Search results for: energy demand model

Authors: Ilze Dimanta, Zane Rutkovska, Vizma Nikolajeva, Janis Kleperis, Indrikis Muiznieks

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Majority of word’s steadily increasing energy consumption is provided by non-renewable fossil resources. Need to find an alternative energy resource is essential for further socio-economic development. Hydrogen is renewable, clean energy carrier with high energy density (142 MJ/kg, accordingly – oil has 42 MJ/kg). Biological hydrogen production is an alternative way to produce hydrogen from renewable resources, e.g. using organic waste material resource fermentation that facilitate recycling of sewage and are environmentally benign. Hydrogen gas is produced during the fermentation process of bacteria in anaerobic conditions. Bacteria are producing hydrogen in the liquid phase and when thermodynamic equilibrium is reached, hydrogen is diffusing from liquid to gaseous phase. Because of large quantities of available crude glycerol and the highly reduced nature of carbon in glycerol per se, microbial conversion of it seems to be economically and environmentally viable possibility. Such industrial organic waste product as crude glycerol is perspective for usage in feedstock for hydrogen producing bacteria. The process of biodiesel production results in 41% (w/w) of crude glycerol. The developed lab-scale test system (experimental bioreactor) with hydrogen micro-electrode (Unisense, Denmark) was used to determine hydrogen production yield and rate in the liquid phase. For hydrogen analysis in the gas phase the RGAPro-100 mass-spectrometer connected to the experimental test-system was used. Fermentative bacteria strains were tested for hydrogen gas production rates. The presence of hydrogen in gaseous phase was measured using mass spectrometer but registered concentrations were comparatively small. To decrease the hydrogen partial pressure in liquid phase reactor with a system for continuous bubbling with inert gas was developed. H2 production rate for the best producer in liquid phase reached 0,40 mmol H2/l, in gaseous phase - 1,32 mmol H2/l. Hydrogen production rate is time dependent – higher rate of hydrogen production is at the fermentation process beginning when concentration increases, but after three hours of fermentation, it decreases.

Keywords: bio-hydrogen, fermentation, experimental bioreactor, crude glycerol

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Authors: Engineer Dilnawaz Shah

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Solid Waste Management (SWM) is perhaps one of the most important elements constituting the environmental health and sanitation of the urban developing sector. The management system has several components that are integrated as well as interdependent; thus, the efficiency and effectiveness of the entire system are affected when any of its functional components fails or does not perform up to the level mark of operation. Sindh Solid Waste Management Board (SSWMB) is responsible for the management of solid waste in the entire city. There is a need to adopt the engineered approach in the redesigning of the existing system. In most towns, street sweeping operations have been mechanized and done by machinery operated by vehicles. Construction of Garbage Transfer Stations (GTS) at a number of locations within the city will cut the cost of transportation of waste to disposal sites. Material processing, recovery of recyclables, compaction, volume reduction, and increase in density will enable transportation of waste to disposal sites/landfills via long vehicles (bulk transport), minimizing transport/traffic and environmental pollution-related issues. Development of disposal sites into proper sanitary landfill sites is mandatory. The transportation mechanism is through garbage vehicles using either hauled or fixed container systems employing crew for mechanical or manual loading. The number of garbage vehicles is inadequate, and due to comparatively long haulage to disposal sites, there are certain problems of frequent vehicular maintenance and high fuel costs. Foreign investors have shown interest in enterprising improvement schemes and proposed operating a solid waste management system in Karachi. The waste to Energy option is being considered to provide a practical answer to be adopted to generate power and reduce waste load – a two-pronged solution for the increasing environmental problem. The paper presents results and analysis of a recent study into waste generation and characterization probing into waste-to-energy options for Karachi City.

Keywords: waste to energy option, integrated approach, solid waste management, physical and chemical composition of waste in Karachi

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Kaoutar Jraida

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Growing evidence demonstrates that thermal conditions in office buildings broadly influence productivity of workers. The purpose of this study is to evaluate and analyze the indoor thermal comfort in an office space based on the calculation of predicted mean vote and predicted percentage of dissatisfied (PMV-PPD) model and field survey.

