Search results for: loss model

Authors: Shuqi Zhang

Abstract:

Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

Procedia PDF Downloads 101

Authors: Chiau Yuan Lim, Hayyiratul Fatimah Mohd Zaid, Fai Kait Chong

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Deep Eutectic Solvent (DES) is used in various applications due to its simplicity in synthesis procedure, biodegradable, inexpensive and easily available chemical ingredients. Graphene Oxide is a popular catalyst that being used in various processes due to its stacking carbon sheets in layer which theoretically rapid up the catalytic processes. In this study, choline chloride based DESs were synthesized and ChCl-PEG(1:4) was found to be the most effective DES in performing desulfurization, which it is able to remove up to 47.4% of the sulfur content in the model oil in just 10 minutes, and up to 95% of sulfur content after repeat the process for six times. ChCl-PEG(1:4) able to perform up to 32.7% desulfurization on real diesel after 6 multiple stages. Thus, future research works should focus on removing the impurities on real diesel before utilising DESs in petroleum field.

Keywords: choline chloride, deep eutectic solvent, fuel desulfurization, graphene oxide

Procedia PDF Downloads 157

Authors: M. Al Azri, M. Elzain, K. Bouziane, S. M. Chérif

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n-Type 6H-SiC(0001) substrates were implanted with three fluencies of Mn+ 5x1015 Mn/cm2 (Mn content: 0.7%), 1x1016 (~2 %), and 5x1016 cm–2 (7%) with implantation energy of 80 keV and substrate temperature of 365ºC. The samples were characterized using Rutherford Backscattering and Channeling Spectroscopy (RBS/C), High-Resolution X-Ray Diffraction technique (HRXRD), micro-Raman Spectroscopy (μRS), and Superconducting Quantum Interference Device (SQUID) techniques. The aim of our work is to investigate implantation induced defects with dose and to study any correlation between disorder-composition and magnetic properties. In addition, ab-initio calculations were used to investigate the structural and magnetic properties of Mn-doped 6H-SiC. Various configurations of Mn sites and vacancy types were considered. The calculations showed that a substitutional Mn atom at Si site possesses larger magnetic moment than Mn atom at C site. A model is introduced to explain the dependence of the magnetic structure on site occupation. The magnetic properties of ferromagnetically (FM) and antiferromagnetically (AFM) coupled pairs of Mn atoms with and without neighboring vacancies have also been explored.

Keywords: ab-initio calculations, diluted magnetic semiconductors, magnetic properties, silicon carbide

Procedia PDF Downloads 329

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 122

Authors: Ehsan Atefi, Michael Grigware

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Respiratory failure secondary to surfactant deficiency resulting from respiratory distress syndrome is considered one major cause of morbidity in preterm infants. Surfactant replacement treatment (SRT) is considered an effective treatment for this disease. Here, we introduce an AI-mediated approach for estimating the distribution of surfactant in the lung airway of a newborn infant during SRT. Our approach implements machine learning to precisely estimate the splitting ratio of a liquid drop during bifurcation at different injection velocities and patient orientations. This technique can be used to calculate the surfactant residue remaining on the airway wall during the surfactant injection process. Our model works by minimizing the pressure drop difference between the two airway branches at each generation, subject to mass and momentum conservation. Our platform can be used to generate feedback for immediately adjusting the velocity of injection and patient orientation during SRT.

Keywords: respiratory failure, surfactant deficiency, surfactant replacement, machine learning

Procedia PDF Downloads 129

Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

Procedia PDF Downloads 181

Authors: Evy Rombaut, Marie-Anne Guerry

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Predicting voluntary turnover of employees is an important topic of study, both in academia and industry. Researchers try to uncover determinants for a broader understanding and possible prevention of turnover. In the current study, we use a data set based approach to reveal determinants for turnover, differing for blue and white collar workers. Our data set based approach made it possible to study actual turnover for more than 500000 employees in 15692 Belgian corporations. We use logistic regression to calculate individual turnover probabilities and test the goodness of our model with the AUC (area under the ROC-curve) method. The results of the study confirm the relationship of known determinants to employee turnover such as age, seniority, pay and work distance. In addition, the study unravels unknown and verifies known differences between blue and white collar workers. It shows opposite relationships to turnover for gender, marital status, the number of children, nationality, and pay.

Keywords: employee turnover, blue collar, white collar, dataset analysis

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

Procedia PDF Downloads 76

Authors: Han-Taw Chen, Tzu-Hsiang Lin, Chung-Hou Lai

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This study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a rectangular closed enclosure. The inverse method with the finite difference method and the experimental temperature data is applied to determine the approximate heat transfer coefficient. Later, based on the obtained results, the zero-equation turbulence model is used to obtain the heat transfer and fluid flow characteristics between two fins. To validate the accuracy of the results obtained, the comparison of the heat transfer coefficient is made. The obtained temperature at selected measurement locations of the fin is also compared with experimental data. The effect of the height of the rectangular enclosure on the obtained results is discussed.

