Search results for: deep cold rolling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2993

Search results for: deep cold rolling

1103 Optimization of Process Parameters Affecting on Spring-Back in V-Bending Process for High Strength Low Alloy Steel HSLA 420 Using FEA (HyperForm) and Taguchi Technique

Authors: Navajyoti Panda, R. S. Pawar

Abstract:

In this study, process parameters like punch angle, die opening, grain direction, and pre-bend condition of the strip for deep draw of high strength low alloy steel HSLA 420 are investigated. The finite element method (FEM) in association with the Taguchi and the analysis of variance (ANOVA) techniques are carried out to investigate the degree of importance of process parameters in V-bending process for HSLA 420&ST12 grade material. From results, it is observed that punch angle had a major influence on the spring-back. Die opening also showed very significant role on spring back. On the other hand, it is revealed that grain direction had the least impact on spring back; however, if strip from flat sheet is taken, then it is less prone to spring back as compared to the strip from sheet metal coil. HyperForm software is used for FEM simulation and experiments are designed using Taguchi method. Percentage contribution of the parameters is obtained through the ANOVA techniques.

Keywords: bending, spring-back, v-bending, FEM, Taguchi, HSLA 420 and St12 materials, HyperForm, profile projector

Procedia PDF Downloads 177
1102 Text2Time: Transformer-Based Article Time Period Prediction

Authors: Karthick Prasad Gunasekaran, B. Chase Babrich, Saurabh Shirodkar, Hee Hwang

Abstract:

Construction preparation is crucial for the success of a construction project. By involving project participants early in the construction phase, project managers can plan ahead and resolve issues early, resulting in project success and satisfaction. This study uses quantitative data from construction management projects to determine the relationship between the pre-construction phase, construction schedule, and customer satisfaction. This study examined a total of 65 construction projects and 93 clients per job to (a) identify the relationship between the pre-construction phase and program reduction and (b) the pre-construction phase and customer retention. Based on a quantitative analysis, this study found a negative correlation between pre-construction status and project schedule in 65 construction projects. This finding means that the more preparatory work done on a particular project, the shorter the total construction time. The Net Promoter Score of 93 clients from 65 projects was then used to determine the relationship between construction preparation and client satisfaction. The pre-construction status and the projects were further analyzed, and a positive correlation between them was found. This shows that customers are happier with projects with a higher ready-to-build ratio than projects with less ready-to-build.

Keywords: NLP, BERT, LLM, deep learning, classification

Procedia PDF Downloads 87
1101 Phenomenological Analysis on the Experience of Volunteer Activities in Pre-Medical School Students

Authors: S. J. Yune, K. H. Park

Abstract:

The purpose of this study was to understand the experiences of medical students in volunteer activities and to draw implications for medical education. For this purpose, the questionnaire and the reflection essay on the volunteer experience of 54 students in the first year and 57 students in the second year were analyzed and analyzed. As a result, the participation of the students in the volunteer activities was the highest in the first semester and once a month in the second grade. Activities were mostly through volunteer organizations. The essence of the volunteering activities experience revealed through reflection essays was 'I want to avoid with fear' and 'I feel far away' in the recognition before volunteering activities. In terms of knowledge after participating in volunteer activities, 'breaking eggs and getting to know the world' and 'intellectual growth through social experience' appeared. In terms of attitude, it revealed 'deep reflection on me and others', 'understanding of service life'. And in terms of behavior, 'Begin preparing for a life of service' appeared. The results of this study revealed that volunteering activities provide students with opportunities for growth and development. In order to obtain more meaningful results, consciousness education related to social service should be done in advance.

Keywords: volunteering activity, pre-medical school student, reflection essay, qualitative analysis

Procedia PDF Downloads 175
1100 Field Study on Thermal Performance of a Green Office in Bangkok, Thailand: A Possibility of Increasing Temperature Set-Points

Authors: T. Sikram, M. Ichinose, R. Sasaki

Abstract:

In the tropics, indoor thermal environment is usually provided by a cooling mode to maintain comfort all year. Indoor thermal environment performance is sometimes different from the standard or from the first design process because of operation, maintenance, and utilization. The field study of thermal environment in the green building is still limited in this region, while the green building continues to increase. This study aims to clarify thermal performance and subjective perception in the green building by testing the temperature set-points. A Thai green office was investigated twice in October 2018 and in May 2019. Indoor environment variables (temperature, relative humidity, and wind velocity) were collected continuously. The temperature set-point was normally set as 23 °C, and it was changed into 24 °C and 25 °C. The study found that this gap of temperature set-point produced average room temperature from 22.7 to 24.6 °C and average relative humidity from 55% to 62%. Thermal environments slight shifted out of the ASHRAE comfort zone when the set-point was increased. Based on the thermal sensation vote, the feeling-colder vote decreased by 30% and 18% when changing +1 °C and +2 °C, respectively. Predicted mean vote (PMV) shows that most of the calculated median values were negative. The values went close to the optimal neutral value (0) when the set-point was set at 25 °C. The neutral temperature was slightly decreased when changing warmer temperature set-points. Building-related symptom reports were found in this study that the number of votes reduced continuously when the temperature was warmer. The symptoms that occurred by a cooler condition had the number of votes more than ones that occurred by a warmer condition. In sum, for this green office, there is a possibility to adjust a higher temperature set-point to +1 °C (24 °C) in terms of reducing cold sensitivity, discomfort, and symptoms. All results could support the policy of changing a warmer temperature of this office to become “a better green building”.

