Search results for: strength prediction models

Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

Procedia PDF Downloads 152

Authors: Saksham

Abstract:

Concrete's versatility and affordability make it a highly competitive building material capable of meeting diverse requirements. However, the increasing demands placed on structures and the need for enhanced durability and performance have driven the development of distinct cementitious materials and concrete composites. One significant aspect of this advancement is the utilization of waste materials from industries, such as fly ash, to improve concrete's properties. Fly ash, a byproduct of coal combustion can enhance concrete's strength and durability while reducing environmental impact. Additionally, steel fibers can enhance concrete's toughness and crack resistance, contributing to improved structural performance. The experimental study aims to optimize the proportion of ingredients in M30-grade concrete, incorporating fly ash and steel fibers. By varying fly ash content (10% to 30%) and steel fiber dosage (0% to 1.5%), the research seeks to determine the optimal combination for achieving the desired compressive strength. Two sets of experiments are conducted: one focusing on varying fly ash content while keeping steel fiber dosage constant, and the other focusing on varying steel fiber dosage while keeping other parameters fixed. Through systematic testing, molding, curing, and evaluation according to specified standards, the research aims to analyze the impact of fly ash and steel fibers on concrete's compressive strength. The findings have the potential to inform engineers about optimized concrete mix designs that balance performance, cost-effectiveness, and sustainability, advancing toward more resilient and environmentally friendly building practices.

Keywords: concrete, sustainability, durability, compressive strength

Procedia PDF Downloads 52

Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

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A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

Procedia PDF Downloads 154

Authors: Hamed A. Keykha, Hadi Miri

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This paper describes a new method of soil stabilisation, electro-biogrouting (EBM), for improvement of soft soil with low hydraulic conductivity. This method uses an applied voltage gradient across the soil to induce the ions and bacteria cells through the soil matrix, resulting in CaCO3 precipitation and an increase of the soil shear strength in the process. The EBM were used effectively with two injection methods; bacteria injection and products of bacteria injection. The bacteria cells, calcium ions and urea were moved across the soil by electromigration and electro osmotic flow respectively. The products of bacteria (CO3-2) were moved by electromigration. The results showed that the undrained shear strength of the soil increased from 6 to 65 and 70 kPa for first and second injection method respectively. The injection of carbonate solution and calcium could be effectively flowed in the clay soil compare to injection of bacteria cells. The detection of CaCO3 percentage and its corresponding water content across the specimen showed that the increase of undrained shear strength relates to the deposit of calcite crystals between soil particles.

Keywords: Sporosarcina pasteurii, electrophoresis, electromigration, electroosmosis, biocement

Procedia PDF Downloads 528

Authors: Ajit Brindhaban

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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

Procedia PDF Downloads 148

Authors: Chayan Gupta, Arun Prasad

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The quick evolution of industrialization causes the scarcity of precious land. Thus, it is vital need to influence the R&D societies to achieve sustainable, economic and social benefits from huge utilization of waste for universal aids. The current study promotes the influence of steel industries waste i.e. ground granulated blast furnace slag (GGBS) in geotechnical properties of jarosite waste (solid waste residues produced from hydrometallurgy operations involved in extraction of Zinc). Numerous strengths tests (unconfined compression (qu) and splitting tensile strength (qt)) are conducted on jarosite-GGBS blends (GGBS, 10-30%) with different curing periods (7, 28 & 90 days). The results indicate that both qu and qt increase with the increase in GGBS content along with curing periods. The increased strength with the addition of GGBS is also observed from microstructural study, which illustrates the occurrence of larger agglomeration of jarosite-GGBS blend particles. The Freezing-Thawing (F-T) durability analysis is also conducted for all the jarosite-GGBS blends and found that the reduction in unconfined compressive strength after five successive F-T cycles enhanced from 62% (natural jarosite) to 48, 42 and 34% at 7, 14 and 28 days curing periods respectively for stabilized jarosite-GGBS samples containing 30% GGBS content. It can be concluded from this study that blending of cementing additives (GGBS) with jarosite waste resulted in a significant improvement in geotechnical characteristics.

