Search results for: ductile damage model

Authors: Xing Feng, Yuanbin Li

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Oil spills at sea can cause severe marine environmental damage, including bringing huge hazards to living resources and human beings. In situ burning or chemical dispersant methods can be used to handle the oil spills sometimes, but these approaches will bring secondary pollution and fail in some situations. Oil recovery techniques have also been developed to recover oil using oil skimmer equipment installed on ships, while the hydrodynamic process of the oil flowing through the oil skimmer is very complicated and important for evaluating the recovery efficiency. Based on this, a two-dimensional numerical simulation platform for simulating the hydrodynamic process of the oil flowing through the oil skimmer is established based on the Navier-Stokes equations for viscous, incompressible fluid. Finally, the influence of the design of the flow channel in the curved plane oil skimmer on the hydrodynamic process of the oil flowing through the oil skimmer is investigated based on the established simulation platform.

Keywords: curved plane oil skimmer, flow channel, CFD, VOF

Procedia PDF Downloads 277

Authors: Murat Erdoğdu, Murat Koçyiğit

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Brand image and brand loyalty are among the most important relational marketing elements for brand owners to be able to set up long – term relationships with their customers and to maintain these relationships. Brand owners improve their brand images with the positive perceptions remaining in the consumers’ minds. In addition, they try to find the customers that are both emotionally and behaviourally faithful to themselves in order to set up long – term relationships. Therefore, the aim of this study is to analyse the effects of the brand image that has a very important role among relational marketing elements on the brand loyalty in terms of the variables such as the perceived value, the trust in brand and the brand satisfaction. In this context, a conceptual model was created to determine the effect of the brand image on the brand loyalty thanks to the Structural Equation Model (SEM). According to this aim and this model, the study was carried out in the scope of the data collected through the questionnaires in Konya with the method of convenience sampling. The results of the research showed that the brand image has positive significant effects on the perceived value and the trust in brand and that the trust in brand has positive significant effects on the brand satisfaction, and that the brand satisfaction has positive significant effects on the brand loyalty. Thus, the hypotheses that the brand image has direct effects on the perceived value and the trust in brand and that the trust in brand has direct effects on the brand satisfaction and that the brand satisfaction has direct effects on the brand loyalty were supported. In addition, the findings about whether the perceived value has a significant effect on the brand satisfaction were also acquired.

Keywords: brand image, brand loyalty, perceived value, satisfaction, trust

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Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

Procedia PDF Downloads 148

Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

Procedia PDF Downloads 319

Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: M. Esmailian, M. Shakouri, A. Mottahedi, S. G. Shabestari

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Heat treatable aluminium alloys such as 7075 and 7055, because of high strength and low density, are used widely in aircraft industry. For best mechanical properties, T6 heat treatment has recommended for this regards, but this temper treatment is sensitive to corrosion induced and Stress Corrosion Cracking (SCC) damage. For improving this property, the over-aging treatment (T7) applies to this alloy, but it decreases the mechanical properties up to 30 percent. Hence, to increase the mechanical properties, without any remarkable decrease in SCC resistant, Retrogression and Re-Aging (RRA) heat treatment is used. This treatment performs in a relatively short time. In this paper, the RRA heat treatment was applied to 7055 aluminum alloy and then effect of RRA time on the mechanical properties of 7055 has been investigated. The results show that the 40 minute time is suitable time for retrogression of 7055 aluminum alloy and ultimate strength increases up to 625MPa.

Keywords: 7055 Aluminum alloy, mechanical properties, SCC resistance, heat Treatment

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Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Food could be used to open up a dialogue about local heritage. Contributing to the world sustainable consumption mission, this research aims to explore the linkages between agriculture, senses of place and performing arts. Thailand and its destination marketing ‘Discover Thainess’ was selected as a working principle, enabling a case example of how the three elements could be conceptualized. The model offered an integrated institutional arrangement where diverse entities could be formed to design how Thainess (local heritage) could be interpreted and embedded into an art of food. Using case study research approach, three areas (Chiangmai, Samutsongkram and Ban Rai Gong King) representing 3 different scales of tourism development were selected. Based on a theoretical analysis, a working model was formulated. An action research was then designed to experiment how the model could be materialized. Brainstorming elicitation and in-depth interview were employed to reflect on how each element could be integrated. The result of this study offered an innovation on how food tourism could be profoundly interpreted and how tourism development could enhance value creation for agricultural based community. The outcomes of the research present co-creative multi-stakeholder model and the value creation method through the whole supply chain of Thai gastronomy. The findings have been eventually incorporated into ‘gastro-diplomacy’ strategy for Thai tourism.

