Search results for: natural language grammar models

Authors: Magda Gorczyca, Zofia Nocoń

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Past and current studies from different countries showed that river engineering leads to environmental degradation and extinction of many species - often those protected by local and international wildlife conservation laws. Through the years, the main focus of rivers utilization has shifted from industrial applications to recreation and wildlife preservation with a focus on keeping the biodiversity which plays a significant role in preventing climate changes. Thus an opportunity appeared to recreate flooding areas and natural habitats, which are very rare in the scale of Europe. Additionally, river restoration helps to avoid floodings and periodic droughts, which are usually very damaging to the economy. In this research, the biodiversity of dragonflies and ground beetles was analyzed in the context of plant communities and forest stands structure. Results were enriched with data from past and current literature. A comparison was made between two parts of the Odra river. A part where oxbow lake and riparian forest were separated from the river bed by embankment and a part of the river with floodplains left intact. Validity assessment of embankments relocation was made based on the research results. In the period between May and September, insects were collected, phytosociological analysis were taken, and forest stand structure properties were specified. In the part of the river not separated by the embankments, rare and protected species of plants were spotted (e.g., Trapanatans, Salvinianatans) as well as greater species and quantitive diversity of dragonfly. Ground beetles fauna, though, was richer in the area separated by the embankment. Even though the research was done during only one season and in a limited area, the results can be a starting point for further extended research and may contribute to acquiring legal wildlife protection and restoration of the researched area. During the research, the presence of invasive species Impatiens parviflora, Echinocystislobata, and Procyonlotor were observed, which may lead to loss of the natural values of the researched areas.

Keywords: carabidae, floodplains, middle Odra river, Odonata, oxbow lakes, riparian forests

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Authors: Joshua Kim Schimpf, Kyun Doo Kim, Jaseok Heo

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In this study, the droplet behavior of under horizontal stratified flow regime for air and water flow in horizontal pipe experiments from a 0.24 m, 0.095 m, and 0.0486 m size diameter pipe are examined. The effects of gravity, pipe diameter, and turbulent diffusion on droplet deposition are considered. Models for droplet entrainment and deposition are proposed that considers developing length. Validation for experimental data dedicated from the REGARD, CEA and Williams, University of Illinois, experiment were performed using SPACE (Safety and Performance Analysis Code for Nuclear Power Plants).

Keywords: droplet, entrainment, deposition, horizontal

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Abdulatif Abdulsalam, Mohamed Shaban

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This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

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Authors: F. Boukli Hacene, W. Soufi, S. Ghalem

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Glaucoma disease is a progressive degenerative optic neuropathy, with irreversible visual field deficits and high eye pressure being one of the risk factors. Sulfonamides are carbonic anhydrase-II inhibitors that aim to decrease the secretion of aqueous humor by direct inhibition of this enzyme at the level of the ciliary processes. These drugs present undesirable effects that are difficult to accept by the patient. In our study, we are interested in the inhibition of carbonic anhydrase-II by different natural ligands (curcumin analogues) using molecular modeling methods using molecular operating environment (MOE) software to predict their interaction with this enzyme.

Keywords: carbonic anhydrase-II, curcumin analogues, drug research, molecular modeling

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Authors: Rizwan Ahmed Bhutto, Noor ul ain Hira Bhutto, Mingwei Wang, Shahid Iqbal, Jiang Yi

