Search results for: churn prediction modeling

Authors: Alexander Pesin, Denis Pustovoytov, Mikhail Sverdlik

Abstract:

Materials with ultrafine-grained structure and unique physical and mechanical properties can be obtained by methods of severe plastic deformation, which include processes of asymmetric rolling (AR). Asymmetric rolling is a very effective way to create ultrafine-grained structures of metals and alloys. Since the asymmetric rolling is a continuous process, it has great potential for industrial production of ultrafine-grained structure sheets. Basic principles of asymmetric rolling are described in detail in scientific literature. In this work finite element modeling of asymmetric rolling and metal forming processes in multiroll gauge was performed. Parameters of the processes which allow achieving significant values of shear strain were defined. The results of the study will be useful for the research of the evolution of ultra-fine metal structure in asymmetric rolling.

Keywords: asymmetric rolling, equivalent strain, FEM, multiroll gauge, profile, severe plastic deformation, shear strain, sheet

Procedia PDF Downloads 257

Authors: N. Massoum, A. Guen. Bouazza, B. Bouazza, A. El Ouchdi

Abstract:

The progress of industry integrated circuits in recent years has been pushed by continuous miniaturization of transistors. With the reduction of dimensions of components at 0.1 micron and below, new physical effects come into play as the standard simulators of two dimensions (2D) do not consider. In fact the third dimension comes into play because the transverse and longitudinal dimensions of the components are of the same order of magnitude. To describe the operation of such components with greater fidelity, we must refine simulation tools and adapted to take into account these phenomena. After an analytical study of the static characteristics of the component, according to the different operating modes, a numerical simulation is performed of field-effect transistor with submicron gate MESFET GaInP. The influence of the dimensions of the gate length is studied. The results are used to determine the optimal geometric and physical parameters of the component for their specific applications and uses.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, GaInP

Procedia PDF Downloads 411

Authors: Rida B. Arieby, Hameed N. Hameed

Abstract:

In this work, tensile tests on high density polyethylene have been carried out under various constant strain rate and strain rate jump tests. The dependency of the true stress and specially the variation of volume strain have been investigated, the volume strain due to the phenomena of damage was determined in real time during the tests by an optical extensometer called Videotraction. A modified constitutive equations, including strain rate and damage effects, are proposed, such a model is based on a non-equilibrium thermodynamic approach called (DNLR). The ability of the model to predict the complex nonlinear response of this polymer is examined by comparing the model simulation with the available experimental data, which demonstrate that this model can represent the deformation behavior of the polymer reasonably well.

Keywords: strain rate jump tests, volume strain, high density polyethylene, large strain, thermodynamics approach

Procedia PDF Downloads 255

Authors: A. Soualem

Abstract:

The design of multi stage deep drawing processes requires the evaluation of many process parameters such as the intermediate die geometry, the blank shape, the sheet thickness, the blank holder force, friction, lubrication etc..These process parameters have to be determined for the optimum forming conditions before the process design. In general sheet metal forming may involve stretching drawing or various combinations of these basic modes of deformation. It is important to determine the influence of the process variables in the design of sheet metal working process. Especially, the punch and die corner for deep drawing will affect the formability. At the same time the prediction of sheet metals springback after deep drawing is an important issue to solve for the control of manufacturing processes. Nowadays, the importance of this problem increases because of the use of steel sheeting with high stress and also aluminum alloys. The aim of this paper is to give a better understanding of the springback and its effect in various sheet metals forming process such as expansion and restraint deep drawing in the cup drawing process, by varying radius die, lubricant for two commercially available materials e.g. galvanized steel and Aluminum sheet. To achieve these goals experiments were carried out and compared with other results. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback.

Keywords: springback, deep drawing, expansion, restricted deep drawing

Procedia PDF Downloads 451

Authors: Cristian Crespo

Abstract:

Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

Procedia PDF Downloads 196

Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

Abstract:

The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: bonded rubber, quasi-static test, shape factor, apparent Young’s modulus

Procedia PDF Downloads 166

Authors: K. Grigoryan, T. Jurcik

Abstract:

Interpersonal and school-related factors, along with individual characteristics, can predict non-suicidal self-injures (NSSI). The objective of this review is to describe psychosocial variables associated with NSSI among adolescents. A better understanding of this phenomenon may facilitate the identification of potentially effective interventions for adolescents. Relevant empirical studies and reviews from clinical, cross-cultural, and social psychology, as well as cognitive psychology literature, were synthesized into two broad topics: social/interpersonal and individual factors. Variables related to the occurrence of NSSI are discussed, including social support, peer modeling, abuse, personality traits, sense of belongingness, self-compassion, and others. Based on these findings, specific clinical recommendations were identified that need to be further evaluated empirically. The systemic interventions recommended in this review may further promote research in circumventing this social and clinical problem.

