Search results for: particle image velocimetry (PIV)

Authors: Vaibhav Barve

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Reversible information hiding has drawn a lot of interest as of late. Being reversible, we can restore unique computerized data totally. It is a plan where mystery data is put away in digital media like image, video, audio to maintain a strategic distance from unapproved access and security reason. By and large JPEG bit stream is utilized to store this key data, first JPEG bit stream is encrypted into all around sorted out structure and then this secret information or key data is implanted into this encrypted region by marginally changing the JPEG bit stream. Valuable pixels suitable for information implanting are computed and as indicated by this key subtle elements are implanted. In our proposed framework we are utilizing RC4 algorithm for encrypting JPEG bit stream. Encryption key is acknowledged by framework user which, likewise, will be used at the time of decryption. We are executing enhanced least significant bit supplanting steganography by utilizing genetic algorithm. At first, the quantity of bits that must be installed in a guaranteed coefficient is versatile. By utilizing proper parameters, we can get high capacity while ensuring high security. We are utilizing logistic map for shuffling of bits and utilization GA (Genetic Algorithm) to find right parameters for the logistic map. Information embedding key is utilized at the time of information embedding. By utilizing precise picture encryption and information embedding key, the beneficiary can, without much of a stretch, concentrate the incorporated secure data and totally recoup the first picture and also the original secret information. At the point when the embedding key is truant, the first picture can be recouped pretty nearly with sufficient quality without getting the embedding key of interest.

Keywords: data embedding, decryption, encryption, reversible data hiding, steganography

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Authors: Erhong Sun, Xuchun Ye

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Technophobia, namely the fear or dislike of modern advanced technologies, plays a central role in age-related digital divides and is considered a new risk factor for older adults, which can affect the daily lives of people through low adherence to digital living. Indeed, there is considerable heterogeneity in the group of older adults who feel technophobia. Therefore, the aim of this study was to identify different technophobia typologies of older people and to examine their associations with the subjective age factor. A sample of 704 retired elderly over the age of 55 was recruited in China. Technophobia and subjective age were assessed with a questionnaire, respectively. Latent profile analysis was used to identify technophobia subgroups, using three dimensions including techno-anxiety, techno-paranoia, and privacy concerns as indicators. The association between the identified technophobia subgroups and subjective age was explored. In summary, four different technophobia typologies were identified among older adults in China. Combined with an investigation of personal background characteristics and subjective age, it draws a more nuanced image of the technophobia phenome among older adults in China. First, not all older adults suffer from technophobia, with about half of the elderly subjects belonging to the profiles of “Low-technophobia” and “Medium-technophobia.” Second, privacy concern plays an important role in the classification of technophobia among older adults. Third, subjective age might be a protective factor for technophobia in older adults. Although the causal direction between identified technophobia typologies and subjective age remains uncertain, our suggests that future interventions should better focus on subjective age by breaking the age stereotype of technology to reduce the negative effect of technophobia on older. Future development of this research will involve extensive investigation of the detailed impact of technophobia in senior populations, measurement of the negative outcomes, as well as formulation of innovative educational and clinical pathways.

Keywords: technophobia, older adults, latent profile analysis, subjective age

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Authors: Quoc Hung Le Pham

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Human beings are motivated to satisfy the physiological needs and psychological needs. In the fundamental needs, bodily excretion is the most basic one, while physiological excretion refers to the final products produced in the process of discharging the body. This physiological process is a common human phenomenon. For instance, bodily secretion is totally natural, but people of various nationalities through the times avoid saying it directly. Terms like ‘shit’ are often negatively regarded as dirty, smelly and vulgar; it will lead people to negative thinking. In fact, it is in the psychology of human beings to avoid such unsightly terms. Especially in social situations where you have to take care of your image, and you have to release. The best way to solve this is to approach the use of euphemism. People prefer to say it as ‘answering nature's call’ or ‘to pass a motion’ instead. Chinese and Vietnamese nations are referring to use euphemisms to replace bodily secretions, so this research will take this phenomenon as the object aims to explore the similarities and dissimilarities between two languages euphemism. The basic of the niche of this paper is human physiological phenomenon excretion. As the preliminary results show, in expressing bodily secretions the deeply impacting factor is language and cultural factors. On language factor terms, two languages are using assonance to replace human nature discharge, whilst the dissimilarities are metonymy, loan word and personification. On culture factor terms, the convergences are metonymy and application of the semantically-contrary-word-euphemism, whilst the difference is Chinese euphemism using allusion but Vietnamese euphemism does not.

