Search results for: VFA membrane extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3010

Search results for: VFA membrane extraction

670 Mordenite as Catalyst Support for Complete Volatile Organic Compounds Oxidation

Authors: Yuri A. Kalvachev, Totka D. Todorova

Abstract:

Zeolite mordenite has been investigated as a transition metal support for the preparation of efficient catalysts in the oxidation of volatile organic compounds (VOCs). The highly crystalline mordenite samples were treated with hydrofluoric acid and ammonium fluoride to get hierarchical material with secondary porosity. The obtained supports by this method have a high active surface area, good diffusion properties and prevent the extraction of metal components during catalytic reactions. The active metal phases platinum and copper were loaded by impregnation on both mordenite materials (parent and acid treated counterparts). Monometalic Pt and Cu, and bimetallic Pt/Cu catalysts were obtained. The metal phases were fine dispersed as nanoparticles on the functional porous materials. The catalysts synthesized in this way were investigated in the reaction of complete oxidation of propane and benzene. Platinum, copper and platinum/copper were loaded and there catalytic activity was investigated and compared. All samples are characterized by X-ray diffraction analysis, nitrogen adsorption, scanning electron microscopy (SEM), X-ray photoelectron measurements (XPS) and temperature programed reduction (TPR). The catalytic activity of the samples obtained is investigated in the reaction of complete oxidation of propane and benzene by using of Gas Chromatography (GC). The oxidation of three organic molecules was investigated—methane, propane and benzene. The activity of metal loaded mordenite catalysts for methane oxidation is almost the same for parent and treated mordenite as a support. For bigger molecules as propane and benzene, the activity of catalysts based on treated mordenite is higher than those based on parent zeolite.

Keywords: metal loaded catalysts, mordenite, VOCs oxidation, zeolites

Procedia PDF Downloads 130
669 Rhizobia-Containing Rhizobacterial Consortia and Intercropping Improved Faba Bean and Wheat Performances Under Stress Combining Drought and Phosphorus Deficiency

Authors: Said Cheto, Khawla Oukaltouma, Imane Chamkhi, Ammar Ibn Yasser, Bouchra Benmrid, Ahmed Qaddoury, Lamfeddal Kouisni, Joerg Geistlinger, Youssef Zeroual, Adnane Bargaz, Cherki Ghoulam

Abstract:

Our study aimed to assess, the role of inoculation of faba bean/wheat intercrops with selected rhizobacteria consortia gathering one rhizobia and two phosphate solubilizing bacteria “PSB” to alleviate the effects of combined water deficit and P limitation on Faba bean/ wheat intercrops versus monocrops under greenhouse conditions. One Vicia faba L variety (Aguadulce “Ag”), and one Triticum durum L. variety (Karim “K”) were grown as sole crops or intercrop in pots containing sterilized substrate (sand: peat 4:1v/v) added either with rock phosphate (RP) as the alone P source (P limitation) or with KH₂PO₄ in nutrient solution (P sufficient control). Plant inoculation was done using rhizobacterial consortia composed; C1(Rhizobium laguerreae, Kocuria sp, and Pseudomonas sp) and C2 (R. laguerreae, Rahnella sp, and Kocuria sp). Two weeks after inoculation, the plants were submitted to water deficit consisting of 40% of substrate water holding Capacity (WHC) versus 80% WHC for well-watered plants. At the flowering stage, the trial was assessed, and the results showed that inoculation with both consortia (C1 and C2) improved faba bean biomass in terms of shoots, roots, and nodules compared to inoculation with rhizobia alone, particularly C2 improved these parametres by 19.03, 78.99, and 72.73%, respectively. Leaf relative water content decreased under combined stress, particularly in response to C1 with a significant improvement of this parameter in wheat intercrops. For faba bean under P limitation, inoculation with C2 increased stomatal conductance (gs) by 35.73% compared to plants inoculated with rhizobia alone. Furthermore, the same inoculum C2 improved membrane stability by 44,33% versus 16,16% for C1 compared to inoculation with rhizobia alone under P deficit. For sole cropped faba bean plants, inoculation with both consortia improved N accumulation compared to inoculation with rhizobia alone with an increase of 70.75% under P limitation. Moreover, under the combined stress, intercropping inoculation with C2 improved plant biomass and N content (112.98%) in wheat plants, compared to the sole crop. Our finding revealed that consortium C2 might offer an agronomic advantage under water and P deficit and could be used as inoculum for enhancing faba bean and wheat production under both monocropping and intercropping systems.

