Search results for: motor reliability test
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11295

Search results for: motor reliability test

5175 Well-being of Parents of Children with Autism Spectrum Disorder or Developmental Coordination Disorder: Cross-Cultural and Cross-disorder Comparative Studies

Authors: Léa Chawki, Émilie Cappe

Abstract:

Context: Nowadays, supporting parents of children with autism spectrum disorder (ASD) and helping them adjust to their child’s condition represents a core clinical and scientific necessity and is encouraged by the French National Strategy for Autism (2018). In France, ASD remains a challenging condition, causing distress, segregation and social stigma to concerned family members concerned by this handicap. The literature highlights that neurodevelopmental disorders in children, such as ASD, influence parental well-being. This impact could be different according to parents’ culture and the child’s particular disorder manifestation, such as developmental coordination disorder (DCC), for instance. Objectives: This present study aims to explore parental stress, anxiety and depressive symptoms, as well as the quality of life in parents of children with ASD or DCD, as well as the explicit individual, psychosocial and cultural factors of parental well-being. Methods: Participants will be recruited through diagnostic centers, child and specialized adolescent units, and organizations representing families with ASD and DCD. Our sample will include five groups of 150 parents: four groups of parents having children with ASD – one living in France, one in the US, one in Canada and the other in Lebanon – and one group of French parents of children with DCD. Self-evaluation measures will be filled directly by parents in order to measure parental stress, anxiety and depressive symptoms, quality of life, coping and emotional regulation strategies, internalized stigma, perceived social support, the child’s problem behaviors severity, as well as motor coordination deficits in children with ASD and DCD. A sociodemographic questionnaire will help collect additional useful data regarding participants and their children. Individual and semi-structured research interviews will be conducted to complete quantitative data by further exploring participants’ distinct experiences related to parenting a child with a neurodevelopmental disorder. An interview grid, specially designed for the needs of this study, will strengthen the comparison between the experiences of parents of children with ASD with those of parents of children with DCD. It will also help investigate cultural differences regarding parent support policies in the context of raising a child with ASD. Moreover, interviews will help clarify the link between certain research variables (behavioral differences between ASD and DCD, family leisure activities, family and children’s extracurricular life, etc.) and parental well-being. Research perspectives: Results of this study will provide a more holistic understanding of the roles of individual, psychosocial and cultural variables related to parental well-being. Thus, this study will help direct the implementation of support services offered to families of children with neurodevelopmental disorders (ASD and DCD). Also, the implications of this study are essential in order to guide families through changes related to public policies assisting neurodevelopmental disorders and other disabilities. The between-group comparison (ASD and DCD) is also expected to help clarify the origins of all the different challenges encountered by those families. Hence, it will be interesting to investigate whether complications perceived by parents are more likely to arise from child-symptom severity, or from the lack of support obtained from health and educational systems.

Keywords: Autism spectrum disorder, cross-cultural, cross-disorder, developmental coordination delay, well-being

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5174 Characterization and Properties of Novel Flame Retardants Based on s-Triazine

Authors: Sameh M. Osman, El-Refaie Kenawy, Zeid A. Al-Othman, Mohamed H. El-Newehy, El-Saied A. Aly, Sherine N. Khattab, Ayman El-Faham

Abstract:

Recently, there has been a huge interest in using cyanuric chloride in a wide range of functional group transformations, as Cyanuric chloride has temperature-dependent differential reactivity for displacement of chlorides with various nucleophiles In the present work, some copolymers based on s-triazine Unit were prepared by microwave-assisted synthesis. For comparison study, the copolymers were synthesized by the conventional method. Synthesized Copolymers were characterized by MP, IR, TGA, DSC and GPC. The result indicated that copolymers are thermally stable and in good in composition and yield. Further studies that involve the test for selected removal of transition elements such as Cu (II), Zn (II) and Mn (II). Moreover, the effects of the polymeric triazine derivatives containing different functional groups which expected to have a good thermal stability and char formation ability on thermal degradation and flame retardancy.

Keywords: flame retardants, heavy metals, microwave-assisted synthesis, s-triazine

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5173 Improving the Performance of Deep Learning in Facial Emotion Recognition with Image Sharpening

Authors: Ksheeraj Sai Vepuri, Nada Attar

Abstract:

We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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5172 Signature Verification System for a Banking Business Process Management

Authors: A. Rahaf, S. Liyakathunsia

Abstract:

In today’s world, unprecedented operational pressure is faced by banks that test the efficiency, effectiveness, and agility of their business processes. In a typical banking process, a person’s authorization is usually based on his signature on most all of the transactions. Signature verification is considered as one of the highly significant information needed for any bank document processing. Banks usually use Signature Verification to authenticate the identity of individuals. In this paper, a business process model has been proposed in order to increase the quality of the verification process and to reduce time and needed resources. In order to understand the current process, a survey has been conducted and distributed among bank employees. After analyzing the survey, a process model has been created using Bizagi modeler which helps in simulating the process after assigning time and cost of it. The outcomes show that the automation of signature verification process is highly recommended for a banking business process.