Keywords: thermal environment, green office, temperature set-point, comfort

Procedia PDF Downloads 110
1099 Managing Children with Autism Spectrum Disorder in Corona Age

Authors: Raju Singh, Shikha Singh

Abstract:

This article is note for managing Autistic Child during the Corona time line. It becomes very critical for the primary caregiver as corona pandemic poses new challenges and completely variety of threats to line of treatment, growth, socialization, mental health for children with autism spectrum disorder (ASD), and, so for the family of the children. It is a highly distressful situation, where the line of treatment has shrunken, physical contact has reduced and therapies footprints reduced in several parts of the world. As children with ASD already face socialization challenges, isolation rules imposed by individuals (or social groups), government agencies have only made the situation worse for the children with ASD and their family. This note will try to touch the basics on understanding the ASD and related development disorders, challenges, impact, and suggest approaches to deal with such situation. This document also covers data analysis, deep dive into the increasing impact of ASD on children. This document can also act as a baseline for many researchers, psychiatrists, psychologists, therapists to view the problem statement and measure its impact.

Keywords: autism spectrum disorder, mental health, applied behavior therapy, occupational therapy, social anxiety

Procedia PDF Downloads 136
1098 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 224
1097 Green Delivery Systems for Fruit Polyphenols

Authors: Boris M. Popović, Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović

Abstract:

Green solvents are environmentally friendly and greatly improve the sustainability of chemical processes. There is a growing interest in the green extraction of polyphenols from fruits. In this study, we consider three Natural Deep Eutectic Solvents (NADES) systems based on choline chloride as a hydrogen bond acceptor and malic acid, urea, and fructose as hydrogen bond donors. NADES systems were prepared by heating and stirring, ultrasound, and microwave (MW) methods. Sour cherry pomace was used as a natural source of polyphenols. Polyphenol extraction from cherry pomace was performed by ultrasound-assisted extraction and microwave-assisted extraction and compared with conventional heat and stirring method extraction. It was found that MW-assisted preparation of NADES was the fastest, requiring less than 30 s. Also, MW extraction of polyphenols was the most rapid, with less than 5 min necessary for the extract preparation. All three NADES systems were highly efficient for anthocyanin extraction, but the most efficient was the system with malic acid as a hydrogen bond donor (yield of anthocyanin content was enhanced by 62.33% after MW extraction with NADES compared with the conventional solvent).

Keywords: anthocyanins, green extraction, NADES, polyphenols

Procedia PDF Downloads 82
1096 Humeral Head and Scapula Detection in Proton Density Weighted Magnetic Resonance Images Using YOLOv8

Authors: Aysun Sezer

Abstract:

Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

Procedia PDF Downloads 54
1095 Exploring Perceptions of Local Stakeholders in Climate Change Adaptation in Central and Western Terai, Nepal

Authors: Shree Kumar Maharjan

Abstract:

Climate change has varied impacts on diverse livelihood sectors, which is more prominent at the community level. The stakeholders and local institutions have been supporting the communities either by building adaptive capacities and resilience or minimizing the impacts of different adaptation interventions. Some of these interventions are effective, whereas others need further dynamisms and exertions considering the complexity of the risks and vulnerabilities. Hence, consolidated efforts of concerned stakeholders are required to minimize and adapt the present and future impacts. This study digs out and analyses the perceptions of local stakeholders in climate change adaptation in Madi and Deukhuri valleys of Nepal through a questionnaire survey. The study has categorized the local stakeholders into 5 groups in the study sites – Farmers groups and cooperatives, Government, I/NGOs, Development banks and education and other organizations. The local stakeholders revealed flood, drought, cold wave and riverbank erosion as the major climatic risks and hazards found in the sites eventually impacting on the loss of agricultural production, loss of agricultural land and properties, loss of livestock, the emergence of diseases and pest. The stakeholders believed that most of the farmers dealing with these impacts based on their traditional knowledge and practices, followed by with the support of NGOs and with the help of neighbors and community. The major supports of the stakeholders to deal with these impacts were on training and awareness, risk analysis and minimization, livelihood improvement, financial support, coordination and networking and facilitation in policy formulation. The stakeholders emphasized primarily on capacity building, appropriate technologies, community-based planning and monitoring, prioritization to the poor and the marginalized and establishment of community fund respectively for building adaptive capacities.

