Search results for: automated fibre placement

Authors: Disha Batra

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The Industrial Revolution 4.0 is quite different, and a paradigm shift is underway in the media industry. With the advent of automated journalism and social media platforms, newspaper organizations have changed the way news was gathered and reported. The emergence of the fourth industrial revolution in the early 21st century has made the newspapers to adapt the changing technologies to remain relevant. This paper investigates the content of Indian business-papers in the era of the fourth industrial revolution and how these organizations have emerged in the time of convergence. The study is the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017 over a decade. The parametric analysis of the different parameters (source of information, use of illustrations, advertisements, layout, and framing, etc.) have been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. Further, this study reveals the effect of high-speed algorithm-based trading, the aftermath of the fourth industrial revolution on the creative and investigative aspect of delivering financial stories by these respective newspapers. The study indicates a change heading towards an ongoing paradigm shift in the business newspaper industry with an adequate change in the source of information gathering along with the subtle increase in the coverage of financial news stories over the time.

Keywords: business-papers, business news, financial news, industrial revolution 4.0.

Procedia PDF Downloads 105

Authors: Dana Page, Erica McClure, Kate Snider, Jenni Pollard, Tim Landrum, Jeff Valentine

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Extensive research has been conducted on students with emotional and behavioral disorders (EBD) and their rates of challenging behavior. In the past, however, less attention has been given to their academic achievement and outcomes. Recent research examining outcomes for students with EBD has indicated that these students receive lower grades, are less likely to pass classes, and experience higher rates of school dropout than students without disabilities and students with other high incidence disabilities. Given that between 2% and 20% of the school-age population is likely to have EBD (though many may not be identified as such), this is no small problem. Despite the need for increased examination of this population’s academic achievement, research on the actual performance of students with EBD has been minimal. This study reports the results of a meta-analysis of the limited research examining academic achievement of students with EBD, including effect sizes of assessment scores and discussion of moderators potentially impacting academic outcomes. Researchers conducted a thorough literature search to identify potentially relevant documents before screening studies for inclusion in the systematic review. Screening identified 35 studies that reported results of academic assessment scores for students with EBD. These studies were then coded to extract descriptive data across multiple domains, including placement of students, participant demographics, and academic assessment scores. Results indicated possible collinearity between EBD disability status and lower academic assessment scores, despite a lack of association between EBD eligibility and lower cognitive ability. Quantitative analysis of assessment results yielded effect sizes for academic achievement of student participants, indicating lower performance levels and potential moderators (e.g., race, socioeconomic status, and gender) impacting student academic performance. In addition to discussing results of the meta-analysis, implications and areas for future research, policy, and practice are discussed.

Keywords: students with emotional behavioral disorders, academic achievement, systematic review, meta-analysis

Procedia PDF Downloads 52

Authors: Ubani Onyedikachi, Atagana Harrison Ifeanyichukwu, Thantsha Mapitsi Silvester

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Components of oil sludge (PAHs) are known cytotoxic, mutagenic and potentially carcinogenic compounds also bacteria and fungi have been found to degrade PAHs to innocuous compounds. This study is aimed at measuring the effect of pig, cow, horse and poultry manures on the degradation in selected PAHs present in oil sludge. Soil spiked with oil sludge was co-composted differently with each manure in a ratio of 2:1 (w/w) spiked soil: manure and wood-chips in a ratio of 2:1 (w/v) spiked soil: wood-chips. Control was set up similar as the one above but without manure. The mixtures were incubated for 10 months at room temperature. Compost piles were turned weekly and moisture level was maintained at between 50% and 70%. Moisture level, pH, temperature, CO2 evolution and oxygen consumption were measured monthly and the ash content at the end of experimentation. Highest temperature reached was 27.5 °C in all compost heaps, pH ranged from 5.5 to 7.8 and CO2 evolution was highest in poultry manure at 18.78μg/dwt/day. Microbial growth and activities were enhanced; bacteria identified were Bacillus, Arthrobacter and Staphylococcus species. Percentage reduction in PAHs was measured using automated soxhlet extractor with Dichloromethane coupled with gas chromatography/mass spectrometry (GC/MS). Results from PAH measurements showed reduction between 77% and 99%. Co-composting of spiked soils with animal manures enhanced the reduction in PAHs.

