Search results for: post-editing machine translation output

Authors: Mustafa Col, Funda Gul Koc, Merve Yangaz, Eylem Subasi, Can Akbasoglu

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G38NiCrMo8-4-4 steel is widely used in mining industries, machine parts, gears due to its high strength and toughness properties. In this study, microstructure, wear and mechanical properties of G38NiCrMo8-4-4 steel modified with boron used in the mining industry were investigated. For this purpose, cast materials were alloyed by melting in an induction furnace to include boron with the rates of 0 ppm, 15 ppm, and 50 ppm (wt.) and were formed in the dimensions of 150x200x150 mm by casting into the sand mould. Homogenization heat treatment was applied to the specimens at 1150˚C for 7 hours. Then all specimens were austenitized at 930˚C for 1 hour, quenched in the polymer solution and tempered at 650˚C for 1 hour. Microstructures of the specimens were investigated by using light microscope and SEM to determine the effect of boron and heat treatment conditions. Changes in microstructure properties and material hardness were obtained due to increasing boron content and heat treatment conditions after microstructure investigations and hardness tests. Wear tests were carried out using a pin-on-disc tribometer under dry sliding conditions. Charpy V notch impact test was performed to determine the toughness properties of the specimens. Fracture and worn surfaces were investigated with scanning electron microscope (SEM). The results show that boron element has a positive effect on the hardness and wear properties of G38NiCrMo8-4-4 steel.

Keywords: G38NiCrMo8-4-4 steel, boron, heat treatment, microstructure, wear, mechanical properties

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Basem Kamal Abasakhiroun Farag

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Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

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Authors: Andres Portocarrero Bonifaz, Caterina Sandra Camarena Rodriguez, Ricardo Palma Esparza, Nicolas Antonio Romero Carlos

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Reference levels for common X-rays procedures have been set in many protocols. In Peru, during quality control tests, the dose tolerance is set by these international recommendations. Nevertheless, further studies can be made to assess the national reality and relate dose levels with different parameters such as kV, mA/mAs, exposure time, type of processing (digital, digitalized or conventional), etc. In this paper three radiologic procedures were taken into account for study, general X-rays (fixed and mobile), intraoral X-rays (fixed, mobile and portable) and mammography. For this purpose, an Unfors Xi detector was used; the dose was measured at a focus - detector distance which varied depending on the procedure, and was corrected afterward to find the surface entry dose. The data used in this paper was gathered over a period of over 3 years (2015-2018). In addition, each X-ray machine was taken into consideration only once. The results hope to achieve a new standard which reflects the local practice, and address the issues of the ‘Bonn Call for Action’ in Peru. For this purpose, the 75% percentile of the dose of each radiologic procedure was calculated. In future quality control services, those machines with dose values higher than the selected threshold should be informed that they surpass the reference dose levels established in comparison other radiological centers in the country.

Keywords: general X-rays, intraoral X-rays, mammography, reference dose levels

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Authors: Azeez Balogun

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Inexperienced building score practices are continually evolving and vary across areas. Yet, a few middle ideas stay steady, such as website selection, design, energy efficiency, water and material conservation, indoor environmental great, operational optimization, and waste discount. The essence of green building lies inside the optimization of 1 or more of those standards. This paper conducts a comparative analysis of 7 extensively recognized sustainable score structures—BREEAM, CASBEE, green GLOBES, inexperienced superstar, HK-BEAM, IGBC green homes, and LEED—based totally on the perceptions and opinions of stakeholders in Nigeria certified in green constructing rating systems. The purpose is to pick out and adopt an appropriate green building rating device for Nigeria. Numerous components of those systems had been tested to determine the high-quality health of the Nigerian built environment. The findings imply that LEED, the important machine within the USA and Canada, is the most suitable for Nigeria due to its sturdy basis, extensive funding, and confirmed blessings. LEED obtained the highest rating of eighty out of one hundred points on this assessment.