Keywords: climate change adaptation, local stakeholders, Madi, Deukhuri, Nepal

Procedia PDF Downloads 173
1094 Localized Dynamic Lensing with Extended Depth of Field via Enhanced Light Sound Interaction

Authors: Hamid R. Chabok, Demetrios N. Christodoulides, Mercedeh Khajavikhan

Abstract:

In recent years, acousto-optic (AO) lenses with tunable foci have emerged as a powerful tool for optical beam shaping, imaging, and particle manipulation. In most current AO lenses, the incident light that propagates orthogonally to a standing ultrasonic wave converts to a Bessel-like beam pattern due to the Raman-Nath effect, thus forming annular fringes that result in compromised focus response. Here, we report a new class of AO dynamic lensing based on generating a 3D-variable refractive index profile via a z-axis-scan ultrasound transducer. By utilizing the co- /counter propagation of light and acoustic waves that interact over a longer distance, the laser beam can be strongly focused in a fully controllable manner. Using this approach, we demonstrate AO lenses with instantaneous extended depth of field (DoF) and laterally localized dynamic focusing. This new light-sound interaction scheme may pave the way towards applications that require remote focusing, 3D micromanipulation, and deep tissue therapy/imaging.

Keywords: acousto-optic, optical beam shaping, dynamic lensing, ultrasound

Procedia PDF Downloads 84
1093 The Integrated Urban Strategies Based on Deep Urban History and Modern Technology Study: Tourism and Leisure Industries as Driving Force to Reactivate Historical Area

Authors: Cheng Li, Jie Shen, Yutian Tang

Abstract:

Embracing the upcoming era of urbanization with the challenges of limitation of resources, disappearing cultural identities and conflicts among different groups of stakeholders, new integrated approaches are offered in our urban practice to help decision-makers and stakeholders frame and develop well-conceived, practical strategies for urban developing trajectories to approach urban-level sustainability in multiple social, cultural, ecological dimensions. Through bottom-up participation, we take advantage of tourism and leisure industries as driving forces for urbanization in China to promote integrated sustainable systems, with the hope of approaching both historical and ecological aspects of urban sustainability; and also thanks to top-down participation, we have codes, standards and rules established by the governments to strengthen the implementation of ecological urban sustainability. The results are monitored and evaluated experimentally and multidimensionally and the sustainable systems we constructed with local stakeholder groups turned out to be effective. The presentation of our selected projects would indicate our different focuses on urban sustainability.

Keywords: urban sustainability, integrated urban strategy, tourism and leisure industries, history, modern technology

Procedia PDF Downloads 370
1092 Ensemble of Deep CNN Architecture for Classifying the Source and Quality of Teff Cereal

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

Procedia PDF Downloads 33
1091 Load Transfer of Steel Pipe Piles in Warming Permafrost

Authors: S. Amirhossein Tabatabaei, Abdulghader A. Aldaeef, Mohammad T. Rayhani

Abstract:

As the permafrost continues to melt in the northern regions due to global warming, a soil-water mixture is left behind with drastically lower strength; a phenomenon that directly impacts the resilience of existing structures and infrastructure systems. The frozen soil-structure interaction, which in ice-poor soils is controlled by both interface shear and ice-bonding, changes its nature into a sole frictional state. Adfreeze, the controlling mechanism in frozen soil-structure interaction, diminishes as the ground temperature approaches zero. The main purpose of this paper is to capture the altered behaviour of frozen interface with respect to rising temperature, especially near melting states. A series of pull-out tests are conducted on model piles inside a cold room to study how the strength parameters are influenced by the phase change in ice-poor soils. Steel model piles, embedded in artificially frozen cohesionless soil, are subjected to both sustained pull-out forces and constant rates of displacement to observe the creep behaviour and acquire load-deformation curves, respectively. Temperature, as the main variable of interest, is increased from a lower limit of -10°C up to the point of melting. During different stages of the temperature rise, both skin deformations and temperatures are recorded at various depths along the pile shaft. Significant reduction of pullout capacity and accelerated creep behaviour is found to be the primary consequences of rising temperature. By investigating the different pull-out capacities and deformations measured during step-wise temperature change, characteristics of the transition from frozen to unfrozen soil-structure interaction are studied.

Keywords: Adfreeze, frozen soil-structure interface, ice-poor soils, pull-out capacity, warming permafrost

Procedia PDF Downloads 102
1090 Application of Artificial Neural Network for Single Horizontal Bare Tube and Bare Tube Bundles (Staggered) of Large Particles: Heat Transfer Prediction

Authors: G. Ravindranath, S. Savitha

Abstract:

This paper presents heat transfer analysis of single horizontal bare tube and heat transfer analysis of staggered arrangement of bare tube bundles bare tube bundles in gas-solid (air-solid) fluidized bed and predictions are done by using Artificial Neural Network (ANN) based on experimental data. Fluidized bed provide nearly isothermal environment with high heat transfer rate to submerged objects i.e. due to through mixing and large contact area between the gas and the particle, a fully fluidized bed has little temperature variation and gas leaves at a temperature which is close to that of the bed. Measurement of average heat transfer coefficient was made by local thermal simulation technique in a cold bubbling air-fluidized bed of size 0.305 m. x 0.305 m. Studies were conducted for single horizontal Bare Tube of length 305mm and 28.6mm outer diameter and for bare tube bundles of staggered arrangement using beds of large (average particle diameter greater than 1 mm) particle (raagi and mustard). Within the range of experimental conditions influence of bed particle diameter ( Dp), Fluidizing Velocity (U) were studied, which are significant parameters affecting heat transfer. Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, and non-linearity. Here, feed-forward architecture and trained by back-propagation technique is adopted to predict heat transfer analysis found from experimental results. The ANN is designed to suit the present system which has 3 inputs and 2 out puts. The network predictions are found to be in very good agreement with the experimental observed values of bare heat transfer coefficient (hb) and nusselt number of bare tube (Nub).

Keywords: fluidized bed, large particles, particle diameter, ANN

Procedia PDF Downloads 354
1089 Efficacy of Plant Extracts on Insect Pests of Watermelon and Their Effects on Nutritional Contents of the Fruits

Authors: Fatai Olaitan Alao, Thimoty Abiodun Adebayo, Oladele Abiodun Olaniran

Abstract:

This experiment was conducted at Ladoke Akintola University of Technology, Ogbomoso, Teaching and Research farm during the major and minor planting season , 2017 to determine the effects of Annona squamosa (Linn.) and Moringa oleifera (Lam) extracts on insect pests of watermelon and their effects on nutritional contents of watermelon fruits. Synthetic insecticide and untreated plots were included in the treatments for comparison. Selected plants were prepared with cold water and each plant extracts was applied at three different concentrations (5,10 and 20% v/v). Data were collected on population density of insect pests, number of aborted fruits, number of defoliated flowers , the yield was calculated in t/ha, nutritional and fatty acid contents were determine using gas chromatography. The results show that the two major insects were observed - Diabrotica undicimpunctata and Dacus cucurbitea. The tested plant extracts had about 65% control of the observed insect pests when compared with the control and the two plant extracts had the same insecticidal efficacy. However, the applied plant extracts at 20% v/v had higher insecticidal effects than the other tested concentrations. Significant higher yield was observed on the plant extracts treated plants compared with untreated plants which had the least yield() but none of the plant extracts performed effectively as Lambdachyalothrin in the control of insect pests and yield. Meanwhile, the tested plant extracts significantly improved the proximate and fatty acid contents of watermelon fruits while Lambdachyalothrin contributed negatively to the nutritional contents of watermelon fruits. Therefore, A. squpmosa and M. oleifera can be used in the management of insect pests and to improve the nutritional contents of the watermelon especially in the organic farming system.

Keywords: Annona squamosa, Dacus cucubitea, Diabrotical undicimpunctata, Moringa oleifera, watermelon

Procedia PDF Downloads 117
1088 Ways to Prevent Increased Wear of the Drive Box Parts and the Central Drive of the Civil Aviation Turbo Engine Based on Tribology

Authors: Liudmila Shabalinskaya, Victor Golovanov, Liudmila Milinis, Sergey Loponos, Alexander Maslov, D. O. Frolov

Abstract:

The work is devoted to the rapid laboratory diagnosis of the condition of aircraft friction units, based on the application of the nondestructive testing method by analyzing the parameters of wear particles, or tribodiagnostics. The most important task of tribodiagnostics is to develop recommendations for the selection of more advanced designs, materials and lubricants based on data on wear processes for increasing the life and ensuring the safety of the operation of machines and mechanisms. The object of tribodiagnostics in this work are the tooth gears of the central drive and the gearboxes of the gas turbine engine of the civil aviation PS-90A type, in which rolling friction and sliding friction with slip occur. The main criterion for evaluating the technical state of lubricated friction units of a gas turbine engine is the intensity and rate of wear of the friction surfaces of the friction unit parts. When the engine is running, oil samples are taken and the state of the friction surfaces is evaluated according to the parameters of the wear particles contained in the oil sample, which carry important and detailed information about the wear processes in the engine transmission units. The parameters carrying this information include the concentration of wear particles and metals in the oil, the dispersion composition, the shape, the size ratio and the number of particles, the state of their surfaces, the presence in the oil of various mechanical impurities of non-metallic origin. Such a morphological analysis of wear particles has been introduced into the order of monitoring the status and diagnostics of various aircraft engines, including a gas turbine engine, since the type of wear characteristic of the central drive and the drive box is surface fatigue wear and the beginning of its development, accompanied by the formation of microcracks, leads to the formation of spherical, up to 10 μm in size, and in the aftermath of flocculent particles measuring 20-200 μm in size. Tribodiagnostics using the morphological analysis of wear particles includes the following techniques: ferrography, filtering, and computer analysis of the classification and counting of wear particles. Based on the analysis of several series of oil samples taken from the drive box of the engine during their operating time, a study was carried out of the processes of wear kinetics. Based on the results of the study and comparing the series of criteria for tribodiagnostics, wear state ratings and statistics of the results of morphological analysis, norms for the normal operating regime were developed. The study allowed to develop levels of wear state for friction surfaces of gearing and a 10-point rating system for estimating the likelihood of the occurrence of an increased wear mode and, accordingly, prevention of engine failures in flight.

