Search results for: synthetic dataset
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2210

Search results for: synthetic dataset

1520 Cultural Effects on the Performance of Non- Profit and For-Profit Microfinance Institutions

Authors: Patrick M. Stanton, William R. McCumber

Abstract:

Using a large dataset of more than 2,400 individual microfinance institutions (MFIs) from 120 countries from 1999 to 2016, this study finds that nearly half of the international MFIs operate as for-profit institutions. Formal institutions (business regulatory environment, property rights, social protection, and a developed financial sector) impact the likelihood of MFIs being for-profit across countries. Cultural differences across countries (power distance, individualism, masculinity, and indulgence) seem to be a factor in the legal status of the MFI (non-profit or for-profit). MFIs in countries with stronger formal institutions, a greater degree of power distance, and a higher degree of collectivism experience better financial and social performance.

Keywords: Hofstede cultural dimensions, international finance, microfinance institutions, non-profite

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1519 Health Expenditure and its Place in Economy: The Case of Turkey

Authors: Ayşe Coban, Orhan Coban, Haldun Soydal, Sükrü Sürücü

Abstract:

While health is a source of prosperity for individuals, it is also one of the most important determinants of economic growth for a country. Health, by increasing the productivity of labor, contributes to economic growth. Therefore, countries should give the necessary emphasis to health services. The primary aim of this study is to analyze the changes occurring in health services in Turkey by examining the developments in the sector. In this scope, the second aim of the study is to reveal the place of health expenditures in the Turkish economy. As a result of the analysis in the dataset, in which the 1999-2013 periods is considered, it was determined that some increase in health expenditures took place and that the increase in the share of health expenditures in GDP was too small. Furthermore, analysis of the results points out that in financing health expenditures, the public sector is prominent compared to the private sector.

Keywords: health, health service, health expenditures, Turkey

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1518 Identification of Synthetic Hybrids of 4-Thiazolidinone-Bromopyrrole Alkaloid as HIV-1 RT Inhibitors

Authors: Rajesh A. Rane, Shital S. Naphade, Rajshekhar Karpoormath

Abstract:

Thiozolidin-4-one, a mimic of thiazolobenzimidazole (TBZ) has drawn many attentions due to its potent and selective inhibition against the HIV-1 and low toxicity by binding to the allosteric site of the reverse transcriptase (RT) as a non-nucleoside RT inhibitor (NNRTI). Similarly, marine bromopyrrole alkaloids are well known for their diverse array of anti-infective properties. Hence, we have reported synthesis and in vitro HIV-1 RT inhibitory activity of a series of 4-thiazolidinone-bromopyrrole alkaloid hybrids tethered with amide linker. The results of in vitro HIV-1 RT kit assay showed that some of the compounds, such as 4c, 4d, and 4i could effectively inhibit RT activity. Among them, compounds 4c having 4-chlorophenyl substituted 4-thiazolidione ring was the best one with the IC50 value of 0.26 µM. The sturdy emerges with key structure-activity relationship that pyrrole-NH-free core benefited inhibition against HIV-1 RT inhibition. This study identified conjugate 4c with potent activity and selectivity as promising compound for further drug development to HIV.

Keywords: antiviral drugs, bromopyrrole alkaloids, HIV-1 RT inhibition, 4-thiazolidinone

Procedia PDF Downloads 459
1517 New Insulation Material for Solar Thermal Collectors

Authors: Nabila Ihaddadene, Razika Ihaddadene, Abdelwahaab Betka

Abstract:

