Search results for: Vapor Extraction

Authors: Tamrat Tesfaye, Bruce Sithole

Abstract:

Box-Behnken Response surface methodology was used to determine the optimum processing conditions that give maximum extraction yield and whiteness index from mango seed. The steeping time ranges from 2 to 12 hours and slurring of the steeped seed in sodium metabisulphite solution (0.1 to 0.5 w/v) was carried out. Experiments were designed according to Box-Behnken Design with these three factors and a total of 15 runs experimental variables of were analyzed. At linear level, the concentration of sodium metabisulphite had significant positive influence on percentage yield and whiteness index at p<0.05. At quadratic level, sodium metabisulphite concentration and sodium metabisulphite concentration2 had a significant negative influence on starch yield; sodium metabisulphite concentration and steeping time*temperature had significant (p<0.05) positive influence on whiteness index. The adjusted R2 above 0.8 for starch yield (0.906465) and whiteness index (0.909268) showed a good fit of the model with the experimental data. The optimum sodium metabisulphite concentration, steeping hours, and temperature for starch isolation with maximum starch yield (66.428%) and whiteness index (85%) as set goals for optimization with the desirability of 0.91939 was 0.255w/v concentration, 2hrs and 50 °C respectively. The determined experimental value of each response based on optimal condition was statistically in accordance with predicted levels at p<0.05. The Mango seeds are the by-products obtained during mango processing and possess disposal problem if not handled properly. The substitution of food based sizing agents with mango seed starch can contribute as pertinent resource deployment for value-added product manufacturing and waste utilization which might play significance role of food security in Ethiopia.

Keywords: mango, synthetic sizing agent, starch, extraction, textile, sizing

Procedia PDF Downloads 230

Authors: Sadam Elayah

Abstract:

Background: One of the most critical competencies in advanced dentistry is alveolar ridge preservation after exodontia. The aim of this clinical trial was to assess the impact of autologous concentrated growth factor (CGF) as a socket-filling material and its ridge preservation properties following the lower third molar extraction. Materials and Methods: A total of 60 sides of 30 participants who had completely symmetrical bilateral impacted lower third molars were enrolled. The short-term outcome variables were wound healing, swelling and pain, clinically assessed at different time intervals (1st, 3rd & 7th days). While the long-term outcome variables were bone height & width, bone density and socket surface area in the coronal section. Cone beam computed tomography images were obtained immediately after surgery and three months after surgery as a temporal measure. Randomization was achieved by opaque, sealed envelopes. Follow-up data were compared to baseline using Paired & Unpaired t-tests. Results: The wound healing index was significantly better in the test sides (P =0.001). Regarding the facial swelling, the test sides had significantly fewer values than the control sides, particularly on the 1st (1.01±.57 vs 1.55 ±.56) and 3rd days (1.42±0.8 vs 2.63±1.2) postoperatively. Nonetheless, the swelling disappeared within the 7th day on both sides. The pain scores of the visual analog scale were not a statistically significant difference between both sides on the 1st day; meanwhile, the pain scores were significantly lower on the test sides compared with the control sides, especially on the 3rd (P=0.001) and 7th days (P˂0.001) postoperatively. Regarding long-term outcomes, CGF sites had higher values in height and width when compared to Control sites (Buccal wall 32.9±3.5 vs 29.4±4.3 mm, Lingual wall 25.4±3.5 vs 23.1±4 mm, and Alveolar bone width 21.07±1.55vs19.53±1.90 mm) respectively. Bone density showed significantly higher values in CGF sites than in control sites (Coronal half 200±127.3 vs -84.1±121.3, Apical half 406.5±103 vs 64.2±158.6) respectively. There was a significant difference between both sites in reducing periodontal pockets. Conclusion: CGF application following surgical extraction provides an easy, low-cost, and efficient option for alveolar ridge preservation. Thus, dentists may encourage using CGF during dental extractions, particularly when alveolar ridge preservation is required.