Keywords: business process management, process modeling, quality, Signature Verification

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5171 Indigenizing the Curriculum: Teaching at the Ifugao State University, Philippines

Authors: Nancy Ann P. Gonzales, Serafin L. Ngohayon

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The Nurturing Indigenous Knowledge Experts (NIKE) among the young generation in Ifugao was a project in Ifugao, Philippines spearheaded by the Ifugao State University (IFSU) and was sponsored by the UNESCO Association in Japan. Through the project, he Ifugao Indigenous Knowledge Workbook was developed. It contains nine chapters. The workbook was pilot-tested to students who had IK classes. The descriptive survey method of research was used. A questionnaire was used to gather data from first year Bachelor of Elementary Education and Bachelor of Political Science students. Frequency count, percentage and mean were computed. T-test was used to determine if there exists significant difference on knowledge gained before and after IK was taught to the students. Results revealed that the respondents have an increased level of IK in all the areas covered in the NIKE workbook after they enrolled in their classes. It is alarming to note that the students are knowledgeable about IK but they are not practicing it. However, according to the respondents, they will apply their IK through teaching after graduation.

Keywords: curriculum, elders, Indigenous knowledge, and students

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5170 Aspects Concerning the Use of Recycled Concrete Aggregates

Authors: Ion Robu, Claudiu Mazilu, Radu Deju

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Natural aggregates (gravel and crushed) are essential non-renewable resources which are used for infrastructure works and civil engineering. In European Union member states from Southeast Europe, it is estimated that the construction industry will grow by 4.2% thereafter complicating aggregate supply management. In addition, a significant additional problem that can be associated to the aggregates industry is wasting potential resources through waste dumping of inert waste, especially waste from construction and demolition activities. In 2012, in Romania, less than 10% of construction and demolition waste (including concrete) are valorized, while the European Union requires that by 2020 this proportion should be at least 70% (Directive 2008/98/EC on waste, transposed into Romanian legislation by Law 211/2011). Depending on the efficiency of waste processing and the quality of recycled aggregate concrete (RCA) obtained, poor quality aggregate can be used as foundation material for roads and at the high quality for new concrete on construction. To obtain good quality concrete using recycled aggregate is necessary to meet the minimum requirements defined by the rules for the manufacture of concrete with natural aggregate. Properties of recycled aggregate (density, granulosity, granule shape, water absorption, weight loss to Los Angeles test, attached mortar content etc.) are the basis for concrete quality; also establishing appropriate proportions between components and the concrete production methods are extremely important for its quality. This paper presents a study on the use of recycled aggregates, from a concrete of specified class, to acquire new cement concrete with different percentages of recycled aggregates. To achieve recycled aggregates several batches of concrete class C16/20, C25/30 and C35/45 were made, the compositions calculation being made according NE012/2007 CP012/2007. Tests for producing recycled aggregate was carried out using concrete samples of the established three classes after 28 days of storage under the above conditions. Cubes with 150mm side were crushed in a first stage with a jaw crusher Liebherr type set at 50 mm nominally. The resulting material was separated by sieving on granulometric sorts and 10-50 sort was used for preliminary tests of crushing in the second stage with a jaw crusher BB 200 Retsch model, respectively a hammer crusher Buffalo Shuttle WA-12-H model. It was highlighted the influence of the type of crusher used to obtain recycled aggregates on granulometry and granule shape and the influence of the attached mortar on the density, water absorption, behavior to the Los Angeles test etc. The proportion of attached mortar was determined and correlated with provenance concrete class of the recycled aggregates and their granulometric sort. The aim to characterize the recycled aggregates is their valorification in new concrete used in construction. In this regard have been made a series of concrete in which the recycled aggregate content was varied from 0 to 100%. The new concrete were characterized by point of view of the change in the density and compressive strength with the proportion of recycled aggregates. It has been shown that an increase in recycled aggregate content not necessarily mean a reduction in compressive strength, quality of the aggregate having a decisive role.

