Search results for: dataset production

Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

Procedia PDF Downloads 177

Authors: Raj Raghupathy

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Recurrent Spontaneous Miscarriage (RSM) is a common form of pregnancy loss, 50% of which are due to ‘unexplained’ causes. Evidence exists to suggest that RSM may be caused by immunologic factors such as cytokines which are critical molecules of the immune system, with an impressive array of capabilities. An association appears to exist between Th2-type reactivity (mediated by Th2 or anti-inflammatory cytokines) and normal, successful pregnancy, and between unexplained RSM and Th1 cytokine dominance. If pro-inflammatory cytokines are indeed associated with pregnancy loss, the suppression of these cytokines, and thus the ‘redirection’ of maternal reactivity, may help prevent cytokine-mediated pregnancy loss. The objective of this study was to explore the possibility of modulating cytokine production using Dydrogesterone (Duphaston®), an orally-administered progestogen. Peripheral blood mononuclear cells from 34 women with a history of at least 3 unexplained recurrent miscarriages were stimulated in vitro with a mitogen (to elicit cytokine production) in the presence and absence of dydrogesterone. Levels of selected pro- and anti-inflammatory cytokines produced by peripheral blood mononuclear cells were measured after exposure to these progestogens. Dydrogesterone down-regulates the production of pro-inflammatory cytokines and up-regulates the production of anti-inflammatory cytokines. The ratios of Th2 to Th1 cytokines are markedly elevated in the presence of dydrogesterone, indicating a shift from potentially harmful maternal Th1 reactivity to a more pregnancy-conducive Th2 profile. We used a progesterone receptor antagonist to show that this cytokine-modulating effect of dydrogesterone is mediated via the progesterone receptor. Dydrogesterone also induces the production of the Progesterone-Induced Blocking Factor (PIBF); lymphocytes exposed to PIBF produce higher levels of Th2 cytokines, affecting a Th1 → Th2 cytokine shift which could be favourable to the success of pregnancy. We conclude that modulation of maternal cytokine production profiles is possible with dydrogesterone which has the merits that it can be administered orally and that it is safe.

Keywords: cytokines, dydrogesterone, progesterone, recurrent spontaneous miscarriage

Procedia PDF Downloads 274

Authors: Maricon E. Gepolani, Edna A. Aguilar, Pearl B. Sanchez, Enrico P. Supangco

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Intercropping farming system and biofertilizer application are sustainable agricultural practices that increase farm productivity by improving the yield performance of the components involved in the production system. Thus, this on-farm trial determined the yield and forage quality of corn and cowpea with and without biofertilizer application when intercropped with ratooned sugarcane. Intercropping corn and cowpea without biofertilizer application had no negative effect on the vegetative growth of sugarcane. However, application of biofertilizer on intercrops decreased tiller production at 117 days after stubble shaving (DASS), consequently reducing the estimated tonnage yield of sugarcane. The yield of intercrops and forage production of Cp3 cowpea variety increased when intercropped to ratooned sugarcane. In contrast, intercropping PSB 97-92 corn variety to ratooned sugarcane reduced its forage production, but when biofertilizer was applied to intercropped Cp5 cowpea variety, the forage production increased. Profitability (income equivalent ratio) of intercropping for both corn and cowpea are higher than monocropping and are thus suitable intercrops to ratooned sugarcane. Unaffected tiller count (a determinant of sugarcane tonnage yield) when biofertilizer was not applied to intercrops and a reduced tiller count with biofertilizer application to intercrops implies the need to develop a nutrient management practices specific for intercropping systems.

Keywords: biofertilizer, corn, cowpea, intercropping system, ratooned sugarcane

Procedia PDF Downloads 121

Authors: Justin Orimisan Ijigbade

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The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

Procedia PDF Downloads 259

Authors: Marlene Kuhn, Franziska Schäfer, Heiner Otten

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Today´s production processes experience a constant increase in complexity paving new ways for progressive forms of leadership. In the customized production, individual customer requirements drive companies to adapt their manufacturing processes constantly while the pressure for smaller lot sizes, lower costs and faster lead times grows simultaneously. When production processes are becoming more dynamic and complex, the conventional quality management approaches show certain limitations. This paper gives an introduction to complexity science from a quality management perspective. By analyzing and evaluating different characteristics of complexity, the critical complexity parameters are identified and assessed. We found that the quality of leadership plays a crucial role when dealing with increasing complexity. Therefore, we developed a concept for qualitative leadership customized for the management within complex processes based on a maturity model. The maturity model was then applied in the industry to assess the leadership quality of several shop floor managers with a positive evaluation feedback. In result, the maturity model proved to be a sustainable approach to leverage the rising complexity in production processes more effectively.