Keywords: platelet, extraction, impacted teeth, alveolar ridge, regeneration, CGF

Procedia PDF Downloads 65

Authors: S. Visetpotjanakit, N. Nakkaew

Abstract:

Determination of low level ⁹⁰Sr in seawater has been widely developed for the purpose of environmental monitoring and radiological research because ⁹⁰Sr is one of the most hazardous radionuclides released from atmospheric during the testing of nuclear weapons, waste discharge from the generation nuclear energy and nuclear accident occurring at power plants. A liquid extraction technique using bis-2-etylhexyl-phosphoric acid to separate and purify yttrium followed by Cherenkov counting using a liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed to monitor ⁹⁰Sr in the Asia Pacific Ocean. The analytical performance was validated for the accuracy, precision, and trueness criteria. Sr-90 determination in seawater using various low concentrations in a range of 0.01 – 1 Bq/L of 30 liters spiked seawater samples and 0.5 liters of IAEA-RML-2015-01 proficiency test sample was performed for statistical evaluation. The results had a relative bias in the range from 3.41% to 12.28%, which is below accepted relative bias of ± 25% and passed the criteria confirming that our analytical approach for determination of low levels of ⁹⁰Sr in seawater was acceptable. Moreover, the approach is economical, non-laborious and fast.

Keywords: proficiency test, radiation monitoring, seawater, strontium determination

Procedia PDF Downloads 168

Authors: Linghui Meng, James Atlas, Deborah Munro

Abstract:

There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.

Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers

Procedia PDF Downloads 23

Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

Abstract:

In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

Procedia PDF Downloads 112

Authors: Dhiflaoui Hafedh, Khlifi Kaouther, Ben Cheikh Larbi Ahmed

Abstract:

Monolayer and multilayer coatings of CrN and AlCrN deposited on 100Cr6 (AISI 52100) substrate by PVD magnetron sputtering system. The micro structures of the coatings were characterized using atomic force microscopy (AFM). The AFM analysis revealed the presence of domes and craters which are uniformly distributed over all surfaces of the various layers. Nano indentation measurement of CrN coating showed maximum hardness (H) and modulus (E) of 14 GPa and 240 GPa, respectively. The measured H and E values of AlCrN coatings were found to be 30 GPa and 382 GPa, respectively. The improved hardness in both the coatings was attributed mainly to a reduction in crystallite size and decrease in surface roughness. The incorporation of Al into the CrN coatings has improved both hardness and Young’s modulus.

Keywords: CrN, AlCrN coatings, hardness, nanoindentation

Procedia PDF Downloads 556

Authors: Ahmed F. Ghanem, Marwa I. Wahba, Asmaa N. El-Dein, Mohamed A. EL-Raey, Ghada E.A. Awad

Abstract:

Numerous attempts are being performed in order to formulate suitable packaging materials for meat products. However, to the best of our knowledge, the incorporation of free hibiscus extract or its microcapsules in the pure polyvinyl alcohol (PVA) matrix as packaging materials for meats is seldom reported. Therefore, this study aims at protection of the aqueous crude extract of hibiscus flowers utilizing spry drying encapsulation technique. Fourier transform infrared (FTIR), scanning electron microscope (SEM), and zetasizer results confirmed the successful formation of assembled capsules via strong interactions, spherical rough microparticles, and ~ 235 nm of particle size, respectively. Also, the obtained microcapsules enjoy high thermal stability, unlike the free extract. Then, the obtained spray-dried particles were incorporated into the casting solution of the pure PVA film with a concentration 10 wt. %. The segregated free-standing composite films were investigated, compared to the neat matrix, with several characterization techniques such as FTIR, SEM, thermal gravimetric analysis (TGA), mechanical tester, contact angle, water vapor permeability, and oxygen transmission. The results demonstrated variations in the physicochemical properties of the PVA film after the inclusion of the free and the extract microcapsules. Moreover, biological studies emphasized the biocidal potential of the hybrid films against microorganisms contaminating the meat. Specifically, the microcapsules imparted not only antimicrobial but also antioxidant activities to PVA. Application of the prepared films on the real meat samples displayed low bacterial growth with a slight increase in the pH over the storage time up to 10 days at 4 oC which further proved the meat safety. Moreover, the colors of the films did not significantly changed except after 21 days indicating the spoilage of the meat samples. No doubt, the dual-functional of prepared composite films pave the way towards combined active/smart food packaging applications. This would play a vital role in the food hygiene, including also quality control and assurance.