Keywords: structure, built surroundings, inexperienced building score gadget, Nigeria Inexperienced Constructing Council, sustainability

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

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Authors: Afshan Ejaz, Syed Asim Ali

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The reality is a combination of perception, reconstruction, and interaction. Augmented Reality is the advancement that layer over consistent everyday existence which includes content based interface, voice-based interfaces, voice-based interface and guide based or gesture-based interfaces, so designing augmented reality application interfaces is a difficult task for the maker. Designing a user interface which is not only easy to use and easy to learn but its more interactive and self-explanatory which have high perceived affordability, perceived usefulness, consistency and high discoverability so that the user could easily recognized and understand the design. For this purpose, a lot of interface design principles such as learnability, Affordance, Simplicity, Memorability, Feedback, Visibility, Flexibly and others are introduced but there no such principles which explain the most appropriate interface design principles for designing an Augmented Reality application interfaces. Therefore, the basic goal of introducing design principles for Augmented Reality application interfaces is to match the user efforts and the computer display (‘plot user input onto computer output’) using an appropriate interface action symbol (‘metaphors’) or to make that application easy to use, easy to understand and easy to discover. In this study by observing Augmented reality system and interfaces, few of well-known design principle related to GUI (‘user-centered design’) are identify and through them, few issues are shown which can be determined through the design principles. With the help of multiple studies, our study suggests different interface design principles which makes designing Augmented Reality application interface more easier and more helpful for the maker as these principles make the interface more interactive, learnable and more usable. To accomplish and test our finding, Pokémon Go an Augmented Reality game was selected and all the suggested principles are implement and test on its interface. From the results, our study concludes that our identified principles are most important principles while developing and testing any Augmented Reality application interface.

Keywords: GUI, augmented reality, metaphors, affordance, perception, satisfaction, cognitive burden

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Authors: Colin Smith, Linsey S Passarella

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Due to the proliferation and decentralized nature of academic publication, no widely accepted scheme exists for organizing papers by their scientific field of study (FoS) to the author’s best knowledge. While many academic journals require author provided keywords for papers, these keywords range wildly in scope and are not consistent across papers, journals, or field domains, necessitating alternative approaches to paper classification. Past attempts to perform field-of-study (FoS) classification on scientific texts have largely used a-hierarchical FoS schemas or ignored the schema’s inherently hierarchical structure, e.g. by compressing the structure into a single layer for multi-label classification. In this paper, we introduce an application of a Layered Neural Network (LNN) to the problem of performing supervised hierarchical classification of scientific fields of study (FoS) on research papers. In this approach, paper embeddings from a pretrained language model are fed into a top-down LNN. Beginning with a single neural network (NN) for the highest layer of the class hierarchy, each node uses a separate local NN to classify the subsequent subfield child node(s) for an input embedding of concatenated paper titles and abstracts. We compare our LNN-FOS method to other recent machine learning methods using the Microsoft Academic Graph (MAG) FoS hierarchy and find that the LNN-FOS offers increased classification accuracy at each FoS hierarchical level.

Keywords: hierarchical classification, layer neural network, scientific field of study, scientific taxonomy

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Authors: Awadhesh Kishore

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The goal of the study was to determine how different non-metallic nutrients are partitioned from feed in various physiological contexts and how buffer addition in ruminant nutrition affects these processes. Six lactating crossbred dairy cows were selected and divided into three groups on the basis of their phenotypic and productive features (374±14 kg LW). Two treatments, T1 and T2, were randomly assigned to one animal from each group. Animals under T1 and T2 were moved to T2 and T1, respectively, after 30 days. T2 was the only group to receive buffers containing magnesium oxide and sodium bicarbonate at 0.0 and 0.01% of LW (the real amounts are equivalent to 75.3±4.0 and 30 7.7±2.0 g/d, respectively). T1 was used as the control. Wheat straw and berseem were part of the base diet, whereas wheat grain and mustard cake were part of the concentrate mixture. Following a 21-day feeding period, metabolic and milk production trials were carried out for seven consecutive days. The Kearl equation used the urine's calorific value to determine its volume. Chemical analyses were performed to determine the levels of nitrogen, carbohydrates, calories, and phosphorus in samples of feed, waste, buffer, mineral mixture, water, feces, urine, and milk that were collected. The information was analyzed statistically. Notable results included decreased nitrogen and carbohydrate partitioning to feces from feed, while increased calorie partitioning to milk and body storage, and increased carbohydrate partitioning to body storage. Phosphorus balance was significantly better in T2. The application of buffers in ruminant diets was found to increase the output of calories in milk, as well as the number of calories and carbohydrates stored in the body, while decreasing the amount of nitrogen in faeces. As a result, it may be advised to introduce buffers to feed crossbred dairy cattle.

