Search results for: link prediction

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Natalia Kartushina

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Foreign (second) language (L2) learning is highly promoted in modern society. Students are encouraged to study abroad (SA) to achieve the most effective learning outcomes. However, L2 learning has side effects for native language (L1) production, as L1 sounds might show a drift from the L1 norms towards those of the L2, and this, even after a short period of L2 learning. L1 assimilatory drift has been attributed to a strong perceptual association between similar L1 and L2 sounds in the mind of L2 leaners; thus, a change in the production of an L2 target leads to the change in the production of the related L1 sound. However, nowadays, it is quite common that speakers acquire two languages from birth, as, for example, it is the case for many bilingual communities (e.g., Basque and Spanish in the Basque Country). Yet, it remains to be established how FL learning affects native production in individuals who have two native languages, i.e., in simultaneous or very early bilinguals. Does FL learning (here a third language, L3) affect bilinguals’ both languages or only one? What factors determine which of the bilinguals’ languages is more susceptible to change? The current study examines the effects of L3 (English) learning on the production of vowels in the two native languages of simultaneous Spanish-Basque bilingual adolescents enrolled into the Erasmus SA English program. Ten bilingual speakers read five Spanish and Basque consonant-vowel-consonant-vowel words two months before their SA and the next day after their arrival back to Spain. Each word contained the target vowel in the stressed syllable and was repeated five times. Acoustic analyses measuring vowel openness (F1) and backness (F2) were performed. Two possible outcomes were considered. First, we predicted that L3 learning would affect the production of only one language and this would be the language that would be used the most in contact with English during the SA period. This prediction stems from the results of recent studies showing that early bilinguals have separate phonological systems for each of their languages; and that late FL learner (as it is the case of our participants), who tend to use their L1 in language-mixing contexts, have more L2-accented L1 speech. The second possibility stated that L3 learning would affect both of the bilinguals’ languages in line with the studies showing that bilinguals’ L1 and L2 phonologies interact and constantly co-influence each other. The results revealed that speakers who used both languages equally often (balanced users) showed an F1 drift in both languages toward the F1 of the English vowel space. Unbalanced speakers, however, showed a drift only in the less used language. The results are discussed in light of recent studies suggesting that the amount of language use is a strong predictor of the authenticity in speech production with less language use leading to more foreign-accented speech and, eventually, to language attrition.

Keywords: language-contact, multilingualism, phonetic drift, bilinguals' production

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Authors: Reuben Newell, Edward Archer, Alistair McIlhagger, Calvin Ralph

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Modern industry has developed a need for innovative 3D composite materials due to their attractive material properties. Composite materials are composed of a fibre reinforcement encased in a polymer matrix. The fibre reinforcement consists of warp, weft and binder yarns or tows woven together into a preform. The mechanical performance of composite material is largely controlled by the properties of the preform. As a result, the bulk of recent textile research has been focused on the design of high-strength preform architectures. Studies looking at optimisation of the weaving process have largely been neglected. It has been reported that yarns experience varying levels of damage during weaving, resulting in filament breakage and ultimately compromised composite mechanical performance. The weaving parameters involved in causing this yarn damage are not fully understood. Recent studies indicate that poor yarn tension control may be an influencing factor. As tension is increased, the yarn-to-yarn and yarn-to-weaving-equipment interactions are heightened, maximising damage. The correlation between yarn tension variation and weaving damage severity has never been adequately researched or quantified. A novel study is needed which accesses the influence of tension variation on the mechanical properties of woven yarns. This study has looked to quantify the variation of yarn tension throughout weaving and sought to link the impact of tension to weaving damage. Multiple yarns were randomly selected, and their tension was measured across the creel and shedding stages of weaving, using a hand-held tension meter. Sections of the same yarn were subsequently cut from the loom machine and tensile tested. A comparison study was made between the tensile strength of pristine and tensioned yarns to determine the induced weaving damage. Yarns from bobbins at the rear of the creel were under the least amount of tension (0.5-2.0N) compared to yarns positioned at the front of the creel (1.5-3.5N). This increase in tension has been linked to the sharp turn in the yarn path between bobbins at the front of the creel and creel I-board. Creel yarns under the lower tension suffered a 3% loss of tensile strength, compared to 7% for the greater tensioned yarns. During shedding, the tension on the yarns was higher than in the creel. The upper shed yarns were exposed to a decreased tension (3.0-4.5N) compared to the lower shed yarns (4.0-5.5N). Shed yarns under the lower tension suffered a 10% loss of tensile strength, compared to 14% for the greater tensioned yarns. Interestingly, the most severely damaged yarn was exposed to both the largest creel and shedding tensions. This study confirms for the first time that yarns under a greater level of tension suffer an increased amount of weaving damage. Significant variation of yarn tension has been identified across the creel and shedding stages of weaving. This leads to a variance of mechanical properties across the woven preform and ultimately the final composite part. The outcome from this study highlights the need for optimised yarn tension control during preform manufacture to minimize yarn-induced weaving damage.

