Search results for: table extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2470

Search results for: table extraction

1720 An Investigation of the Use of Visible Spectrophotometric Analysis of Lead in an Herbal Tea Supplement

Authors: Salve Alessandria Alcantara, John Armand E. Aquino, Ma. Veronica Aranda, Nikki Francine Balde, Angeli Therese F. Cruz, Elise Danielle Garcia, Antonie Kyna Lim, Divina Gracia Lucero, Nikolai Thadeus Mappatao, Maylan N. Ocat, Jamille Dyanne L. Pajarillo, Jane Mierial A. Pesigan, Grace Kristin Viva, Jasmine Arielle C. Yap, Kathleen Michelle T. Yu, Joanna J. Orejola, Joanna V. Toralba

Abstract:

Lead is a neurotoxic metallic element that is slowly accumulated in bones and tissues especially if present in products taken in a regular basis such as herbal tea supplements. Although sensitive analytical instruments are already available, the USP limit test for lead is still widely used. However, because of its serious shortcomings, Lang Lang and his colleagues developed a spectrophotometric method for determination of lead in all types of samples. This method was the one adapted in this study. The actual procedure performed was divided into three parts: digestion, extraction and analysis. For digestion, HNO3 and CH3COOH were used. Afterwards, masking agents, 0.003% and 0.001% dithizone in CHCl3 were added and used for the extraction. For the analysis, standard addition method and colorimetry were performed. This was done in triplicates under two conditions. The 1st condition, using 25µg/mL of standard, resulted to very low absorbances with an r2 of 0.551. This led to the use of a higher concentration, 1mg/mL, for condition 2. Precipitation of lead cyanide was observed and the absorbance readings were relatively higher but between 0.15-0.25, resulting to a very low r2 of 0.429. LOQ and LOD were not computed due to the limitations of the Milton-Roy Spectrophotometer. The method performed has a shorter digestion time, and used less but more accessible reagents. However, the optimum ratio of dithizone-lead complex must be observed in order to obtain reliable results while exploring other concentration of standards.

Keywords: herbal tea supplement, lead-dithizone complex, standard addition, visible spectroscopy

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1719 Revised Bloom’s Taxonomy for Assessment in Engineering Education

Authors: K. Sindhu, V. Shubha Rao

Abstract:

The goal of every faculty is to guide students to learn fundamental concepts and also improve thinking skills. Curriculum questionnaires must be framed, which would facilitate students to improve their thinking skills. Improving thinking skill is a difficult task and one of the ways to achieve this is to frame questionnaires using Bloom’s Taxonomy. Bloom’s Taxonomy helps the faculty to assess the students in a systematic approach which involves students performing successfully at each level in a systematic manner. In this paper, we have discussed on Revised Bloom’s Taxonomy and how to frame our questions based on the taxonomy for assessment. We have also presented mapping the questions with the taxonomy table which shows the mapping of the questions in knowledge and cognitive domain.

Keywords: bloom’s taxonomy, assessment, questions, engineering education

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1718 Concentric Circle Detection based on Edge Pre-Classification and Extended RANSAC

Authors: Zhongjie Yu, Hancheng Yu

Abstract:

In this paper, we propose an effective method to detect concentric circles with imperfect edges. First, the gradient of edge pixel is coded and a 2-D lookup table is built to speed up normal generation. Then we take an accumulator to estimate the rough center and collect plausible edges of concentric circles through gradient and distance. Later, we take the contour-based method, which takes the contour and edge intersection, to pre-classify the edges. Finally, we use the extended RANSAC method to find all the candidate circles. The center of concentric circles is determined by the two circles with the highest concentricity. Experimental results demonstrate that the proposed method has both good performance and accuracy for the detection of concentric circles.

