liquid layers, Planar Laser Induced Fluorescence (PLIF), High Speed Camera (HSC), interfacial energy and tension, Cahn-Hilliard Navier-Stokes (CHNS) equations

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Authors: Chang Li Yu

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Resistances commonly happened during sexual offenders treatment program (SOTP), and removing resistances was one of the treatment goals on it. Studies concerning treatment effectiveness relied on pre- and post-treatment evaluations, however, no significant difference on resistance revealed after treatment, and the above consequences generally contributed to the low motivation for change instead. Therefore, the aim of this study was to investigate the resistance across each stage of change among sexual offenders (SO). The present study recruited prisoned SO in Taiwan, excluding those with literacy difficulties; finally, 272 participants were included. Of all participants completed revised version of URICA (University of Rhode Island Change Assessment) and resistance scale specifically for SO. The former included four stages of change: pre-contemplation (PC), contemplation (C), action (A), and maintain (M); the later composed eight types of resistance: system blaming, victims blaming, problems with treatment alliance, social justification, hopelessness, isolation, psychological reactance, and passive reactance. Both of the instruments were with well reliability and validity. Descriptive statistics and ANOVA were performed. All of 272 participants, age under 25 were 18(6.6%), 25-39 were 133(48.9%), 40-54 were 102(37.5%), and age over 55 were 19(7.0%); college level and above were 53(19.5%), high school level were 110(40.4%), and under high school level were 109(40.1%); first offended were 117(43.0%), and recidivist were 23(8.5%). Further deleting data with missing values and invalid questionnaires, SO with stage of change on PC were 43(18.9%), C were 109(47.8%), A were 70(30.7%), and on M were 6(2.6%). One-way ANOVA showed significant differences on every kind of resistances, excepting isolation and passive reactance. Post-hoc analysis showed that SO with different stages had their main resistance. There are two contributions to the present study. First, this study provided a clinical and theoretical measurement of evaluation that was never used in the past. Second, this study used an evidence-based methodology to prove a clinical perspective differed from the past, suggesting that resistances to treatment on SO appear the whole therapeutic process, when SO progress into the next stage of change, clinicians have to deal with their main resistance for working through the therapy.

Keywords: resistance, sexual offenders treatment program (SOTP), motivation for change, prisoned sexual offender

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Authors: Arash Ahmadi, Amirreza Kavousizadeh, Sanaz Heidarzadeh

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Stage-discharge curve is one of the conventional methods for continuous river flow measurement. In this paper, an innovative approach is proposed for predicting the stage-discharge relationship using the application of isovel contours. Using the proposed method, it is possible to estimate the stage-discharge curve in the whole section with only using discharge information from just one arbitrary water level. For this purpose, multivariate relationships are used to determine the mean velocity in a cross-section. The unknown exponents of the proposed relationship have been obtained by using the second version of the Strength Pareto Evolutionary Algorithm (SPEA2), and the appropriate equation was selected by applying the TOPSIS (Technique for Order Preferences by Similarity to an Ideal Solution) approach. Results showed a close agreement between the estimated and observed data in the different cross-sections.

Keywords: rating curves, SPEA2, natural rivers, bed roughness distribution

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Authors: Zaw Min Tun

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The paper focuses on the spacecraft’s trajectory transition from interplanetary hyperbolic orbit to the planet’s orbit using the aerobraking in the atmosphere of the planet. A considerable mass of fuel is consumed during the spacecraft transition from the planet’s gravitation assist trajectory into the planet’s satellite orbit. To reduce the fuel consumption in this transition need to slow down the spacecraft’s velocity in the planet’s atmosphere and reduce its orbital transition time. The paper is devoted to the use of the planet’s atmosphere for slowing down the spacecraft during its transition into the satellite orbit with uncertain atmospheric parameters. To reduce the orbital transition time of the spacecraft is controlled by the change of attack angles’ values at the aerodynamic deceleration path and adjusting the minimum flight altitude of the spacecraft at the pericenter of the planet’s upper atmosphere.

