Search results for: image processing algorithms

Authors: Verónica Díaz

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A Cartesian graph, as a mathematical object, becomes a tool for configuration of change. Its best comprehension is done through everyday life problem-solving associated with its representation. Despite this, the current educational framework favors general graphs, without consideration of their argumentation. Students are required to find the mathematical function without associating it to the development of graphical language. This research describes the use made by students of configurations made prior to Cartesian graphs with regards to an everyday life problem related to a time and distance variation phenomenon. The theoretical framework describes the function conditions of study and their modeling. This is a qualitative, descriptive study involving six undergraduate case studies that were carried out during the first term in 2016 at University of Los Lagos. The research problem concerned the graphic modeling of a real person’s movement phenomenon, and two levels of analysis were identified. The first level aims to identify local and global graph interpretations; a second level describes the iconicity and referentiality degree of an image. According to the results, students were able to draw no figures before the Cartesian graph, highlighting the need for students to represent the context and the movement of which causes the phenomenon change. From this, they managed Cartesian graphs representing changes in position, therefore, achieved an overall view of the graph. However, the local view only indicates specific events in the problem situation, using graphic and verbal expressions to represent movement. This view does not enable us to identify what happens on the graph when the movement characteristics change based on possible paths in the person’s walking speed.

Keywords: cartesian graphs, higher education, movement modeling, problem solving

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Authors: Constantin Haita

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The chalcolithic tell settlements from south-eastern Romania, attributed to Gumelnița culture, are characterised by a well-defined surface, marked often by delimitation structures, a succession of many layers of construction, destruction, and rebuilding, and a well-structured area of occupation: built spaces, passage areas, waste zones. Settlements of tell type are located in the river valleys –on erosion remnants, alluvial bars or small islands, at the border of the valleys– on edges or prominences of Pleistocene terraces, lower Holocene terraces, and banks of lakes. This study integrates data on the geographical position, the morphological background, and the general stratigraphy of these important settlements. The correlation of the spatial distribution with the geomorphological units of each area of evolution creates an image of the natural landscape in which they occurred. The sedimentological researches achieved in the floodplain area of Balta Ialomiței showed important changes in the alluvial activity of Danube, after the Chalcolithic period (ca. 6500 - 6000 BP), to Iron Age and Middle Ages. The micromorphological analysis, consisting in thin section interpretation, at the microscopic scale, of sediments and soils in an undisturbed state, allowed the interpretation of the identified sedimentary facies, in terms of mode of formation and anthropic activities. Our studied cases reflect some distinct situations, correlating either with the geomorphological background or with the vertical development, the presence of delimiting structures and the internal organization. The characteristics of tells from this area bring significant information about the human habitation of Lower Danube in Prehistory.

Keywords: chalcolithic, micromorphology, Romania, sedimentology, tell settlements

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Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Feng Xu, Zhaozhi Liu, Junhua Xu, Xiaolong Tang, Dunwen Zuo

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Chemical vapor deposition (CVD) diamond coated cutting tool has excellent cutting performance, it is the most ideal tool for the processing of nonferrous metals and alloys, composites, nonmetallic materials and other difficult-to-machine materials efficiently and accurately. Depositing CVD diamond coating on the cemented carbide with high cobalt content can improve its toughness and strength, therefore, it is very important to research on the preparation technology and cutting properties of CVD diamond coated cemented carbide cutting tool with high cobalt content. The preparation technology of boron-doped diamond (BDD) coating has been studied and the coated drills were prepared. BDD coating were deposited on the drills by using the optimized parameters and the SEM results show that there are no cracks or collapses in the coating. Cutting tests with the prepared drills against the silumin and aluminum base printed circuit board (PCB) have been studied. The results show that the wear amount of the coated drill is small and the machined surface has a better precision. The coating does not come off during the test, which shows good adhesion and cutting performance of the drill.

