Search results for: q-rung orthopair fuzzy sets

Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Yi-Ting Wang, Wen-Shu Lai

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The subject of this paper is the photography in the 1983 film Paris, Texas, directed by Wim Wenders. Wenders is well known as a film director as well as a photographer. We have found that photography is shown as a photographic element in many of his films. Some of these photographs serve as details within the films, while others play important roles that are relevant to the story. This paper aims to consider photographs in film as a specific type of text, which is the output of both still photography and the film itself. In the film Paris, Texas, three sets of important photographs appear whose symbolic meanings are as dialectical as their text types. The relationship between the existence of these photos and the storyline is both dependent and isolated. The film’s images fly by and progress into other images, while the photos in the film serve a unique narrative function by stopping the continuously flowing images thus provide the viewer a space for imagination and contemplation. They are more than just artistic forms; they also contained multiple meanings. The photographs in Paris, Texas play the role of both presence and absence according to their shifting meanings. There are references to their presence: photographs exist between film time and narrative time, so in terms of the interaction between the characters in the film, photographs are a common symbol of the beginning and end of the characters’ journeys. In terms of the audience, the film’s photographs are a link in the viewing frame structure, through which the creative motivation of the film director can be explored. Photographs also point to the absence of certain objects: the scenes in the photos represent an imaginary map of emotion. The town of Paris, Texas is therefore isolated from the physical presence of the photograph, and is far more abstract than the reality in the film. This paper embraces the ambiguous nature of photography and demonstrates its presence and absence in film with regard to the meaning of text. However, it is worth reflecting that the temporary nature of the interpretation of the film’s photographs is far greater than any other type of photographic text: the characteristics of the text cause the interpretation results to change along with the variations in the interpretation process, which makes their meaning a dynamic process. The photographs’ presence or absence in the context of Paris, Texas also demonstrates the presence and absence of the creator, time, the truth, and the imagination. The film becomes more complete as a result of the revelation of the photographs, while the intertextual connection between these two forms simultaneously provides multiple possibilities for the interpretation of the photographs in the film.

Keywords: film, Paris, Texas, photography, Wim Wenders

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Authors: Zilungile Sosibo

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Constructivism in teacher education is growing tremendously in both the developed and developing world. Proponents of constructivism emphasize active engagement of students in the teaching and learning process. In an effort to keep students engaged while they learn to learn, teachers use a variety of methods to incorporate constructivism in the teaching-learning situations. One area that has a potential for realizing constructivism in the classroom is self-assessment. Sadly, students are rarely involved in the assessment of their work. Instead, the most knowing teacher dominates this process. Student involvement in self-assessments has a potential to teach student teachers to become objective assessors of their students’ work by the time they become credentialed. This is important, as objectivity in assessments is a much-needed skill in the classroom contexts within which teachers deal with students from diverse backgrounds and in which biased assessments should be avoided at all cost. The purpose of the study presented in this paper was to investigate whether student teachers acquired the skills of administering self-assessments objectively after they had been immersed in a formal training program and participated in four sets of self-assessments. The objectives were to determine the extent to which they had mastered the skills of objective self-assessments, their growth and development in this area, and the challenges they encountered in administering self-assessments objectively. The research question was: To what extent did student teachers acquire objectivity in self-assessments after their theoretical and practical engagement in this activity? Data were collected from student teachers through participant observation and semi-structured interviews. The design was a qualitative case study. The sample consisted of 39 final-year student teachers enrolled in a Bachelor of Education teacher education program at a university in South Africa. Results revealed that the formal training program and participation in self-assessments had a minimal effect on students’ acquisition of objectivity in self-assessments, due to the factors associated with self-aggrandizement and hegemony, the latter resulting from gender, religious and racial differences. These results have serious implications for the need to incorporate self-assessments in the teacher-education curriculum, as well as for extended formal training programs for student teachers on assessment in general.

Keywords: objectivity, self-assessment, student teachers, teacher education curriculum