Keywords: drought, phosphorus, intercropping, PSB, rhizobia, vicia faba, Triticum durum

Procedia PDF Downloads 73
668 Transdermal Delivery of Sodium Diclofenac from Palm Kernel Oil Esteres Nanoemulsions

Authors: Malahat Rezaee, Mahiran Basri, Abu Bakar Salleh, Raja Noor Zaliha Raja Abdul Rahman

Abstract:

Sodium diclofenac is one of the most commonly used drugs of nonsteroidal anti-inflammatory drugs (NSAIDs). It is especially effective in the controlling the severe conditions of inflammation and pain, musculoskeletal disorders, arthritis, and dysmenorrhea. Formulation as nanoemulsions is one of the nanoscience approaches that has been progressively considered in pharmaceutical science for transdermal delivery of the drug. Nanoemulsions are a type of emulsion with particle sizes ranging from 20 nm to 200 nm. An emulsion is formed by the dispersion of one liquid, usually the oil phase in another immiscible liquid, water phase that is stabilized using the surfactant. Palm kernel oil esters (PKOEs), in comparison to other oils, contain higher amounts of shorter chain esters, which suitable to be applied in micro and nanoemulsion systems as a carrier for actives, with excellent wetting behavior without the oily feeling. This research aimed to study the effect of terpene type and concentration on sodium diclofenac permeation from palm kernel oil esters nanoemulsions and physicochemical properties of the nanoemulsions systems. The effect of various terpenes of geraniol, menthone, menthol, cineol and nerolidol at different concentrations of 0.5, 1.0, 2.0, and 4.0% on permeation of sodium diclofenac were evaluated using Franz diffusion cells and rat skin as permeation membrane. The results of this part demonstrated that all terpenes showed promoting effect on sodium diclofenac penetration. However, menthol and menthone at all concentrations showed significant effects (<0.05) on drug permeation. The most outstanding terpene was menthol with the most significant effect for skin permeability of sodium diclofenac. The effect of terpenes on physicochemical properties of nanoemulsion systems was investigated on the parameters of particle size, zeta potential, pH, viscosity and electrical conductivity. The result showed that all terpenes had the significant effect on particle size and non-significant effects on the zeta potential of the nanoemulsion systems. The effect of terpenes was significant on pH, excluding the menthone at concentrations of 0.5 and 1.0%, and cineol and nerolidol at the concentration of 2.0%. Terpenes also had significant effect on viscosity of nanoemulsions exception of menthone and cineol at the concentration of 0.5%. The result of conductivity measurements showed that all terpenes at all concentration except cineol at the concentration of 0.5% represented significant effect on electrical conductivity.

Keywords: nanoemulsions, palm kernel oil esters, sodium diclofenac, terpenes, skin permeation

Procedia PDF Downloads 421
667 Preserving Urban Cultural Heritage with Deep Learning: Color Planning for Japanese Merchant Towns

Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue

Abstract:

With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.

Keywords: historic districts, color planning, semantic segmentation, natural language processing

Procedia PDF Downloads 88
666 Unlocking Justice: Exploring the Power and Challenges of DNA Analysis in the Criminal Justice System

Authors: Sandhra M. Pillai

Abstract:

This article examines the relevance, difficulties, and potential applications of DNA analysis in the criminal justice system. A potent tool for connecting suspects to crime sites, clearing the innocent of wrongdoing, and resolving cold cases, DNA analysis has transformed forensic investigations. The scientific foundations of DNA analysis, including DNA extraction, sequencing, and statistical analysis, are covered in the article. To guarantee accurate and trustworthy findings, it also discusses the significance of quality assurance procedures, chain of custody, and DNA sample storage. DNA analysis has significantly advanced science, but it also brings up substantial moral and legal issues. To safeguard individual rights and uphold public confidence, privacy concerns, possible discrimination, and abuse of DNA information must be properly addressed. The paper also emphasises the effects of the criminal justice system on people and communities while highlighting the necessity of equity, openness, and fair access to DNA testing. The essay describes the obstacles and future directions for DNA analysis. It looks at cutting-edge technology like next-generation sequencing, which promises to make DNA analysis quicker and more affordable. To secure the appropriate and informed use of DNA evidence, it also emphasises the significance of multidisciplinary collaboration among scientists, law enforcement organisations, legal experts, and policymakers. In conclusion, DNA analysis has enormous potential for improving the course of criminal justice. We can exploit the potential of DNA technology while respecting the ideals of justice, fairness, and individual rights by navigating the ethical, legal, and societal issues and encouraging discussion and collaboration.

Keywords: DNA analysis, DNA evidence, reliability, validity, legal frame, admissibility, ethical considerations, impact, future direction, challenges

Procedia PDF Downloads 64
665 Computational Intelligence and Machine Learning for Urban Drainage Infrastructure Asset Management

Authors: Thewodros K. Geberemariam

Abstract:

The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 152
664 Credit Card Fraud Detection with Ensemble Model: A Meta-Heuristic Approach

Authors: Gong Zhilin, Jing Yang, Jian Yin

Abstract:

The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 131
663 A Systematic Review and Meta-Analysis of Diabetes Ketoacidosis in Ethiopia

Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu

Abstract:

Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.

Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis

Procedia PDF Downloads 59
662 Component Test of Martensitic/Ferritic Steels and Nickel-Based Alloys and Their Welded Joints under Creep and Thermo-Mechanical Fatigue Loading

Authors: Daniel Osorio, Andreas Klenk, Stefan Weihe, Andreas Kopp, Frank Rödiger

Abstract:

Future power plants currently face high design requirements due to worsening climate change and environmental restrictions, which demand high operational flexibility, superior thermal performance, minimal emissions, and higher cyclic capability. The aim of the paper is, therefore, to investigate the creep and thermo-mechanical material behavior of improved materials experimentally and welded joints at component scale under near-to-service operating conditions, which are promising for application in highly efficient and flexible future power plants. These materials promise an increase in flexibility and a reduction in manufacturing costs by providing enhanced creep strength and, therefore, the possibility for wall thickness reduction. At the temperature range between 550°C and 625°C, the investigation focuses on the in-phase thermo-mechanical fatigue behavior of dissimilar welded joints of conventional materials (ferritic and martensitic material T24 and T92) to nickel-based alloys (A617B and HR6W) by means of membrane test panels. The temperature and external load are varied in phase during the test, while the internal pressure remains constant. At the temperature range between 650°C and 750°C, it focuses on the creep behavior under multiaxial stress loading of similar and dissimilar welded joints of high temperature resistant nickel-based alloys (A740H, A617B, and HR6W) by means of a thick-walled-component test. In this case, the temperature, the external axial load, and the internal pressure remain constant during testing. Numerical simulations are used for the estimation of the axial component load in order to induce a meaningful damage evolution without causing a total component failure. Metallographic investigations after testing will provide support for understanding the damage mechanism and the influence of the thermo-mechanical load and multiaxiality on the microstructure change and on the creep and TMF- strength.

Keywords: creep, creep-fatigue, component behaviour, weld joints, high temperature material behaviour, nickel-alloys, high temperature resistant steels

Procedia PDF Downloads 119
661 Magnetized Cellulose Nanofiber Extracted from Natural Resources for the Application of Hexavalent Chromium Removal Using the Adsorption Method

Authors: Kebede Gamo Sebehanie, Olu Emmanuel Femi, Alberto Velázquez Del Rosario, Abubeker Yimam Ali, Gudeta Jafo Muleta

Abstract:

Water pollution is one of the most serious worldwide issues today. Among water pollution, heavy metals are becoming a concern to the environment and human health due to their non-biodegradability and bioaccumulation. In this study, a magnetite-cellulose nanocomposite derived from renewable resources is employed for hexavalent chromium elimination by adsorption. Magnetite nanoparticles were synthesized directly from iron ore using solvent extraction and co-precipitation technique. Cellulose nanofiber was extracted from sugarcane bagasse using the alkaline treatment and acid hydrolysis method. Before and after the adsorption process, the MNPs-CNF composites were evaluated using X-ray diffraction (XRD), Scanning electron microscope (SEM), Fourier transform infrared (FTIR), and Vibrator sample magnetometer (VSM), and Thermogravimetric analysis (TGA). The impacts of several parameters such as pH, contact time, initial pollutant concentration, and adsorbent dose on adsorption efficiency and capacity were examined. The kinetic and isotherm adsorption of Cr (VI) was also studied. The highest removal was obtained at pH 3, and it took 80 minutes to establish adsorption equilibrium. The Langmuir and Freundlich isotherm models were used, and the experimental data fit well with the Langmuir model, which has a maximum adsorption capacity of 8.27 mg/g. The kinetic study of the adsorption process using pseudo-first-order and pseudo-second-order equations revealed that the pseudo-second-order equation was more suited for representing the adsorption kinetic data. Based on the findings, pure MNPs and MNPs-CNF nanocomposites could be used as effective adsorbents for the removal of Cr (VI) from wastewater.

Keywords: magnetite-cellulose nanocomposite, hexavalent chromium, adsorption, sugarcane bagasse

Procedia PDF Downloads 129
660 Noncovalent Antibody-Nanomaterial Conjugates: A Simple Approach to Produce Targeted Nanomedicines

Authors: Nicholas Fletcher, Zachary Houston, Yongmei Zhao, Christopher Howard, Kristofer Thurecht

Abstract:

One promising approach to enhance nanomedicine therapeutic efficacy is to include a targeting agent, such as an antibody, to increase accumulation at the tumor site. However, the application of such targeted nanomedicines remains limited, in part due to difficulties involved with biomolecule conjugation to synthetic nanomaterials. One approach recently developed to overcome this has been to engineer bispecific antibodies (BsAbs) with dual specificity, whereby one portion binds to methoxy polyethyleneglycol (mPEG) epitopes present on synthetic nanomedicines, while the other binds to molecular disease markers of interest. In this way, noncovalent complexes of nanomedicine core, comprising a hyperbranched polymer (HBP) of primarily mPEG, decorated with targeting ligands are able to be produced by simple mixing. Further work in this area has now demonstrated such complexes targeting the breast cancer marker epidermal growth factor receptor (EGFR) to show enhanced binding to tumor cells both in vitro and in vivo. Indeed the enhanced accumulation at the tumor site resulted in improved therapeutic outcomes compared to untargeted nanomedicines and free chemotherapeutics. The current work on these BsAb-HBP conjugates focuses on further probing antibody-nanomaterial interactions and demonstrating broad applicability to a range of cancer types. Herein are reported BsAb-HBP materials targeted towards prostate-specific membrane antigen (PSMA) and study of their behavior in vivo using ⁸⁹Zr positron emission tomography (PET) in a dual-tumor prostate cancer xenograft model. In this model mice bearing both PSMA+ and PSMA- tumors allow for PET imaging to discriminate between nonspecific and targeted uptake in tumors, and better quantify the increased accumulation following BsAb conjugation. Also examined is the potential for formation of these targeted complexes in situ following injection of individual components? The aim of this approach being to avoid undesirable clearance of proteinaceous complexes upon injection limiting available therapeutic. Ultimately these results demonstrate BsAb functionalized nanomaterials as a powerful and versatile approach for producing targeted nanomedicines for a variety of cancers.

Keywords: bioengineering, cancer, nanomedicine, polymer chemistry

Procedia PDF Downloads 141
659 Morphological and Molecular Evaluation of Dengue Virus Serotype 3 Infection in BALB/c Mice Lungs

Authors: Gabriela C. Caldas, Fernanda C. Jacome, Arthur da C. Rasinhas, Ortrud M. Barth, Flavia B. dos Santos, Priscila C. G. Nunes, Yuli R. M. de Souza, Pedro Paulo de A. Manso, Marcelo P. Machado, Debora F. Barreto-Vieira

Abstract:

The establishment of animal models for studies of DENV infections has been challenging, since circulating epidemic viruses do not naturally infect nonhuman species. Such studies are of great relevance to the various areas of dengue research, including immunopathogenesis, drug development and vaccines. In this scenario, the main objective of this study is to verify possible morphological changes, as well as the presence of antigens and viral RNA in lung samples from BALB/c mice experimentally infected with an epidemic and non-neuroadapted DENV-3 strain. Male BALB/c mice, 2 months old, were inoculated with DENV-3 by intravenous route. After 72 hours of infection, the animals were euthanized and the lungs were collected. Part of the samples was processed by standard technique for analysis by light and transmission electronic microscopies and another part was processed for real-time PCR analysis. Morphological analyzes of lungs from uninfected mice showed preserved tissue areas. In mice infected with DENV-3, the analyzes revealed interalveolar septum thickening with presence of inflammatory infiltrate, foci of alveolar atelectasis and hyperventilation, bleeding foci in the interalveolar septum and bronchioles, peripheral capillary congestion, accumulation of fluid in the blood capillary, signs of interstitial cell necrosis presence of platelets and mononuclear inflammatory cells circulating in the capillaries and/or adhered to the endothelium. In addition, activation of endothelial cells, platelets, mononuclear inflammatory cell and neutrophil-type polymorphonuclear inflammatory cell evidenced by the emission of cytoplasmic membrane prolongation was observed. DEN-like particles were seen in the cytoplasm of endothelial cells. The viral genome was recovered from 3 in 12 lung samples. These results demonstrate that the BALB / c mouse represents a suitable model for the study of the histopathological changes induced by DENV infection in the lung, with tissue alterations similar to those observed in human cases of DEN.

Keywords: BALB/c mice, dengue, histopathology, lung, ultrastructure

Procedia PDF Downloads 253
658 A Multi-Templated Fe-Ni-Cu Ion Imprinted Polymer for the Selective and Simultaneous Removal of Toxic Metallic Ions from Wastewater

Authors: Morlu Stevens, Bareki Batlokwa

Abstract:

The use of treated wastewater is widely employed to compensate for the scarcity of safe and uncontaminated freshwater. However, the existence of toxic heavy metal ions in the wastewater pose a health hazard to animals and the environment, hence, the importance for an effective technique to tackle the challenge. A multi-templated ion imprinted sorbent (Fe,Ni,Cu-IIP) for the simultaneous removal of heavy metal ions from waste water was synthesised employing molecular imprinting technology (MIT) via thermal free radical bulk polymerization technique. Methacrylic acid (MAA) was employed as the functional monomer, and ethylene glycol dimethylacrylate (EGDMA) as cross-linking agent, azobisisobutyronitrile (AIBN) as the initiator, Fe, Ni, Cu ions as template ions, and 1,10-phenanthroline as the complexing agent. The template ions were exhaustively washed off the synthesized polymer by solvent extraction in several washing steps, while periodically increasing solvent (HCl) concentration from 1.0 M to 10.0 M. The physical and chemical properties of the sorbents were investigated using Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were employed. Optimization of operational parameters such as time, pH and sorbent dosage to evaluate the effectiveness of sorbents were investigated and found to be 15 min, 7.5 and 666.7 mg/L respectively. Selectivity of ion-imprinted polymers and competitive sorption studies between the template and similar ions were carried out and showed good selectivity towards the targeted metal ion by removing 90% - 98% of the templated ions as compared to 58% - 62% of similar ions. The sorbents were further applied for the selective removal of Fe, Ni and Cu from real wastewater samples and recoveries of 92.14 ± 0.16% - 106.09 ± 0.17% and linearities of R2 = 0.9993 - R2 = 0.9997 were achieved.