Keywords: cultural factors, euphemism, human needs, language factors

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Authors: Kheireddine El-Boubbou

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Drug delivery to target human acute myeloid leukemia (AML) using a nanoparticulate chemotherapeutic formulation that can deliver drugs selectively to AML cancer is hugely needed. In this work, we report the development of a nanoformulation made of polymeric-stabilized multifunctional magnetic iron oxide nanoparticles (PMNP) loaded with the anticancer drug Doxorubicin (Dox) as a promising drug carrier to treat AML. Dox@PMNP conjugates simultaneously exhibited high drug content, maximized fluorescence, and excellent release properties. Nanoparticulate uptake and cell death following addition of Dox@PMNPs were then evaluated in different types of human AML target cells, as well as on normal human cells. While the unloaded MNPs were not toxic to any of the cells, Dox@PMNPs were found to be highly toxic to the different AML cell lines, albeit at different inhibitory concentrations (IC₅₀ values), but showed very little toxicity towards the normal cells. In comparison, free Dox showed significant potency concurrently to all the cell lines, suggesting huge potentials for the use of Dox@PMNPs as selective AML anticancer cargos. Live confocal imaging, fluorescence and electron microscopy confirmed that Dox is indeed delivered to the nucleus in relatively short periods of time, causing apoptotic cell death. Importantly, this targeted payload may potentially enhance the effectiveness of the drug in AML patients and may further allow physicians to image leukemic cells exposed to Dox@PMNPs using MRI.

Keywords: magnetic nanoparticles, drug delivery, acute myeloid leukemia, iron oxide, cancer nanotherapy

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Authors: Driss Haddouche

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Pastoral crisis in Algeria has its origins in rangeland degradation which are the main factor in any activity in the steppe zones. Indeed, faced with the increasing human and animal population on a living space smaller and smaller, there is an overuse of what remains of the steppe range lands, consequently the not sustainability of biomass production. Knowing the amount of biomass available, the practice of grazing options, taking into account the use of "Use Factor" factor remains an essential method for managing pastoral resources. This factor has three options: at 40% Conservative pasture; at 60 % the beginning of overgrazing; at 80% destructive grazing. Accessibility on the pasture is based on our field observations of a type any flock along a grazing cycle. The main purpose of these observations is to highlight the speed of herd grazing situation. Several individuals from the herd were timed to arrive at an average duration of about 5 seconds to move between two tufts of grass, separated by a distance of one meter. This gives a rate of 5 s/m (0.72 km/h) flat. This speed varies depending on the angle of the slope. Knowing the speed and slope of each pixel of the study area, given by the digital elevation model of Spot Image (MNE) and whose pitch is 15 meters, a map of pasture according to the distances is generated. Knowing the stocking and biomass available, the examination of the common Mécheria at regular distances (8.64 km or 12 hours of grazing, 17.28 km or 24 hours of grazing and 25.92 Km or 36 hours of grazing), offers three different options (conservation grazing resource: utilization at 40%; overgrazing statements for use at 60% and grazing destructive for use by more than 80%) for each distance traveled by sheep from the starting point is the town of Mécheria.

