Search results for: random number

Authors: Zaaraoui Abdelkader, Kerfah Rabeh, Noura Belkheir, Matene Elhacene

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The trapezoidal bluff body is a typical configuration of vortex shedding bodies. The aim of this work is to study flow behaviour over a trapezoidal cylinder at low Reynolds number. The geometry was constructed from a prototype device for measuring the volumetric flow-rate by counting vortices. Simulations were run for this geometry under steady and unsteady flow conditions using finite volume discretization. Laminar flow was investigated in this model with rigid walls and homogeneous incompressible Newtonian fluid. Calculations were performed for Reynolds number range 5 ≤ Re ≤ 180 and several flow parameters were documented. The present computations are in good agreement with the experimental observations and the numerical calculations by several investigators.

Keywords: bluff body, confined flow, numerical calculations, steady and unsteady flow, vortex shedding flow meter

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Frances Bernard Kominkiewicz

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Demonstrating the ability to build social justice and peace is integral in undergraduate and graduate education. Many disciplines are involved in peace education and peace studies, and the collaboration of those disciplines are examined in this paper. To the author’s best knowledge, no content analysis research previously existed regarding peace studies and peace education from a multidisciplinarity, interdisciplinarity, and transdisciplinarity perspective. Peacebuilding is taught through these approaches, which adds to the depth, breadth, and richness of peace education and peace studies. This paper presents a content analysis of academic peace studies programs and course descriptions. Variables studied include contributions and foci of disciplines in peace studies programs and students’ engagement in community peacebuilding. The social work discipline, for example, focuses on social and economic justice as one of the nine competencies that undergraduate and graduate students must attain before earning a Bachelor of Social Work degree or a Master of Social Work degree and becoming social work practitioners. Demonstrating the ability to build social justice and peace is integral in social work education. Peacebuilding is taught through such social work courses as conflict resolution, and social work practice with communities and organizations, and these courses are examined in this research through multidisciplinarity, interdisciplinarity, and transdisciplinarity approach. Peace and social justice are linked terms in various fields, including social work. Social justice is of paramount importance in social work programs, and social workers are trained to advocate for human rights and social, economic, and environmental justice. Social workers use knowledge of oppression, globally as well as nationally, in the practice of peace education and peace studies. Social work is at the forefront in advocating for social justice as a discipline and joins with other educators in strengthening the peacebuilding opportunities for students. The content analysis, conducted through a random sample of peace studies and peace education university and college programs in the United States, found that although courses teach the concepts of peace education and peace studies, courses often are not given these titles in the social work discipline. Therefore, this analysis also includes a discussion of the multidisciplinarity, interdisciplinarity, and transdisciplinarity approach to peace education, peace studies, and peacebuilding and the importance of these approaches in educating students about peace. The content analysis further found great variability in the number of disciplines involved in peace studies programs, the focus of those disciplines in peace education, the placement of peace studies and peace education within the university or college, and the number of courses and concentrations available in peace studies and peace education. In conclusion, the research points toward very robust and diverse approaches to peace education with opportunities for further research and discussion.

Keywords: content analysis, interdisciplinarity, multidisciplinarity, peace education programs

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Esther O. Adebitan, Florence Oyelade

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The Millennium Development Goals (MDGs) was initiated by the UN member nations’ aspiration for the betterment of human life. It is expressed in a set of numerical ‎and time-bound targets. In more recent time, the aspiration is shifting away from just the achievement to the sustainability of achieved MDGs beyond the 2015 target. The main objective of this study was assessing how much the hotel industry within the Nigerian Federal Capital Territory (FCT) as a member of the global community is involved in the achievement of sustainable MDGs within the FCT. The study had two population groups consisting of 160 hotels and the communities where these are located. Stratified random sampling technique was adopted in selecting 60 hotels based on large, medium ‎and small hotels categorisation, while simple random sampling technique was used to elicit information from 30 residents of three of the hotels host communities. The study was guided by tree research questions and two hypotheses aimed to ascertain if hotels see the need to be involved in, and have policies in pursuit of achieving sustained MDGs, and to determine public opinion regarding hotels contribution towards the achievement of the MDGs in their communities. A 22 item questionnaire was designed ‎and administered to hotel managers while 11 item questionnaire was designed ‎and administered to hotels’ host communities. Frequency distribution and percentage as well as Chi-square were used to analyse data. Results showed no significant involvement of the hotel industry in achieving sustained MDGs in the FCT and that there was disconnect between the hotels and their immediate communities. The study recommended that hotels should, as part of their Corporate Social Responsibility pick at least one of the goals to work on in order to be involved in the attainment of enduring Millennium Development Goals.

