Search results for: Gaussian Mixture Model

Authors: Sina Saadati, Mohammadreza Razzazi

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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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Authors: Ahmed Mohamed Nasr, Waseim Ragab Azzam, Nada Osama Ramadan

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Contaminated soil can weaken the stability of buildings and infrastructure, posing serious risks to their structural integrity. Therefore, this study aims to understand how oil contamination affects the torsion behavior of model steel piles at different soil densities. This research is crucial for evaluating the structural integrity and stability of piles in oil-contaminated environments. Clean sand samples and heavy motor oil were mixed in amounts ranging from 0 to 6% of the soil's dry weight. The mixture was thoroughly mixed to ensure uniform distribution of the oil throughout the sandy soil for simulating the field conditions. In these investigations, the relative densities (Dr), pile slenderness ratio (Lp/Dp), oil content (O.C%), and contaminated sand layer thickness (LC) were all different. Also, the paper presents an analysis of piles that are loaded both vertically and torsionally. The findings demonstrated that the pre-applied torsion load led to a decrease in the vertical bearing ability of the pile. Also, at Dr = 80%, the ultimate vertical load under combined load at constant torsional load T = (1/3Tu, 2/3Tu, and Tu) in the cases of (Lc/Lp) = 0.5 and (Lp/Dp) =13.3 was found to be reduced by (1.48, 2.78, and 4.15%) less than piles under independent vertical load, respectively so it is crucial to consider the torsion load during pile design.

Keywords: torsion-vertical load, oil-contaminated sand, twist angle, steel pile

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Authors: Isam A. H. Al Zubaidy

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A quick process may be needed to get the benefit the big generated quantity of waste oil sludge (WOS). The process includes the mixing process of WOS with commercial diesel fuel. Different ratios of WOS to diesel fuel were prepared ranging 1:1 to 20:1 by mass. The mixture was continuously mixing for 10 minutes using bench type overhead stirrer and followed by filtration process to separate the soil waste from filtrate oil product. The quantity and the physical properties of the oil filtrate were measured. It was found that the addition of up to 15% WOS to diesel fuel was accepted without dramatic changes to the properties of diesel fuel. The amount of waste oil sludge was decreased by about 60% by mass. This means that about 60 % of the mass of sludge was recovered as light fuel oil. The physical properties of the resulting fuel from 10% sludge mixing ratio showed that the specific gravity, ash content, carbon residue, asphaltene content, viscosity, diesel index, cetane number, and calorific value were affected slightly. The color was changed to light black color. The sulfur content was increased also. This requires other processes to reduce the sulfur content of the resulting light fuel. A new desulfurization process was achieved using adsorption techniques with activated biomaterial to reduce the sulfur content to acceptable limits. Adsorption process by ZnCl₂ activated date palm kernel powder was effective for improvement of the physical properties of diesel like fuel. The final sulfur content was increased to 0.185 wt%. This diesel like fuel can be used in all tractors, buses, tracks inside and outside the refineries. The solid remaining seems to be smooth and can be mixed with asphalt mixture for asphalting the roads or can be used with other materials as an asphalt coating material for constructed buildings. Through this process, valuable fuel has been recovered, and the amount of waste material had decreased.

Keywords: oil sludge, diesel fuel, blending process, filtration process

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Authors: Mahacine Amrani

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This paper aims at reviewing some Moroccan industrial applications of wavelet especially in the dynamic identification of a process model using Haar wavelet mother response. Two recent Moroccan study cases are described using dynamic data originated by a distillation column and an industrial polyethylene process plant. The purpose of the wavelet scheme is to build on-line dynamic models. In both case studies, a comparison is carried out between the Haar wavelet mother response model and a linear difference equation model. Finally it concludes, on the base of the comparison of the process performances and the best responses, which may be useful to create an estimated on-line internal model control and its application towards model-predictive controllers (MPC). All calculations were implemented using AutoSignal Software.

Keywords: process performance, model, wavelets, Haar, Moroccan

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Authors: Okike Benjamin, Garba E. J. D.