Keywords: pastoral crisis, biomass, animal charge, use factor, Algeria

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Authors: Zahra Asgharpour, Eric Renteria, Sebastian De Boodt

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There is a growing trend towards personalization of medical care, as evidenced by the emphasis on outcomes based medicine, the latest developments in CT and MR imaging and personalized treatment in a variety of surgical disciplines. 3D Printing has been introduced and applied in the medical field since 2000. The first applications were in the field of dental implants and custom prosthetics. According to recent publications, 3D printing in the medical field has been used in a wide range of applications which can be organized into several categories including implants, prosthetics, anatomical models and tissue bioprinting. Some of these categories are still in their infancy stage of the concept of proof while others are in application phase such as the design and manufacturing of customized implants and prosthesis. The approach of 3D printing in this category has been successfully used in the health care sector to make both standard and complex implants within a reasonable amount of time. In this study, some of the clinical applications of 3D printing in design and manufacturing of a patient-specific hip implant would be explained. In cases where patients have complex bone geometries or are undergoing a complex revision on hip replacement, the traditional surgical methods are not efficient, and hence these patients require patient-specific approaches. There are major advantages in using this new technology for medical applications, however, in order to get this technology widely accepted in medical device industry, there is a need for gaining more acceptance from the medical device regulatory offices. This is a challenge that is moving onward and will help the technology find its way at the end as an accepted manufacturing method for medical device industry in an international scale. The discussion will conclude with some examples describing the future directions of 3D Medical Printing.

Keywords: CT/MRI, image processing, 3D printing, medical devices, patient specific implants

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Authors: Camila Hurtado, Maria A. Morales, Diego Torres, L.H. Reyes, Alejandro Maranon, Alicia Porras

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This work presents the physical and chemical characterization of beer brand fibers and the properties of novel composite materials made of these fibers and polylactic acid (PLA). Treated and untreated fibers were physically characterized in terms of their moisture content (ASTM D1348), density, and particle size (ASAE S319.2). A chemical analysis following TAPPI standards was performed to determine ash, extractives, lignin, and cellulose content on fibers. Thermal stability was determined by TGA analysis, and an FTIR was carried out to check the influence of the alkali treatment in fiber composition. An alkali treatment with NaOH (5%) of fibers was performed for 90 min, with the objective to improve the interfacial adhesion with polymeric matrix in composites. Composite materials based on either treated or untreated beer brand fibers and polylactic acid (PLA) were developed characterized in tension (ASTM D638), bending (ASTM D790) and impact (ASTM D256). Before composites manufacturing, PLA and brand beer fibers (10 wt.%) were mixed in a twin extruder with a temperature profile between 155°C and 180°C. Coupons were manufactured by compression molding (110 bar) at 190°C. Physical characterization showed that alkali treatment does not affect the moisture content (6.9%) and the density (0.48 g/cm³ for untreated fiber and 0.46 g/cm³ for the treated one). Chemical and FTIR analysis showed a slight decrease in ash and extractives. Also, a decrease of 47% and 50% for lignin and hemicellulose content was observed, coupled with an increase of 71% for cellulose content. Fiber thermal stability was improved with the alkali treatment at about 10°C. Tensile strength of composites was found to be between 42 and 44 MPa with no significant statistical difference between coupons with either treated or untreated fibers. However, compared to neat PLA, composites with beer bran fibers present a decrease in tensile strength of 27%. Young modulus increases by 10% with treated fiber, compared to neat PLA. Flexural strength decreases in coupons with treated fiber (67.7 MPa), while flexural modulus increases (3.2 GPa) compared to neat PLA (83.3 MPa and 2.8 GPa, respectively). Izod impact test results showed an improvement of 99.4% in coupons with treated fibers - compared with neat PLA.

Keywords: beer bran, characterization, green composite, polylactic acid, surface treatment

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Authors: Chen-En Lin, Lih-Rou Rau, Jiunn-Woei Liaw, Shiao-Wen Tsai