Keywords: cattle, Magnesium oxide, non-metallic nutrients, partitioning, Sodium bicarbonate

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: David Halley, Tyra Oseng-Rees, Luca Pagano, Juan A Ferriz-Papi

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Recycled glass material is made from 100% recycled bottle glass and consumes less energy than re-melt technology. It also uses no additives in the manufacturing process allowing the recycled glass material, in principal, to go back to the recycling stream after end-of-use, contributing to the circular economy with a low ecological impact. The aim of this paper is to investigate the procedure for testing the recycled glass material for impact resistance, so it can be applied to pavements and other surfaces which are at risk of impact during service. A review of different impact test procedures for construction materials was undertaken, comparing methodologies and international standards applied to other materials such as natural stone, ceramics and glass. A drop weight impact testing machine was designed and manufactured in-house to perform these tests. As a case study, samples of the recycled glass material were manufactured with two different thicknesses and tested. The impact energy was calculated theoretically, obtaining results with 5 and 10 J. The results on the material were subsequently discussed. Improvements on the procedure can be made using high speed video technology to calculate velocity just before and immediately after the impact to know the absorbed energy. The initial results obtained in this procedure were positive although repeatability needs to be developed to obtain a correlation of results and finally be able to validate the procedure. The experiment with samples showed the practicality of this procedure and application to the recycled glass material impact testing although further research needs to be developed.

Keywords: construction materials, drop weight impact, impact testing, recycled glass

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Authors: Nadir Atayev, Mehman Hasanov

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Future spacecraft will require a structural change in the way data is transmitted due to the increase in the volume of data required for space communication. Current radio frequency communication systems are already facing a bottleneck in the volume of data sent to the ground segment due to their technological and regulatory characteristics. To overcome these issues, free space optics communication plays an important role in the integrated terrestrial space network due to its advantages such as significantly improved data rate compared to traditional RF technology, low cost, improved security, and inter-satellite free space communication, as well as uses a laser beam, which is an optical signal carrier to establish satellite-ground & ground-to-satellite links. In this approach, there is a need for high-speed and energy-efficient systems as a base platform for sending high-volume video & audio data. Nano Satellite and its branch CubeSat platforms have more technical functionality than large satellites, wheres cover an important part of the space sector, with their Low-Earth-Orbit application area with low-cost design and technical functionality for building networks using different communication topologies. Along the research theme developed in this regard, the output parameter indicators for the FSO of the optical communication transceiver subsystem on the existing CubeSat platforms, and in the direction of improving the mentioned parameters of this communication methodology, 3D optical switch and laser beam controlled optical transponder with 2U CubeSat structural subsystems and application in the Low Earth Orbit satellite network topology, as well as its functional performance and structural parameters, has been studied accordingly.

Keywords: cubesat, free space optics, nano satellite, optical laser communication.

