Search results for: extraction techniques

Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 95

Authors: B. M. Vishal, Monamie Basu, Gopinath M., Rose Havilah Pulla

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Though there are several methods of synthesizing silver nano particles, Green synthesis always has its own dignity. Ranging from the cost-effectiveness to the ease of synthesis, the process is simplified in the best possible way and is one of the most explored topics. This study of extracting secondary metabolites from Perilla frutescens and using them for therapeutic additives has its own significance. Unlike the other researches that have been done so far, this study aims to synthesize Silver nano particles from Perilla frutescens using three available forms of the plant: leaves, seed, and commercial leaf extract powder. Perilla frutescens, commonly known as 'Beefsteak Plant', is a perennial plant and belongs to the mint family. The plant has two varieties classed within itself. They are frutescens crispa and frutescens frutescens. The species, frutescens crispa (commonly known as 'Shisho' in Japanese), is generally used for edible purposes. Its leaves occur in two forms, varying on the colors. It is found in two different colors of red with purple streaks and green with crinkly pattern on it. This species is aromatic due to the presence of two major compounds: polyphenols and perillaldehyde. The red (purple streak) variety of this plant is due to the presence of a pigment, Perilla anthocyanin. The species, frutescens frutescens (commonly known as 'Egoma' in Japanese), is the main source for perilla oil. This species is also aromatic, but in this case, the major compound which gives the aroma is Perilla ketone or egoma ketone. Shisho grows short as compared with Wild Sesame and both produce seeds. The seeds of Wild Sesame are large and soft whereas that of Shisho is small and hard. The seeds have a large proportion of lipids, ranging about 38-45 percent. Excluding those, the seeds have a large quantity of Omega-3 fatty acids, linoleic acid, and an Omega-6 fatty acid. Other than these, Perilla leaf extract has gold and silver nano particles in it. The yield comparison in all the cases have been done, and the process’ optimal conditions were modified, keeping in mind the efficiencies. The characterization of secondary metabolites includes GC-MS and FTIR which can be used to identify the components of purpose that actually helps in synthesizing silver nano particles. The analysis of silver was done through a series of characterization tests that include XRD, UV-Vis, EDAX, and SEM. After the synthesis, for being used as therapeutic additives, the toxin analysis was done, and the results were tabulated. The synthesis of silver nano particles was done in a series of multiple cycles of extraction from leaves, seeds and commercially purchased leaf extract. The yield and efficiency comparison were done to bring out the best and the cheapest possible way of synthesizing silver nano particles using Perilla frutescens. The synthesized nano particles can be used in therapeutic drugs, which has a wide range of application from burn treatment to cancer treatment. This will, in turn, replace the traditional processes of synthesizing nano particles, as this method will prove effective in terms of cost and the environmental implications.

Keywords: nanoparticles, green synthesis, Perilla frutescens, characterisation, toxin analysis

Procedia PDF Downloads 212

Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Toshanlal Meenpal, Ankita Meenpal

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A very important technique in reversible data hiding field is Difference expansion. Secret message as well as the cover image may be completely recovered without any distortion after data extraction process due to reversibility feature. In general, in any difference expansion scheme embedding is performed by integer transform in the difference image acquired by grouping two neighboring pixel values. This paper proposes an improved reversible difference expansion embedding scheme. We mainly consider edge direction for embedding by modifying the difference of two neighboring pixels values. In general, the larger difference tends to bring a degraded stego image quality than the smaller difference. Image quality in the range of 0.5 to 3.7 dB in average is achieved by the proposed scheme, which is shown through the experimental results. However payload wise it achieves almost similar capacity in comparisons with previous method.

Keywords: information hiding, wedge direction, difference expansion, integer transform

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Luca Preis

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A primary healthcare facility in developing countries should be a multifunctional space able to respond to different requirements: Flexibility, modularity, aggregation and reversibility. These basic features could be better satisfied if applied to an architectural artifact that complies with the typological, figurative and constructive aspects of the context in which it is located. Therefore, the purpose of this paper is to identify a procedure that can define the figurative aspects of the architectural structure of the health prototype for the marginal areas of developing countries through a critical approach. The application context is the rural areas of the Northeast of Bahia in Brazil. The prototype should be located in the rural district of Quingoma, in the municipality of Lauro de Freitas, a particular place where there is still a cultural fusion of black and indigenous populations. Based on the historical analysis of settlement strategies and architectural structures in spaces of public interest or collective use, this paper aims to provide a procedure able to identify the categories and rules underlying typological and figurative aspects, in order to detect significant and generalizable elements, as well as materials and constructive techniques typically adopted in the rural areas of Brazil. The object of this work is therefore not only the recovery of certain constructive approaches but also the development of a procedure that integrates the requirements of the primary healthcare prototype with its surrounding economic, social, cultural, settlement and figurative conditions.

