Search results for: deep mixing column

Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

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Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

Procedia PDF Downloads 444

Authors: Navajyoti Panda, R. S. Pawar

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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 187

Authors: Mohammad Zaeimzade

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The development of communication technologies is clearly and rapidly moving towards reducing the distance between the virtual and real worlds. Of course, living in a two-spatial or two-globalized world or any other interpretation that means mixing real and virtual life is still relevant and debatable. In the present age of communication, where social networks have transformed the message equation and turned the audience out of passivity and turned into a user. Platforms have penetrated widely in various aspects of human life, from culture and education and economy. Among the messengers, Instagram, which is one of the most extensive image-based interactive networks, plays a significant role in the new economic life. It doesn't need much explanation that the era of thinking of every messenger as a non-insulating conductor that is just a neutral load has passed. Every messenger has its own economic, political and of course security background, Instagram is no exception to this rule and of course it leaves its effects in bio-economics as well. Iran, as the 19th largest economy in the world, has not been unaffected by new platforms, including Instagram, and their consequences in the economy. Generally, in the policy-making space, there are two simple and inflexible pessimistic or optimistic views on this issue, and each of the holders of these views usually have their own one-dimensional policy recommendations regarding how to deal with Instagram. Prescriptions that are usually very different and sometimes contradictory. In this article, we show that this confusion of policymakers is the result of not accurately describing the reality of its effect, and the reason for this inaccurate description is the existence of a conflict of interests in the eyes of describers and researchers. In this article, we first take a look at the main indicators of the Iranian economy, estimate the role of the digital economy in Iran's economic growth, then study the conflicting descriptions of the Instagram-based digital economy, the statistics that show the tolerance of economic users of Instagram in Iran. 300 thousand to 9 million have been estimated. Finally, we take a look at the government's actions in this matter, especially in the context of street riots in October and November 2022. And we suggest an intermediate idea.

Keywords: digital economy, instagram, conflict of interest, social networks

Procedia PDF Downloads 74

Authors: Rosemary Anibogwu, Kavita Sharma, Karl De Jesus

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Sagebrush is an abundant and naturally occurring plant in the Intermountain West region of the United States. The plant contains an array of bioactive compounds such as flavonoids, terpenoids, sterols, and phenolic acids. It is important to identify and characterize these compounds because Native Americans use sagebrush as herbal medicine. These compounds are also utilized for preventing infection in wounds, treating headaches and colds, and possess antitumor properties. This research is an exploratory study on the sesquiterpene present in the leaves of sagebrush. The leaf foliage was extracted with 100 % chloroform and 100 % methanol. The percentage yield for the crude was considerably higher in chloroform. The Thin Layer Chromatography (TLC) analysis of the crude extracted unveiled a brown band at Rf = 0.25 and a dark brown band at Rf = 0.74, along with three unknown faint bands the 254 nm UV lamp. Furthermore, the two distinct brown (Achillin) and dark brown band (Hydroxyachillin) in TLC were further utilized in the isolation of pure compounds with column chromatography. The structures of Achillin and Hydroxyachillin were elucidated based on extensive spectroscopic analysis, including TLC, High-Performance Liquid Chromatography (HPLC), 1D- and 2D-Nuclear Magnetic Resonance (NMR), and Mass Spectroscopy (MS). The antioxidant activities of crude extract and three pure compounds were evaluated in terms of their peroxyl radical scavenging by Ferric Reducing Ability of Plasma (FRAP) and 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) methods. The crude extract showed the antioxidant activity of 18.99 ± 0.51 µmol TEg -1 FW for FRAP and 11.59 ± 0.38 µmol TEg -1 FW for DPPH. The activities of Achillin, Hydroxyachillin, and Quercetagetin trimethyl ether were 13.03, 15.90 and 14.02 µmol TEg -1 FW respectively for the FRAP assay. The three purified compounds have been submitted to the National Cancer Institute 60 cancer cell line for further study.