Keywords: Office, Predicted Mean Vote (PMV), Percentage People Dissatisfied (PPD), Thermal comfort

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Authors: Vishnu Asokan, Zaid M. Paloba

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Flow over cavities is an important area of research due to the significant change in flow physics caused by cavity aspect ratio, free stream Mach number and the nature of upstream boundary layer approaching the cavity leading edge. Cavity flow finds application in aircraft wheel well, weapons bay, combustion chamber of scramjet engines, etc. These flows are highly unsteady, compressible and turbulent and it involves mass entrainment coupled with acoustics phenomenon. Variation of flow dynamics in an angled cavity with a heated and cooled pylon upstream to the cavity with spatial combinations of heat flux addition and removal to the wall studied numerically. The goal of study is to investigate the effect of energy addition, removal to the cavity walls and pylon cavity flow dynamics. Preliminary steady state numerical simulations on inclined cavities with heat addition have shown that wall pressure profiles, as well as the recirculation, are influenced by heat transfer to the compressible fluid medium. Such a hybrid control of cavity flow dynamics in the form of heat transfer and pylon geometry can open out greater opportunities in enhancement of mixing and flame holding requirements of supersonic combustors. Addition of pylon upstream to the cavity reduces the acoustic oscillations emanating from the geometry. A numerical unsteady analysis of supersonic flow past cavities exposed to cavity wall heating and cooling with heated and cooled pylon helps to get a clear idea about the oscillation suppression in the cavity. A Cavity of L/D 4 and aft wall angle 22 degree with an upstream pylon of h/D=1.5 mm with a wall angle 29 degree exposed to supersonic flow of Mach number 2 and heat flux of 40 W/cm² and -40 W/cm² modeled for the above study. In the preliminary study, the domain is modeled and validated numerically with a turbulence model of SST k-ω using an HLLC implicit scheme. Both qualitative and quantitative flow data extracted and analyzed using advanced CFD tools. Flow visualization is done using numerical Schlieren method as the fluid medium gives the density variation. The heat flux addition to the wall increases the secondary vortex size of the cavity and removal of energy leads to the reduction in vortex size. The flow field turbulence seems to be increasing at higher heat flux. The shear layer thickness increases as heat flux increases. The steady state analysis of wall pressure shows that there is variation on wall pressure as heat flux increases. Shift in frequency of unsteady wall pressure analysis is an interesting observation for the above study. The time averaged skin friction seems to be reducing at higher heat flux due to the variation in viscosity of fluid inside the cavity.

Keywords: energy addition, frequency shift, Numerical Schlieren, shear layer, vortex evolution

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Authors: Kgolagano Mpejane

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The study applies a New Institutional Economics (NIE) analytical framework to trade in developing economies by assessing the impacts of institutional quality and institutional quality distance on agricultural trade using a panel data of 15 Southern African Development Community (SADC) countries from the years 1991-2010. The issue of institutions on agricultural trade has not been accorded the necessary attention in the literature, particularly in developing economies. Therefore, the paper empirically tests the gravity model of international trade by measuring the impact of political, economic and legal institutions on intra SADC agricultural trade. The gravity model is noted for its exploratory power and strong theoretical foundation. However, the model has statistical shortcomings in dealing with zero trade values and heteroscedasticity residuals leading to biased results. Therefore, this study employs a two stage Heckman selection model with a Probit equation to estimate the influence of institutions on agricultural trade. The selection stages include the inverse Mills ratio to account for the variable bias of the gravity model. The Heckman model accounts for zero trade values and is robust in the presence of heteroscedasticity. The empirical results of the study support the NIE theory premise that institutions matter in trade. The results demonstrate that institutions determine bilateral agricultural trade on different margins with political institutions having positive and significant influence on bilateral agricultural trade flows within the SADC region. Legal and economic institutions have significant and negative effects on SADC trade. Furthermore, the results of this study confirm that institutional quality distance influences agricultural trade. Legal and political institutional distance have a positive and significant influence on bilateral agricultural trade while the influence of economic, institutional quality is negative and insignificant. The results imply that nontrade barriers, in the form of institutional quality and institutional quality distance, are significant factors limiting intra SADC agricultural trade. Therefore, gains from intra SADC agricultural trade can be attained through the improvement of institutions within the region.