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Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Today, with the increase in quantity and quality and variety of crimes, the discussion of crime prevention has faced a serious challenge that human resources alone and with traditional methods will not be effective. One of the developments in the modern world is the presence of artificial intelligence in various fields, including criminal law. In fact, the use of artificial intelligence in criminal investigations and fighting crime is a necessity in today's world. The use of artificial intelligence is far beyond and even separate from other technologies in the struggle against crime. Second, its application in criminal science is different from the discussion of prevention and it comes to the prediction of crime. Crime prevention in terms of the three factors of the offender, the offender and the victim, following a change in the conditions of the three factors, based on the perception of the criminal being wise, and therefore increasing the cost and risk of crime for him in order to desist from delinquency or to make the victim aware of self-care and possibility of exposing him to danger or making it difficult to commit crimes. While the presence of artificial intelligence in the field of combating crime and social damage and dangers, like an all-seeing eye, regardless of time and place, it sees the future and predicts the occurrence of a possible crime, thus prevent the occurrence of crimes. The purpose of this article is to collect and analyze the studies conducted on the use of artificial intelligence in predicting and preventing crime. How capable is this technology in predicting crime and preventing it? The results have shown that the artificial intelligence technologies in use are capable of predicting and preventing crime and can find patterns in the data set. find large ones in a much more efficient way than humans. In crime prediction and prevention, the term artificial intelligence can be used to refer to the increasing use of technologies that apply algorithms to large sets of data to assist or replace police. The use of artificial intelligence in our debate is in predicting and preventing crime, including predicting the time and place of future criminal activities, effective identification of patterns and accurate prediction of future behavior through data mining, machine learning and deep learning, and data analysis, and also the use of neural networks. Because the knowledge of criminologists can provide insight into risk factors for criminal behavior, among other issues, computer scientists can match this knowledge with the datasets that artificial intelligence uses to inform them.

Keywords: artificial intelligence, criminology, crime, prevention, prediction

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Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: Renu Pattanshetty

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The aim of this narrative review is to highlight the impact of menopause on osteoporosis and weight gain. The review also aims to summarize physiotherapeutic strategies to combat the same.A thorough literature search was conducted using electronic databases like MEDline, PUBmed, Highwire Press, PUBmed Central for English language studies that included search terms like menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies from the year 2000 till date. Out of 157 studies that included metanalyses, critical reviews and randomized clinical trials, a total of 84 were selected that met the inclusion criteria. Prevalence of obesity is increasing world - wide and is reaching epidemic proportions even in the menopausal women. Prevalence of abdominal obesity is almost double than that general obesity with rates in the US with 65.5% in women ages 40-59 years and 73.8 in women aged 60 years or more. Physical activities and exercises play a vital role in prevention and treatment of osteoporosis and weight gain related to menopause that aim to boost the general well-being and any symptoms brought about by natural body changes. Endurance exercises lasting about 30 minutes /day for 5 days/ week has shown to decrease weight and prevent weight gain. In addition, strength training with at least 8 exercises of 8-12 repetitions working for whole body and for large muscle groups has shown to result positive outcomes. Hot flashes can be combatted through yogic breathing and relaxation exercises. Prevention of fall strategies and resistance training are key to treat diagnosed cases of osteoporosis related to menopause. One to three sets with five to eight repetitions of four to six weight bearing exercises have shown positive results. Menopause marks an important time for women to evaluate their risk of obesity and osteoporosis. It is known fact that bone benefit from exercises are lost when training is stopped, hence, practicing bone smart habits and strict adherence to recommended physical activity programs are recommended which are enjoyable, safe and effective.

Keywords: menopause, osteoporosis, obesity, weight gain, exercises, physical activity, physiotherapy strategies

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Sandra Cecilia Bautista-Rodríguez, Vladimir Melgarejo

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Climate change, loss of ecosystems, increasing poverty, increasing marginalization of rural communities and declining food security are global issues that require urgent attention. In this regard, a great deal of research has focused on how agroecosystems respond to these challenges as they provide ecosystem services (ES) that lead to higher levels of resilience, adaptation, productivity and self-sufficiency. Hence, the valuing of ecosystem services plays an important role in the decision-making process for the design and management of agroecosystems. This paper aims to define the link between ecosystem service valuation methods and ES value dimensions in agroecosystems from ecological economics and agroecology. The method used to identify valuation methodologies was a literature review in the fields of Agroecology and Ecological Economics, based on a strategy of information search and classification. The conceptual framework of the work is based on the multidimensionality of value, considering the social, ecological, political, technological and economic dimensions. Likewise, the valuation process requires consideration of the ecosystem function associated with ES, such as regulation, habitat, production and information functions. In this way, valuation methods for ES in agroecosystems can integrate more than one value dimension and at least one ecosystem function. The results allow correlating the ecosystem functions with the ecosystem services valued, and the specific tools or models used, the dimensions and valuation methods. The main methodologies identified are multi-criteria valuation (1), deliberative - consultative valuation (2), valuation based on system dynamics modeling (3), valuation through energy or biophysical balances (4), valuation through fuzzy logic modeling (5), valuation based on agent-based modeling (6). Amongst the main conclusions, it is highlighted that the system dynamics modeling approach has a high potential for development in valuation processes, due to its ability to integrate other methods, especially multi-criteria valuation and energy and biophysical balances, to describe through causal cycles the interrelationships between ecosystem services, the dimensions of value in agroecosystems, thus showing the relationships between the value of ecosystem services and the welfare of communities. As for methodological challenges, it is relevant to achieve the integration of tools and models provided by different methods, to incorporate the characteristics of a complex system such as the agroecosystem, which allows reducing the limitations in the processes of valuation of ES.

