Search results for: square root modulo problem

Authors: Pradeepa Teegala, Ramreddy Chetteti

Abstract:

This work emphasizes the effects of heat generation/absorption and Joule heating on chemically reacting micropolar fluid flow over a truncated cone with convective boundary condition. For this complex fluid flow problem, the similarity solution does not exist and hence using non-similarity transformations, the governing fluid flow equations along with related boundary conditions are transformed into a set of non-dimensional partial differential equations. Several authors have applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The influence of pertinent parameters namely Biot number, Joule heating, heat generation/absorption, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, spectral quasilinearization method

Procedia PDF Downloads 333

Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

Abstract:

The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

Procedia PDF Downloads 76

Authors: Yuanhao Gao, Pin Lin, Kees Weijer

Abstract:

In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

Procedia PDF Downloads 386

Authors: Enva Doda

Abstract:

Recent statistical analyses within the European Union (EU) underscore the enduring significance of the Gender Pay Gap in amplifying the Gender Pension Gap, a phenomenon resisting proportional reduction over time. This study meticulously calculates the Pension Gap, scrutinizing contributing variables within diverse pension systems. Furthermore, it investigates whether the "unexplained" segment of the Gender Gap correlates with political institutions, economic systems, historical events, or discrimination, utilizing quantitative methods and the Blinder-Oaxaca Decomposition Method to pinpoint potential discriminatory factors. The descriptive analysis reveals a conspicuous Gender Pension Gap across European nations, displaying notable variation. While an overall reduction in the Gender Gap is observed, the degree of improvement varies among countries. Subsequent analyses will delve into the specific reasons or variables influencing distinct Gender Gap percentages, forming the basis for nuanced policy recommendations. This comprehensive research enriches the ongoing discourse on gender equality and economic equity. By focusing on the root causes of the Pension Gap, the study has the potential to instigate policy adjustments, urging policymakers to reassess systemic structures and contribute to informed decision-making. Emphasizing gender equality as essential for a flourishing and resilient economy, the research aspires to drive positive change on academic and policy fronts.

Keywords: blinder Oaxaca decomposition method, discrimination, gender pension gap, quantitative methods, unexplained gender gap

Procedia PDF Downloads 32

Authors: Paul Han, Jun-Geol Baek

Abstract:

In the flat panel display industry, the scheduler and dispatching system to meet production target quantities and the deadline of production are the major production management system which controls each facility production order and distribution of WIP (Work in Process). In dispatching system, delivery time is a key factor for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors and a forecasting model of delivery time. Of survival analysis techniques to select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the Accelerated Failure Time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the Mean Square Error (MSE) criteria, the AFT model decreased by 33.8% compared to the existing prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing a delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

Keywords: delivery time, survival analysis, Cox PH model, accelerated failure time model

Procedia PDF Downloads 523

Authors: Ekin Nurbaş

Abstract:

One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 134

Authors: Fouzieh Rouzmehr, Mehdi Mousavi

Abstract:

Hot mix asphalt concrete (HMAC) is a mixture of aggregates and bitumen. The primary ingredient that determines the mechanical properties of HMAC is the bitumen in it, which displays viscoelastic behavior under normal service conditions. For simplicity, asphalt concrete is considered an elastic material, but this is far from reality at high service temperatures and longer loading times. Viscoelasticity means that the material's stress-strain relationship depends on the strain rate and loading duration. The goal of this paper is to simulate the mechanical response of flexible pavements using linear elastic and viscoelastic modeling of asphalt concrete and predict pavement performance. Falling Weight Deflectometer (FWD) load will be simulated and the results for elastic and viscoelastic modeling will be evaluated. The viscoelastic simulation is performed by the Prony series, which will be modeled by using ANSYS software. Inflexible pavement design, tensile strain at the bottom of the surface layer and compressive strain at the top of the last layer plays an important role in the structural response of the pavement and they will imply the number of loads for fatigue (Nf) and rutting (Nd) respectively. The differences of these two modelings are investigated on fatigue cracking and rutting problem, which are the two main design parameters in flexible pavement design. Although the differences in rutting problem between the two models were negligible, in fatigue cracking, the viscoelastic model results were more accurate. Results indicate that modeling the flexible pavement with elastic material is efficient enough and gives acceptable results.