Keywords: PVA, hibiscus, extraction, encapsulation, active packaging, smart and intelligent packaging, meat spoilage

Procedia PDF Downloads 81

Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

Abstract:

The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

Procedia PDF Downloads 456

Authors: Ali Kadivar, Kaveh Niayesh

Abstract:

This work simulates the voltage drop and resistance of the explosion of copper wires of diameters 25, 40, and 100 µm surrounded by 1 bar nitrogen exposed to a 150 A current and before plasma formation. The absorption of electrical energy in an exploding wire is greatly diminished when the plasma is formed. This study shows the importance of considering radiation and heat conductivity in the accuracy of the circuit simulations. The radiation of the dense plasma formed on the wire surface is modeled with the Net Emission Coefficient (NEC) and is mixed with heat conductivity through PLASIMO® software. A time-transient code for analyzing wire explosions driven by a slow current rise rate is developed. It solves a circuit equation coupled with one-dimensional (1D) equations for the copper electrical conductivity as a function of its physical state and Net Emission Coefficient (NEC) radiation. At first, an initial voltage drop over the copper wire, current, and temperature distribution at the time of expansion is derived. The experiments have demonstrated that wires remain rather uniform lengthwise during the explosion and can be simulated utilizing 1D simulations. Data from the first stage are then used as the initial conditions of the second stage, in which a simplified 1D model for high-Mach-number flows is adopted to describe the expansion of the core. The current was carried by the vaporized wire material before it was dispersed in nitrogen by the shock wave. In the third stage, using a three-dimensional model of the test bench, the streamer threshold is estimated. Electrical breakdown voltage is calculated without solving a full-blown plasma model by integrating Townsend growth coefficients (TdGC) along electric field lines. BOLSIG⁺ and LAPLACE databases are used to calculate the TdGC at different mixture ratios of nitrogen/copper vapor. The simulations show both radiation and heat conductivity should be considered for an adequate description of wire resistance, and gaseous discharges start at lower voltages than expected due to ultraviolet radiation and the exploding shocks, which may have ionized the nitrogen.

Keywords: exploding wire, Townsend breakdown mechanism, streamer, metal vapor, shock waves

Procedia PDF Downloads 86

Authors: Ching-Ting Hsu, Wei-Hua Ho, Yi-Chun Chang

Abstract:

Video object tracking is one of the popular research topics in computer graphics area. The trajectory can be applied in security, traffic control, even the sports training. The trajectory for sports training can be utilized to analyze the athlete’s performance without traditional sensors. There are many relevant works which utilize mean shift algorithm with background subtraction. This kind of the schemes should select a kernel function which may affect the accuracy and performance. In this paper, we consider the motion information in the pre-coded bitstream. The proposed algorithm extracts the trajectory by composing the motion vectors from the pre-coded bitstream. We gather the motion vectors from the overlap area of the object and calculate mean of the overlapped motion vectors. We implement and simulate our proposed algorithm in H.264 video codec. The performance is better than relevant works and keeps the accuracy of the object trajectory. The experimental results show that the proposed trajectory extraction can extract trajectory form the pre-coded bitstream in high accuracy and achieve higher performance other relevant works.