Keywords: ecological economics, agroecosystems, ecosystem services, valuation of ecosystem services

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Authors: Martin Kleynhans, Margot Soler, Gavin Quibell

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Malawi is one of the world’s poorest nations and consequently, the design of flood risk management infrastructure comes with a different set of challenges. There is a lack of good quality hydromet data, both in spatial terms and in the quality thereof and the challenge in the design of flood risk management infrastructure is compounded by the fact that maintenance is almost completely non-existent and that solutions have to be simple to be effective. Solutions should not require any further resources to remain functional after completion, and they should be resilient. They also have to be cost effective. The Lower Shire Valley of Malawi suffers from frequent flood events. Various flood risk management interventions have been designed across the valley during the course of the Shire River Basin Management Project – Phase I, and due to the data poor environment, indigenous knowledge was relied upon to a great extent for hydrological and hydraulic model calibration and verification. However, indigenous knowledge comes with the caveat that it is ‘fuzzy’ and that it can be manipulated for political reasons. The experience in the Lower Shire valley suggests that indigenous knowledge is unlikely to invent a problem where none exists, but that flood depths and extents may be exaggerated to secure prioritization of the intervention. Indigenous knowledge relies on the memory of a community and cannot foresee events that exceed past experience, that could occur differently to those that have occurred in the past, or where flood management interventions change the flow regime. This complicates communication of planned interventions to local inhabitants. Indigenous knowledge is, for the most part, intuitive, but flooding can sometimes be counter intuitive, and the rural poor may have a lower trust of technology. Due to a near complete lack of maintenance of infrastructure, infrastructure has to be designed with no moving parts and no requirement for energy inputs. This precludes pumps, valves, flap gates and sophisticated warning systems. Designs of dykes during this project included ‘flood warning spillways’, that double up as pedestrian and animal crossing points, which provide warning of impending dangerous water levels behind dykes to residents before water levels that could cause a possible dyke failure are reached. Locally available materials and erosion protection using vegetation were used wherever possible to keep costs down.

Keywords: design of dykes in low-income countries, flood warning spillways, indigenous knowledge, Malawi

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Authors: Danhua Xu, Zhenlan Qian, Zhu Wang, Jiayan Fu, Ling Wang

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A new business mode called rural complex is proposed by the China’s government to promote the development the economy in the rural area. However, for the sake of current national conditions including the great number of labor farmers owning the small scale farmlands and the uncertain enthusiasm from the enterprises, it is challenging to develop the big scale rural complex. To react to the dilemmas, this paper puts forward the micro-rural complex to boost the small scale farms by co-participation from a bottom-up mode. By analyzing the potential opportunities to find the suitable mode, exploring the interdisciplinary and interdepartmental co-participation way beyond architecture design and spatial planning between different actors, the paper tries to find a complete process towards the sustainable micro-rural complex and conducts an ongoing practice to optimize it, to bring new insights and reference to the rural development. According to the transformation of the economy, the micro-rural complex will develop into two phases, both of which can be discussed in three parts, the economic mode, the spatial support, and the Cooperating mechanism. The first stage is the agriculture co-participation based on the rise of Community supported agriculture (CSA) in which the consumers buy the products planted in an organic way from the farmers directly with a higher price to support the small-scale agriculture and overcome the food safety issues. The following stage sets up the agritourism catering the citizens with the restaurants, inns and other tourist service facilities to be planned and designed. In the whole process, the interdisciplinary co-participation will play an important role to provide the guidelines and consultation from the agronomists, architects and rural planners to the farmers. This mode has been applied to an on-going farm project, from which to explore the mode in a more practical way. In conclusion, the micro-rural complex aims at creating a balanced urban-rural relationship by co-participation taking advantage of the different actors. The spatial development is considered from the economic mode and social organization. The integration of the mode based on the small-scale agriculture will contribute to a sustainable growth and realize the long run development in the rural area.

Keywords: micro-rural complex, co-participation, sustainable development, China

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Authors: Hsueh-Hsing Lu, Thi-Cuc Le, Tung-Sheng Tsai, Chuen-Jinn Tsai