Keywords: maturity model, process complexity, quality of leadership, quality management

Procedia PDF Downloads 358

Authors: Dupe Olufunke Ogunbosoye, Thaofik Badmos Mustapha, Lanre Shaffihy Adeaga, R. O. Imam

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Efforts have been made to reduce ruminants' methane emissions while improving animal productivity. Hence, an experiment was conducted to investigate the in vitro fermentation pattern, methane production, and performance of West African dwarf (WAD) rams-fed diets at graded levels of ginger. Sixteen (16) rams were randomly allocated into four dietary treatments with four animals per treatment in a completely randomized design for 84 days. Ginger powder was added at 0.00%, 0.25%, 0.50% and 0.75% as T1, T2, T3 and T4 respectively. The results indicated that at the 24-hour diet incubation, gas production, methane, metabolizable energy (ME), organic matter digestibility (OMD), and short-chain fatty acids (SCFA) concentrations decreased with the increasing level of ginger. Conversely, the sheep-fed T4 recorded the highest daily weight gain (47.61g/day), while the least daily weight gain (17.86g/day) was recorded in ram-fed T1. The daily weight gain of the rams fed T3 and T4 was similar but significantly different from the daily weight gain in T1 (17.86g/day) and T2 (29.76g/day). Daily feed intake was not significantly different across the treatments. T4 recorded the best response regarding feed conversion ratio (18.59) compared with other treatments. Based on the results obtained, rams fed T4 perform best in terms of growth and methane production. It is therefore concluded that the addition of ginger powder into the diet of sheep up to 0.75% enhances the growth rate of WAD sheep and reduces enteric methane production to create a smart nutrition system in ruminant animal production.

Keywords: enteric methane, growth, in vitro, sheep, nutrition system

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Authors: Mohammad Didar Hossain

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Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

Procedia PDF Downloads 255

Authors: Reza Vakili

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The aim of this experiment was to optimize the effect of moisture, the production rate, grain particle size and steam conditioning temperature on pellet quality in broiler feed using Taguchi method and a 43 fractional factorial arrangement was conducted. Production rate, steam conditioning temperatures, particle sizes and moisture content were performed. During the production process, sampling was done, and then pellet durability index (PDI) and hardness evaluated in broiler feed grower and finisher. There was a significant effect of processing parameters on PDI and hardness. Based on the results of this experiment Taguchi method can be used to find the best combination of factors for optimal pellet quality.

Keywords: broiler, feed physical quality, hardness, processing parameters, PDI

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Authors: Ashima Sharma, Tapan K. Chaudhuri

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Human Serum Albumin (HSA) is one of the most demanded therapeutic protein with immense biotechnological applications. The current source of HSA is human blood plasma. Blood is a limited and an unsafe source as it possesses the risk of contamination by various blood derived pathogens. This issue led to exploitation of various hosts with the aim to obtain an alternative source for the production of the rHSA. But, till now no host has been proven to be effective commercially for rHSA production because of their respective limitations. Thus, there exists an indispensable need to promote non-animal derived rHSA production. Of all the host systems, Escherichia coli is one of the most convenient hosts which has contributed in the production of more than 30% of the FDA approved recombinant pharmaceuticals. E. coli grows rapidly and its culture reaches high cell density using inexpensive and simple substrates. The fermentation batch turnaround number for E. coli culture is 300 per year, which is far greater than any of the host systems available. Therefore, E. coli derived recombinant products have more economical potential as fermentation processes are cheaper compared to the other expression hosts available. Despite of all the mentioned advantages, E. coli had not been successfully adopted as a host for rHSA production. The major bottleneck in exploiting E. coli as a host for rHSA production was aggregation i.e. majority of the expressed recombinant protein was forming inclusion bodies (more than 90% of the total expressed rHSA) in the E. coli cytosol. Recovery of functional rHSA form inclusion body is not preferred because it is tedious, time consuming, laborious and expensive. Because of this limitation, E. coli host system was neglected for rHSA production for last few decades. Considering the advantages of E. coli as a host, the present work has targeted E. coli as an alternate host for rHSA production through resolving the major issue of inclusion body formation associated with it. In the present study, we have developed a novel and innovative method for enhanced soluble and functional production of rHSA in E.coli (~60% of the total expressed rHSA in the soluble fraction) through modulation of the cellular growth, folding and environmental parameters, thereby leading to significantly improved and enhanced -expression levels as well as the functional and soluble proportion of the total expressed rHSA in the cytosolic fraction of the host. Therefore, in the present case we have filled in the gap in the literature, by exploiting the most well studied host system Escherichia coli which is of low cost, fast growing, scalable and ‘yet neglected’, for the enhancement of functional production of HSA- one of the most crucial biomolecule for clinical and biotechnological applications.