Keywords: animal manures, bioremediation, co-composting, oil refinery sludge, PAHs

Procedia PDF Downloads 256

Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

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In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

Procedia PDF Downloads 101

Authors: Recep Keşli, Onur Türkyılmaz, Hayriye Tokay, Kasım Demir

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Objective: Coeliac disease (CD) is a primary small intestine disorder caused by high sensitivity to gluten which is present in the crops, characterized by inflammation in the small intestine mucosa. The goal of this study was to determine and to compare the sensitivity and specificity values of anti-endomysial IgA (EMA IgA) (IFA) and anti-tissue transglutaminase IgA (anti-tTG IgA) (ELISA) antibodies in the diagnosis of patients suspected with the CD. Methods: One thousand two hundred seventy three patients, who have applied to gastroenterology and pediatric disease polyclinics of Afyon Kocatepe University ANS Research and Practice Hospital were included into the study between 23.09.2010 and 30.05.2016. Sera samples were investigated by immunofluorescence method for EMA positiveness (Euroimmun, Luebeck, Germany). In order to determine quantitative value of Anti-tTG IgA (EIA) (Orgentec Mainz, Germany) fully automated ELISA device (Alisei, Seac, Firenze, Italy) were used. Results: Out of 1273 patients, 160 were diagnosed with coeliac disease according to ESPGHAN 2012 diagnosis criteria. Out of 160 CD patients, 120 were female, 40 were male. The EMA specificity and sensitivity were calculated as 98% and 80% respectively. Specificity and sensitivity of Anti-tTG IgA were determined as 99% and 96% respectively. Conclusion: The specificity of EMA for CD was excellent because all EMA-positive patients (n = 144) were diagnosed with CD. The presence of human anti-tTG IgA was found as a reliable marker for diagnosis and follow-up the CD. Diagnosis of CD should be established on both the clinical and serologic profiles together.

Keywords: anti-endomysial antibody, anti-tTG IgA, coeliac disease, immunofluorescence assay (IFA)

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Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li

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Transports of solid particles through the drill pipe, drill string-hole annulus and hydraulically generated fractures are important dynamic processes encountered in oil and gas well drilling and completion operations. Different from particle transport in infinite space, the transports of cuttings, proppants and formation sand are hindered by a finite boundary. Therefore, an accurate description of the particle transport behavior under the bounded wall conditions encountered in drilling and hydraulic fracturing operations is needed to improve drilling safety and efficiency. In this study, the particle settling experiments were carried out to investigate the particle settling behavior in the pipe, annulus and between the parallel plates filled with power-law fluids. Experimental conditions simulated the particle Reynolds number ranges of 0.01-123.87, the dimensionless diameter ranges of 0.20-0.80 and the fluid flow behavior index ranges of 0.48-0.69. Firstly, the wall effect of the annulus is revealed by analyzing the settling process of the particles in the annular geometry with variable inner pipe diameter. Then, the geometric continuity among the pipe, annulus and parallel plates was determined by introducing the ratio of inner diameter to an outer diameter of the annulus. Further, a unified dimensionless diameter was defined to confirm the relationship between the three different geometry in terms of the wall effect. In addition, a dimensionless term independent from the settling velocity was introduced to establish a unified explicit settling velocity model applicable to pipes, annulus and fractures with a mean relative error of 8.71%. An example case study was provided to demonstrate the application of the unified model for predicting particle settling velocity. This paper is the first study of annulus wall effects based on the geometric continuity concept and the unified model presented here will provide theoretical guidance for improved hydraulic design of cuttings transport, proppant placement and sand management operations.

Keywords: wall effect, particle settling velocity, cuttings transport, proppant transport in fracture

Procedia PDF Downloads 152

Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Agustine Melviana, Rizkita Esyanti