Keywords: flexible pavement, asphalt, FEM, viscoelastic, elastic, ANSYS, modeling

Procedia PDF Downloads 116

Authors: Dmitry Ustinov, Olga Lobareva

Abstract:

The method of Deep Systemic Constellations is based on a phenomenological approach. Using the phenomenon of substitutive perception it was established that the human consciousness has a hierarchical structure, where deeper levels govern more superficial ones (reactive level, energy or ancestral level, spiritual level, magical level, and deeper levels of consciousness). Every human possesses a depth of consciousness to the spiritual level, however deeper levels of consciousness are not found for every person. It was found that the spiritual level of consciousness is not homogeneous and has its own internal hierarchy of sublevels (the level of formation of spiritual values, the level of the 'inner observer', the level of the 'path', the level of 'God', etc.). The depth of the spiritual level of a person defines the paradigm of all his internal processes and the main motives of the movement through life. At any level of consciousness disturbances can occur. Disturbances at a deeper level cause disturbances at more superficial levels and are manifested in the daily life of a person in feelings, behavioral patterns, psychosomatics, etc. Without removing the deepest source of a disturbance it is impossible to completely correct its manifestation in the actual moment. Thus a destructive pattern of feeling and behavior in the actual moment can exist because of a disturbance, for example, at the spiritual level of a person (although in most cases the source is at the energy level). Psychological work with superficial levels without removing a source of disturbance cannot fully solve the problem. The method of Deep Systemic Constellations allows one to work effectively with the source of the problem located at any depth. The methodology has confirmed its effectiveness in working with more than a thousand people.

Keywords: constellations, spiritual psychology, structure of consciousness, transpersonal psychology

Procedia PDF Downloads 234

Authors: Joseph Uche Azubike, Evelyn Ngozi Agbasi, M. I. Ogbonna

Abstract:

The audit committee of the board of directors could no longer handle the enterprise's risks. Therefore, a risk management committee was created to control them. Thus, this study examined how enterprise risk management committee characteristics affected Nigerian exchange-listed banks' financial performance from 2013 to 2022. The study's hypotheses and three objectives were to determine how enterprise risk management committee size, composition, and gender diversity affect Nigerian banks' performance. An ex-post facto study design collected secondary data from bank annual reports. We used descriptive statistics, correlation analysis, and Ordinary least square regression to analyze panel data. Enterprise risk management committee size and composition had both negative and no significant effect on bank financial performance in Nigeria, whereas enterprise risk committee gender diversity has a 10% favorable effect. The report advises that adding more women with relevant knowledge to the risk committee to boost performance and allowing women to be at the lead of such risk management could improve bank performance in Nigeria since they are noted to be thorough in their tasks.

Keywords: bank, committee, enterprise, management, performance, risk

Procedia PDF Downloads 26

Authors: Alisan Kayabolen, Dilek Keskin, Ferit Avcu, Andac Aykan, Fatih Zor, Aysen Tezcaner

Abstract:

Adipose tissue engineering is a promising field for regeneration of soft tissue defects. However, only very thin implants can be used in vivo since vascularization is still a problem for thick implants. Another problem is finding a biocompatible scaffold with good mechanical properties. In this study, the aim is to develop a thick vascularized adipose tissue that will integrate with the host, and perform its in vitro and in vivo characterizations. For this purpose, a hydrogel of decellularized adipose tissue (DAT) and fibroin was produced, and both endothelial cells and adipocytes that were differentiated from adipose derived stem cells were encapsulated in this hydrogel. Mixing DAT with fibroin allowed rapid gel formation by vortexing. It also provided to adjust mechanical strength by changing fibroin to DAT ratio. Based on compression tests, gels of DAT/fibroin ratio with similar mechanical properties to adipose tissue was selected for cell culture experiments. In vitro characterizations showed that DAT is not cytotoxic; on the contrary, it has many natural ECM components which provide biocompatibility and bioactivity. Subcutaneous implantation of hydrogels resulted with no immunogenic reaction or infection. Moreover, localized empty hydrogels gelled successfully around host vessel with required shape. Implantations of cell encapsulated hydrogels and histological analyses are under study. It is expected that endothelial cells inside the hydrogel will form a capillary network and they will bind to the host vessel passing through hydrogel.