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The unique optical properties of plasmon resonance metallic particles have attracted considerable applications in the fields of physics, chemistry and biology. Metal-Enhanced Fluorescence (MEF) effect is one of the useful applications. MEF effect stated that fluorescence intensity can be quenched or be enhanced depending on the distance between fluorophores and the metal nanoparticles. Silver nanoparticles have used widely in antibacterial studies. However, the major limitation for silver nanoparticles (AgNPs) in biomedical application is well-known cytotoxicity on cells. There were numerous literatures have been devoted to overcome the disadvantage. The aim of the study is to evaluate the cytotoxicity and biocompatibility of silica coated AgNPs against NIH-3T3 cells. The results were shown that NIH-3T3 cells started to detach, shrink, become rounded and finally be irregular in shape after 24 h of exposure at 10 µg/ml AgNPs. Besides, compared with untreated cells, the cell viability significantly decreased to 60% and 40% which were exposed to 10 µg/ml and 20 µg/ml AgNPs respectively. The result was consistent with previously reported findings that AgNPs induced cytotoxicity was concentration dependent. However, the morphology and cell viability of cells appeared similar to the control group when exposed to 20 µg/ml of silica coated AgNPs. We further utilized the dark-field hyperspectral imaging system to analysis the optical properties of the intracellular nanoparticles. The image displayed that the red shift of the surface plasmonic resonances band of the enclosed AgNPs further confirms the agglomerate of the AgNPs rather than their distribution in cytoplasm. In conclusion, the study demonstrated the silica coated of AgNPs showed well biocompatibility and significant lower cytotoxicity compared with bare AgNPs.

Keywords: silver nanoparticles, silica, cell viability, morphology

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Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

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Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

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Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

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Authors: Thomas Arink, Isam Janajreh

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The petroleum industry generates significant amounts of waste in the form of drill cuttings, contaminated soil and oily sludge. Drill cuttings are a product of the off-shore drilling rigs, containing wet soil and total petroleum hydrocarbons (TPH). Contaminated soil comes from different on-shore sites and also contains TPH. The oily sludge is mainly residue or tank bottom sludge from storage tanks. The two main treatment methods currently used are incineration and thermal desorption (TD). Thermal desorption is a method where the waste material is heated to 450ºC in an anaerobic environment to release volatiles, the condensed volatiles can be used as a liquid fuel. For the thermal desorption unit dry contaminated soil is mixed with moist drill cuttings to generate a suitable mixture. By thermo gravimetric analysis (TGA) of the TD feedstock it was found that less than 50% of the TPH are released, the discharged material is stored in landfill. This study proposes co-gasification of petroleum waste with waste tires as an alternative to thermal desorption. Co-gasification with a high-calorific material is necessary since the petroleum waste consists of more than 60 wt% ash (soil/sand), causing its calorific value to be too low for gasification. Since the gasification process occurs at 900ºC and higher, close to 100% of the TPH can be released, according to the TGA. This work consists of three parts: 1. a mathematical gasification model, 2. a reactive flow CFD model and 3. experimental work on a drop tube reactor. Extensive material characterization was done by means of proximate analysis (TGA), ultimate analysis (CHNOS flash analysis) and calorific value measurements (Bomb calorimeter) for the input parameters of the mathematical and CFD model. The mathematical model is a zero dimensional model based on Gibbs energy minimization together with Lagrange multiplier; it is used to find the product species composition (molar fractions of CO, H2, CH4 etc.) for different tire/petroleum feedstock mixtures and equivalence ratios. The results of the mathematical model act as a reference for the CFD model of the drop-tube reactor. With the CFD model the efficiency and product species composition can be predicted for different mixtures and particle sizes. Finally both models are verified by experiments on a drop tube reactor (1540 mm long, 66 mm inner diameter, 1400 K maximum temperature).

Keywords: computational fluid dynamics (CFD), drop tube reactor, gasification, Gibbs energy minimization, petroleum waste, waste tires

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Authors: Aasaithambi Kalaiselvi, Michael Gabriel Paulraj, Ekambaram Nakkeeran