Keywords: optimisation of preform manufacture, tensile testing of damaged tows, variation of yarn weaving tension, weaving damage

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Authors: Mangala. Sadasivan, Mary Hughes, Bryan Kelly

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Medical Education must focus on bridging the gap between teaching and learning when training pre-clinical year students in skills needed to keep up with medical knowledge and to meet the demands of health care in the future. The authors were interested in showing that a 3-S Model (building strength, developing stamina, and increasing speed) using a bridged curriculum design helps connect teaching and learning and improves students’ retention of basic science and clinical knowledge. The authors designed three learning modules using the 3-S Model within a systems course in a pre-clerkship medical curriculum. Each module focused on a bridge (concept map) designed by the instructor for specific content delivered to students in the course. This with-in-subjects design study included 304 registered MSU osteopathic medical students (3 campuses) ranked by quintile based on previous coursework. The instructors used the bridge to create self-directed learning exercises (building strength) to help students master basic science content. Students were video coached on how to complete assignments, and given pre-tests and post-tests designed to give them control to assess and identify gaps in learning and strengthen connections. The instructor who designed the modules also used video lectures to help students master clinical concepts and link them (building stamina) to previously learned material connected to the bridge. Boardstyle practice questions relevant to the modules were used to help students improve access (increasing speed) to stored content. Unit Examinations covering the content within modules and materials covered by other instructors teaching within the units served as outcome measures in this study. This data was then compared to each student’s performance on a final comprehensive exam and their COMLEX medical board examinations taken some time after the course. The authors used mean comparisons to evaluate students’ performances on module items (using 3-S Model) to non-module items on unit exams, final course exam and COMLEX medical board examination. The data shows that on average, students performed significantly better on module items compared to non-module items on exams 1 and 2. The module 3 exam was canceled due to a university shut down. The difference in mean scores (module verses non-module) items disappeared on the final comprehensive exam which was rescheduled once the university resumed session. Based on Quintile designation, the mean scores were higher for module items than non-module items and the difference in scores between items for Quintiles 1 and 2 were significantly better on exam 1 and the gap widened for all Quintile groups on exam 2 and disappeared in exam 3. Based on COMLEX performance, all students on average as a group, whether they Passed or Failed, performed better on Module items than non-module items in all three exams. The gap between scores of module items for students who passed COMLEX to those who failed was greater on Exam 1 (14.3) than on Exam 2 (7.5) and Exam 3 (10.2). Data shows the 3-S Model using a bridge effectively connects teaching and learning

Keywords: bridging gap, medical education, teaching and learning, model of learning

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Authors: Jessie Rapoza, Petr Moroshkin, Jimmy Xu

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Chirality is omnipresent, in nature, in life, and in the field of physics. One intriguing example is the homochirality that has remained a great secret of life. Another is the pairs of mirror-image molecules – enantiomers. They are identical in atomic composition and therefore indistinguishable in the scalar physical properties. Yet, they can be either therapeutic or toxic, depending on their chirality. Recent studies suggest a potential link between abnormal levels of certain D-amino acids and some serious health impairments, including schizophrenia, amyotrophic lateral sclerosis, and potentially cancer. Although indistinguishable in their scalar properties, the chirality of a molecule reveals itself in interaction with the surrounding of a certain chirality, or more generally, a broken mirror-symmetry. In this work, we report on a system for chiral molecule detection, in which the mirror-symmetry is doubly broken, first by asymmetric structuring a nanopatterned plasmonic surface than by the incidence of circularly polarized light (CPL). In this system, the incident circularly-polarized light induces a surface plasmon polariton (SPP) wave, propagating along the asymmetric plasmonic surface. This SPP field itself is chiral, evanescently bound to a near-field zone on the surface (~10nm thick), but with an amplitude greatly intensified (by up to 104) over that of the incident light. It hence probes just the molecules on the surface instead of those in the volume. In coupling to molecules along its path on the surface, the chiral SPP wave favors one chirality over the other, allowing for chirality detection via the change in an optical rectification current measured at the edges of the sample. The asymmetrically structured surface converts the high-frequency electron plasmonic-oscillations in the SPP wave into a net DC drift current that can be measured at the edge of the sample via the mechanism of optical rectification. The measured results validate these design concepts and principles. The observed optical rectification current exhibits a clear differentiation between a pair of enantiomers. Experiments were performed by focusing a 1064nm CW laser light at the sample - a gold grating microchip submerged in an approximately 1.82M solution of either L-arabinose or D-arabinose and water. A measurement of the current output was then recorded under both rights and left circularly polarized lights. Measurements were recorded at various angles of incidence to optimize the coupling between the spin-momentums of the incident light and that of the SPP, that is, spin-momentum locking. In order to suppress the background, the values of the photocurrent for the right CPL are subtracted from those for the left CPL. Comparison between the two arabinose enantiomers reveals a preferential signal response of one enantiomer to left CPL and the other enantiomer to right CPL. In sum, this work reports on the first experimental evidence of the feasibility of chiral molecule detection via optical rectification in a metal meta-grating. This nanoscale interfaced electrical detection technology is advantageous over other detection methods due to its size, cost, ease of use, and integration ability with read-out electronic circuits for data processing and interpretation.