Keywords: agricultural trade, institutions, gravity model, SADC

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Authors: J. Naalamle Amissah, Dorcas Osei‐Safo, C. M. Asare, Benjamin Missah‐Assihene, Eric. Y. Danquah, Ivan Addae‐Mensah

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Medicinal plants serve as a reservoir of active ingredients for the treatment of common ailments such as cancer, malaria and diabetes. With the recent wave of health consciousness and reliance on plant based medicines, the demand for medicinal plants has increased considerably. This surge in medicinal plant use has raised great concern amongst key players (herbalist, collectors, conservationist and researchers) along the value chain about the sustainability of the raw material. The over reliance on wild crafting as a means to obtain the raw material spells doom for several of Africa’s native medicinal plant species. In this study domestication protocols for the cultivation of Cryptolepis sanguinolenta (CS), a medicinal plant used in the treatment of malaria were developed. Initial surveys were conducted, using questionnaires comprising of open and close ended questions, to gather information that would inform the domestication and cultivation of the species. A field study was then conducted to determine the plant’s cropping cycle and the effect of staking and plant age on the active ingredient (cryptolepine) concentration in its roots. Results of the survey confirmed the demand for the raw material and threw more light on the harvesting methods and intensity of CS collection from the wild. Cryptolepine concentration was found to be highest (~1.84 mg/100 mg of root material) at 289 days after planting (DAP) which coincided with the peak of root dry weight (52.8 g), signifying the best time for root harvest. Staking was found to be important for seed production. The first 105 DAP were characterized by low yields of root dry weight (13.5 g), followed by a period of rapid growth in which the root dry weight increased almost linearly until 289 DAP. Although dry matter partitioned to the vines increased towards the end of the experimental period (60%), dry matter partitioned to the roots remained fairly constant (30%) throughout the experimental period. Cryptolepine was found to increase as the plant aged and the practice of staking CS promoted pod formation. A suitable cropping cycle for the cultivation of CS was also developed.

Keywords: domestication, staking, conservation, wild harvesting

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Authors: Varvara Roubtsova, Mohamed Chekired

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Recent studies on the numerical simulation of geotechnical problems show the importance of considering the soil micro-structure. At this scale, soil is a discrete particle medium where the particles can interact with each other and with water flow under external forces, structure loads or natural events. This paper presents research conducted in a virtual laboratory named SiGran, developed at IREQ (Institut de recherche d’Hydro-Quebec) for the purpose of investigating a broad range of problems encountered in geotechnics. Using Discrete Element Method (DEM), SiGran simulated granular materials directly by applying Newton’s laws to each particle. The water flow was simulated by using Marker and Cell method (MAC) to solve the full form of Navier-Stokes’s equation for non-compressible viscous liquid. In this paper, examples of numerical simulation and their comparisons with real experiments have been selected to show the complexity of geotechnical research at the micro level. These examples describe transient flows into a porous medium, interaction of particles in a viscous flow, compacting of saturated and unsaturated soils and the phenomenon of liquefaction under seismic load. They also provide an opportunity to present SiGran’s capacity to compute the distribution and evolution of energy by type (particle kinetic energy, particle internal elastic energy, energy dissipated by friction or as a result of viscous interaction into flow, and so on). This work also includes the first attempts to apply micro discrete results on a macro continuum level where the Smoothed Particle Hydrodynamics (SPH) method was used to resolve the system of governing equations. The material behavior equation is based on the results of simulations carried out at a micro level. The possibility of combining three methods (DEM, MAC and SPH) is discussed.

Keywords: discrete element method, marker and cell method, numerical simulation, multi-scale simulations, smoothed particle hydrodynamics

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Zeiler M., Stadler D., Schmaderer C.