Keywords: architectural typology, developing countries, local construction techniques, primary health care.

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Authors: Azher Jameel, Ghulam Ashraf Harmain

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In the recent years, the enriched techniques like the extended finite element method, the element free Galerkin method, and the Coupled finite element-element free Galerkin method have found wide application in modeling different types of discontinuities produced by cracks, contact surfaces, and bi-material interfaces. The extended finite element method faces severe mesh distortion issues while modeling large deformation problems. The element free Galerkin method does not have mesh distortion issues, but it is computationally more demanding than the finite element method. The coupled FE-EFGM proves to be an efficient numerical tool for modeling large deformation problems as it exploits the advantages of both FEM and EFGM. The present paper employs the coupled FE-EFGM to model large elastoplastic deformations in bi-material engineering components. The large deformation occurring in the domain has been modeled by using the total Lagrangian approach. The non-linear elastoplastic behavior of the material has been represented by the Ramberg-Osgood model. The elastic predictor-plastic corrector algorithms are used for the evaluation stresses during large deformation. Finally, several numerical problems are solved by the coupled FE-EFGM to illustrate its applicability, efficiency and accuracy in modeling large elastoplastic deformations in bi-material samples. The results obtained by the proposed technique are compared with the results obtained by XFEM and EFGM. A remarkable agreement was observed between the results obtained by the three techniques.

Keywords: XFEM, EFGM, coupled FE-EFGM, level sets, large deformation

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Authors: Shakhawan K. Mawlood, Catriona Pickard, Benjamin Pickard

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In summer 2015 the remains of 800 children are among 1,967 bodies were exhumed by archaeologists at St Peter's Burial Ground in Blackburn, Lancashire. One hundred samples from these 19th century ancient bones were selected for DNA analysis. These comprised samples biased for those which prior osteological evidence indicated a potential for microbial infection by Mycobacterium tuberculosis (causing tuberculosis, TB) or Treponema pallidum (causing Syphilis) species, as well a random selection of other bones for which visual inspection suggested good preservation (and, therefore, likely DNA retrieval).They were subject to polymerase chain reaction (PCR) assays aimed at detecting traces of DNA from infecting mycobacteria, with the purpose both of confirming the palaeopathological diagnosis of tuberculosis and determining in individual cases whether disease and death was due to M. tuberculosis or other reasons. Our secondary goal was to determine sex determination and age prediction. The results demonstrated that extraction of vast majority ancient bones DNA samples succeeded.

Keywords: ancient bone, DNA, tuberculosis, age prediction

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Authors: Shubham Giri Goswami, Yogesh Tiwari

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In today’s developing world, India and other countries are developing different instruments and accessories for the better standard and life to be happy and prosper. But rather than this we human-beings have been using different energy sources accordingly, many persons such as scientist, researchers etc have developed many Energy sources like renewable and non-renewable energy sources. Like fossil fuel, coal, gas, petroleum products as non-renewable sources, and solar, wind energy as renewable energy source. Thus all non-renewable energy sources, these all Created pollution as in form of air, water etc. due to ultimate use of these sources by human the future became uncertain. Thus to minimize all this environmental affects and destroy the healthy environment we discovered a solution as renewable energy source. Renewable energy source in form of biomass energy, solar, wind etc. We found different techniques in biomass energy, that good energy source for people. The domestic waste, and is a good source of energy as daily extract from cow in form of dung and many other domestic products naturally can be used eco-friendly fertilizers. Moreover, as from my point of view the cow is able to extract 08-12 kg of dung which can be used to make wormy compost fertilizers. Furthermore, the calf urine as insecticides and use of such a compounds will lead to destroy insects and thus decrease communicable diseases. Therefore, can be used by every person and biomass energy can be in those areas such as rural areas where non-renewable energy sources cannot reach easily. Biomass can be used to develop fertilizers, cow-dung plants and other power generation techniques, and this energy is clean and pollution free and is available everywhere thus saves our beautiful planet or blue or life giving planet called as “EARTH”. We can use the biomass energy, which may be boon for the world in future.