Keywords: ion imprinting, ion imprinted polymers, heavy metals, wastewater

Procedia PDF Downloads 313
657 Changes on Some Physical and Chemical Properties of Red Beetroot Juice during Ultrasound Pretreatment

Authors: Serdal Sabanci, Mutlu Çevik, Derya Tezcan, Cansu Çelebi, Filiz Içier

Abstract:

Ultrasound is defined as sound waves having frequencies higher than 20 kHz, which is greater than the limits of the human hearing range. In recent years, ultrasonic treatment is an emerging technology being used increasingly in the food industry. It is applied as an alternative technique for different purposes such as microbial and enzyme inactivation, extraction, drying, filtration, crystallization, degas, cutting etc. Red beetroot (Beta vulgaris L.) is a root vegetable which is rich in mineral components, folic acid, dietary fiber, anthocyanin pigments. In this study, the application of low frequency high intensity ultrasound to the red beetroot slices and red beetroot juice for different treatment times (0, 5, 10, 15, 20 min) was investigated. Ultrasonicated red beetroot slices were also squeezed immediately. Changes on colour, betanin, pH and titratable acidity properties of red beetroot juices (the ultrasonicated juice (UJ) and the juice from ultrasonicated slices (JUS)) were determined. Although there was no significant difference statistically in the changes of color value of JUS samples due to ultrasound application (p>0.05), the color properties of UJ samples ultrasonicated for low durations were statistically different from raw material (p<0.05). The difference between color values of UJ and raw material disappeared (p>0.05) as the ultrasonication duration increased. The application of ultrasound to red beet root slices adversely affected and decreased the betanin content of JUS samples. On the other hand, the betanin content of UJ samples increased as the ultrasonication duration increased. Ultrasound treatment did not affect pH and titratable acidity of red beetroot juices statistically (p>0.05). The results suggest that ultrasound technology is the simple and economical technique which may successfully be employed for the processing of red beetroot juice with improved color and betanin quality. However, further investigation is still needed to confirm this.

Keywords: red beetroot, ultrasound, color, betanin

Procedia PDF Downloads 399
656 A Study on Soil Micro-Arthropods Assemblage in Selected Plantations in The Nilgiris, Tamilnadu

Authors: J. Dharmaraj, C. Gunasekaran

Abstract:

Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.

Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris

Procedia PDF Downloads 308
655 Frequency of Alloimmunization in Sickle Cell Disease Patients in Africa: A Systematic Review with Meta-analysis

Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

Abstract:

Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

Procedia PDF Downloads 99
654 An Integrated Label Propagation Network for Structural Condition Assessment

Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

Abstract:

Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

Procedia PDF Downloads 97
653 Flexible Coupling between Gearbox and Pump (High Speed Machine)

Authors: Naif Mohsen Alharbi

Abstract:

This paper present failure occurred on flexible coupling installed at oil anf gas operation. Also it presents maintenance ideas implemented on the flexible coupling installed to transmit high torque from gearbox to pump. Basically, the machine train is including steam turbine which drives the pump and there is gearbox located in between for speed reduction. investigation are identifying the root causes, solving and developing the technology designs or bad actor. This report provides the study intentionally for continues operation optimization, utilize the advanced opportunity and implement a improvement. Objective: The main objectives of the investigation are identifying the root causes, solving and developing the technology designs or bad actor. Ultimately, fulfilling the operation productivity, also ensuring better technology, quality and design by solutions. This report provides the study intentionally for continues operation optimization, utilize the advanced opportunity and implemet improvement. Method: The method used in this project was a very focused root cause analysis procedure that incorporated engineering analysis and measurements. The analysis method extensively covers the measuring of the complete coupling dimensions. Including the membranes thickness, hubs, bore diameter and total length, dismantle flexible coupling to diagnose how deep the coupling has been affected. Also, defining failure modes, so that the causes could be identified and verified. Moreover, Vibration analysis and metallurgy test. Lastly applying several solutions by advanced tools (will be mentioned in detail). Results and observation: Design capacity: Coupling capacity is an inadequate to fulfil 100% of operating conditions. Therefore, design modification of service factor to be at least 2.07 is crucial to address this issue and prevent recurrence of similar scenario, especially for the new upgrading project. Discharge fluctuation: High torque flexible coupling encountered during the operation. Therefore, discharge valve behaviour, tuning, set point and general conditions revaluated and modified subsequently, it can be used as baseline for upcoming Coupling design project. Metallurgy test: Material of flexible coupling membrane (discs) tested at the lab, for a detailed metallurgical investigation, better material grade has been selected for our operating conditions,

