Search results for: world café method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25204

Search results for: world café method

21004 Lead Free BNT-BKT-BMgT-CoFe₂O₄ Magnetoelectric Nanoparticulate Composite Thin Films Prepared by Chemical Solution Deposition Method

Authors: A. K. Paul, Vinod Kumar

Abstract:

Lead free magnetoelectric (ME) nanoparticulate (1−x) BNT-BKT-BMgT−x CFO (x = 0, 0.1, 0.2, 0.3) composite films were synthesized using chemical solution deposition method. The X-ray diffraction and transmission electron microscope (TEM) reveal that CFO nanoparticles were well distributed in the matrix of BNT-BKT-BMgT. The nanocomposite films exhibit both good magnetic and ferroelectric properties at room temperature (R-T). It is concluded that the modulation in compositions of piezomagnetic/piezoelectric components plays a fundamental role in the magnetoelectric coupling in these nanoparticulate composite films. These ME composites provide a great opportunity as potential lead-free systems for ME devices.

Keywords: lead free multiferroic, nanocomposite, ferroelectric, ferromagnetic and magneto-electric properties

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21003 Improving Fake News Detection Using K-means and Support Vector Machine Approaches

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

Abstract:

Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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21002 Immigration in British Southern Cameroons from 2016 to 2020

Authors: Geraldine Ambe

Abstract:

Cameroon is a country in a country in Central Africa. Before the first World War, Germany colonized Cameroon, including some parts of Gabon, Chad, Nigeria, and the Central African Republic. After the war, the United Nations divided most of the colony into Britain and France. In 1960, Eastern Cameroon (‘La Republique du Cameroon’) gained its independence from France while British Southern Cameroons obtained its independence from Britain. The two entities agreed to live together as a federal state officially called the Federal Republic of Cameroon. In 1962, the name of the name of the country was changed from the Federal Republic of Cameroon to the United Republic of Cameroon, while the Prime Minister of Western Cameroon was moved to Yaounde. In 1984, President Paul Biya singlehandedly changed the name to the Republic of Cameroon, implying that Southern Cameroon is not recognized in the union again. From the words of Am Cohen, the two territories came together to form a federal government with one currency, one army, and one foreign policy like states in the United States of America. However, the name Republic of Cameroon (‘La Republique du Cameroun’) does not recognize BSC, and this is exactly what has been practiced: politics of exclusion and excessive centralization in Yaounde. In 2016, teachers and Lawyers started strikes to call the attention of the government on the inhalation of the English culture/people. They were greeted with guns, causing the radicalization of the youths. The civil society came together to form a union to address the issues facing the people, and the government took their leaders and sentenced them to live imprisonment. The consequence was a civil war with nobody to dialogue with. Out of Cameroon, more than half a million people from BSC have been taking dangerous trips through the air, land, and sea. In the jungles and the deserts, the snow of Europe, these people have been seen for the last 4 years. This paper will present some personalities, political fractions, and their stands of decentralization, federalism, and independence as the war continues. The paper will further look at the consequence of this crisis on migration in Central and Eastern Europe.

Keywords: British Southern Cameroons, decolonization, Second World War, dialogue, civil war, immigration

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21001 Midterm Clinical and Functional Outcomes After Treatment with Ponseti Method for Idiopathic Clubfeet: A Prospective Cohort Study

Authors: Neeraj Vij, Amber Brennan, Jenni Winters, Hadi Salehi, Hamy Temkit, Emily Andrisevic, Mohan V. Belthur

Abstract:

Idiopathic clubfoot is a common lower extremity deformity with an incidence of 1:500. The Ponseti Method is well known as the gold standard of treatment. However, there is limited functional data demonstrating correction of the clubfoot after treatment with the Ponseti method. The purpose of this study was to study the clinical and functional outcomes after the Ponseti method with the Clubfoot Disease-Specific Instrument (CDS) and pedobarography. This IRB-approved prospective study included patients aged 3-18 who were treated for idiopathic clubfoot with the Ponseti method between January 2008 and December 2018. Age-matched controls were identified through siblings of clubfoot patients and other community members. Treatment details were collected through a chart review of the included patients. Laboratory assessment included a physical exam, gait analysis, and pedobarography. The Pediatric Outcomes Data Collection Instrument and the Clubfoot Disease-Specific Instrument were also obtained on clubfoot patients (CF). The Wilcoxson rank-sum test was used to study differences between the CF patients and the typically developing (TD) patients. Statistical significance was set at p < 0.05. There were a total of 37 enrolled patients in our study. 21 were priorly treated for CF and 16 were TD. 94% of the CF patients had bilateral involvement. The age at the start of treatment was 29 days, the average total number of casts was seven to eight, and the average total number of casts after Achilles tenotomy was one. The reoccurrence rate was 25%, tenotomy was required in 94% of patients, and ≥1 tenotomy was required in 25% of patients. There were no significant differences between step length, step width, stride length, force-time integral, maximum peak pressure, foot progression angles, stance phase time, single-limb support time, double limb support time, and gait cycle time between children treated with the Ponseti method and typically developing children. The average post-treatment Pirani and Dimeglio scores were 5.50±0.58 and 15.29±1.58, respectively. The average post-treatment PODCI subscores were: Upper Extremity: 90.28, Transfers: 94.6, Sports: 86.81, Pain: 86.20, Happiness: 89.52, Global: 88.6. The average post-treatment Clubfoot Disease-Specific Instrument scores subscores were: Satisfaction: 73.93, Function: 80.32, Overall: 78.41. The Ponseti Method has a very high success rate and remains to be the gold standard in the treatment of idiopathic clubfoot. Timely management leads to good outcomes and a low need for repeated Achilles tenotomy. Children treated with the Ponseti method demonstrate good functional outcomes as measured through pedobarography. Pedobarography may have clinical utility in studying congenital foot deformities. Objective measures for hours of brace wear could represent an improvement in clubfoot care.

Keywords: functional outcomes, pediatric deformity, patient-reported outcomes, talipes equinovarus

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21000 American Sign Language Recognition System

Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

Abstract:

The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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20999 An Approximate Formula for Calculating the Fundamental Mode Period of Vibration of Practical Building

Authors: Abdul Hakim Chikho

Abstract:

Most international codes allow the use of an equivalent lateral load method for designing practical buildings to withstand earthquake actions. This method requires calculating an approximation to the fundamental mode period of vibrations of these buildings. Several empirical equations have been suggested to calculate approximations to the fundamental periods of different types of structures. Most of these equations are knowing to provide an only crude approximation to the required fundamental periods and repeating the calculation utilizing a more accurate formula is usually required. In this paper, a new formula to calculate a satisfactory approximation of the fundamental period of a practical building is proposed. This formula takes into account the mass and the stiffness of the building therefore, it is more logical than the conventional empirical equations. In order to verify the accuracy of the proposed formula, several examples have been solved. In these examples, calculating the fundamental mode periods of several farmed buildings utilizing the proposed formula and the conventional empirical equations has been accomplished. Comparing the obtained results with those obtained from a dynamic computer has shown that the proposed formula provides a more accurate estimation of the fundamental periods of practical buildings. Since the proposed method is still simple to use and requires only a minimum computing effort, it is believed to be ideally suited for design purposes.

Keywords: earthquake, fundamental mode period, design, building

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20998 New Subculture in Social Media

Authors: Maryam Mousivand

Abstract:

Subculture is one of the important concepts in social sciences and the field of cultural studies, which falls under the huge concept of culture. In general, subculture is a kind of movement and experience of collective resistance that is manifested by a population as a reaction against the acceptance of official identities approved by custom and society. Subcultures exist in the virtual world in the new era, and they emerged in various forms, such as the emergence of a subculture under common concepts and interests in the form of sites, channels, and groups of virtual space, which will be discussed in this article.