Keywords: cemented carbide with high cobalt content, CVD boron-doped diamond, cutting test, drill

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Authors: Ketankumar Gandabhai Patel, Jalpit Balvantkumar Prajapati

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Plate type heat exchangers has many thin plates that are slightly apart and have very large surface areas and fluid flow passages that are good for heat transfer. This can be a more effective heat exchanger than the tube or shell heat exchanger due to advances in brazing and gasket technology that have made this plate exchanger more practical. Plate type heat exchangers are most widely used in food processing industries and dairy industries. Mostly fouling occurs in plate type heat exchanger due to deposits create an insulating layer over the surface of the heat exchanger, that decreases the heat transfer between fluids and increases the pressure drop. The pressure drop increases as a result of the narrowing of the flow area, which increases the gap velocity. Therefore, the thermal performance of the heat exchanger decreases with time, resulting in an undersized heat exchanger and causing the process efficiency to be reduced. Heat exchangers are often over sized by 70 to 80%, of which 30 % to 50% is assigned to fouling. The fouling can be reduced by varying some geometric parameters and flow parameters. Based on the study, a correlation will estimate for Nusselt number as a function of Reynolds number, Prandtl number and chevron angle.

Keywords: heat transfer coefficient, single phase flow, mass flow rate, pressure drop

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Authors: Abhijit Pattnayak, Abhijith N.V, Deepak Kumar, Jayant Jain, Vijay Chaudhry

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Hard and dense ceramic coatings deposited on the surface provide the ideal solution to the poor tribological properties exhibited by some popular stainless steels like EN-36, 17-4PH, etc. These steels are widely used in nuclear, fertilizer, food processing, and marine industries under extreme environmental conditions. The present study focuses on the development of Al₂O₃-CeO₂-rGO-based coatings on the surface of 17-4PH steel using High-Velocity Oxygen Flame (HVOF) thermal spray process. The coating is developed using an oxyacetylene flame. Further, we report the physical (Density, Surface roughness, Surface energetics), Metallurgical (Scanning electron microscopy, X-ray diffraction, Raman), Mechanical (Hardness(Vickers and Nano Hard-ness)), Tribological (Wear, Scratch hardness) and Chemical (corrosion) characterization of both As-sprayed coating and the Substrate (17-4 PH steel). The comparison of the properties will help us to understand the microstructure-property relationship of the coating and reveal the necessity and challenges of such coatings.

Keywords: thermal spray process, HVOF, ceramic coating, hardness, wear, corrosion

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

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High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

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Authors: Iftikhar Ahmad, Mohammad Islam

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Thermally exfoliated graphene nanomaterial was reinforced into Al2O3 ceramic and the nanocomposites were consolidated using rapid high-frequency induction heat sintering route. The resulting nanocomposites demonstrated higher mechanical properties due to efficient GNS incorporation and chemical interaction with the Al2O3 matrix grains. The enhancement in mechanical properties is attributed to (i) uniformly-dispersed GNS in the consolidated structure (ii) ability of GNS to decorate Al2O3 nanoparticles and (iii) strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. The formation of an intermediate aluminum oxycarbide phase (Al2OC) via a confined carbothermal reduction reaction at the GNS/Al2O3 interface was observed using advanced electron microscopes. The GNS surface roughness improves GNS/Al2O3 mechanical locking and chemical compatibility. The sturdy interface phase facilitates efficient load transfer and delayed failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Keywords: ceramics, nanocomposites, interfaces, nanostructures, electron microscopy, Al2O3

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Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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Authors: Robertoes K. K. Wibowo, Siswoyo Soekarno, Irma Puspitasari

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Indonesian people use trains for their transportation, especially they use economy class train transportation because it is cheaper and has a more precise schedule than any other ground transportation. Nevertheless, the economy class passenger seat raises some inconvenience issues for passengers. This is due to the design of the chair on the economic class of trains that did not adjusted to the shape of anthropometry of Indonesian people. Thus, research needs to be conducted on the design of the seats in the economic class of trains. The purpose of this research is to make the design of economy class passenger seats ergonomic. This research method uses questionnaires and anthropometry measurements. The data obtained is processed using House of Quality of Ergonomic Function Development. From the results of analysis and data processing were obtained important changes from the original design. Ergonomic chair design according to the analysis is a stainless steel frame, seat height 390 mm, with a seat width for each passenger of 400 mm and a depth of 400 mm. Design of the backrest has a height of 840 mm, width of 430 mm and length of 300 mm that can move at the angle of 105-115 degrees. The width of the footrest is 42 mm and 400 mm length. The thickness of the seat cushion is 100 mm.

