Search results for: Deep Shikha

Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

Abstract:

Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

Procedia PDF Downloads 147

Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

Abstract:

Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

Procedia PDF Downloads 135

Authors: Avatharam Ganivada, Krishna Shah

Abstract:

The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

Procedia PDF Downloads 72

Authors: Djarot B. Darmadi

Abstract:

The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo-Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.

Keywords: residual stress, ferritic steels, SSPT, coupled-TMM

Procedia PDF Downloads 270

Authors: J. Sánchez-Beaskoetxea

Abstract:

The analysis of accidents, such as marine accidents, is one of the most useful instruments to avoid future accidents. In the case of marine accidents, from a simple collision of a small boat in a port to the wreck of a gigantic tanker ship, the study of the causes of the accidents is the basis of a great part of the marine international legislation. Some countries have official institutions who investigate all the accidents in which a ship with their flag is involved. In the case of the USA, the National Transportation Safety Board (NTSB) is responsible for these researches. The NTSB, after a deep investigation into each accident, publishes a Marine Accident Report with the possible cause of the accident. This paper analyses all the Marine Accident Reports published by the NTBS and focuses its attention especially in the Human Errors that led to reported accidents. In this research, the different Human Errors made by crew members are cataloged in 10 different groups. After a complete analysis of all the reports, the statistical analysis on the Human Errors typology in marine accidents is presented in order to use it as a tool to avoid the same errors in the future.

Keywords: human error, marine accidents, ship crew, USA

Procedia PDF Downloads 418

Authors: Shamini Dhana, G. Subrahmanya VRK Rao

Abstract:

The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

Procedia PDF Downloads 64

Authors: Praveen Kumar, R. Uma, R. P. Sharma

Abstract:

This study investigates the generation of turbulence in a deep-fluid environment using a damped 1D-modified nonlinear Schrödinger equation model. The well-known damped modified nonlinear Schrödinger equation (d-MNLS) is solved using numerical methods. Artificial damping is added to the MNLS equation, and turbulence generation is investigated through a numerical simulation. The numerical simulation employs a finite difference method for temporal evolution and a pseudo-spectral approach to characterize spatial patterns. The results reveal a recurring periodic pattern in both space and time when the nonlinear Schrödinger equation is considered. Additionally, the study shows that the modified nonlinear Schrödinger equation disrupts the localization of structure and the recurrence of the Fermi-Pasta-Ulam (FPU) phenomenon. The energy spectrum exhibits a power-law behavior, closely following Kolmogorov's spectra steeper than k⁻⁵/³ in the inertial sub-range.

Keywords: water waves, modulation instability, hydrodynamics, nonlinear Schrödinger's equation

Procedia PDF Downloads 72

Authors: Zhengrong Wu, Haibo Yang

Abstract:

In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

Procedia PDF Downloads 56

Authors: Ezra Yehuwalashet, Alireza Malehmir

Abstract:

Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

Procedia PDF Downloads 65

Authors: Brahim El Fadil

Abstract:

The nature of science as a solution (NOS) to life problems is well established in school activities the world over. However, this study reveals the lack of representation of the NOS in science textbooks used in Quebec Province. A content analysis method was adopted to analyze the NOS in relation to optics knowledge and teaching-learning activities in Grade 9 science and technology textbooks and Grade 11 physics textbooks. The selected textbooks were approved and authorized by the Provincial Ministry of Education. Our analysis points out that most of these editions provided a poor representation of NOS. None of them indicates that scientific knowledge is subject to change, even though the history of optics reveals evolutionary and revolutionary changes. Moreover, the analysis shows that textbooks place little emphasis on the discussion of scientific laws and theories. Few of them argue that scientific inquiries are required to gain a deep understanding of scientific concepts. Moreover, they rarely present empirical evidence to support their arguments.