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The researcher has developed a new encryption technique known as Merged Irregular Transposition Cipher. In this cipher method of encryption, a message to be encrypted is split into parts and each part encrypted separately. Before the encrypted message is transmitted to the recipient(s), the positions of the split in the encrypted messages could be swapped to ensure more security. This work seeks to develop a model by considering the split number, S and the average number of characters per split, L as the message under consideration is split from 2 through 10. Again, after developing the model, the error level in the model would be determined.

Keywords: merged irregular transposition, error level, model estimation, message splitting

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Authors: Mohanaad Talal Shakir

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This paper tries to propose educational design by using multimedia technology for Engineering of computer Technology, Alma'ref University College in Iraq. This paper evaluates the acceptance, cognition, and interactiveness of the proposed model by students by using the statistical relationship to determine the stage of the model. Objectives of proposed education design are to develop a user-friendly software for education purposes using multimedia technology and to develop animation for 3D model to simulate assembling and disassembling process of high-speed flow.

Keywords: CAL, multimedia, shock tunnel, interactivity, engineering education

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Authors: Zineddine Bouyahiaoui, Rabah Haoui

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The aim of this work is to analyze a flow around the axisymmetric blunt body taken into account the chemical and vibrational nonequilibrium flow. This work concerns the entry of spacecraft in the atmosphere of the planet Mars. Since the equations involved are non-linear partial derivatives, the volume method is the only way to solve this problem. The choice of the mesh and the CFL is a condition for the convergence to have the stationary solution.

Keywords: blunt body, finite volume, hypersonic flow, viscous flow

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Authors: Zhidong Zhang, Yingchen Yang

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In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

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Authors: Mozhgan Bahadory, Gholam-Hossein Rostami

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Over the next quarter of a century, the US government and the private sector will spend billions of dollars annually to clean the contaminated sites from pollution such as petroleum products, heavy metals, and solvents organic compounds. During the past three decades, almost 750,000 sites that require remediation have been reported to the United States federal and state agencies. Out of these contamination sites, approximately 300,000 are still in need of remediation. In these sites, the most widespread forms of contamination are petroleum products and heavy metals. At least half of US Department of Defense, US Department of Energy, Superfund sites, and Resource Conservation and Recovery Act (RCRA) sites have been reported to contain heavy metals. Heavy metals most often found in the contaminated water are lead, mercury, chromium, cadmium, arsenic, and zinc. This investigation emphasizes the elimination of arsenic and cadmium from aqueous solution. During the past several years, we developed a novel material called Alkali-Activated fly ash Material Permeable Reactive Barrier (AAM-PRB), which includes fly ash, fine aggregates, coarse aggregates, activating chemicals, and water. AAM can be produced with high permeability, 10-1 cm/s, then crushed into pelletized form. Laboratory experiments showed that water containing 10 ppm, 100 ppm, and 1000 ppm of arsenic and cadmium ion passing through AAM-PRB reduced to less than 0.1 ppm. However, water containing 10,000 ppm arsenic ion passing through AAM- PRB shows that the breakthrough was achieved. The removal of the mixture of arsenic and cadmium from aqueous solutions was also tested by using AAM-PRB. The results indicate that the efficiency of AAM-PRB for simultaneous removal of arsenic and cadmium from 10 ppm, 100 ppm, and 1,000 ppm were marginally below that of arsenic alone. Still, it was significantly lower for cadmium from the aqueous solution. The basic science behind removing heavy metal and microstructural investigation AAM-PRB will be the focus of our future work.

Keywords: arsenic, cadmium, contaminated water, fly ash, permeability, reactive barrier

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Authors: Ion Smeureanu, Adriana Reveiu, Marian Dardala, Titus Felix Furtuna, Roman Kanala

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This paper proposes a linear model for optimizing domestic energy consumption, in Romania. Both techno-economic and consumer behavior approaches have been considered, in order to develop the model. The proposed model aims to reduce the energy consumption, in households, by assembling in a unitary model, aspects concerning: residential lighting, space heating, hot water, and combined space heating – hot water, space cooling, and passenger transport. This paper focuses on space heating domestic energy consumption model, and quantify not only technical-economic issues, but also consumer behavior impact, related to people decision to envelope and insulate buildings, in order to minimize energy consumption.