Keywords: recycled concrete aggregate, characteristics, recycled aggregate concrete, properties

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5169 Respiratory Indices and Sports Performance: A Comparision between Different Levels Basketballers

Authors: Ranjan Chakravarty, Satpal Yadav, Biswajit Basumatary, Arvind S. Sajwan

Abstract:

The purpose of this study is to compare the basketball players of different level on selected respiratory indices. Ninety male basketball players from different universities those who participated in intercollegiate and inter- varsity championship. Selected respiratory indices were resting pulse rate, resting blood pressure, vital capacity and resting respiratory rate. Mean and standard deviation of selected respiratory indices were calculated and three different levels i.e. beginners, intermediate and advanced were compared by using analysis of variance. In order to test the hypothesis, level of significance was set at 0.05. It was concluded that variability does not exist among the basketball players of different groups with respect to their selected respiratory indices i.e. resting pulse rate, resting blood pressure, vital capacity and resting respiratory rate.

Keywords: respiratory indices, sports performance, basketball players, intervarsity level

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5168 The Effect of Political Characteristics on the Budget Balance of Local Governments: A Dynamic System Generalized Method of Moments Data Approach

Authors: Stefanie M. Vanneste, Stijn Goeminne

Abstract:

This paper studies the effect of political characteristics of 308 Flemish municipalities on their budget balance in the period 1995-2011. All local governments experience the same economic and financial setting, however some governments have high budget balances, while others have low budget balances. The aim of this paper is to explain the differences in municipal budget balances by a number of economic, socio-demographic and political variables. The economic and socio-demographic variables will be used as control variables, while the focus of this paper will be on the political variables. We test four hypotheses resulting from the literature, namely (i) the partisan hypothesis tests if left wing governments have lower budget balances, (ii) the fragmentation hypothesis stating that more fragmented governments have lower budget balances, (iii) the hypothesis regarding the power of the government, higher powered governments would resolve in higher budget balances, and (iv) the opportunistic budget cycle to test whether politicians manipulate the economic situation before elections in order to maximize their reelection possibilities and therefore have lower budget balances before elections. The contributions of our paper to the existing literature are multiple. First, we use the whole array of political variables and not just a selection of them. Second, we are dealing with a homogeneous database with the same budget and election rules, making it easier to focus on the political factors without having to control for the impact of differences in the political systems. Third, our research extends the existing literature on Flemish municipalities as this is the first dynamic research on local budget balances. We use a dynamic panel data model. Because of the two lagged dependent variables as explanatory variables, we employ the system GMM (Generalized Method of Moments) estimator. This is the best possible estimator as we are dealing with political panel data that is rather persistent. Our empirical results show that the effect of the ideological position and the power of the coalition are of less importance to explain the budget balance. The political fragmentation of the government on the other hand has a negative and significant effect on the budget balance. The more parties in a coalition the worse the budget balance is ceteris paribus. Our results also provide evidence of an opportunistic budget cycle, the budget balances are lower in pre-election years relative to the other years to try and increase the incumbents reelection possibilities. An additional finding is that the incremental effect of the budget balance is very important and should not be ignored like is being done in a lot of empirical research. The coefficients of the lagged dependent variables are always positive and very significant. This proves that the budget balance is subject to incrementalism. It is not possible to change the entire policy from one year to another so the actions taken in recent past years still have an impact on the current budget balance. Only a relatively small amount of research concerning the budget balance takes this considerable incremental effect into account. Our findings survive several robustness checks.

Keywords: budget balance, fragmentation, ideology, incrementalism, municipalities, opportunistic budget cycle, panel data, political characteristics, power, system GMM

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5167 Mesoporous Tussah Silk Fibroin Microspheres for Drug Delivery

Authors: Weitao Zhou, Qing Wang, Jianxin He, Shizhong Cui

Abstract:

Mesoporous Tussah silk fibroin (TSF) spheres were fabricated via the self-assembly of TSF molecules in aqueous solutions. The results showed that TSF particles were approximately three-dimensional spheres with the diameter ranging from 500nm to 6μm without adherence. More importantly, the surface morphology is mesoporous structure with nano-pores of 20nm - 200nm in size. Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) studies demonstrated that mesoporous TSF spheres mainly contained beta-sheet conformation (44.1 %) as well as slight amounts of random coil (13.2 %). Drug release test was performed with 5-fluorouracil (5-Fu) as a model drug and the result indicated the mesoporous TSF microspheres had a good capacity of sustained drug release. It is expected that these stable and high-crystallinity mesoporous TSF sphere produced without organic solvents, which have significantly improved drug release properties, is a very promising material for controlled gene medicines delivery.