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Emergences of mosquito vector-borne diseases are considered as a perpetual problem globally in tropical countries. The outbreak of several diseases such as chikungunya, zika virus infection and dengue fever has created a massive threat towards the living population. Frequent usage of synthetic insecticides like Dichloro Diphenyl Trichloroethane (DDT) eventually had its adverse harmful effects on humans as well as the environment. Since there are no perennial vaccines, prevention, treatment or drugs available for these pathogenic vectors, WHO is more concerned in eradicating their breeding sites effectively without any side effects on humans and environment by approaching plant-derived natural eco-friendly bio-insecticides. The aim of this study is to investigate the larvicidal potency of Cinnamomum verum essential oil (CEO) loaded niosomes. Cholesterol and surfactant variants of Span 20, 60 and 80 were used in synthesizing CEO loaded niosomes using Transmembrane pH gradient method. The synthesized CEO loaded niosomes were characterized by Zeta potential, particle size, Fourier Transform Infrared Spectroscopy (FT-IR), GC-MS and SEM analysis to evaluate charge, size, functional properties, the composition of secondary metabolites and morphology. The Z-average size of the formed niosomes was 1870.84 nm and had good stability with zeta potential -85.3 meV. The entrapment efficiency of the CEO loaded niosomes was determined by UV-Visible Spectrophotometry. The bio-potency of CEO loaded niosomes was treated and assessed against gram-positive (Bacillus subtilis) and gram-negative (Escherichia coli) bacteria and fungi (Aspergillus fumigatus and Candida albicans) at various concentrations. The larvicidal activity was evaluated against II to IV instar larvae of Aedes aegypti, Anopheles stephensi and Culex quinquefasciatus at various concentrations for 24 h. The mortality rate of LC₅₀ and LC₉₀ values were calculated. The results exhibited that CEO loaded niosomes have greater efficiency against mosquito larvicidal activity. The results suggest that niosomes could be used in various applications of biotechnology and drug delivery systems with greater stability by altering the drug of interest.

Keywords: Cinnamomum verum, niosomes, entrapment efficiency, bactericidal and fungicidal, mosquito larvicidal activity

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Hsiu-Chuan Hsueh, Kuei-Feng Shen Jr., Chia-Ling Chao, Hui-Chuan Pan

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This article described a 75 years old woman who has suffered from intestinal perforation and accepted surgery with temporary enterostomy, the operation makes her depressed, refused relatives and friend's care, facing low willingness to participate in various activities due to fear of changing body appearance caused by surgery and leave enterostomy. The author collected information through observation talks, physical evaluation, and medical records during the period of care from November 14 to November 30, 2016, we used the four aspects of physiology, psychology, society and spirituality as a whole sexual assessment to establish the nursing problems of patient, included of acute pain, disturbance of body image,coping ineffective individual. For patient care issues, to encouraged case to express their inner feelings and take part in self-care programs through providing good therapeutic interpersonal relationships with their families. However, it provided clear information about the disease and follow-up treatment plan, give compliments in a timely manner, enhanced self-confidence of individual cases and their motivation to participate in self-care of stoma, further face the disease in a positive manner. At the same time, cross-section team care model and individual care measures were developed to enhance the care skills after returning home and at the same time assist the individual in facing the psychological impact caused by stoma. Hope to provide this experience, as a reference for the future care of the disease.

Keywords: enterostomy, intestinal perforation, nursing experience, ostomy

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Authors: Jin-Hui Lee, Myung-Min Oh

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The application of temporary abiotic stresses before crop harvest is a potential strategy to enhance phytochemical content. The objective of this study was to determine the effect of various UV-A LED lights on the growth and content of bioactive compounds in kale (Brassica oleracea var. acephala). Fourteen-day-old kale seedlings were cultivated in a plant factory with artificial lighting (air temperature of 20℃, relative humidity of 60%, photosynthesis photon flux density (PPFD) of 125 µmol·m⁻²·s⁻¹) for 3 weeks. Kale plants were irradiated by four types of UV-A LEDs (peak wavelength; 365, 375, 385, and 395 nm) with 30 W/m² for 7 days. As a result, image chlorophyll fluorescence (Fv/Fm) value of kale leaves was lower as the UV-A LEDs peak wavelength was shorter. Fresh and dry weights of shoots and roots of kale plants were significantly higher in the plants under UV-A than the control at 7 days of treatment. In particular, the growth was significantly increased with a longer peak wavelength of the UV-A LEDs. The results of leaf area and specific leaf weight showed a similar pattern with those of growth characteristics. Chlorophyll content was highest in kale leaves subjected to UV-A LEDs with the peak wavelength of 395 nm at 3 days of treatment compared with the control. Total phenolic contents of UV-A LEDs with the peak wavelength of 395 nm at 5 and 6 days of treatment were 44% and 47% higher than those of the control, respectively. Antioxidant capacity showed almost the same pattern as the results of total phenol content. The activity of phenylalanine ammonia-lyase was approximately 11% and 8% higher in the UV-A LEDs with the peak wavelength of 395 nm compared to the control at 5 and 6 days of treatment, respectively. Our results imply that the UV-A LEDs with relative longer peak wavelength were effective to improve growth as well as the content of bioactive compounds of kale plants.