Keywords: aviation, box of drives, morphological analysis, tribodiagnostics, tribology, ferrography, filtering, wear particle

Procedia PDF Downloads 250
1087 Operator Optimization Based on Hardware Architecture Alignment Requirements

Authors: Qingqing Gai, Junxing Shen, Yu Luo

Abstract:

Due to the hardware architecture characteristics, some operators tend to acquire better performance if the input/output tensor dimensions are aligned to a certain minimum granularity, such as convolution and deconvolution commonly used in deep learning. Furthermore, if the requirements are not met, the general strategy is to pad with 0 to satisfy the requirements, potentially leading to the under-utilization of the hardware resources. Therefore, for the convolution and deconvolution whose input and output channels do not meet the minimum granularity alignment, we propose to transfer the W-dimensional data to the C-dimension for computation (W2C) to enable the C-dimension to meet the hardware requirements. This scheme also reduces the number of computations in the W-dimension. Although this scheme substantially increases computation, the operator’s speed can improve significantly. It achieves remarkable speedups on multiple hardware accelerators, including Nvidia Tensor cores, Qualcomm digital signal processors (DSPs), and Huawei neural processing units (NPUs). All you need to do is modify the network structure and rearrange the operator weights offline without retraining. At the same time, for some operators, such as the Reducemax, we observe that transferring the Cdimensional data to the W-dimension(C2W) and replacing the Reducemax with the Maxpool can accomplish acceleration under certain circumstances.

Keywords: convolution, deconvolution, W2C, C2W, alignment, hardware accelerator

Procedia PDF Downloads 92
1086 Domain Adaptation Save Lives - Drowning Detection in Swimming Pool Scene Based on YOLOV8 Improved by Gaussian Poisson Generative Adversarial Network Augmentation

Authors: Simiao Ren, En Wei

Abstract:

Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

Procedia PDF Downloads 79
1085 Italian Speech Vowels Landmark Detection through the Legacy Tool 'xkl' with Integration of Combined CNNs and RNNs

Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

Abstract:

This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

Procedia PDF Downloads 45
1084 Numerical Study for the Estimation of Hydrodynamic Current Drag Coefficients for the Colombian Navy Frigates Using Computational Fluid Dynamics

Authors: Mauricio Gracia, Luis Leal, Bharat Verma

Abstract:

Computational fluid dynamics (CFD) has become nowadays an important tool in the process of hydrodynamic design of modern ships. CFD is used to model any phenomena related to fluid flow in a control volume like a ship or any offshore structure in the sea. In the present study, the current force drag coefficients for a Colombian Navy Frigate in deep and shallow water are estimated through the application of CFD. The study shows the process of simulating the ship current drag coefficients using the CFD simulations method, which is conducted using STAR-CCM+ software package. The Almirante Padilla class Frigate ship scale model is investigated. The results show the ship current drag coefficient calculated considering a current speed of 1 knot with a 90° drift angle for the full-scale ship. Predicted results were compared against the current drag coefficients published in the Lloyds register OCIMF report. It is shown that the simulation results agree fairly well with the published results and that STAR-CCM+ code can predict current drag coefficients.

Keywords: CFD, current draft coefficient, STAR-CCM+, OCIMF, Bollard pull

Procedia PDF Downloads 150
1083 Technological Developments to Reduce Wind Blade Turbine Levelized Cost of Energy

Authors: Pedro Miguel Cardoso Carneiro, Ricardo André Nunes Borges, João Pedro Soares Loureiro, Hermínio Maio Graça Fernandes

Abstract:

Wind energy has been exponentially growing over the last years and will allow countries to progress regarding the decarbonization objective. In parallel, the maintenance activities have also been increasing in consequence of ageing and deterioration of the wind farms. The time available for wind blade maintenance is given by the weather window that is based upon weather conditions. Most of the wind blade repair and maintenance activities require a narrow window of temperature and humidity. Due to this limitation, the current weather windows result only on approximately 35% days/year are used for maintenance, that takes place mostly during summertime. This limitation creates large economic losses in the energy production of the wind towers, since they can be inoperative or with the energy production output reduced for days or weeks due to existing damages. Another important aspect is that the maintenance costs are higher due to the high standby time and seasonality imposed on the technicians. To reduce the relevant maintenance costs of blades and energy loses some technological developments were carried out to significantly improve this reality. The focus of this activity was to develop a series of key developments to have in the near future a suspended access equipment that can operate in harsh conditions, wind rain, cold/hot environment. To this end we have identified key areas that need to be revised and require new solutions to be found; a habitat system, multi-configurable roof and floor, roof and floor interface to blade, secondary attachment solutions to the blade and to the tower. On this paper we will describe the advances produced during a national R&D project made in partnership with an end-user (Onrope) and a test center (ISQ).