Keywords: Tussah silk fibroin, porous materials, microsphere, drug release

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5166 Contribution Spending on Intellectual Capital in the Performance of Industrial Enterprise Case study: Sonatrach

Authors: Dahmani Aziz, Mekdad Yousra

Abstract:

The intellectual capital is an important source of profitability and the main supporter of the competitive where this study examines the contribution of expenditure on intellectual capital in the performance of industrial enterprises Algerian, and through a case study Sonatrach as the most important industrial enterprises in Algeria and the driving force of the Algerian economy. It has been the use of value-added intellectual coefficient (VAIC) in measuring the contribution of intellectual capital and analyzing data Sonatrach during the period from the year 2001 until the year 2012, and test the validity of hypotheses using Stepwise Regression model through the SPSS statistical software, and the study has proved the existence of a positive relationship between spending on human capital and financial performance and a stronger degree relationship between the structural capital and economic performance.

Keywords: industrial enterprise, intellectual capital, performance, economy of Algeria, spending

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5165 Correlation between Potential Intelligence Explanatory Study in the Perspective of Multiple Intelligence Theory by Using Dermatoglyphics and Culture Approaches

Authors: Efnie Indrianie

Abstract:

Potential Intelligence constitutes one essential factor in every individual. This intelligence can be a provision for the development of Performance Intelligence if it is supported by surrounding environment. Fingerprint analysis is a method in recognizing this Potential Intelligence. This method is grounded on pattern and number of finger print outlines that are assumed symmetrical with the number of nerves in our brain, in which these areas have their own function among another. These brain’s functions are later being transposed into intelligence components in accordance with the Multiple Intelligences theory. This research tested the correlation between Potential Intelligence and the components of its Performance Intelligence. Statistical test results that used Pearson correlation showed that five components of Potential Intelligence correlated with Performance Intelligence. Those five components are Logic-Math, Logic, Linguistic, Music, Kinesthetic, and Intrapersonal. Also, this research indicated that cultural factor had a big role in shaping intelligence.

Keywords: potential intelligence, performance intelligence, multiple intelligences, fingerprint, environment, brain

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5164 Effects of Conjugated Linoleic Acid(CLA) on Some Reproductive Hormones in Ram

Authors: Behnaz Mahdavi, Hamidreza Khodaei, Leila Karshenas

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Conjugated Linoleic Acid is a group of long-chain unsaturated fatty acids with more than one double bond and a mixture of 28 isomers of Linoleic acid (C 18:2) and it is counted as one of the essential acids. The main purpose of this study was to investigate the effect of CLA on some reproductive hormones in rams. In this study, six rams 3 to 4 years old with an average weight of 90 kg were selected. Rams were randomly divided into 3 groups and were treated by CLA treatment for 30 days. The first group (as a control group) didn’t receive CLA, The second group received 0.5 gr and the third group received 1 gram of CLA. The blood testing was done on rams every 15 days using a 20 ml syringe. Data analysis was performed by SAS software. Also mean comparison was done using Duncan's test method (p<0.05). Obtained results showed that the serum concentration of testosterone hormone was decreased numerically as well as the concentration of FSH hormone however the concentration of LH was increased. CLA in oral form can reduce the concentration of testosterone in rams.

Keywords: CLA, ram, testosterone, DHT, Conjugated Linoleic Acid

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5163 Implementation of Correlation-Based Data Analysis as a Preliminary Stage for the Prediction of Geometric Dimensions Using Machine Learning in the Forming of Car Seat Rails

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

Abstract:

When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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5162 Impact of Brand Image, Brand Personality and Brand Love on Word of Mouth: Pakistani Fashion Brands

Authors: Amna Asif, Rabia Naseem

Abstract:

In the domain of consumer-brand relationship, love for a fashion brand is a dominant idea. Brand executives incline to build more endearing brands, for example, Levi’s “Quality never goes out of style”. Though, the significance of this notion is not often debated in the literature of marketing. Moreover, the effect of brand image and personality on brand love has not been examined in any quantitative study in Pakistan. The current research aims to fill this study gap by evolving a causal framework integrating word-of-mouth, brand love, image, and personality to examine the relationships among them. Data was gathered through questionnaires survey, and it was filled by 409 university students. AMOS 20 was used to draw a path analysis and test the hypotheses. Results discovered that brand personality and brand image leads to brand love that ultimately impacts word-of-mouth. Results give thorough suggestions on which future research can be constructed.