Keywords: MDGs, hotels, FCT, host communities, corporate social responsibility

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Authors: Kai-Jui Kou, Tzu-Ling Shen, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the different working type in 3D printing room and the stack flue during 3D printing process. The studied laboratory (10.5 m× 7.2 m × 3.2 m) with a ventilation rate of 500 m³/H is installed a 3D metal printing machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L/min, respectively. The concentrations of background, printing process, clearing operation, and screening operation were performed in the laboratory. On the other hand, we also conducted nanoparticle measurement on the 3D printing machine's stack flue to understand its emission characteristics. Results show that the nanoparticles emitted from the different operation process were the same distribution in the form of the uni-modal with number median diameter (NMD) as approximately 28.3 nm to 29.6 nm. The number concentrations of nanoparticles were 2.55×10³ count/cm³ in laboratory background, 2.19×10³ count/cm³ during printing process, 2.29×10³ count/cm³ during clearing process, 3.05×10³ count/cm³ during screening process, 2.69×10³ count/cm³ in laboratory background after printing process, and 6.75×10³ outside laboratory, respectively. We found that there are no emission nanoparticles during the printing process. However, the number concentration of stack flue nanoparticles in the ongoing print is 1.13×10⁶ count/cm³, and that of the non-printing is 1.63×10⁴ count/cm³, with a NMD of 458 nm and 29.4 nm, respectively. It can be confirmed that the measured particle size belongs to easily penetrate the filter in theory during the printing process, even though the 3D printer has a high-efficiency filtration device. Therefore, it is recommended that the stack flue of the 3D printer would be equipped with an appropriate dust collection device to prevent the operators from exposing these hazardous particles.

Keywords: nanoparticle, particle emission, 3D printing, number concentration

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Authors: Binyam Teferi

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In this paper, a theoretical analysis of blood flow in the presence of thermal radiation and chemical reaction under the influence of time dependent magnetic field intensity has been studied. The unsteady non linear partial differential equations of blood flow considers time dependent stretching velocity, the energy equation also accounts time dependent temperature of vessel wall, and concentration equation includes time dependent blood concentration. The governing non linear partial differential equations of motion, energy, and concentration are converted into ordinary differential equations using similarity transformations solved numerically by applying ode45. MATLAB code is used to analyze theoretical facts. The effect of physical parameters viz., permeability parameter, unsteadiness parameter, Prandtl number, Hartmann number, thermal radiation parameter, chemical reaction parameter, and Schmidt number on flow variables viz., velocity of blood flow in the vessel, temperature and concentration of blood has been analyzed and discussed graphically. From the simulation study, the following important results are obtained: velocity of blood flow increases with both increment of permeability and unsteadiness parameter. Temperature of the blood increases in vessel wall as Prandtl number and Hartmann number increases. Concentration of the blood decreases as time dependent chemical reaction parameter and Schmidt number increases.

Keywords: stretching velocity, similarity transformations, time dependent magnetic field intensity, thermal radiation, chemical reaction

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Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

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This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

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Authors: Fahad Alanazi, Andrew Jones

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Digital forensics seeks to achieve the successful investigation of digital crimes through obtaining acceptable evidence from digital devices that can be presented in a court of law. Thus, the digital forensics investigation is normally performed through a number of phases in order to achieve the required level of accuracy in the investigation processes. Since 1984 there have been a number of models and frameworks developed to support the digital investigation processes. In this paper, we review a number of the investigation processes that have been produced throughout the years and introduce a proposed digital forensic model which is based on the scope of the Saudi Arabia investigation process. The proposed model has been integrated with existing models for the investigation processes and produced a new phase to deal with a situation where there is initially insufficient evidence.