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Curcumin, a natural polyphenolic compound, boasts numerous health benefits; however, its industrial applications are hindered by instabilities and poor solubility. Encapsulating curcumin in Pickering emulsion presents a promising strategy to enhance its bioavailability. Yet, the development of an efficient and straightforward method to fabricate a natural emulsifier for Pickering emulsion poses a significant challenge. Chitosan has garnered attention due to its non-toxicity and excellent emulsifying properties. This study aimed to prepare four distinct types of self-aggregated chitosan particles using a pH-responsive self-assembling approach. The properties of the aggregated particles were adjusted by pH, degree of deacetylation (DDA), and molecular weight (MW), thereby controlling surface charge, size (ranging from nano to micro and floc), and contact angle. Pickering emulsions were then formulated using these various aggregated particles. As MW and pH increased and DDA decreased, the networked structures of the aggregated particles formed, resulting in highly elastic gels that were more resistant to the breakdown of Pickering emulsion at ambient temperature. With elevated temperatures, the kinetic energy of the aggregated particles increased, disrupting hydrogen bonds and potentially transforming the systems from fluids to gels. The Pickering emulsion based on aggregated particles served as a carrier for curcumin encapsulation. It was observed that DDA and MW played crucial roles in regulating drug loading, encapsulation efficiency, and release profile. This research sheds light on selecting suitable chitosan for controlling the release of bioactive compounds in Pickering emulsions, considering factors such as adjustable rheological properties, microstructure, and macrostructure. Furthermore, this study introduces an environmentally friendly and cost-effective synthesis of pH-responsive aggregate particles without the need for high-pressure homogenizers. It underscores the potential of aggregate particles with various MWs and DDAs for encapsulating other bioactive compounds, offering valuable applications in industries including food, flavor/fragrance, cosmetics, and medicine.

Keywords: chitosan, molecular weight, rheological properties, curcumin encapsulation

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Robert John Godby

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To be responsive now and in the future, workplaces must address the demands of multicultural teams as they become more common elements of the global labor force. This is especially the case for aged care due to the aging population, industry growth and migrant recruitment. This research identifies influences on and improvements for learning in these environments. Its unique contribution is to illuminate how culturally diverse workplaces can work and learn together more effectively. A mixed-methods approach was used to gather data about this topic in two phases. Firstly, the research methods included a survey of 102 aged care workers around Australia from two multi-site aged care organisations. The questionnaire elicited both quantitative and qualitative data about worker characteristics and perspectives on working and learning in aged care. Secondly, a case study of one aged care worksite was formulated drawing on worksite information and interviews with workers. A review of the literature suggests that learning in multicultural work environments is influenced by three main factors: 1) the individual workers themselves, 2) their interaction with each other and 3) the environment in which they work. There are various accounts of these three factors, how they are manifested and how they lead to a change in workers’ disposition, knowledge, or expertise when confronted with new circumstances. The study has found that a key individual factor influencing learning is cultural background. Their unique view of the world was shown to affect their approach to both their work and co-working. Interactional factors suggest that the high requirement for collaboration in aged care positively supports learning in this context; however, it can be hindered by cultural bias and spoken accent. The study also found that environmental factors, such as disruptions caused by the pandemic, were another key influence. For example, the need to wear face masks hindered the communication needed for workplace learning. This was especially challenging due to the diverse language backgrounds and abilities within the teams. Potential improvements for learning in multicultural aged care work environments were identified. These include more frequent and structured inter-peer learning (e.g. buddying), communication training (e.g. English language usage for both native and non-native speaking workers) and support for cross-cultural habitude (e.g. recognizing and adapting to cultural differences). Workplace learning in cross-cultural aged care environments is an area that is not extensively dealt with in the literature. This study addresses this gap and holds the potential to contribute practical insights to aged care and other diverse industries.

Keywords: cross-cultural learning, learning in aged care, migrant learning, workplace learning

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Authors: Zahirah Dhurmeea, Iker Zudaire, Heidi Pethybridge, Emmanuel Chassot, Maria Cedras, Natacha Nikolic, Jerome Bourjea, Wendy West, Chandani Appadoo, Nathalie Bodin