Keywords: non-suicidal self-injury, psychosocial factors, mental health, adolescence

Procedia PDF Downloads 184

Authors: Anastasios Zopiatis, Antonis L. Theocharous

Abstract:

In the midst of a fierce war for talent, the hospitality industry is seeking new and innovative ways to enrich its image as an employer of choice and not a necessity. Historically, the industry’s professions are portrayed as ‘unattractive’ due to their repetitious nature, long and unsocial working schedules, below average remunerations, and the mental and physical demands of the job. Aligning with the industry, hospitality and tourism scholars embarked on a journey to investigate pertinent topics with the aim of enhancing our conceptual understanding of the elements that influence employees at the hospitality world of work. Topics such as job involvement, commitment, job and career satisfaction, and turnover intentions became the focal points in a multitude of relevant empirical and conceptual investigations. Nevertheless, gaps or inconsistencies in existing theories, as a result of both the volatile complexity of the relationships governing human behavior in the hospitality workplace, and the academic community’s unopposed acceptance of theoretical frameworks mainly propounded in the United States and United Kingdom years ago, necessitate our continuous vigilance. Thus, in an effort to enhance and enrich the discourse, we set out to investigate the relationship between intrinsic and extrinsic job satisfaction traits and the individual’s career satisfaction, and subsequent intention to remain in the hospitality industry. Reflecting on existing literature, a quantitative survey was developed and administered, face-to-face, to 650 individuals working as full-time employees in 4- and 5- star hotel establishments in Cyprus, whereas a multivariate statistical analysis method, namely Structural Equation Modeling (SEM), was utilized to determine whether relationships existed between constructs as a means to either accept or reject the hypothesized theory. Findings, of interest to both industry stakeholders and academic scholars, suggest that the individual’s future intention to remain within the industry is primarily associated with extrinsic job traits. Our findings revealed that positive associations exist between extrinsic job traits, and both career satisfaction and future intention. In contrast, when investigating the relationship of intrinsic traits, a positive association was revealed only with career satisfaction. Apparently, the local industry’s environmental factors of seasonality, excessive turnover, overdependence on seasonal, and part-time migrant workers, prohibit industry stakeholders in effectively investing the time and resources in the development and professional growth of their employees. Consequently intrinsic job satisfaction factors such as advancement, growth, and achievement, take backstage to the more materialistic extrinsic factors. Findings from the subsequent mediation analysis support the notion that intrinsic traits can positively influence future intentions indirectly only through career satisfaction, whereas extrinsic traits can positively impact both career satisfaction and future intention both directly and indirectly.

Keywords: career satisfaction, Cyprus, hotel employees, structural equation modeling, SEM

Procedia PDF Downloads 276

Authors: Hossein Emari, Hossein Vazifehdoust, Hashem Nikoo Maram

Abstract:

This study aims to develop an original framework of Environmental Consciousness (EC) to explore the positive effect of environmental consciousness on financial performance through the partial mediator - green intellectual capital. A questionnaire survey on the environmental consciousness, intellectual capital, and financial performance of Iran’s manufacturing firms was conducted, and 324 samples were analyzed. This study utilizes structural equation modeling to explore the direct and indirect influences of EC on financial performance. Research results reveal that environmental consciousness had an indirect impact on financial performance through investment in green intellectual capital. It was thus known that green intellectual capital is a mediator of the relationship between environmental consciousness and financial performance. This paper may serve as a reference for firms mapping out future environmental policies and provide an input of various perspectives and arguments into the discipline of green management.