Keywords: inverse method, fluent, heat transfer characteristics, plate-fin heat sink

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Authors: Shiuh-Jer Huang, Yun-Han Yeh

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A 40 steps manual adjusting shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system for a four-wheel drive electric vehicle. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. A fuzzy logic controller was designed to derive appropriate damping target based on vehicle running condition for semi-active suspension system to follow. The damping ratio control of each wheel axis suspension system is executed with a robust fuzzy sliding mode controller (FSMC). Different road surface conditions are chosen to evaluate the control performance of this semi-active suspension system based on wheel axis acceleration signal.

Keywords: semi-active suspension, electric vehicle, fuzzy sliding mode control, accelerometer

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

Procedia PDF Downloads 149

Authors: Pablo Enrique Sartor Del Giudice

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Penalty shootouts often decide the outcome of important soccer matches. Although usually referred to as ”lotteries”, there is evidence that some national teams and clubs consistently perform better than others. The outcomes are therefore not explained just by mere luck, and therefore there are ways to improve the average performance of players, naturally at the expense of some sort of effort. In this article we study the payoff of player performance improvements in terms of the performance of the team as a whole. To do so we develop an analytical model with static individual performances, as well as Monte Carlo models that take into account the known influence of partial score and round number on individual performances. We find that within a range of usual values, the team performance improves above 70% faster than individual performances do. Using these models, we also estimate that the new ABBA penalty shootout ordering under test reduces almost all the known bias in favor of the first-shooting team under the current ABAB system.

Keywords: football, penalty shootouts, Montecarlo simulation, ABBA

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

Procedia PDF Downloads 428

Authors: Hawraa Zbeeb, Hala Khalifeh, Mohamad Khalil, Francesca Storace, Francesca Baldini, Giulio Lupidi, Laura Vergani

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Sarcopoterium spinosum, a widely distributed spiny shrub belonging to the Rosaceae family, is rich in essential and beneficial constituents. In fact, S. spinosum fruits and roots are traditionally used as herbal medicine in the eastern Mediterranean landscape, and this shrub is mentioned as a medicinal plant in a large number of ethnobotanical surveys. Aqueous root extracts from S. spinosum are used by traditional medicinal practitioners for weight loss treatment of diabetes and pain. Moreover, the anti-diabetic activity of S. spinosum root extract has been reported in different studies, but the beneficial effects of aerial parts, especially fruits, have not been elucidated yet. The aim of the present study was to investigate the in vitro antioxidant and lipid-lowering properties of an ethanolic extract from S. spinosum fruits using both hepatic (FaO) and endothelial (HECV) cells in an attempt to evaluate its possible employment as a nutraceutical supplement. First of all, in vitro spectrophotometric assays were employed to characterize the extract. The total phenol content (TPC) was evaluated by Folin–Ciocalteu spectrophotometric method and the radical scavenging activity was tested by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assays. After that, the beneficial effects of the extract were tested on cells. FaO cells treated for 3 hours with 0.75 mM oleate/palmitate mix (1:2 molar ratio) mimic in vitro a moderate hepato-steatosis. HECV cells exposed for 1 hour to 100 µM H₂O₂ mimic an oxidative insult leading to oxidative stress conditions. After the metabolic and oxidative insult, both cell lines were treated with increasing concentrations of the S. spinosum extract (1, 10, 25 µg/mL) for 24 hours. The results showed the S. spinosum ethanolic extract is rather rich in phenols (TPC of 18.6 mgGAE/g dry extracts). Moreover, the extract showed a good scavenging ability in vitro (IC₅₀ 15.9 µg/ml and 10.9 µg/ml measured by DPPH and ABTS assays, respectively). When the extract was tested on cells, the results showed that it could ameliorate some markers of cell dysfunction. The three concentrations of the extract led to a significant decrease in the intracellular triglyceride (TG) content in steatotic FaO cells measured by spectrophotometric assay. On the other hand, HECV cells treated with increasing concentrations of the extract did not result in a significant decrease in both lipid peroxidation measured by the Thiobarbituric Acid Reactive Substances (TBARS) assay, and in reactive oxygen species (ROS) production measured by fluorometric analysis after DCF staining. Interestingly, the ethanolic extract was able to accelerate the wound repair of confluent HECV cells with respect to H₂O₂-insulted cells as measured by T-scratch assay. Taken together, these results seem to indicate that the ethanol extract from S. spinosum fruits is rich in phenol compounds and plays considerable lipid-lowering activity in vitro on steatotic hepatocytes and accelerates wound healing repair on endothelial cells. In light of that, the ethanolic extract from S. spinosum fruits could be a potential candidate for nutraceutical applications.