Keywords: community-based tourism, gastro-diplomacy, gastronomy tourism, sustainable tourism development

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Authors: Ksenia Siadkowska, Łukasz Grabowski, Michał Gęca

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The dynamic development of photovoltaics in the 21st century has resulted in more possibilities for using photovoltaic systems. In order to reduce emissions, a retrofitting of vehicles with photovoltaic modules has recently become increasingly popular. Preparing such an installation, however, requires professional knowledge and compliance with safety rules. The paper discusses the advantages and disadvantages of some types of flexible photovoltaic modules that can be applied to mobile installations, types and causes of damage to photovoltaic modules as well as the most frequent types of misinstallation. Our attention has been drawn to the risk of fire caused by misintallation or defective insulation and the need to closely monitor mobile installations, for example by a non-destructive testing with a thermal imaging camera. The paper also presents certain selected results of the research conducted at the Lublin University of Technology. This work has been financed by the Polish National Centre for Research and Development, under Grant Agreement No. PBS2/A6/16/2013.

Keywords: flexible PV module, mobile PV module, photovoltaic module, photovoltaic

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Authors: Gunawan Prayitno, Kakuya Matshusima, Kiyoshi Kobayashi

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Indonesia’s rural regions are characterized by wide-spread poverty, under-employment, and surplus of low-skilled labor. The aim of this paper is to empirically prove the effect of social ties (strong and weak tie) as social capital construct on households’ migration decision in the case of developing country (Indonesia). The methodology incorporated indicators of observe variables (four demographic attributes data: income, occupation, education, and family members) and indicators of latent variables (ties to neighbors, ties to community and sense of place) provided by responses to survey questions to aid in estimating the model. Using structural equation model that we employed in Mplus program, the result of our study shows that ties to community positively have a significant impact to the decision of respondents (migrate or not). Besides, education as observed variable directly influences the migration decisions. It seems that higher level of education have impact on migration decision. Our current model so far could explain the relation between social capital and migration decision choice.

Keywords: migration, ties to community, ties to neighbors, education

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Authors: Gabriel Sanjo Aruwajoye, E. B. Gueguim Kana

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Agricultural residues present a low-cost feedstock for bioenergy production around the world. Cassava peels waste are rich in organic molecules that can be readily converted to value added products such as biomaterials and biofuels. However, due to the presence of high proportion of structural carbohydrates and lignin, the hydrolysis of this feedstock is imperative to achieve maximum substrate utilization and energy yield. This study model and optimises the release of Fermentable Sugar (FS) from cassava peels waste using the Response Surface Methodology. The investigated pretreatment input parameters consisted of soaking temperature (oC), soaking time (hours), autoclave duration (minutes), acid concentration (% v/v), substrate solid loading (% w/v) within the range of 30 to 70, 0 to 24, 5 to 20, 0 to 5 and 2 to 10 respectively. The Box-Behnken design was used to generate 46 experimental runs which were investigated for FS release. The obtained data were used to fit a quadratic model. A coefficient of determination of 0.87 and F value of 8.73 was obtained indicating the good fitness of the model. The predicted optimum pretreatment conditions were 69.62 oC soaking temperature, 2.57 hours soaking duration, 5 minutes autoclave duration, 3.68 % v/v HCl and 9.65 % w/v solid loading corresponding to FS yield of 91.83g/l (0.92 g/g cassava peels) thus 58% improvement on the non-optimised pretreatment. Our findings demonstrate an efficient pretreatment model for fermentable sugar release from cassava peels waste for various bioprocesses.

Keywords: feedstock pretreatment, cassava peels, fermentable sugar, response surface methodology

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Authors: Abdulsalam Mas’ud

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Though Nigerian Biofuel Policy and Incentive was introduced in 2007, however, little if any is known about the impact of such policy for biodiesel development in Nigeria. It can be argued that lack of raw materials is one of the important factors that hinder the proper implementation of the policy. In line with this argument, this study aims to explore the determinants of smallholder farmers’ intention to adopt Jatropha as raw materials for biodiesel development in northern Nigeria, with Jigawa State as area of study. The determinants proposed for investigation covers personal factors, physical factors, institutional factors, economic factors, risk and uncertainty factors as well as social factors. The validation of the proposed model will have the implication of guiding policymakers towards enhancement of farmers’ participation in the Jatropha project for biodiesel raw materials production. The eventual byproducts of the proposed model validation and implementation will be employment generation, poverty reduction, combating dessert encroachment, economic diversification to renewable energy sources and electricity generation.