Keywords: enhanced functional production of rHSA in E. coli, recombinant human serum albumin, recombinant protein expression, recombinant protein processing

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Authors: Vaclav Musil, Robert Cep, Sarka Malotova, Jiri Hajnys, Frantisek Spalek

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The new designs of satellite gears comprising a number of small gears pose high requirements on the precise production of small module gears. The objective of the experimental activity stated in this article was to compare the conventional rolling gear cutting technology with the modern wire electrical discharge machining (WEDM) technology for the production of small module gear m=0.6 mm (thickness of 2.5 mm and material 30CrMoV9). The WEDM technology lies in copying the profile of gearing from the rendered trajectory which is then transferred to the track of a wire electrode. During the experiment, we focused on the comparison of these production methods. Main measured parameters which significantly influence the lifetime and noise was chosen. The first parameter was to compare the precision of gearing profile in respect to the mathematic model. The second monitored parameter was the roughness and surface topology of the gear tooth side. The experiment demonstrated high accuracy of WEDM technology, but a low quality of machined surface.

Keywords: precision of gearing, small module gears, surface topology, WEDM technology

Procedia PDF Downloads 224

Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

Procedia PDF Downloads 51

Authors: Ryspek Usubamatov, Tan San Chin, Sarken Kapaeva

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Productivity of the manufacturing systems depends on technological processes, a technical data of machines and a structure of systems. Technology is presented by the machining mode and data, a technical data presents reliability parameters and auxiliary time for discrete production processes. The term structure of manufacturing systems includes the number of serial and parallel production machines and links between them. Structures of manufacturing systems depend on the complexity of technological processes. Mathematical models of productivity rate for manufacturing systems are important attributes that enable to define best structure by criterion of a productivity rate. These models are important tool in evaluation of the economical efficiency for production systems.

Keywords: productivity, structure, manufacturing systems, structural design

Procedia PDF Downloads 573

Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 57

Authors: P. Arun Subhash, B. N. Suresh, M. C. Shivakumar, N. Suma

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An experiment was conducted to study the effect of dietary supplementation of ashwagandha (Withania somnifera) root powder on the egg production performance and egg quality in commercial layer birds. A practical type layer diet was prepared as per Bureau of Indian Standards (1992) to serve as the control, and the test diet was prepared by supplementing control diet with ashwagandha powder at 1kg/ton of feed. Each diet was assigned to twenty replicate groups of 5 laying hens each for duration of 84 days. The result revealed that cumulative egg production (%) was comparable between control and test group. The feed consumption and its conversion efficiency were similar among both the groups. The egg weight and egg characteristics viz., yolk index, yolk color, haugh unit score, albumen index, egg shape index and eggshell thickness were also remained similar between both the groups. It was concluded that supplementation of ashwagandha powder at 1kg/ton in layer diets has no beneficial effect on egg production and egg quality parameters.