Keywords: jarosite, GGBS, strength characteristics, microstructural study, durability analysis

Procedia PDF Downloads 168

Authors: Zhenhua Wei, Gabriel Falzone, Bu Wang, Laurent Pilon, Gaurav Sant

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The production of ordinary Portland cement (OPC) is a CO₂ intensive process. Specifically, cement clinkering reactions require not only substantial energy in the form of heat, but also result in the release of CO₂, from limestone decarbonation and the combustion of fuel. To overcome this CO₂ intensive process, clinkering-free cementation is demonstrated by the carbonation of fly ash; i.e., a by-product of coal combustion. It is shown that in moist environments and at sub-boiling temperatures, calcium-rich fly ashes readily react with gas-phase CO₂ to provide cementation. After seven days of CO₂ exposure at 75°C, such formulations achieve a compressive strength on the order of 35 MPa and take-up 9% CO₂ (by mass of the solid). On the other hand, calcium-deficient fly ashes, due to their lack of alkalinity (i.e., abundance of mobile Ca or Mg), show little if any potential for CO₂ uptake and strength gain. The role of the CO₂ concentration and processing temperature are discussed and linked to the progress of reactions, and the development of microstructure. The outcomes demonstrate a means for enabling clinkering-free cementation while enabling beneficial utilization of CO₂ and fly ash; i.e., two abundant but underutilized industrial by-products.

Keywords: fly ash, carbonation, concrete, strength

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Authors: Sidique Fofanah

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This paper explores the intersection of traditional communication theories and modern digital technologies, analyzing how established models adapt to contemporary communication platforms. It examines the evolving nature of interpersonal, group, and mass communication within digital environments, emphasizing the role of social media, AI-driven communication tools, and virtual reality in reshaping communication paradigms. The paper also discusses the implications for future research and practice in communication studies, proposing an integrated framework that accommodates both classical and emerging theories.

Keywords: communication, traditional models, emerging platforms, digital media

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

Procedia PDF Downloads 259

Authors: Xianghe Dai, Dennis Lam, Therese Sheehan, Naveed Rehman, Jie Yang

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Concrete is one of the most used construction materials that may be made onsite as fresh concrete and then placed in formwork to produce the desired shapes of structures. It has been recognized that the raw materials and mix proportion of concrete dominate the mechanical characteristics of hardened concrete, and the curing method and environment applied to the concrete in early stages of hardening will significantly influence the concrete properties, such as compressive strength, durability, permeability etc. In construction practice, there are various curing methods to maintain the presence of mixing water throughout the early stages of concrete hardening. They are also beneficial to concrete in hot weather conditions as they provide cooling and prevent the evaporation of water. Such methods include ponding or immersion, spraying or fogging, saturated wet covering etc. Also there are various curing methods that may be implemented to decrease the level of water lost which belongs to the concrete surface, such as putting a layer of impervious paper, plastic sheeting or membrane on the concrete to cover it. In the concrete material laboratory, accelerated strength gain methods supply the concrete with heat and additional moisture by applying live steam, coils that are subject to heating or pads that have been warmed electrically. Currently when determining the mechanical parameters of a concrete, the concrete is usually sampled from fresh concrete on site and then cured and tested in laboratories where standardized curing procedures are adopted. However, in engineering practice, curing procedures in the construction sites after the placing of concrete might be very different from the laboratory criteria, and this includes some standard curing procedures adopted in the laboratory that can’t be applied on site. Sometimes the contractor compromises the curing methods in order to reduce construction costs etc. Obviously the difference between curing procedures adopted in the laboratory and those used on construction sites might over- or under-estimate the real concrete quality. This paper presents the effect of three typical curing methods (air curing, water immersion curing, plastic film curing) and of maintaining concrete in steel moulds on the compressive strength development of normal concrete. In this study, Portland cement with 30% fly ash was used and different curing periods, 7 days, 28 days and 60 days were applied. It was found that the highest compressive strength was observed from concrete samples to which 7-day water immersion curing was applied and from samples maintained in steel moulds up to the testing date. The research results implied that concrete used as infill in steel tubular members might develop a higher strength than predicted by design assumptions based on air curing methods. Wrapping concrete with plastic film as a curing method might delay the concrete strength development in the early stages. Water immersion curing for 7 days might significantly increase the concrete compressive strength.