Keywords: biomass, energy, environment, human, pollution, renewable, solar energy, sources, wind

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Authors: Chintan Chandrachud

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When primary legislation is challenged for breaching fundamental rights, many courts around the world adopt interpretive techniques to avoid finding such legislation incompatible or invalid. In the UK, these techniques find sanction in section 3 of the Human Rights Act 1998, which directs courts to interpret legislation in a manner which is compatible with European Convention rights, ‘so far as it is possible to do so’. In India, courts begin with the interpretive presumption that Parliament intended to comply with fundamental rights under the Constitution of 1949. In comparing rights-compliant interpretation of primary legislation under the Human Rights Act and the Indian Constitution, this paper makes two arguments. First, that in the absence of a section 3-type mandate, Indian courts have a smaller range of interpretive tools at their disposal in interpreting primary legislation in a way which complies with fundamental rights. For example, whereas British courts frequently read words into statutes, Indian courts consider this an inapposite interpretive technique. The second argument flows naturally from the first. Given that Indian courts have a smaller interpretive toolbox, one would imagine that ceteris paribus, Indian courts’ power to strike down legislation would be triggered earlier than the declaration of incompatibility is in the UK. However, this is not borne out in practice. Faced with primary legislation which appears to violate fundamental rights, Indian courts often reluctantly uphold the constitutionality of statutes (rather than striking them down), as opposed to British courts, which make declarations of incompatibility. The explanation for this seeming asymmetry hinges on the difference between the ‘strike down’ power and the declaration of incompatibility. Whereas the former results in the disapplication of a statute, the latter throws the ball back into Parliament’s court, if only formally.

Keywords: constitutional law, judicial review, constitution of India, UK Human Rights Act

Procedia PDF Downloads 273

Authors: Jessy Mattar, Mohamad Turk, Maurice Nonus, Nikolai Lebovka, Henri El Zakhem, Eugene Vorobiev

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The effects of electro-stimulation of S. cerevisiae cells in colloidal suspension by Pulsed Electric Fields ‎‎(PEF) with electric field strength E = 20 – 2000 V.cm-1 and effective PEF treatment time tPEF = 10^−5 – 1 s were ‎investigated. The applied experimental procedure includes variations in the preliminary fermentation time and ‎electro-stimulation by PEF-treatment. Plate counting was performed.‎ At relatively high electric fields (E ≥ 1000 V.cm-1) and moderate PEF treatment time (tPEF > 100 µs), the ‎extraction of ionic components from yeast was observed by conductivity measurements, which can be related to ‎electroporation of cell membranes. Cell counting revealed a dependency of the colonies’ size on the time of ‎preliminary fermentation tf and the power consumption W, however no dependencies were noticeable by varying the initial yeast concentration in the treated suspensions.‎

Keywords: intensification, yeast, fermentation, electroporation, biotechnology

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: N. Yang, R. Linforth, I. Fisk

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The influence of food processing and choice of flavour solvent was investigated using biscuits prepared with vanillin flavour as an example. Powder vanillin either was added directly into the dough or dissolved into flavour solvent then mixed into the dough. The impact of two commonly used flavour solvents on food quality was compared: propylene glycol (PG) or triacetin (TA). The analytical approach for vanillin detection was developed by chromatography (HPLC-PDA), and the standard extraction method for vanillin was also established. The results indicated the impact of solvent choice on vanillin level during biscuit preparation. After baking, TA as a more heat resistant solvent retained more vanillin than PG, so TA is a better solvent for products that undergo a heating process. The results also illustrated the impact of mixing and baking on vanillin stability in the matrices. The average loss of vanillin was 33% during mixing and 13% during baking, which indicated that the binding of vanillin to fat or flour before baking might cause larger loss than evaporation loss during baking.

Keywords: biscuit, flavour stability, food quality, vanillin

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Authors: Rupali, Anil Kumar Jaiswal

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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model

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Authors: Ait Slimane-Ait Kaki Sabrina, Foudi Lamia

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The present work consists of the study of the bio-ecology and the therapeutic effects of the belladone (Atropa belladonna L.). It is a medicinal plant of the Solanacées family, herbaceous, robust 0.5 up to 1.50 m high. The phytochemical analysis of leaves revealed alkaloids, tannins, catechin, coumarins, mucilages, saponins, starch, and reducing compounds. The experimental study concerns the extraction and characterization of belladonna alkaloids. Analysis of the purified extract by staining tests confirmed the presence of tropane alkaloids. The dosage chromatography revealed the presence of components that have been identified atropine, scopolamine and hyoscyamine. Evaluation of antimicrobial and antifungal alkaloids from the methanol extract and aqueous extract of belladonna on pathogenic germs showed a positive bactericidal against strains of Escherichia coli and Staphylococcus aureus. Our preliminary results allow us an overall assessment of the medicinal value of Atropa belladonna.