Keywords: bioactive compounds, growth, Kale, UV-A LEDs

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Authors: Shailly Kumar

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Gender is a social construction resulting in defining roles and responsibilities to carried out according to masculine and feminine traits. The main aim of the study was to explore gender awareness among college going students of Delhi. The objectives of studies were to find out (i) the understanding of term gender and roles and responsibilities associated with male and female as masculine and feminine traits in our society. (ii)Gender images representing the attributes and characteristics attached to particular gender. (iii) Gender discrimination prevailing among girls and boys in our society. (iv)Gender stereotypes resulting in gendering with respect to religion, culture, family and media. The sample of study consisted of 100 undergraduate college girl students. The findings of study stated that the students had this understanding that sex is a natural phenomenon and gender is socially constructed. Gender defines the roles and responsibilities among two sexes. On a gender image students concluded that males are represented as a powerful members of society showing physical strength and violence, force and society gave the power to men oppress and subjugate women in society that's why women are treated inferior and given secondary position in society. On gender discrimination, girl students stated that they faced discrimination at all level such as family, media ,education, workplace etc .There is strong prevailing gender stereotypes among girls and boys with respect to religious practices, choice of career ,preference of child etc. This study concluded that students were aware of gendered practices in various domains of life. The study helped to interpret the notions and perceptions of students towards gendering of social spaces and in their lives.

Keywords: gender, gender awareness, gender role, masculinity and feminity

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Authors: Vijaykumar M. Baragi, Ramtilak Gattu, Gabriela Trifan, John L. Woodard, K. Meyers, Tim S. Halstead, Eric Hipple, Ewart Mark Haacke, Randall R. Benson

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NFL players, by virtue of their exposure to repetitive head injury, are at least twice as likely to develop Alzheimer's disease (AD) and dementia as the general population. Early recognition and intervention prior to onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Since AD is thought to have a long preclinical incubation period, the aim of the current research was to determine whether former NFL players, referred to a depression center, showed evidence of incipient dementia in their structural imaging prior to diagnosis of dementia. Thus, to identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a comprehensive volumetric analysis using a cohort of early stage AD patients (ADNI) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A cohort of 46 former NFL players’ brain MRIs were then interrogated using the AD fingerprint. Brain scans were done using a T1-weighted MPRAGE sequence. The Free Surfer image analysis suite (version 6.0) was used to obtain the volumetric and cortical thickness data. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients vs. healthy controls. Of the 46 former NFL players, 19 (41%) demonstrated a greater than expected number of atrophied/dilated AD regions when compared with age-matched controls, presumably reflecting AD pathology.

Keywords: alzheimers, neuroimaging biomarkers, traumatic brain injury, free surfer, ADNI

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Authors: Md. Shakhawat Hossain, Jimma Hossain, Md. Naushad Ali