Keywords: compressive strength, air curing, water immersion curing, plastic film curing, maintaining in steel mould, comparison

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Authors: Armenuhi Ghazaryan, Qnarik Poghosyan, Tadevos Markosyan

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We have considered the high-order harmonic generation in-plane graphene quantum dots of hexagonal shape by the independent quasiparticle approximation-tight binding model. We have investigated how such a nonlinear effect is affected by a strong optical wave field, quantum dot typical band gap and lateral size, and dephasing processes. The equation of motion for the density matrix is solved by performing the time integration with the eight-order Runge-Kutta algorithm. If the optical wave frequency is much less than the quantum dot intrinsic band gap, the main aspects of multiphoton high harmonic emission in quantum dots are revealed. In such a case, the dependence of the cutoff photon energy on the strength of the optical pump wave is almost linear. But when the wave frequency is comparable to the bandgap of the quantum dot, the cutoff photon energy shows saturation behavior with an increase in the wave field strength.

Keywords: strong wave field, multiphoton, bandgap, wave field strength, nanostructure

Procedia PDF Downloads 156

Authors: Zahid Ahmad, Nosheen Imran, Nauman Ali, Farah Amir

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The objective of the study is to forecast the US Dollar and Pak Rupee exchange rate by using time series models. For this purpose, daily exchange rates of US and Pakistan for the period of January 01, 2007 - June 2, 2017, are employed. The data set is divided into in sample and out of sample data set where in-sample data are used to estimate as well as forecast the models, whereas out-of-sample data set is exercised to forecast the exchange rate. The ADF test and PP test are used to make the time series stationary. To forecast the exchange rate ARIMA model and GARCH model are applied. Among the different Autoregressive Integrated Moving Average (ARIMA) models best model is selected on the basis of selection criteria. Due to the volatility clustering and ARCH effect the GARCH (1, 1) is also applied. Results of analysis showed that ARIMA (0, 1, 1 ) and GARCH (1, 1) are the most suitable models to forecast the future exchange rate. Further the GARCH (1,1) model provided the volatility with non-constant conditional variance in the exchange rate with good forecasting performance. This study is very useful for researchers, policymakers, and businesses for making decisions through accurate and timely forecasting of the exchange rate and helps them in devising their policies.

Keywords: exchange rate, ARIMA, GARCH, PAK/USD

Procedia PDF Downloads 561

Authors: Cheng-Hao Jiang, Mu-Xuan Tao

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The rigid diaphragm model may cause errors in the calculation of internal forces due to neglecting the in-plane deformation of the diaphragm. This paper thus studies the effects of different diaphragm in-plane models (including in-plane rigid model and in-plane flexible model) on the seismic performance of structures. Taking an actual industrial plant as an example, the seismic performance of the structure is predicted using different floor diaphragm models, and the analysis errors caused by different diaphragm in-plane models including deformation error and internal force error are calculated. Furthermore, the influence of the aspect ratio on the analysis errors is investigated. Finally, the code rationality is evaluated by assessing the analysis errors of the structure models whose floors were determined as rigid according to the code’s criterion. It is found that different floor models may cause great differences in the distribution of structural internal forces, and the current code may underestimate the influence of the floor in-plane effect.