Keywords: subculture, social media, cultural studies, culture

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20997 La₀.₈Ba₀.₂FeO₃ Perovskite as an Additive in the Three-Way Catalyst (TWCs) for Reduction of PGMs Loading

Authors: Mahshid Davoodpoor, Zahra Shamohammadi Ghahsareh, Saeid Razfar, Alaleh Dabbaghi

Abstract:

Nowadays, air pollution has become a topic of great concern all over the world. One of the main sources of air pollution is automobile exhaust gas, which introduces a large number of toxic gases, including CO, unburned hydrocarbons (HCs), NOx, and non-methane hydrocarbons (NMHCs), into the air. The application of three-way catalysts (TWCs) is still the most effective strategy to mitigate the emission of these pollutants. Due to the stringent environmental regulations which continuously become stricter, studies on the TWCs are ongoing despite several years of research and development. This arises from the washcoat complexity and the several numbers of parameters involved in the redox reactions. The main objectives of these studies are the optimization of washcoat formulation and the investigation of different coating modes. Perovskite (ABO₃), as a promising class of materials, has unique features that make it versatile to use as an alternative to commonly mixed oxides in washcoats. High catalytic activity for oxidation reactions and its relatively high oxygen storage capacity are important properties of perovskites in catalytic applications. Herein, La₀.₈Ba₀.₂FeO₃ perovskite material was synthesized using the co-precipitation method and characterized by XRD, ICP, and BET analysis. The effect of synthesis conditions, including B site metal (Fe and Co), metal precursor concentration, and dopant (Ba), were examined on the phase purity of the products. The selected perovskite sample was used as one of the components in the TWC formulation to evaluate its catalytic performance through Light-off, oxygen storage capacity, and emission analysis. Results showed a remarkable increment in oxygen storage capacity and also revealed that T50 and emission of CO, HC, and NOx reduced in the presence of perovskite structure which approves the enhancement of catalytic performance for the new washcoat formulation. This study shows the brilliant future of advanced oxide structures in the TWCs.

Keywords: Perovskite, three-way catalyst, PGMs, PGMs reduction

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20996 "Gurza Incinerator" : Biomass Incinerator Powered by Empty Bunch of Palm Oil Fruits as Electrical Biomass Base Development

Authors: Andi Ismanto

Abstract:

Indonesia is the largest palm oil producer in the world. The increasing number of palm oil extensification in Indonesia started on 2000-2011. Based on preliminary figures from the Directorate General of Plantation, palm oil area in Indonesia until 2011 is about 8.91 million hectares.On 2011 production of palm oil CPO reaches 22.51 million tons. In the other hands, the increasing palm oil production has impact to environment. The Empty Bunch of Palm Oil (EBPO)waste was increased to 20 million tons in 2009. Utilization of waste EBPO currently only used as an organic fertilizer for plants. But, it was not a good solution, because TKKS that used as organic compost has high content of carbon and hydrogen compound. The EBPO waste has potential used as fuel by gasification because it has short time of decomposition. So, the process will be more efficient in time. Utilization of urban wastehas been created using an incinerator used as a source of electrical energy for household.Usually, waste burning process by incinerator is using diesel fuel and kerosene. It is certainly less effective and not environment friendly, considering the waste incineration process using Incinerator tools are continuously. Considering biomass is a renewable source of energy and the world's energy system must be switch from an energy based on fossil resources into the energy based on renewable resources, the "Gurza Incinerator": Design Build Powerful Biomass Incinerator Empty Bunch of Palm Oil (EBPO) as Elecrical Biomass Base Development, a renewable future technology. The tools is using EBPO waste as source of burning to burn garbage inside the Incinerator hopper. EBPO waste will be processed by means of gasification. Gasification isa process to produce gases that can be used as fuel for electrical power. Hopefully, this technology could be a renewable future energy and also as starting point of electrical biomass base development.

Keywords: incinerator, biomass, empty bunch palm oil, electrical energy

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20995 Caputo-Type Fuzzy Fractional Riccati Differential Equations with Fuzzy Initial Conditions

Authors: Trilok Mathur, Shivi Agarwal

Abstract:

This paper deals with the solutions of fuzzy-fractional-order Riccati equations under Caputo-type fuzzy fractional derivatives. The Caputo-type fuzzy fractional derivatives are defined based on Hukuhura difference and strongly generalized fuzzy differentiability. The Laplace-Adomian-Pade method is used for solving fractional Riccati-type initial value differential equations of fractional order. Moreover, we also displayed some examples to illustrate our methods.