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Stevia plant contains steviol glycosides which is estimated to be 300 times sweeter than sucrose. However in Indonesia, conventional (in vivo) propagation of Stevia rebaudiana was not effective due to a poor result. Therefore, alternative methods to propagate S. rebaudiana plants is needed, one of it is using in vitro method. Multiplication with a large quantity of stevia biomass in relatively short period can be conducted by using TIS RITA® (Recipient for Automated Temporary Immersion System). The objective of this study was to evaluate the effect of immersion period of the medium on growth and the medium bioconversion into the production of shoot biomass. The study was conducted to determine the effect of different intensity period of medium to enhance biomass of stevia shoots. Shoot culture of S. rebaudiana was grown in full strength MS medium supplemented with 1 ppm Kinetin. RITA® bioreactors were set up with two different immersion periods, 15 min (RITA® 15) and 30 min (RITA® 30), scheduled every 6 hours and incubated for 21 days. The result indicated that immersion period affected the biomass and growth rate (µ). Thirty-minutes immersion showed greater percentage of shoot multiplication (93.44 ± 0.83%), percentage of leaf growth (85.24 ± 5.99%), growth rate (0.042 ± 0.001 g/day), and productivity (0.066 g/L medium/day) compared to that immersed in RITA® 15 min (76.90 ± 4.85%; 79.73 ± 7.76; 0.045 ± 0.004 g/day, and 0.045 g/L medium/day respectively). Enhancement of biomass in RITA® 30 reached 1,702 ± 0,114 gr, whereas in RITA® 15 only 0,953 ± 0,093 gr. Additionally, the pattern of sucrose, mineral, and inorganic compounds consumption followed the growth of plant biomass for both systems. In conclusion, the bioconversion efficiency from medium to biomass in RITA® 30 is better than RITA® 15.

Keywords: intensity period, shoot culture, Stevia rebaudiana, TIS RITA®

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Authors: Kruti Jaruriya

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Distribution of arsenic (As) and its compound and related toxicology are serious concerns. This is particularly so since millions worldwide are suffering from toxicity due to drinking of As-contaminated groundwater. The Bengal delta plain, formed by the Ganga– Padma–Meghna–Brahmaputra river basin, covering several districts of West Bengal, India and Bangladesh is considered as the worst As affected alluvial basin. However, some equally affected, if not more, areas are emerging in upper Brahmaputra plains. The present study was carried out to examine As contamination trends in the worst affected part of Assam, India. Arsenic (As) mobilization to the groundwater of Brahmaputra floodplains was investigated in Titabor, Jorhat District, located in the North Eastern part of India. The groundwater and the aquifer geochemistry were characterized. The groundwater is characterized by high dissolved Fe, Mn, and HCO-3 and low concentrations of NO-3 and SO2-4 indicating anoxic conditions prevailing in the groundwater. Fifty groundwater samples collected from shallow and deep tubewells of Titabor, Jorhat district (Assam) were examined. Along with total As, examination of concentration levels of other key parameters, viz., pH, EC, Fe, Mn , Mg2+, Ca2+, Na+, K+, PO43- , HCO-3 , NO3- ,Cl - and SO42- was also carried out. In respect to the permissible guideline of World Health Organization (WHO: As 0.01 ppm, Fe 1.0 ppm, and Mn 0.3 ppm for potable water), the range of As concentration in the groundwater varied from 0.014 to 0.604 mg/L with mean concentration 0.184 mg/L. The present study showed that out of the 50 groundwater samples,100%, 54%, and 42% were found contaminated with higher metal contents (for total As, Fe, and Mn, respectively). The results of hydrogeochemical study revealed that the reductive dissolution of MnOOH and FeOOH represents an important mechanism of arsenic release in the study area along with major cations playing an important role in leaching of As into the groundwater. Arsenic released by oxidation of pyrite, as water levels are drawn down and air enters the aquifer, contributes negligibly to the problem of As pollution. Identification of the mechanism of As release to groundwater helps to provide a framework to guide the placement of new water wells so that they will have acceptable concentrations of As.