1973 energy crisis (rising oil prices) pushed the world to consider other alternative energy resources to existing conventional energies consisting predominantly of hydrocarbons. Renewable energies such as solar, the wind and geothermal have received renewed interest, especially to preserve nature ( the low-temperature rise of global environmental problems). Solar energy as an available, cheap and environmental friendly alternative source has various applications such as heating, cooling, drying, power generation, etc. In short, there is no life on earth without this enormous nuclear reactor, called the sun. Among available solar collector designs, flat plate collector (FPC) is low-temperature applications (heating water, space heating, etc.) due to its simple design and ease of manufacturing. Flat plate collectors are permanently fixed in position and do not track the sun (non-concentrating collectors). They operate by converting solar radiation into heat and transferring that heat to a working fluid (usually air, water, water plus antifreeze additive) flowing through them. An FPC generally consists of the main following components: glazing, absorber plate of high absorptivity, fluid tubes welded to or can be an integral part of the absorber plate, insulation and container or casing of the above-mentioned components. Insulation is of prime importance in thermal applications. There are three main families of insulation: mineral insulation; vegetal insulation and synthetic organic insulation. The old houses of the inhabitants of North Africa were built of brick made of composite material that is clay and straw. These homes are characterized by their thermal comfort; i.e. the air inside these houses is cool in summer and warm in winter. So, the material composed from clay and straw act as a thermal insulation. In this research document, the polystyrene used as insulation in the ET200 flat plate solar collector is replaced by the cheapest natural material which is clay and straw. Trials were carried out on a solar energy demonstration system (ET 200). This system contains a solar collector, water storage tank, a high power lamp simulating solar energy and a control and command cabinet. In the experimental device, the polystyrene is placed under the absorber plate and in the edges of the casing containing the components of the solar collector. In this work, we have replaced the polystyrene of the edges by the composite material. The use of the clay and straw as insulation instead of the polystyrene increases temperature difference (T2-T1) between the inlet and the outlet of the absorber by 0.9°C; thus increases the useful power transmitted to water in the solar collector. Tank Water is well heated when using the clay and straw as insulation. However, it is less heated when using the polystyrene as insulation. Clay and straw material improves also the performance of the solar collector by 5.77%. Thus, it is recommended to use this cheapest non-polluting material instead of synthetic insulation to improve the performance of the solar collector.

Keywords: clay, insulation material, polystyrene, solar collector, straw

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1516 Artificial Intelligence Based Meme Generation Technology for Engaging Audience in Social Media

Authors: Andrew Kurochkin, Kostiantyn Bokhan

Abstract:

In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 138
1515 Automatic Threshold Search for Heat Map Based Feature Selection: A Cancer Dataset Analysis

Authors: Carlos Huertas, Reyes Juarez-Ramirez

Abstract:

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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1514 Zinc Adsorption Determination of H2SO4 Activated Pomegranate Peel

Authors: S. N. Turkmen Koc, A. S. Kipcak, M. B. Piskin, E. Moroydor Derun, N. Tugrul

Abstract:

Active carbon can be obtained from agricultural sources. Due to the high surface area, the production of activated carbon from cheap resources is very important. Since the surface area of 1 g activated carbon is approximately between 300 and 2000 m2, it can be used to remove both organic and inorganic impurities. In this study, the adsorption of Zn metal was studied with the product of activated carbon, which is obtained from pomegranate peel by microwave and chemical activation methods. The microwave process of pomegranate peel was carried out under constant microwave power of 800 W and 1 to 4 minutes. After the microwave process, samples were treated with H2SO4 for 3 h. Then prepared product was used in synthetic waste water including 40 ppm Zn metal. As a result, removal of waste Zn in waste water ranged from 91% to 93%.

Keywords: activated carbon, chemical activation, H₂SO₄, microwave, pomegranate peel

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1513 The Effect of Finding and Development Costs and Gas Price on Basins in the Barnett Shale

Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

Abstract:

Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

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1512 Review on Rainfall Prediction Using Machine Learning Technique

Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

Abstract:

Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

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1511 On the Effect of Immigration on Destination: Country Corruption

Authors: Eugen Dimant, Tim Krieger, Margarete Redlin

Abstract:

This paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD coun-tries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. What is more, we also address the issue of endogeneity by using the Difference-Generalized Method of Moments (GMM) estimator. Independent of the econometric methodology we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the economic implications associated with migration flows.

Keywords: corruption, migration, impact of migration, destination-country corruption

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1510 A Green Method for Selective Spectrophotometric Determination of Hafnium(IV) with Aqueous Extract of Ficus carica Tree Leaves

Authors: A. Boveiri Monji, H. Yousefnia, M. Haji Hosseini, S. Zolghadri

Abstract:

A clean spectrophotometric method for the determination of hafnium by using a green reagent, acidic extract of Ficus carica tree leaves is developed. In 6-M hydrochloric acid, hafnium reacts with this reagent to form a yellow product. The formed product shows maximum absorbance at 421 nm with a molar absorptivity value of 0.28 × 104 l mol⁻¹ cm⁻¹, and the method was linear in the 2-11 µg ml⁻¹ concentration range. The detection limit value was found to be 0.312 µg ml⁻¹. Except zirconium and iron, the selectivity was good, and most of the ions did not show any significant spectral interference at concentrations up to several hundred times. The proposed method was green, simple, low cost, and selective.