Keywords: ashwagandha, egg production, egg quality, layers

Procedia PDF Downloads 143

Authors: Washaya Soul, Mupangwa John, Mapfumo Lizwell, Muchenje Voster

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Ruminant animals contribute a considerable amount of methane to the atmosphere, which is a cause of concern for global warming. Two studies were conducted in beef and goats where the studies aimed to determine the enteric CH₄ levels from a herd of beef cows raised on semi-arid rangelands and to evaluate the effect of supplementing goats with forage legumes: Vigna unguiculata and Lablab purpureus on enteric methane production. A total of 24 cows were selected from Boran and Nguni cows (n = 12 per breed) from two different farms; parity (P1 – P4) and season (dry vs. wet) were considered predictor variables in the first experiment. Eighteen goats (weaners, 9 males, 9 females) were used, in which sex and forage species were predictor variables in the second experiment. Three treatment diets were used in goats. Methane was measured using a Laser methane detector [LMD] for six consecutive days and repeated once after every three months in beef cows and once every week for 6 weeks in goats during the post-adaptation period. Parity and breed had no effects on CH₄ production in beef cows; however, season significantly influenced CH₄ outputs. Methane production was higher (P<0.05) in the dry compared to the wet season, 31.1CH₄/DMI(g/kg) and 28.8 CH₄/DMI(g/kg) for the dry and wet seasons, respectively. In goats, forage species and sex of the animal affected enteric methane production (P<0.05). Animals produce more gas when ruminating than feeding or just standing for all treatments. The control treatment exhibited higher (P<0.05) methane emissions per kg of DMI. Male goats produced more methane compared to females (17.40L/day; 12.46 g/kg DMI and 0.126g/day) versus (15.47L/day, 12.28 g/kg DMI, 0.0109g/day) respectively. It was concluded that cows produce more CH₄/DMI during the dry season, while forage legumes reduce enteric methane production in goats, and male goats produce more gas compared to females. It is recommended to introduce forage legumes, particularly during the dry season, to reduce the amount of gas produced.

Keywords: beef cows, extensive grazing system, forage legumes, greenhouse gases, goats Laser methane detector.

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Authors: Worrapol Koranuntachai, Tonkid Chantrasmi, Udomkiat Nontakaew

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Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: I. V. Pinto, M. R. Sooriyarachchi

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It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, penalized quasi-likelihood, power, quasi-likelihood, type-I error

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Authors: Yun-Ho Ahn, Hyery Kang, Dong-Yeun Koh, Huen Lee

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In this study, we demonstrate the production of natural gas hydrates from permeable marine sediments with simultaneous mechanisms for methane recovery and methane-air or methane-air/carbon dioxide replacement. The simultaneous melting happens until the chemical potentials become equal in both phases as natural gas hydrate depletion continues and self-regulated methane-air replacement occurs over an arbitrary point. We observed certain point between dissociation and replacement mechanisms in the natural gas hydrate reservoir, and we call this boundary as critical methane concentration. By the way, when carbon dioxide was added, the process of chemical exchange of methane by air/carbon dioxide was observed in the natural gas hydrate. The suggested process will operate well for most global natural gas hydrate reservoirs, regardless of the operating conditions or geometrical constraints.

Keywords: air injection, carbon dioxide sequestration, hydrate production, natural gas hydrate

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Babagana Mohammed, Abdulmuminu Mustapha Ali, Solomon Ibrahim, Buba Ahmad Umdagas

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This research investigated the possibility of replacing coarse and fine aggregates with waste road-asphalt (RWA), when sieved appropriately, in concrete production. Interlock pavement block is used widely in many parts of the world as modern day solution to outdoor flooring applications. The weight-percentage replacements of both coarse and fine aggregates with RWA at 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% respectively using a concrete mix ratio of 1:2:4 and water-to-cement ratio of 0.45 were carried out. The interlock block samples produced were then cured for 28days. Unconfined compressive strength (UCS) and the water absorption properties of the samples were then tested. Comparison of the results of the RWA-containing samples to those of the respective control samples shows significant benefits of using RWA in interlock block production. UCS results of RWA-containing samples compared well with those of the control samples and the RWA content also influenced the lowering of the water absorption of the samples. Overall, the research shows that it is possible to replace both coarse and fine aggregates with RWA materials when sieved appropriately, hence indicating that RWA could be recycled beneficially.