Keywords: arsenic, assam, brahmaputra floodplain, groundwater, hydrogeochemistry

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

Procedia PDF Downloads 119

Authors: Ava Zarif Sanayei, Sedigheh Sina

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Interventional radiology (IR) uses imaging guidance, including X-rays and CT scans, to deliver therapy precisely. Most IR procedures are performed under local anesthesia and start with a small needle being inserted through the skin, which may be called pinhole surgery or image-guided surgery. There is increasing concern about radiation exposure during interventional radiology procedures due to procedure complexity. The basic aim of optimizing radiation protection as outlined in ICRP 139, is to strike a balance between image quality and radiation dose while maximizing benefits, ensuring that diagnostic interpretation is satisfactory. This study aims to estimate the equivalent doses to the main trunk of the body for the Interventional radiologist and Superintendent using LiF: Mg, Ti (TLD-100) chips at the IR department of a hospital in Shiraz, Iran. In the initial stage, the dosimeters were calibrated with the use of various phantoms. Afterward, a group of dosimeters was prepared, following which they were used for three months. To measure the personal equivalent dose to the body, three TLD chips were put in a tissue-equivalent batch and used under a protective lead apron. After the completion of the duration, TLDs were read out by a TLD reader. The results revealed that these individuals received equivalent doses of 387.39 and 145.11 µSv, respectively. The findings of this investigation revealed that the total radiation exposure to the staff was less than the annual limit of occupational exposure. However, it's imperative to implement appropriate radiation protection measures. Although the dose received by the interventional radiologist is a bit noticeable, it may be due to the reason for using conventional equipment with over-couch x-ray tubes for interventional procedures. It is therefore important to use dedicated equipment and protective means such as glasses and screens whenever compatible with the intervention when they are available or have them fitted to equipment if they are not present. Based on the results, the placement of staff in an appropriate location led to increasing the dose to the radiologist. Manufacturing and installation of moveable lead curtains with a thickness of 0.25 millimeters can effectively minimize the radiation dose to the body. Providing adequate training on radiation safety principles, particularly for technologists, can be an optimal approach to further decreasing exposure.

Keywords: interventional radiology, personal monitoring, radiation protection, thermoluminescence dosimetry

Procedia PDF Downloads 54

Authors: B.Shukir, H.Woo, P.Barzo, D.Kis

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Preoperative brain mapping in tumors involving the speech areas has an important role to reduce surgical risks. Functional magnetic resonance imaging (fMRI) is the gold standard method to localize cortical speech areas preoperatively, but its availability in clinical routine is difficult. Diffusion MRI based probabilistic tractography is available in head MRI. It’s used to segment cortical subregions by their structural connectivity. In our study, we used probabilistic tractography to localize the frontal and temporal cortical speech areas. 15 patients with left frontal tumor were enrolled to our study. Speech fMRI and diffusion MRI acquired preoperatively. The standard automated anatomical labelling atlas 3 (AAL3) cortical atlas used to define 76 left frontal and 118 left temporal potential speech areas. 4 types of tractography were run according to the structural connection of these regions to the left arcuate fascicle (FA) to localize those cortical areas which have speech functions: 1, frontal through FA; 2, frontal with FA; 3, temporal to FA; 4, temporal with FA connections were determined. Thresholds of 1%, 5%, 10% and 15% applied. At each level, the number of affected frontal and temporal regions by fMRI and tractography were defined, the sensitivity and specificity were calculated. At the level of 1% threshold showed the best results. Sensitivity was 61,631,4% and 67,1523,12%, specificity was 87,210,4% and 75,611,37% for frontal and temporal regions, respectively. From our study, we conclude that probabilistic tractography is a reliable preoperative technique to localize cortical speech areas. However, its results are not feasible that the neurosurgeon rely on during the operation.

Keywords: brain mapping, brain tumor, fMRI, probabilistic tractography

Procedia PDF Downloads 146

Authors: Carol Yue-En Ong, Angelina Hui-Min Tan, Quan Liu, Paul Chi-Lui Ho

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A public general hospital in Singapore has recently implemented an automated unit-dose machine in their inpatient dispensary, Swisslog, with the objective of reducing human error and improving patient safety. However, a concern in stability arises as tablets are removed from their original packaging (bottled loose tablets/capsules) and are repackaged into individual, clear plastic wrappers as unit doses in the system. Drugs that are light-sensitive and hygroscopic would be more susceptible to degradation as the wrapper does not offer full protection. Hence, this study was carried out to study the stability of haloperidol tablets and phenytoin capsules that are light-sensitive and hygroscopic respectively. Validated HPLC-UV assays were first established for quantification of these two compounds. The medications involved were put in the Swisslog and sampled every week for one month. The collected data was analysed and showed no degradation over time. This study also explored an alternative approach for drug stability determination-Raman spectroscopy. The advantage of Raman spectroscopy is its high time efficiency and non-destructive nature. The results suggest that drug degradation can indeed be detected using Raman microscopy, but further research is needed to establish this approach for quantification or qualification of compounds. NanoRam®, a portable Raman spectrocope was also used alongside Raman microscopy but was unsuccessful in detecting degradation in this study.