Keywords: Caputo-type fuzzy fractional derivative, Fractional Riccati differential equations, Laplace-Adomian-Pade method, Mittag Leffler function

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20994 Effect of Electromagnetic Fields on Protein Extraction from Shrimp By-Products for Electrospinning Process

Authors: Guido Trautmann-Sáez, Mario Pérez-Won, Vilbett Briones, María José Bugueño, Gipsy Tabilo-Munizaga, Luis Gonzáles-Cavieres

Abstract:

Shrimp by-products are a valuable source of protein. However, traditional protein extraction methods have limitations in terms of their efficiency. Protein extraction from shrimp (Pleuroncodes monodon) industrial by-products assisted with ohmic heating (OH), microwave (MW) and pulsed electric field (PEF). It was performed by chemical method (using NaOH and HCl 2M) assisted with OH, MW and PEF in a continuous flow system (5 ml/s). Protein determination, differential scanning calorimetry (DSC) and Fourier-transform infrared (FTIR). Results indicate a 19.25% (PEF) 3.65% (OH) and 28.19% (MW) improvement in protein extraction efficiency. The most efficient method was selected for the electrospinning process and obtaining fiber.

Keywords: electrospinning process, emerging technology, protein extraction, shrimp by-products

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20993 Solving Transient Conduction and Radiation using Finite Volume Method

Authors: Ashok K. Satapathy, Prerana Nashine

Abstract:

Radiative heat transfer in participating medium was anticipated using the finite volume method. The radiative transfer equations are formulated for absorbing and anisotropically scattering and emitting medium. The solution strategy is discussed and the conditions for computational stability are conferred. The equations have been solved for transient radiative medium and transient radiation incorporated with transient conduction. Results have been obtained for irradiation and corresponding heat fluxes for both the cases. The solutions can be used to conclude incident energy and surface heat flux. Transient solutions were obtained for a slab of heat conducting in slab by thermal radiation. The effect of heat conduction during the transient phase is to partially equalize the internal temperature distribution. The solution procedure provides accurate temperature distributions in these regions. A finite volume procedure with variable space and time increments is used to solve the transient energy equation. The medium in the enclosure absorbs, emits, and anisotropically scatters radiative energy. The incident radiations and the radiative heat fluxes are presented in graphical forms. The phase function anisotropy plays a significant role in the radiation heat transfer when the boundary condition is non-symmetric.

Keywords: participating media, finite volume method, radiation coupled with conduction, heat transfer

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20992 Preparation of Protective Coating Film on Metal Alloy

Authors: Rana Th. A. Al-rubaye

Abstract:

A novel chromium-free protective coating films based on a zeolite coating was growing onto a FeCrAlloy metal using in –situ hydrothermal method. The zeolite film was obtained using in-situ crystallization process that is capable of coating large surfaces with complex shape and in confined spaces has been developed. The zeolite coating offers an advantage of a high mechanical stability and thermal stability. The physico-chemical properties were investigated using X-ray diffraction (XRD), Electron microscopy (SEM), Energy Dispersive X–ray analysis (EDX) and Thermogravimetric Analysis (TGA). The transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces was followed using SEM and XRD. In addition, the robustness of the prepared coating was confirmed by subjecting these to thermal cycling (ambient to 550°C).

Keywords: fecralloy, zsm-5 zeolite, zeolite coatings, hydrothermal method

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20991 Feasibility of Leukemia Cancer Treatment (K562) by Atmospheric Pressure Plasma Jet

Authors: Mashayekh Amir Shahriar, Akhlaghi Morteza, Rajaee Hajar, Khani Mohammad Reza, Shokri Babak

Abstract:

A new and novel approach in medicine is the use of cold plasma for various applications such as sterilization blood coagulation and cancer cell treatment. In this paper a pin-to-hole plasma jet suitable for biological applications is investigated, characterized and the possibility and feasibility of cancer cell treatment is evaluated. The characterization includes power consumption via Lissajous method, thermal behavior of plasma using Infra-red camera as a novel method, Optical Emission Spectroscopy (OES) to determine the species that are generated. Treatment of leukemia cancer cells is also implemented and MTT assay is used to evaluate viability.