Keywords: aerobraking, atmosphere of the planet, orbital transition time, Spacecraft’s trajectory

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: E. Keramaris, V. Kanakoudis

Abstract:

In this study the water flow in an open channel over a sharp-crested weir is investigated experimentally. For this reason a series of laboratory experiments were performed in an open channel with a sharp-crested weir. The maximum head expected over the weir, the total upstream water height and the downstream water height of the impact in the constant bed of the open channel were measured. The discharge was measured using a tank put right after the open channel. In addition, the discharge and the upstream velocity were also calculated using already known equations. The main finding is that the relative error percentage for the majority of the experimental measurements is ± 4%, meaning that the calculation of the discharge with a sharp-crested weir gives very good results compared to the numerical results from known equations.

Keywords: sharp-crested weir, weir height, flow measurement, open channel flow

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Authors: Walaa Diab, Baher Atlam, Nadia El Nimer

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Egypt faces many obvious economic challenges, and it is so clear that a real economic transformation is needed to address those problems, especially after the recent decisions of floating the Egyptian pound and the gradual subsidy cuts that are trying to meet the needed conditions to get the IMF support of (a £12bn loan) for its economic reform program. Following the post-2008 revival of the interest in the fiscal policy and its vital role in speeding up or slowing down the economic growth. Here comes the value of this paper as it seeks to analyze the macroeconomic effects of fiscal policy in Egypt by applying A Bayesian SVAR Approach. The study uses the Bayesian method because it includes the prior information and no relevant information is omitted and so it is well suited for rational, evidence-based decision-making. Since the study aims to define the effects of fiscal policy shocks in Egypt to help the decision-makers in determining the proper means to correct the structural problems in the Egyptian economy, it has to study the period of 1990s economic reform, but unfortunately; the available data is on an annual frequency. Thus, it uses annual time series to study the period 1991: 2005 And quarterly data over the period 2006–2016. It uses a set of six main variables includes government expenditure and net tax revenues as fiscal policy arms affecting real GDP, unemployment, inflation and the interest rate. The study also tries to assess the 'crowding out' effects by considering the effects of government spending and government revenue shocks on the composition of GDP, namely, on private consumption and private investment. Last but not least the study provides its policy implications regarding the needed role of fiscal policy in Egypt in the upcoming economic reform building on the results it concludes from the previous reform program.

Keywords: fiscal policy, government spending, structural vector autoregression, taxation

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Authors: Haleh Dadgostar, Sara Kaviani, Hanieh Adib, Ali Mazaherinezhad, Masoud Solaymani-Dodaran, Fahimeh Soheilipour, Abdolreza Pazouki

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Background and Objectives: Effectiveness of various exercise protocols in weight reduction after bariatric surgery has not been sufficiently explored in the literature. We compared the effect of minimally supervised home-based and closely supervised Gym based exercise programs on weight reduction and insulin resistance after bariatric surgery. Methods: Women undergoing gastric bypass surgery were invited to participate in an exercise program and were randomly allocated into two groups. They were either offered a minimally supervised home-based (MSHB) or closely supervised Gym-based (CSGB) exercise program. The CSGB protocol constitute two sessions per week of training under ACSM guidelines. In the MSHB protocol participants received a notebook containing a list of recommended aerobic and resistance exercises, a log to record their activity and a schedule of follow up phone calls and clinic visits. Both groups received a pedometer. We measured their weight, BMI, lipid profile, FBS, and insulin level at the baseline and after 20 weeks of exercise and were compared at the end of the study. Results: A total of 80 patients completed our study (MSHB=38 and CSGB=42). The baseline comparison showed that the two groups are similar. Using the ANCOVA method of analysis the mean change in BMI (covariate: BMI at the beginning of the study) was slightly better in CSGB compared with the MSHB (between-group mean difference: 3.33 (95%CI 4.718 to 1.943, F: 22.844 p < 0.001)). Conclusion: Our results showed that both MSHB and CSGB exercise methods are somewhat equally effective in improvement of studied factors in the two groups. With considerably lower costs of Minimally Supervised Home Based exercise programs, these methods should be considered when adequate funding are not available.

Keywords: postoperative exercise, insulin resistance, bariatric surgery, morbid obesity

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Authors: Fathi Abid, Bilel Kaffel

Abstract:

The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

Abstract:

Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 193