Keywords: wind turbine maintenance, cost reduction, technological innovations, wind turbine blade

Procedia PDF Downloads 79
1082 Numerical Study on Jatropha Oil Pool Fire Behavior in a Compartment

Authors: Avinash Chaudhary, Akhilesh Gupta, Surendra Kumar, Ravi Kumar

Abstract:

This paper presents the numerical study on Jatropha oil pool fire in a compartment. A fire experiment with jatropha oil was conducted in a compartment of size 4 m x 4 m x m to study the fire development and temperature distribution. Fuel is burned in the center of the compartment in a pool diameter of 0.5 m with an initial fuel depth of 0.045 m. Corner temperature in the compartment, doorway temperature and hot gas layer temperature at various locations are measured. Numerical simulations were carried out using Fire Dynamics Simulator (FDS) software at grid size of 0.05 m, 0.12 m and for performing simulation heat release rate of jatropha oil measured using mass loss method were inputted into FDS. Experimental results shows that like other fuel fires, the whole combustion process can be divided into four stages: initial stage, growth stage, steady profile or developed phase and decay stage. The fire behavior shows two zone profile where upper zone consists of mainly hot gases while lower zone is relatively at colder side. In this study, predicted temperatures from simulation are in good agreement in upper zone of compartment. Near the interface of hot and cold zone, deviations were reported between the simulated and experimental results which is probably due to the difference between the predictions of smoke layer height by FDS. Also, changing the grid size from 0.12 m to 0.05 m does not show any effect in temperatures at upper zone while in lower zone, grid size of 0.05 m showed satisfactory agreement with experimental results. Numerical results showed that calculated temperatures at various locations matched well with the experimental results. On the whole, an effective method is provided with reasonable results to study the burning characteristics of jatropha oil with numerical simulations.

Keywords: jatropha oil, compartment fire, heat release rate, FDS (fire dynamics simulator), numerical simulation

Procedia PDF Downloads 244
1081 Relationship of Indoor and Outdoor Levels of Black Carbon in an Urban Environment

Authors: Daria Pashneva, Julija Pauraite, Agne Minderyte, Vadimas Dudoitis, Lina Davuliene, Kristina Plauskaite, Inga Garbariene, Steigvile Bycenkiene

Abstract:

Black carbon (BC) has received particular attention around the world, not only for its impact on regional and global climate change but also for its impact on air quality and public health. In order to study the relationship between indoor and outdoor BC concentrations, studies were carried out in Vilnius, Lithuania. The studies are aimed at determining the relationship of concentrations, identifying dependencies during the day and week with a further opportunity to analyze the key factors affecting the indoor concentration of BC. In this context, indoor and outdoor continuous real-time measurements of optical BC-related light absorption by aerosol particles were carried out during the cold season (from October to December 2020). The measurement venue was an office located in an urban background environment. Equivalent black carbon (eBC) mass concentration was measured by an Aethalometer (Magee Scientific, model AE-31). The optical transmission of carbonaceous aerosol particles was measured sequentially at seven wavelengths (λ= 370, 470, 520, 590, 660, 880, and 950 nm), where the eBC mass concentration was derived from the light absorption coefficient (σab) at 880 nm wavelength. The diurnal indoor eBC mass concentration was found to vary in the range from 0.02 to 0.08 µgm⁻³, while the outdoor eBC mass concentration - from 0.34 to 0.99 µgm⁻³. Diurnal variations of eBC mass concentration outdoor vs. indoor showed an increased contribution during 10:00 and 12:00 AM (GMT+2), with the highest indoor eBC mass concentration of 0.14µgm⁻³. An indoor/outdoor eBC ratio (I/O) was below one throughout the entire measurement period. The weekend levels of eBC mass concentration were lower than in weekdays for indoor and outdoor for 33% and 28% respectively. Hourly mean mass concentrations of eBC for weekdays and weekends show diurnal cycles, which could be explained by the periodicity of traffic intensity and heating activities. The results show a moderate influence of outdoor eBC emissions on the indoor eBC level.

Keywords: black carbon, climate change, indoor air quality, I/O ratio

Procedia PDF Downloads 185
1080 Comparative Performance and Emission Analysis of Diesel Engine Fueled with Diesel and Bitter Apricot Kernal Oil Biodiesel Blends

Authors: Virender Singh Gurau, Akash Deep, Sarbjot S. Sandhu

Abstract:

Vegetable oils are produced from numerous oil seed crops. While all vegetable oils have high energy content, most require some processing to assure safe use in internal combustion engines. Some of these oils already have been evaluated as substitutes for diesel fuels. In the present research work Bitter Apricot kernel oil was employed as a feedstock for the production of biodiesel. The physicochemical properties of the Bitter Apricot kernel oil methyl ester were investigated as per ASTM D6751. From the series of engine testing, it is concluded that the brake thermal efficiency (BTE) with biodiesel blend was little lower than that of diesel. BSEC is slightly higher for Bitter apricot kernel oil methyl ester blends than neat diesel. For biodiesel blends, CO emission was lower than diesel fuel as B 20 reduced CO emissions by 18.75%. Approximately 11% increase in NOx emission was observed with 20% biodiesel blend. It is observed that HC emissions tend to decrease for biodiesel based fuels and Smoke opacity was found lower for biodiesel blends in comparison to diesel fuel.