Keywords: nature of science, history of optics, geometrical theory of optics, wave theory of optics

Procedia PDF Downloads 77

Authors: Shyhrete Morina

Abstract:

This paper deals with morphological features in Mjeda's works. To make such a distinction, these features will be compared to standard Albanian language, considering the linguistic structure in the morphological field, which represent an all-important segment of Albanian language. Therefore, the study will focus mainly on the description and construction of these paradigms, which will give a linguistic insight into the entire work of Mjeda as the author who wrote in the dialect of northwestern Geg. Therefore, we have tried to distinguish different parts of the author's language, as well as the distinctive features or even the similarities of these paradigms that arise in the literary work of Mjeda. By constructing the corpus of this phonetic and grammar segment from the whole of Mjeda's work, we have seen that in these fields has built a variety of grammar structures, which for the history of Albanian are of special importance, that in the full variant of the work, as far as we can investigate, we will point out in all the distinctive features. Therefore, our study aims to highlight the linguistic features, namely the author's deep knowledge toward the language, the authenticity of its use, and its mutual relationship with it.

Keywords: distinctive morpholgy, nouns, adjetives, pronouns, Albanian standard language

Procedia PDF Downloads 161

Authors: Wei Xiao, Gangzhi Cai, Xingliang Qin, Hongyan Ren, Zaidong Hua, Zhe Zhu, Hongwei Xiao, Ximin Zheng, Jie Yao, Yanzhen Bi

Abstract:

Myostatin (MSTN) is the master regulator of double muscling phenotype with overgrown muscle and decreased fatness in animals, but its action mode to regulate fat deposition remains to be elucidated. In this study a swin-specific pathway through which MSTN acts to regulate the fat deposition was deciphered. Deep sequenincing of the mRNA and miRNA of fat tissues of MSTN knockout (KO) and wildtype (WT) pigs discovered the positive correlation of myocyte enhancer factor 2C (MEF2C) and fat-inhibiting miR222 expression, and the inverse correlation of miR222 and stearoyl-CoA desaturase 5 (SCD5) expression. SCD5 is rodent-absent and expressed only in pig, sheep and cattle. Fatty acid spectrum of fat tissues revealed a lower percentage of oleoyl-CoA (18:1) and palmitoleyl CoA (16:1) in MSTN KO pigs, which are the catalyzing products of SCD5-mediated desaturation of steroyl CoA (18:0) and palmitoyl CoA (16:0). Blood metrics demonstrated a 45% decline of triglyceride (TG) content in MSTN KO pigs. In light of these observations we hypothesized that MSTN might act through MEF2C/miR222/SCD5 pathway to regulate desaturation of fatty acid as well as triglyceride synthesis in pigs. To this end, real-time PCR and Western blotting were carried out to detect the expression of the three genes stated above. These experiments showed that MEF2C expression was up-regulated by nearly 2-fold, miR222 up-regulated by nearly 3-fold and SCD5 down-regulated by nearly 50% in MSTN KO pigs. These data were consistent with the expression change in deep sequencing analysis. Dual luciferase reporter was then used to confirm the regulation of MEF2C upon the promoter of miR222. Ecotopic expression of MEF2C in preadipocyte cells enhanced miR222 expression by 3.48-fold. CHIP-PCR identified a putative binding site of MEF2C on -2077 to -2066 region of miR222 promoter. Electrophoretic mobility shift assay (EMSA) demonstrated the interaction of MEF2C and miR222 promoter in vitro. These data indicated that MEF2C transcriptionally regulates the expression of miR222. Next, the regulation of miR222 on SCD5 mRNA as well as its physiological consequences were examined. Dual luciferase reporter testing revealed the translational inhibition of miR222 upon the 3´ UTR (untranslated region) of SCD5 in preadipocyte cells. Transfection of miR222 mimics and inhibitors resulted in the down-regulation and up-regulation of SCD5 in preadipocyte cells respectively, consistent with the results from reporter testing. RNA interference of SCD5 in preadipocyte cells caused 26.2% reduction of TG, in agreement with the results of TG content in MSTN KO pigs. In summary, the results above supported the existence of a molecular pathway that MSTN signals through MEF2C/miR222/SCD5 to regulate the fat deposition in pigs. This swine-specific pathway offers potential molecular markers for the development and breeding of a new pig line with optimised fatty acid composition. This would benefit human health by decreasing the takeup of saturated fatty acid.