Keywords: brand love, brand personality, brand image, fashion brands, word-of-mouth

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5161 Temperature Susceptibility for Optimal Biogas Production

Authors: Ujjal Chattaraj, Pbharat Saikumar, Thinley Dorji

Abstract:

Earth is going to be a planet where no further life can sustain if people continue to pollute the environment. We need energy and fuels everyday for heating and lighting purposes in our life. It’s high time we know this problem and take measures at-least to reduce pollution and take alternative measures for everyday livelihood. Biogas is one of them. It is very essential to define and control the parameters for optimization of biogas production. Biogas plants can be made of different size, but it is very vital to make a biogas which will be cost effective, with greater efficiency (more production) and biogas plants that will sustain for a longer period of time for usage. In this research, experiments were carried out only on cow dung and Chicken manure depending on the substrates people out there (Bhutan) used. The experiment was done within 25 days and was tested for different temperatures and found out which produce more amount. Moreover, it was also statistically tested for their dependency and non-dependency which gave clear idea more on their production.

Keywords: digester, mesophilic temperature, organic manure, statistical analysis, thermophilic temperature, t-test

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5160 Effects of Mechanical Test and Shape of Grain Boundary on Martensitic Transformation in Fe-Ni-C Steel

Authors: Mounir Gaci, Salim Meziani, Atmane Fouathia

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The purpose of the present paper is to model the behavior of metal alloy, type TRIP steel (Transformation Induced Plasticity), during solid/solid phase transition. A two-dimensional micromechanical model is implemented in finite element software (ZEBULON) to simulate the martensitic transformation in Fe-Ni-C steel grain under mechanical tensile stress of 250 MPa. The effects of non-uniform grain boundary and the criterion of mechanical shear load on the transformation and on the TRIP value during martensitic transformation are studied. The suggested mechanical criterion is favourable to the influence of the shear phenomenon on the progression of the martensitic transformation (Magee’s mechanism). The obtained results are in satisfactory agreement with experimental ones and show the influence of the grain boundary shape and the chosen mechanical criterion (SMF) on the transformation parameters.

Keywords: martensitic transformation, non-uniform Grain Boundary, TRIP, shear Mechanical force (SMF)

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5159 Engineering Topology of Ecological Model for Orientation Impact of Sustainability Urban Environments: The Spatial-Economic Modeling

Authors: Moustafa Osman Mohammed

Abstract:

The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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5158 Development and Characterization of Wear Properties of Aluminum 8011 Hybrid Metal Matrix Composites

Authors: H. K. Shivanand, A. Yogananda

Abstract:

The objective of present investigation is to study the effect of reinforcements on the wear properties of E-Glass short fibers and Flyash reinforced Al 8011 hybrid metal matrix composites. The alloy of Al 8011 reinforced with E-glass and fly ash particulates are prepared by simple stir casting method. The MMC is obtained for different composition of E-glass and flyash particulates (varying E-glass with constant fly ash and varying flyash with constant E-glass percentage). The wear results of ascast hybrid composites with different compositions of reinforcements at varying sliding speeds and different loads are discussed. The results reveals that as the percentage of reinforcement increases wear rate will decrease.

Keywords: metal matrix composites, aluminum alloy 8011, stir casting, wear test

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5157 The Processing of Context-Dependent and Context-Independent Scalar Implicatures

Authors: Liu Jia’nan

Abstract:

The default accounts hold the view that there exists a kind of scalar implicature which can be processed without context and own a psychological privilege over other scalar implicatures which depend on context. In contrast, the Relevance Theorist regards context as a must because all the scalar implicatures have to meet the need of relevance in discourse. However, in Katsos, the experimental results showed: Although quantitatively the adults rejected under-informative utterance with lexical scales (context-independent) and the ad hoc scales (context-dependent) at almost the same rate, adults still regarded the violation of utterance with lexical scales much more severe than with ad hoc scales. Neither default account nor Relevance Theory can fully explain this result. Thus, there are two questionable points to this result: (1) Is it possible that the strange discrepancy is due to other factors instead of the generation of scalar implicature? (2) Are the ad hoc scales truly formed under the possible influence from mental context? Do the participants generate scalar implicatures with ad hoc scales instead of just comparing semantic difference among target objects in the under- informative utterance? In my Experiment 1, the question (1) will be answered by repetition of Experiment 1 by Katsos. Test materials will be showed by PowerPoint in the form of pictures, and each procedure will be done under the guidance of a tester in a quiet room. Our Experiment 2 is intended to answer question (2). The test material of picture will be transformed into the literal words in DMDX and the target sentence will be showed word-by-word to participants in the soundproof room in our lab. Reading time of target parts, i.e. words containing scalar implicatures, will be recorded. We presume that in the group with lexical scale, standardized pragmatically mental context would help generate scalar implicature once the scalar word occurs, which will make the participants hope the upcoming words to be informative. Thus if the new input after scalar word is under-informative, more time will be cost for the extra semantic processing. However, in the group with ad hoc scale, scalar implicature may hardly be generated without the support from fixed mental context of scale. Thus, whether the new input is informative or not does not matter at all, and the reading time of target parts will be the same in informative and under-informative utterances. People’s mind may be a dynamic system, in which lots of factors would co-occur. If Katsos’ experimental result is reliable, will it shed light on the interplay of default accounts and context factors in scalar implicature processing? We might be able to assume, based on our experiments, that one single dominant processing paradigm may not be plausible. Furthermore, in the processing of scalar implicature, the semantic interpretation and the pragmatic interpretation may be made in a dynamic interplay in the mind. As to the lexical scale, the pragmatic reading may prevail over the semantic reading because of its greater exposure in daily language use, which may also lead the possible default or standardized paradigm override the role of context. However, those objects in ad hoc scale are not usually treated as scalar membership in mental context, and thus lexical-semantic association of the objects may prevent their pragmatic reading from generating scalar implicature. Only when the sufficient contextual factors are highlighted, can the pragmatic reading get privilege and generate scalar implicature.