Keywords: consumer behavior, open source energy modeling system (OSeMOSYS), MARKAL/TIMES Romanian energy model, virtual technologies

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Hassan Al Salman

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We consider a nonlinear parabolic cross diffusion model arising in applied mathematics. A fully practical piecewise linear finite element approximation of the model is studied. By using entropy-type inequalities and compactness arguments, existence of a global weak solution is proved. Providing further regularity of the solution of the model, some uniqueness results and error estimates are established. Finally, some numerical experiments are performed.

Keywords: cross diffusion model, entropy-type inequality, finite element approximation, numerical analysis

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Abdulrazzak Akroot, Lutfu Namli

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Solid oxide fuel cells (SOFCs) are one of the most promising technologies since they can produce electricity directly from fuel and generate a lot of waste heat that is generally used in the gas turbines to promote the general performance of the thermal power plant. In this study, the energy, and exergy analysis of a solid oxide fuel cell/gas turbine hybrid system was proceed in MATLAB to examine the performance characteristics of the hybrid system in two different configurations: anode-supported model and electrolyte-supported model. The obtained results indicate that if the fuel utilization factor reduces from 0.85 to 0.65, the overall efficiency decreases from 64.61 to 59.27% for the anode-supported model whereas it reduces from 58.3 to 56.4% for the electrolyte-supported model. Besides, the overall exergy reduces from 53.86 to 44.06% for the anode-supported model whereas it reduces from 39.96 to 33.94% for the electrolyte-supported model. Furthermore, increasing the air utilization factor has a negative impact on the electrical power output and the efficiencies of the overall system due to the reduction in the O₂ concentration at the cathode-electrolyte interface.

Keywords: solid oxide fuel cell, anode-supported model, electrolyte-supported model, energy analysis, exergy analysis

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Authors: Mustapha Kamel Mihoubi, Hocine Dahmani

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The purpose of work is to study the phenomenon of agitation of storm waves at basin caused by different directions of waves relative to the current provision thrown numerical model based on the equation in shallow water using Boussinesq model MIKE 21 BW. According to the diminishing effect of penetration of a wave optimal solution will be available to be reproduced in reduced model. Another alternative arrangement throws will be proposed to reduce the agitation and the effects of the swell reflection caused by the penetration of waves in the harbor.

Keywords: agitation, Boussinesq equations, combination, harbor

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Authors: Matthew Perkins-McVey

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The pharmacological arm of mental health treatment is in a state of crisis. The promises of the Prozac century have fallen short; the number of different therapeutically significant medications that successfully complete development shrinks with every passing year, and the demand for better treatments only grows. Answering these hardships is a renewed optimism concerning the efficacy of controlled psychedelic therapy, a renaissance that has seen the return of a familiar concept: intoxication as a model psychosis. First appearing in the mid-19th century and featuring in an array of 20th century efforts in psychedelic research, model psychosis has, once more, come to the foreground of psychedelic research. And yet, little has been made of where this peculiar, perhaps even intoxicatingly mad, the idea originates. This paper seeks to uncover the conceptual foundations underlying the early emergence of model psychosis. This narrative will explore the conceptual foundations behind their independent development of the concept of model psychosis, considering their similarities and differences. In the course of this examination, it becomes apparent that the definition of endogenous psychosis, which formed in the mid-19th century, is the direct product of emerging understandings of exogenous psychosis, or model psychosis. Ultimately, the goal is not merely to understand how and why model psychosis became thinkable but to examine how seemingly secondary concept changes can engender new ways of being a psychiatric subject.

Keywords: history of psychiatry, model psychosis, history of medicine, history of science

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Gerald Amatre, Julius Bunny Lejju, Morgan Andama