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This study designed and tested a novel wet electrostatic precipitators (WEP) system featuring a Pulse-Air-Jet-Assisted Water Flow (PJWF) to shorten water cleaning time, reduce water usage, and maintain high particle removal efficiency. The PJWF injected cleaning water tangentially at the cylinder wall, rapidly enhancing the momentum of the water flow for efficient dust cake removal. Each PJWF cycle uses approximately 4.8 liters of cleaning water in 18 seconds. Comprehensive laboratory tests were conducted using a single-tube WEP prototype within a flow rate range of 3.0 to 6.0 cubic meters per minute(CMM), operating voltages between -35 to -55 kV, and high-frequency power supply. The prototype, consisting of 72 sets of double-spike rigid discharge electrodes, demonstrated that with the PJWF, -35 kV, and 3.0 CMM, the PM2.5 collection efficiency remained as high as the initial value of 88.02±0.92% after loading with Al2O3 particles at 35.75± 2.54 mg/Nm3 for 20-hr continuous operation. In contrast, without the PJWF, the PM2.5 collection efficiency drastically dropped from 87.4% to 53.5%. Theoretical modeling closely matched experimental results, confirming the robustness of the system's design and its scalability for larger industrial applications. Future research will focus on optimizing the PJWF system, exploring its performance with various particulate matter, and ensuring long-term operational stability and reliability under diverse environmental conditions. Recently, this WEP was combined with a preceding CT (cooling tower) and a HWS (honeycomb wet scrubber) and pilot-tested (40 CMM) to remove SO2 and PM2.5 emissions in a sintering plant of an integrated steel making plant. Pilot-test results showed that the removal efficiencies for SO2 and PM2.5 emissions are as high as 99.7 and 99.3 %, respectively, with ultralow emitted concentrations of 0.3 ppm and 0.07 mg/m3, respectively, while the white smoke is also eliminated at the same time. These new technologies are being used in the industry and the application in different fields is expected to be expanded to reduce air pollutant emissions substantially for a better ambient air quality.

Keywords: wet electrostatic precipitator, pulse-air-jet-assisted water flow, particle removal efficiency, air pollution control

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Authors: Catarina Seco Matos, Miguel Amaral

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The developed world is facing falling birth rates and rising life expectancies. As a result, the overall demographic structure of societies is becoming markedly older. This leads to an economic and political pressure towards the extension of individuals’ working lives. On the other hand, evidence shows that some older workers choose to stay in the labour force as employees, whereas others choose to pursue a more entrepreneurial occupational path. Thus, entrepreneurship or self-employment may be an option for socioeconomic participation of older individuals. Previous research on senior entrepreneurship is scarce and it focuses mainly on entrepreneurship determinants and individuals’ intentions. The fact that entrepreneurship is perceived as a voluntary or involuntary decision or as a positive or a negative outcome by older individuals is, to the best of our knowledge, still unexplored in the literature. In order to analyse the determinants of entrepreneurial satisfaction among older individuals, primary data were obtained from a unique questionnaire survey, which was sent to Portuguese senior entrepreneurs who have launched their company aged 50 and over (N=181). Portugal is one of the countries in the world with the with the largest ageing population and with a high proportion of older individuals who remain active after their official retirement age – which makes it an extremely relevant case study on senior entrepreneurship. Findings suggest that non pecuniary factors (rather than pecuniary) are the main driver for entrepreneurship at older ages. Specifically, results show that the will to remain active is the main motivation of older individuals to become entrepreneurs. This is line with the activity and continuity theories. Furthermore, senior entrepreneurs tend to have had an active working life (using their professional experience as a proxy) and, thus, want to keep the same lifestyle at an older age (in line with theory of continuity). Finally, results show that even though older individuals’ companies may not show the best financial performance that does not seem to affect their satisfaction with the company and with entrepreneurship in general. The present study aims at exploring, discussing and bring new research on senior entrepreneurship to the fore, rather than assuming purely deductive approach; hence, further confirmatory analyses with larger sets from different countries of data are required.

Keywords: active ageing, entrepreneurship, older entrepreneur, Portugal, satisfaction, senior entrepreneur

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Authors: Amira Rjiba, Mohamed Ghanmi, Tahar Aifa, Achref Boulares

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This study, involving the interpretation of geological outcrops data (structures, and lithostratigraphiec colones) and subsurface structures (seismic and gravimetric data) help us to identify and precise (i) the lithology of the sedimentary formations between the Aptian and the recent formations, (ii) to differentiate the sedimentary formations it from the salt-bearing Triassic (iii) and to specify the major structures though the tectonics effects having affected the region during its geological evolution. By placing our study area placed in the context of Tunisia, located on the southern margin of the Tethys show us through tectonic traces and structural analysis conducted, that this area was submitted during the Triassic perio at an active rifting triggered extensional tectonic events and extensive respectively in the Cretaceous and Paleogene. Lithostratigraphic correlations between outcrops and seismic data sets on those of six oil wells conducted in the region have allowed us to better understand the structural complexity and the role of different tectonic faults having contributed to the current configuration, and marked by the current rifts. Indeed, three directions of NW-SE faults, NNW-SSE to NS and NE-SW to EW had a major role in the genesis of folds and open ditches collapse of NW-SE direction. These results were complemented by seismic reflection data to clarify the geometry of the southern and western areas of Kalaa Khasba ditch. The eight selected seismic lines for this study allowed to characterize the main structures, with isochronous maps, contour and isovitesse of Serdj horizon that presents the main reservoir in the region. The line L2, keyed by the well 6, helped highlight the NW-SE compression that has resulted in persistent discrepancies widely identifiable in its lithostratigraphic column. The gravity survey has confirmed the extension of most of the accidents deep subsurface whose activity seems to go far. Gravimetry also reinforced seismic interpretation confirming, at the L2 well, that both SW and NE flank of the moat are two opposite faults and trace the boundaries of NNW-SSE direction graben whose sedimentation of Mio-Pliocene age and Quaternary.