Keywords: scalar implicature, ad hoc scale, dynamic interplay, default account, Mandarin Chinese processing

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5156 The Relation between Proactive Coping and Well-Being: An Example of Middle-Aged and Older Learners from Taiwan

Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

Abstract:

The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: middle-age and older adults, learners, proactive coping, well-being

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5155 DC Bus Voltage Ripple Control of Photo Voltaic Inverter in Low Voltage Ride-Trough Operation

Authors: Afshin Kadri

Abstract:

Using Renewable Energy Resources (RES) as a type of DG unit is developing in distribution systems. The connection of these generation units to existing AC distribution systems changes the structure and some of the operational aspects of these grids. Most of the RES requires to power electronic-based interfaces for connection to AC systems. These interfaces consist of at least one DC/AC conversion unit. Nowadays, grid-connected inverters must have the required feature to support the grid under sag voltage conditions. There are two curves in these conditions that show the magnitude of the reactive component of current as a function of voltage drop value and the required minimum time value, which must be connected to the grid. This feature is named low voltage ride-through (LVRT). Implementing this feature causes problems in the operation of the inverter that increases the amplitude of high-frequency components of the injected current and working out of maximum power point in the photovoltaic panel connected inverters are some of them. The important phenomenon in these conditions is ripples in the DC bus voltage that affects the operation of the inverter directly and indirectly. The losses of DC bus capacitors which are electrolytic capacitors, cause increasing their temperature and decreasing its lifespan. In addition, if the inverter is connected to the photovoltaic panels directly and has the duty of maximum power point tracking, these ripples cause oscillations around the operating point and decrease the generating energy. Using a bidirectional converter in the DC bus, which works as a buck and boost converter and transfers the ripples to its DC bus, is the traditional method to eliminate these ripples. In spite of eliminating the ripples in the DC bus, this method cannot solve the problem of reliability because it uses an electrolytic capacitor in its DC bus. In this work, a control method is proposed which uses the bidirectional converter as the fourth leg of the inverter and eliminates the DC bus ripples using an injection of unbalanced currents into the grid. Moreover, the proposed method works based on constant power control. In this way, in addition, to supporting the amplitude of grid voltage, it stabilizes its frequency by injecting active power. Also, the proposed method can eliminate the DC bus ripples in deep voltage drops, which cause increasing the amplitude of the reference current more than the nominal current of the inverter. The amplitude of the injected current for the faulty phases in these conditions is kept at the nominal value and its phase, together with the phase and amplitude of the other phases, are adjusted, which at the end, the ripples in the DC bus are eliminated, however, the generated power decreases.

Keywords: renewable energy resources, voltage drop value, DC bus ripples, bidirectional converter

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5154 Damage Micromechanisms of Coconut Fibers and Chopped Strand Mats of Coconut Fibers

Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

Abstract:

The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

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5153 Experience of Using Expanding Polyurethane Resin for Ground Improvement Under Existing Shallow Foundations on The Arabian Peninsula

Authors: Evgeny N. Zakharin, Bartosz Majewski

Abstract:

Foaming polyurethane is a ground improvement technology that is increasingly used for foundation stabilization with differential settlement and controlled foundation structure lifting. This technology differs from conventional mineral grout due to its injection composition, which provides high-pressure expansion quickly due to a chemical reaction. The technology has proven efficient in the typical geological conditions of the United Arab Emirates. An in-situ trial foundation load test has been proposed to objectively assess the deformative and load-bearing characteristics of the soil after injection. The article provides a detailed description of the experiment carried out in field conditions. Based on the practical experiment's results and its finite element modeling, the deformation modulus of the soil after treatment was determined, which was more than five times higher than the initial value.