Keywords: biodiesel, transesterification, bitter apricot kernel oil, performance and emission testing

Procedia PDF Downloads 322
1079 Environmental Assessment of Roll-to-Roll Printed Smart Label

Authors: M. Torres, A. Moulay, M. Zhuldybina, M. Rozel, N. D. Trinh, C. Bois

Abstract:

Printed electronics are a fast-growing market as their applications cover a large range of industrial needs, their production cost is low, and the additive printing techniques consume less materials than subtractive manufacturing methods used in traditional electronics. With the growing demand for printed electronics, there are concerns about their harmful and irreversible contribution to the environment. Indeed, it is estimated that 80% of the environmental load of a product is determined by the choices made at the conception stage. Therefore, examination through a life cycle approach at the developing stage of a novel product is the best way to identify potential environmental issues and make proactive decisions. Life cycle analysis (LCA) is a comprehensive scientific method to assess the environmental impacts of a product in its different stages of life: extraction of raw materials, manufacture and distribution, use, and end-of-life. Impacts and major hotspots are identified and evaluated through a broad range of environmental impact categories of the ReCiPe (H) middle point method. At the conception stage, the LCA is a tool that provides an environmental point of view on the choice of materials and processes and weights-in on the balance between performance materials and eco-friendly materials. Using the life cycle approach, the current work aims to provide a cradle-to-grave life cycle assessment of a roll-to-roll hybrid printed smart label designed for the food cold chain. Furthermore, this presentation will present the environmental impact of metallic conductive inks, a comparison with promising conductive polymers, evaluation of energy vs. performance of industrial printing processes, a full assessment of the impact from the smart label applied on a cellulosic-based substrate during the recycling process and the possible recovery of precious metals and rare earth elements.

Keywords: Eco-design, label, life cycle assessment, printed electronics

Procedia PDF Downloads 148
1078 Dissipation of Tebuconazole in Cropland Soils as Affected by Soil Factors

Authors: Bipul Behari Saha, Sunil Kumar Singh, P. Padmaja, Kamlesh Vishwakarma

Abstract:

Dissipation study of tebuconazole in alluvial, black and deep-black clayey soils collected from paddy, mango and peanut cropland of tropical agro-climatic zone of India at three concentration levels were carried out for monitoring the water contamination through persisted residual toxicity. The soil-slurry samples were analyzed by capillary GC-NPD methods followed by ultrasound-assisted extraction (UAE) technique and cleanup process. An excellent linear relationship between peak area and concentration obtained in the range 1 to 50 μgkg-1. The detection (S/N, 3 ± 0.5) and quantification (S/N, 7.5 ± 2.5) limits were 3 and 10 μgkg-1 respectively. Well spiked recoveries were achieved from 96.28 to 99.33 % at levels 5 and 20 μgkg-1 and method precision (% RSD) was ≤ 5%. The soils dissipation of tebuconazole was fitted in first order kinetic-model with half-life between 34.48 to 48.13 days. The soil organic-carbon (SOC) content correlated well with the dissipation rate constants (DRC) of the fungicide Tebuconazole. An increase in the SOC content resulted in faster dissipation. The results indicate that the soil organic carbon and tebuconazole concentrations plays dominant role in dissipation processes. The initial concentration illustrated that the degradation rate of tebuconazole in soils was concentration dependent.

Keywords: cropland soil, dissipation, laboratory incubation, tebuconazole

Procedia PDF Downloads 244
1077 Design, Modelling, and Fabrication of Bioinspired Frog Robot for Synchronous and Asynchronous Swimming

Authors: Afaque Manzoor Soomro, Faheem Ahmed, Fida Hussain Memon, Kyung Hyun Choi

Abstract:

This paper proposes the bioinspired soft frog robot. All printing technology was used for the fabrication of the robot. Polyjet printing was used to print the front and back limbs, while ultrathin filament was used to print the body of the robot, which makes it a complete soft swimming robot. The dual thrust generation approach has been proposed by embedding the main muscle and antagonistic muscle in all the limbs, which enables it to attain high speed (18 mm/s), and significant control of swimming in dual modes (synchronous and asynchronous modes). To achieve the swimming motion of the frog, the design, motivated by the rigorous modelling and real frog dynamics analysis, enabled the as-developed frog robot (FROBOT) to swim at a significant level of consistency with the real frog. The FROBOT (weighing 65 g) can swim at different controllable frequencies (0.5–2Hz) and can turn in any direction by following custom-made LabVIEW software’s commands which enables it to swim at speed up to 18 mm/s on the surface of deep water (100 cm) with excellent weight balance.