Keywords: spectrophotometric determination, Ficus caricatree leaves, synthetic reagents, hafnium

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1509 One Plus One is More than Two: Why Nurse Recruiters Need to Use Various Multivariate Techniques to Understand the Limitations of the Concept of Emotional Intelligence

Authors: Austyn Snowden

Abstract:

Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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1508 Emotion-Convolutional Neural Network for Perceiving Stress from Audio Signals: A Brain Chemistry Approach

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

Abstract:

Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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1507 Investigation of the Catalytic Role of Surfactants on Carbon Dioxide Hydrate Formation in Sediments

Authors: Ehsan Heidaryan

Abstract:

Gas hydrate sediments are ice like permafrost in deep see and oceans. Methane production in sequestration process and reducing atmospheric carbon dioxide, a main source of greenhouse gas, has been accentuated recently. One focus is capture, separation, and sequestration of industrial carbon dioxide. As a hydrate former, carbon dioxide forms hydrates at moderate temperatures and pressures. This phenomenon could be utilized to capture and separate carbon dioxide from flue gases, and also has the potential to sequester carbon dioxide in the deep seabeds. This research investigated the effect of synthetic surfactants on carbon dioxide hydrate formation, catalysis and consequently, methane production from hydrate permafrosts in sediments. It investigated the sequestration potential of carbon dioxide hydrates in ocean sediments. Also, the catalytic effect of biosurfactants in these processes was investigated.

Keywords: carbon dioxide, hydrate, sequestration, surfactant

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1506 High Speed Rail vs. Other Factors Affecting the Tourism Market in Italy

Authors: F. Pagliara, F. Mauriello

Abstract:

The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: tourists, overnights, high speed rail, attractions, security

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1505 Force Feedback Enabled Syringe for Aspiration and Biopsy

Authors: Pelin Su Firat, Sohyung Cho

Abstract:

Biopsy or aspiration procedures are known to be complicated as they involve the penetration of a needle through human tissues, including vital organs. This research presents the design of a force sensor-guided device to be used with syringes and needles for aspiration and biopsy. The development of the device was aimed to help accomplish accurate needle placement and increase the performance of the surgeon in navigating the tool and tracking the target. Specifically, a prototype for a force-sensor embedded syringe has been created using 3D (3-Dimensional) modeling and printing techniques in which two different force sensors were used to provide significant force feedback to users during the operations when needles pernitrate different tissues. From the extensive tests using synthetic tissues, it is shown that the proposed syringe design has accomplished the desired accuracy, efficiency, repeatability, and effectiveness. Further development is desirable through usability tests.

Keywords: biopsy, syringe, force sensors, haptic feedback

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1504 The Next Game Changer: 3-D Printed Musical Instruments

Authors: Leonardo Ko

Abstract:

In an era marked by rapid technological innovation, the classical instrument industry nonetheless has not seen significant change. Is this a matter of stubborn traditionalism, or do old, conventional instruments really sound better? Because of the widespread use of 3-D printing, it seems feasible to produce modern, 3-D printed instruments that adhere to the basic conventions of standard construction. This study aimed to design and create a practical, effective 3-D printed acoustic violin. A cost-benefit analysis of materials and design is presented in addition to a report on sound tests in which a pool of professional musicians compared the traditional violin to its synthetic counterpart with regard to acoustic properties. With a low-cost yet functional instrument, musicians of all levels would be able to afford instruments with much greater ease; the present study thus hopes to contribute to efforts to increase the accessibility of classical music education.

Keywords: acoustic musical instrument, classical musical education, low-cost, 3-D printing

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1503 Influence of Synthetic Antioxidant in the Iodine Value and Acid Number of Jatropha Curcas Biodiesel

Authors: Supriyono, Sumardiyono

Abstract:

Biodiesel is one of the alternative fuels that promising for substituting petrodiesel as energy source which is have advantage on sustainability and eco-friendly. Due to the raw material that tend to decompose during storage, biodiesel also have the same characteristic that tend to decompose and formed higher acid value which is the result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could prevent by introduce a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. The quality degradation on biodiesel could evaluated by measuring iodine value and acid number of biodiesel. Biodiesel made from High Fatty Acid Jatropha curcas oil equality by using esterification and esterification process will stand on the quality by introduce 90 ppm pyrogallol powder on the biodiesel, which could extend the quality from 2 hours to more than 6 hours in rancimat test evaluation.