Keywords: chemical grout, expanding polyurethane resin, foundation remediation, ground improvement

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5152 Multiple Plant-Based Cell Suspension as a Bio-Ink for 3D Bioprinting Applications in Food Technology

Authors: Yusuf Hesham Mohamed

Abstract:

Introduction: Three-dimensional printing technology includes multiple procedures that fabricate three-dimensional objects through consecutively layering two-dimensional cross-sections on top of each other. 3D bioprinting is a promising field of 3D printing, which fabricates tissues and organs by accurately controlling the proper arrangement of diverse biological components. 3D bioprinting uses software and prints biological materials and their supporting components layer-by-layer on a substrate or in a tissue culture plate to produce complex live tissues and organs. 3D food printing is an emerging field of 3D bioprinting in which the 3D printed products are food products that are cheap, require less effort to produce, and have more desirable traits. The Aim of the Study is the development of an affordable 3D bioprinter by altering a locally made CNC instrument with an open-source platform to suit the 3D bio-printer purposes. Later, we went through applying the prototype in several applications regarding food technology and drug testing, including the organ-On-Chip. Materials and Methods: An off-the-shelf 3D printer was modified by designing and fabricating the syringe unit, which was designed on the basis of the Milli-fluidics system. Sodium alginate and gelatin hydrogels were prepared, followed by leaf cell suspension preparation from narrow sections of Fragaria’s viable leaves. The desired 3D structure was modeled, and 3D printing preparations took place. Cell-free and cell-laden hydrogels were printed at room temperature under sterile conditions. Post printing curing process was performed. The printed structure was further studied. Results: Positive results have been achieved using the altered 3D bioprinter where a 3D hydrogel construct of two layers made of the combination of sodium alginate to gelatin (15%: 0.5%) has been printed. DLP 3D printer was used to design the syringe component with a transparent PLA-Pro resin for the creation of a microfluidics system having two channels altered to the double extruder. The hydrogel extruder’s design was based on peristaltic pumps, which utilized a stepper motor. The design and fabrication were made using DIY-3D printed parts. Hard plastic PLA was the material utilized for printing. SEM was used to carry out the porous 3D construct imaging. Multiple physical and chemical tests were performed in order to ensure that the cell line was suitable for hosting. Fragaria plant was developed by suspending Fragaria’s cells from its leaves using the 3D bioprinter. Conclusion: 3D bioprinting is considered to be an emerging scientific field that can facilitate and improve many scientific tests and studies. Thus, having a 3D bioprinter in labs is considered to be an essential requirement. 3D bioprinters are very expensive; however, the fabrication of a 3D printer into a 3D bioprinter can lower the cost of the bioprinter. The 3D bioprinter implemented made use of peristaltic pumps instead of syringe-based pumps in order to extend the ability to print multiple types of materials and cells.

Keywords: scaffold, eco on chip, 3D bioprinter, DLP printer

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5151 An Evolutionary Approach for Automated Optimization and Design of Vivaldi Antennas

Authors: Sahithi Yarlagadda

Abstract:

The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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5150 Electrophysiological Correlates of Statistical Learning in Children with and without Developmental Language Disorder

Authors: Ana Paula Soares, Alexandrina Lages, Helena Oliveira, Francisco-Javier Gutiérrez-Domínguez, Marisa Lousada

Abstract:

From an early age, exposure to a spoken language allows us to implicitly capture the structure underlying the succession of the speech sounds in that language and to segment it into meaningful units (words). Statistical learning (SL), i.e., the ability to pick up patterns in the sensory environment even without intention or consciousness of doing it, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language and possibly to lie behind the language difficulties exhibited by children with development language disorder (DLD). The research conducted so far has, however, led to inconsistent results, which might stem from the behavioral tasks used to test SL. In a classic SL experiment, participants are first exposed to a continuous stream (e.g., syllables) in which, unbeknownst to the participants, stimuli are grouped into triplets that always appear together in the stream (e.g., ‘tokibu’, ‘tipolu’), with no pauses between each other (e.g., ‘tokibutipolugopilatokibu’) and without any information regarding the task or the stimuli. Following exposure, SL is assessed by asking participants to discriminate between triplets previously presented (‘tokibu’) from new sequences never presented together during exposure (‘kipopi’), i.e., to perform a two-alternative-forced-choice (2-AFC) task. Despite the widespread use of the 2-AFC to test SL, it has come under increasing criticism as it is an offline post-learning task that only assesses the result of the learning that had occurred during the previous exposure phase and that might be affected by other factors beyond the computation of regularities embedded in the input, typically the likelihood two syllables occurring together, a statistic known as transitional probability (TP). One solution to overcome these limitations is to assess SL as exposure to the stream unfolds using online techniques such as event-related potentials (ERP) that is highly sensitive to the time-course of the learning in the brain. Here we collected ERPs to examine the neurofunctional correlates of SL in preschool children with DLD, and chronological-age typical language development (TLD) controls who were exposed to an auditory stream in which eight three-syllable nonsense words, four of which presenting high-TPs and the other four low-TPs, to further analyze whether the ability of DLD and TLD children to extract-word-like units from the steam was modulated by words’ predictability. Moreover, to ascertain if the previous knowledge of the to-be-learned-regularities affected the neural responses to high- and low-TP words, children performed the auditory SL task, firstly, under implicit, and, subsequently, under explicit conditions. Although behavioral evidence of SL was not obtained in either group, the neural responses elicited during the exposure phases of the SL tasks differentiated children with DLD from children with TLD. Specifically, the results indicated that only children from the TDL group showed neural evidence of SL, particularly in the SL task performed under explicit conditions, firstly, for the low-TP, and, subsequently, for the high-TP ‘words’. Taken together, these findings support the view that children with DLD showed deficits in the extraction of the regularities embedded in the auditory input which might underlie the language difficulties.