Keywords: aggregate, block-production, pavement, road-asphalt, use, waste

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Authors: Alonggot Limcharoen, Jintana Wannarat, Vorawat Panich

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This study aims to investigate the balancing of the number of operators (Line Balancing technique) in the production line of hard disk drive components in order to increase efficiency. At present, the trend of using hard disk drives has continuously declined leading to limits in a company’s revenue potential. It is important to improve and develop the production process to create market share and to have the ability to compete with competitors with a higher value and quality. Therefore, an effective tool is needed to support such matters. In this research, the Arena program was applied to analyze the results both before and after the improvement. Finally, the precedent was used before proceeding with the real process. There were 14 work stations with 35 operators altogether in the RA production process where this study was conducted. In the actual process, the average production time was 84.03 seconds per product piece (by timing 30 times in each work station) along with a rating assessment by implementing the Westinghouse principles. This process showed that the rating was 123% underlying an assumption of 5% allowance time. Consequently, the standard time was 108.53 seconds per piece. The Takt time was calculated from customer needs divided by working duration in one day; 3.66 seconds per piece. Of these, the proper number of operators was 30 people. That meant five operators should be eliminated in order to increase the production process. After that, a production model was created from the actual process by using the Arena program to confirm model reliability; the outputs from imitation were compared with the original (actual process) and this comparison indicated that the same output meaning was reliable. Then, worker numbers and their job responsibilities were remodeled into the Arena program. Lastly, the efficiency of production process enhanced from 70.82% to 82.63% according to the target.

Keywords: hard disk drive, line balancing, ECRS, simulation, arena program

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Authors: Ruolan Zhou

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Trisomy of human chromosome 21 is the primary cause of Down Syndrome (DS), and this genetic disease has significantly burdened families and countries, causing great controversy. To address this problem, the research takes an approach in exploring the relationship between genetic abnormality and this disease's symptoms, adopting several techniques, including data analysis and enrichment analysis. It also explores open-source websites, such as NCBI, DAVID, SOURCE, STRING, as well as UCSC, to complement its result. This research has analyzed the variety of genes on human chromosome 21 with simple coding, and by using analysis, it has specified the protein-coding genes, their function, and their location. By using enrichment analysis, this paper has found the abundance of keratin production-related coding-proteins on human chromosome 21. By adopting past researches, this research has attempted to disclose the relationship between trisomy of human chromosome 21 and keratin production abnormality, which might be the reason for common diseases in patients with Down Syndrome. At last, by addressing the advantage and insufficiency of this research, the discussion has provided specific directions for future research.

Keywords: Down Syndrome, protein production, genome, enrichment analysis

Procedia PDF Downloads 113

Authors: Arwa Alzughaibi

Abstract:

Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

Procedia PDF Downloads 249

Authors: Hiba Akrout, Khaoula Hidouri, Béchir Chaouachi, Romdhane Ben Slama

Abstract:

A simple solar distiller has been constructed in order to desalt water via the solar distillation process. An experimental study has been conducted in June. The aim of this work is to study the effect of the distance between the cold condensing surface and the hot steam generation surface in order to optimize the geometric characteristics of a simple solar still. To do this, we have developed a mathematical model based on thermal and mass equations system. Subsequently, the equations system resolution has been made through a program developed on MATLAB software, which allowed us to evaluate the production of this system as a function of the distance separating the two surfaces. In addition, this model allowed us to determine the evolution of the humid air temperature inside the solar still as well as the humidity ratio profile all over the day. Simulations results show that the solar distiller production, as well as the humid air temperature, are proportional to the global solar radiation. It was also found that the air humidity ratio inside the solar still has a similar evolution of that of solar radiation. Moreover, the solar distiller average height augmentation, for constant water depth, induces the diminution of the production. However, increasing the water depth for a fixed average height of solar distiller reduces the production.

Keywords: distillation, solar energy, heat transfer, mass transfer, average height

Procedia PDF Downloads 136

Authors: Yung-Chen Hsu, Juan Hernandez, W. T. Evert Ting, Dawit Gizachew

Abstract:

Mycotoxin contamination of foods and feeds poses a high risk for human and animal health. Ochratoxin A (OTA) is a ubiquitous mycotoxin produced by Aspergillus and Penicillium fungi. It exhibits nephrotoxicity, teratogenicity, mutagenicity, and immunotoxicity in both humans and animals. OTA has been detected in foods such as cereals, coffee, grapes, cocoa, wine, and spices. Consumption of food contaminated with OTA has been linked to kidney and liver diseases. Niger (Guizotia abyssinica) is an oil seed that is used for extracting cooking oil in countries like Ethiopia and India. The seed cake (a byproduct from oil extraction) is also used as dairy cattle feed in Ethiopia. It is also exported to North America and Europe to be used mainly as bird feed. To our knowledge, there have been no studies on the growth and production of OTA on niger seeds. In this study, the environment conditions that support OTA production including effects of water activity, temperature, and incubation time on growth and OTA production by A. fresenii and A. sulphureus were investigated.