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Authors: Srutirekha Giri, Manoranjan Sahoo, Anuradha Das, Pravanjan Mallick, Biswajit Mallick

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Ion Beam (IB) technique is a very powerful experimental technique for both material synthesis and material modifications. In this work, 3MeV proton beam was generated using the 3MV Tandem machine of the Institute of Physics, Bhubaneswar and extracted into air for the irradiation-induced modification purpose[1]. The polymeric material can be modeled for a three-phase system viz. crystalline(I), amorphous(II) and mesomorphic(III). So far, our knowledge is concerned. There are only few techniques reported for the synthesis of this third-phase(III) of polymer. The IB induced technique is one of them and has been reported very recently [2-4]. It was observed that by irradiating polyethylene terephthalate (PET) fiber at very low proton fluence, 10¹⁰ - 10¹² p/s, possess 2D mesophase structure. This was confirmed using X-ray diffraction technique. A low-intensity broad peak was observed at small angle of about 2θ =6º, when the fiber axis was mounted parallel to the X-ray direction. Such peak vanished in the diffraction spectrum when the fiber axis was mounted perpendicular to the beam direction. The appearance of this extra peak in a particular orientation confirms that the phase is 2-dimensionally oriented (mesophase). It is well known that the mesophase is a 2-dimensionally ordered structure but 3-dimensionally disordered. Again, the crystallite of the mesophase peak particle was measured about 3nm. The MeV proton-induced 2D mesophase patterning of nanocrystallites (3nm) of PET due to irradiation was observed within the above low fluence range and failed in high proton fluence. This is mainly due to the breaking of crystallites, radiation-induced thermal degradation, etc.

Keywords: Ion irradiation, mesophase, nanocrystallites, polymer

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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“Health transition” is defined to be “a process through which high levels of mortality, morbidity and disability are reduced to low levels by influencing cultural, social and behavioural factors”. Life expectancy in India has been on the rise and parallel the burden of disease and disability has also risen noticeably. Borrowing data from Indian Census (2001, 2011), this study identifies the gender-wise burden of disability by calculating disability free life expectancy (DFLE) and life lived with disability (LWD). Sullivan’s method of calculating DFLE using proportion of disabled is used for this purpose. The change in person years lived with disability in the decade 2001-11 is further decomposed using Arriaga’s method into mortality and disability effects (ME and DE) to check the magnitude and direction of contribution of mortality and disability. Nationally, along with DFLE, LWD has amplified too. Despite having the highest life expectancy and DFLE, LWD in Kerala, was highest for both sexes in 2001. But in 2011, the LWD was highest among the males of Orissa and females of Rajasthan. For the overall population, DE is positive for the prime working age groups of 20-40years indicating that there has been an increase in the disability proportion holding mortality constant for 2001-2011. Females exhibit higher positive DE implying greater loss of healthy years due to disability than males. The findings call for an immediate attention to the causes of rising disability burden among the working population, especially females, as this might heavily effect the availability of quality labour force and its relative economic output in the Indian labour market. This also hints at the degrading quality of the elongated life and needs to be given the required attention to enhance the quality of life lead in the Nation.

Keywords: disability-free life expectancy, disability effect, life expectancy, mortality effect

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Authors: Sumaira Zafar, Arjumand Zaidi

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During past few years, several floods have adversely affected the areas along lower Indus River. Besides other climate related anomalies, rapidly increasing urbanization and blockage of natural drains due to siltation or encroachments are two other critical causes that may be responsible for these disasters. Due to flat topography of river Indus plains and blockage of natural waterways, drainage of storm water takes time adversely affecting the crop health and soil properties of the area. Government of Sindh is taking a keen interest in revival of natural drainage network in the province and has initiated this work under Sindh Irrigation and Drainage Authority. In this paper, geospatial techniques are used to analyze landuse/land-cover changes of Larkana district over the past three decades (1980-present) and their impact on natural drainage system. Satellite derived Digital Elevation Model (DEM) and topographic sheets (recent and 1950) are used to delineate natural drainage pattern of the district. The urban landuse map developed in this study is further overlaid on drainage line layer to identify the critical areas where the natural floodwater flows are being inhibited by urbanization. Rainfall and flow data are utilized to identify areas of heavy flow, whereas, satellite data including Landsat 7 and Google Earth are used to map previous floods extent and landuse/cover of the study area. Alternatives to natural drainage systems are also suggested wherever possible. The output maps of natural drainage pattern can be used to develop a decision support system for urban planners, Sindh development authorities and flood mitigation and management agencies.