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Acute pancreatitis is a dangerous medical emergency in the practice of gastroenterology. Management of acute pancreatitis needs multidisciplinary approach with support starts from emergency to ICU. So, there is a chance of mismanagement in every steps, especially in low resource settings. Other factors such as patient’s financial condition, education, social custom, transport facility, referral system from periphery may also challenge the current guidelines for management. The present study is intended to determine the clinico-pathological profile, severity assessment and challenges of management of acute pancreatitis in a government laid tertiary care hospital to image the real scenario of management in a low resource place. A total 100 patients of acute pancreatitis were studied in this prospective study, held in the Department of Gastroenterology, Rangpur medical college hospital, Bangladesh from July 2017 to July 2018 within one year. Regarding severity, 85 % of the patients were mild, whereas 13 were moderately severe, and 2 had severe acute pancreatitis according to the revised Atlanta criteria. The most common etiologies of acute pancreatitis in our study were gall stone (15%) and biliary sludge (15%), whereas 54% were idiopathic. The most common challenges we faced were delay in hospital admission (59%) and delay in hospital diagnosis (20%). Others are non-adherence of patient party, and lack of investigation facility, physician’s poor knowledge about current guidelines. We were able to give early aggressive fluid to only 18% of patients as per current guideline. Conclusion: Management of acute pancreatitis as per guideline is challenging when optimum facility is lacking. So, modified guidelines for assessment and management of acute pancreatitis should be prepared for low resource setting.

Keywords: acute pancreatitis, challenges of management, severity, prognosis

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Authors: Anand Choudhary

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Following the global economic crisis in 2008, businesses and more especially the big multinational conglomerates were increasingly viewed by the people world over as one of the major causes of the economic problems faced by millions globally, in terms of job loss and lifetime savings being wiped out as banks and pension funds went bankrupt and people stared at an insecure financial future. This caused a lot of resentment in the public against big businesses and fueled several protest movements by the people such as “Occupy Wall Street” in different parts of the world. This forced the big businesses to respond to the challenge by adopting more people-centric policies and initiatives for local communities in societies where they operate as part of their corporate social responsibility (CSR), in order to regain their social acceptance among the people whilst earning their ‘social license to operate’. The current paper studies many of such large MNCs across the United States of America, India and South Africa, which changed the way they did business earlier, following the global economic crisis in 2008, by incorporating capacity building initiatives for local communities as part of their CSR strategy and explores whether it has contributed to improving their financial performance. It is a conceptual research paper using secondary source data. The findings reveal that there is a positive correlation between the companies’ corporate social performance and corporate financial performance. In addition, the findings also bring to light that the MNCs examined as part of the current paper have improved their image in the eyes of their stakeholders following the change in their CSR strategy and initiatives.

Keywords: corporate social responsibility (CSR), Corporate Social Performance (CSP), Corporate Financial Performance (CFP), local communities

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Marcela Ondova, Adriana Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO2 emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills. Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: life cycle assessment, fly ash, waste, concrete pavements

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Authors: Michal Lach, Maria Hebdowska-Krupa, Justyna Stefanek, Artur Stanek, Anna Stefanska, Janusz Mikula, Marek Hebda

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Limited resources of raw materials determine the necessity of obtaining materials from other sources. In this area, the most known and widespread are recycling processes, which are mainly focused on the reuse of material. Another possible solution used in various companies to achieve improvement in sustainable development is waste-free production. It involves the production exclusively from such materials, whose waste is included in the group of renewable raw materials. This means that they can: (i) be recycled directly during the manufacturing process of further products or (ii) be raw material obtained by other companies for the production of alternative products. The article presents the possibility of using post-production clay from the Jurassic limestone deposit "Raciszyn II" as a raw material for the production of alkali activated materials (AAM). Such products are currently increasingly used, mostly in various building applications. However, their final properties depend significantly on many factors; the most important of them are: chemical composition of the raw material, particle size, specific surface area, type and concentration of the activator and the temperature range of the heat treatment. Conducted mineralogical and chemical analyzes of clay from the “Raciszyn II” deposit confirmed that this material, due to its high content of aluminosilicates, can be used as raw material for the production of AAM. In order to obtain the product with the best properties, the optimization of the clay calcining process was also carried out. Based on the obtained results, it was found that this process should occur in the range between 750 oC and 800 oC. The use of a lower temperature causes getting a raw material with low metakaolin content which is the main component of materials suitable for alkaline activation processes. On the other hand, higher heat treatment temperatures cause thermal dissociation of large amounts of calcite, which is associated with the release of large amounts of CO2 and the formation of calcium oxide. This compound significantly accelerates the binding process, which consequently often prevents the correct formation of geopolymer mass. The effect of the use of various activators: (i) NaOH, (ii) KOH and (iii) a mixture of KOH to NaOH in a ratio of 10%, 25% and 50% by volume on the compressive strength of the AAM was also analyzed. Obtained results depending on the activator used were in the range from 25 MPa to 40 MPa. These values are comparable with the results obtained for materials produced on the basis of Portland cement, which is one of the most popular building materials.