Keywords: concentric circle detection, gradient, contour, edge pre-classification, RANSAC

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1717 From Sampling to Sustainable Phosphate Recovery from Mine Waste Rock Piles

Authors: Hicham Amar, Mustapha El Ghorfi, Yassine Taha, Abdellatif Elghali, Rachid Hakkou, Mostafa Benzaazoua

Abstract:

Phosphate mine waste rock (PMWR) generated during ore extraction is continuously increasing, resulting in a significant environmental footprint. The main objectives of this study consist of i) elaboration of the sampling strategy of PMWR piles, ii) a mineralogical and chemical characterization of PMWR piles, and iii) 3D block model creation to evaluate the potential valorization of the existing PMWR. Destructive drilling using reverse circulation from 13 drills was used to collect samples for chemical (X-ray fluorescence analysis) and mineralogical assays. The 3D block model was created based on the data set, including chemical data of the realized drills using Datamine RM software. The optical microscopy observations showed that the sandy phosphate from drills in the PMWR piles is characterized by the abundance of carbonate fluorapatite with the presence of calcite, dolomite, and quartz. The mean grade of composite samples was around 19.5±2.7% for P₂O₅. The mean grade of P₂O₅ exhibited an increasing tendency by depth profile from bottom to top of PMWR piles. 3D block model generated with chemical data confirmed the tendency of the mean grades’ variation and may allow a potential selective extraction according to %P₂O₅. The 3D block model of P₂O₅ grade is an efficient sampling approach that confirmed the variation of P₂O₅ grade. This integrated approach for PMWR management will be a helpful tool for decision-making to recover the residual phosphate, adopting the circular economy and sustainability in the phosphate mining industry.

Keywords: 3D modelling, reverse circulation drilling, circular economy, phosphate mine waste rock, sampling

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1716 Cytotoxic Activity against MCF-7 Breast Cancer Cells and Antioxidant Property of Aqueous Tempe Extracts from Extended Fermentation

Authors: Zatil Athaillah, Anastasia Devi, Dian Muzdalifah, Wirasuwasti Nugrahani, Linar Udin

Abstract:

During tempe fermentation, some chemical changes occurred and they contributed to sensory, appearance, and health benefits of soybeans. Many studies on health properties of tempe have specialized on their isoflavones. In this study, other components of tempe, particularly water soluble chemicals, was investigated for their biofunctionality. The study was focused on the ability to suppress MCF-7 breast cancer cell growth and antioxidant activity, as expressed by DPPH radical scavenging activity, total phenols and total flavonoids, of the water extracts. Fermentation time of tempe was extended up to 120 hr to increase the possibility to find the functional components. Extraction yield and soluble nitrogen content were also quantified as accompanying data. Our findings suggested that yield of water extraction of tempe increased as fermentation was extended up to 120 hr, except for a slight decrease at 72 hr. Water extracts of tempe showed inhibition of MCF-7 breast cancer cell growth, as shown by lower IC50 values when compared to control (unfermented soybeans). Among the varied fermentation timescales, 60-hr period showed the highest activity (IC50 of 8.7 ± 4.95 µg/ml). The anticancer activity of extracts obtained from different fermentation time was positively correlated with total soluble nitrogens, but less relevant with antioxidant data. During 48-72 hr fermentation, at which cancer suppression activity was significant, the antioxidant properties from the three assays were not higher than control. These findings indicated that water extracts of tempe from extended fermentation could inhibit breast cancer cell growth but further study to determine the mechanism and compounds that play important role in the activity should be conducted.

Keywords: tempe, anticancer, antioxidant, phenolic compounds

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1715 Effects of Drying and Extraction Techniques on the Profile of Volatile Compounds in Banana Pseudostem

Authors: Pantea Salehizadeh, Martin P. Bucknall, Robert Driscoll, Jayashree Arcot, George Srzednicki

Abstract:

Banana is one of the most important crops produced in large quantities in tropical and sub-tropical countries. Of the total plant material grown, approximately 40% is considered waste and left in the field to decay. This practice allows fungal diseases such as Sigatoka Leaf Spot to develop, limiting plant growth and spreading spores in the air that can cause respiratory problems in the surrounding population. The pseudostem is considered a waste residue of production (60 to 80 tonnes/ha/year), although it is a good source of dietary fiber and volatile organic compounds (VOC’s). Strategies to process banana pseudostem into palatable, nutritious and marketable food materials could provide significant social and economic benefits. Extraction of VOC’s with desirable odor from dried and fresh pseudostem could improve the smell of products from the confectionary and bakery industries. Incorporation of banana pseudostem flour into bakery products could provide cost savings and improve nutritional value. The aim of this study was to determine the effects of drying methods and different banana species on the profile of volatile aroma compounds in dried banana pseudostem. The banana species analyzed were Musa acuminata and Musa balbisiana. Fresh banana pseudostem samples were processed by either freeze-drying (FD) or heat pump drying (HPD). The extraction of VOC’s was performed at ambient temperature using vacuum distillation and the resulting, mostly aqueous, distillates were analyzed using headspace solid phase microextraction (SPME) gas chromatography – mass spectrometry (GC-MS). Optimal SPME adsorption conditions were 50 °C for 60 min using a Supelco 65 μm PDMS/DVB Stableflex fiber1. Compounds were identified by comparison of their electron impact mass spectra with those from the Wiley 9 / NIST 2011 combined mass spectral library. The results showed that the two species have notably different VOC profiles. Both species contained VOC’s that have been established in literature to have pleasant appetizing aromas. These included l-Menthone, D-Limonene, trans-linlool oxide, 1-Nonanol, CIS 6 Nonen-1ol, 2,6 Nonadien-1-ol, Benzenemethanol, 4-methyl, 1-Butanol, 3-methyl, hexanal, 1-Propanol, 2-methyl- acid، 2-Methyl-2-butanol. Results show banana pseudostem VOC’s are better preserved by FD than by HPD. This study is still in progress and should lead to the optimization of processing techniques that would promote the utilization of banana pseudostem in the food industry.

Keywords: heat pump drying, freeze drying, SPME, vacuum distillation, VOC analysis

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1714 Control of an Outbreak of Vancomycin-Resistant Enterococci in a Tunisian Teaching Hospital

Authors: Hela Ghali, Sihem Ben Fredj, Mohamed Ben Rejeb, Sawssen Layouni, Salwa Khefacha, Lamine Dhidah, Houyem Said Laatiri

Abstract:

Background: Antimicrobial resistance is a growing threat to public health and motivates to improve prevention and control programs both at international (WHO) and national levels. Despite their low pathogenicity, vancomycin-resistant enterococci (VRE) are common nosocomial pathogens in several countries. The high potential for transmission of VRE between patients and the threat to send its resistance genes to other bacteria such as staphylococcus aureus already resistant to meticilin, justify strict control measures. Indeed, in Europe, the proportion of Enterococcus faecium responsible for invasive infections, varies from 1% to 35% in 2011 and less than 5% were resistant to vancomycin. In addition, it represents the second cause of urinary tract and wound infections and the third cause of nosocomial bacteremia in the United States. The nosocomial outbreaks of VRE have been mainly described in intensive care services, hematology-oncology and haemodialysis. An epidemic of VRE has affected our hospital and the objective of this work is to describe the measures put in place. Materials/Methods: Following the alert given by the service of plastic surgery concerning a patient carrier of VRE, a team of the prevention and healthcare security service (doctor + technician) made an investigation. A review of files was conducted to draw the synoptic table and the table of cases. Results: By contacting the microbiology laboratory, we have identified four other cases of VRE and who were hospitalized in Medical resuscitation department (2 cases, one of them was transferred to the Physical rehabilitation department), and Nephrology department (2 cases). The visit has allowed to detect several malfunctions in professional practice. A crisis cell has allowed to validate, coordinate and implement control measures following the recommendations of the Technical Center of nosocomial infections. In fact, the process was to technically isolate cases in their sector of hospitalization, to restrict the use of antibiotics, to strength measures of basic hygiene, and to make a screening by rectal swab for both cases and contacts (other patients and health staff). These measures have helped to control the situation and no other case has been reported for a month. 2 new cases have been detected in the intensive care unit after a month. However, these are short-term strategies, and other measures in the medium and long term should be taken into account in order to face similar outbreaks. Conclusion: The efforts to control the outbreak were not efficient since 2 new cases have been reported after a month. Therefore, a continuous monitoring in order to detect new cases earlier is crucial to minimize the dissemination of VRE.