Keywords: HPLC, nuclear magnetic resonance spectroscopy, sagebrush, sesquiterpene lactones

Procedia PDF Downloads 130

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

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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 102

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

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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 185

Authors: Raju Singh, Shikha Singh

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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 145

Authors: Tamas Madl

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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 232

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

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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 90

Authors: Aysun Sezer

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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 64

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

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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 99

Authors: Cheng Li, Jie Shen, Yutian Tang

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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 380

Authors: Belayneh Matebie, Michael Melese

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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 52

Authors: Tomas Vincze, Michal Micjan, Milan Pavuk, Martin Weis

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In recent years, alternative materials are gaining attention to replace polycrystalline and amorphous silicon, which are a standard for low requirement devices, where silicon is unnecessarily and high cost. For that reason, metal oxides are envisioned as the new materials for these low-requirement applications such as sensors, solar cells, energy storage devices, or field-effect transistors. Their most common way of layer growth is sputtering; however, this is a high-cost fabrication method, and a more industry-suitable alternative is the sol-gel method. In this group of materials, many oxides exhibit a semiconductor-like behavior with sufficiently high mobility to be applied as transistors. The sol-gel method is a cost-effective deposition technique for semiconductor-based devices. Copper oxides, as p-type semiconductors with free charge mobility up to 1 cm2/Vs., are suitable replacements for poly-Si or a-Si:H devices. However, to reach the potential of silicon devices, a fine-tuning of material properties is needed. Here we focus on the optimization of the electrical parameters of copper oxide-based field-effect transistors by modification of precursor solvent (usually 2-methoxy ethanol). However, to achieve solubility and high-quality films, a better solvent is required. Since almost no solvents have both high dielectric constant and high boiling point, an alternative approach was proposed with blend solvents. By mixing isopropyl alcohol (IPA) and 2-methoxy ethanol (2ME) the precursor reached better solubility. The quality of the layers fabricated using mixed solutions was evaluated in accordance with the surface morphology and electrical properties. The IPA:2ME solution mixture reached optimum results for the weight ratio of 1:3. The cupric oxide layers for optimal mixture had the highest crystallinity and highest effective charge mobility.

Keywords: copper oxide, field-effect transistor, semiconductor, sol-gel method

Procedia PDF Downloads 133

Authors: Qingqing Gai, Junxing Shen, Yu Luo

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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 103

Authors: W. Thongkham, K. Sinthiptharakoon, K. Tantisantisom, A. Klamchuen, P. Khanchaitit, K. Jiramitmongkon, C. Lertsatitthanakorn, M. Liangruksa

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Due to demands of sustainable energy, thermoelectricity converting waste heat into electrical energy has become one of the intensive fields of worldwide research. However, such harvesting technology has shown low device performance in the temperature range below 150℃. In this work, a hybrid nanowire of inorganic bismuth telluride (Bi₂Te₃) and organic poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) synthesized using a simple in-situ one-pot synthesis, enhancing efficiency of the nanowire-incorporated PEDOT:PSS-based thermoelectric converter is highlighted. Since the improvement is ascribed to the increased electrical conductivity of the thermoelectric host material, the individual hybrid nanowires are investigated using voltage-dependent conductive atomic force microscopy (CAFM) and spectroscopy (CAFS) considering that the electrical transport measurement can be performed either on insulating or conducting areas of the sample. Correlated with detailed chemical information on the crystalline structure and compositional profile of the nanowire core-shell structure, an electrical transporting pathway through the nanowire and the corresponding electronic-band structure have been determined, in which the native oxide layer on the Bi₂Te₃ surface is not considered, and charge conduction on the topological surface states of Bi₂Te₃ is suggested. Analyzing the core-shell nanowire synthesized using the conventional mixing of as-prepared Bi₂Te₃ nanowire with PEDOT:PSS for comparison, the oxide-removal effect of the in-situ encapsulating polymeric layer is further supported. The finding not only provides a structural information for mechanistic determination of the thermoelectricity, but it also encourages new approach toward more appropriate encapsulation and consequently higher efficiency of the nanowire-based thermoelectric generation.

Keywords: electrical transport measurement, hybrid Bi₂Te₃-PEDOT:PSS nanowire, nanoencapsulation, thermoelectricity, topological insulator

Procedia PDF Downloads 203

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 98

Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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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 62

Authors: Fatemeh Sadat Sharifi

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In the present study, the capabilities of WAVEWATCH-III and MIKE21-SW for predicting the characteristics of wind waves in Hormuz Strait are evaluated. The GFS wind data (Global Forecast System) were derived. The bathymetry of gride with 2 arc-minute resolution, also were extracted from the ETOPO1. WAVEWATCH-III findings illustrate more valid prediction of wave features comparing to the MIKE-21 SW in deep water. Apparently, in shallow area, the MIKE-21 provides more uniformities with altimetry measurements. This may be due to the merits of the unstructured grid which are used in MIKE-21, leading to better representations of the coastal area. The findings on the direction of waves generated by wind in the modeling area indicate that in some regions, despite the increase in wind speed, significant wave height stays nearly unchanged. This is fundamental because of swift changes in wind track over the Strait of Hormuz. After discussing wind-induced waves in the region, the impact of instability of the surface layer on wave growth has been considered. For this purpose, the average monthly mean air temperature has been used. The results in cold months, when the surface layer is unstable, indicates an acceptable increase in the accuracy of prediction of the indicator wave height.