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Scientific advice on the status of fish stocks relies on indicators that are based on strong assumptions on biological parameters such as condition, maturity and fecundity. Currently, information on the biology of albacore tuna, Thunnus alalunga, in the Indian Ocean is scarce. Consequently, many parameters used in stock assessment models for Indian Ocean albacore originate largely from other studied stocks or species of tuna. Inclusion of incorrect biological data in stock assessment models would lead to inappropriate estimates of stock status used by fisheries manager’s to establish future catch allowances. The reproductive biology of albacore tuna in the western Indian Ocean was examined through analysis of the sex ratio, spawning season, length-at-maturity (L50), spawning frequency, fecundity and fish condition. In addition, the total lipid content (TL) and lipid class composition in the gonads, liver and muscle tissues of female albacore during the reproductive cycle was investigated. A total of 923 female and 867 male albacore were sampled from 2013 to 2015. A bias in sex-ratio was found in favour of females with fork length (LF) <100 cm. Using histological analyses and gonadosomatic index, spawning was found to occur between 10°S and 30°S, mainly to the east of Madagascar from October to January. Large females contributed more to reproduction through their longer spawning period compared to small individuals. The L50 (mean ± standard error) of female albacore was estimated at 85.3 ± 0.7 cm LF at the vitellogenic 3 oocyte stage maturity threshold. Albacore spawn on average every 2.2 days within the spawning region and spawning months from November to January. Batch fecundity varied between 0.26 and 2.09 million eggs and the relative batch fecundity (mean  standard deviation) was estimated at 53.4 ± 23.2 oocytes g-1 of somatic-gutted weight. Depending on the maturity stage, TL in ovaries ranged from 7.5 to 577.8 mg g-1 of wet weight (ww) with different proportions of phospholipids (PL), wax esters (WE), triacylglycerol (TAG) and sterol (ST). The highest TL were observed in immature (mostly TAG and PL) and spawning capable ovaries (mostly PL, WE and TAG). Liver TL varied from 21.1 to 294.8 mg g-1 (ww) and acted as an energy (mainly TAG and PL) storage prior to reproduction when the lowest TL was observed. Muscle TL varied from 2.0 to 71.7 g-1 (ww) in mature females without a clear pattern between maturity stages, although higher values of up to 117.3 g-1 (ww) was found in immature females. TL results suggest that albacore could be viewed predominantly as a capital breeder relying mostly on lipids stored before the onset of reproduction and with little additional energy derived from feeding. This study is the first one to provide new information on the reproductive development and classification of albacore in the western Indian Ocean. The reproductive parameters will reduce uncertainty in current stock assessment models which will eventually promote sustainability of the fishery.

Keywords: condition, size-at-maturity, spawning behaviour, temperate tuna, total lipid content

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Authors: Yenisleidy Martinez Martinez, Yannay Casas-Ledon, Jo Dewulf

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The ecosystem services (ES) concept has contributed to draw attention to the benefits ecosystems generate for people and how necessary natural resources are for human well-being. The identification and prioritization of the ES constitute the first steps to undertake conservation and valuation initiatives on behalf of people. Additionally, mapping the supply of ES is a powerful tool to support decision making regarding the sustainable management of landscape and natural resources. In this context, the present study aimed to identify, prioritize and map the primary ES in Biobio and Nuble regions using a methodology that combines expert judgment, multi-attribute evaluation methods, and Geographic Information Systems (GIS). Firstly, scores about the capacity of different land use/cover types to supply ES and the importance attributed to each service were obtained from experts and stakeholders via an online survey. Afterward, the ES assessment matrix was constructed, and the weighted linear combination (WLC) method was applied to mapping the overall capacity of supply of provisioning, regulating and maintenance, and cultural services. Finally, prioritized ES for the study area were selected and mapped. The results suggest that native forests, wetlands, and water bodies have the highest supply capacities of ES, while urban and industrial areas and bare areas have a very low supply of services. On the other hand, fourteen out of twenty-nine services were selected by experts and stakeholders as the most relevant for the regions. The spatial distribution of ES has shown that the Andean Range and part of the Coastal Range have the highest ES supply capacity, mostly regulation and maintenance and cultural ES. This performance is related to the presence of native forests, water bodies, and wetlands in those zones. This study provides specific information about the most relevant ES in Biobio and Nuble according to the opinion of local stakeholders and the spatial identification of areas with a high capacity to provide services. These findings could be helpful as a reference by planners and policymakers to develop landscape management strategies oriented to preserve the supply of services in both regions.