Keywords: chair, ergonomics, function development, train passenger

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

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Authors: Amine Benmoussa, Mohamed Bouanini, Mebrouk Rebhi

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Stirring is one of the unifying processes which form part of the mechanical unit operations in process technology such chemical, biotechnological, pharmaceutical, petrochemical, cosmetic, and food processing. Therefore determining the level of mixing and overall behavior and performance of the mixing tanks are crucial from the product quality and process economics point of views. The most fundamental needs for the analysis of these processes from both a theoretical and industrial perspective are the knowledge of the hydrodynamic behavior and the flow structure in such tanks. Depending on the purpose of the operation carried out in mixer, the best choice for geometry of the tank and agitator type can vary widely. Initially, a local and global study namely the velocity and power number on a typical agitation system agitated by a mobile-type two-blade straight (d/D=0.5) allowed us to test the reliability of the CFD, the result were compared with those of experimental literature, a very good concordance was observed. The stream function, the velocity profile, the velocity fields and power number are analyzed. It was shown that the hydrodynamics is modified by the curvature of the mobile which plays a key role.

Keywords: agitated vessels, curved blade agitator, laminar flow, finite volume method

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Authors: Tahir Ali Akbar, Hirra Jabbar

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Land cover change analysis plays a significant role in understanding the trends of urban sprawl and land use transformation due to anthropogenic activities. In this study, the spatio-temporal dynamics of major land covers were analyzed in the last twenty years (1988-2016) for District Lahore located in the Punjab Province of Pakistan. The Landsat satellite imageries were downloaded from USGS Global Visualization Viewer of Earth Resources Observation and Science Center located in Sioux Falls, South Dakota USA. The imageries included: (i) Landsat TM-5 for 1988 and 2001; and (ii) Landsat-8 OLI for 2016. The raw digital numbers of Landsat-5 images were converted into spectral radiance and then planetary reflectance. The digital numbers of Landsat-8 image were directly converted into planetary reflectance. The normalized difference vegetation index (NDVI) was used to classify the processed images into six major classes of water, buit-up, barren land, shrub and grassland, sparse vegetation and dense vegetation. The NDVI output results were improved by visual interpretation using high-resolution satellite imageries. The results indicated that the built-up areas were increased to 21% in 2016 from 10% in 1988. The decrease in % areas was found in case of water, barren land and shrub & grassland. There were improvements in percentage of areas for the vegetation. The increasing trend of urban sprawl for Lahore requires implementation of GIS based spatial planning, monitoring and management system for its sustainable development.

Keywords: land cover changes, NDVI, remote sensing, urban sprawl

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: A.Boularouk, F. Chouikh, M. Lamri, H. Moualkia, Y. Bouznit

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The principal aim of this study is to considerably reduce the resistivity of the SnO2 thin layers. In this order, we have doped tin oxide with aluminum and antimony incorporation with different atomic percentages (0 and 4%). All the pure and doped SnO2 films were grown by simple, flexible and cost-effective Automatic Spray Pyrolysis Method (ASPM) on glass substrates at a temperature of 350 °C. The microstructural, optical, morphological and electrical properties of the films have been studied. The XRD results demonstrate that all films have polycrystalline nature with a tetragonal rutile structure and exhibit the (200) preferential orientation. It has been observed that all the dopants are soluble in the SnO2 matrix without forming secondary phases. However, dopant introduction does not modify the film growth orientation. The crystallite size of the pure SnO2 film is about 36 nm. The films are highly transparent in the visible region with an average transmittance reaching up to 80% and it slightly reduces with increasing doping concentration (Al and Sb). The optical band gap value was evaluated between 3.60 eV and 3.75 eV as a function of doping. The SEM image reveals that all films are nanostructured, densely continuous, with good adhesion to the substrate. We note again that the surface morphology change with the type and concentration dopant. The minimum resistivity is 0.689*10-4, which is observed for SnO2 film doped 4% Al. This film shows better properties and is considered the best among all films. Finally, we concluded that the physical properties of the pure and doped SnO2 films grown on a glass substrate by ASPM strongly depend on the type and concentration dopant (Al and Sb) and have highly desirable optical and electrical properties and are promising materials for several applications.