Keywords: Chirality, detection, molecule, spin

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Authors: Margarita Ivanova, Julia Dao, Andrew Friedman, Neil Kasaci, Rekha Gopal, Ozlem Goker-Alpan

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In Fabry disease (FD), α-galactosidase A (α-Gal A) deficiency leads to the accumulation of globotriaosylceramide (Lyso-Gb3 and Gb3), triggering a pathologic cascade that causes the severity of organs damage. The heart is one of the several organs with high sensitivity to the α-Gal A deficiency. A subgroup of patients with significant residual of α-Gal A activity with primary cardiac involvement is occasionally referred to as “cardiac variant.” The cardiovascular complications are most frequently encountered, contributing substantially to morbidity, and are the leading cause of premature death in male and female patients with FD. The deposition of Lyso-Gb-3 and Gb-3 within the myocardium affects cardiac function with resultant progressive cardiovascular pathology. Gb-3 and Lyso-Gb-3 accumulation at the cellular level trigger a cascade of events leading to end-stage fibrosis. In the cardiac tissue, Lyso-Gb-3 deposition is associated with the increased release of inflammatory factors and transforming growth factors. Infiltration of lymphocytes and macrophages into endomyocardial tissue indicates that inflammation plays a significant role in cardiac damage. Moreover, accumulated data suggest that chronic inflammation leads to multisystemic FD pathology even under enzyme replacement therapy (ERT). NF-κB activation plays a subsequent role in the inflammatory response to cardiac dysfunction and advanced heart failure in the general population. TNFalpha/NF-κB signaling protects the myocardial evoking by ischemic preconditioning; however, this protective effect depends on the concentration of TNF-α. Thus, we hypothesize that TNF-α is a critical factor in determining the grade of cardio-pathology. Cardiac hypertrophy corresponds to the expansion of the coronary vasculature to maintain a sufficient supply of nutrients and oxygen. Coronary activation of angiogenesis and fibrosis plays a vital role in cardiac vascularization, hypertrophy, and tissue remodeling. We suggest that the interaction between the inflammatory pathways and cardiac vascularization is a bi-directional process controlled by secreted cytokines and growth factors. The co-coordination of these two processes has never been explored in FD. In a cohort of 40 patients with FD, biomarkers associated with inflammation and cardio hypertrophic remodeling were studied. FD patients were categorized into three groups based on LVmass/DSA, LVEF, and ECG abnormalities: FD with no cardio complication, FD with moderate cardio complication, and severe cardio complication. Serum levels of NF-kB, TNFalpha, Il-6, Il-2, MCP1, ING-gamma, VEGF, IGF-1, TGFβ, and FGF2 were quantified by enzyme-linked immunosorbent assays (ELISA). Among the biomarkers, MCP-1, INF-gamma, VEGF, TNF-alpha, and TGF-beta were elevated in FD patients. Some of these biomarkers also have the potential to correlate with cardio pathology in FD. Conclusion: The study provides information about the role of inflammatory pathways and biomarkers of cardio hypertrophic remodeling in FD patients. This study will also reveal the mechanisms that link intracellular accumulation of Lyso-GB-3 and Gb3 to the development of cardiomyopathy with myocardial thickening and resultant fibrosis.

Keywords: biomarkers, Fabry disease, inflammation, growth factors

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Marzieh Nojomi, Azadeh Mottaghi, Arghavan Haj-Sheykholeslami, Narjes Khalili, Arash Tehrani Banihashemi