Keywords: geospatial techniques, satellite data, natural drainage, flood, urbanization

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Authors: Selina Schwaabe

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Community pharmacies deliver high-quality health care and are responsible for medication safety. During the pandemic, accessibility to the nearest pharmacy became more essential to get vaccinated against Covid-19 and to get medical aid. The government's goal is to ensure nationwide, reachable, and affordable medical health care services by pharmacies. Therefore, the density of community pharmacies matters. Overall, the density of community pharmacies is fluctuating, with slightly decreasing tendencies in some countries. So far, the literature has shown that changes in the system affect prices and density. However, a European overview of the development of the density of community pharmacies and its triggers is still missing. This research is essential to counteract against decreasing density consulting in a lack of professional health care through pharmacies. The analysis focuses on liberal versus regulated market structures, mail-order prescription drug regulation, and third-party ownership consequences. In a panel analysis, the relative influence of the measures is examined across 27 European countries over the last 21 years. In addition, the paper examines seven selected countries in depth, selected for the substantial variance in their pharmacy system: Germany, Austria, Portugal, Denmark, Sweden, Finland and Poland. Overall, the results show that regulated pharmacy markets have over 10.75 pharmacies/100.000 inhabitants more than liberal markets. Further, mail-order prescription drugs decrease the density by -17.98 pharmacies/100.000 inhabitants. Countries allowing third-party ownership have 7.67 pharmacies/100.000 inhabitants more. The results are statistically significant at a 0.001 level. The output of this analysis recommends regulated pharmacy markets, with a ban on mail-order prescription drugs allowing third-party ownership to support nationwide medical health care through community pharmacies.

Keywords: community pharmacy, market conditions, pharmacy, pharmacy market, pharmacy lobby, prescription, e-prescription, ownership structures

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Authors: Noury Bakrim

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Translatability is one of Walter Benjamin’s most influential notions, it is somehow representing the philosophy of language and history of what we might call and what we indeed coined as ‘the other German Speaking Modernity’ which could be shaped as a parallel thought form to the Marxian-Hegelian philosophy of history, the one represented by the school of Frankfurt. On the other hand, we should consider the influence of the plural German speaking identity and the Nietzschian and Goethean heritage, this last being focused on a positive will of power: the humanised human being. Having in perspective the benjaminian notion of translatability (Übersetzbarkeit), to be defined as an internal permanent hermeneutical possibility as well as a phenomenological potential of a translation relation, we are in fact touching this very double limit of both historical and linguistic reason. By life component, we mean the changing conditions of genetic and neurolinguistic post-partum functions, to be grasped as an individuation beyond the historical determinism and teleology of an event. It is, so to speak, the retrospective/introspective canettian auto-fiction, the benjaminian crystallization of the language experience in the now-time of writing/transmission. Furthermore, it raises various questioning points when it comes to translatability, they are basically related to psycholinguistic separate poles, the fatherly ladino Spanish and the motherly Vienna German, but relating more in particular to the permanent ontological quest of a world loss/belonging. Another level of this quest would be the status of Veza Canetti-Taubner Calderón, german speaking Author, Canetti’s ‘literary wife’, writer’s love, his inverted logos, protective and yet controversial ‘official private life partner’, the permanence of the jewish experience in the exiled german language. It sheds light on a traumatic relation of an inadequate/possible language facing the reconstruction of an oral life, the unconscious split of the signifier and above all on the frustrating status of writing in Canetti’s work : Using a suffering/suffered written German to save his remembered acquisition of his tongue/mother tongue by saving the vanishing spoken multilingual experience. While Canetti’s only novel ‘Die Blendung’ designates that fictional referential dynamics focusing on the nazi worldless horizon: the figure of Kien is an onomastic signifier, the anti-Canetti figure, the misunderstood legacy of Kant, the system without thought. Our postulate would be the double translatability of his auto-fiction inventing the bios oral signifier basing on the new praxemes created by Canetti’s german as observed in the English, French translations of his memory corpus. We aim at conceptualizing life component and translatability as two major features of a german speaking modernity.