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Despite several interventions, jigger flea infestations continue to be reported in the Busoga sub-region in Eastern Uganda. The purpose of this study was to identify factors that expose the indigenous people to jigger flea infestations and evaluate the effectiveness of any indigenous materials used in flea control by the affected communities. Flea compositions in residences were described, factors associated with flea infestation and indigenous materials used in flea control were evaluated. Field surveys were conducted in the affected communities after obtaining preliminary information on jigger infestation from the offices of the District Health Inspectors to identify the affected villages and households. Informed consent was then sought from the local authorities and household heads to conduct the study. Focus group discussions were conducted with key district informants, namely, the District Health Inspectors, District Entomologists and representatives from the District Health Office. A GPS coordinate was taken at central point at every household enrolled. Fleas were trapped inside residences using Kilonzo traps. A Kilonzo Trap comprised a shallow pan, about three centimetres deep, filled to the brim with water. The edges of the pan were smeared with Vaseline to prevent fleas from crawling out. Traps were placed in the evening and checked every morning the following day. The trapped fleas were collected in labelled vials filled with 70% aqueous ethanol and taken to the laboratory for identification. Socio-economic and environmental data were collected. The results indicate that the commonest flea trapped in the residences was the cat flea (Ctenocephalides felis) (50%), followed by Jigger flea (Tunga penetrans) (46%) and rat flea (Xenopsylla Cheopis) (4%), respectively. The average size of residences was seven squire metres with a mean of six occupants. The residences were generally untidy; with loose dusty floors and the brick walls were not plastered. The majority of the jigger affected households were headed by peasants (86.7%) and artisans (13.3%). The household heads mainly stopped at primary school level (80%) and few at secondary school level (20%). The jigger affected households were mainly headed by peasants of low socioeconomic status. The affected community members use soil-cow dung-ash mixture to smear floors of residences as the only measure to control fleas. This method was found to be ineffective in controlling the insects. The study recommends that home improvement campaigns be continued in the affected communities to improve sanitation and hygiene in residences as one of the interventions to combat flea infestations. Other cheap, available and effective means should be identified to curb jigger flea infestations.

Keywords: cow dung-soil-ash mixture, infestations, jigger flea, Tunga penetrans

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: Babak Bashari Rad

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A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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Authors: Vilma Sasyte, Vilma Viliene, Asta Raceviciute-Stupeliene, Agila Dauksiene, Romas Gruzauskas, Virginijus Slausgalvis, Jamal Al-Saifi

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The aim of the present study was to investigate the effect of butyrate, acids, medium-chain fatty acids and plant extract mixture on performance, blood and gastrointestinal tract characteristics of laying hens’. For the period of 8 weeks, 24 Hisex Brown laying hens were randomly assigned to 2 dietary treatments: 1) control wheat-corn-soybean meal based diet (Control group), 2) control diet supplemented with the mixture of butyrate, acids, medium chain fatty acids and plant extract (Lumance®) at the level of 1.5 g/kg of feed (Experimental group). Hens were fed with a crumbled diet at 125 g per day. Housing and feeding conditions were the same for all groups and met the requirements of growth for laying hens of Hisex Brown strain. In the blood serum total protein, bilirubin, cholesterol, DTL- and MTL- cholesterol, triglycerides, glucose, GGT, GOT, GPT, alkaline phosphatase, alpha amylase, contents of c-reactive protein, uric acid, and lipase were analyzed. Development of intestines and internal organs (intestinal length, intestinal weight, the weight of glandular and muscular stomach, pancreas, heart, and liver) were determined. The concentration of short chain fatty acids in caecal content was measured using the method of HPLC. The results of the present study showed that 1.5 g/kg supplementation of feed additive affected egg production and feed conversion ratio for the production of 1 kg of egg mass. Dietary supplementation of analyzed additive in the diets increased the concentration of triglycerides, GOT, alkaline phosphatase and decreased uric acid content compared with the control group (P<0.05). No significant difference for others blood indices in comparison to the control was observed. The addition of feed additives in laying hens’ diets increased intestinal weight by 11% and liver weight by 14% compared with the control group (P<0.05). The short chain fatty acids (propionic, acetic and butyric acids) in the caecum of laying hens in experimental groups decreased compared with the control group. The supplementation of the mixture of butyrate, acids, medium-chain fatty acids and plant extract at the level of 1.5 g/kg in the laying hens’ diets had the effect on the performance, some gastrointestinal tract function and blood parameters of laying hens.

Keywords: acids, butyrate, laying hens, MCFA, performance, plant extract, psysiological state

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Heung Sun Yoon, Jong Tae Kim

Abstract:

In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle

Procedia PDF Downloads 396

Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

Abstract:

The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

Abstract:

A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

Procedia PDF Downloads 157