Keywords: biodiesel, antioxidant, iodine number, acid value

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1502 Performance of an Anaerobic Baffled Reactor (ABR) during Start-Up Period

Authors: D. M. Bassuney, W. A. Ibrahim, Medhat A. E. Moustafa

Abstract:

Appropriate start-up of an anaerobic baffled reactor (ABR) is considered to be the most delicate and important issue in the anaerobic process, and depends on several factors such as wastewater composition, reactor configuration, inoculum and operating conditions. In this work, the start-up performance of an ABR with working volume of 30 liters, fed continuously with synthetic food industrial wastewater along with semi-batch study to measure the methangenic activity by specific methanogenic activity (SMA) test were carried out at various organic loading rates (OLRs) to determine the best OLR used to start up the reactor. The comparison was based on COD removal efficiencies, start-up time, pH stability and methane production. An OLR of 1.8 Kg COD/m3d (5400 gCOD/m3 and 3 days HRT) showed best overall performance with COD removal efficiency of 94.44% after four days from the feeding and methane production of 3802 ml/L with an overall SMA of 0.36 gCH4-COD/gVS.d

Keywords: anaerobic baffled reactor, anaerobic reactor start-up, food industrial wastewater, specific methanogenic activity

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1501 Treatment of Onshore Petroleum Drill Cuttings via Soil Washing Process: Characterization and Optimal Conditions

Authors: T. Poyai, P. Painmanakul, N. Chawaloesphonsiya, P. Dhanasin, C. Getwech, P. Wattana

Abstract:

Drilling is a key activity in oil and gas exploration and production. Drilling always requires the use of drilling mud for lubricating the drill bit and controlling the subsurface pressure. As drilling proceeds, a considerable amount of cuttings or rock fragments is generated. In general, water or Water Based Mud (WBM) serves as drilling fluid for the top hole section. The cuttings generated from this section is non-hazardous and normally applied as fill materials. On the other hand, drilling the bottom hole to reservoir section uses Synthetic Based Mud (SBM) of which synthetic oils are composed. The bottom-hole cuttings, SBM cuttings, is regarded as a hazardous waste, in accordance with the government regulations, due to the presence of hydrocarbons. Currently, the SBM cuttings are disposed of as an alternative fuel and raw material in cement kiln. Instead of burning, this work aims to propose an alternative for drill cuttings management under two ultimate goals: (1) reduction of hazardous waste volume; and (2) making use of the cleaned cuttings. Soil washing was selected as the major treatment process. The physiochemical properties of drill cuttings were analyzed, such as size fraction, pH, moisture content, and hydrocarbons. The particle size of cuttings was analyzed via light scattering method. Oil present in cuttings was quantified in terms of total petroleum hydrocarbon (TPH) through gas chromatography equipped with flame ionization detector (GC-FID). Other components were measured by the standard methods for soil analysis. Effects of different washing agents, liquid-to-solid (L/S) ratio, washing time, mixing speed, rinse-to-solid (R/S) ratio, and rinsing time were also evaluated. It was found that drill cuttings held the electrical conductivity of 3.84 dS/m, pH of 9.1, and moisture content of 7.5%. The TPH in cuttings existed in the diesel range with the concentration ranging from 20,000 to 30,000 mg/kg dry cuttings. A majority of cuttings particles held a mean diameter of 50 µm, which represented silt fraction. The results also suggested that a green solvent was considered most promising for cuttings treatment regarding occupational health, safety, and environmental benefits. The optimal washing conditions were obtained at L/S of 5, washing time of 15 min, mixing speed of 60 rpm, R/S of 10, and rinsing time of 1 min. After washing process, three fractions including clean cuttings, spent solvent, and wastewater were considered and provided with recommendations. The residual TPH less than 5,000 mg/kg was detected in clean cuttings. The treated cuttings can be then used for various purposes. The spent solvent held the calorific value of higher than 3,000 cal/g, which can be used as an alternative fuel. Otherwise, the recovery of the used solvent can be conducted using distillation or chromatography techniques. Finally, the generated wastewater can be combined with the produced water and simultaneously managed by re-injection into the reservoir.