Keywords: mycotoxin, ochratoxin A, aspergillus, niger seed

Procedia PDF Downloads 359

Authors: Nana Segu Acquaah-Harrison, James Osei Mensah, Richard Aidoo, David Amponsah, Amy Buah, Gilbert Aboagye

Abstract:

The study aimed at assessing the feasibility of commercial meat rabbit production in the Kumasi Metropolis of Ghana. Structured and unstructured questionnaires were utilized in obtaining information from two hundred meat consumers and 15 meat rabbit farmers. Data were analyzed using Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR)/Profitability Index (PI) technique, percentages and chi-square contingency test. The study found that the current demand for rabbit meat is low (36%). The desirable nutritional attributes of rabbit meat and other socio economic factors of meat consumers make the potential demand for rabbit meat high (69%). It was estimated that GH¢5,292 (approximately $ 2672) was needed as a start-up capital for a 40-doe unit meat rabbit farm in Kumasi Metropolis. The cost of breeding animals, housing and equipment formed 12.47%, 53.97% and 24.87% respectively of the initial estimated capital. A Net Present Value of GH¢ 5,910.75 (approximately $ 2984) was obtained at the end of the fifth year, with an internal rate return and profitability index of 70% and 1.12 respectively. The major constraints identified in meat rabbit production were low price of rabbit meat, shortage of fodder, pest and diseases, high cost of capital, high cost of operating materials and veterinary care. Based on the analysis, it was concluded that meat rabbit production is feasible in the Kumasi Metropolis of Ghana. The study recommends embarking on mass advertisement; farmer association and adapting to new technologies in the production process will help to enhance productivity.

Keywords: feasibility, commercial meat rabbit, production, Kumasi, Ghana

Procedia PDF Downloads 121

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

Abstract:

The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

Procedia PDF Downloads 206

Authors: Ahn Yun-Ho, Hyery Kang, Koh Dong-Yeun, Huen Lee

Abstract:

In this study, we demonstrate the production of natural gas hydrates from permeable marine sediments with simultaneous mechanisms for methane recovery and methane-air or methane-air/carbon dioxide replacement. The simultaneous melting happens until the chemical potentials become equal in both phases as natural gas hydrate depletion continues and self-regulated methane-air replacement occurs over an arbitrary point. We observed certain point between dissociation and replacement mechanisms in the natural gas hydrate reservoir, and we call this boundary as critical methane concentration. By the way, when carbon dioxide was added, the process of chemical exchange of methane by air/carbon dioxide was observed in the natural gas hydrate. The suggested process will operate well for most global natural gas hydrate reservoirs, regardless of the operating conditions or geometrical constraints.

Keywords: air injection, carbon dioxide sequestration, hydrate production, natural gas hydrate

Procedia PDF Downloads 565

Authors: Jian Li

Abstract:

Carotenoids area group of metabolites in mostly photosynthetic organisms such as plants and microalgae and have wide applications in cosmetics, food, feed, and health industries. Although phototrophic cultivation of microalgae has been developed to produce some carotenoids for decades, most carotenoids are currently synthesized chemically at industrial scales because of affordable production costs. Chemical carotenoids are regarded not as safe for human beings as natural carotenoids and are restricted only for animal feed markets, and the industries call for inexpensive sources of natural products. Microalgae grow much quicker in mixotrophy than in phototrophy, and thus mixotrophic cultivation processes have great potential to reduce the production cost of carotenoids from microalgae. However, much more expensive photobioreactor systems and more strictly controlled sterile processes are needed to avoid contamination by heterotrophic organisms during mixotrophic cultivation processes, which makes mixotrophy, in fact, much more expensive than phototrophic cultivation. Recently technical breakthroughs have been reported to overcome contamination problems in photobioreactor systems traditionally used for phototrophic cultivation, and a much lower process cost of mixotrophic cultivation than that of phototrophic cultivation might be achieved for carotenoid production. These reviews intend to summarize recent technical advancements in mixotrophic cultivation of microalgae, to evaluate the economic viability of carotenoid production from mixotrophically cultivated microalgae, and to prospect mixotrophy as a strategy to produce a variety of carotenoids for industrial applications.

Keywords: microalgae, carotenoid, mixotrophy, biotechnology

Procedia PDF Downloads 146