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Background and objectives: Domestic violence is a global problem with severe consequences throughout the life of the victims. Iran’s Ministry of Health has launched an intimate partner violence (IPV) prevention program, integrated in the primary health care services since 2016. The present study is a part of this national program’s evaluation. In this section, we aimed to examine spousal abuse victims’ knowledge and attitude towards domestic violence before and after receivingthese services. Methods: To assess the knowledge and attitudes of victims, a questionnaire designed by Ahmadzadand colleagues in 2013 was used. This questionnaire includes 15 questions regarding knowledge in the fields of definition, epidemiology, and effects on children, outcomes, and prevention of domestic violence. To assess the attitudes, this questionnaire has 10 questions regarding the attitudes toward the causes, effects, and legal or protective support services of domestic violence. To assess the satisfaction and the effect of the program on prevention or reduction of spousal violence episodes, two more questions were also added. Since domestic violence prevalence differs in different parts of the country, we chose nine areas with the highest, the lowest, and moderate prevalence of IPVfor the study. The link to final electronic version of the questionnaire was sent to the randomly selected public rural or urban health centers in the nine chosen areas. Since the study had to be completed in one month, we used newly identified victims as pre-intervention group and people who had at least received one related service from the program (like psychiatric consultation, education about safety measures, supporting organizations and etc.) during the previous year, as our post- intervention group. Results: A hundred and ninety-two newly identified IPV victims and 267 victims who had at least received one related program service during the previous year entered the study. All of the victims were female. Basic characteristics of the two groups, including age, education, occupation, addiction, spouses’ age, spouses’ addiction, duration of the current marriage, and number of children, were not statistically different. In knowledge questions, post- intervention group had statistically better scores in the fields of domestic violence outcomes and its effects on children; however, in the remaining areas, the scores of both groups were similar. The only significant difference in the attitude across the two groups was in the field of legal or protective support services. From the 267 women who had ever received a service from the program, 91.8% were satisfied with the services, and 74% reported a decrease in the number of violent episodes. Conclusion: National IPV prevention program integrated in the primary health care services in Iran is effective in improving the knowledge of victims about domestic violence outcomes and its effects on children. Improving the attitude and knowledge of domestic violence victims about its causes and preventive measures needs more effective interventions. This program can reduce the number of IPV episodes between the spouses, and satisfaction among the service users is high.

Keywords: intimate partner violence, assessment, health services, efficacy

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Authors: Manasi Mahanty

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In the current phase of globalization, the mobility of capital facilitates outsourcing and subcontracting of production processes to the developing economies for cheap and flexible labour force. In such process, the globalization of production networks operates at multi-locational points within the nation. Under the new quota regime in the globalization period, the Indian manufacturing exporters came under the influence of corporate buyers and large retailers from the importing countries. As part of such process, the garment manufacturing sector is expected to create huge employment opportunities and to expand the export market in the country. While following these, expectations, the apparel and garment industries mostly target to hire female migrant workers with a purpose of establishing more flexible industrial relations through the casual nature of employment contract. It leads to an increasing women’s participation in the labour market as well as the rise in precarious forms of female paid employment. In the context, the main objective of the paper is to understand the wider dynamics of globalization of production and its link with informalization, feminization of labour force and internal migration process of the country. For this purpose, the study examines the changing labour relations in the KINFRA Apparel Park at Kerala’s Special Economic Zone which operates under the scheme ‘Apparel Parks for Export’ (APE) of the Government of India. The present study was based on both quantitative and qualitative analysis. In the first, the secondary sources of data were collected from the source location (SEAM centre) and destination (KINFRA Park). The official figures and data were discussed and analyzed in order to find out the various dimensions of labour relations under globalization of production. In the second, the primary survey was conducted to make a comparative analysis of local and migrant female workers. The study is executed by taking 100 workers in total. The local workers comprised of 53% of the sample whereas the outside state workers were 47%. Even personal interviews with management staff, and workers were also made for collecting the information regarding the organisational structure, nature, and mode of recruitment, work environment, etc. The study shows the enormous presence of rural women migrant workers in KINFRA Apparel Park. A Public Private Partnership (PPP) arranged migration system is found as Skills for Employment in Apparel Manufacturing (SEAM) from where young women and girls are being sent to work in garment factories of Kerala’s KINFRA International Apparel Park under the guise of an apprenticeship based recruitment. The study concludes that such arrangements try to avoid standard employment relationships and strengthen informalization, casualization and contractualization of work. In this process, the recruitment of women migrant workers is to be considered as best option for the employers of private industries which could be more easily hired and fired.