Keywords: adipose tissue engineering, decellularization, encapsulation, hydrogel, vascularization

Procedia PDF Downloads 514

Authors: Deniz Peksen

Abstract:

This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 66

Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

Abstract:

There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: artificial neural network, high performance concrete, rebound hammer, strength prediction

Procedia PDF Downloads 140

Authors: Okorowo Cyril Agochi

Abstract:

The Niger Delta Region of Nigeria is home to about 20 million people and 40 different ethnic groups. The region has an area of seventy thousand square kilometers (70,000 KM2) of wetlands, formed primarily by sediments deposition and makes up 7.5 percent of Nigeria's total landmass. The notable ecological zones in this region includes: coastal barrier islands; mangrove swamp forests; fresh water swamps; and lowland rainforests. This incredibly naturally-endowed ecosystem region, which contains one of the highest concentrations of biodiversity on the planet, in addition to supporting abundant flora and fauna, is threatened by the inhuman act known as gas flaring. Gas flaring is the combustion of natural gas that is associated with crude oil when it is pumped up from the ground. In petroleum-producing areas such as the Niger Delta region of Nigeria where insufficient investment was made in infrastructure to utilize natural gas, flaring is employed to dispose of this associated gas. This practice has impoverished the communities where it is practiced, with attendant environmental, economic and health challenges. This paper discusses the adverse environmental and health implication associated with the practice, the role of Government, Policy makers, Oil companies and the Local communities aimed at bring this inhuman practice to a prompt end.

Keywords: natural combustion, emission, environment, flaring, gas, health, Niger Delta

Procedia PDF Downloads 245

Authors: H. Apaza, L. Chévez, H. Loro

Abstract:

Plastic and microplastic pollution in human food chain is a big problem for human health that requires more elaborated techniques that can identify their presences in different kinds of food. Hyperspectral imaging technique is an optical technique than can detect the presence of different elements in an image and can be used to detect plastics and microplastics in a scene. To do this statistical techniques are required that need to be evaluated and compared in order to find the more efficient ones. In this work, two problems related to the presence of plastics are addressed, the first is to detect and identify pieces of plastic immersed in almond seeds, and the second problem is to detect and quantify microplastic in almond flour. To do this we make use of the analysis hyperspectral images taken in the range of 900 to 1700 nm using 4 unmixing techniques of hyperspectral imaging which are: least squares unmixing (LSU), non-negatively constrained least squares unmixing (NCLSU), fully constrained least squares unmixing (FCLSU), and scaled constrained least squares unmixing (SCLSU). NCLSU, FCLSU, SCLSU techniques manage to find the region where the plastic is found and also manage to quantify the amount of microplastic contained in the almond flour. The SCLSU technique estimated a 13.03% abundance of microplastics and 86.97% of almond flour compared to 16.66% of microplastics and 83.33% abundance of almond flour prepared for the experiment. Results show the feasibility of applying near-infrared hyperspectral image analysis for the detection of plastic contaminants in food.

Keywords: food, plastic, microplastic, NIR hyperspectral imaging, unmixing

Procedia PDF Downloads 117

Authors: J. Thiele

Abstract:

Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

Procedia PDF Downloads 112

Authors: Shipra Sharma, Jagat Jerath

Abstract:

Human resource training is an essential element of talent management in the current era of global competitiveness and dynamic trade in the manufacturing industry. Globally, India is behind only China as the largest textile manufacturer. The major challenges faced by the Indian textile manufacturing Industry are low technology levels, growing skill gaps, unorganized structure, lower efficiencies, etc. indicating the need for constant talent up-gradation. Assessment of training needs from a strategic perspective is an essential step for the formulation of effective training. The paper established the significance of training in the Indian textile industry and to determine the training needs on various parameters as presented. 40 HR personnel/s working in the textile and apparel companies based in the industrial region of Punjab, India, were the respondents for the study. The research tool used in this case was a structured questionnaire as per five-point Likert scale. Statistical analysis through descriptive statistics and chi-square test indicated the increased need for training whenever there were technical changes in the organizations. As per the data presented in this study, most of the HR personnel/s agreed that the variables associated with organizational analysis, task analysis, and individual analysis have a statistically significant role to play in determining the need for training in an organization.