Keywords: graben, graben collapse, gravity, Kalat Es Senan, seismic, tectogenesis

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Wenli Tsou, Jessica Wu

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Courses of English for specific academic purposes (ESAP) have become popular for higher education in Taiwan; however, no standardized tests have been developed for evaluating learners’ English proficiency in individual designated fields. Assuming a learner’s proficiency in a specific academic area is built up with one’s general proficiency in English with specific knowledge and vocabulary in the content areas, an adequate ESAP proficiency test may be constructed by some selected test items related to the designated academic areas. In this study, through collaboration between a language testing institution and a university in Taiwan, three sets of ESAP tests, covering three disciplinary areas of business and the workplace, science and engineering, and health and medicine majors, were developed and administered to sophomore students (N=1704) who were enrolled in ESAP courses at a university in southern Taiwan. For this study, the courses were grouped into the above-mentioned three disciplines, and students took the specialized proficiency test based on the ESAP course they were taking. Because students were free to select which ESAP course to take, each course had both major and non-major students. Toward the end of the one-semester course, ending in January, 2015, each student took two tests, one of general English (General English Proficiency Test, or GEPT) and the other ESAP. Following each test, students filled out a survey, reporting their test taking experiences. After comparing students’ two test scores, it was found that business majors and health and medical students performed better in ESAP than the non-majors in the class, whereas science and engineering majors did about the same as their non-major counterparts. In addition, test takers with CERF B2 (upper intermediate) level or above performed well in both tests, while students who are below B2 did slightly better in ESAP. The findings suggest that students’ test performance have been enhanced by their specialist content and vocabulary knowledge. Furthermore, results of the survey show that the difficulty levels reported by students are consistent with their test performances. Based on the item analysis, the findings can be used to develop proficiency tests for specific disciplines and to identify ability indicators for college students in their designated fields.

Keywords: english for specific academic purposes (ESAP), general english proficiency test (GEPT), higher education, proficiency test

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Authors: David Serero, Loic Couton, Jean-Denis Parisse, Robert Leroy

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This paper presents an analysis method of airflow at the periphery of several typologies of architectural volumes. To understand the complexity of the urban environment on the airflows in the city, we compared three sites at different architectural scale. The research sets a method to identify the optimal location for the installation of wind turbines on the edges of a building and to achieve an improvement in the performance of energy extracted by precise localization of an accelerating wing called “aero foil”. The objective is to define principles for the installation of wind turbines and natural ventilation design of buildings. Instead of theoretical winds analysis, we combined numerical aeraulic simulations using STAR CCM + software with wind data, over long periods of time (greater than 1 year). If airflows computer fluid analysis (CFD) simulation of buildings are current, we have calibrated a virtual wind tunnel with wind data using in situ anemometers (to establish localized cartography of urban winds). We can then develop a complete volumetric model of the behavior of the wind on a roof area, or an entire urban island. With this method, we can categorize: - the different types of wind in urban areas and identify the minimum and maximum wind spectrum, - select the type of harvesting devices - fixing to the roof of a building, - the altimetry of the device in relation to the levels of the roofs - The potential nuisances around. This study is carried out from the recovery of a geolocated data flow, and the connection of this information with the technical specifications of wind turbines, their energy performance and their speed of engagement. Thanks to this method, we can thus define the characteristics of wind turbines to maximize their performance in urban sites and in a turbulent airflow regime. We also study the installation of a wind accelerator associated with buildings. The “aerofoils which are integrated are improvement to control the speed of the air, to orientate it on the wind turbine, to accelerate it and to hide, thanks to its profile, the device on the roof of the building.