Keywords: industrial plant, diaphragm, calculating error, code rationality

Procedia PDF Downloads 140

Authors: Chaiyaporn Yuksen

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Backgroud: Supraventricular tachycardia (SVT) is an abnormally fast atrial tachycardia characterized by narrow (≤ 120 ms) and constant QRS. Adenosine was the drug of choice; the first dose was 6 mg. It can be repeated with the second and third doses of 12 mg, with greater than 90% success. The study found that patients observed at 4 hours after normal sinus rhythm was no recurrence within 24 hours. The objective of this study was to investigate the factors that influence the recurrence of SVT after adenosine in the emergency department (ED). Method: The study was conducted retrospectively exploratory model, prognostic study at the Emergency Department (ED) in Faculty of Medicine, Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand. The study was conducted for ten years period between 2010 and 2020. The inclusion criteria were age > 15 years, visiting the ED with SVT, and treating with adenosine. Those patients were recorded with the recurrence SVT in ED. The multivariable logistic regression model developed the predictive model and prediction score for recurrence PSVT. Result: 264 patients met the study criteria. Of those, 24 patients (10%) had recurrence PSVT. Five independent factors were predictive of recurrence PSVT. There was age>65 years, heart rate (after adenosine) > 100 per min, structural heart disease, and dose of adenosine. The clinical risk score to predict recurrence PSVT is developed accuracy 74.41%. The score of >6 had the likelihood ratio of recurrence PSVT by 5.71 times Conclusion: The clinical predictive score of > 6 was associated with recurrence PSVT in ED.

Keywords: clinical prediction score, SVT, recurrence, emergency department

Procedia PDF Downloads 155

Authors: Okafor C. Uche, Agbo P. Ejiofor, Okezie C. Eziuche

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This study provides a regeneration protocol for Treculia africana Decne (an endangered plant) through embryo culture. Mature zygotic embryos of T. africana were excised from the seeds aseptically and cultured on varied strengths (full, half and quarter) of Murashige and Skoog (MS) basal medium supplemented. All treatments experienced 100±0.00 percent sprouting except for half and quarter strengths. Plantlets in MS full strength had the highest fresh weight, leaf area, and longest shoot length when compared to other treatments. All explants in full, half, quarter strengths and control had the same number of leaves and sprout rate. Between the treatments, there was a significant difference (P>0.05) in their effect on the length of shoot and root, number of adventitious root, leaf area, and fresh weight. Full strength had the highest mean value in all the above-mentioned parameters and differed significantly (P>0.05) from others except in shoot length, number of adventitious roots, and root length where it did not differ (P<0.05) from half strength. The result of this study indicates that full strength MS basal medium offers a better option for the optimum growth for Treculia africana regeneration in vitro.

Keywords: medium strengths, Murashige and Skoog, Treculia africana, zygotic embryos

Procedia PDF Downloads 254

Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 149

Authors: S. A. Naeini, A. Mahigir

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Naturally occurring cohesive soil deposits are inherently anisotropic with respect to different properties amongst which is the shear strength. The anisotropy is primary due to the process of sedimentation followed by predominantly one-dimensional consolidation. However, most soils in their natural states exhibit some anisotropy with respect to shear strength and some non-homogeneity with respect to depth. In this paper the standard Mohr-Coulomb yield criterion was modified to consider the anisotropic shear strength properties. The term non-homogeneity used in this paper refers to only the cohesion intercept which is assumed to vary linearly with depth. The effect of both anisotropy and deterministic non-homogeneity on bearing capacity of shallow foundation was investigated using finite difference method. Result of numerical analysis indicates that the cohesion anisotropy has a significant effect on bearing capacity of shallow foundation. Furthermore, the linear and bilinear heterogeneity affects the bearing capacity in a similar way although the anisotropy issue emerges to be more important as far as shallow foundations are considered.

Keywords: anisotropic ratio, finite difference analysis, bearing capacity, heterogeneity

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Authors: Brahim Safi, Mohammed Saidi, A. Benmounah, Jozef Mitterpach

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The aim of this work is to study the rheological and physico-mechanical properties of a self-compacting concrete elaborated with sea shells as an addition cementitious (total replacement of limestone fillers) and sand (partial and total substitution fine aggregate). Also, this present study is registered in the context of sustainable development by using this waste type which caused environmental problems. After preparation the crushed shells (obtaining fine aggregate) and finely crushed shells (obtaining end powder), concretes were manufactured using these two products. Rheological characterization tests (fluidity, filling capacity and segregation) and physico-mechanical properties (density and strength) were carried on these concretes. The results obtained show that it can be used as fin addition (by total replacement of limestone) or also used as sand by total substitution of natural sand.