Keywords: adoption, biodiesel, factors, jatropha

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Authors: Fatemeh Keivanifard

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E-learning is becoming increasingly prominent in higher education, with universities increasing provision and more students signing up. This paper examines factors that predict students' attitudes to adapt e-learning at the Khuzestan province Iran. Understanding the nature of these factors may assist these universities in promoting the use of information and communication technology in teaching and learning. The main focus of the paper is on the university students, whose decision supports effective implementation of e-learning. Data was collected through a survey of 300 post graduate students at the University of dezful, shooshtar and chamran in Khuzestan. The technology adoption model put forward by Davis is utilized in this study. Two more independent variables are added to the original model, namely, the pressure to act and resources availability. The results show that there are five factors that can be used in modeling students' attitudes to adapt e-learning. These factors are intention toward e-learning, perceived usefulness of e-learning, perceived ease of e-learning use, pressure to use e-learning, and the availability of resources needed to use e-learning.

Keywords: e-learning, intention, ease of use, pressure to use, usefulness

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Mohammad Yusuf, Qazi Fariduddin

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The main aim of this study was to explore the different cultivars of Vigna radiata on basis of photosynthesis, antioxidants and proline to assess Ni-sensitive and Ni-tolerant cultivar. Seeds of five different cultivars were sown in soil amended with different levels of Ni (0, 50, 100, or 150 mg kg 1). At 30 d stage, plants were harvested to assess the various parameters. The Ni treatment diminished growth, leaf water potential, chlorophyll content and net photosynthesis along with nitrate reductase and carbonic anhydrase activities in the concentration dependent manner whereas, it enhanced proline content and various antioxidant enzymes. The varieties T-44 found least affected, whereas PDM-139 experienced maximum damage at 150 mg kg-1 of Ni. Moreover, T-44 possessed maximum activity of antioxidant enzymes and proline content at all the levels of metal whereas PDM-139 possessed minimum values. Therefore, T-44 and PDM-139 were established as the most resistant and sensitive varieties, respectively.

Keywords: Vigna radiata, antioxidants, nickel, photosynthesis, proline

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Authors: Mostafa Zandi, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and  equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.

Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function

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Authors: Moses E. Emetere, M. L. Akinyemi

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Agricultural activities in the South–West Nigeria are mitigated by the global increase in temperature. The unpredictive surface temperature of the area had increased health challenges amongst other social influence. The satellite data of surface temperatures were compared with the ground station Davis weather station. The differential heating of the lower atmosphere were represented mathematically. A numerical predictive model was propounded to forecast future surface temperature.

Keywords: numerical predictive model, surface temperature, satellite date, ground data

Procedia PDF Downloads 454

Authors: Rowland R. Ogunrinde, Yusmadi Y. Jusoh, Noraini Che Pa, Wan Nurhayati W. Rahman, Azizol B. Abdullah

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Enterprise Applications (EAs) aid the organizations achieve operational excellence and competitive advantage. Over time, most Small and Medium Enterprises (SMEs), which are known to be the major drivers of most thriving global economies, use the costly on-premise versions of these applications thereby making business difficult to competitively thrive in the same market environment with their large enterprise counterparts. The advent of cloud computing presents the SMEs an affordable offer and great opportunities as such EAs can be cloud-hosted and rented on a pay-per-use basis which does not require huge initial capital. However, as there are numerous Cloud Service Providers (CSPs) offering EAs as Software-as-a-Service (SaaS), there is a challenge of choosing a suitable provider with Quality of Service (QoS) that meet the organizations’ customized requirements. The proposed model takes care of that and goes a step further to select the most affordable among a selected few of the CSPs. In the earlier stage, before developing the instrument and conducting the pilot test, the researchers conducted a structured interview with three experts to validate the proposed model. In conclusion, the validity and reliability of the instrument were tested through experts, typical respondents, and analyzed with SPSS 22. Results confirmed the validity of the proposed model and the validity and reliability of the instrument.

Keywords: cloud service provider, enterprise application, quality of service, selection criteria, small and medium enterprise

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Authors: Isaac Kofi Mensah

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The adoption and application of Information and Communication Technologies (ICTs) in government administration through e-government is expected to permeate all sectors of state/ public institutions as well as democratic institutions. One of such public institutions is the Electoral Commission of Ghana mandated by the 1992 Constitution to hold all public elections including presidential and parliamentary elections. As Ghana holds its 7th General Elections since 1992, on 7th November 2016, there are demands from key stakeholders for the Election Management Body, which is the Electoral Commission (EC) of Ghana to adopt and implement an electronic voting system. This case study, therefore, attempts to contribute significantly to the debate by examining influencing factors that would impact on citizen’s readiness to adopt and use an electronic voting system in Ghana. The Technology Acceptance Model (TAM) was used as a theoretical framework for this study, out of which a research model and hypotheses were developed. Importantly, the outcome of this research finding would form a basis for appropriate policy recommendation for consideration of Government and EC of Ghana.