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Over the years of dialysis treatment, most patients experience significant weight loss. The primary emphasis in earlier research was the underlying mechanism of protein energy wasting and the subsequent malnutrition inflammation syndrome. In the interest to provide an effective and rapid solution for the patients, the aim of this study is identifying individual influences of their assumed reduced dietary intake, such as nausea, appetite loss and taste changes, and to determine whether the patients adhere to their nutrition guidelines. A prospective, controlled study with 38 end-stage renal disease patients was performed using a questionnaire to reflect their diet within the last 12 months. Thereby, the daily intake for the most important macro-and micronutrients was calculated to be compared with the individual KDQOI-guideline value, as well as controls matched in age and gender. The majority of the study population did not report symptoms commonly associated with dialysis, such as nausea or inappetence, and denied any change in dietary behavior since receiving renal replacement therapy. The patients’ daily intake of energy (3080kcal ± 1266) and protein (89,9g [53,4-142,0]) did not differ significantly from the controls (energy intake: 3233kcal ± 1046, p=0,597; protein intake: 103,7g [90,1-125,5], p=0,120). The average difference to the individual calculated KDQOI-guideline was +176,0kcal ± 1156 (p=0,357) for energy intake and -1,75g ± 45,9 (p=0,491) for protein intake. However, there was an observed imbalance in the distribution of macronutrients, with a preference for fats over proteins. The patients’ daily intake of sodium (5,4g [ 2,95-10,1]) was higher than in the controls (4,1g [2,04-5,99], p= 0,058) whereas both values for potassium (3,7g ± 1,84) and phosphorous (1,79g ± 0,91) went significantly below the controls’ values (potassium intake: 4,89g ± 1,74, p=0,014; phosphorous intake: 2,04g ± 0,64, p=0,038). Thus, the values exceeded the calculated KDQOI-recommendation by + 3,3g [0,63-7,90] (p<0,001) for sodium, +1,49g ± 1,84 (p<0,001) for potassium and +0,89g ± 0,91 (p<0,001) for phosphorous. Contrary to the assumption, the patients did not under-eat. Nevertheless, their diets did not align with the recommended values. These findings highlight the need for intervention and education among patients and that regular dietary monitoring could prevent unhealthy nutrition habits. The elaboration of individual references instead of standardized guidelines could increase the compliance to the advised diet so that interdisciplinary comorbidities do not develop or worsen.

Keywords: compliance, dialysis, end-stage renal disease, KDQOI, malnutrition, nutrition guidelines, questionnaire, salt intake

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Authors: Lamia Bourdache, Amar Djema

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The effect of non-Newtonian property (power law index n) on traveling waves of thin layer of power law fluid flowing over an inclined plane is investigated. For this, a simplified second-order two-equation model (SM) is used. The complete model is second-order four-equation (CM). It is derived by combining the weighted residual integral method and the lubrication theory. This is due to the fact that at the beginning of the instability waves, a very small number of waves is observed. Using a suitable set of test functions, second order terms are eliminated from the calculus so that the model is still accurate to the second order approximation. Linear, spatial, and temporal stabilities are studied. For travelling waves, a particular type of wave form that is steady in a moving frame, i.e., that travels at a constant celerity without changing its shape is studied. This type of solutions which are characterized by their celerity exists under suitable conditions, when the widening due to dispersion is balanced exactly by the narrowing effect due to the nonlinearity. Changing the parameter of celerity in some range allows exploring the entire spectrum of asymptotic behavior of these traveling waves. The (SM) model is converted into a three dimensional dynamical system. The result is that the model exhibits bifurcation scenarios such as heteroclinic, homoclinic, Hopf, and period-doubling bifurcations for different values of the power law index n. The influence of the non-Newtonian parameter on the nonlinear development of these travelling waves is discussed. It is found at the end that the qualitative characters of bifurcation scenarios are insensitive to the variation of the power law index.

Keywords: inclined plane, nonlinear stability, non-Newtonian, thin film

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Authors: M. Y. Ismail, M. Inam, A. F. M. Zain, N. Misran

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Progressive phase distribution is an important consideration in reflect array antenna design which is required to form a planar wave in front of the reflect array aperture. This paper presents a detailed mathematical model in order to determine the required reflection phase values from individual element of a reflect array designed in Ku-band frequency range. The proposed technique of obtaining reflection phase can be applied for any geometrical design of elements and is independent of number of array elements. Moreover the model also deals with the solution of reflect array antenna design with both centre and off-set feed configurations. The theoretical modeling has also been implemented for reflect arrays constructed on 0.508 mm thickness of different dielectric substrates. The results show an increase in the slope of the phase curve from 4.61°/mm to 22.35°/mm by varying the material properties.

Keywords: mathematical modeling, progressive phase distribution, reflect array antenna, reflection phase

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Authors: Michiko Miyamoto

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This paper empirically investigates whether information technology (IT) strategies, business strategies, and divisions are aligned to meet overall business goals for Korean Small and medium-sized enterprises (SMEs), based on structure based Strategic Alignment Model, and make comparison with those of Japanese SMEs. Using 2,869 valid responses of Korean Human Capital Corporate Panel survey, a result of this study suggests that Korean human resources (HR) departments have a major influence over IT strategy, which is the same as Japanese SMEs, even though their management styles are quite different. As for IT strategy, it is not related to other departments at all for Korean SMEs. The Korean management seems to possess a great power over each division, such as Sales/Service, Research and Development/Technical Experts, HR, and Production.