Keywords: female migration, globalization, informalization, KINFRA apparel park

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Luisa Kynast

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It is obvious that buildings and infrastructure are highly impacted by climate change (CC). Both, design and material of buildings need to be resilient to weather events in order to shelter humans, animals, or goods. As well as buildings and infrastructure are exposed to weather events, the construction process itself is generally carried out outdoors without being protected from extreme temperatures, heavy rain, or storms. The production process is restricted by technical limitations for processing materials with machines and physical limitations due to human beings (“outdoor-worker”). In future due to CC, average weather patterns are expected to change as well as extreme weather events are expected to occur more frequently and more intense and therefore have a greater impact on production processes and on the construction businesses itself. This research aims to examine this impact by analyzing an association between responses to CC and financial performance of businesses within the construction industry. After having embedded the above depicted field of research into the resource dependency theory, a literature review was conducted to expound the state of research concerning a contingent relation between climate change adaptation measures (CCAM) and corporate financial performance for construction businesses. The examined studies prove that this field is rarely investigated, especially for construction businesses. Therefore, reports of the Carbon Disclosure Project (CDP) were analyzed by applying content analysis using the software tool MAXQDA. 58 construction companies – located worldwide – could be examined. To proceed even more systematically a coding scheme analogous to findings in literature was adopted. Out of qualitative analysis, data was quantified and a regression analysis containing corporate financial data was conducted. The results gained stress adaptation measures as a response to CC as a crucial proxy to handle climate change impacts (CCI) by mitigating risks and exploiting opportunities. In CDP reports the majority of answers stated increasing costs/expenses as a result of implemented measures. A link to sales/revenue was rarely drawn. Though, CCAM were connected to increasing sales/revenues. Nevertheless, this presumption is supported by the results of the regression analysis where a positive effect of implemented CCAM on construction businesses´ financial performance in the short-run was ascertained. These findings do refer to appropriate responses in terms of the implemented number of CCAM. Anyhow, still businesses show a reluctant attitude for implementing CCAM, which was confirmed by findings in literature as well as by findings in CDP reports. Businesses mainly associate CCAM with costs and expenses rather than with an effect on their corporate financial performance. Mostly companies underrate the effect of CCI and overrate the costs and expenditures for the implementation of CCAM and completely neglect the pay-off. Therefore, this research shall create a basis for bringing CC to the (financial) attention of corporate decision-makers, especially within the construction industry.

Keywords: climate change adaptation measures, construction businesses, financial implication, resource dependency theory

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Authors: Nino Kobakhidze, Endi Varsimashvili, Davit Makadze

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The Caucasus is a link of the Alpine-Himalayan fold belt and involves the Greater Caucasus and the Lesser Caucasus fold systems and the Intermountain area. The study object is located within the northernmost part of the Lesser Caucasus orogen, in the eastern part of Achara-Trialeti fold -thrust belt. This area was rather well surveyed in 70th of the twentieth century in terms of oil-and-gas potential, but to our best knowledge, detailed sedimentological studies have not been conducted so far. In order to fill this gap, the authors of the present thesis started research in this direction. One of the objects selected for the research was the deposits of the Kavtura river valley situated on the northern slope of the Trialeti ridge. Paleocene-Lower Eocene deposits known in scientific literature as ‘Borjomi Flysch’ (Turbidites) are exposed in the mentioned area. During the research, the following methodologies were applied: selection of key cross sections, a collection of rock samples, microscopic description of thin sections, mineralogical and petrological analysis of material and identification of trace fossils. The study of Paleocene-Lower Eocene deposits starts with Kavtura river valley in the east, where they are well characterized by microfauna. The cross-section of the deposits starts with Danian variegated marlstone conformably overlain by the alternation of thick and thin-bedded sandstones (thickness 40-50 cm). They are continued with interbedded of thin-bedded sandstones and shales(thickness 4-5 m). On the sole surface of sandstones ichnogenera ‘Helmintopsis’ and ‘Scolicia’ are recorded and within the bed –‘Chondrites’ is found. Towards the Riverhead, there is a 1-2 m gap in sedimentation; then again the Paleocene-Lower Eocene sediments crop out. They starting with alternation of grey-green medium-grained sandstones and shales enclosing dark color plant detritus. They are overlain by the interbedded of calcareous sandstones and marls, where the thickness of sandstones is variable (20-70 cm). Ichnogenus – ‘Scolicia’ is found here. Upwards the above-mentioned deposits pass into Middle Eocenian volcanogenic-sedimentary suits. In the Kavtura river valley, the thickness of the Paleocene-Lower Eocene deposits is 300-400 m. In the process of research, the following activities are conducted: the facial analysis of host rocks, correlation of the study section with other cross sections and interpretation of depositional environment of the area. In the area the authors have found and described ichnogenera; their preliminary determination have shown that they belong to pre-depositional (‘Helmintopsis’) and post-depositional (‘Chondrites’) forms. As known, during the Cretaceous-Paleogene time, the Achara-Trialeti fold-thrust belt extensional basin was the accumulation area with great thicknesses (from shallow to deep marine sediments). It is confirmed once more by the authors investigations preliminary results of paleoichnological studies inclusive.