Keywords: drug stability, haloperidol, HPLC, phenytoin, raman spectroscopy, Swisslog

Procedia PDF Downloads 332

Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

Procedia PDF Downloads 82

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: N. G. I. Aroshana, S. Edirisooriya

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Construction of highway is the most emerging development tendency in Sri Lanka. With these development activities, there are a lot of environmental and social issues started. Landscape fragmentation is one of the main issues that highly effect to the environment by the construction of expressways. Sri Lankan expressway system getting effort to treat fragmented landscape by using highway crossing structures. This paper designates, a highway post construction landscape study on the effectiveness of the landscape connectivity structures to restore connectivity. Geographic Information Systems (GIS), least cost path tool has been used in the selected two plots; 25km alone the expressway to identify animal crossing paths. Animal accident data use as measure for determining the most contributed plot for landscape connectivity. Number of patches, Mean patch size, Class area use as a parameter to determine the most effective land use class to reestablish the landscape connectivity. The findings of the research express scrub, grass and marsh were the most positively affected land use typologies for increase the landscape connectivity. It represents the growth increased by 8% within the 12 years of time. From the least cost analysis within the plot one, 28.5% of total animal crossing structures are within the high resistance land use classes. Southern expressway used reinforced compressed earth technologies for construction. It has been controlled the growth of the climax community. According to all findings, it could assume that involvement of the landscape crossing structures contributes to re-establish connectivity, but it is not enough to restore the majority of disturbance performed by the expressway. Connectivity measures used within the study can use as a tool for re-evaluate future involvement of highway crossing structures. Proper placement of the highway crossing structures leads to increase the rate of connectivity. The study recommends that monitoring the all stages (preconstruction, construction and post construction) of the project and preliminary design, and the involvement of the research applied connectivity assessment strategies helps to overcome the complication regarding the re-establishment of landscape connectivity using the highway crossing structures that facilitate the growth of flora and fauna.

Keywords: landscape fragmentation, least cost path, land use analysis, landscape connectivity structures

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Authors: Sajad A. Rather, F. A. Masoodi, Rehana Akhter, S. M. Wani, Adil Gani

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Modern trend towards convenience foods has resulted in increased production and consumption of restructured meat products and are of great importance to the meat industry. In meat products fat plays an important role in cooking properties, texture & sensory scores, however, high fat contents in particular animal fats provide high amounts of saturated fatty acids and cholesterol and are associated with several types of non communicable diseases such as obesity, hypertension and coronary heart diseases. Thus, fat reduction has generally been seen as an important strategy to produce healthier meat products. This study examined the effects of reducing fat level from 20% to 10% and substituting mutton back fat with guar gum (0.5%, 1% & 1.5%) on cooking properties, proximate composition, lipid and protein oxidation, texture, microstructure and sensory characteristics of goshtaba- a traditional meat product of J & K, India were investigated and compared with high fat counterparts. Reduced- fat goshtaba samples containing guar gum had significantly (p ≤ 0.05) higher yield, less shrinkage, more moisture retention and more protein content than the control sample. TBARs and protein oxidation (carbonyl content) values of the control was significantly (p ≤ 0.05) higher than reduced fat goshtaba samples and showed a positive correlation between lipid and protein oxidation. Hardness, gumminess & chewiness of the control (20%) were significantly higher than reduced fat goshtaba samples. Microstructural differences were significant (p ≤ 0.05) between control and treated samples due to an increased moisture content in the reduced fat samples. Sensory evaluation showed significant (p ≤ 0.05) reduction in texture, flavour and overall acceptability scores of treatment products; however the scores for 0.5% and 1% treated samples were in the range of acceptability. Guar gum may also be used as a source of soluble dietary fibre in food products and a number of clinical studies have shown a reduction in postprandial glycemia and insulinemia on consumption of guar gum, with the mechanism being attributed to an increased transit time in the stomach and small intestine, which may have been due to the viscosity of the meal hindering the access of glucose to the epithelium.