Keywords: belladone, alkaloid, antibacterial activity, antifungal activity

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Authors: Lawrence Koech, Hilary Rutto, Olga Mothibedi

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Worldwide demand for copper has led to intensive search for methods of extraction and recovery of copper from different sources. The study investigates the leaching properties of a low-grade copper ore by optimizing the leaching variables using response surface methodology. The effects of key parameters, i.e., temperature, solid to liquid ratio, stirring speed and pH, on the leaching rate constant was investigated using a pH stat apparatus. A Central Composite Design (CCD) of experiments was used to develop a quadratic model which specifically correlates the leaching variables and the rate constant. The results indicated that the model is in good agreement with the experimental data with a correlation coefficient (R2) of 0.93. The temperature and solid to liquid ratio were found to have the most substantial influence on the leaching rate constant. The optimum operating conditions for copper leaching from the ore were identified as temperature at 65C, solid to liquid ratio at 1.625 and stirring speed of 325 rpm which yielded an average leaching efficiency of 93.16%.

Keywords: copper, leaching, CCD, rate constant

Procedia PDF Downloads 216

Authors: Pierre Moulis, Markus Herderich, Doris Rauhut, Patricia Ballestra

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Nowadays, it is starting to be more frequent to detect wines with mousy off-flavor. The reasons behind this could be the significant decrease in sulphur dioxide, the increase in pH, and the trend for spontaneous fermentation in wine. This off-flavor can be produced by Brettanomyces bruxellensis or some Lactic acid bacteria. So far there is no study working on the influence of the genetic group on the production of these microorganisms. Objectives: The objectives of this research are to increase knowledge and to have a better understanding of the microbiological phenomena related to the production of the mousy off-flavor in the wine. Methodologies: In this research, microorganisms were screened in an N-heterocycle assay medium (this medium contained all known precursors) and the production of mousy compounds was quantified by Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry (SBSE-GC-MS). Main contributions: Brettanomyces bruxellensis and Oenococcus oeni could produce mousiness at a different amount depending on the strain. But there is no group effect.

Keywords: mousy off-flavor, wine, Brettanomyces bruxellensis, Oenococcus oeni

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Authors: Shirin Jalili, Ramin Ghasemi Shayan

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Coarctation of the aorta (CoA) may be a common (CHD), which is the seventh most common sort of CHD. Still, this is often likely a think little off since the determination may be deferred, indeed within the pediatric populace. The choice for surgical repair incorporates resection of the contracted section with end-to-end or end-to-side anastomosis, subclavian fold aortoplasty, resection, and join the intervention, or prosthetic fix aortoplasty. Drastically expanded end-to-end repair or switched subclavian fold aortoplasty can be utilized when the coarctation expands to the distal arch. Swell angioplasty can be a palliative choice sometime recently the conclusive redress. Its objective is to stabilize high-risk patients that cannot be submitted to quick surgical intercession, such as untimely newborns. For disconnected and discrete coarctations, it can, as a rule, be drawn nearer and repaired by means of cleared out thoracotomy, extraction of the infected aorta (coarctectomy), and remaking, ordinarily by amplified end-to-end anastomosis. In this article, we need to supply a diagram of current proposals and strategies utilized to picture coarctations of the aorta.

Keywords: coarctation of the aorta, congenital heart disease, strategies, surgical repair

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Authors: Erika Duggan

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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 233

Authors: Bita Mohajernia, R. J. Urbanic

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Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

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Authors: Ghazi Faisal Najmuldeen, Noridah Abdullah, Mimi Sakinah

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Bioethanol is an alcohol made by fermentation, mostly from carbohydrates, Cellulosic biomass, derived from non-food sources, such as castor shell waste, is also being developed as a feedstock for ethanol production Cellulose extracted from biomass sources is considered the future feedstock for many products due to the availability and eco-friendly nature of cellulose. In this study, castor shell (CS) biowaste resulted from the extraction of Castor oil from castor seeds was evaluated as a potential source of cellulose. The cellulose was extracted after pretreatment process was done on the CS. The pretreatment process began with the removal of other extractives from CS, then an alkaline treatment, bleaching process with hydrogen peroxide, and followed by a mixture of acetic and nitric acids. CS cellulose was analysed by infrared absorption spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The result showed that the overall process was adequate to produce cellulose with high purity and crystallinity from CS waste. The cellulose was then hydrolyzed to produce glucose and then fermented to bioethanol.