Keywords: alkaline activation, aluminosilicates, calcination, compressive strength

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

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Authors: Nour Tawil, Sandra Weber, Kirsten K. Roessler, Martin Mau, Simone Kuhn

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The link between “quality” residential environments and human health and well-being has long been proposed. While the physical properties of a sound environment have been fairly defined, little focus has been given to the psychological impact of architectural elements. Recently, studies have investigated the response to architectural parameters, using measures of physiology, brain activity, and emotion. Results showed different aspects of interest: detailed and open versus blank and closed facades, patterns in perceiving different elements, and a visual bias for capturing faces in buildings. However, in the absence of a consensus on methodologies, the available studies remain unsystematic and face many limitations regarding the underpinning psychological mechanisms. To bridge some of these gaps, an online study was launched to investigate design features that influence the aesthetic judgement and emotional evaluation of house facades, using a well-controlled stimulus set of Canadian houses. A methodical modelling of design features will be performed to extract both high and low level image properties, in addition to segmentation of layout-related features. 300 participants from Canada, Denmark, and Germany will rate the images on twelve psychological dimensions representing appealing aspects of a house. Subjective ratings are expected to correlate with specific architectural elements while controlling for typicality and familiarity, and other individual differences. With the lack of relevant studies, this research aims to identify architectural elements of beneficial qualities that can inform design strategies for optimized residential spaces.

Keywords: architectural elements, emotions, psychological response, residential facades.

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Ravi Inder Singh

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Due to high heat transfer rate, high carbon utilizing efficiency, fuel flexibilities and other advantages numerous circulating fluidized bed boilers have grown up in India in last decade. Many companies like BHEL, ISGEC, Thermax, Cethar Limited, Enmas GB Power Systems Projects Limited are making CFBC and installing the units throughout the India. Due to complexity many problems exists in CFBC units and only few have been reported. Agglomeration i.e clinker formation in riser, loop seal leg and stripper ash coolers is one of problem industry is facing. Proper documentation is rarely found in the literature. Circulating fluidized bed (CFB) boiler bottom ash contains large amounts of physical heat. While the boiler combusts the low-calorie fuel, the ash content is normally more than 40% and the physical heat loss is approximately 3% if the bottom ash is discharged without cooling. In addition, the red-hot bottom ash is bad for mechanized handling and transportation, as the upper limit temperature of the ash handling machinery is 200 °C. Therefore, a bottom ash cooler (BAC) is often used to treat the high temperature bottom ash to reclaim heat, and to have the ash easily handled and transported. As a key auxiliary device of CFB boilers, the BAC has a direct influence on the secure and economic operation of the boiler. There are many kinds of BACs equipped for large-scale CFB boilers with the continuous development and improvement of the CFB boiler. These ash coolers are water cooled ash cooling screw, rolling-cylinder ash cooler (RAC), fluidized bed ash cooler (FBAC).In this study prototype of a novel stripper ash cooler is studied. The Circulating Fluidized bed Ash Coolers (CFBAC) combined the major technical features of spouted bed and bubbling bed, and could achieve the selective discharge on the bottom ash. The novel stripper ash cooler is bubbling bed and it is visible cold test rig. The reason for choosing cold test is that high temperature is difficult to maintain and create in laboratory level. The aim of study to know the flow pattern inside the stripper ash cooler. The cold rig prototype is similar to stripper ash cooler used industry and it was made after scaling down to some parameter. The performance of a fluidized bed ash cooler is studied using a cold experiment bench. The air flow rate, particle size of the solids and air distributor type are considered to be the key parameters of the operation of a fluidized bed ash cooler (FBAC) are studied in this.

Keywords: CFD, Eulerian-Eulerian, Eulerian-Lagraingian model, parallel simulations

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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