Keywords: tin oxide, automatic spray, Al and Sb doped, transmittance, MEB, XRD and UV-VIS

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Authors: Muammer Kaya

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The main purpose of this article is to provide a comprehensive review of various physical and chemical processes for electronic waste (e-waste) recycling, their advantages and shortfalls towards achieving a cleaner process of waste utilization, with especial attention towards extraction of metallic values. Current status and future perspectives of waste printed circuit boards (PCBs) recycling are described. E-waste characterization, dismantling/ disassembly methods, liberation and classification processes, composition determination techniques are covered. Manual selective dismantling and metal-nonmetal liberation at – 150 µm at two step crushing are found to be the best. After size reduction, mainly physical separation/concentration processes employing gravity, electrostatic, magnetic separators, froth floatation etc., which are commonly used in mineral processing, have been critically reviewed here for separation of metals and non-metals, along with useful utilizations of the non-metallic materials. The recovery of metals from e-waste material after physical separation through pyrometallurgical, hydrometallurgical or biohydrometallurgical routes is also discussed along with purification and refining and some suitable flowsheets are also given. It seems that hydrometallurgical route will be a key player in the base and precious metals recoveries from e-waste. E-waste recycling will be a very important sector in the near future from economic and environmental perspectives.

Keywords: e-waste, WEEE, recycling, metal recovery, hydrometallurgy, pirometallurgy, biometallurgy

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Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez

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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.

Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks

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Authors: Abdulmannan Fadel

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Arabinoxylan is a non-starch polysaccharide (NSP), which is one of the most important polysaccharides contained within cereal grains. Wheat endosperm pentosan and rice bran contain a significant amount of arabinoxylan (7% in rice bran and 10-12% in wheat endosperm pentosan). Several methods have been used for arabinoxylan extraction with varying degrees of success e.g. enzymatic and alkaline treatment. Yet, the use of extrusion alone as a pre-treatment to increase the yield and reduce the molecular weight in wheat endosperm pentosan and rice bran has not been investigated. The samples (wheat pentosan and rice bran) were extruded using a Twin-screw extruder at a range of screw speeds (80 and 160 rpm) and barrel temperatures range (80 to 140°C) with a throughput of 30 Kg hr-1 and moisture content of 25%. Arabinoxylans were extracted with water and the extraction yield and molecular weight was determined using size exclusion high-pressure liquid chromatography system. It was found that increasing screw speed from 80 rpm to 160 rpm, did not effect the extraction yield (p < 0.05) of arabinoxylan from either the wheat endosperm pentosan or the rice bran. However, the molecular weight of the extracted arabinoxylans from pentosan was found to decrease with increasing screw speed in wheat endosperm pentosan. These low molecular weight arabinoxylans have been suggested as immunomodulators.

Keywords: arabinoxylans, extrusion, wheat endosperm pentosan, rice bran

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Almutazballlah Qablan, Jihan M. Muhaidat, Bana Abu Rajab

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Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, BMI, smoking, case-control

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Authors: Wu You, Burra Venkata Durga Kumar

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This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Pavel Shcherban, Vlad Golovanov

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Nowadays, the depletion of hydrocarbon deposits on the land of the Kaliningrad region leads to active geological exploration and development of oil and natural gas reserves in the southeastern part of the Baltic Sea. LLC 'Lukoil-Kaliningradmorneft' implements a comprehensive program for the development of the region's shelf in 2014-2023. Due to heterogeneity of reservoir rocks in various open fields, as well as with ambiguous conclusions on the contours of deposits, additional geological prospecting and refinement of the recoverable oil reserves are carried out. The key element is use of an effective technique of computer stock modeling at the first stage of processing of the received data. The following step uses information for the cluster analysis, which makes it possible to optimize the field development approaches. The article analyzes the effectiveness of various methods for reserves' calculation and computer modelling methods of the offshore hydrocarbon fields. Cluster analysis allows to measure influence of the obtained data on the development of a technical and economic model for mining deposits. The relationship between the accuracy of the calculation of recoverable reserves and the need of modernization of existing mining infrastructure, as well as the optimization of the scheme of opening and development of oil deposits, is observed.