Keywords: flysh deposits, lithology, The Lesser Caucasus, trace fossils

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Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

Procedia PDF Downloads 200

Authors: Nejmeddine Ouhichi, Fethi Lachaal, Radhouane Hamdi, Olivier Grunberger

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Located in Cap Bon peninsula (Tunisia), the Lebna dam was built in 1987 to balance local water salt intrusion taking place in the coastal aquifer of Korba. The first intention was to reduce coastal groundwater over-pumping by supplying surface water to a large irrigation system. The unpredicted beneficial effect was recorded with the occurrence of a direct localized recharge to the coastal aquifer by leakage through the geological material of the southern bank of the lake. The hydrological balance of the reservoir dam gave an estimation of the annual leakage volume, but dynamic processes and sound quantification of recharge inputs are still required to understand the localized effect of the recharge in terms of piezometry and quality. Present work focused on simulating the recharge process to confirm the hypothesis, and established a sound quantification of the water supply to the coastal aquifer and extend it to multi-annual effects. A spatial frame of 30km² was used for modeling. Intensive outcrops and geophysical surveys based on 68 electrical resistivity soundings were used to characterize the aquifer 3D geometry and the limit of the Plio-quaternary geological material concerned by the underground flow paths. Permeabilities were determined using 17 pumping tests on wells and piezometers. Six seasonal piezometric surveys on 71 wells around southern reservoir dam banks were performed during the 2019-2021 period. Eight monitoring boreholes of high frequency (15min) piezometric data were used to examine dynamical aspects. Model boundary conditions were specified using the geophysics interpretations coupled with the piezometric maps. The dam-groundwater flow model was performed using Visual MODFLOW software. Firstly, permanent state calibration based on the first piezometric map of February 2019 was established to estimate the permanent flow related to the different reservoir levels. Secondly, piezometric data for the 2019-2021 period were used for transient state calibration and to confirm the robustness of the model. Preliminary results confirmed the temporal link between the reservoir level and the localized recharge flow with a strong threshold effect for levels below 16 m.a.s.l. The good agreement of computed flow through recharge cells on the southern banks and hydrological budget of the reservoir open the path to future simulation scenarios of the dilution plume imposed by the localized recharge. The dam reservoir-groundwater flow-model simulation results approve a potential for storage of up to 17mm/year in existing wells, under gravity-feed conditions during level increases on the reservoir into the three years of operation. The Lebna dam groundwater flow model characterized a spatiotemporal relation between groundwater and surface water.

Keywords: leakage, MODFLOW, saltwater intrusion, surface water-groundwater interaction

Procedia PDF Downloads 137

Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

Procedia PDF Downloads 59

Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

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Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

Procedia PDF Downloads 286

Authors: Eliane Abdo, Olivier Colot

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SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

Procedia PDF Downloads 108

Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

Procedia PDF Downloads 487

Authors: N. C. van der Merwe, J. Oosthuizen, M. F. Makhetha, J. Adams, B. K. Dajee, S-R. Schneider

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Women representing high-risk breast cancer families, who tested negative for pathogenic mutations in BRCA1 and BRCA2, are four times more likely to develop breast cancer compared to women in the general population. Sequencing of genes involved in genomic stability and DNA repair led to the identification of novel contributors to familial breast cancer risk. These include BLM and PALB2. Bloom's syndrome is a rare homozygous autosomal recessive chromosomal instability disorder with a high incidence of various types of neoplasia and is associated with breast cancer when in a heterozygous state. PALB2, on the other hand, binds to BRCA2 and together, they partake actively in DNA damage repair. Archived DNA samples of 66 BRCA1/2 negative high-risk breast cancer patients were retrospectively selected based on the presence of an extensive family history of the disease ( > 3 affecteds per family). All coding regions and splice-site boundaries of both genes were screened using High-Resolution Melting Analysis. Samples exhibiting variation were bi-directionally automated Sanger sequenced. The clinical significance of each variant was assessed using various in silico and splice site prediction algorithms. Comprehensive screening identified a total of 11 BLM and 26 PALB2 variants. The variants detected ranged from global to rare and included three novel mutations. Three BLM and two PALB2 likely pathogenic mutations were identified that could account for the disease in these extensive breast cancer families in the absence of BRCA mutations (BLM c.11T > A, p.V4D; BLM c.2603C > T, p.P868L; BLM c.3961G > A, p.V1321I; PALB2 c.421C > T, p.Gln141Ter; PALB2 c.508A > T, p.Arg170Ter). Conclusion: The study confirmed the contribution of pathogenic mutations in BLM and PALB2 to the familial breast cancer burden in South Africa. It explained the presence of the disease in 7.5% of the BRCA1/2 negative families with an extensive family history of breast cancer. Segregation analysis will be performed to confirm the clinical impact of these mutations for each of these families. These results justify the inclusion of both these genes in a comprehensive breast and ovarian next generation sequencing cancer panel and should be screened simultaneously with BRCA1 and BRCA2 as it might explain a significant percentage of familial breast and ovarian cancer in South Africa.