Keywords: development language disorder, statistical learning, transitional probabilities, word segmentation

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5149 Abating the Barriers to the Deployment of RFID for Construction Project Delivery in South Africa

Authors: Matthew O. Ikuabe, Ayodeji E. Oke, Clinton O. Aigbavboa, Douglas O. Aghimien

Abstract:

The use of technological innovations have been touted to be beneficial in the delivery of construction projects. Particularly, Radio Frequency Identification (RFID) technology is widely regarded to be of immense advantage for the management of construction projects. This study focused on evaluating the barriers to the use of Radio Frequency Identification (RFID) technology for the delivery of construction projects. Using Gauteng Provincein South Africa as the study area, questionnaire was used in eliciting responses from construction professionals, which made up the population of the study. Retrieved data was analysed using Mean Item Score and One-Sample t-test. Findings from the study showed that the most significant barriers to the deployment of RFID for construction project delivery are high cost and lack of awareness. Conclusively, the study made recommendations that would aid in the abatement of the barriers to the use of RFID technology for construction project delivery.

Keywords: barriers, construction, project delivery, RFID

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5148 Examining the Dynamics of FDI Inflows in Both BRICS and G7 Economies: Dissecting the Influence of Geopolitical Risk versus Economic Policy Uncertainty

Authors: Adelakun O. Johnson

Abstract:

The quest to mitigate the probable adverse effects of geopolitical risk on FDI inflows tends to result in more frequent changes in economic policies and, as a result, heightened policy uncertainty. In this regard, we extend the literature on the dynamics of FDI inflows to include the hypothesis of the possibility of geopolitical risk escalating the adverse effects of economic policy uncertainty on FDI inflows. To test the robustness of this hypothesis, we use the cases of different economic groups characterized by different levels of economic development and varying degrees of FDI confidence. Employing an ARDL-based dynamic panel data model that accounts for both non-stationarity and heterogeneity effects, we show result that suggests GPR and EPU retard the inflows of FDI in both economies but mainly in the short-run situation. In the long run, however, higher EPU not attributed to GPR is likely to boost the inflows of FDI rather than retarding, at least in the case of the G7 economy.

Keywords: FDI inflows, geopolitical risk, economic policy uncertainty, panel ARDL model

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5147 Rodriguez Diego, Del Valle Martin, Hargreaves Matias, Riveros Jose Luis

Authors: Nathainail Bashir, Neil Anderson

Abstract:

The objective of this study site was to investigate the current state of the practice with regards to karst detection methods and recommend the best method and pattern of arrays to acquire the desire results. Proper site investigation in karst prone regions is extremely valuable in determining the location of possible voids. Two geophysical techniques were employed: multichannel analysis of surface waves (MASW) and electric resistivity tomography (ERT).The MASW data was acquired at each test location using different array lengths and different array orientations (to increase the probability of getting interpretable data in karst terrain). The ERT data were acquired using a dipole-dipole array consisting of 168 electrodes. The MASW data was interpreted (re: estimated depth to physical top of rock) and used to constrain and verify the interpretation of the ERT data. The ERT data indicates poorer quality MASW data were acquired in areas where there was significant local variation in the depth to top of rock.

Keywords: dipole-dipole, ERT, Karst terrains, MASW

Procedia PDF Downloads 314
5146 Enhancing Fault Detection in Rotating Machinery Using Wiener-CNN Method

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 74