Keywords: wind energy harvesting, wind turbine selection, urban wind potential analysis, CFD simulation for architectural design

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Authors: Hung-Yuan Chang, Wen-Lung Chiang, Kuo-Liang Wu, Chen-Tsung Lin

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National Space Organization (NSPO) has completed in 2014 the development of a space-borne GPS receiver, including design, manufacture, comprehensive functional test, environmental qualification test and so on. The main performance of this receiver include 8-meter positioning accuracy, 0.05 m/sec speed-accuracy, the longest 90 seconds of cold start time, and up to 15g high dynamic scenario. The receiver will be integrated in the autonomous FORMOSAT-7 NSPO-Built satellite scheduled to be launched in 2019 to execute pre-defined scientific missions. The flight model of this receiver manufactured in early 2015 will pass comprehensive functional tests and environmental acceptance tests, etc., which are expected to be completed by the end of 2015. The space-borne GPS receiver is a pure software design in which all GPS baseband signal processing are executed by a digital signal processor (DSP), currently only 50% of its throughput being used. In response to the booming global navigation satellite systems, NSPO will gradually expand this receiver to become a multi-mode, multi-band, high-precision navigation receiver, and even a science payload, such as the reflectometry receiver of a global navigation satellite system. The fundamental purpose of this extension study is to port some software algorithms such as signal acquisition and correlation, reused code and large amount of computation load to the FPGA whose processor is responsible for operational control, navigation solution, and orbit propagation and so on. Due to the development and evolution of the FPGA is pretty fast, the new system architecture upgraded via an FPGA should be able to achieve the goal of being a multi-mode, multi-band high-precision navigation receiver, or scientific receiver. Finally, the results of tests show that the new system architecture not only retains the original overall performance, but also sets aside more resources available for future expansion possibility. This paper will explain the detailed DSP/FPGA architecture, development, test results, and the goals of next development stage of this receiver.

Keywords: space-borne, GPS receiver, DSP, FPGA, multi-mode multi-band

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Authors: Brian Fleischli, Shani Robins

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In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

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Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Padmaja Kaja, Kiran Kumar Gellaboina

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A lion’s share of agricultural work is contributed by women in India as it is the case in many developing countries, yet women are not securing the pride as a farmer. Many policies are supporting women empowerment in India, especially in agriculture sector considering the importance of sustainable food security. However these policies many times failed to achieve the targeted results of mainstreaming gender. Implementing the principles of governance would lead to gender equality in agriculture. This paper deals with the social norms and obligations prevailed with reference to Indian context which abstain women from having resources. This paper is formulated by using primary research done in eight districts of Telangana and Andhra Pradesh states of India supported by secondary research. Making amendments to Hindu Succession Act in united Andhra Pradesh much prior to the positioning of the amended act in the whole country lead to a better land holding a share of women in Andhra Pradesh. The policies like registering government distributed lands in the name of women in the state also have an added value. However, the women participation in decision-making process in agriculture is limited in elite families when compared to socially under privileged families, further too it was higher in drought affected districts like Mahbubnagar in Telangana when compared to resource-rich East Godavari district in Andhra Pradesh. Though National Gender Resource Centre for Agriculture (NGRCA) at centre and Gender Cells in the states were established a decade ago, extension reach to the women farmers is still lagging behind. Capturing the strength of women self groups in India especially in Andhra Pradesh to link up with agriculture extension might improve the extension reach of women farmers. Maintenance of micro level women data sets, creating women farmers networks with government departments like agriculture, irrigation, revenue and formal credit institutes would result in good governance to mainstream gender in agriculture. Further to add that continuous monitoring and impact assessments of the programmes and projects for gender inclusiveness would reiterate the government efforts.

Keywords: food security, gender, governance, mainstreaming

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Authors: M. Shemis, O. Maher, G. Casterou, F. Gauffre

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Hepatitis C virus (HCV) is a major cause of chronic liver disease with a global 170 million chronic carriers at risk of developing liver cirrhosis and/or liver cancer. Egypt reports the highest prevalence of HCV worldwide. Currently, two classes of assays are used in the diagnosis and management of HCV infection. Despite the high sensitivity and specificity of the available diagnostic assays, they are time-consuming, labor-intensive, expensive, and require specialized equipment and highly qualified personal. It is therefore important for clinical and economic terms to develop a low-tech assay for the direct detection of HCV RNA with acceptable sensitivity and specificity, short turnaround time, and cost-effectiveness. Such an assay would be critical to control HCV in developing countries with limited resources and high infection rates, such as Egypt. The unique optical and physical properties of gold nanoparticles (AuNPs) have allowed the use of these nanoparticles in developing simple and rapid colorimetric assays for clinical diagnosis offering higher sensitivity and specificity than current detection techniques. The current research aims to develop a detection assay for HCV RNA using gold nanoparticles (AuNPs). Methods: 200 anti-HCV positive samples and 50 anti-HCV negative plasma samples were collected from Egyptian patients. HCV viral load was quantified using m2000rt (Abbott Molecular Inc., Des Plaines, IL). HCV genotypes were determined using multiplex nested RT- PCR. The assay is based on the aggregation of AuNPs in presence of the target RNA. Aggregation of AuNPs causes a color shift from red to blue. AuNPs were synthesized using citrate reduction method. Different sets of probes within the 5’ UTR conserved region of the HCV genome were designed, grafted on AuNPs and optimized for the efficient detection of HCV RNA. Results: The nano-gold assay could colorimetrically detect HCV RNA down to 125 IU/ml with sensitivity and specificity of 91.1% and 93.8% respectively. The turnaround time of the assay is < 30 min. Conclusions: The assay allows sensitive and rapid detection of HCV RNA and represents an inexpensive and simple point-of-care assay for resource-limited settings.