Keywords: Indian textile manufacturing industry, significance of training, training needs analysis, parameters for training needs assessment

Procedia PDF Downloads 144

Authors: Leah Burton, Sara Cumming, Julianne DiSanto

Abstract:

Homelessness is a widespread and complex problem in Canada and around the globe. Many Canadians will face homelessness at least once in their lifetime, with several experiencing subsequent bouts or cyclical patterns of housing precarity. While a Housing First approach to homelessness is a long-standing and widely accepted best practice, it is also recognized that the acquisition of life skills is an effective way to reduce cycles of homelessness. Indeed, when individuals are provided with a range of life skills—such as (but not limited to) financial literacy, household management, interpersonal skills, critical thinking, and resource management—they are given the tools required to maintain long-term Housing for a lifetime; thus reducing a repetitive need for services. However, there is limited research regarding the best ways to teach life skills, a problem that has been further complicated in a post-pandemic world, where services are being delivered online or in a hybrid model of care. More than this, it is difficult to provide life skills on a large scale without losing a client-centered approach to services. This lack of client-centeredness is also seen in the lack of attention to culturally sensitive life skills, which consider the diverse needs of individuals and imbed equity, diversity, and inclusion (EDI) within the skills being taught. This study aims to fill these identified gaps in the literature by employing a community-engaged (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, EDI-informed life skill learning management system. A triangulation methodology was utilized for this research. An environmental scan was conducted for current best practices, and over 100 front-line staff (including workers, managers, and executive directors who work with homeless populations) participated in two separate Creative Problem Solving Sessions. Over 200 individuals with experience in homelessness completed quantitative and open-ended surveys. All sections of this research aimed to discover the areas of skills that individuals need to maintain Housing and to ascertain what a more client-driven EDI approach to life skills training should include. This presentation will showcase the findings on which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, housing first, life skills, community engaged research, client- centered

Procedia PDF Downloads 81

Authors: Tamer Üstüner, Sena Nur Arı

Abstract:

This study was carried out at Kahramanmaras Sutcu Imam University, trial area Faculty of Agriculture and ÜSKİM laboratory in 2022. Many problems are encountered in broad bean (Vicia faba L.) cultivation. One of these problems is weeds. In this study, weed species, families, and densities of weeds that are a problem in broad beans were determined. A total of 47 weed species belonging to 20 different families were determined in the experimental area. Weed species found very densely in control 1 plots of the broad bean experimental area were Sinapis arvensis 11.50 pieces/m², Lolium temulentum L. 11.20, Ranunculus arvensis L. 10.95, Galium tricornutum Dany. 10.81, Avena sterilis 10.60, Bupleurum lancifolium 10.40, Convolvulus arvensis 10.25 ve Cynodon dactylon 10.14 pieces/m². The weed species Cuscuta campestris Yunck. which is very common in the control plots of the broad bean experimental area, was calculated as 11.94 units/m². It was determined that C. campestris alone caused significant yield and quality loss in broad beans. In this study, it was determined that the most effective method in reducing the weed population was hand hoeing, followed by pre-emergence pendimethalin and post-emergence herbicide with Imazamox active substance. In terms of the effect of these control applications on the pod yield, the hand hoeing application ranked first, the pendimethalin application ranked second, the Imazamox application ranked third, and the control 2 and control 1 plot took the last place.

Keywords: broad bean, weed, struggle, yield

Procedia PDF Downloads 73

Authors: Anisa Luli, Alessandra Santona

Abstract:

Wanting a child and experiencing the impossibility to conceive is a painful condition that often is linked to infertility and often leads infertile individuals to experience psychological, relational and social problems. In this situation, infertile couples have to review their choices and take into consideration new ones. Few studies have focused on the decision-making style used by infertile individuals to solve their problem and on the factors that influences it. The aim of this paper is to define the style of decision-making used by infertile persons to give a solution to the “problem” and the predictive role of the attachment, of the representations of the relationship with parents in childhood and of the dyadic adjustment. The total sample is composed by 251 participants, divided in two groups: the experimental group composed by 114 participants, 62 males and 52 females, age between 25 and 59 years, and the control group composed by 137 participants, 65 males and 72 females, age between 22 and 49 years. The battery of instruments comprises: General Decision Making Style (GDMS), Experiences in Close Relationships Questionnaire Revised (ECR-R), Dyadic Adjustment Scale (DAS), Parental Bonding Instrument (PBI) and Symptom Checklist-90-R (SCL-90-R). The results from the analysis of the samples showed a prevalence of the rational decision-making style for both males and females, experimental and control group. There have been founded significant statistical relationships between the attachment scales, the representations of the parenting style, the dyadic adjustment and the decision-making styles. These results contribute to enrich the literature on the subject of decision-making in infertile people and show the relationship between the attachment and decision-making styles, confirming the few results in literature.

Keywords: attachment, decision-making style, infertility, dyadic adjustment

Procedia PDF Downloads 561

Authors: Meziani Samir, Moussi Abderrahmane, Chaouchi Sofiane, Guendouzi Awatif, Djema Oussama

Abstract:

Laser doping has a large potential for integration into silicon solar cell technologies. The ability to process local, heavily diffused regions in a self-aligned manner can greatly simplify processing sequences for the fabrication of selective emitter. The choice of laser parameters for a laser doping process with 532nm is investigated. Solid state lasers with different power and speed were used for laser doping. In this work, the aim is the formation of selective emitter solar cells with a reduced number of technological steps. In order to have a highly doped localized emitter region, we used a 532 nm laser doping. Note that this region will receive the metallization of the Ag grid by screen printing. For this, we use SOLIDWORKS software to design a single type of pattern for square silicon cells. Sheet resistances, phosphorus doping concentration and silicon bulk lifetimes of irradiated samples are presented. Additionally, secondary ion mass spectroscopy (SIMS) profiles of the laser processed samples were acquired. Scanning electron microscope and optical microscope images of laser processed surfaces at different parameters are shown and compared.

Keywords: laser doping, selective emitter, silicon, solar cells

Procedia PDF Downloads 81

Authors: Wei Sun, Yan Dong

Abstract:

There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: robotics, computational thinking, programming, young children, flow chart

Procedia PDF Downloads 131

Authors: Masahiro Miyaji

Abstract:

When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

Procedia PDF Downloads 346

Authors: Rattanamanee Chomchan, Sunisa Siripongvutikorn, Panupong Puttarak

Abstract:

Ricegrass or young rice sprouts can be introduced as one of functional product since cereal sprouts have been much interested in this era due to their high nutritive values. Bio-fortification of selenium is one strategy to improve plant bioactive compounds. However, the level of selenium used are varied among species of plants, hence, the proper level need to be investigated. In this current study, influence of selenium bio-fortification hydroponically in the form of sodium selenite following the range 0, 10, 20, 30 and 40 mg Se/L on growth characteristics, selenium content, total extractable phenolic content (TPC) accumulation, lipid peroxidation and anti-oxidative properties of ricegrass were investigated. Results revealed that selenium bio-fortified exogenously increased the accumulation of selenium in ricegrass by 5.3 fold at 40 mg Se/L treatment without significant changes in leaves biomass at harvesting day while root part weight were slightly decreased when increased selenium level, respectively. Selenium at low concentration (10 and 20 mg Se/L) can stimulate the production of phenolic compounds and antioxidant activities in young ricegrass as measured by DPPH, ABTS and FRAP assay. Conversely, higher level of selenium fortification reduced the accumulation of phenolics in ricegrass afterward by acting as pro-oxidant. Moreover, highest significant reduction in oxidative stress, measured as malondialdehyde content was also observed at 20 mg Se/L treatment which in correlation to high TPC and antioxidant activities. In conclusion, selenium bio-fortification can be used as a technique to improve precious to ricegrass.