Keywords: hospitals, nosocomial infection, outbreak, vancomycin-resistant enterococci

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1713 Metropolitan Governance in Statutory Plan Making Process

Authors: Vibhore Bakshi

Abstract:

This research paper is a step towards understanding the role of governance in the plan preparation process. It addresses the complexities of the peri-urban, historical constructions, politics and policies of sustainability, and legislative frameworks. The paper reflects on the Delhi NCT as one of the classical cases that have happened to witness different structural changes in the master plan around 1981, 2001, 2021, and Proposed Draft 2041. The Delhi Landsat imageries for 1989 and 2018 show an increase in the built-up areas around the periphery of NCT. The peri-urbanization has been a result of increasing in-migration to peri–urban areas of Delhi. The built-up extraction for years 1981, 1991, 2001, 2011, and 2018 highlights the growing peri-urbanization on scarce land therefore, it becomes equally important to research the history of the land and its legislative measures. It is interesting to understand the streaks of changes that have occurred in the land of Delhi in accordance with the different master plans and land legislative policies. The process of masterplan process in Delhi has experienced a lot of complexities in juxtaposition to other metropolitan regions of the world. The paper identifies the shortcomings in the current master planning process approach in regard to the stage of the planning process, traditional planning approach, and lagging ICT-based interventions. The metropolitan governance systems across the globe and India depict diversity in the organizational setup and varied dissemination of functions. It addresses the complexity of the peri-urban, historical constructions, politics and policies of sustainability, and legislative frameworks.

Keywords: governance, land provisions, built-up areas, in migration, built up extraction, master planning process, legislative policies, metropolitan governance systems

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1712 Extraction of Dye from Coconut Husk and Its Application on Wool and Silk

Authors: Deepali Rastogi

Abstract:

Natural dyes are considered to be eco-friendly as they cause no pollution and are safe to use. With the growing interest in natural dyes, new sources of natural dyes are being explored. Coconut (Cocos nucifera) is native to tropical eastern region. It is abundantly available in Asia, Africa and South America. While coconut has tremendous commercial value in food, oil, pharmaceutical and cosmetic industry, the most important use of coconut husk has been as coir which is used for making mats, ropes, etc. In the present study an attempt has been made to extract dye from the coconut husk and study its application on wool and silk. Dye was extracted from coconut husk in an aqueous medium at three different pH. The coconut husk fibres were boiled in water at different pH of 4, 7 and 9 for one hour. On visual inspection of the extracted dye solution, maximum colour was found to be extracted at pH 9. The solution was obtained in neutral medium whereas, no dye was extracted in acidic medium. Therefore, alkaline medium at pH 9 was selected for the extraction of dye from coconut husk. The extracted dye was applied on wool and silk at three different pH, viz., 4, 7 and 9. The effect of pre- and post- mordanting with alum and ferrous sulphate on the colour value of coconut husk dye was also studied. The L*a*b*/L*c*h* values were measured to see the effect of the mordants on the colour values of all the dyed and mordanted samples. Bright golden brown to dark brown colours were obtained at pH 4 on both wool and silk. The colour yield was not very good at pH 7 and 9. Mordanting with alum resulted in darker and brighter shades of brown, whereas mordanting with ferrous sulphate resulted in darker and duller shades. All the samples were tested for colourfastness to light, rubbing, washing and perspiration. Both wool and silk dyed with dye extracted from coconut husk exhibited good to excellent wash, rub and perspiration fastness. Fastness to light was moderate to good.

Keywords: coconut husk, wool, silk, natural dye, mordants

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1711 Experimental Investigation of Physical Properties of Bambusa Oldhamii and Yushania Alpina on the Influence of Age and Harvesting Season

Authors: Tigist Girma Kedane

Abstract:

The purpose of the current research work is to measure the physical properties of bamboo species in Ethiopia on the impact of age, harvesting seasons and culm height. Three representatives of bamboo plants are harvested in three groups of ages, 2 harvesting months, and 3 regions of Ethiopia. Research has not been done on the physical properties of bamboo species in Ethiopia so far. Moisture content and shrinkage of bamboo culm increase when the culm ages younger and moves from top to bottom position. The harvesting month of November has a higher moisture content and shrinkage compared to February. One year old of Injibara, Kombolcha, and Mekaneselam bamboo culm has 40%, 30%, and 33% higher moisture content, 29%, 24%, and 28% higher radial shrinkage, 32%, 37%, and 32% higher tangential shrinkage compared to 3 years old respectively. The bottom position of Injibara, Kombolcha, and Mekaneselam in November have 45%, 28%, and 25% higher moisture content, 41%, 29%, and 34% radial shrinkage, 29%, 28%, and 42% tangential shrinkage than the top position, respectively. The basic density increases as the age of the bamboo becomes older and moves from the bottom to the top position. November has the lowest basic density compared to February. 3 years old of Injibara, Kombolcha, and Mekaneselam at the age of 3 years have 32%, 50%, and 24% higher basic density compared to 1 year, whereas the top position has 35%, 26%, and 22% higher than the bottom position in February, respectively. The current research proposed that 3 years and February are suited for structural purposes and furniture making, but 1 year and November are suited for fiber extraction in the composite industry. The existence of water in the culm improves an easy extraction of the fibers without damage from the culm.