Keywords: digital forensics, process, metadata, Traceback, Sauid Arabia

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Authors: Marsudi, Noor Hidayat, Ratno Bagus Edy Wibowo

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This paper considers a deterministic model for the transmission dynamics of HIV/AIDS in which condom campaign and treatment are both important for the disease management. In modelling of the spread of AIDS, the population is divided into six subpopulations, namely susceptible population, susceptible population who change their behavior due to education condom campaign, infected population, pre-AIDS population, treated population and full-blown AIDS population. We calculate the effective reproduction number using the next generation matrix method and investigate the existence and stability of the equilibrium points. A sensitivity analysis discovers parameters that have a high impact on effective reproduction number and should be targeted by intervention strategies. Numerical simulations are given to illustrate and verify our analytic results.

Keywords: HIV/AIDS, condom campaign, antiretroviral treatment, effective reproduction number, stability and sensitivity analysis

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Authors: Juliza Hidayati, Yesie M. Sinuhaji, Sawarni Hasibuan

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A company producing drinking water through many incompatibility issues that affect supply chain performance. The study was conducted to determine the factors that affect the performance of the supply chain and improve it. To obtain the dominant factors affecting the performance of the supply chain used Analytic Network Process, while to improve performance is done by using Kaizen. Factors affecting the performance of the supply chain to be a reference to identify the cause of the non-conformance. Results weighting using ANP indicates that the dominant factor affecting the level of performance is the precision of the number of shipments (15%), the ability of the fulfillment of the booking amount (12%), and the number of rejected products when signing (12%). Incompatibility of the factors that affect the performance of the supply chain are identified, so that found the root cause of the problem is most dominant. Based on the weight of Risk Priority Number (RPN) gained the most dominant root cause of the problem, namely the poorly maintained engine, the engine worked for three shifts, machine parts that are not contained in the plant. Improvements then performed using the Kaizen method of systematic and sustainable.

Keywords: analytic network process, booking amount, risk priority number, supply chain performance

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Authors: Zafar Mahmood, Surayya Naz, Nazir Shah Khattak

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The degree of freedom relates to our capability to observe or model the energy paths within the system. Higher the number of energy paths being modeled leaves to us a higher degree of freedom, but increasing the time and modeling complexity rendering it useless for today’s world’s need for minimum time to market. Since the number of residuals that can be uniquely isolated are dependent on the number of independent outputs of the system, increasing the number of sensors required. The examples of discrete position sensors that may be used to form an array include limit switches, Hall effect sensors, optical sensors, magnetic sensors, etc. Their mechanical design can usually be tailored to fit in the transitional path of an STME in a variety of mechanical configurations. The case studies into multi-sensor system were carried out and actual data from sensors is used to test this generic framework. It is being investigated, how the proper modeling of limit switches as timing sensors, could lead to unified and neutral residual space while keeping the implementation cost reasonably low.

Keywords: low-cost limit sensors, fault diagnostics, Single Throw Mechanical Equipment (STME), parameter estimation, parity-space

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Authors: Raliatu Mohammed Kashim

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The study investigated primary school teachers conceptual and procedural knowledge of rational numbers to determine how it effects on pupil’s achievement on rational number. Specifically, primary school teachers’ level of conceptual and procedural knowledge about rational number and its effects on their pupils understanding of rational number in primary school was explored. The study was carried out in Bauchi state of Nigeria, Using a multistage design. The first stage was a descriptive design. The second stage involves a pre-test post-test only quasi experiment design. The population of the study comprises of six mathematics teachers holding the Nigerian Certificate in Education (NCE) teaching primary six and their two hundred and ten pupils in intact class. Two instrument namely Conceptual and Procedural knowledge Test (CPKT) and Rational number Achievement Test (RAT) were used for data collection. Data collected was analyzed using ANCOVA and Scheffe’s Test. The result revealed a significant differences between pupils taught by teachers with high conceptual and procedural knowledge and those target by teachers with low conceptual and procedural knowledge.