Keywords: Atmospheric Pressure Plasma Jet (APPJ), Plasma Medicine, Cancer cell treatment, leukemia, Optical Emission

Procedia PDF Downloads 653
20990 Steel Bridge Coating Inspection Using Image Processing with Neural Network Approach

Authors: Ahmed Elbeheri, Tarek Zayed

Abstract:

Steel bridges deterioration has been one of the problems in North America for the last years. Steel bridges deterioration mainly attributed to the difficult weather conditions. Steel bridges suffer fatigue cracks and corrosion, which necessitate immediate inspection. Visual inspection is the most common technique for steel bridges inspection, but it depends on the inspector experience, conditions, and work environment. So many Non-destructive Evaluation (NDE) models have been developed use Non-destructive technologies to be more accurate, reliable and non-human dependent. Non-destructive techniques such as The Eddy Current Method, The Radiographic Method (RT), Ultra-Sonic Method (UT), Infra-red thermography and Laser technology have been used. Digital Image processing will be used for Corrosion detection as an Alternative for visual inspection. Different models had used grey-level and colored digital image for processing. However, color image proved to be better as it uses the color of the rust to distinguish it from the different backgrounds. The detection of the rust is an important process as it’s the first warning for the corrosion and a sign of coating erosion. To decide which is the steel element to be repainted and how urgent it is the percentage of rust should be calculated. In this paper, an image processing approach will be developed to detect corrosion and its severity. Two models were developed 1st to detect rust and 2nd to detect rust percentage.

Keywords: steel bridge, bridge inspection, steel corrosion, image processing

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20989 Enhanced Fluid Discrimination in Reservoir Rocks Using Deep Learning-Based Seismic Inversion with Poroelastic Modelling

Authors: Badreldein Mohamed, Song Jianguo

Abstract:

Seismic inversion is the most efficient technique that yields critical information for fluid differentiation inside reservoir rocks. Conventional approaches depend extensively on unreliable stochastic techniques and necessitate considerable computational resources and effort. Deep learning is an economical and effective approach for extracting complex patterns from data to provide accurate predictions. The lack of borehole label data, essential for training precise models, impedes its application. Moreover, the utilization of synthetic data is inadequate for producing data that aligns with actual geological conditions and necessitates additional modification of the trained models for practical applications. This study commenced with poroelastic modelling to mimic the bulk and shear moduli of rock using various saturating fluids. Subsequently, we employed the acquired moduli in empirical equations to calculate the density and velocities of the saturated reservoir, then computed Vp/Vs, Poisson’s ratio, and acoustic impedance, which is critical for fluid analysis. This supplied essential labels for training multi-base inversion deep learning models with diverse topologies and hyperparameters. We integrated a prior knowledge component into the methodology to guarantee stability and compatibility with the local geological conditions. Subsequently, we assigned weights to individual models according to their accuracies and combined them to attain the most desirable outcome. The suggested method demonstrated superior performance compared to conventional inversion and popular deep learning approaches in a real-world application. This result is particularly crucial for understanding the reservoir’s potential for oil and gas production as well as for predicting its behaviour under different conditions.

Keywords: deep learning, reservoir rock characterization, rock-physics models, seismic inversion

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20988 Contourlet Transform and Local Binary Pattern Based Feature Extraction for Bleeding Detection in Endoscopic Images

Authors: Mekha Mathew, Varun P Gopi

Abstract:

Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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20987 Study of the Optical Illusion Effects of Color Contrasts on Body Image Perception

Authors: A. Hadj Taieb, H. Ennouri

Abstract:

The current study aimed to investigate the effect that optical illusion garments have on a woman’s self-perception of her own body shape. First, we created different optical illusion garment by using color contrasts. Second, a short survey based on visual perception is addressed to women in order to compare the different optical illusion garments to determine if they met the established 'ideal' body shape. A ‘visual analysis method’ was used to investigate the clothing models with optical illusions. The theories in relation with the optical illusion were used through this method. The effects of the optical illusion of color contrast on body shape in the fashion sector were tried to be revealed.