Keywords: translatability, language biography, presentification, bioeme, life Order

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Yu-Chen Hsu, Kuang C. Lin

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The artificial lung called extracorporeal membrane oxygenation (ECMO) is an important medical machine that supports persons whose heart and lungs dysfunction. Previously, investigation of steady deoxygenated blood flows passing through hollow fibers for oxygen transport was carried out experimentally and computationally. The present study computationally analyzes the effect of biological pulsatile flow on the oxygen transport in blood. A 2-D model with a pulsatile flow condition is employed. The power law model is used to describe the non-Newtonian flow and the Hill equation is utilized to simulate the oxygen saturation of hemoglobin. The dimensionless parameters for the physical model include Reynolds numbers (Re), Womersley parameters (α), pulsation amplitudes (A), Sherwood number (Sh) and Schmidt number (Sc). The present model with steady-state flow conditions is well validated against previous experiment and simulations. It is observed that pulsating flow amplitudes significantly influence the velocity profile, pressure of oxygen (PO2), saturation of oxygen (SO2) and the oxygen mass transfer rates (m ̇_O2). In comparison between steady-state and pulsating flows, our findings suggest that the consideration of pulsating flow in the computational model is needed when Re is raised from 2 to 10 in a typical range for flow in artificial lung.

Keywords: artificial lung, oxygen transport, non-Newtonian flows, pulsating flows

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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Authors: Gunjita Shami, Noopur Anand

Abstract:

The pilot run of 50 days was undertaken to test employability potential of people with visual and hearing & speech impairment. Various roles in an apparel manufacturing set up like spreading of fabric for cutting, folding, sealing and labeling cartons, pasting size barcode stickers on packed garments, removing tickets from the garments in the finishing stage were studied. Their performance was quantified basis timesheets for all the days and improvement per day was quantified. Their final day output was compared to that of the able-bodied worker. For example in the carton making activity on day one visually impaired worker was making one box every three minutes which improved to four boxes per minute on day 28 displaying 91.6% improvement compared or an improvement of 3.6% per day which was comparable to the able-bodied seasoned workers, who were making 5 boxes per minute. The performance of persons with hearing and speech impairment in the finishing department was 10% higher than that of able-bodied seasoned workers in the same process. Overall in all the activities the differently abled showed day to day improvement of 65% while able bodied displayed improvement of 52%. On the first day performance of able-bodied worker was 75% better than that of differently abled while on the 50th day it was only 20% better. Therefore the performance of persons with disabilities was found comparable to the able bodied person. The results, though on a small scale, showed a big promise of employment of persons with disability in the apparel industry. Armed with the promising result a full-scale study has been undertaken to identify the roles suitable for certain kind of disability in apparel production, work-aids required to assist the differently abled to improve performance and measures to be undertaken to make production floor 'friendlier' for them. The results have been discussed in this paper which opens doors for integrating differently abled into the world projected and assumed for only able-bodied.

Keywords: apparel sector, differently abled, employability, performance, work-aid

Procedia PDF Downloads 147

Authors: Alireza Vahid, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh, Thomas Dorin

Abstract:

Aluminum is the preferred material for lightweight applications and its alloys are constantly improving. The high strength 7xxx alloys have been extensively used for structural components in aerospace and automobile industries for the past 50 years. In the next decade, a great number of airplanes will be retired, providing an obvious source of valuable used metals and great demand for cost-effective methods to re-use these alloys. The design of proper aerospace alloys is primarily based on optimizing strength and ductility, both of which can be improved by controlling the additional alloying elements as well as heat treatment conditions. In this project, we explore the design of high-performance alloys with 7xxx as a base material. These designed alloys have to be optimized and improved to compare with modern 7xxx-series alloys and to remain competitive for aircraft manufacturing. Aerospace alloys are extremely complex with multiple alloying elements and numerous processing steps making optimization often intensive and costly. In the present study, we used Bayesian optimization algorithm, a well-known adaptive design strategy, to optimize this multi-variable system. An Al alloy was proposed and the relevant heat treatment schedules were optimized, using the tensile yield strength as the output to maximize. The designed alloy has a maximum yield strength and ultimate tensile strength of more than 730 and 760 MPa, respectively, and is thus comparable to the modern high strength 7xxx-series alloys. The microstructure of this alloy is characterized by electron microscopy, indicating that the increased strength of the alloy is due to the presence of a high number density of refined precipitates.