Keywords: HCV, gold nanoparticles, point of care, viral load

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

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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 needs 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. A river flow consisting of small and shallow channels sometimes divide and recombine numerous times because of the slow water flow or the built up sediments. The pattern formed during this process resembles the strands of a braid. Braided streams form where the sediment load is so heavy that some of the sediments are deposited as shifting islands. Braided rivers often exist near the mountainous regions and typically carry coarse-grained and heterogeneous sediments down a fairly steep gradient. In this paper, the apparent shear stress formulae were suitably modified, and the Energy Concept Method (ECM) was applied for the prediction of discharges at the junction of a two-flow braided compound channel. The Energy Concept Method has not been applied for estimating the discharges in the braided channels. The energy loss in the channels is analyzed based on mechanical analysis. The cross-section of channel is divided into two sub-areas, namely the main-channel below the bank-full level and region above the bank-full level for estimating the total discharge. The experimental data are compared with a wide range of theoretical data available in the published literature to verify this model. The accuracy of this approach is also compared with Divided Channel Method (DCM). From error analysis of this method, it is observed that the relative error is less for the data-sets having smooth floodplains when compared to rough floodplains. Comparisons with other models indicate that the present method has reasonable accuracy for engineering purposes.

Keywords: critical flow, energy concept, open channel flow, sediment, two-flow braided compound channel

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Authors: Burcu Uçan

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The certification approach differs in civil and military projects in aviation. Sets of criteria and standards created by airworthiness authorities for the determination of certification basis are distinct. While the civil standards are more understandable and clear because of not only include detailed specifications but also the help of guidance materials such as Advisory Circular, military criteria do not provide this level of guidance. Therefore, specifications that are more negotiable and sometimes more difficult to reconcile arise for the certification basis of a military aircraft. This study investigates a method of how to develop a military specification set by taking advantage of civil standards, regarding the European Military Airworthiness Criteria (EMACC) that establishes the airworthiness criteria for aircraft systems. Airworthiness Certification Criteria (MIL-HDBK-516C) is a handbook published for guidance that contains qualitative evaluation for military aircrafts meanwhile Certification Specifications (CS-29) is published for civil aircrafts by European Union Aviation Safety Agency (EASA). This method intends to compare and contrast specifications that MIL-HDBK-516C and CS-29 contain within the scope of Human Factors. Human Factors supports human performance and aims to improve system performance by encompassing knowledge from a range of scientific disciplines. Human Factors focuses on how people perform their tasks and reduce the risk of an accident occurring due to human physical and cognitive limitations. Hence, regardless of whether the project is civil or military, the specifications must be guided at a certain level by taking into account human limits. This study presents an advisory method for this purpose. The method in this study develops a solution for the military certification process by identifying the CS requirement corresponding to the criteria in the MIL-HDBK-516C by means of EMACC. Thus, it eases understanding the expectations of the criteria and establishing derived requirements. As a result of this method, it may not always be preferred to derive new requirements. Instead, it is possible to add remarks to make the expectancy of the criteria and required verification methods more comprehensible for all stakeholders. This study contributes to creating a certification basis for military aircraft, which is difficult and takes plenty of time for stakeholders to agree due to gray areas in the certification process for military aircrafts.

Keywords: human factors, certification, aerospace, requirement

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Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Gonzalo Reyes, Magdalena Walczak, Esteban Ramos-Moore, Jorge Ramos-Grez