Keywords: soft robotics, soft actuator, frog robot, 3D printing

Procedia PDF Downloads 93
1076 Nitrogen and Potassium Fertilizer Response on Growth and Yield of Hybrid Luffa –Naga F1 Variety

Authors: D. R. T. N. K. Dissanayake, H. M. S. K. Herath, H. K. S. G. Gunadasa, P. Weerasinghe

Abstract:

Luffa is a tropical and subtropical vegetable, belongs to family Cucurbiteceae. It is predominantly monoecious in sex expression and provides an ample scope for utilization of hybrid vigor. Hybrid varieties develop through open pollination, produce higher yields due to its hybrid vigor. Naga F1 hybrid variety consists number of desirable traits other than higher yield such as strong and vigorous plants, fruits with long deep ridges, attractive green color fruits ,better fruit weight, length and early maturity compared to the local Luffa cultivars. Unavailability of fertilizer recommendations for hybrid cucurbit vegetables leads to an excess fertilizer application causing a vital environmental issue that creates undesirable impacts on nature and the human health. Main Objective of this research is to determine effect of different nitrogen and potassium fertilizer rates on growth and yield of Naga F1 Variety. Other objectives are, to evaluate specific growth parameters and yield, to identify the optimum nitrogen and potassium fertilizer levels based on growth and yield of hybrid Luffa variety. As well as to formulate the general fertilizer recommendation for hybrid Luffa -Naga F1 variety.

Keywords: hybrid, nitrogen, phosphorous, potassium

Procedia PDF Downloads 577
1075 Mimicking of Various ECM Tangible Cues for the Manipulation of Hepatocellular Behaviours

Authors: S. A. Abdellatef, A. Taniguchi, Namiki, Tsukuba, Ibaraki

Abstract:

The alterations in the physicochemical characteristics of bio-materials are renowned for their impact in cellular behaviors. Surface chemistry and substratum topography are separately considered as mutable characteristics with deep impact on the overall cell behaviors. In our recent work, we examined the manipulation of the physical cues on hepatic cellular behaviors. We have proven that the geometrical or dimensional characteristics of nano features are essential for the optimum hepatocellular functions. While here, the collective impact of both physical and chemical cues on hepatocellular behaviors was investigated. On which RGD peptide was immobilized on a TiO2 nano pattern that imitates the hierarchically extend collagen nano fibrillar structures. The hepatocytes morphological and functional changes induced by simultaneously combining the diversified cues were investigated. TiO2 substrates that integrate nano topography with the adhesive peptide motif (RGD) had showed an increase in the hepatocellular functionality to the maximum extent. While a significant enhancement in expression of these liver specific markers on RGD coated surfaces were observed compared to uncoated substrates regardless of topography. Consequently in depth understanding of the relationship between various kind of cues and hepatocytes behaviors would be a paving step in the application of tissue engineering and bio reactor technology.

Keywords: biomaterial, tiO2, hepG2, RGD

Procedia PDF Downloads 385
1074 Petrogenesis of the Neoproterozoic Rocks of Megele Area, Asosa, Western Ethiopia

Authors: Temesgen Oljira, Olugbenga Akindeji Okunlola, Akinade Shadrach Olatunji, Dereje Ayalew, Bekele Ayele Bedada

Abstract:

The Western Ethiopian Shield (WES) is underlain by volcano-sedimentary terranes, gneissic terranes, and ophiolitic rocks intruded by different granitoid bodies. For the past few years, Neoproterozoic rocks of the Megele area in the western part of the WES have been explored. Understanding the geology of the area and assessing the mineralized area's economic potential requires petrological, geochemical, and geological characterization of the Neoproterozoic granitoids and associated metavolcanic rocks. Thus, the geological, geochemical, and petrogenetic features of Neoproterozoic granitoids and associated metavolcanic rocks were elucidated using a combination of field mapping, petrological, and geochemical study. The Megele area is part of a low-grade volcano-sedimentary zone that has been intruded by mafic (dolerite dyke) and granitoid intrusions (granodiorite, diorite, granite gneiss). The granodiorite, associated diorite, and granite gneiss are calc-alkaline, peraluminous to slightly metaluminous, S-type granitoids formed in volcanic arc subduction (VAG) to syn-collisional (syn-COLD) tectonic setting by fractionation of LREE-enriched, HREE-depleted basaltic magma with considerable crustal input. While the metabasalt is sub-alkaline (tholeiitic), metaluminous bodies are generated at the mid-oceanic ridge tectonic setting by partially melting HREE-depleted and LREE-enriched basaltic magma. The reworking of sediment-loaded crustal blocks at depth in a subduction zone resulted in the production of S-type granitoids. This basaltic magma was supplied from an LREE-enriched, HREE-depleted mantle.

Keywords: fractional crystallization, geochemistry, Megele, petrogenesis, s-type granite

Procedia PDF Downloads 114