Keywords: H.264, video bitstream, video object tracking, sports training

Procedia PDF Downloads 427

Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

Abstract:

The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

Procedia PDF Downloads 380

Authors: Narmeen Mehmood

Abstract:

The current study was conducted to evaluate the pharmacognostic parameters, phytochemical analysis and antibacterial activity of the plant. Microscopic studies were carried out to determine various Pharmacognostic parameters. Section cutting of the leaf was also done. The study of the ariel parts of Beaumontia grandiflora resulted in the identification of fatty acids mixture and unsaponifiable matters. For the separation of various constituents of the plant, successive solvent extraction was carried out in a laboratory. Material and Methods: The study was carried out with all three extracts of Beaumontia grandiflora i.e. Petroleum ether, Chloroform and Methanol. For the separation of various constituents of the plant, successive solvent extraction was carried out in the laboratory. Raw data containing the measured zones of inhibition in mm was tabulated. Results: The microscopic studies showed the presence of Upper epidermis in surface view, Part of Lamina in section view, cortical parenchyma in longitudinal view, Parenchyma with collapsed tissues, Parenchyma Cells, Epidermal cells with a part of covering trichome, starch granules, reticulated thickened vessels, Transverse Section of leaf of Beaumontia grandiflora showed Upper Epidermis, Lower Epidermis, Hairs, Vascular Bundles, Parenchyma. Phytochemical analysis of leaves of Beaumontia grandiflora indicates that Alkaloids are present. There is a possibility of the presence of some bioactive components in the crude extracts due to which it shows strong activity. Petroleum ether extract shows a greater zone of inhibition at low concentrations. Conclusion: The alkaloids possess good antibacterial activity so the presence of alkaloids may be responsible for the antibacterial activity observed in the crude organic extract of Beaumontia grandiflora.

Keywords: successive solvent extraction, zone of inhibitions., microscopy, phytochemical analysis

Procedia PDF Downloads 20

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

Procedia PDF Downloads 331

Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

Abstract:

This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

Procedia PDF Downloads 431

Authors: Muhammad Ahmad

Abstract:

In this research, Chrysanthemum (morifolium) flowers are used as a natural dye to reduce synthetic dyes and take a step toward sustainability in the fashion industry. The aqueous extraction method is utilized for natural dye extraction and then applied to silk and cotton fabric samples. The color of the dye extracted from dried chrysanthemum flowers is originally a shade of rich green, but after being washed with detergent, it turns to a shade of yellow. Traditional salt and vinegar are used as a natural mordant to fix the dye color. This study also includes a phenolic and chemical analysis of the natural dye (Chrysanthemum flowers) and the textiles (cotton and silk). Compared to cotton fabric, silk fabric has far superior chemical qualities to use in natural dyeing. The results of this study show that the Chrysanthemum flower offers a variety of colors when treated with detergent, without detergent, and with mordants. Chrysanthemum flowers have long been used in other fields, such as medicine; therefore, it is time to start using them in the fashion industry as a natural dye to lessen the harm that synthetic dyes cause.

Keywords: natural dyes, Chrysanthemum flower, sustainability, textile fabrics, chemical and phenolic analysis

Procedia PDF Downloads 15

Authors: Chen Wang, Qiuxiao Chen

Abstract:

With the advent of the information age and the era of big data, urban planning research is no longer satisfied with the analysis and application of traditional data. Because of the limitations of traditional urban commercial center system research, big data provides new opportunities for urban research. Therefore, based on the quantitative evaluation method of big data, the commercial center system of the main city of Hangzhou is analyzed and evaluated, and the scale and hierarchical structure characteristics of the urban commercial center system are studied. In order to make up for the shortcomings of the existing POI extraction method, it proposes a POI extraction method based on adaptive adjustment of search window, which can accurately and efficiently extract the POI data of commercial business in the main city of Hangzhou. Through the visualization and nuclear density analysis of the extracted Point of Interest (POI) data, the current situation of the commercial center system in the main city of Hangzhou is evaluated. Then it compares with the commercial center system structure of 'Hangzhou City Master Plan (2001-2020)', analyzes the problems existing in the planned urban commercial center system, and provides corresponding suggestions and optimization strategy for the optimization of the planning of Hangzhou commercial center system. Then get the following conclusions: The status quo of the commercial center system in the main city of Hangzhou presents a first-level main center, a two-level main center, three third-level sub-centers, and multiple community-level business centers. Generally speaking, the construction of the main center in the commercial center system is basically up to standard, and there is still a big gap in the construction of the sub-center and the regional-level commercial center, further construction is needed. Therefore, it proposes an optimized hierarchical functional system, organizes commercial centers in an orderly manner; strengthens the central radiation to drive surrounding areas; implements the construction guidance of the center, effectively promotes the development of group formation and further improves the commercial center system structure of the main city of Hangzhou.