Keywords: aluminum alloys, Bayesian optimization, heat treatment, tensile properties

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

Abstract:

We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

Abstract:

The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

Procedia PDF Downloads 146

Authors: Chandra Gupt Porwal

Abstract:

Excessive vibration means increased wear, increased repair efforts, bad product selection & quality and high energy consumption. This may be sometimes experienced by cavitation or suction/discharge re-circulation which could occur only when net positive suction head available NPSHA drops below the net positive suction head required NPSHR. Cavitation can cause axial surging if it is excessive, will damage mechanical seals, bearings, possibly other pump components frequently and shorten the life of the impeller. Efforts have been made to explain Suction Energy (SE), Specific Speed (Ns), Suction Specific Speed (Nss), NPSHA, NPSHR & their significance, possible reasons of cavitation /internal re-circulation, its diagnostics and remedial measures to arrest and prevent cavitation in this paper. A case study is presented by the author highlighting that the root cause of unwanted noise and vibration is due to cavitation, caused by high specific speeds or inadequate net- positive suction head available which results in damages to material surfaces of impeller & suction bells and degradation of machine performance, its capacity and efficiency too. The author strongly recommends revisiting the technical specifications of CW pumps to provide sufficient NPSH margin ratios > 1.5, for future projects and Nss be limited to 8500 -9000 for cavitation free operation.

Keywords: best efficiency point (BEP), net positive suction head NPSHA, NPSHR, specific speed NS, suction specific speed NSS

Procedia PDF Downloads 252

Authors: Makda Yeshitela Kifele

Abstract:

Hair treatment prevents the hair from loss of volume, changing colour, and damaging its properties of the hair. Hair is the beauty of human beings that makes people beautiful and takes the other hearts to see them and to give them an appreciation for their effort to treat their hair and save it from damage. There are different methods to protect human hair from loss and damage that influence human psychology better than the problems. Chemicals products are available in the world that keeps safely the hair and provide beauty for the hair. But chemical products have side effects and are not cost-effective. Even some of the chemicals are allergic for users and left some changes in the hair. Indigenous hair treatment is an effective method that reduces the bad effects and the problems of the chemical that are lefts in human being’slife. Indigenous hair treatment can treat the hair safely and effectively that does not have much effect or spots in the human hair the users rather, it improves some attributes of the hair such that shine, quality, quantity improvements, length, and flexibility can be modified by these indigenous treatments. Rate is the local plant that plays a significant role in hair treatment. Rate is the local plant that can be available everywhere in the country, and anybody can be used for hair treatments. For this research, 50 women are identified as sample populations with different hair characteristics. The treatments were collected from the fields and squeezed into the pots to be prepared as specimens. The squeezed plants were deposited in the refrigerator for three days with some amounts of salts to prevent some bacteria. Chemical analysis has been done to sort out some detrimental substances. So the result showed that there are no detrimental substances that affect the hair properties and the health of the users. The sample population used the oil for one month without any other oily cosmetics that disturbs the treatment. The output is very effective and brings shining the hair, preventing greying of the hair, showing fast-growing, increasing the volume of the hair, and becoming flexible and curly, straight hair, thicker, and with no allergic effects.

Keywords: indigenous, chemicals, curly, treatment

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Authors: Mst Shapna Akter, Hossain Shahriar

Abstract:

Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

Procedia PDF Downloads 111