Keywords: goshtaba, guar gum, traditional, fat reduction, acceptability

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Authors: Keerthilatha Pai, Sakshi Kamra

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Objectives: Determining the position of the mandibular canal prior to implant placement and surgeries of the posterior mandible are important to avoid the nerve injury. The visibility of the mandibular canal varies according to the imaging modality. Although panoramic radiography is the most common, slowly cone beam computed tomography is replacing it. This study was conducted with an aim to determine and compare the visibility of superior and inferior borders of the mandibular canal in digital panoramic radiograph, reformatted panoramic radiograph and cross-sectional images of cone beam computed tomography. Study design: digital panoramic, reformatted panoramic radiograph and cross sectional CBCT images of 25 human mandibles were evaluated for the visibility of the superior and inferior borders of the mandibular canal according to a 5 point scoring criteria. Also, the canal was evaluated as completely visible, partially visible and not visible. The mean scores and visibility percentage of all the imaging modalities were determined and compared. The interobserver and intraobserver agreement in the visualization of the superior and inferior borders of the mandibular canal were determined. Results: The superior and inferior borders of the mandibular canal were completely visible in 47% of the samples in digital panoramic, 63% in reformatted panoramic and 75.6% in CBCT cross-sectional images. The mandibular canal was invisible in 24% of samples in digital panoramic, 19% in reformatted panoramic and 2% in cross-sectional CBCT images. Maximum visibility was seen in Zone 5 and least visibility in Zone 1. On comparison of all the imaging modalities, CBCT cross-sectional images showed better visibility of superior border in Zones 2,3,4,6 and inferior border in Zones 2,3,4,6. The difference was statistically significant. Conclusion: CBCT cross-sectional images were much superior in the visualization of the mandibular canal in comparison to reformatted and digital panoramic radiographs. The inferior border was better visualized in comparison to the superior border in digital panoramic imaging. The mandibular canal was maximumly visible in posterior one-third region of the mandible and the visibility decreased towards the mental foramen.

Keywords: cone beam computed tomography, mandibular canal, reformatted panoramic radiograph, visualization

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Authors: Ada Garus

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This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Walaa Mohammed Saeed

Abstract:

Studies suggest a crosstalk between bone and metabolism through Osteocalcin (OC), a bone-derived protein that plays an important role in regulating glucose and fat metabolism. Studies relate type II Diabetes Mellitus (DMII) with Homocysteine (Hcy) and cardiovascular diseases (CVD). This study investigates the relationship between levels of OC, Hcy, and DMII in 85 subjects of which 50 were diabetic female patients (29–65 years) and 35 healthy controls. OC and Hcy levels were measured in fasting blood samples using immunoassay analyzer. Fasting serum glucose, glycated hemoglobin, lipid profile, were estimated by automated Siemens Dimension XP auto-analyzer. A significant increase in the frequency of low OC levels (p < 0.001) and high Hcy levels (p < 0.001) was detected in diabetic patients compared to controls (chi-squared test). Using ANOVA test, patients were divided into tertiles based on plasma OC and Hcy levels; fasting serum glucose varied inversely with OC but directly with Hcy tertiles (p=0.049, p=0.033 respectively). Atherogenic Index of Plasma (AIP=Log TG/HDL) predicts that diabetic patients with 36% high and 15% intermediate cardiovascular risk had increased frequency of low OC levels compared to low-risk patients (p=0.047). Another group of diabetic patients with 39% high and 11% intermediate CVD risk had increased frequency of high Hcy levels (p=0.033). A significant negative correlation existed between OC and glucose (r = -0.318; p = 0.035) while correlation between glucose level and Hcy (r = 0.851 p=0.022) was positive. Hence, low serum OC levels and high Hcy levels were associated with impaired glucose metabolism that may increase cardiovascular risk in DMII.

Keywords: osteocalcin, homocysteine, type 2 diabetes, cardiovascular

Procedia PDF Downloads 142

Authors: Oluibukun G. Ajayi, Joseph O. Odumosu, Oladimeji T. Babafemi, Azeez Z. Opeyemi, Asaleye O. Samuel

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The need for the complete automation of every procedure of surveying and most especially, its engineering applications cannot be overemphasized due to the many demerits of the conventional manual or analogue approach. This paper presents the summarized details of the development of a Route Information Management (RIM) software. The software, codenamed ‘AutoROUTE’, was encoded using Microsoft visual studio-visual basic package, and it offers complete automation of the computational procedures and plan production involved in route surveying. It was experimented using a route survey data (longitudinal profile and cross sections) of a 2.7 km road which stretches from Dama to Lunko village in Minna, Niger State, acquired with the aid of a Hi-Target DGPS receiver. The developed software (AutoROUTE) is capable of computing the various simple curve parameters, horizontal curve, and vertical curve, and it can also plot road alignment, longitudinal profile, and cross-section with a capability to store this on the SQL incorporated into the Microsoft visual basic software. The plotted plans with AutoROUTE were compared with the plans produced with the conventional AutoCAD Civil 3D software, and AutoROUTE proved to be more user-friendly and accurate because it plots in three decimal places whereas AutoCAD plots in two decimal places. Also, it was discovered that AutoROUTE software is faster in plotting and the stages involved is less cumbersome compared to AutoCAD Civil 3D software.