Keywords: environmental consciousness, social responsibility, green intellectual capital, financial performance

Procedia PDF Downloads 482

Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

Abstract:

The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

Procedia PDF Downloads 482

Authors: Zohra Benfodda, Valentin Duvauchelle, Chaimae Majdi, David Bénimélis, Catherine Dunyach-Remy, Patrick Meffre

Abstract:

New antibiotics are necessary to treat microbial pathogens, especially ESKAPE pathogens that are becoming increasingly resistant to available treatment. Despite the medical need, the number of newly approved drugs continues to decline. The majority of antibiotics under clinical development are natural products or derivatives thereof. 43 juglone/naphthazarin derivatives were synthesized using Minisci-type direct C–H alkylation and evaluated for their antibacterial properties against various clinical and reference Gram-positive MSSA, clinical Gram-positive MRSA. Different compounds of the synthesized series showed promising activity against clinical and reference MSSA (MIC: 1–8 μg/ml) and good efficacy against clinical MRSA (MIC: 2–8 μg/ml) strains. The synergistic effects of active compounds were evaluated with reference antibiotics (vancomycin and cloxacillin), and it was found that the antibiotic combination with those active compounds efficiently enhanced the antimicrobial activity and consequently the MIC values of reference antibiotics were lowered up to 1/16th of the original MIC. These synthesized compounds did not present hemolytic activity on sheep red blood cells. In addition to the in silico prediction of ADME profile parameter which is promising and encouraging for further development.

Keywords: juglone, naphthazarin, antibacterial, clinical MRSA, synergistic studies, MIC determination

Procedia PDF Downloads 120

Authors: Mahmoud Owais

Abstract:

Public Transit (P.T) is very important means to reduce traffic congestion, to improve urban environmental conditions and consequently affects people social lives. Planning, designing and management of P.T are the key issues for offering a competitive mode that can compete with the private transportation. These transportation planning, designing and management issues are addressed in the Transit Network Design Problem (TNDP). It deals with a complete hierarchy of decision making process. It includes strategic, tactical and operational decisions. The main body of TNDP is two stages, namely; route design stage and frequency setting. The TNDP is extensively studied in the last five decades; however the research gate is still widely open due to its many practical and modeling challenges. In this paper, a comprehensive background is given to illustrate the issues and challenges related to the TNDP to help in directing the incoming researches towards the untouched areas of the problem.

Keywords: frequency setting, network design, transit planning, urban planning

Procedia PDF Downloads 377

Authors: M. Najafi, F. Rahimi Dehgolan

Abstract:

In this paper, the dynamic modeling of a single-link flexible beam with a tip mass is given by using Hamilton's principle. The link has been rotational and translational motion and it was assumed that the beam is moving with a harmonic velocity about a constant mean velocity. Non-linearity has been introduced by including the non-linear strain to the analysis. Dynamic model is obtained by Euler-Bernoulli beam assumption and modal expansion method. Also, the effects of rotary inertia, axial force, and associated boundary conditions of the dynamic model were analyzed. Since the complex boundary value problem cannot be solved analytically, the multiple scale method is utilized to obtain an approximate solution. Finally, the effects of several conditions on the differences among the behavior of the non-linear term, mean velocity on natural frequencies and the system stability are discussed.

Keywords: non-linear vibration, stability, axially moving beam, bifurcation, multiple scales method

Procedia PDF Downloads 362

Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

Abstract:

This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: noise, signal-to-noise ratio, stochastic signals, variance estimation

Procedia PDF Downloads 382

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

Abstract:

The river is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that need to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between the main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of the main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel, and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

Procedia PDF Downloads 169

Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

Procedia PDF Downloads 148

Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

Abstract:

This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

Procedia PDF Downloads 246

Authors: J. F. Viljoen, Catherine Foxcroft

Abstract:

Expert sight readers rely on their ability to recognize patterns in scores, their inner hearing and prediction skills in order to perform complex sight reading exercises. They also have the ability to observe deviations from expected patterns in musical scores. This increases the “Eye-hand span” (reading ahead of the point of playing) in order to process the elements in the score. The study aims to investigate the gaze patterns of expert and non-expert sight readers focusing on key and time signatures. 20 musicians were tasked with playing 12 sight reading examples composed for one hand and five examples composed for two hands to be performed on a piano keyboard. These examples were composed in different keys and time signatures and included accidentals and changes of time signature to test this theory. Results showed that the experts fixate more and for longer on key and time signatures as well as deviations in examples for two hands than the non-expert group. The inverse was true for the examples for one hand, where expert sight readers showed fewer and shorter fixations on key and time signatures as well as deviations. This seems to suggest that experts focus more on the key and time signatures as well as deviations in complex scores to facilitate sight reading. The examples written for one appeared to be too easy for the expert sight readers, compromising gaze patterns.