Keywords: conceptual knowledge, procedural knowledge, rational numbers, multistage design

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: Ovais U. Khan, G. M. Arshed, S. A. Raza, H. Ali

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A numerical model based on the computational fluid dynamics (CFD) approach is developed to investigate heat transfer across a longitudinal row of six circular cylinders. The momentum and energy equations are solved using the finite volume discretization technique. The convective terms are discretized using a second-order upwind methodology, whereas diffusion terms are discretized using a central differencing scheme. The second-order implicit technique is utilized to integrate time. Numerical simulations have been carried out for three different values of free stream Reynolds number (ReD) 100, 200, 300 and two different values of dimensionless longitudinal pitch ratio (SL/D) 1.5, 2.5 to demonstrate the fluid flow and heat transfer behavior. Numerical results are validated with the analytical findings reported in the literature and have been found to be in good agreement. The maximum percentage error in values of the average Nusselt number obtained from the numerical and analytical solutions is in the range of 10% for the free stream Reynolds number up to 300. It is demonstrated that the average Nusselt number for the array of cylinders increases with increasing the free stream Reynolds number and dimensionless longitudinal pitch ratio. The information generated would be useful in the design of more efficient heat exchangers or other fluid systems involving arrays of cylinders.

Keywords: computational fluid dynamics, array of cylinders, longitudinal pitch ratio, finite volume method, incompressible navier-stokes equations

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Authors: Davie G. Dave, Prisca H. Mugabe, Tonderai Mutibvu

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Globally, HWCs are on the rise. Such is the case with urban areas in Zimbabwe, yet little has been documented about it. This study was done to provide insights into the occurrence of human-wildlife conflicts in urban areas. The study was carried out in Harare, Bindura, Masvingo, Beitbridge, and Chiredzi to determine the cause, nature, extent, and frequency of occurrence of HWC, to determine the key wildlife species involved in conflicts and management practices done to combat wildlife conflicts in these areas. Several sampling techniques encompassing multi-stage sampling, stratified random, purposive, and simple random sampling were employed for placing residential areas into three strata according to population density, selecting residential areas, and selecting actual participants. Data were collected through a semi-structured questionnaire and key informant interviews. The results revealed that property destruction and crop damage were the most prevalent conflicts. Of the 15 animals that were cited, snakes, baboons, and monkeys were associated with the most conflicts. The occurrence of HWCs was mainly attributed to the increase in both animal and human populations. To curtail these HWCs, the local people mainly used non-lethal methods, whilst lethal methods were used by authorities for some of the reported cases. The majority of the conflicts were seasonal and less severe. There were growing concerns by respondents on the issues of wildlife conflicts, especially in those areas that had primates, such as Warren Park in Harare and Limpopo View in Beitbridge. There are HWCs hotspots in urban areas, and to ameliorate this, suggestions are that there is a need for a multi-action approach that includes general awareness campaigns on HWCs and land use planning that involves the creation of green spaces to ease wildlife management.

Keywords: human-wildlife conflicts, mitigation measures, residential areas, types of conflicts, urban areas

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Authors: Swati Bhasin, Ali Ahmed, Valence Xavier, Ben Liu

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Aims: Diarrhea is a problem that is a frequent clinic referral to the gastroenterology and surgical team from the General practitioner. To establish a diagnosis, these patients undergo colonoscopy. The current practice at our district general hospital is to perform random left and right colonic biopsies. National guidelines issued by the British Society of Gastroenterology advise all patients presenting with chronic diarrhea should have an Ileoscopy as an indicator for colonoscopy completion. Our primary aim was to check if Terminal ileum (TI) biopsy is required to establish a diagnosis of inflammatory bowel disease (IBD). Methods: Data was collected retrospectively from November 2018 to November 2019. The target population were patients who underwent colonoscopies for diarrhea. Demographic data, endoscopic and histology findings of TI were assessed and analyzed. Results: 140 patients with a mean age of 57 years (19-84) underwent a colonoscopy (M: F; 1:2.3). 92 patients had random colonic biopsies taken and based on the histological results of these, 15 patients (16%) were diagnosed with IBD. The TI was successfully intubated in 40 patients, of which 32 patients had colonic biopsies taken as well. 8 patients did not have a colonic biopsy taken. Macroscopic abnormality in the TI was detected in 5 patients, all of whom were biopsied. Based on histological results of the biopsy, 3 patients (12%) were diagnosed with IBD. These 3 patients (100%) also had colonic biopsies taken simultaneously and showed inflammation. None of the patients had a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were not done). None of the patients has a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were negative). Conclusion: TI intubation is a highly-skilled, time-consuming procedure with a higher risk of perforation, which as per our study, has little additional diagnostic value in finding IBD for symptoms of diarrhea if colonic biopsies are taken. We propose that diarrhea is a colonic symptom; therefore, colonic biopsies are positive for inflammation if the diarrhea is secondary to IBD. We conclude that all of the IBDs can be diagnosed simply with colonic biopsies.