Keywords: cluster analysis, computer modelling of deposits, correction of the feasibility study, offshore hydrocarbon fields

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Asma Zaib, Saeed Khan, Ayaz Ahmed Noonari, Sehrish Bint-e-Mohsin

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Breast cancer is the most common cancer among females worldwide and is estimated that more than 450,000 deaths are reported each year. It accounts for about 14% of all female cancer deaths. Angiogenesis plays an essential role in Breast cancer development, invasion, and metastasis. Breast cancer predominantly begins in luminal epithelial cells lining the normal breast ducts. Breast carcinoma likely requires coordinated efforts of both increased proliferation and increased motility to progress to metastatic stages.Resveratrol: a natural stilbenoid, has anti-inflammatory and anticancer effects that inhibits proliferation of variety of human cancer cell lines, including breast, prostate, stomach, colon, pancreatic, and thyroid cancers.The objective of this study is:To investigate anti-neoangiogenesis effects of Resveratrol in breast cancer and to analyze inhibitory effects of resveratrol on aromatase, Erα, HER2/neu, and VEGFR.Docking is the computational determination of binding affinity between molecule (protein structure and ligand).We performed molecular docking using Swiss-Dock and to determine docking effects of (1) Resveratrol with Aromatase, (2) Resveratrol with ERα (3) Resveratrol with HER2/neu and (4) Resveratrol with VEGFR2.Docking results of resveratrol determined inhibitory effects on aromatase with binding energy of -7.28 kcal/mol which shows anticancerous effects on estrogen dependent breast tumors. Resveratrol also show inhibitory effects on ERα and HER2/new with binging energy -8.02, and -6.74 respectively; which revealed anti-cytoproliferative effects upon breast cancer. On the other hand resveratrol v/s VEGFR showed potential inhibitory effects on neo-angiogenesis with binding energy -7.68 kcal/mol, angiogenesis is the important phenomenon that promote tumor development and metastasis. Resveratrol is an anti-breast cancer agent conformed by in silico studies, it has been identified that resveratrol can inhibit breast cancer cells proliferation by acting as competitive inhibitor of aromatase, ERα and HER2 neo, while neo-angiogemesis is restricted by binding to VEGFR which authenticates the anti-carcinogenic effects of resveratrol against breast cancer.

Keywords: angiogenesis, anti-cytoproliferative, molecular docking, resveratrol

Procedia PDF Downloads 298

Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

Procedia PDF Downloads 290

Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

Procedia PDF Downloads 331

Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

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Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

Procedia PDF Downloads 417

Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: general data protection regulation, human resource management, educational system

Procedia PDF Downloads 79

Authors: Chayanika Hazarika Bordoloi

Abstract:

This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

Procedia PDF Downloads 172

Authors: Shamm Kidane, Ibrahim Abdella, Fitsum Gaim, Simon Mulugeta, Sirak Asmerom, Natnael Ambasager, Yoel Ghebrihiwot

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The call for natural language processing (NLP) systems for low-resource languages has become more apparent than ever in the past few years, with the arduous challenges still present in preparing such systems. This paper presents an improved dataset version of the Nagaoka Tigrinya Corpus for Parts-of-Speech (POS) classification system in the Tigrinya language. The size of the initial Nagaoka dataset was incremented, totaling the new tagged corpus to 118K tokens, which comprised the 12 basic POS annotations used previously. The additional content was also annotated manually in a stringent manner, followed similar rules to the former dataset and was formatted in CONLL format. The system made use of the novel approach in NLP tasks and use of the monolingually pre-trained TiELECTRA, TiBERT and TiRoBERTa transformer models. The highest achieved score is an impressive weighted F1-score of 94.2%, which surpassed the previous systems by a significant measure. The system will prove useful in the progress of NLP-related tasks for Tigrinya and similarly related low-resource languages with room for cross-referencing higher-resource languages.

Keywords: Tigrinya POS corpus, TiBERT, TiRoBERTa, conditional random fields

Procedia PDF Downloads 63