Keywords: fat deposition, MEF2C, miR222, myostatin, SCD5, pig

Procedia PDF Downloads 129

Authors: Fathi Mohamed Abdrabbo, Khaled Esayed Gaaver, Musab Musa Eldooma

Abstract:

This paper presents an attempt made to investigate the behavior of a single vertical steel hollow pile embedded in sand subjected to compressive inclined load at various inclination angles α through FEM package MIDAS GTS/NX 2019. The effect of the inclination angle and slenderness ratio on the performance of the pile was investigated. Inclined load caring capacity and pile stiffness, as well as lateral deformation profiles along with the pile, were presented. The global, vertical, and horizontal load displacements of pile head, as well as the deformation profiles along the pile and the pile stiffness, are significantly affected by α. It was observed that the P-Y curves of the pile-soil system are independent of α. Also, the slenderness ratios are markedly affecting the behavior of the pile. In addition, there was a noticeable effect of the horizontal load component of the applied load on the vertical behavior of the pile, whereas there was no influence of the presence of vertical load on the horizontal behavior of the pile.

Keywords: deep foundation, piles, inclined load, pile deformations

Procedia PDF Downloads 149

Authors: Sezgi Isik, Yasin Urersoy, Gizem Ustunel, Ilkyaz Yalcin

Abstract:

Improvement of the digital tile application, lots of process revolutions have occurred in the tile production. In order to create unique and inimitable designs, all the competitors start to try different applications. Both Europian and domestic ceramic producers focus on the deep and realistic surfaces. In this study, the trend of engoglaze, which is becoming widespread in glaze porcelain tile designs to create the most intensive colours, were investigated. The aim of the study is to develop engoglaze formulation that supports digital ink activation. Thermal expansion coefficient values were determined by a dilatometer. Chemical analyses and sintering behaviors of engoglazes were made by X-ray diffraction and heat microscopy analysis. According to these glaze formulation studies, it has been reported that using engoglaze could easily reduce the digital ink consumption of the design. On the other hand, the advantage of the production cost is gained, and deepness of the design is provided.

Keywords: ceramic, engoglaze, digital ink activation, glazed porcelain tile

Procedia PDF Downloads 132

Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

Abstract:

As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

Procedia PDF Downloads 291

Authors: Oussama Fertaq

Abstract:

This paper investigates the latest advancements in CO₂ capture and storage (CCS) technologies, which are vital for addressing the growing challenge of climate change. The study focuses on multiple techniques for CO₂ capture, including chemical absorption, membrane separation, and adsorption, analyzing their efficiency, scalability, and environmental impact. The research further explores geological storage options such as deep saline aquifers and depleted oil fields, providing insights into the challenges and opportunities presented by each method. This paper emphasizes the importance of integrating CCS with existing industrial processes to reduce greenhouse gas emissions effectively. It also discusses the economic and policy frameworks required to promote wider adoption of CCS technologies. The findings of this study offer a comprehensive view of the potential of CCS in achieving global climate goals, particularly in hard-to-abate sectors such as energy and manufacturing.

Keywords: CO₂ capture, carbon storage, climate change mitigation, carbon sequestration, environmental sustainability

Procedia PDF Downloads 11

Authors: Sarra Khelifi, Youcef Guerabli, Ahcene Boumaiza

Abstract:

Advances in techniques for measuring individual crystallographic orientations have made it possible to investigate the role of local crystallography during the plastic deformation of materials. In this study, the change in crystallographic orientation distribution during deformation by deep drawing in carbon steel has been investigated in order to understand their role in propagation and arrest of crack. The results show that the change of grain orientation from initial recrystallization texture components of {111}<112> to deformation orientation {111}<110> incites the initiation and propagation of cracks in the region of {111}<112> small grains. Moreover, the misorientation profile and local orientation are analyzed in detail to discuss the change from {111}<112> to {111}<110>. The deformation of the grain with {111}<110> orientation is discussed in terms of stops of the crack in carbon steel during drawing. The SEM-EBSD technique was used to reveal the change of orientation; XRD was performed for the characterization of the global evolution of texture for deformed samples.

Keywords: fracture, heterogeneity, misorientation profile, stored energy

Procedia PDF Downloads 198

Authors: Zoe Polk

Abstract:

In cities across the US, race continues to predict an individual’s likelihood to be employed, to receive a quality education, to live in a safe neighborhood, to life expectancy to contacts with the criminal justice system. Deep and pervasive disparities exist despite laws enacted at the federal, state and local level to eliminate discrimination. This paper examines the strengths of the U.S. civil rights movement in making discrimination a moral issue. Following the passage of the 1964 Civil Rights Act, cities throughout the US adopted laws that mirror the language, theories of practice and enforcement of the law. This paper argues that while those laws were relevant to the way discrimination was conducted in that time, they are limited in their ability to help cities address discrimination today. This paper reviews health indicators This paper concludes that in order for cities to create environments where race no longer predicts one’s success, cities must conduct institutional and structural racism audits.