Keywords: automated systems, cross sections, curves, engineering construction, longitudinal profile, route surveying

Procedia PDF Downloads 128

Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: automation, customer value, heterogenic, integration, IT services, optimization, processes

Procedia PDF Downloads 100

Authors: Vinay Singh, Chandra Deo, Asit Chakrabarti, Lopamudra Sahoo, Mahak Singh, Rakesh Kumar, Dinesh Kumar, H. Bharati, Biswajit Das, V. K. Mishra

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The most widely used feed resources in poultry feed, like maize and soybean, are expensive as well as in short supply. Hence, there is a need to utilize non-conventional feed ingredients to cut down feed costs. As an alternative, brewery by-products like brewers’ dried grains are potential non-conventional feed resources. North-East India is inhabited by many tribes, and most of these tribes prepare their indigenous local brew, mostly using rice grains as the primary substrate. Choak, a homemade rice beer waste, is an excellent and cheap source of protein and other nutrients. Fresh homemade rice beer waste (rice brewer’s grain) was collected locally. The proximate analysis indicated 28.53% crude protein, 92.76% dry matter, 5.02% ether extract, 7.83% crude fibre, 2.85% total ash, 0.67% acid insoluble ash, 0.91% calcium, and 0.55% total phosphorus. A feeding trial with 5 treatments (incorporating rice beer waste at the inclusion levels of 0,10,20,30 & 40% by replacing maize and soybean from basal diet) was conducted with 25 laying hens per treatment for 16 weeks under completely randomized design in order to study the production performance, blood-biochemical parameters, immunity, egg quality and cost economics of laying hens. The results showed substantial variations (P<0.01) in egg production, egg mass, FCR per dozen eggs, FCR per kg egg mass, and net FCR. However, there was not a substantial difference in either body weight or feed intake or in egg weight. Total serum cholesterol reduced significantly (P<0.01) at 40% inclusion of rice beer waste. Additionally, the egg haugh unit grew considerably (P<0.01) when the graded levels of rice beer waste increased. The inclusion of 20% rice brewers dried grain reduced feed cost per kg egg mass and per dozen egg production by Rs. 15.97 and 9.99, respectively. Choak (homemade rice beer waste) can thus be safely incorporated into the diet of laying hens at a 20% inclusion level for better production performance and cost-effectiveness.

Keywords: choak, rice beer waste, laying hen, production performance, cost economics

Procedia PDF Downloads 46

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

Procedia PDF Downloads 439

Authors: Erika Duggan

Abstract:

A Major Hospital had identified that there was no standard process for handling a patient’s medication that they brought with them to the hospital. It was also identified that each floor was handling the patient’s medication differently and storing it in multiple locations. Based on this disconnect many patients were leaving the hospital without their medication. The project team was tasked with creating a cohesive process to send a patient’s unneeded medication home on admission, storing any of the patient’s medication that could not be sent home, storing any of the patient’s medication for inpatient administration, and sending all of the patient’s medication home on discharge. The project team consisted of pharmacists, RNs, LPNs, members from nursing informatics and a project engineer and followed a DMAIC framework. Working together observations were performed to identify what was working and not working on the different floors which resulted in process maps. Using the multidisciplinary team, brainstorming, including affinity diagramming and other lean six sigma techniques, the best process for receiving, storing, and returning the medication was created. It was highlighted that being able to track the medication throughout the patient’s stay would be beneficial and would help make sure the medication left with the patient on discharge. Using an automated medications dispensing system would help store, and track patient’s medications. Also, the use of a specific order that would show up on the discharge instructions would assist the front line staff in retrieving the medication from a set location and sending it home with the patient. This new process will effectively streamline the admission and discharge process for patients who brought their medication with them as well as effectively tracking the medication during the patient’s stay. As well as increasing patient safety as it relates to medication administration.

Keywords: lean six sigma, medication dispensing, process improvement, process mapping

Procedia PDF Downloads 247

Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

Abstract:

Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

Procedia PDF Downloads 124

Authors: Zhichao Song, Swanand Vaidya

Abstract:

Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

Procedia PDF Downloads 97