Keywords: bamboo age, bamboo height, harvesting seasons, physical properties

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1710 Residual Evaluation by Thresholding and Neuro-Fuzzy System: Application to Actuator

Authors: Y. Kourd, D. Lefebvre, N. Guersi

Abstract:

The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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1709 Developing an Automated Protocol for the Wristband Extraction Process Using Opentrons

Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

Abstract:

To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

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1708 Analysis of Real Time Seismic Signal Dataset Using Machine Learning

Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

Abstract:

Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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1707 Recent Advancement in Fetal Electrocardiogram Extraction

Authors: Savita, Anurag Sharma, Harsukhpreet Singh

Abstract:

Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

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1706 Beneficiation of Low Grade Chromite Ore and Its Characterization for the Formation of Magnesia-Chromite Refractory by Economically Viable Process

Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

Abstract:

Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr2O3), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr2O3, FeO, Al2O3 and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr2O3) was reduced at 1200 0C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 0C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: apparent porosity, beneficiation, low-grade chromite, refractory, spinel compounds, slag resistance

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1705 Renewable Energy Interfaced Shunt Active Filter Using a Virtual Flux Direct Power Control

Authors: M. R. Bengourina, M. Rahli, L. Hassaine, S. Saadi

Abstract:

In this study, we present a control method entitled virtual flux direct power control of a grid connected photovoltaic system associated with an active power filter. The virtual flux direct control of power (VF-DPC) is employed for the calculation of reference current generation. In this technique, the switches states of inverter are selected from a table of switching based on the immediate errors between the active and reactive powers and their reference values. The objectives of this paper are the reduction of Total Harmonic Distortion (THD) of source current, compensating reactive power and injecting the maximum active power available from the PV array into the load and/or grid. MATLAB/SIMULINK simulations are provided to demonstrate the performance of the proposed approach.

Keywords: shunt active power filter, VF-DPC, photovoltaic, MPPT

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1704 An Analysis of Eco-efficiency and GHG Emission of Olive Oil Production in Northeast of Portugal

Authors: M. Feliciano, F. Maia, A. Gonçalves

Abstract:

Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO2e/kgolive) than in F1 (148g CO2e/kgolive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO2e/Lolive oil) than in 2P (92g CO2e/Lolive oil); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO2e/Lolive oil. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil

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1703 Medi-Conf: Conference Management System

Authors: Dishant Kothari, Pankaj Gaur, Priyanshu Sharma, Ratnesh Litoriya, Sachin Solanki, Shimpy Goyal

Abstract:

Web based Conference Management System comprises of all the processes needed for round table conference, research paper publication includes the phases-call for paper, paper submission, paper review, acknowledgement to the author, paper acceptance and payment for publication. It will also help colleges and universities to conduct conferences for research, thus spreading awareness and will contribute to the overall development of students. Web based Conference Management System will streamline the procedure for paper publication by reducing the time and efforts needed in physical (offline mode) submission. A conference can be organized from anywhere and anytime. Authors can easily trace the status of the paper, and the program committee can review them anywhere and provide necessary comments to it.

Keywords: peer review, paper publication, author, chair, reviewer, virtualization, new normal

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1702 Improved Impossible Differential Cryptanalysis of Midori64

Authors: Zhan Chen, Wenquan Bi, Xiaoyun Wang

Abstract:

The Midori family of light weight block cipher is proposed in ASIACRYPT2015. It has attracted the attention of numerous cryptanalysts. There are two versions of Midori: Midori64 which takes a 64-bit block size and Midori128 the size of which is 128-bit. In this paper an improved 10-round impossible differential attack on Midori64 is proposed. Pre-whitening keys are considered in this attack. A better impossible differential path is used to reduce time complexity by decreasing the number of key bits guessed. A hash table is built in the pre-computation phase to reduce computational complexity. Partial abort technique is used in the key seiving phase. The attack requires 259 chosen plaintexts, 214.58 blocks of memory and 268.83 10-round Midori64 encryptions.