Keywords: high speed machine, reliabilty, flexible coupling, rotating equipment

Procedia PDF Downloads 68
652 Work System Design in Productivity for Small and Medium Enterprises: A Systematic Literature Review

Authors: Silipa Halofaki, Devi R. Seenivasagam, Prashant Bijay, Kritin Singh, Rajeshkannan Ananthanarayanan

Abstract:

This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria, such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality, were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.

Keywords: literature review, productivity, small and medium sized enterprises-SMEs, work system design

Procedia PDF Downloads 93
651 Evaluation of Life Cycle Assessment in Furniture Manufacturing by Analytical Hierarchy Process

Authors: Majid Azizi, Payam Ghorbannezhad, Mostafa Amiri, Mohammad Ghofrani

Abstract:

Environmental issues in the furniture industry are of great importance due to the use of natural materials such as wood and chemical substances like adhesives and paints. These issues encompass environmental conservation and managing pollution and waste generated. Improper use of wood resources, along with the use of chemicals and their release, leads to the depletion of natural resources, damage to forests, and the emission of greenhouse gases. Therefore, identifying influential indicators in the life cycle assessment of classic furniture and proposing solutions to reduce environmental impacts becomes crucial. In this study, the life cycle of classic furniture was evaluated using a hierarchical analytical process from cradle to grave. The life cycle assessment was employed to assess the environmental impacts of the furniture industry, ranging from raw material extraction to waste disposal and recycling. The most significant indicators in the furniture industry's production chain were also identified. The results indicated that the wood quality indicator is the most essential factor in the life cycle of classic furniture. Furthermore, the relative contribution of each type of traditional furniture was proposed concerning impact categories in the life cycle assessment. The results showed that among the three proposed types, the design and production of furniture with prefabricated parts had the most negligible impact in categories such as global warming potential and ozone layer depletion compared to furniture design with solid wood and furniture design with recycled components. Among the three suggested types of furniture to reduce environmental impacts, producing furniture with solid wood or other woods was chosen as the most crucial solution.

Keywords: life cycle assessment, analytic hierarchy process, environmental issues, furniture

Procedia PDF Downloads 64
650 Functional Performance of Unpaved Roads Reinforced with Treated Coir Geotextiles

Authors: Priya Jaswal, Vivek, S. K. Sinha

Abstract:

One of the most important and complicated factors influencing the functional performance of unpaved roads is traffic loading. The complexity of traffic loading is caused by the variable magnitude and frequency of load, which causes unpaved roads to fail prematurely. Unpaved roads are low-volume roads, and as peri-urbanization increases, unpaved roads act as a means to boost the rural economy. This has also increased traffic on unpaved roads, intensifying the issue of settlement, rutting, and fatigue failure. This is a major concern for unpaved roads built on poor subgrade soil, as excessive rutting caused by heavy loads can cause driver discomfort, vehicle damage, and an increase in maintenance costs. Some researchers discovered that when a consistent static load is exerted as opposed to a rapidly changing load, the rate of deformation of unpaved roads increases. Previously, some of the most common methods for overcoming the problem of rutting and fatigue failure included chemical stabilisation, fibre reinforcement, and so on. However, due to their high cost, engineers' attention has shifted to geotextiles which are used as reinforcement in unpaved roads. Geotextiles perform the function of filtration, lateral confinement of base material, vertical restraint of subgrade soil, and the tension membrane effect. The use of geotextiles in unpaved roads increases the strength of unpaved roads and is an economically viable method because it reduces the required aggregate thickness, which would need less earthwork, and is thus recommended for unpaved road applications. The majority of geotextiles used previously were polymeric, but with a growing awareness of sustainable development to preserve the environment, researchers' focus has shifted to natural fibres. Coir is one such natural fibre that possesses the advantage of having a higher tensile strength than other bast fibres, being eco-friendly, low in cost, and biodegradable. However, various researchers have discovered that the surface of coir fibre is covered with various impurities, voids, and cracks, which act as a plane of weakness and limit the potential application of coir geotextiles. To overcome this limitation, chemical surface modification of coir geotextiles is widely accepted by researchers because it improves the mechanical properties of coir geotextiles. The current paper reviews the effect of using treated coir geotextiles as reinforcement on the load-deformation behaviour of a two-layered unpaved road model.