Keywords: IT-business alignment, structured based strategic alignment model, structural equation model, human resources department

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Authors: Mohammed Alonazi, Natalia Beloff, Martin White

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This paper presents a proposal for a mobile government adoption and utilization model (MGAUM), which is a framework designed to increase the adoption rate of m-government services in Saudi Arabia. Recent advances in mobile technologies such are Mobile compatibilities, The development of wireless communication, mobile applications and devices are enabling governments to deliver services in new ways to citizens more efficiently and economically. In the last decade, many governments around the globe are utilizing these advances effectively to develop their next generation of e-government services. However, a low adoption rate of m-government services by citizens is a common problem in Arabian countries, including Saudi Arabia. Yet, to our knowledge, very little research has been conducted focused on understanding the factors that influence citizen adoption of these m-government services in this part of the world. A set of social, cultural and technological factors have been identified in the literature, which has led to the formulation of associated research questions and hypotheses. These hypotheses will be tested on Saudi citizens using questionnaires and interview methods based around the technology acceptance model. A key objective of the MGAUM framework is to investigate and understand Saudi citizens perception towards adoption and utilization of m-government services.

Keywords: e-government, m-government, citizen services quality, technology acceptance model, Saudi Arabia, adoption framework.

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Warda Nasir, M. N. S. Qureshi

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Whistler waves are right handed circularly polarized waves and are frequently observed in space plasmas. The Low frequency branch of the Whistler waves having frequencies nearly around 100 Hz, known as Lion roars, are frequently observed in magnetosheath. Another feature of the magnetosheath is the observations of flat top electron distributions with single as well as two electron populations. In the past, lion roars were studied by employing kinetic model using classical bi-Maxwellian distribution function, however, could not be justified both on quantitatively as well as qualitatively grounds. We studied Whistler waves by employing kinetic model using non-Maxwellian distribution function such as the generalized (r,q) distribution function which is the generalized form of kappa and Maxwellian distribution functions by employing kinetic theory with single or two electron populations. We compare our results with the Cluster observations and found good quantitative and qualitative agreement between them. At times when lion roars are observed (not observed) in the data and bi-Maxwellian could not provide the sufficient growth (damping) rates, we showed that when generalized (r,q) distribution function is employed, the resulted growth (damping) rates exactly match the observations.

Keywords: kinetic model, whistler waves, non-maxwellian distribution function, space plasmas

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Neslihan Sahin Celik, Ali Eraslan

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Mathematical model and modeling are one of the topics that have been intensively discussed in recent years. In line with the results of the PISA studies, researchers in many countries have begun to question how much students in school-education system are prepared to solve the real-world problems they encounter in their future professional lives. As a result, many mathematics educators have begun to emphasize the importance of new skills and understanding such as constructing, Hypothesizing, Describing, manipulating, predicting, working together for complex and multifaceted problems for success in beyond the school. When students increasingly face this kind of situations in their daily life, it is important to make sure that students have enough experience to work together and interpret mathematical situations that enable them to think in different ways and share their ideas with their peers. Thus, model eliciting activities are one of main tools that help students to gain experiences and the new skills required. This research study was carried on the town center of a big city located in the Black Sea region in Turkey. The participants were eighth-grade students in a middle school. After a six-week preliminary study, three students in an eighth-grade classroom were selected using criterion sampling technique and placed in a focus group. The focus group of three students was videotaped as they worked on a model eliciting activity, the Summer Job Problem. The conversation of the group was transcribed, examined with students’ written work and then qualitatively analyzed through the lens of Blum’s (1996) modeling processing cycle. The study results showed that eighth grade students can successfully work with the model eliciting, develop a model based on the two parameters and review the whole process. On the other hand, they had difficulties to relate parameters to each other and take all parameters into account to establish the model.