Keywords: optical illusion, color contrasts, body image perception, self-esteem

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20986 Evaluation of Aggregate Risks in Sustainable Manufacturing Using Fuzzy Multiple Attribute Decision Making

Authors: Gopinath Rathod, Vinod Puranik

Abstract:

Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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20985 Effect of Floods on Water Quality: A Global Review and Analysis

Authors: Apoorva Bamal, Agnieszka Indiana Olbert

Abstract:

Floods are known to be one of the most devastating hydro-climatic events, impacting a wide range of stakeholders in terms of environmental, social and economic losses. With difference in inundation durations and level of impact, flood hazards are of different degrees and strength. Amongst various set of domains being impacted by floods, environmental degradation in terms of water quality deterioration is one of the majorly effected but less highlighted domains across the world. The degraded water quality is caused by numerous natural and anthropogenic factors that are both point and non-point sources of pollution. Therefore, it is essential to understand the nature and source of the water pollution due to flooding. The major impact of floods is not only on the physico-chemical water quality parameters, but also on the biological elements leading to a vivid influence on the aquatic ecosystem. This deteriorated water quality is impacting many water categories viz. agriculture, drinking water, aquatic habitat, and miscellaneous services requiring an appropriate water quality to survive. This study identifies, reviews, evaluates and assesses multiple researches done across the world to determine the impact of floods on water quality. With a detailed statistical analysis of top relevant researches, this study is a synopsis of the methods used in assessment of impact of floods on water quality in different geographies, and identifying the gaps for further abridgement. As per majority of the studies, different flood magnitudes have varied impact on the water quality parameters leading to either increased or decreased values as compared to the recommended values for various categories. There is also an evident shift of the biological elements in the impacted waters leading to a change in its phenology and inhabitants of the specified water body. This physical, chemical and biological water quality degradation by floods is dependent upon its duration, extent, magnitude and flow direction. Therefore, this research provides an overview into the multiple impacts of floods on water quality, along with a roadmap of way forward to an efficient and uniform linkage of floods and impacted water quality dynamics.

Keywords: floods, statistical analysis, water pollution, water quality

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20984 Nutritional Characteristics, Phytochemical and Antimicrobial Potential of Leaf Protein Concentrates from Huckleberry

Authors: Sodamade Abiodun, Adeboye Olubunmi Omolara

Abstract:

Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that can serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of Huckleberry was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education campus, Oyo. The sample was authenticated at the forestry research institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition; mineral analysis phytochemical and antimicrobial properties of the leaf protein concentrates were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive results of the mineral analysis showed that the sample contains Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g while cadmium was not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, steroid, Terpenoid, cordial glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Huckleberry leaf protein concentrates showed that it contains bioactive compounds that are capable of eradicating some tested microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisidlae pneumonia and Proteus merabilis. The results of the analysis of leaf protein concentrates of Huckleberry showed that the sample contains high nutrient and mineral constituents and phytochemical compounds that could make the sample useful for medicinal activities.

Keywords: huckleberry, mentha piperita, phytochemical, leaf protein concentrates, nutritional characteristics

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20983 Time/Temperature-Dependent Finite Element Model of Laminated Glass Beams

Authors: Alena Zemanová, Jan Zeman, Michal Šejnoha

Abstract:

The polymer foil used for manufacturing of laminated glass members behaves in a viscoelastic manner with temperature dependence. This contribution aims at incorporating the time/temperature-dependent behavior of interlayer to our earlier elastic finite element model for laminated glass beams. The model is based on a refined beam theory: each layer behaves according to the finite-strain shear deformable formulation by Reissner and the adjacent layers are connected via the Lagrange multipliers ensuring the inter-layer compatibility of a laminated unit. The time/temperature-dependent behavior of the interlayer is accounted for by the generalized Maxwell model and by the time-temperature superposition principle due to the Williams, Landel, and Ferry. The resulting system is solved by the Newton method with consistent linearization and the viscoelastic response is determined incrementally by the exponential algorithm. By comparing the model predictions against available experimental data, we demonstrate that the proposed formulation is reliable and accurately reproduces the behavior of the laminated glass units.

Keywords: finite element method, finite-strain Reissner model, Lagrange multipliers, generalized Maxwell model, laminated glass, Newton method, Williams-Landel-Ferry equation

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20982 Local Directional Encoded Derivative Binary Pattern Based Coral Image Classification Using Weighted Distance Gray Wolf Optimization Algorithm

Authors: Annalakshmi G., Sakthivel Murugan S.