Keywords: seashells, limestone, sand, self-compacting concrete, fluidity, compressive strength, flexural strength

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Authors: S. Girish, N. Ajay

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Permeation properties have been widely used to quantify durability characteristics of concrete for assessing long term performance and sustainability. The processes of deterioration in concrete are mediated largely by water. There is a strong interest in finding a better way of assessing the material properties of concrete in terms of durability. Water sorptivity is a useful single material property which can be one of the measures of durability useful in service life planning and prediction, especially in severe environmental conditions. This paper presents the results of the comparative study of sorptivity of Self-Compacting Concrete (SCC) with conventionally vibrated concrete. SCC is a new, special type of concrete mixture, characterized by high resistance to segregation that can flow through intricate geometrical configuration in the presence of reinforcement, under its own mass, without vibration and compaction. SCC mixes were developed for the paste contents of 0.38, 0.41 and 0.43 with fly ash as the filler for different cement contents ranging from 300 to 450 kg/m3. The study shows better performance by SCC in terms of capillary absorption. The sorptivity value decreased as the volume of paste increased. The use of higher paste content in SCC can make the concrete robust with better densification of the micro-structure, improving the durability and making the concrete more sustainable with improved long term performance. The sorptivity based on secondary absorption can be effectively used as a durability index to predict the time duration required for the ingress of water to penetrate the concrete, which has practical significance.

Keywords: self-compacting concrete, service life prediction, sorptivity, volume of paste

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Authors: Bowen Ding, Yihao Kuang

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In recent years, large-scale pre-trained language models have achieved state-of-the-art performance on a variety of natural language processing tasks. The word vectors produced by these language models can be viewed as dense encoded presentations of natural language that in text form. However, it is unknown how much linguistic information is encoded and how. In this paper, we construct several corresponding probing tasks for multiple linguistic information to clarify the encoding capabilities of different language models and performed a visual display. We firstly obtain word presentations in vector form from different language models, including BERT, ELMo, RoBERTa and GPT. Classifiers with a small scale of parameters and unsupervised tasks are then applied on these word vectors to discriminate their capability to encode corresponding linguistic information. The constructed probe tasks contain both semantic and syntactic aspects. The semantic aspect includes the ability of the model to understand semantic entities such as numbers, time, and characters, and the grammatical aspect includes the ability of the language model to understand grammatical structures such as dependency relationships and reference relationships. We also compare encoding capabilities of different layers in the same language model to infer how linguistic information is encoded in the model.

Keywords: language models, probing task, text presentation, linguistic information

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Alireza Barari, Saeed Shirali

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The etiology of obesity is heterogeneous with several factors, and the pathophysiology of obesity has recently related to leptin, oxidative damage, and inflammation. Silybum marianum have a health-promoting perspective and has shown that bioactive molecules of silymarin have the antioxidant and antitumor properties and can affect secretion of hormones and enzyme activity in animal. This study aimed to evaluate the antioxidant effects and changes in hormonal levels and body composition after silymarin consumption. Forty-five healthy untrained colleges male take part in the 4-week investigation. The subjects were assigned to 5 groups: endurance training, Silymarin with endurance training, strength training with placebo, Silymarin with strength training or placebo. Body fat percentage and Blood sample analysis were measured before and after the intervention to assay leptin, adiponectin and paraoxonase in the sample of subject's serum. There was a considerable decrease in body fat percent and a significant increase in VO2 max in 'Strength training' and 'Strength training with Silymarin' groups. But, no significant changes in levels of leptin, adiponectinin, and paraoxanase (PON) that were observed between exercise and exercise with Silymarin in these groups. We observed reduction in body fat% and increase in adiponectin induced by exercise for 4 weeks in untrained healthy men. Silybin, could not effectively improve all parameters and don’t prevent the progression of cell damage by antioxidant activity of PON.