Keywords: cryptanalysis, impossible differential, light weight block cipher, Midori

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1701 Power Quality Modeling Using Recognition Learning Methods for Waveform Disturbances

Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

Abstract:

This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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1700 Data Mining Spatial: Unsupervised Classification of Geographic Data

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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1699 Solid Phase Micro-Extraction/Gas Chromatography-Mass Spectrometry Study of Volatile Compounds from Strawberry Tree and Autumn Heather Honeys

Authors: Marinos Xagoraris, Elisavet Lazarou, Eleftherios Alissandrakis, Christos S. Pappas, Petros A. Tarantilis

Abstract:

Strawberry tree (Arbutus unedo L.) and autumn heather (Erica manipuliflora Salisb.) are important beekeeping plants of Greece. Six monofloral honeys (four strawberry tree, two autumn heather) were analyzed by means of Solid Phase Micro-Extraction (SPME, 60 min, 60 oC) followed by Gas Chromatography coupled to Mass Spectrometry (GC-MS) for the purpose of assessing the botanical origin. A Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was employed, and benzophenone was used as internal standard. The volatile compounds with higher concentration (μg/ g of honey expressed as benzophenone) from strawberry tree honey samples, were α-isophorone (2.50-8.12); 3,4,5-trimethyl-phenol (0.20-4.62); 2-hydroxy-isophorone (0.06-0.53); 4-oxoisophorone (0.38-0.46); and β-isophorone (0.02-0.43). Regarding heather honey samples, the most abundant compounds were 1-methoxy-4-propyl-benzene (1.22-1.40); p-anisaldehyde (0.97-1.28); p-anisic acid (0.35-0.58); 2-furaldehyde (0.52-0.57); and benzaldehyde (0.41-0.56). Norisoprenoids are potent floral markers for strawberry-tree honey. β-isophorone is found exclusively in the volatile fraction of this type of honey, while also α-isophorone, 4-oxoisophorone and 2-hydroxy-isophorone could be considered as additional marker compounds. The analysis of autumn heather honey revealed that phenolic compounds are the most abundant and p-anisaldehyde; 1-methoxy-4-propyl-benzene; and p-anisic acid could serve as potent marker compounds. In conclusion, marker compounds for the determination of the botanical origin for these honeys could be identified as several norisoprenoids and phenolic components were found exclusively or in higher concentrations compared to common Greek honey varieties.

Keywords: SPME/GC-MS, volatile compounds, heather honey, strawberry tree honey

Procedia PDF Downloads 186
1698 Lecture Video Indexing and Retrieval Using Topic Keywords

Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

Abstract:

In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

Procedia PDF Downloads 244
1697 A Q-Methodology Approach for the Evaluation of Land Administration Mergers

Authors: Tsitsi Nyukurayi Muparari, Walter Timo De Vries, Jaap Zevenbergen

Abstract:

The nature of Land administration accommodates diversity in terms of both spatial data handling activities and the expertise involved, which supposedly aims to satisfy the unpredictable demands of land data and the diverse demands of the customers arising from the land. However, it is known that strategic decisions of restructuring are in most cases repelled in favour of complex structures that strive to accommodate professional diversity and diverse roles in the field of Land administration. Yet despite of this widely accepted knowledge, there is scanty theoretical knowledge concerning the psychological methodologies that can extract the deeper perceptions from the diverse spatial expertise in order to explain the invisible control arm of the polarised reception of the ideas of change. This paper evaluates Q methodology in the context of a cadastre and land registry merger (under one agency) using the Swedish cadastral system as a case study. Precisely, the aim of this paper is to evaluate the effectiveness of Q methodology towards modelling the diverse psychological perceptions of spatial professionals who are in a widely contested decision of merging the cadastre and land registry components of Land administration using the Swedish cadastral system as a case study. An empirical approach that is prescribed by Q methodology starts with the concourse development, followed by the design of statements and q sort instrument, selection of the participants, the q-sorting exercise, factor extraction by PQMethod and finally narrative development by logic of abduction. The paper uses 36 statements developed from a dominant competing value theory that stands out on its reliability and validity, purposively selects 19 participants to do the Qsorting exercise, proceeds with factor extraction from the diversity using varimax rotation and judgemental rotation provided by PQMethod and effect the narrative construction using the logic abduction. The findings from the diverse perceptions from cadastral professionals in the merger decision of land registry and cadastre components in Sweden’s mapping agency (Lantmäteriet) shows that focus is rather inclined on the perfection of the relationship between the legal expertise and technical spatial expertise. There is much emphasis on tradition, loyalty and communication attributes which concern the organisation’s internal environment rather than innovation and market attributes that reveals customer behavior and needs arising from the changing humankind-land needs. It can be concluded that Q methodology offers effective tools that pursues a psychological approach for the evaluation and gradations of the decisions of strategic change through extracting the local perceptions of spatial expertise.