Keywords: antioxidant activities, bio-fortification, ricegrass, selenium

Procedia PDF Downloads 267

Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

Abstract:

Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

Procedia PDF Downloads 82

Authors: Kareem Abdelwahed, Ahmed Salama, Ahmed Rabie, Ahmed Hamdy, Waleed Abdelfattah, Ahmed Abd El-Rahman

Abstract:

Conventional vapor-compression refrigeration systems rely on typical refrigerants, such as CFC, HCFC and ammonia. Despite of their suitable thermodynamic properties and their stability in the atmosphere, their corresponding global warming potential and ozone depletion potential raise concerns about their usage. Thus, the need for new refrigeration systems, which are environment-friendly, inexpensive and simple in construction, has strongly motivated the development of thermoacoustic energy conversion systems. A thermoacoustic refrigerator (TAR) is a device that is mainly consisting of a resonator, a stack and two heat exchangers. Typically, the resonator is a long circular tube, made of copper or steel and filled with Helium as a the working gas, while the stack has short and relatively low thermal conductivity ceramic parallel plates aligned with the direction of the prevailing resonant wave. Typically, the resonator of a standing-wave refrigerator has one end closed and is bounded by the acoustic driver at the other end enabling the propagation of half-wavelength acoustic excitation. The hot and cold heat exchangers are made of copper to allow for efficient heat transfer between the working gas and the external heat source and sink respectively. TARs are interesting because they have no moving parts, unlike conventional refrigerators, and almost no environmental impact exists as they rely on the conversion of acoustic and heat energies. Their fabrication process is rather simpler and sizes span wide variety of length scales. The viscous and thermal interactions between the stack plates, heat exchangers' plates and the working gas significantly affect the flow field within the plates' channels, and the energy flux density at the plates' surfaces, respectively. Here, the design, the manufacture and the testing of a compact refrigeration system that is based on the thermoacoustic energy-conversion technology is reported. A 1-D linear acoustic model is carefully and specifically developed, which is followed by building the hardware and testing procedures. The system consists of two harmonically-oscillating pistons driven by a simple 1-HP rotary drive mechanism operating at a frequency of 42Hz -hereby, replacing typical expensive linear motors and loudspeakers-, and a thermoacoustic stack within which the energy conversion of sound into heat is taken place. Air at ambient conditions is used as the working gas while the amplitude of the driver's displacement reaches 19 mm. The 30-cm-long stack is a simple porous ceramic material having 100 square channels per square inch. During operation, both oscillating-gas pressure and solid-stack temperature are recorded for further analysis. Measurements show a maximum temperature difference of about 27 degrees between the stack hot and cold ends with a Carnot coefficient of performance of 11 and estimated cooling capacity of five Watts, when operating at ambient conditions. A dynamic pressure of 7-kPa-amplitude is recorded, yielding a drive ratio of 7% approximately, and found in a good agreement with theoretical prediction. The system behavior is clearly non-linear and significant non-linear loss mechanisms are evident. This work helps understanding the operation principles of thermoacoustic refrigerators and presents a keystone towards developing commercial thermoacoustic refrigerator units.

Keywords: refrigeration system, rotary drive mechanism, standing-wave, thermoacoustic refrigerator

Procedia PDF Downloads 354

Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

Abstract:

Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

Procedia PDF Downloads 328

Authors: Sachin Saxena, Manju Srivastava

Abstract:

The present study describes a stable, highly sensitive and selective analytical sensor. Fe-BTC was synthesized at room temperature using the noble Iron-trimesate system. The high surface area of as synthesized Fe-BTC proved MOFs as ideal modifiers for glassy carbon electrode. The characterization techniques such as TGA, XRD, FT-IR, BET (BET surface area= 1125 m2/gm) analysis explained the electrocatalytic behaviour of Fe-BTC towards these two drugs. The material formed is cost effective and exhibit higher catalytic behaviour towards analyte systems. The synergism between synthesized Fe-BTC and electroanalytical techniques helped in developing a highly sensitive analytical method for studying the redox fate of ARP and RZ, respectively. Cyclic voltammetry of ferricyanide system proved Fe-BTC/GCE with an increase in 132% enhancement in peak current value as compared to that of GCE. The response characteristics of cyclic voltammetry (CV) and square wave voltammetry (SWV) revealed that the ARP and RZ could be effectively accumulated at Fe-BTC/GCE. On the basis of the electrochemical measurements, electrode dynamics parameters have been evaluated. Present study opens up new field of applications of MOFs modified GCE for drug sensing.