Keywords: biopsy, colon, IBD, terminal ileum

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Authors: Shahid Mahboob, Hafiz Muhammad Ashraf, Salma Sultana, Tayyaba Sultana, Khalid Al-Ghanim, Fahid Al-Misned, Zubair Ahmedd

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There is an increasing need for an effective tool to estimate the risks derived from the large number of pollutants released to the environment by human activities. Typical screening procedures are highly invasive or lethal to the fish. Recent studies show that fish scales biochemically respond to a range of contaminants, including toxic metals, organic compounds, and endocrine disruptors. The present study evaluated the effects of the surface water contaminants on Cyprinus carpio in the Ravi River by comparing DNA extracted non-lethally from their scales to DNA extracted from the scales of fish collected from a controlled fish farm. A single, random sampling was conducted. Fish were broadly categorised into three weight categories (W1, W2 and W3). The experimental samples in the W1, W2 and W3 categories had an average DNA concentration (µg/µl) that was lower than the control samples. All control samples had a single DNA band; whereas the experimental samples in W1 fish had 1 to 2 bands, the experimental samples in W2 fish had two bands and the experimental samples in W3 fish had fragmentation in the form of three bands. These bands exhibit the effects of pollution on fish in the Ravi River. On the basis findings of this study, we propose that fish scales can be successfully employed as a new non-lethal tool for the evaluation of the effect of surface water contaminants.

Keywords: fish scales, Cyprinus carpio, heavy metals, non-invasive, DNA fragmentation

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

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Authors: Supriyono, Sumardiyono

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Biodiesel is one of the alternative fuels that promising for substituting petrodiesel as energy source which is have advantage on sustainability and eco-friendly. Due to the raw material that tend to decompose during storage, biodiesel also have the same characteristic that tend to decompose and formed higher acid value which is the result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could prevent by introduce a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. The quality degradation on biodiesel could evaluated by measuring iodine value and acid number of biodiesel. Biodiesel made from High Fatty Acid Jatropha curcas oil equality by using esterification and esterification process will stand on the quality by introduce 90 ppm pyrogallol powder on the biodiesel, which could extend the quality from 2 hours to more than 6 hours in rancimat test evaluation.

Keywords: biodiesel, antioxidant, iodine number, acid value

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Authors: Muhammad Yusuf, Abdul Latief Toleng, Djoni Prawira Rahardja, Ambo Ako, Sahiruddin Sahiruddin, Abdi Eriansyah

Abstract:

The objective of this study was to know the reproductive performance of dairy cows at different parities. A total of 60 dairy Holstein-Friesian cows with parity one to three from five small farms raised by the farmers were used in the study. All cows were confined in tie stall barn with rubber on the concrete floor. The herds were visited twice for survey with the help of a questionnaire. Reproductive parameters used in the study were days open, calving interval, and service per conception (S/C). The results of this study showed that the mean (±SD) days open of the cows in parity 2 was slightly longer than those in parity 3 (228.2±121.5 vs. 205.5±144.5; P=0.061). None cows conceived within 85 days postpartum in parity 3 in comparison to 13.8% cows conceived in parity 2. However, total cows conceived within 150 days post partum in parity 2 and parity 3 were 30.1% and 36.4%, respectively. Likewise, after reaching 210 days after calving, number of cows conceived in parity 3 had higher than number of cows in parity 2 (72.8% vs. 44.8%; P<0.05). The mean (±SD) calving interval of the cows in parity 2 and parity 3 were 508.2±121.5 and 495.5±144.1, respectively. Number of cows with calving interval of 400 and 450 days in parity 3 was higher than those cows in parity 2 (23.1% vs. 17.2% and 53.9% vs. 31.0%). Cows in parity 1 had significantly (P<0.01) lower number of S/C in comparison to the cows with parity 2 and parity 3 (1.6±1.2 vs. 3.5±3.4 and 3.3±2.1). It can be concluded that reproductive performance of the cows is affected by different parities.