Keywords: cadastre, factor extraction, land administration merger, land registry, q-methodology, rotation

Procedia PDF Downloads 180
1696 Assessing Acute Toxicity and Endocrine Disruption Potential of Selected Packages Internal Layers Extracts

Authors: N. Szczepanska, B. Kudlak, G. Yotova, S. Tsakovski, J. Namiesnik

Abstract:

In the scientific literature related to the widely understood issue of packaging materials designed to have contact with food (food contact materials), there is much information on raw materials used for their production, as well as their physiochemical properties, types, and parameters. However, not much attention is given to the issues concerning migration of toxic substances from packaging and its actual influence on the health of the final consumer, even though health protection and food safety are the priority tasks. The goal of this study was to estimate the impact of particular foodstuff packaging type, food production, and storage conditions on the degree of leaching of potentially toxic compounds and endocrine disruptors to foodstuffs using the acute toxicity test Microtox and XenoScreen YES YAS assay. The selected foodstuff packaging materials were metal cans used for fish storage and tetrapak. Five stimulants respectful to specific kinds of food were chosen in order to assess global migration: distilled water for aqueous foods with a pH above 4.5; acetic acid at 3% in distilled water for acidic aqueous food with pH below 4.5; ethanol at 5% for any food that may contain alcohol; dimethyl sulfoxide (DMSO) and artificial saliva were used in regard to the possibility of using it as an simulation medium. For each packaging three independent variables (temperature and contact time) factorial design simulant was performed. Xenobiotics migration from epoxy resins was studied at three different temperatures (25°C, 65°C, and 121°C) and extraction time of 12h, 48h and 2 weeks. Such experimental design leads to 9 experiments for each food simulant as conditions for each experiment are obtained by combination of temperature and contact time levels. Each experiment was run in triplicate for acute toxicity and in duplicate for estrogen disruption potential determination. Multi-factor analysis of variation (MANOVA) was used to evaluate the effects of the three main factors solvent, temperature (temperature regime for cup), contact time and their interactions on the respected dependent variable (acute toxicity or estrogen disruption potential). From all stimulants studied the most toxic were can and tetrapak lining acetic acid extracts that are indication for significant migration of toxic compounds. This migration increased with increase of contact time and temperature and justified the hypothesis that food products with low pH values cause significant damage internal resin filling. Can lining extracts of all simulation medias excluding distilled water and artificial saliva proved to contain androgen agonists even at 25°C and extraction time of 12h. For tetrapak extracts significant endocrine potential for acetic acid, DMSO and saliva were detected.

Keywords: food packaging, extraction, migration, toxicity, biotest

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1695 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

Procedia PDF Downloads 144
1694 Web Data Scraping Technology Using Term Frequency Inverse Document Frequency to Enhance the Big Data Quality on Sentiment Analysis

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

Procedia PDF Downloads 80
1693 Multi-source Question Answering Framework Using Transformers for Attribute Extraction

Authors: Prashanth Pillai, Purnaprajna Mangsuli

Abstract:

Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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1692 Efficient Video Compression Technique Using Convolutional Neural Networks and Generative Adversarial Network

Authors: P. Karthick, K. Mahesh

Abstract:

Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 178
1691 DAG Design and Tradeoff for Full Live Virtual Machine Migration over XIA Network

Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

Abstract:

Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

Procedia PDF Downloads 846