Keywords: Bloom Syndrome, familial breast cancer, PALB2, South Africa

Procedia PDF Downloads 232

Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

Procedia PDF Downloads 161

Authors: Cristina Chaminade, Mandar Kulkarni, Balaji Parthasarathy, Monica Plechero

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The characteristics of a regional innovation system (RIS) and the specificity of the knowledge base of an industry may contribute to create peculiar paths for innovation and development of firms’ geographic extended innovation networks. However, the relative empirical evidence in emerging economies remains underexplored. The paper aims to fill the research gap by means of some recent qualitative research conducted in 2016 in Beijing (China) and Bangalore (India). It analyzes cases studies of firms in the new media industry, a sector that merges different IT competences with competences from other knowledge domains and that is emerging in those RIS. The results show that while in Beijing the new media sector results to be more in line with the existing institutional setting and governmental goals aimed at targeting specific social aspects and social problems of the population, in Bangalore it remains a more spontaneous firms-led process. In Beijing what matters for the development of innovation networks is the governmental setting and the national and regional strategies to promote science and technology in this sector, internet and mass innovation. The peculiarities of recent governmental policies aligned to the domestic goals may provide good possibilities for start-ups to develop innovation networks. However, due to the specificities of those policies targeting the Chinese market, networking outside the domestic market are not so promoted. Moreover, while some institutional peculiarities, such as a culture of collaboration in the region, may be favorable for local networking, regulations related to Internet censorship may limit the use of global networks particularly when based on virtual spaces. Mainly firms with already some foreign experiences and contact take advantage of global networks. In Bangalore, the role of government in pushing networking for the new media industry at the present stage is quite absent at all geographical levels. Indeed there is no particular strategic planning or prioritizing in the region toward the new media industry, albeit one industrial organization has emerged to represent the animation industry interests. This results in a lack of initiatives for sustaining the integration of complementary knowledge into the local portfolio of IT specialization. Firms actually involved in the new media industry face institutional constrains related to a poor level of local trust and cooperation, something that does not allow for full exploitation of local linkages. Moreover, knowledge-provider organizations in Bangalore remain still a solid base for the IT domain, but not for other domains. Initiatives to link to international networks seem therefore more the result of individual entrepreneurial actions aimed at acquiring complementary knowledge and competencies from different domains and exploiting potentiality in different markets. From those cases, it emerges that role of government, soft institutions and organizations in the two RIS differ substantially in the creation of barriers and opportunities for the development of innovation networks and their specific aim.

Keywords: regional innovation system, emerging economies, innovation network, institutions, organizations, Bangalore, Beijing

Procedia PDF Downloads 320

Authors: Jose CanIzares

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In the last decades, resilience has received much attention in relation to understanding and managing new forms of risk, especially in the context of urban adaptation to climate change. There are abundant concerns, however, on how to best interpret resilience and related ideas, and on whether they can guide ethically appropriate risk-related or adaptation efforts. Narrative creation and framing are critical steps in shaping public discussion and policy in large-scale interventions, since they favor or inhibit early decision and interpretation habits, which can be morally sensitive and then become persistent on time. This article adds to such framing process by contesting a conventional narrative on resilience and offering an alternative one. Conventionally, present ideas on resilience are traced to the work of ecologist C. S. Holling, especially to his article Resilience and Stability in Ecosystems. This article is usually portrayed as a contribution of complex systems thinking to theoretical ecology, where Holling appeals to resilience in order to challenge received views on ecosystem stability and the diversity-stability hypothesis. In this regard, resilience is construed as a “purely scientific”, precise and descriptive concept, denoting a complex property that allows ecosystems to persist, or to maintain functions, after disturbance. Yet, these formal features of resilience supposedly changed with Holling’s later work in the 90s, where, it is argued, Holling begun to use resilience as a more pragmatic “boundary term”, aimed at unifying transdisciplinary research about risks, ecological or otherwise, and at articulating public debate and governance strategies on the issue. In the conventional story, increased vagueness and degrees of normativity are the price to pay for this conceptual shift, which has made the term more widely usable, but also incompatible with scientific purposes and morally problematic (if not completely objectionable). This paper builds on a detailed analysis of Holling’s early work to propose an alternative narrative. The study will show that the “complexity turn” has often entangled theoretical and pragmatic aims. Accordingly, Holling’s primary aim was to fight what he termed “pathologies of natural resource management” or “pathologies of command and control management”, and so, the terms of his reform of ecosystem science are partly subordinate to the details of his proposal for reforming the management sciences. As regards resilience, Holling used it as a polysemous, ambiguous and normative term: sometimes, as an instrumental value that is closely related to various stability concepts; other times, and more crucially, as an intrinsic value and a tool for attacking efficiency and instrumentalism in management. This narrative reveals the limitations of its conventional alternative and has several practical advantages. It captures well the structure and purposes of Holling’s project, and the various roles of resilience in it. It helps to link Holling’s early work with other philosophical and ideological shifts at work in the 70s. It highlights the currency of Holling’s early work for present research and action in fields such as risk and climate adaptation. And it draws attention to morally relevant aspects of resilience that the conventional narrative neglects.