Keywords: MOFs, anti-psychotic, electrochemical sensor, anti-migraine drugs

Procedia PDF Downloads 152

Authors: Faranak Omidian

Abstract:

The aim of this research was to examine the quality of education service at master's level in the Islamic Azad University of Dezful. In terms of objective, this is an applied research and in regard to methodology, it is a descriptive analytical research. The statistical population included all students of master's degree in the Islamic Azad University of Dezful. The sample size was determined using stratified random sampling method in different fields of study. The research questionnaire is the translated version of standardized Abdullah's HEdPERF 41-item scale which is based on a 5-point Likert scale. In order to determine the validity, the translated questionnaire was given to the professors of educational sciences. The correlation among all questions has been regarded at a value of 0.644. The results showed that the quality of educational service at master's level in this university, based on chi-square goodness of fit test, was equal to 73.36 and its degree of freedom was 2 at a significant level of 0.001, indicating the low desirability of the services. According to Friedman test, academic responsiveness has been reported to be in a higher status than other dimensions with an average rank of 3.94 while accessibility, with an average rank of 2.15, has been in the lowest status from master's students' viewpoint.

Keywords: educational service quality, master's level, Iranian university

Procedia PDF Downloads 266

Authors: Habibi Said Mustafa, Hiroko Ono

Abstract:

Kabul, the capital of Afghanistan, has witnessed a major population growth in the last decades which caused a significant increase in the number of informal settlements. The residents are suffering from many problems such as poor infrastructure, shortage of public facilities, depriving of the sense of ownership and facing much environmental degradation. Even though majority of the residents are living in such condition, the government response has been quite weak. The government’s main planning strategy has been upgrading in the form of provision of facilities and improving elements of physical infrastructure, unfortunately most of the projects which had not community’s support, faced with lots of challenges such as people’s resistance or even in some cases the project rather than solving the problem, compounded them to a worse condition. A major reason as to why many projects have not been effective in achieving certain objectives in the past is the results of local people were not being involved. Community participation plays an important role in slum development projects. The development of an integrated urban development concept these days without the mobilization of participants and community seems difficult and impossible. Therefore this paper looks into factors and methods which can help in creating a participatory approach for developing the slums in Kabul city. Furthermore, it describes the result of a questionnaire which was conducted on a part of the Kabul Old City due to hear resident’s problem related to the slum upgrading and collect their opinions on this regard. The research also points out some factors which can severely hamper the successful implementation of a slum upgrading project if not adequately addressed.

Keywords: Community empowerment, Informal settlements, Job opportunities, People participation

Procedia PDF Downloads 156

Authors: M. C. Yu, Z. L. Niu, L. G. Zhang, W. W. Cui, Y. L. Zhang

Abstract:

According to the theory of the vibration isolation for linear systems, linear damping can reduce the transmissibility at the resonant frequency, but inescapably increase the transmissibility of the isolation frequency region. To resolve this problem, nonlinear vibration isolation technology has recently received increasing attentions. Shear thickening fluid (STF) is a special colloidal material. When STF is subject to high shear rate, it rheological property changes from a flowable behavior into a rigid behavior, i.e., it presents shear thickening effect. STF isolator is a vibration isolator using STF as working material. Because of shear thickening effect, STF isolator is a variable-damped isolator. It exhibits small damping under high vibration frequency and strong damping at resonance frequency due to shearing rate increasing. So its special inherent character is very favorable for vibration isolation, especially for restraining resonance. In this paper, firstly, STF was prepared by dispersing nano-particles of silica into polyethylene glycol 200 fluid, followed by rheological properties test. After that, an STF isolator was designed. The vibration isolation system supported by STF isolator was modeled, and the numerical simulation was conducted to study the vibration isolation properties of STF. And finally, the effect factors on vibrations isolation performance was also researched quantitatively. The research suggests that owing to its variable damping, STF vibration isolator can effetely restrain resonance without bringing unfavorable effect at high frequency, which meets the need of ideal damping properties and resolves the problem of traditional isolators.

Keywords: shear thickening fluid, variable-damped isolator, vibration isolation, restrain resonance

Procedia PDF Downloads 163