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Metal additive manufacture technologies have gained strong support and acceptance as a promising and alternative method to manufacture high performance complex geometry products. The main purpose of the present work is to study the microstructure and phase transformation temperatures of Cu-Al-Ni shape memory alloys fabricated from a direct laser additive process using metallic powders as precursors. The potential application is to manufacture self-centering seismic dampers for earthquake protection of buildings out of a copper based alloy by an additive process. In this process, the Cu-Al-Ni alloy is melted, inside of a high temperature and vacuum chamber with the aid of a high power fiber laser under inert atmosphere. The laser provides the energy to melt the alloy powder layer. The process allows fabricating fully dense, oxygen-free Cu-Al-Ni specimens using different laser power levels, laser powder interaction times, furnace ambient temperatures, and cooling rates as well as modifying concentration of the alloying elements. Two sets of specimens were fabricated with a nominal composition of Cu-13Al-3Ni and Cu-13Al-4Ni in wt.%, however, semi-quantitative chemical analysis using EDX examination showed that the specimens’ resulting composition was closer to Cu-12Al-5Ni and Cu-11Al-8Ni, respectively. In spite of that fact, it is expected that the specimens should still possess shape memory behavior. To confirm this hypothesis, phase transformation temperatures will be measured using DSC technique, to look for martensitic and austenitic phase transformations at 150°C. So far, metallographic analysis of the specimens showed defined martensitic microstructures. Moreover, XRD technique revealed diffraction peaks corresponding to (0 0 18) and (1 2 8) planes, which are too associated with the presence of martensitic phase. We conclude that it would be possible to obtain fully dense Cu-Al-Ni alloys having shape memory effect behavior by direct laser fabrication process, and to advance into fabrication of self centering seismic dampers by a controllable metal additive manufacturing process.

Keywords: Cu-Al-Ni alloys, direct laser fabrication, shape memory alloy, self-centering seismic dampers

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Authors: Azariah Sosa, Carlos Renedo Sanchez

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The development of a new motorway north of Auckland (New Zealand) includes steep rock cuts, from 63 up to 85 degrees, in an interbedded sandstone and siltstone rock mass of the geological unit Waitemata Group (Pakiri Formation), which shows sub-horizontal bedding planes, various sub-vertical joint sets, and a diverse weathering profile. In this kind of rock mass -that can be classified as a weak rock- the definition of the stable maximum geometry is not only governed by discontinuities and defects evident in the rock but is important to also consider the global stability of the rock slope, including (in the analysis) the rock mass characterisation, influence of the groundwater, the geological evolution, and the weathering processes. Depending on the weakness of the rock and the processes suffered, the global stability could, in fact, be a more restricting element than the potential instability of individual blocks through discontinuities. This paper discusses those elements that govern the stability of the rock slopes constructed in a rock formation with favourable bedding and distribution of discontinuities (horizontal and vertical) but with a weak behaviour in terms of global rock mass characterisation. In this context, classifications as Q-Slope and slope stability assessment methodology (SSAM) have been demonstrated as important tools which complement the assessment of the global stability together with the analytical tools related to the wedge-type failures and limit equilibrium methods. The paper focuses on the applicability of these two new empirical classifications to evaluate the slope stability in 18 already excavated rock slopes in the Pakiri formation through comparison between the predicted and observed stability issues and by reviewing the outcome of analytical methods (Rocscience slope stability software suite) compared against the expected stability determined from these rock classifications. This exercise will help validate such findings and correlations arising from the two empirical methods in order to adjust the methods to the nature of this specific kind of rock mass and provide a better understanding of the long-term stability of the slopes studied.

Keywords: Pakiri formation, Q-slope, rock slope stability, SSAM, weak rock

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Authors: Ann Devitt, Mairead Brady, Markus Lamest, Stephen Gomez

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This study set out to explore the use of an online collaborative serious game for student learning in a postgraduate introductory marketing module. The simulation game aimed to bridge the theory-practice divide in marketing by allowing students to apply theory in a safe, simulated marketplace. This study addresses the following research questions: Does an online marketing simulation game engage students higher order cognitive skills? Does collaborative activity required develop students’ “soft” skills, such as communication and negotiation? What specific affordances of the online simulation promote learning? This qualitative case study took place in 2014 with 40 postgraduate students on a Business Masters Programme. The two-week intensive module combined lectures with collaborative activity on a marketing simulation game, MMX from Pearsons. The game requires student teams to compete against other teams in a marketplace and design a marketing plan to maximize key performance indicators. The data for this study comprise essays written by students after the module reflecting on their learning on the module. A thematic analysis was conducted of the essays using the following a priori theme sets: 6 levels of the cognitive domain of Blooms taxonomy; 5 principles of Cooperative Learning; affordances of simulation environments including experiential learning; motivation and engagement; goal orientation. Preliminary findings would strongly suggest that the game facilitated students identifying the value of theory in practice, in particular for future employment; enhanced their understanding of group dynamics and their role within that; and impacted very strongly, both positively and negatively on motivation. In particular the game mechanics of MMX, which hinges on the correct identification of a target consumer group, was identified as a key determinant of extrinsic and intrinsic motivation for learners. The findings also suggest that the situation of the simulation game within a broader module which required post-game reflection was valuable in identifying key learning of marketing concepts in both the positive and the negative experiences of the game.

Keywords: simulation, marketing, serious game, cooperative learning, bloom's taxonomy

Procedia PDF Downloads 553