Keywords: ecosystem services, expert judgment, mapping, multi-criteria decision making, prioritization

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: Binay Pattanayak

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Multilingual state, Jharkhand is home to more than 19 tribal and regional languages. These are used by more than 33 communities in the state. The state has declared 12 of these languages as official languages of the state. However, schools in the state do not recognize any of these community languages even in early grades! Children, who speak in their mother tongues at home, local market and playground, find it very difficult to understand their teacher and textbooks in school. They fail to acquire basic literacy and numeracy skills in early grades. Out of frustration due to lack of comprehension, the majority of children leave school. Jharkhand sees the highest dropout in early grades in India. To address this, the state under the guidance of the author designed a mother tongue based pre-school education programme named Bhasha Puliya and bilingual picture dictionaries in 9 tribal and regional mother tongues of children. This contributed significantly to children’s school readiness in the school. Followed by this, the state designed a mother-tongue based multilingual education programme (MTB-MLE) for multilingual context. The author guided textbook development in 5 tribal (Santhali, Mundari, Ho, Kurukh and Kharia) and two regional (Odia and Bangla) languages. Teachers and community members were trained for MTB-MLE in around 1,000 schools of the concerned language pockets. Community resource groups were constituted along with their academic calendars in each school to promote story-telling, singing, painting, dancing, riddles, etc. with community support. This, on the one hand, created rich learning environments for children. On the other hand, the communities have discovered a great potential in the process of developing a wide variety of learning materials for children in own mother-tongue using their local stories, songs, riddles, paintings, idioms, skits, etc. as a process of their literary, cultural and technical enrichment. The majority of children are acquiring strong early grade reading skills (basic literacy and numeracy) in grades I-II thereby getting well prepared for higher studies. In a phased manner they are learning Hindi and English after 4-5 years of MTB-MLE using the foundational language learning skills. Community members have started designing new books, audio-visual learning materials in their mother-tongues seeing a great potential for their cultural and technological rejuvenation.

Keywords: community resource groups, MTB-MLE, multilingual, socio-linguistic survey, learning

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Authors: M. Salih Taci, N. Tayebi, I. Bozkır

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This paper investigates the operation of a sinusoidal supplied autotransformer on the different states of magnetic polarity of primary and secondary terminals for four different step-up and step-down analytical conditions. In this paper, a new analytical modeling and equations for dot-marked and polarity-based step-up and step-down autotransformer are presented. These models are validated by the simulation of current and voltage waveforms for each state. PSpice environment was used for simulation.

Keywords: autotransformer modeling, autotransformer simulation, step-up autotransformer, step-down autotransformer, polarity

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Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Madan Chandra Maurya, A. R. Dar