Keywords: resilience, complexity turn, risk management, positivistic, framing

Procedia PDF Downloads 163

Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

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The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

Procedia PDF Downloads 149

Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 148

Authors: Johnas Buhori, Meinrad Haule Lembuka

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Introduction: Social work expands its boundary to accommodate indigenous knowledge and practice for better competence and services. In Tanzania, Mama Mkubwa Mkubwa (MMM) (Mother’s elder sister) is an indigenous practice of alternative child care that represents other traditional practices across African societies known as Ubuntu practice. Ubuntu is African Humanism with values and approaches that are connected to the social work. MMM focuses on using the elder sister of a deceased mother or father, a trusted elder woman from the extended family or indigenous community to provide alternative care to an orphan or vulnerable child. In Ubuntu's perspective, it takes a whole village or community to raise a child, meaning that every person in the community is responsible for child care. Methodology: A desk review method guided by Ubuntu theory was applied to enrich the study. Findings: MMM resembles the Ubuntu ideal of traditional child protection of those in need as part of alternative child care throughout Tanzanian history. Social work practice, along with other formal alternative child care, was introduced in Tanzania during the colonial era in 1940s and socio-economic problems of 1980s affected the country’s formal social welfare system, and suddenly HIV/AIDS pandemic triggered the vulnerability of children and hampered the capacity of the formal sector to provide social welfare services, including alternative child care. For decades, AIDS has contributed to an influx of orphans and vulnerable children that facilitated the re-emerging of traditional alternative child care at the community level, including MMM. MMM strongly practiced in regions where the AIDS pandemic affected the community, like Njombe, Coastal region, Kagera, etc. Despite of existing challenges, MMM remained to be the remarkably alternative child care practiced in both rural and urban communities integrated with social welfare services. Tanzania envisions a traditional mechanism of family or community environment for alternative child care with the notion that sometimes institutionalization care fails to offer children all they need to become productive members of society, and later, it becomes difficult to reconnect in the society. Implications to Social Work: MMM is compatible with social work by using strengths perspectives; MMM reflects Ubuntu's perspective on the ground of humane social work, using humane methods to achieve human goals. MMM further demonstrates the connectedness of those who care and those cared for and the inextricable link between them as Ubuntu-inspired models of social work that view children from family, community, environmental, and spiritual perspectives. Conclusion: Social work and MMM are compatible at the micro and mezzo levels; thus, application of MMM can be applied in social work practice beyond Tanzania when properly designed and integrated into other systems. When MMM is applied in social work, alternative care has the potential to support not only children but also empower families and communities. Since MMM is a community-owned and voluntary base, it can relieve the government, social workers, and other formal sectors from the annual burden of cost in the provision of institutionalized alternative child care.

Keywords: ubuntu, indigenous social work, african social work, ubuntu social work, child protection, child alternative care

Procedia PDF Downloads 65

Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

Procedia PDF Downloads 203

Authors: E. Menga, S. Hernandez

Abstract:

Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

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Authors: Markus Rütten, Olaf Wünsch

Abstract:

Non-Newtonian fluid properties can change the flow behaviour significantly, its prediction is more difficult when thermal effects come into play. Hence, the focal point of this work is the wake flow behind a heated circular cylinder in the laminar vortex shedding regime for thermo-viscous shear thinning fluids. In the case of isothermal flows of Newtonian fluids the vortex shedding regime is characterised by a distinct Reynolds number and an associated Strouhal number. In the case of thermo-viscous shear thinning fluids the flow regime can significantly change in dependence of the temperature of the viscous wall of the cylinder. The Reynolds number alters locally and, consequentially, the Strouhal number globally. In the present CFD study the temperature dependence of the Reynolds and Strouhal number is investigated for the flow of a Carreau fluid around a heated cylinder. The temperature dependence of the fluid viscosity has been modelled by applying the standard Williams-Landel-Ferry (WLF) equation. In the present simulation campaign thermal boundary conditions have been varied over a wide range in order to derive a relation between dimensionless heat transfer, Reynolds and Strouhal number. Together with the shear thinning due to the high shear rates close to the cylinder wall this leads to a significant decrease of viscosity of three orders of magnitude in the nearfield of the cylinder and a reduction of two orders of magnitude in the wake field. Yet the shear thinning effect is able to change the flow topology: a complex K´arm´an vortex street occurs, also revealing distinct characteristic frequencies associated with the dominant and sub-dominant vortices. Heating up the cylinder wall leads to a delayed flow separation and narrower wake flow, giving lesser space for the sequence of counter-rotating vortices. This spatial limitation does not only reduce the amplitude of the oscillating wake flow it also shifts the dominant frequency to higher frequencies, furthermore it damps higher harmonics. Eventually the locally heated wake flow smears out. Eventually, the CFD simulation results of the systematically varied thermal flow parameter study have been used to describe a relation for the main characteristic order parameters.

Keywords: heat transfer, thermo-viscous fluids, shear thinning, vortex shedding

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

Abstract:

Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

Procedia PDF Downloads 126