Keywords: middle school, modeling, mathematical modeling, summer job problem

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Authors: M. K. Kim, C. H. Shin, W. G. Park

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Recently, natural gas resources are issued due to alternative and eco-friendly energy policies, and development of even unconventional gas resources including tight gas, coal bed methane and shale gas is being rapidly expanded from North America all over the world. For developing these gas reservoirs, it is necessary to investigate reservoir characteristics by using reservoir simulation. In reservoir simulation, calculation of permeability of fractured zone is very important to predict the gas production. However, it is difficult to accurately calculate the permeability by using conventional methods which use analytic solution for laminar flow. The flow in gas reservoirs exhibits complex flow behavior such as slip around the wall roughness effect and turbulence because the size of the apertures of fractures is ranged over various scales from nano-scale to centi-scale. Therefore, it is required to apply new reservoir flow analysis methods which can accurately consider complex gas flow owing to the geometric characteristics and distributions of various pores and flow paths within gas reservoirs. Hence, in this study, the flow characteristics and the relation between each characteristic variable was investigated and multi-effect was quantified when the fractures are compounded for devising a new calculation model of permeability of fractured zone in gas reservoirs by using CFD.

Keywords: fractured zone, gas reservoir, permeability, CFD

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Authors: Keith D. Nare, Mohau J. Phiri, James Carson, Chris D. Woolard, Shanganyane P. Hlangothi

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In an energy-intensive world, minimizing energy consumption is paramount to cost saving and reducing the carbon footprint. Improving mixture procedures utilizing warm mix additive Fischer-Tropsch (FT) wax in ethylene vinyl acetate (EVA) and modified bitumen highlights a greener and sustainable approach to modified bitumen. In this study, the impact of FT wax on optimized EVA/waste crumb rubber modified bitumen is assayed with a maximum loading of 2.5%. The rationale of the FT wax loading is to maintain the original maximum loading of EVA in the optimized mixture. The phase change abilities of FT wax enable EVA co-crystallization with the support of the elastomeric backbone of crumb rubber. Less than 1% loading of FT wax worked in the EVA/crumb rubber modified bitumen energy-sustainability nexus. Response surface methodology approach to the mixture design is implemented amongst the different loadings of FT wax, EVA for a consistent amount of crumb rubber and bitumen. Rheological parameters (complex shear modulus, phase angle and rutting parameter) were the factors used as performance indicators of the different optimized mixtures. The low temperature chemistry of the optimized mixtures is analyzed using elementary beam theory and the elastic-viscoelastic correspondence principle. Master curves and black space diagrams are developed and used to predict age-induced cracking of the different long term aged mixtures. Modified binder rheology reveals that the strain response is not linear and that there is substantial re-arrangement of polymer chains as stress is increased, this is based on the age state of the mixture and the FT wax and EVA loadings. Dominance of individual effects is evident over effects of synergy in co-interaction of EVA and FT wax. All-inclusive FT wax and EVA formulations were best optimized in mixture 4 with mixture 7 reflecting increase in ease of workability. Findings show that interaction chemistry of bitumen, crumb rubber EVA, and FT wax is first and second order in all cases involving individual contributions and co-interaction amongst the components of the mixture.

Keywords: bitumen, crumb rubber, ethylene vinyl acetate, FT wax

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Authors: Kristopher A. Pruitt, Justin M. Hill

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The purpose of this research is to determine the pacing and nutrition strategies which minimize completion time and carbohydrate intake for athletes competing in ultramarathon races. The model formulation consists of a two-phase optimization. The first-phase mixed-integer nonlinear program (MINLP) determines the minimum completion time subject to the altitude, terrain, and distance of the race, as well as the mass and cardiovascular fitness of the athlete. The second-phase MINLP determines the minimum total carbohydrate intake required for the athlete to achieve the completion time prescribed by the first phase, subject to the flow of carbohydrates through the stomach, liver, and muscles. Consequently, the second phase model provides the optimal pacing and nutrition strategies for a particular athlete for each kilometer of a particular race. Validation of the model results over a wide range of athlete parameters against completion times for real competitive events suggests strong agreement. Additionally, the kilometer-by-kilometer pacing and nutrition strategies, the model prescribes for a particular athlete suggest unconventional approaches could result in lower completion times. Thus, the MINLP provides prescriptive guidance that athletes can leverage when developing pacing and nutrition strategies prior to competing in ultramarathon races. Given the highly-variable topographical characteristics common to many ultramarathon courses and the potential inexperience of many athletes with such courses, the model provides valuable insight to competitors who might otherwise fail to complete the event due to exhaustion or carbohydrate depletion.