Keywords: dairy cows, parity, days open, calving interval, service per conception

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Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Abhishek Kumar, Nilam

Abstract:

As we know that, time delay exists almost in every biological phenomenon. Therefore, in the present study, we propose a susceptible–infected–recovered (SIR) epidemic model along with time delay, modulated incidence rate of infection, and Holling Type II nonlinear treatment rate. The present model aims to provide a strategy to control the spread of epidemics. In the mathematical study of the model, it has been shown that the model has two equilibriums which are named as disease-free equilibrium (DFE) and endemic equilibrium (EE). Further, stability analysis of the model is discussed. To prove the stability of the model at DFE, we derived basic reproduction number, denoted by (R₀). With the help of basic reproduction number (R₀), we showed that the model is locally asymptotically stable at DFE when the basic reproduction number (R₀) less than unity and unstable when the basic reproduction number (R₀) is greater than unity. Furthermore, stability analysis of the model at endemic equilibrium has also been discussed. Finally, numerical simulations have been done using MATLAB 2012b to exemplify the theoretical results.

Keywords: time delayed SIR epidemic model, modulated incidence rate, Holling type II nonlinear treatment rate, stability

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Authors: Mohd A. Azizan, Mohd Z. Zali

Abstract:

It is well established that exposure to vibration has an adverse effect on human health, comfort, and performance. However, there is little quantitative knowledge on performance combined with drowsiness level during vibration exposure. This paper reports a study investigating the influence of vibration amplitude on seated occupant reaction time and drowsiness level. Eighteen male volunteers were recruited for this experiment. Before commencing the experiment, total transmitted acceleration measured at interfaces between the seat pan and seatback to human body was adjusted to become 0.2 ms-2 r.m.s and 0.4 ms-2 r.m.s for each volunteer. Seated volunteers were exposed to Gaussian random vibration with frequency band 1-15 Hz at two level of amplitude (low vibration amplitude and medium vibration amplitude) for 20-minutes in separate days. For the purpose of drowsiness measurement, volunteers were asked to complete 10-minutes PVT test before and after vibration exposure and rate their subjective drowsiness by giving score using Karolinska Sleepiness Scale (KSS) before vibration, every 5-minutes interval and following 20-minutes of vibration exposure. Strong evidence of drowsiness was found as there was a significant increase in reaction time and number of lapse following exposure to vibration in both conditions. However, the effect is more apparent in medium vibration amplitude. A steady increase of drowsiness level can also be observed in KSS in all volunteers. However, no significant differences were found in KSS between low vibration amplitude and medium vibration amplitude. It is concluded that exposure to vibration has an adverse effect on human alertness level and more pronounced at higher vibration amplitude. Taken together, these findings suggest a role of vibration in promoting drowsiness, especially at higher vibration amplitude.

Keywords: drowsiness, human vibration, karolinska sleepiness scale, psychomotor vigilance test

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Authors: Madhu Aneja, Sapna Sharma

Abstract:

The water-based bioconvection of a nanofluid containing motile gyrotactic micro-organisms over nonlinear inclined stretching sheet has been investigated. The governing nonlinear boundary layer equations of the model are reduced to a system of ordinary differential equations via Oberbeck-Boussinesq approximation and similarity transformations. Further, the modified set of equations with associated boundary conditions are solved using Finite Element Method. The impact of various pertinent parameters on the velocity, temperature, nanoparticles concentration, density of motile micro-organisms profiles are obtained and analyzed in details. The results show that with the increase in angle of inclination δ, velocity decreases while temperature, nanoparticles concentration, a density of motile micro-organisms increases. Additionally, the skin friction coefficient, Nusselt number, Sherwood number, density number are computed for various thermophysical parameters. It is noticed that increasing Brownian motion and thermophoresis parameter leads to an increase in temperature of fluid which results in a reduction in Nusselt number. On the contrary, Sherwood number rises with an increase in Brownian motion and thermophoresis parameter. The findings have been validated by comparing the results of special cases with existing studies.

Keywords: bioconvection, finite element method, gyrotactic micro-organisms, inclined stretching sheet, nanofluid

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Authors: Obied A. Alwan, Elgerbi, M. Ali

Abstract:

This study was conducted on the cow milk which is used in the local milk factories of Zawia. This was completely random sampling the unscheduled samples. The microbiologic result have approved that the count of bacteria and the count of E.Coli are very high and all the manufacturing places which were included in the study have lacked the health conditions.

Keywords: raw milk, dairy factories, Libya, microbiologic

Procedia PDF Downloads 441

Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

Abstract:

Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

Procedia PDF Downloads 163