Keywords: numerical modeling, WAVEWATCH-III, Strait of Hormuz, MIKE21-SW

Procedia PDF Downloads 206

Authors: Mauricio Gracia, Luis Leal, Bharat Verma

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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 171

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

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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 333

Authors: H. Daaou Nedjari, O. Guerri, M. Saighi

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A numerical study was conducted to optimize the positioning of wind turbines over complex terrains. Thus, a two-dimensional disk model was used to calculate the flow velocity deficit in wind farms for both flat and complex configurations. The wind turbine wake was assessed using the hybrid methods that combine CFD (Computational Fluid Dynamics) with the actuator disc model. The wind turbine rotor has been defined with a thrust force, coupled with the Navier-Stokes equations that were resolved by an open source computational code (Code_Saturne V3.0 developed by EDF) The simulations were conducted in atmospheric boundary layer condition considering a two-dimensional region located at the north of Algeria at 36.74°N longitude, 02.97°E latitude. The topography elevation values were collected according to a longitudinal direction of 1km downwind. The wind turbine sited over topography was simulated for different elevation variations. The main of this study is to determine the topography effect on the behavior of wind farm wake flow. For this, the wake model applied in complex terrain needs to selects the singularity effects of topography on the vertical wind flow without rotor disc first. This step allows to determine the existence of mixing scales and friction forces zone near the ground. So, according to the ground relief the wind flow waS disturbed by turbulence and a significant speed variation. Thus, the singularities of the velocity field were thoroughly collected and thrust coefficient Ct was calculated using the specific speed. In addition, to evaluate the land effect on the wake shape, the flow field was also simulated considering different rotor hub heights. Indeed, the distance between the ground and the hub height of turbine (Hhub) was tested in a flat terrain for different locations as Hhub=1.125D, Hhub = 1.5D and Hhub=2D (D is rotor diameter) considering a roughness value of z0=0.01m. This study has demonstrated that topographical farm induce a significant effect on wind turbines wakes, compared to that on flat terrain.

Keywords: CFD, wind turbine wake, k-epsilon model, turbulence, complex topography

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

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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 250

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 99

Authors: Ewa Siedlecka

Abstract:

Emotional stress is an important risk factor in the rate and severity of traffic accidents. Moreover, incorrect time perception is implicated in the increase of traffic violations, such as running red lights or collisions. While the role of emotional arousal on perceived time is well-established, the role of physiological arousal in time perception remains unexamined. Specific emotions can be, however, associated with distinct physiological responses. In the current research, two studies examined the role of physiological arousal in time perception. In the first experiment, 41 participants engaged in a cold pressor task and had their time perception measured throughout the experiment. In the second study, 138 participants engaged in either isometric or deep breathing exercises. These activities were designed to simulate the sympathetic and parasympathetic nervous systems, respectively. Participants completed a bisection task to measure time perception in both studies, as well as a physiological response via an Electrocardiography (ECG). Results found that activation of the parasympathetic nervous system is associated with greater time perception. These findings are discussed with reference to models of time perception, as well as implications for emotional driving and misperceptions of speed. It is important to consider the role of physiology in the misperception of time, as these factors can lead to increases in driving accidents.