Keywords: coir, geotextile, treated, unpaved

Procedia PDF Downloads 94
649 Low-Cost Image Processing System for Evaluating Pavement Surface Distress

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 181
648 Deep Learning-Based Approach to Automatic Abstractive Summarization of Patent Documents

Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

Abstract:

A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

Procedia PDF Downloads 123
647 Solvent-Aided Dispersion of Tannic Acid to Enhance Flame Retardancy of Epoxy

Authors: Matthew Korey, Jeffrey Youngblood, John Howarter

Abstract:

Background and Significance: Tannic acid (TA) is a bio-based high molecular weight organic, aromatic molecule that has been found to increase thermal stability and flame retardancy of many polymer matrices when used as an additive. Although it is biologically sourced, TA is a pollutant in industrial wastewater streams, and there is a desire to find applications in which to downcycle this molecule after extraction from these streams. Additionally, epoxy thermosets have revolutionized many industries, but are too flammable to be used in many applications without additives which augment their flame retardancy (FR). Many flame retardants used in epoxy thermosets are synthesized from petroleum-based monomers leading to significant environmental impacts on the industrial scale. Many of these compounds also have significant impacts on human health. Various bio-based modifiers have been developed to improve the FR of the epoxy resin; however, increasing FR of the system without tradeoffs with other properties has proven challenging, especially for TA. Methodologies: In this work, TA was incorporated into the thermoset by use of solvent-exchange using methyl ethyl ketone, a co-solvent for TA, and epoxy resin. Samples were then characterized optically (UV-vis spectroscopy and optical microscopy), thermally (thermogravimetric analysis and differential scanning calorimetry), and for their flame retardancy (mass loss calorimetry). Major Findings: Compared to control samples, all samples were found to have increased thermal stability. Further, the addition of tannic acid to the polymer matrix by the use of solvent greatly increased the compatibility of the additive in epoxy thermosets. By using solvent-exchange, the highest loading level of TA found in literature was achieved in this work (40 wt%). Conclusions: The use of solvent-exchange shows promises for circumventing the limitations of TA in epoxy.

Keywords: sustainable, flame retardant, epoxy, tannic acid

Procedia PDF Downloads 130
646 Prevalence of Visual Impairment among School Children in Ethiopia: A Systematic Review and Meta-Analysis

Authors: Merkineh Markos Lorato, Gedefaw Diress Alene

Abstract:

Introduction: Visual impairment is any condition of the eye or visual system that results in loss/reduction of visual functioning. It significantly influences the academic routine and social activities of children, and the effect is severe for low-income countries like Ethiopia. So, this study aimed to determine the pooled prevalence of visual impairment among school children in Ethiopia. Methods: Databases such as Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, World Wide Web of Science, and Cochrane Library searched to retrieve eligible articles. In addition, Google Scholar and a reference list of the retrieved eligible articles were addressed. Studies that reported the prevalence of visual impairment were included to estimate the pooled prevalence. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and analysis was held using STATA 11 statistical software. I² was used to assess the heterogeneity. Because of considerable heterogeneity, a random effect meta-analysis model was used to estimate the pooled prevalence of visual impairment among school children in Ethiopia. Results: The result of 9 eligible studies showed that the pooled prevalence of visual impairment among school children in Ethiopia was 7.01% (95% CI: 5.46, 8.56%). In the subgroup analysis, the highest prevalence was reported in South Nations Nationalities and Tigray region together (7.99%; 3.63, 12.35), while the lowest prevalence was reported in Addis Ababa (5.73%; 3.93, 7.53). Conclusion: The prevalence of visual impairment among school children is significantly high in Ethiopia. If it is not detected and intervened early, it will cause a lifetime threat to visually impaired school children, so that school vision screening program plan and its implementation may cure the life quality of future generations in Ethiopia.

Keywords: visual impairment, school children, Ethiopia, prevalence

Procedia PDF Downloads 36
645 A Review on Silicon Based Induced Resistance in Plants against Insect Pests

Authors: Asim Abbasi, Muhammad Sufyan, Muhammad Kamran, Iqra

Abstract:

Development of resistance in insect pests against various groups of insecticides has prompted the use of alternative integrated pest management approaches. Among these induced host plant resistance represents an important strategy as it offers a practical, cheap and long lasting solution to keep pests populations below economic threshold level (ETL). Silicon (Si) has a major role in regulating plant eco-relationship by providing strength to the plant in the form of anti-stress mechanism which was utilized in coping with the environmental extremes to get a better yield and quality end produce. Among biotic stresses, insect herbivore signifies one class against which Si provide defense. Silicon in its neutral form (H₄SiO₄) is absorbed by the plants via roots through an active process accompanied by the help of different transporters which were located in the plasma membrane of root cells or by a passive process mostly regulated by transpiration stream, which occurs via the xylem cells along with the water. Plants tissues mainly the epidermal cell walls are the sinks of absorbed silicon where it polymerizes in the form of amorphous silica or monosilicic acid. The noteworthy function of this absorbed silicon is to provide structural rigidity to the tissues and strength to the cell walls. Silicon has both direct and indirect effects on insect herbivores. Increased abrasiveness and hardness of epidermal plant tissues and reduced digestibility as a result of deposition of Si primarily as phytoliths within cuticle layer is now the most authenticated mechanisms of Si in enhancing plant resistance to insect herbivores. Moreover, increased Si content in the diet also impedes the efficiency by which insects transformed consumed food into the body mass. The palatability of food material has also been changed by Si application, and it also deters herbivore feeding for food. The production of defensive compounds of plants like silica and phenols have also been amplified by the exogenous application of silicon sources which results in reduction of the probing time of certain insects. Some studies also highlighted the role of silicon at the third trophic level as it also attracts natural enemies of insects attacking the crop. Hence, the inclusion of Si in pest management approaches can be a healthy and eco-friendly tool in future.

Keywords: defensive, phytoliths, resistance, stresses

Procedia PDF Downloads 188
644 Patient Tracking Challenges During Disasters and Emergencies

Authors: Mohammad H. Yarmohammadian, Reza Safdari, Mahmoud Keyvanara, Nahid Tavakoli

Abstract:

One of the greatest challenges in disaster and emergencies is patient tracking. The concept of tracking has different denotations. One of the meanings refers to tracking patients’ physical locations and the other meaning refers to tracking patients ‘medical needs during emergency services. The main goal of patient tracking is to provide patient safety during disaster and emergencies and manage the flow of patient and information in different locations. In most of cases, there are not sufficient and accurate data regarding the number of injuries, medical conditions and their accommodation and transference. The objective of the present study is to survey on patient tracking issue in natural disaster and emergencies. Methods: This was a narrative study in which the population was E-Journals and the electronic database such as PubMed, Proquest, Science direct, Elsevier, etc. Data was gathered by Extraction Form. All data were analyzed via content analysis. Results: In many countries there is no appropriate and rapid method for tracking patients and transferring victims after the occurrence of incidents. The absence of reliable data of patients’ transference and accommodation, even in the initial hours and days after the occurrence of disasters, and coordination for appropriate resource allocation, have faced challenges for evaluating needs and services challenges. Currently, most of emergency services are based on paper systems, while these systems do not act appropriately in great disasters and incidents and this issue causes information loss. Conclusion: Patient tracking system should update the location of patients or evacuees and information related to their states. Patients’ information should be accessible for authorized users to continue their treatment, accommodation and transference. Also it should include timely information of patients’ location as soon as they arrive somewhere and leave therein such a way that health care professionals can be able to provide patients’ proper medical treatment.

Keywords: patient tracking, challenges, disaster, emergency

Procedia PDF Downloads 304
643 A Comprehensive Study and Evaluation on Image Fashion Features Extraction

Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

Abstract:

Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

Procedia PDF Downloads 139
642 Optimization of Digestive Conditions of Opuntia ficus-indica var. Saboten using Food-Grade Enzymes

Authors: Byung Wook Yang, Sae Kyul Kim, Seung Il Ahn, Jae Hee Choi, Heejung Jung, Yejin Choi, Byung Yong Kim, Young Tae Hahm

Abstract:

Opuntia ficus-indica is a member of the Cactaceae family that is widely grown in all the semiarid countries throughout the world. Opuntia ficus-indica var. Saboten (OFS), commonly known as prickly pear cactus, is commercially cultivated as a dietary foodstuffs and medicinal stuffs in Jeju Island, Korea. Owing to high viscosity of OFS’ pad, its application to the commercial field has been limited. When the low viscosity of OFS’s pad is obtained, it is useful for the manufacture of healthy food in the related field. This study was performed to obtain the optimal digestion conditions of food-grade enzymes (Pectinex, Viscozyme and Celluclast) with the powder of OFS stem. And also, the contents of water-soluble dietary fiber (WSDF) of the dried powder prepared by the extraction of OFS stem were monitored and optimized using the response surface methodology (RSM), which included 20 experimental points with 3 replicates for two independent variables (fermentation temperature and time). A central composite design was used to monitor the effect of fermentation temperature (30-90 °C, X1) and fermentation time (1-10h, X2) on dependent variables, such as viscosity (Y1), water-soluble dietary fiber (Y2) and dietary fiber yield (Y3). Estimated maximum values at predicted optimum conditions were in agreement with experimental values. Optimum temperature and duration were 50°C and 12 hours, respectively. Viscosity value reached 3.4 poise. Yield of water-soluble dietary fiber is determined in progress.

Keywords: Opuntia ficus-indica var. saboten, enzymatic fermentation, response surface methodology, water-soluble dietary fiber, viscosity

Procedia PDF Downloads 346
641 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

Procedia PDF Downloads 348