Keywords: racism, racial equity, constitutional law, social justice

Procedia PDF Downloads 368

Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

Abstract:

Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

Procedia PDF Downloads 442

Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

Abstract:

This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

Procedia PDF Downloads 104

Authors: Vasudev Das

Abstract:

The specific problem is that many leaders of the 21st century do not understand that the extermination of embryos wreaks havoc on peace leadership. The purpose of the document review is to understand embryology in facilitating peace leadership. Extermination of human embryos generates a requital wave of violence which later falls on human society in the form of disturbances, considering that violence breeds further violence as a consequentiality. The study results reveal that a deep understanding of embryology facilitates peace leadership, given that minimizing embryo extermination enhances non-violence in the global village. Neo-Newtonians subscribe to the idea that every action has an equal and opposite reaction. The US Federal Government recognizes the embryo or fetus as a member of Homo sapiens. The social change implications of this study are that understanding human embryology promotes peace leadership, considering that the consequentiality of embryo extermination can serve as a deterrent for violence on embryos.

Keywords: consequentiality, Homo sapiens, neo-Newtonians, violence

Procedia PDF Downloads 136

Authors: Shao-Di Feng, Von-Wun Soo

Abstract:

To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

Procedia PDF Downloads 89

Authors: Mputu Ngandu Simon

Abstract:

Culture and religion are two of the most significant markers of an individual or group's identity. Religion finds its expression in a given culture, and culture is the costume in which a religion is dressed. In other words, there is a crucial relationship between religion and culture which should not be ignored. On the one hand, religion influences the way in which a culture is consumed. A person's consumption of a certain cultural practice is influenced by his/her religious identity. On the other hand, cultural identity plays an important role in how a religion is practiced by its adherents. Some cultural practices become more credible when interpreted in religious terms just as religious doctrines and dogmas need cultural interpretation to be understood by a given people in a given context. This relationship goes so deep that sometimes the boundaries between culture and religion become blurred, and people end up mixing religion and culture. In some cases, the two are considered to be one and the same thing. However, despite this apparent sameness, religion and culture are two distinct aspects of identity, and they should always be considered as such. One results from knowledge, while the other has beliefs as its foundation. This essay explores the difference between cultural and religious identity by drawing from existing literature on this topic as a whole before applying that knowledge to two specific case studies: Christianity and Islam in some African and Asian countries.

Keywords: culture, religion, identity, knowledge, belief

Procedia PDF Downloads 192

Authors: David Loh, Wan Chee Wai, Pei Nan, Chen Zhe

Abstract:

To increase the conveyance capacity to Western Singapore and to meet Singapore’s long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of two 2200 mm diameter water pipes and two 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the west region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected to lay the proposed 1.6km-long pipelines that cross a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examined the difficulties such as (1) construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater; (2) manpower and supply disruptions caused by the COVID-19 pandemic situation.

Keywords: underwater tunnel, subsea engineering, subsea tunnel construction, waterpipe construction

Procedia PDF Downloads 27

Authors: Abraham Kuruvilla

Abstract:

Since the inception of Christianity, one of the most important precepts has been that of the ‘word becoming flesh.’ Incarnation, as we understand it, is that the ‘word became flesh.’ As we know, it is a commonly held understanding that the concept of Logos was borrowed from the Greek religion. Such understanding has dominated our thought process. This is problematic as it does not draw out the deep roots of Logos. The understanding of Logos also existed in religion such as Hinduism. For the Hindu faith, the understanding of Shabd is pivotal. It could be arguably equated with the understanding of the Logos. The paper looks into the connection of the primal Christian doctrine of the Logos with that of the Hindu understanding of Shabd. The methodology of the paper would be a comparative theological analysis with the New Testament understanding of the Logos with that of the understanding of Shabd as perceived in the different Vedas of the Hindu faith. The paper would come to the conclusion that there is a conceptual connectivity between Logos and the Shabd. As such the understanding of Logos cannot just be attributed to the Greek understanding of Logos, but rather it predates the Greek understanding of Logos by being connected to the Hindu understanding of Shabd. Accordingly, such comparison brings out the implication for a constructive dialogue between Christianity and the Hindu faith.