Keywords: cognition, eye tracking, musical notation, sight reading

Procedia PDF Downloads 136

Authors: Herlina Abdul Rahim, Javad Abbaszadeh, Ruzairi Abdul Rahim

Abstract:

In this research, the non-invasive ultrasonic transmission tomography is investigated. In order to model the ultrasonic wave scattering for different thickness of metal pipes, two-dimensional (2D) finite element modeling (FEM) has been utilized. The wall thickness variation of the metal pipe and its influence on propagation of the ultrasonic pressure wave are explored in this paper, includes frequency analysing in order to find the maximum applicable frequency. The simulation results have been compared to experimental data and are shown to provide key insight for this well-defined experimental case by explaining the achieved reconstructed images from experimental setup. Finally, the experimental results which are useful for further investigation for the application of ultrasonic transmission tomography in industry are illustrated.

Keywords: ultrasonic transmission tomography, ultrasonic sensors, ultrasonic wave, non-invasive tomography, metal pipe

Procedia PDF Downloads 351

Authors: Rachid Zentar, Mokrane Bala, Pascal Boustingorry

Abstract:

The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.

Keywords: crushed aggregates, intrinsic viscosity, packing density, rolled aggregates, slump, yield stress of concrete

Procedia PDF Downloads 120

Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović

Abstract:

This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (R_a) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.

Keywords: fuzzy logic, metal machining, process modeling, surface roughness

Procedia PDF Downloads 158

Authors: Naso Isaiah Thanavisuth

Abstract:

Medical cannabis can be used for treatment including pain, multiple sclerosis, Parkinson's disease, and cancer. However, medical cannabis leads to adverse effects (AEs), which is delta-9-tetrahydrocannabinol (THC). In previous studies, the major of THC metabolism enzymes are CYP2C9. Especially, the variation of CYP2C9 gene consist of CYP2C9*2 on exon 3 and CYP2C9*3 on exon 7 to decrease enzyme activity. Notwithstanding, there is no data describing whether the variant of CYP2C9 genes are apharmacogenetics marker for the prediction of THC-induced AEs in Thai patients. We want to investigate the association between CYP2C9 gene and THC-induced AEs in Thai patients. We enrolled 39 Thai patients with medical cannabis treatment who were classified by clinical data. The CYP2C9*2 and *3 genotyping were conducted using the TaqMan real time PCR assay. All Thai patients who received the medical cannabis consist of twenty-four (61.54%) patients were female, and fifteen (38.46%) were male, with age range 27- 87 years. Moreover, the most AEs in Thai patients who were treated with medical cannabis between cases and controls were tachycardia, arrhythmia, dry mouth, and nausea. Particularly, thirteen (72.22%) medical cannabis-induced AEs were female and age range 33 – 69 years. In this study, none of the medical cannabis groups carried CYP2C9*2 variants in Thai patients. The CYP2C9*3 variants (*1/*3, intermediate metabolizer, IM) and (*3/*3, poor metabolizer, PM) were found, three of thirty-nine (7.69%) and one of thirty-nine (2.56%), respectively. Although, our results indicate that there is no found the CYP2C9*2. However, the variation of CYP2C9 allele might serve as a pharmacogenetics marker for screening before initiating the therapy with medical cannabis for the prevention of medical cannabis-induced AEs.