Keywords: bioethanol, castor shell, cellulose, biowaste

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Udeh Nneka Evelyn

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The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

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Authors: Abdelmessih Malak Sadek Labib

Abstract:

Ceramic materials are known for their stability in harsh environments and excellent electrical, mechanical, and thermal properties. They have been widely used in various applications despite the emergence of new materials such as plastics and composites. However, ceramics are often brittle, which can lead to catastrophic failure. The fragility of ceramics and the mechanisms behind their failure have been a topic of extensive research, particularly in load-bearing applications like veneers. Porcelain, a type of traditional pottery, is commonly used in such applications. Traditional pottery consists of clay, silica, and feldspar, and the presence of quartz in the ceramic body can lead to microcracks and stress concentrations. The mullite hypothesis suggests that the strength of porcelain can be improved by increasing the interlocking of mullite needles in the ceramic body. However, there is a lack of reports on Young's moduli in the literature, leading to erroneous conclusions about the mechanical behavior of porcelain. This project aims to investigate the role of quartz and mullite on the mechanical strength of various porcelains while considering factors such as particle size, flexural strength, and fractographic forces. Research Aim: The aim of this research project is to assess the role of quartz and mullite in enhancing the mechanical strength of different porcelains. The project will also explore the effect of reducing particle size on the properties of porcelain, as well as investigate flexural strength and fractographic techniques. Methodology: The methodology for this project involves using scientific expressions and a mix of modern English to ensure the understanding of all attendees. It will include the measurement of Young's modulus and the evaluation of the mechanical behavior of porcelains through various experimental techniques. Findings: The findings of this study will provide a realistic assessment of the role of quartz and mullite in strengthening and reducing the fragility of porcelain. The research will also contribute to a better understanding of the mechanical behavior of ceramics, specifically in load-bearing applications. Theoretical Importance: The theoretical importance of this research lies in its contribution to the understanding of the factors influencing the mechanical strength and fragility of ceramics, particularly porcelain. By investigating the interplay between quartz, mullite, and other variables, this study will enhance our knowledge of the properties and behavior of traditional ceramics. Data Collection and Analysis Procedures: Data for this research will be collected through experiments involving the measurement of Young's modulus and other mechanical properties of porcelains. The effects of quartz, mullite, particle size, flexural strength, and fractographic forces will be examined and analyzed using appropriate statistical techniques and fractographic analysis. Questions Addressed: This research project aims to address the following questions: (1) How does the presence of quartz and mullite affect the mechanical strength of porcelain? (2) What is the impact of reducing particle size on the properties of porcelain? (3) How do flexural strength and fractographic forces influence the behavior of porcelains? Conclusion: In conclusion, this research project aims to enhance the understanding of the role of quartz and mullite in strengthening and reducing the fragility of porcelain. By investigating the mechanical properties of porcelains and considering factors such as particle size, flexural strength, and fractographic forces, this study will contribute to the knowledge of traditional ceramics and their potential applications. The findings will have practical implications for the use of ceramics in various fields.

Keywords: stability, harsh environments, electrical, techniques, mechanical disadvantages, materials

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Authors: Ahmad Kayvani Fard, Yehia Manawi

Abstract:

Qatar’s primary source of fresh water is through seawater desalination. Amongst the major processes that are commercially available on the market, the most common large scale techniques are Multi-Stage Flash distillation (MSF), Multi Effect distillation (MED), and Reverse Osmosis (RO). Although commonly used, these three processes are highly expensive down to high energy input requirements and high operating costs allied with maintenance and stress induced on the systems in harsh alkaline media. Beside that cost, environmental footprint of these desalination techniques are significant; from damaging marine eco-system, to huge land use, to discharge of tons of GHG and huge carbon footprint. Other less energy consuming techniques based on membrane separation are being sought to reduce both the carbon footprint and operating costs is membrane distillation (MD). Emerged in 1960s, MD is an alternative technology for water desalination attracting more attention since 1980s. MD process involves the evaporation of a hot feed, typically below boiling point of brine at standard conditions, by creating a water vapor pressure difference across the porous, hydrophobic membrane. Main advantages of MD compared to other commercially available technologies (MSF and MED) and specially RO are reduction of membrane and module stress due to absence of trans-membrane pressure, less impact of contaminant fouling on distillate due to transfer of only water vapor, utilization of low grade or waste heat from oil and gas industries to heat up the feed up to required temperature difference across the membrane, superior water quality, and relatively lower capital and operating cost. To achieve the objective of this study, state of the art flat-sheet cross-flow DCMD bench scale unit was designed, commissioned, and tested. The objective of this study is to analyze the characteristics and morphology of the membrane suitable for DCMD through SEM imaging and contact angle measurement and to study the water quality of distillate produced by DCMD bench scale unit. Comparison with available literature data is undertaken where appropriate and laboratory data is used to compare a DCMD distillate quality with that of other desalination techniques and standards. Membrane SEM analysis showed that the PTFE membrane used for the study has contact angle of 127º with highly porous surface supported with less porous and bigger pore size PP membrane. Study on the effect of feed solution (salinity) and temperature on water quality of distillate produced from ICP and IC analysis showed that with any salinity and different feed temperature (up to 70ºC) the electric conductivity of distillate is less than 5 μS/cm with 99.99% salt rejection and proved to be feasible and effective process capable of consistently producing high quality distillate from very high feed salinity solution (i.e. 100000 mg/L TDS) even with substantial quality difference compared to other desalination methods such as RO and MSF.

Keywords: membrane distillation, waste heat, seawater desalination, membrane, freshwater, direct contact membrane distillation

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Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

Abstract:

Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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Authors: Sara Heidari, Jafar Mohammadzadeh Milani, Elmira Pouladi Borj

Abstract:

In this research, stability of Ochratoxin A (OTA) during bread making process including fermentation with yeasts (Saccharomyces cerevisiae) and Sourdough (Lactobacillus casei, Lactobacillus rhamnosus, Lactobacillus acidophilus and Lactobacillus fermentum) and baking at 200°C were examined. Bread was prepared on a pilot-plant scale by using wheat flour spiked with standard solution of OTA. During this process, mycotoxin levels were determined after fermentation of the dough with sourdough and three types of yeast including active dry yeast, instant dry yeast and compressed yeast after further baking 200°C by high performance liquid chromatography (HPLC) with fluorescence detector after extraction and clean-up on an immunoaffinity column. According to the results, the highest stability of was observed in the first fermentation (first proof), while the lowest stability was observed in the baking stage in comparison to contaminated flour. In addition, compressed yeast showed the maximum impact on stability of OTA during bread making process.

Keywords: Ochratoxin A, bread, dough, yeast, sourdough

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Authors: Analise Borg, Paul Micallef

Abstract:

Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

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Authors: Issam Lakdhar, Akram Alhussein, Juan Creus

Abstract:

With the huge increase in world energy consumption, researchers are working to find other alternative sources of energy instead of fossil fuel one causing many environmental problems as the production of greenhouse effect gases. Hydrogen is considered a green energy source, which its combustion does not cause environmental pollution. The transport and the storage of the gas molecules or the other products containing this smallest chemical element in metallic structures (pipelines, tanks) are crucial issues. The dissolve and the permeation of hydrogen into the metal lattice lead to the formation of hydride phases and the embrittlement of structures. To protect the metallic structures, a surface treatment could be a good solution. Among the different techniques, magnetron sputtering is used to elaborate micrometric coatings capable of slowing down or stop hydrogen permeation. In the plasma environment, the deposition parameters of new thin-film metallic glasses Al-Ti-W were optimized and controlled in order to obtain, hydrogen barrier. Many characterizations were carried out (SEM, XRD and Nano-indentation…) to control the composition and understand the influence of film microstructure and chemical composition on the hydrogen permeation through the coatings. The coating performance was evaluated under two hydrogen production methods: chemical and electrochemical (cathodic protection) techniques. The hydrogen quantity absorbed was experimentally determined using the Thermal-Desorption Spectroscopy method (TDS)). An ideal ATW thin film was developed and showed excellent behavior against the diffusion of hydrogen.

Keywords: thin films, hydrogen, PVD, plasma technology, electrochemical properties

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Authors: Ju-Hong Lee, Ching-Wei Liao

Abstract:

An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

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