Keywords: Christianity, Hinudism, Logos, Shabd

Procedia PDF Downloads 224

Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

Abstract:

Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

Procedia PDF Downloads 72

Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

Abstract:

Non-stationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables interactions.

Keywords: cardiac diseases, complex systems theory, ECG analysis, matrix analysis

Procedia PDF Downloads 344

Authors: Habab Ahmed Hassan Abuzeid

Abstract:

Organizations are social systems. If one wishes to work in them or to manage them, it is necessary to understand how they operate. Organizations combine science and people–technology and humanity. Unless we have qualified people to design and implement, techniques alone will not produce desirable results. Human behavior in organizations is rather unpredictable. It is unpredictable because it arises from people’s deep-seated needs and value systems. However, it can be partially understood in terms of the framework of behavioral science, management and other disciplines. There is no idealistic solution to organizational problems. All that can be done is to increase our understanding and skills so that human relations at work can be enhanced. In this paper, we consider management of organization behavior utilizing human resources. Study the elements of organization behavior, the effectiveness of mechanism to enhance staff relationships. Many approaches could be applied for healthy organizational environment, it’s highlighted more details in this paper. Organization behavior can raise the employees’ engagement, loyalty and commitment; to accomplish the goal.

Keywords: environment, engagement, human resources, organization behavior

Procedia PDF Downloads 364

Authors: Abdelkader Soumaya, Aymen Arfaoui, Noureddine Ben Ayed, Ali Kadri

Abstract:

The Chotts belt represents the southernmost folded structure in the Tunisian Atlas domain. It is dominated by inherited deep extensional E-W trending fault zones, which are reactivated as strike-slip faults during the Cenozoic compression. By examining the geological maps at different scales and based on the fieldwork data, we propose new structural interpretations for the geometries and fault kinematics in the Chotts chain. A set of ENE-WSW right-lateral en echelon folds, with curved shapes and steeply inclined southern limbs, is visible in the map view of this belt. These asymmetric tight anticlines are affected by E-W trending fault segments linked by local bends and stepovers. The revealed kinematic indicators along one of these E-W striated faults (Tafferna segment), such as breccias and gently inclined slickenlines (N094, 80N, 15°W pitch angles), show direct evidence of dextral strike-slip movement. The calculated stress tensors from corresponding faults slip data reveal an overall strike-slip tectonic regime with reverse component and NW-trending sub-horizontal σ1 axis ranking between N130 to N150. From west to east, we distinguished several types of structures along the segmented dextral fault system of the Chotts Range. The NE-SW striking fold-thrust belt (~25 km-long) between two continuously linked E-W fault segments (NW of Tozeur town) has been suggested as a local restraining bend. The central part of the Chotts chain is occupied by the ENE-striking Ksar Asker anticlines (Taferna, Torrich, and Sif Laham), which are truncated by a set of E-W strike-slip fault segments. Further east, the fault segments of Hachichina and Sif Laham connected across the NW-verging asymmetric fold-thrust system of Bir Oum Ali, which can be interpreted as a left-stepping contractional bend (~20 km-long). The oriental part of the Chotts belt corresponds to an array of subparallel E-W oriented fault segments (i.e., Beidha, Bouloufa, El Haidoudi-Zemlet El Beidha) with similar lengths (around 10 km). Each of these individual separated segments is associated with curved ENE-trending en echelon right-stepping anticlines. These folds are affected by a set of conjugate R and R′ shear-type faults indicating a dextral strike-lip motion. In addition, the relay zones between these E-W overstepping fault segments define local releasing stepovers dominated by NW-SE subsidiary faults. Finally, the Chotts chain provides well-exposed examples of strike-slip tectonics along E-W distributed fault segments. Each fault zone shows a typical strike-slip architecture, including parallel fault segments connecting via local stepovers or bends. Our new structural interpretations for this region reveal a great influence of the E-W deep fault segments on regional tectonic deformations and stress field during the Cenozoic shortening.

Keywords: chotts belt, tunisian atlas, strike-slip fault, stepovers, fault segments

Procedia PDF Downloads 69

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 77