Keywords: CYP2C9, medical cannabis, adverse effects, THC, P450

Procedia PDF Downloads 115

Authors: Sourita Ghosh, Falguni Pati, Suhanya Duraiswamy

Abstract:

Spheroid, a simple three-dimensional cellular aggregate, allows us to simulate the in-vivo complexity of cellular signaling and interactions in greater detail than traditional 2D cell culture. It can be used as an in-vitro model for drug toxicity testing, tumor modeling and many other such applications specifically for cancer. Our work is focused on the development of an affordable, user-friendly, robust, reproducible, high throughput microfluidic device for water in oil droplet production, which can, in turn, be used for spheroids manufacturing. Here, we have investigated the droplet breakup between two non-Newtonian fluids, viz. silicone oil and decellularized liver matrix, which acts as our extra cellular matrix (ECM) for spheroids formation. We performed some biochemical assays to characterize the liver ECM, as well as rheological studies on our two fluids and observed a critical dependence of capillary number (Ca) on droplet breakup and homogeneous drop formation

Keywords: chip less, droplets, extracellular matrix, liver spheroid

Procedia PDF Downloads 84

Authors: Joselito Medina Marin, Norberto Hernández Romero, Juan Carlos Seck Tuoh Mora, Erick S. Martinez Gomez

Abstract:

The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools.

Keywords: flow-shop scheduling problem, makespan, Petri nets, state equation

Procedia PDF Downloads 292

Authors: H. Golchoobian, S. Saedodin, M. H. Taheri, A. Sarafraz

Abstract:

In this paper, natural convection in an attic is numerically investigated. The geometry of the problem is considered to be a triangular enclosure. ANSYS Fluent software is used for modeling and numerical solution. This study is for steady state. Four right-angled triangles with height to base ratios of 2, 1, 0.5 and 0.25 are considered. The behavior of various parameters related to its performance, including temperature distribution and velocity vectors are evaluated, and graphs for the Nusselt number have been drawn. Also, in this study, the effect of geometric shape of enclosure with different height-to-base ratios has been evaluated for three types of boundary conditions of winter, summer day and one another state. It can be concluded that as the bottom side temperature and ratio of base to height of the enclosure increases, the convective effects become more prominent and circulation happened.

Keywords: enclosure, natural convection, numerical solution, Nusselt number, triangular

Procedia PDF Downloads 192

Authors: N. F. F. Ebecken, G. C. Pereira

Abstract:

Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.

Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks

Procedia PDF Downloads 295

Authors: Naoyuki Sugihashi, Toshiharu Kishi

Abstract:

The probability of occurrence of thermal cracks in mass concrete in Japan is evaluated by the cracking probability diagram that represents the relationship between the thermal cracking index and the probability of occurrence of cracks in the actual structure. In this paper, we propose a method to directly calculate the cracking probability, following a probabilistic theory by modeling the variance of tensile stress and tensile strength. In this method, the relationship between the variance of tensile stress and tensile strength, the thermal cracking index, and the cracking probability are formulated and presented. In addition, standard deviation of tensile stress and tensile strength was identified, and the method of calculating cracking probability in a general construction controlled environment was also demonstrated.

Keywords: thermal crack control, mass concrete, thermal cracking probability, durability of concrete, calculating method of cracking probability

Procedia PDF Downloads 337

Authors: Wen-Shyong Tzou, Chih-Ching Huang, Chin-Hwa Hu, Ying-Tsang Lo, Tun-Wen Pai, Chia-Yin Chiang, Chung-Hao Li, Hong-Jyuan Jian

Abstract:

Plasmin plays an important role in the human circulatory system owing to its catalytic ability of fibrinolysis. The immediate injection of plasmin in patients of strokes has intrigued many scientists to design vectors that can transport plasmin to the desired location in human body. Here we predict the structure of human plasmin and investigate the interaction of plasmin with the gold-nanoparticle. Because the crystal structure of plasminogen has been solved, we deleted N-terminal domain (Pan-apple domain) of plasminogen and generate a mimic of the active form of this enzyme (plasmin). We conducted a simulated annealing process on plasmin and discovered a very large conformation occurs. Kringle domains 1, 4 and 5 had been observed to leave its original location relative to the main body of the enzyme and the original doughnut shape of this enzyme has been transformed to a V-shaped by opening its two arms. This observation of conformational change is consistent with the experimental results of neutron scattering and centrifugation. We subsequently docked the plasmin on the simulated gold surface to predict their interaction. The V-shaped plasmin could utilize its Kringle domain and catalytic domain to contact the gold surface. Our findings not only reveal the flexibility of plasmin structure but also provide a guide for the design of a plasmin-gold nanoparticle.

Keywords: docking, gold nanoparticle, molecular simulation, plasmin

Procedia PDF Downloads 470

Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

Abstract:

There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

Procedia PDF Downloads 102

Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 209