Keywords: business center system, business format, main city of Hangzhou, POI extraction method

Procedia PDF Downloads 139

Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

Abstract:

Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

Procedia PDF Downloads 168

Authors: K. Parthiban, P. Pradeep, I. Pon Surya Prakash, S. Vinoth, A. Murugan

Abstract:

The main aim of this project is to analyze the performance of vapor compression refrigeration system with alternate refrigerants. Currently we are using R134a as refrigerant. It is used in both household and industrial appliances as refrigerant. It has an advantage that the ozone depletion potential is zero i.e. R134a does not affects ozone layer. But its Global warming potential is considerably high. Also the compressor failure occurs frequently. Hence this project deals with how the performance of R134a varies with blended refrigerants such as R416a and R407c. This analysis is based on how much the Co-efficient of Performance (COP) varies with different refrigerants.

Keywords: compressor, condenser, expansion valve, evaporator

Procedia PDF Downloads 320

Authors: Lorena Coelho, David Ramada, Catarina Nobre, Joaquim Gaião, Juliana Duarte

Abstract:

The development of processes that allows the valorization of waste and by-products generated by industries is crucial to promote symbiotic relationships between different sectors and is mandatory to “close the loop” in the circular economy paradigm. In recent years, by-products and waste from agro-food and forestry sector have attracted attention due to their potential application and technical characteristics. The extraction of bio-based active compounds to be reused is in line with the circular bioeconomy concept trends, combining the use of renewable resources with the process’s circularity, aiming the waste reduction and encouraging reuse and recycling. Among different types of bio-based materials, which are being explored and can be extracted, proteins fractions are becoming an attractive new raw material. Within this context, BioTrace4Leather project, a collaboration between two Technological Centres – CeNTI and CTIC, and a company of Tanning and Finishing of Leather – Curtumes Aveneda, aims to develop innovative and biologically sustainable solutions for leather industry and accomplish the market circularity trends. Specifically, it aims to the valorisation of waste and by-products from the tannery industry through proteins extraction and the development of an innovative and biologically sustainable materials. The achieved results show that keratin, gelatine, and collagen fractions can be successfully extracted from hair and leather bovine waste. These products could be reintegrated into the industrial manufacturing process to attain innovative and functional textile and leather substrates. ACKNOWLEDGEMENT This work has been developed under BioTrace4Leather scope, a project co-funded by Operational Program for Competitiveness and Internationalization (COMPETE) of PORTUGAL2020, through the European Regional Development Fund (ERDF), under grant agreement Nº POCI-01-0247-FEDER-039867.

Keywords: leather by-products, circular economy, sustainability, protein fractions

Procedia PDF Downloads 156

Authors: A. Bouloufa, K. Djessas

Abstract:

In this paper, we reported the effect of substrate temperature on the structural, electrical and optical properties of In2S3 thin films deposited on soda-lime glass substrates by physical vapor deposition technique at various substrate temperatures. The In2Se3 material used for deposition was synthesized from its constituent elements. It was found that all samples exhibit one phase which corresponds to β-In2S3 phase. Values of band gap energy of the films obtained at different substrate temperatures vary in the range of 2.38-2.80 eV and decrease with increasing substrate temperature.

Keywords: buffer layer, In2S3, optical properties, PVD, structural properties

Procedia PDF Downloads 317

Authors: Supakan Rattanakon, Jakkrapan Boonpimon, Akkaragiat Bhuangsaeng, Aphiwat Ratriphruek

Abstract:

Rice bran oil (RBO) has been found to lower the level of serum cholesterol, has antioxidant and anti-carcinogenic property, and attenuate allergic inflammation. These properties of RBO are due to antioxidant compositions, especially, phenolic compounds. The higher amount of these active compounds in RBO, the greater value of RBO is. Thermal process of rice bran before solvent RBO extraction has been found to have a higher phenolic contents. Therefore, the purpose of this study is to using different heating methods on rice bran before the solvent extraction. Then, % yield of RBO, total phenolic content (TPC), and antioxidant property of two white Thai rice; KDML105 and RD6 were determined. The Folin-Ciocalteu colorimetric assay was used to determine TPC and scavenging of free radicals (DPPH) was used to determine antioxidant property expressed as EC50. The result showed that thermal process did not increase % yield of RBO but increase the TPC with 1.41 mg gallic acid equivalent (GAEmg-1). The highest TPC was found in KDML105 by using sonicator. The highest antioxidant activity was found in RD6 using autoclave. The EC50 of RBO was 0.04 mg/mL. Further study should be performed on different pretreatments to increase the TPC and antioxidant property.

Keywords: antioxidant, rice bran oil, total phenol content, white rice

Procedia PDF Downloads 250

Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

Abstract:

Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

Procedia PDF Downloads 152

Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

Abstract:

This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

Procedia PDF Downloads 665

Authors: Tarikayehu Amanuel, Abraham Mohammed

Abstract:

The production of biodiesel from waste materials is becoming an increasingly important research area in the field of renewable energy. One potential waste material source is avocado, a fruit with a large seed and peel that are typically discarded after consumption. This research aims to investigate the feasibility of using avocado waste as a feedstock for the production of biodiesel. The study focuses on extracting oil from the waste material using the transesterification technique and then characterizing the properties of oil to determine its suitability for conversion to biodiesel. The study was conducted experimentally, and a maximum oil yield of 11.583% (150g of oil produced from 1.295kg of avocado waste powder) was obtained from avocado waste powder at an extraction time of 4hr. An 87% fatty acid methyl ester (biodiesel) conversion was also obtained using a methanol/oil ratio of 6:1, 1.3g NaOH, reaction time 60min, and 65°C reaction temperature. Furthermore, from 145 ml of avocado waste oil, 126.15 ml of biodiesel was produced, indicating a high percentage of conversion (87%). Conclusively, the produced biodiesel showed comparable physical and chemical characteristics to that of standard biodiesel samples considered for the study. The results of this research could help to identify a new source of biofuel production while also addressing the issue of waste disposal in the food industry.

Keywords: biodiesel, avocado, transesterification, soxhlet extraction

Procedia PDF Downloads 68

Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

Abstract:

This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

Procedia PDF Downloads 19

Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

Procedia PDF Downloads 256

Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

Abstract:

We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

Procedia PDF Downloads 139

Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

Abstract:

The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

Procedia PDF Downloads 147

Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

Abstract:

The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

Procedia PDF Downloads 364

Authors: Y. B. Idris, M. Sirajo, L. G. Hassan, T. Izuagie, T. Muktar, I. Lawal, A. U. Abubakar

Abstract:

This study investigates the extraction, phytochemical composition, and antimicrobial activity of bioactive compounds from red millipedes using three different solvents: n-Hexane, Chloroform, and Methanol. The largest yield was obtained from the methanol extract, which had percentage yields of 0.8%, 2.2%, and 5.6%, respectively. Terpenoids and sterols were found in all extracts according to preliminary zoochemical screening, but only the methanol extract included saponins and phenols. With a maximum zone of inhibition of 9 mm at 1000 µg/ml, antimicrobial susceptibility tests revealed that the methanol extract had the strongest antibacterial activity, especially against Escherichia coli and Staphylococcus aureus. Significant activity was also shown by the n-hexane extract, although the chloroform extract had only mild antibacterial activity. Tests for minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) verified that the methanol extract was more effective than the other extracts, particularly against S. aureus and S. typhi. None of the extracts, nonetheless, showed any discernible antifungal action. The potential of red millipede extracts, especially those based on methanol, as a source of antimicrobial chemicals for use in the future is highlighted by this work.

Keywords: millipedes, defensive extraction, antibacterial, antifungal, antimicrobial, minimum inhibitory concentration (MIC), minimum bacterial concentration (MBC)

Procedia PDF Downloads 9