Keywords: emotions, nervous system, physiology, time perception

Procedia PDF Downloads 321

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 591

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 392

Authors: Y. A. Prada, Fanny Guzman, Rafael Cabanzo, John J. Castillo, Enrique Mejia-Ospino

Abstract:

In this work, we show the important results about of synthesis of photoluminiscents gold nanoclusters using a small peptide as template for biosensing applications. Interestingly, we design one peptide (NBC2854) homologue to conservative domain from 215 250 residue of a galactolectin protein which can recognize the proteophosphoglycans (PPG) from Leishmania. Peptide was synthetized by multiple solid phase synthesis using FMoc group methodology in acid medium. Finally, the peptide was purified by High-Performance Liquid Chromatography using a Vydac C-18 preparative column and the detection was at 215 nm using a Photo Diode Array detector. Molecular mass of this peptide was confirmed by MALDI-TOF and to verify the α-helix structure we use Circular Dichroism. By means of the methodology used we obtained a novel fluorescents gold nanoclusters (AuNC) using NBC2854 as a template. In this work, we described an easy and fast microsonic method for the synthesis of AuNC with ≈ 3.0 nm of hydrodynamic size and photoemission at 630 nm. The presence of cysteine residue in the C-terminal of the peptide allows the formation of Au-S bond which confers stability to Peptide-based gold nanoclusters. Interactions between the peptide and gold nanoclusters were confirmed by X-ray Photoemission and Raman Spectroscopy. Notably, from the ultrafine spectra shown in the MALDI-TOF analysis which containing only 3-7 KDa species was assigned to Au₈-₁₈[NBC2854]₂ clusters. Finally, we evaluated the Peptide-gold nanocluster as an optical biosensor based on fluorescence spectroscopy and the fluorescence signal of PPG (0.1 µg-mL⁻¹ to 1000 µg-mL⁻¹) was amplified at the same wavelength emission (≈ 630 nm). This can suggest that there is a strong interaction between PPG and Pep@AuNC, therefore, the increase of the fluorescence intensity can be related to the association mechanism that take place when the target molecule is sensing by the Pep@AuNC conjugate. Further spectroscopic studies are necessary to evaluate the fluorescence mechanism involve in the sensing of the PPG by the Pep@AuNC. To our best knowledge the fabrication of an optical biosensor based on Pep@AuNC for sensing biomolecules such as Proteophosphoglycans which are secreted in abundance by parasites Leishmania.

Keywords: biosensing, fluorescence, Leishmania, peptide-gold nanoclusters, proteophosphoglycans

Procedia PDF Downloads 166

Authors: Adeyi Akindele Oluwatosin, Mustapha Kaosarat Keji, Ajisebiola Babafemi Siji, Adeyi Olubisi Esther, Damilohun Samuel Metibemu, Raphael Emuebie Okonji

Abstract:

Envenoming by Echis ocellatus is potentially life-threatening due to severe hemorrhage, renal failure, and capillary leakage. These effects are attributed to snake venom metalloproteinases (SVMPs). Due to drawbacks in the use of antivenom, natural inhibitors from plants are of interest in studies of new antivenom treatment. Antagonizing effects of bioactive compounds of Moringa oleifera, a known antisnake plant, are yet to be tested against SVMPs of E. ocellatus (SVMP-EO). Ethanol crude extract of M. oleifera was partitioned using n-hexane and ethyl acetate. Each partition was fractionated using column chromatography and tested against SVMP-EO purified through ion-exchange chromatography with EchiTab-PLUS polyvalent anti-venom as control. Phytoconstituents of ethyl acetate fraction were screened against the catalytic site of crystal of BaP1-SVMP, while drug-likeness and ADMET toxicity of compound were equally determined. The molecular weight of isolated SVMP-EO was 43.28 kDa, with a specific activity of 245 U/ml, a percentage yield of 62.83 %, and a purification fold of 0.920. The Vmax and Km values are 2 mg/ml and 38.095 μmol/ml/min, respectively, while the optimal pH and temperature are 6.0 and 40°C, respectively. Polyvalent anti-venom, crude extract, and ethyl acetate fraction of M. oleifera exhibited a complete inhibitory effect against SVMP-EO activity. The inhibitions of the P-1 and P-II metalloprotease’s enzymes by the ethyl acetate fraction are largely due to methanol, 6, 8, 9-trimethyl-4-(2-phenylethyl)-3-oxabicyclo[3.3.1]non-6-en-1-yl)- and paroxypropione, respectively. Both compounds are potential drug candidates with little or no concern of toxicity, as revealed from the in-silico predictions. The inhibitory effects suggest that this compound might be a therapeutic candidate for further exploration for treatment of Ocellatus’ envenoming.

Keywords: Echis ocellatus, Moringa oleifera, anti-venom, metalloproteases, snakebite, molecular docking

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Authors: Ailing Yang, Penghan Song, Aihua Cai

Abstract:

The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

Procedia PDF Downloads 175