Abstract:

This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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20981 Advanced Machine Learning Algorithm for Credit Card Fraud Detection

Authors: Manpreet Kaur

Abstract:

When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

Procedia PDF Downloads 103
20980 The System-Dynamic Model of Sustainable Development Based on the Energy Flow Analysis Approach

Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

Abstract:

Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

Procedia PDF Downloads 51
20979 Thermoluminescence Study of Cu Doped Lithium Tetra Borate Samples Synthesized by Water/Solution Assisted Method

Authors: Swarnapriya Thiyagarajan, Modesto Antonio Sosa Aquino, Miguel Vallejo Hernandez, Senthilkumar Kalaiselvan Dhivyaraj, Jayaramakrishnan Velusamy

Abstract:

In this paper the lithium tetra borate (Li2B4O7) was prepared by used water/solution assisted synthesis method. Once finished the synthesization, Copper (Cu) were used to doping material with Li2B4O7 in order to enhance its thermo luminescent properties. The heating temperature parameters were 750°C for 2 hr and 150°C for 2hr. The samples produced by water assisted method were doped at different doping percentage (0.02%, 0.04%, 0.06%, 0.08%, 0.12%, 0.5%, 0.1%, and 1%) of Cu.The characteristics and identification of Li2B4O7 (undoped and doped) were determined in four tests. They are X-ray diffraction (XRD), Scanning electron microscope (SEM), Photoluminescence (PL), Ultra violet visible spectroscopy (UV Vis). As it is evidence from the XRD and SEM results the obtained Li2B4O7 and Li2B4O7 doping with Cu was confirmed and also confirmed the chemical compositition and their morphologies. The obtained lithium tetraborate XRD pattern result was verified with the reference data of lithium tetraborate with tetragonal structure from JCPDS. The glow curves of Li2B4O7 and Li2B4O7 : Cu were obtained by thermo luminescence (TLD) reader (Harshaw 3500). The pellets were irradiated with different kind of dose (58mGy, 100mGy, 500mGy, and 945mGy) by using an X-ray source. Finally this energy response was also compared with TLD100. The order of kinetics (b), frequency factor (S) and activation energy (E) or the trapping parameters were calculated using peak shape method. Especially Li2B4O7: Cu (0.1%) presents good glow curve in all kind of doses. The experimental results showed that this Li2B4O7: Cu could have good potential applications in radiation dosimetry. The main purpose of this paper is to determine the effect of synthesis on the TL properties of doped lithium tetra borate Li2B4O7.

Keywords: dosimetry, irradiation, lithium tetraborate, thermoluminescence

Procedia PDF Downloads 272
20978 Application of the Electrical Resistivity Tomography and Tunnel Seismic Prediction 303 Methods for Detection Fracture Zones Ahead of Tunnel: A Case Study

Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost

Abstract:

The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.

Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones

Procedia PDF Downloads 139
20977 Non-Linear Causality Inference Using BAMLSS and Bi-CAM in Finance

Authors: Flora Babongo, Valerie Chavez

Abstract:

Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

Procedia PDF Downloads 146
20976 Comparative Study of R.C.C. Steel and Concrete Building

Authors: Mahesh Suresh Kumawat

Abstract:

Steel concrete composite construction means the concrete slab is connected to the steel beam with the help of shear connectors so that they act as a single unit. In the present work, steel concrete composite with RCC options are considered for comparative study of G+9 story commercial building which is situated in earthquake zone-III and for earthquake loading, the provisions of IS: 1893(Part1)-2002 is considered. A three dimensional modeling and analysis of the structure are carried out with the help of SAP 2000 software. Equivalent Static Method of Analysis and Response spectrum analysis method are used for the analysis of both Composite & R.C.C. structures. The results are compared and it was found that composite structure is more economical.

Keywords: composite beam, column, RCC column, RCC beam, shear connector, SAP 2000 software

Procedia PDF Downloads 449
20975 Gender Recognition with Deep Belief Networks

Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

Abstract:

A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

Procedia PDF Downloads 445