Keywords: citizens readiness, e-government, electronic voting, technology acceptance model (TAM)

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Authors: Kyung Min Kang, Peng Mou, Dong Xiang, Gang Shen

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For planetary gear system, Planet pin-hole position accuracy is one of most influential factor to efficiency and reliability of planetary gear system. This study considers planet pin-hole position error as a main input error for model and build multi body dynamic simulation model of planetary gear including planet pin-hole position error using MSC. ADAMS. From this model, the mesh load results between meshing gears in each pin-hole position error cases are obtained and based on these results, planet load sharing factor which reflect equilibrium state of mesh load sharing between whole meshing gear pair is calculated. Analysis result indicates that the pin-hole position error of tangential direction cause profound influence to mesh load and load sharing factor between meshing gear pair.

Keywords: planetary gear, load sharing factor, multibody dynamics, pin-hole position error

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: N. Bazyar Shourabi, K. Nyarko, C. Scott, M. Jeihnai

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Ground drones have the potential to reduce the cost and time of making last-mile deliveries. They also have the potential to make a huge impact on human life. Despite this potential, little work has gone into developing a suitable feasibility model for ground drone delivery in dense urban areas. Today, most of the experimental ground delivery drones utilize sidewalks only, with just a few of them starting to use bike lanes, which a significant portion of some urban areas have. This study works on the feasibility of using bike lanes in conjunction with sidewalks for ground drone applications in last-mile delivery for dense urban areas. This work begins with surveying bike lanes and sidewalks within the city of Boston using Geographic Information System (GIS) software to determine the percentage of coverage currently available within the city. Then six scenarios are examined. Based on this research, a mathematical model is developed. The daily cost of delivering packages using each scenario is calculated by the mathematical model. Comparing the drone delivery scenarios with the traditional method of package delivery using trucks will provide essential information concerning the feasibility of implementing routing protocols that combine the use of sidewalks and bike lanes. The preliminary results of the model show that ground drones that can travel via sidewalks or bike lanes have the potential to significantly reduce delivery cost.

Keywords: ground drone, intelligent transportation system, last-mile delivery, sidewalk robot

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Authors: Malika Fekih, Abdenour Bourabaa, Rafika Hariti, Mohamed Saighi

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In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values.

Keywords: global solar radiation, empirical model, semi arid areas, climatological parameters

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Authors: P. Sathyakala, G. Sai Sundara Krishnan

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The objective of this paper is to derive an exergy model for a solar water heater with honey comb structure in order to identify the element which has larger irreversibility in the system. This will help us in finding the means to reduce the wasted work potential so that the overall efficiency of the system can be improved by finding the ways to reduce those wastages.

Keywords: exergy, energy balance, entropy balance, work potential, degradation, honey comb, flat plate collector

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Laura Florez

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The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

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Authors: Saad A. Aljlil

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Adsorption of cobalt ions on quartz and illite and calcite from waste water was investigated. The effect of pH on the adsorption of cobalt ions was studied. The maximum capacities of cobalt ions of the three adsorbents increase with increasing cobalt solution temperature. The maximum capacities were (4.66) mg/g for quartz, (3.94) mg/g for illite, and (3.44) mg/g for calcite. The enthalpy, Gibbs free energy, and entropy for adsorption of cobalt ions on the three adsorbents were calculated. It was found that the adsorption process of the cobalt ions of the adsorbent was an endothermic process. consequently increasing the temperature causes the increase of the cobalt ions adsorption of the adsorbents. Therefore, the adsorption process is preferred at high temperature levels. The equilibrium adsorption data were correlated using Langmuir model, Freundlich model. The experimental data of cobalt ions of the adsorbents correlated well with Freundlich model.

Keywords: adsorption, Langmuir, Freundlich, quartz, illite, calcite, waste water

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Authors: Muhammad Usman

Abstract:

Pattern extraction has been done in past to extract hidden and interesting patterns from large datasets. Recently, advancements are being made in these techniques by providing the ability of multi-level mining, effective dimension reduction, advanced evaluation and visualization support. This paper focuses on reviewing the current techniques in literature on the basis of these parameters. Literature review suggests that most of the techniques which provide multi-level mining and dimension reduction, do not handle mixed-type data during the process. Patterns are not extracted using advanced algorithms for large datasets. Moreover, the evaluation of patterns is not done using advanced measures which are suited for high-dimensional data. Techniques which provide visualization support are unable to handle a large number of rules in a small space. We present a theoretical model to handle these issues. The implementation of the model is beyond the scope of this paper.

Keywords: association rule mining, data mining, data warehouses, visualization of association rules

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Authors: Buruk Kitachew Wossenyeleh

Abstract:

Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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