Keywords: drill cuttings, green solvent, soil washing, total petroleum hydrocarbon (TPH)

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1500 Software Defect Analysis- Eclipse Dataset

Authors: Amrane Meriem, Oukid Salyha

Abstract:

The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

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1499 ISAR Imaging and Tracking Algorithm for Maneuvering Non-ellipsoidal Extended Objects Using Jump Markov Systems

Authors: Mohamed Barbary, Mohamed H. Abd El-azeem

Abstract:

Maneuvering non-ellipsoidal extended object tracking (M-NEOT) using high-resolution inverse synthetic aperture radar (ISAR) observations is gaining momentum recently. This work presents a new robust implementation of the Jump Markov (JM) multi-Bernoulli (MB) filter for M-NEOT, where the M-NEOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on an MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, JM-MB-TBD filter

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1498 Slice Bispectrogram Analysis-Based Classification of Environmental Sounds Using Convolutional Neural Network

Authors: Katsumi Hirata

Abstract:

Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

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1497 The Toxicity Effects of HICIDE VD-9 on the Mortality of Lucilia cuprina under Laboratory Conditions

Authors: Mehdi Shahmoradi Moghadam, Saba Kavian, Mehdi Zabihzadeh, Amir Mohammad Alborzi, Reza Sadeghi

Abstract:

Cypermethrin is one of the most widely used synthetic insecticides to control pests in veterinary, industrial and agricultural environments. In the present study, the mortalities of Lucilia Cuprina as the key pest of meat were studied after being exposed to HICIDE VD-9 (a ready-to-use disinfectant/insecticide containing cypermethrin, polyhexanide and quaternary ammonium compounds produced by Dana pharmed lotus Co., Iran) within 15 minutes. The experimental results showed that moralities percentage of egg, larvae and adults of Lucilia Cuprina were 48%, 81% and 70%, respectively. Based on the obtained results, it can be predicted that in addition to controlling the insect pests of blow flies, HICIDE VD-9, as a cost-effective and environmentally friendly disinfectant/insecticide, can be effective against other insects, e.g., biting flies, fleas, midges, mosquitoes and ticks.

Keywords: cypermethrin, HICIDE VD-9, Lucilia cuprina, mortality, toxicity

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1496 Wikipedia World: A Computerized Process for Cultural Heritage Data Dissemination

Authors: L. Rajaonarivo, M. N. Bessagnet, C. Sallaberry, A. Le Parc Lacayrelle, L. Leveque

Abstract:

TCVPYR is a European FEDER (European Regional Development Fund) project which aims to promote tourism in the French Pyrenees region by leveraging its cultural heritage. It involves scientists from various domains (geographers, historians, anthropologists, computer scientists...). This paper presents a fully automated process to publish any dataset as Wikipedia articles as well as the corresponding linked information on Wikidata and Wikimedia Commons. We validate this process on a sample of geo-referenced cultural heritage data collected by TCVPYR researchers in different regions of the Pyrenees. The main result concerns the technological prerequisites, which are now in place. Moreover, we demonstrated that we can automatically publish cultural heritage data on Wikimedia.

Keywords: cultural heritage dissemination, digital humanities, open data, Wikimedia automated publishing

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1495 Analyzing Large Scale Recurrent Event Data with a Divide-And-Conquer Approach

Authors: Jerry Q. Cheng

Abstract:

Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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1494 Texture-Based Image Forensics from Video Frame

Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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1493 ENDO-β-1,4-Xylanase from Thermophilic Geobacillus stearothermophilus: Immobilization Using Matrix Entrapment Technique to Increase the Stability and Recycling Efficiency

Authors: Afsheen Aman, Zainab Bibi, Shah Ali Ul Qader

Abstract:

Introduction: Xylan is a heteropolysaccharide composed of xylose monomers linked together through 1,4 linkages within a complex xylan network. Owing to wide applications of xylan hydrolytic products (xylose, xylobiose and xylooligosaccharide) the researchers are focusing towards the development of various strategies for efficient xylan degradation. One of the most important strategies focused is the use of heat tolerant biocatalysts which acts as strong and specific cleaving agents. Therefore, the exploration of microbial pool from extremely diversified ecosystem is considerably vital. Microbial populations from extreme habitats are keenly explored for the isolation of thermophilic entities. These thermozymes usually demonstrate fast hydrolytic rate, can produce high yields of product and are less prone to microbial contamination. Another possibility of degrading xylan continuously is the use of immobilization technique. The current work is an effort to merge both the positive aspects of thermozyme and immobilization technique. Methodology: Geobacillus stearothermophilus was isolated from soil sample collected near the blast furnace site. This thermophile is capable of producing thermostable endo-β-1,4-xylanase which cleaves xylan effectively. In the current study, this thermozyme was immobilized within a synthetic and a non-synthetic matrice for continuous production of metabolites using entrapment technique. The kinetic parameters of the free and immobilized enzyme were studied. For this purpose calcium alginate and polyacrylamide beads were prepared. Results: For the synthesis of immobilized beads, sodium alginate (40.0 gL-1) and calcium chloride (0.4 M) was used amalgamated. The temperature (50°C) and pH (7.0) optima of immobilized enzyme remained same for xylan hydrolysis however, the enzyme-substrate catalytic reaction time raised from 5.0 to 30.0 minutes as compared to free counterpart. Diffusion limit of high molecular weight xylan (corncob) caused a decline in Vmax of immobilized enzyme from 4773 to 203.7 U min-1 whereas, Km value increased from 0.5074 to 0.5722 mg ml-1 with reference to free enzyme. Immobilized endo-β-1,4-xylanase showed its stability at high temperatures as compared to free enzyme. It retained 18% and 9% residual activity at 70°C and 80°C, respectively whereas; free enzyme completely lost its activity at both temperatures. The Immobilized thermozyme displayed sufficient recycling efficiency and can be reused up to five reaction cycles, indicating that this enzyme can be a plausible candidate in paper processing industry. Conclusion: This thermozyme showed better immobilization yield and operational stability with the purpose of hydrolyzing the high molecular weight xylan. However, the enzyme immobilization properties can be improved further by immobilizing it on different supports for industrial purpose.

Keywords: immobilization, reusability, thermozymes, xylanase

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1492 Mask-Prompt-Rerank: An Unsupervised Method for Text Sentiment Transfer

Authors: Yufen Qin

Abstract:

Text sentiment transfer is an important branch of text style transfer. The goal is to generate text with another sentiment attribute based on a text with a specific sentiment attribute while maintaining the content and semantic information unrelated to sentiment unchanged in the process. There are currently two main challenges in this field: no parallel corpus and text attribute entanglement. In response to the above problems, this paper proposed a novel solution: Mask-Prompt-Rerank. Use the method of masking the sentiment words and then using prompt regeneration to transfer the sentence sentiment. Experiments on two sentiment benchmark datasets and one formality transfer benchmark dataset show that this approach makes the performance of small pre-trained language models comparable to that of the most advanced large models, while consuming two orders of magnitude less computing and memory.

Keywords: language model, natural language processing, prompt, text sentiment transfer

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1491 Crude Palm Oil Antioxidant Extraction and the Antioxidation Activity

Authors: Supriyono Supriyono, Sumardiyono Sumardiyono, Peni Pujiastuti, Dian Indriana Hapsari

Abstract:

Crude palm oil (CPO) is a vegetable oil that came from a palm tree bunch. The productivity of the oil is 12 ton/hectare/year. Thus palm oil tree was known as highest vegetable oil yield. It was grown across Equatorial County, especially in Malaysia and Indonesia. The greenish-red color on CPO was come from carotenoid. Carotenoid is one of the antioxidants that could be extracted. Carotenoid could be used as functional food and other purposes. Another antioxidant that also found in CPO is tocopherol. The aim of the research work is to find antioxidant activity on CPO comparing to the synthetic antioxidant that available in a market. In this research work, antioxidant was extracted by a mixture of acetone and n.hexane, while the activity of the antioxidant extract was determined by DPPH method. Antioxidant activity of the extracted compound about 46% compared to pure tocopherol. While the solvent mixture compose by 90% acetone and 10% n. hexane meet the best on the antioxidant activity.

Keywords: antioxidant, beta carotene, crude palm oil, DPPH, tocopherol

Procedia PDF Downloads 213