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Among the entire natural calamities earthquake is the one which is most devastating. If the losses due to all other calamities are added still it will be very less than the losses due to earthquakes. So it means we must be ready to face such a situation, which is only possible if we make our structures earthquake resistant. A review of structural damages to the braced frame systems after several major earthquakes—including recent earthquakes—has identified some anticipated and unanticipated damage. This damage has prompted many engineers and researchers around the world to consider new approaches to improve the behavior of braced frame systems. Extensive experimental studies over the last fourty years of conventional buckling brace components and several braced frame specimens have been briefly reviewed, highlighting that the number of studies on the full-scale concentric braced frames is still limited. So for this reason the study surrounds the words plastic behavior, steel structure, brace frame system. In this study, there are two different analytical approaches which have been used to predict the behavior and strength of an un-braced frame. The first is referred as incremental elasto-plastic analysis a plastic approach. This method gives a complete load-deflection history of the structure until collapse. It is based on the plastic hinge concept for fully plastic cross sections in a structure under increasing proportional loading. In this, the incremental elasto-plastic analysis- hinge by hinge method is used in this study because of its simplicity to know the complete load- deformation history of two storey un-braced scaled model. After that the experiments were conducted on two storey scaled building model with and without bracing system to know the true or experimental load deformation curve of scaled model. Only way, is to understand and analyze these techniques and adopt these techniques in our structures. The study named as Plastic Behavior of Steel Frames using Different Concentric Bracing Configurations deals with all this. This study aimed at improving the already practiced traditional systems and to check the behavior and its usefulness with respect to X-braced system as reference model i.e. is how plastically it is different from X-braced. Laboratory tests involved determination of plastic behavior of these models (with and without brace) in terms of load-deformation curve. Thus, the aim of this study is to improve the lateral displacement resistance capacity by using new configuration of brace member in concentric manner which is different from conventional concentric brace. Once the experimental and manual results (using plastic approach) compared, simultaneously the results from both approach were also compared with nonlinear static analysis (pushover analysis) approach using ETABS i.e how both the previous results closely depicts the behavior in pushover curve and upto what limit. Tests results shows that all the three approaches behaves somewhat in similar manner upto yield point and also the applicability of elasto-plastic analysis (hinge by hinge method) to know the plastic behavior. Finally the outcome from three approaches shows that the newer one configuration which is chosen for study behaves in-between the plane frame (without brace or reference frame) and the conventional X-brace frame.

Keywords: elasto-plastic analysis, concentric steel braced frame, pushover analysis, ETABS

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Authors: Ardalan Sabamehr, Ashutosh Bagchi

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Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods.

Keywords: ambient vibration, frequency domain decomposition, stochastic subspace identification, continuous wavelet transform

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Authors: I. D. Arroyo

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This article seeks to integrate different concepts from contemporary software engineering with an agile development approach. We seek to clarify some definitions and uses, we make a difference between the Systems Development Life Cycle (SDLC) and the methodologies, we differentiate the types of frameworks such as methodological, philosophical and behavioral, standards and documentation. We define relationships based on the documentation of the development process through formal and ad hoc models, and we define the usefulness of using DevOps and Agile Modeling as integrative methodologies of principles and best practices.

Keywords: methodologies, modeling languages, agile modeling, UML

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Authors: Mustafa Gülen, Eylem Güzel, Soner Guler

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The studies concentrated on the historical background of Van show the fact that Van has had a significant position as a settlement since ancient times and that it has hosted many civilizations during history. With the dominance of Ottoman Empire in 16th century, the region had been re-constructed by building new walls at the southern side of Van Castle. These construction activities had mostly been fulfilled by the usage of adobe which had been a fundamental material for thousands of years. As a result of natural disasters, battles and the move at the threshold of 20th century to the new settlement which is 9 kilometers away from the Ancient City Van is an open-air museum with the ruins of churches, mosques and baths. In this study, the usage of adobe in historical structures of Van city is evaluated in detail.

Keywords: historical structures, adobe, Van city, adobe

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Mustafa Aydın, Ali Murat Sunbul

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Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

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Authors: Wasan Ismail Khalil, Hisham Khalid Ahmed, Zainab Ali

Abstract:

Structural Lightweight Aggregate Concrete (SLWAC) has been developed in recent years because it reduces the dead load, cost, thermal conductivity and coefficient of thermal expansion of the structure. So SLWAC has the advantage of being a relatively green building material. Lightweight Aggregate (LWA) is either occurs as natural material such as pumice, scoria, etc. or as artificial material produced from different raw materials such as expanded shale, clay, slate, etc. The use of SLWAC in Iraq is limited due to the lack in natural LWA. The existence of Iraqi clay deposit with different types and characteristics leads to the idea of producing artificial expanded clay aggregate. The main aim in this work is to present of the properties of artificial LWA produced in the laboratory. Available local bentonite clay which occurs in the Western region of Iraq was used as raw material to produce the LWA. Sodium silicate as liquid industrial waste material from glass plant was mixed with bentonite clay in mix proportion 1:1 by weight. The manufacturing method of the lightweight aggregate including, preparation and mixing of clay and sodium silicate, burning of the mixture in the furnace at the temperature between 750-800˚C for two hours, and finally gradually cooling process. The produced LWA was then crushed to small pieces then screened on standard sieve series and prepared with grading which conforms to the specifications of LWA. The maximum aggregate size used in this investigation is 10 mm. The chemical composition and the physical properties of the produced LWA are investigated. The results indicate that the specific gravity of the produced LWA is 1.5 with the density of 543kg/m3 and water absorption of 20.7% which is in conformity with the international standard of LWA. Many trail mixes were carried out in order to produce LWAC containing the artificial LWA produced in this research. The selected mix proportion is 1:1.5:2 (cement: sand: aggregate) by weight with water to cement ratio of 0.45. The experimental results show that LWAC has oven dry density of 1720 kg/m3, water absorption of 8.5%, the thermal conductivity of 0.723 W/m.K and compressive strength of 23 N/mm2. The SLWAC produced in this research can be used in the construction of different thermal insulated buildings and masonry units. It can be concluded that the SLWA produced in this study contributes to sustainable development by, using industrial waste materials, conserving energy, enhancing the thermal and structural efficiency of concrete.

Keywords: expanded clay, lightweight aggregate, structural lightweight aggregate concrete, sustainable

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Authors: Dimple Juneja, Aarti Singh, Renu Hooda

Abstract:

Knowledge Query Manipulation Language (KQML) and FIPA ACL are two prime communication languages existing in multi agent systems (MAS). Both languages are more or less similar in terms of semantics (based on speech act theory) and offer cutting edge competition while establishing agent communication across Internet. In contrast to the fact that software agents operating on the internet are required to be more safeguarded from their counter-peer, both protocols lack security performatives. The paper proposes a three tier security interface with few novel security related performatives enhancing the basic architecture of KQML. The three levels are attestation, certification and trust establishment which enforces a tight security and hence reduces the security breeches.

Keywords: multiagent systems, KQML, FIPA ACL, performatives

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Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

Abstract:

Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

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Authors: O. Rachinel, C. Recchia, M. Bourel, B. Recchia

Abstract:

Dry microfine steam (DMS) technology, developed by Laurastar, was shown to effectively eliminate a range of pathogens such as Sars-CoV-2, E. coli, S. aureus and C. Albicans. The aim of this study was to investigate the effect of DMS technology on allergens. Therefore, the application of the DMS technology was tested on two common allergens (Dermatophagoides pteronyssinus and cat allergen Fel d 1), on different inert surfaces (e.g., cotton), during 2 to 3 seconds. Quantification of the remaining allergens was performed and the reduction rates reached 100% in 3 seconds for D. pteronyssinus and 97,74% in 2 seconds for cat allergens. In conclusion, DMS showed high efficacy in the elimination of common allergens and could be seen as a natural solution to improve domestic hygiene and reduce allergies.

Keywords: steam, allergens, dust mites, pollens

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Maroof Sakhi

Abstract:

This article studies writing style in A Thousand Splendid Suns. It mainly discusses code-switching and usage of Persian words in the novel. Hosseini mainly writes in English; however, constantly he applies Persian words, phrases and syntax. Code-switching is used for different purposes in A Thousand Splendid Suns. It gives a voice to a character from Afghanistan. It is also used to mark a difference between the American and Afghanistan cultures and languages. Furthermore, representation of Persian language can be interpreted as valorization of the author’s mother tongue. In short, the writing style in A Thousand Splendid Suns represents Hosseini’s identity, culture and linguistic background.