Keywords: nutrition, optimization, pacing, ultramarathons

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Authors: Kais Ben-Ahmed, Mhamed Ali-El-Aroui

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This paper develops a Local Generalized Linear Spatial Model (LGLSM) to describe the spatial variation of Visceral Leishmaniasis (VL) infection risk in northern and central Tunisia. The response from each region is a number of affected children less than five years of age recorded from 1996 through 2006 from Tunisian pediatric departments and treated as a poison county level data. The model includes climatic factors, namely averages of annual rainfall, extreme values of low temperatures in winter and high temperatures in summer to characterize the climate of each region according to each continentality index, the pluviometric quotient of Emberger (Q2) to characterize bioclimatic regions and component for residual extra-poison variation. The statistical results show the progressive increase in the number of affected children in regions with high continentality index and low mean yearly rainfull. On the other hand, an increase in pluviometric quotient of Emberger contributed to a significant increase in VL incidence rate. When compared with the original GLSM, Bayesian locally modeling is improvement and gives a better approximation of the Tunisian VL risk estimation. According to the Bayesian approach inference, we use vague priors for all parameters model and Markov Chain Monte Carlo method.

Keywords: generalized linear spatial model, local model, extra-poisson variation, continentality index, visceral leishmaniasis, Tunisia

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Fadwa Haraka, Ahmad Elouatouati, Mourad Taha Janan

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In this study, we propose a neural network based method in order to calculate the heat source temperature of isotropic plate with lower surface forced cooling. To validate the proposed model, the heat source temperatures values will be compared to the analytical method -variables separation- and finite element model. The mathematical simulation is done through 3D numerical simulation by COMSOL software considering three different materials: Aluminum, Copper, and Graphite. The proposed method will lead to a formulation of the heat source temperature based on the thermal and geometric properties of the base plate.

Keywords: thermal model, thermal resistance, finite element simulation, neural network

Procedia PDF Downloads 342

Authors: R. Hellmuth

Abstract:

The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

Procedia PDF Downloads 96

Authors: Eleni Stefania Kalapoda

Abstract:

Recurring heat waves due to the global climate change emergency pose continuous risks to human health and urban resources. Local and state decision-makers incorporate Heat Vulnerability Indices (HVIs) to quantify and map the relative impact on human health in emergencies. These maps enable government officials to identify the highest-risk districts and to concentrate emergency planning efforts and available resources accordingly (e.g., to reevaluate the location and the number of heat-relief centers). Even though the framework of conducting an HVI is unique per municipality, its accuracy in assessing the heat risk is limited. To resolve this issue, varied housing-related metrics should be included. This paper quantifies and classifies NYC’s single detached housing typology within high-vulnerable NYC districts using detailed energy simulations and post-processing calculations. The results show that the variation in indoor heat risk depends significantly on the dwelling’s design/operation characteristics, concluding that low-ventilated dwellings are the most vulnerable ones. Also, it confirmed that when building-level determinants of exposure are excluded from the assessment, HVI fails to capture important components of heat vulnerability. Lastly, the overall vulnerability ratio of the housing units was calculated between 0.11 to 1.6 indoor heat degrees in terms of ventilation and shading capacity, insulation degree, and other building attributes.

Keywords: heat vulnerability index, energy efficiency, urban heat, resiliency to heat, climate adaptation, climate mitigation, building energy

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Authors: Maha Bakkari, R.Tadili

Abstract:

The present work is a study of the performance of a solar copper coil heating system in a greenhouse microclimate. Our system is based on the circulation of a Heat transfer fluid, which is water in our case, in a closed loop under the greenhouse's roof in order to store heat all day, and then this heat will supply the greenhouse during the night. In order to evaluate our greenhouse, we made an experimental study in two identical greenhouses, where the first one is equipped with a heating system and the second (without heating) is used for control. The heating system allows the establishment of the thermal balance and determines the mass of water necessary for the process in order to ensure its functioning during the night. The results obtained showed that this solar heating system and the climatic parameters inside the experimental greenhouse were improved, and it presents a significant gain compared to a controlled greenhouse without a heating system. This research is one of the solutions that help to reduce the greenhouse effect of the planet Earth, a problem that worries the world.

Keywords: solar energy, energy storage, greenhouse, environment

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Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu

Abstract:

Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.

Keywords: earnings call script, random forest, sentiment analysis, stock price prediction

Procedia PDF Downloads 281

Authors: Desplanches Maxime

Abstract:

Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

Procedia PDF Downloads 54