Keywords: anti-inflammatory activity, antioxidant activity, silymarin, body composition, paraoxonase (PON)

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Authors: Martin Alexander Eder, Sergei Semenov

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Many glass-epoxy composite structures, such as large utility wind turbine rotor blades (WTBs), comprise of adhesive joints with typically thick bond lines used to connect the different components during assembly. Performance optimization of rotor blades to increase power output by simultaneously maintaining high stiffness-to-low-mass ratios entails intricate geometries in conjunction with complex anisotropic material behavior. Consequently, adhesive joints in WTBs are subject to multiaxial stress states with significant stress gradients depending on the local joint geometry. Moreover, the dynamic aero-elastic interaction of the WTB with the airflow generates non-proportional, variable amplitude stress histories in the material. Empiricism shows that a prominent failure type in WTBs is high cycle fatigue failure of adhesive bond line interfaces, which in fact over time developed into a design driver as WTB sizes increase rapidly. Structural optimization employed at an early design stage, therefore, sets high demands on computationally efficient interface fatigue models capable of predicting the critical locations prone for interface failure. The numerical stress-based interface fatigue model presented in this work uses the Drucker-Prager criterion to compute three different damage indices corresponding to the two interface shear tractions and the outward normal traction. The two-parameter Drucker-Prager model was chosen because of its ability to consider shear strength enhancement under compression and shear strength reduction under tension. The governing interface damage index is taken as the maximum of the triple. The damage indices are computed through the well-known linear Palmgren-Miner rule after separate rain flow-counting of the equivalent shear stress history and the equivalent pure normal stress history. The equivalent stress signals are obtained by self-similar scaling of the Drucker-Prager surface whose shape is defined by the uniaxial tensile strength and the shear strength such that it intersects with the stress point at every time step. This approach implicitly assumes that the damage caused by the prevailing multiaxial stress state is the same as the damage caused by an amplified equivalent uniaxial stress state in the three interface directions. The model was implemented as Python plug-in for the commercially available finite element code Abaqus for its use with solid elements. The model was used to predict the interface damage of an adhesively bonded, tapered glass-epoxy composite cantilever I-beam tested by LM Wind Power under constant amplitude compression-compression tip load in the high cycle fatigue regime. Results show that the model was able to predict the location of debonding in the adhesive interface between the webfoot and the cap. Moreover, with a set of two different constant life diagrams namely in shear and tension, it was possible to predict both the fatigue lifetime and the failure mode of the sub-component with reasonable accuracy. It can be concluded that the fidelity, robustness and computational efficiency of the proposed model make it especially suitable for rapid fatigue damage screening of large 3D finite element models subject to complex dynamic load histories.

Keywords: adhesive, fatigue, interface, multiaxial stress

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Authors: Susmita Panda, Arnab Banerjee, Ajinkya Baxy, Bappaditya Manna

Abstract:

The design of short to medium-span high-speed bridges in critical locations is an essential aspect of vehicle-bridge interaction. Due to dynamic interaction between moving load and bridge, mathematical models or finite element modeling computations become time-consuming. Thus, to reduce the computational effort, a universal approximator using an artificial neural network (ANN) has been used to evaluate the dynamic response of the bridge. The data set generation and training of surrogate models have been conducted over the results obtained from mathematical modeling. Further, the robustness of the surrogate model has been investigated, which showed an error percentage of less than 10% with conventional methods. Additionally, the dependency of the dynamic response of the bridge on various load and bridge parameters has been highlighted through a parametric study.

Keywords: artificial neural network, mode superposition method, moving load analysis, surrogate models

Procedia PDF Downloads 100

Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

Abstract:

This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

Procedia PDF Downloads 11

Authors: Marthin Dody Josias Sumajouw, Bryan Wijaya, Servie O. Dapas, Ronny E. Pandaleke, Banu Handono, Fabian J. Manoppo

Abstract:

Ordinary Portland Cement (OPC) takes a big role as a concrete binder in infrastructure construction purposes, nevertheless, it produces CO2 emissions abundantly. To reduce the CO2 emissions produced by OPC concrete, nowadays, geopolymer material become one of the solutions due to it being a binder made from waste with pozzolan material. In concrete industries, geopolymer concrete has evolved as a more environmentally friendly material than OPC concrete. The geopolymer concrete was created without the usage of OPC known as cementless concrete materials. Geopolymer concrete obtains silicon and aluminum from industrial by-products such as fly ash, ground granulated blast furnace slag, and kaolinite. A highly alkaline solution chemically activates Si and Al, forming a matrix that holds together the loose aggregates as well as additional unreacted components in the mixture. They are then dissolved in alkaline activating solutions, where they polymerize into molecular chains, resulting in rigid binders. This research aims to get an eco-friendly material that can reduce the use of OPC as a binder and be used for infrastructure development end-products such as Curbs, Pavement Bricks, and Wall Bricks. This research was conducted as applied research to develop new products of environmentally friendly materials by utilizing fly ash and employed for infrastructure development, particularly for the production of end products such as Curbs, Pavement Bricks, and Wall Bricks. Three types of end products with various dimensions and mix designs have been made and tested in the laboratory, resulting in quantitative datasets to be used for identifying patterns and relationships among density, compressive strength, flexural strength, and water absorption. The result found that geopolymer binders can be used for the production of curbs, pavement bricks, and wall bricks. Geopolymer curbs have an average compressive strength of 19,36 MPa, which can be determined as K-233 concrete. Geopolymer pavement bricks have an average compressive strength of 20,79 MPa. It can be used in parking areas and determined as the grade B of pavement bricks according to SNI 03-0691-1996. Geopolymer wall bricks have an average compressive strength of 11,24 MPa, which can be determined as the grade I of Wall Bricks according to SNI 03-0349-1989.

Keywords: absorption, compressive strength, curbs, end products, geopolymer, pavement bricks, wall bricks

Procedia PDF Downloads 31

Authors: A. I. O. Zaid, A. M. Attieh, S. M. A. Al Qawabah

Abstract:

Aluminum and its alloys solidify in columnar structure with large grain size which tends to reduce their mechanical strength and surface quality. They are, therefore, grain refined by addition of either titanium or titanium plus boron to their melt before solidification. Equal channel angular pressing, ECAP, process is a recent forming method for producing heavy plastic deformation in materials. In this paper, the effect of molybdenum addition to aluminum grain refined by Ti+B on its metallurgical and mechanical characteristics are investigated in the as cast condition and after pressing by the ECAP process. It was found that addition of Mo or Ti+B alone or together to aluminum resulted in grain refining of its microstructure in the as cast condition, as the average grain size was reduced from 139 micron to 46 micron when Mo and Ti+B are added together. Pressing by the ECAP process resulted in further refinement of the microstructure where 32 micron of average grain size was achieved in Al and the Al-Mo microalloy. Regarding the mechanical strength, addition of Mo or Ti+B alone to Al resulted in deterioration of its mechanical behavior but resulted in enhancement of its mechanical behavior when added together, increase of 10% in flow stress was achieved at 20% strain. However, pressing by ECAP addition of Mo or Ti+B alone to Al resulted in enhancement of its mechanical strength but reduced its strength when added together.

Keywords: ECAP, aluminum, cast, mechanical characteristics, Mo grain refiner

Procedia PDF Downloads 472

Authors: Animish Jain

Abstract:

This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

Procedia PDF Downloads 79

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

Procedia PDF Downloads 242

Authors: Esma Gizem Daskiran, Mehmet Mustafa Daskiran, Mustafa Gencoglu

Abstract:

Textile reinforced cementitious composite (TRCC) is a development of a composite material where textile and fine-grained concrete (matrix) materials are used in combination. These matrices offer high performance properties in many aspects. To achieve high performance, polymer modified fine-grained concretes were used as matrix material which have high flexural strength. In this study, ten latex polymers and ten powder polymers were added to fine-grained concrete mixtures. These latex and powder polymers were added to the mixtures at different rates related to binder weight. Mechanical properties such as compressive and flexural strength were studied. Results showed that latex polymer and redispersible polymer modified fine-grained concretes showed different mechanical performance. A wide range of both latex and redispersible powder polymers were studied. As the addition rate increased compressive strength decreased for all mixtures. Flexural strength increased as the addition rate increased but significant enhancement was not observed through all mixtures.

Keywords: textile reinforced composite, cement, fine grained concrete, latex, redispersible powder

Procedia PDF Downloads 256