Keywords: code-switching, hybridity, identity, linguistic background, Persian literature

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Authors: Mausumi Chetia

Abstract:

One of the main causes of impoverishment of the rural areas of Assam has been the recurrent floods and riverbank erosion. One of the life-changing consequences is displacement. This results not only in a loss of livelihoods but also has wide-reaching socio-economic and cultural effects. Thus, due to such disasters, not only families but communities too are being displaced at large. This compels them to find temporary shelter and begin life from scratch. The role of the state has been highly negligible, with a displacement not being perceived as an ‘issue’ to be addressed. A more holistic approach is thus needed to take socio-economic, cultural, political as well as ecological considerations into account.

Keywords: displacement, policy-framework, human-induced disasters, marginalised communities, India, Assam

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Authors: Lev Idels, Arcady Ponosov

Abstract:

Stochastic fractional differential equations have recently attracted considerable attention, as they have been used to model real-world processes, which are subject to natural memory effects and measurement uncertainties. Compared to conventional hereditary differential equations, one of the advantages of fractional differential equations is related to more realistic geometric properties of their trajectories that do not intersect in the phase space. In this report, a Peano-like existence theorem for nonlinear stochastic fractional differential equations is proven under very general hypotheses. Several specific classes of equations are checked to satisfy these hypotheses, including delay equations driven by the fractional Brownian motion, stochastic fractional neutral equations and many others.

Keywords: delay equations, operator methods, stochastic noise, weak solutions

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Authors: Carlos Tadeu Santana Tatum, Suzana Leitão Russo

Abstract:

This paper aims to show comparative studies of different types of innovation applied to lighting, along with a theoretical review by means of a bibliographic method. We demonstrate that it is possible to understand the impacts of industries with a conventional innovation that uses natural resources to manufacture lights, and the opposite, when a frugal innovation solves the problems of a society at the bottom of the pyramid, helping people without access to electricity to get home lighting. The frugal innovation is simply the use of recycled PET bottles. We achieved the objective of our study by gathering data from environment, electrical engineering, international rules, and innovation, which gave us the best results. With all these variables, we can characterize this work as an interdisciplinary study.

Keywords: frugal, innovation, PET bottle, light

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Authors: Mayowa Saheed Sanusi A, Musiliu Olushola Sunmonua, Abdulquadri Alakab Owolabi Raheema, Adeyemi Ikimot Adejokea

Abstract:

The development of healthy cookies for health-conscious consumers cannot be overemphasized in the present global health crisis. This study was aimed to evaluate and model the influence of ripeness levels of papaya puree (unripe, ripe and overripe), oven temperature (130°C, 150°C and 170°C) and oven rack speed (stationary, 10 and 20 rpm) on physicochemical properties of papaya-based cookies using Response Surface Methodology (RSM). The physicochemical properties (baking time, cookies mass, cookies thickness, spread ratio, proximate composition, Calcium, Vitamin C and Total Phenolic Content) were determined using standard procedures. The data obtained were statistically analysed at p≤0.05 using ANOVA. The polynomial regression model of response surface methodology was used to model the physicochemical properties. The adequacy of the models was determined using the coefficient of determination (R²) and the response optimizer of RSM was used to determine the optimum physicochemical properties for the papaya-based cookies. Cookies produced from overripe papaya puree were observed to have the shortest baking time; ripe papaya puree favors cookies spread ratio, while the unripe papaya puree gives cookies with the highest mass and thickness. The highest crude protein content, fiber content, calcium content, Vitamin C and Total Phenolic Content (TPC) were observed in papaya based-cookies produced from overripe puree. The models for baking time, cookies mass, cookies thickness, spread ratio, moisture content, crude protein and TPC were significant, with R2 ranging from 0.73 – 0.95. The optimum condition for producing papaya based-cookies with desirable physicochemical properties was obtained at 149°C oven temperature, 17 rpm oven rack speed and with the use of overripe papaya puree. The Information on the use of puree from unripe, ripe and overripe papaya can help to increase the use of underutilized unripe or overripe papaya and also serve as a strategic means of obtaining a fat substitute to produce new products with lower production cost and health benefit.

Keywords: papaya based-cookies, modeling, response surface methodology, physicochemical properties

Procedia PDF Downloads 160