Keywords: antioxidant activity, ethanolic extract, lipid-lowering activity, phenolic compounds, Sarcopoterium spinosum fruits

Procedia PDF Downloads 179

Authors: Kosuri Harshitha Durga, Ritesh Yaduwanshi

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Potholes are one of the most significant problems that affect road safety and the quality of infrastructure. The aim of pothole detection using OpenCV is to design an automated system that will detect and create a map of potholes on the road surfaces to improve the safety of roads and ease the maintenance process. This system is based on high-powered computer vision methods that use still images or video footage taken by cameras located in cars or drones. This paper presents an analysis of the implementation of the YOLOv11 model in pedestrian detection and demonstrates greater effectiveness of this method in regards to accuracy, speed, and efficiency of inference. The improved system now supports enhanced prompt diagnosis and timely repair leaving little or no damage on the infrastructure and also ensuring that enhanced road safety is achieved. This technology can also be used as a safety feature for the car itself by being installed in ADAS systems that would alert drivers in real-time while driving to avoid driving over potholes.

Keywords: deep learning, Potholes, segmentation, object detection, YOLO

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Authors: Chin Tangtarntana

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The main purpose of this study was to investigate the effects of animation in offensive product advertising. Experiment was conducted to collect consumer responses toward animated and static ads of offensive and non-offensive products. The study was conducted by distributing questionnaires to the target respondents. According to statistics from Innovative Internet Research Center, Thailand, majority of internet users are 18 – 44 years old. The results revealed an interaction between ad design and offensive product. Specifically, when used in offensive product advertisements, animated ads were not effective for consumer attention, but yielded positive response in terms of attitude toward product. The findings support that information processing model is accurate in predicting consumer cognitive response toward cartoon ads, whereas U&G, arousal, and distinctive theory is more accurate in predicting consumer affective response. In practical, these findings can also be used to guide ad designers and marketers that are suitable for offensive products.

Keywords: animation, banner ad design, consumer responses, offensive product advertising, stock exchange of Thailand

Procedia PDF Downloads 275

Authors: S. S. Kharintsev, E. A. Chernykh, S. K. Saikin, A. I. Fishman, S. G. Kazarian

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Recent advances in improving information storage performance are inseparably linked with circumvention of fundamental constraints such as the supermagnetic limit in heat assisted magnetic recording, charge loss tolerance in solid-state memory and the Abbe’s diffraction limit in optical storage. A substantial breakthrough in the development of nonvolatile storage devices with dimensional scaling has been achieved due to phase-change chalcogenide memory, which nowadays, meets the market needs to the greatest advantage. A further progress is aimed at the development of versatile nonvolatile high-speed memory combining potentials of random access memory and archive storage. The well-established properties of light at the nanoscale empower us to use them for recording optical information with ultrahigh density scaled down to a single molecule, which is the size of a pit. Indeed, diffraction-limited optics is able to record as much information as ~1 Gb/in2. Nonlinear optical effects, for example, two-photon fluorescence recording, allows one to decrease the extent of the pit even more, which results in the recording density up to ~100 Gb/in2. Going beyond the diffraction limit, due to the sub-wavelength confinement of light, pushes the pit size down to a single chromophore, which is, on average, of ~1 nm in length. Thus, the memory capacity can be increased up to the theoretical limit of 1 Pb/in2. Moreover, the field confinement provides faster recording and readout operations due to the enhanced light-matter interaction. This, in turn, leads to the miniaturization of optical devices and the decrease of energy supply down to ~1 μW/cm². Intrinsic features of light such as multimode, mixed polarization and angular momentum in addition to the underlying optical and holographic tools for writing/reading, enriches the storage and encryption of optical information. In particular, the finite extent of the near-field penetration, falling into a range of 50-100 nm, gives the possibility to perform 3D volume (layer-to-layer) recording/readout of optical information. In this study, we demonstrate a comprehensive evidence of isotropic-to-homeotropic phase transition of the azobenzene-functionalized polymer thin film exposed to light and dc electric field using near-field optical microscopy and scanning capacitance microscopy. We unravel a near-field Raman dichroism of a sub-10 nm thick epoxy-based side-chain azo-polymer films with polarization-controlled tip-enhanced Raman scattering. In our study, orientation of azo-chromophores is controlled with a bias voltage gold tip rather than light polarization. Isotropic in-plane and homeotropic out-of-plane arrangement of azo-chromophores in glassy environment can be distinguished with transverse and longitudinal optical near-fields. We demonstrate that both phases are unambiguously visualized by 2D mapping their local dielectric properties with scanning capacity microscopy. The stability of the polar homeotropic phase is strongly sensitive to the thickness of the thin film. We make an analysis of α-transition of the azo-polymer by detecting a temperature-dependent phase jump of an AFM cantilever when passing through the glass temperature. Overall, we anticipate further improvements in optical storage performance, which approaches to a single molecule level.

Keywords: optical memory, azo-dye, near-field, tip-enhanced Raman scattering

Procedia PDF Downloads 180

Authors: Navid Daryasafar, Nima Farshidfar

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In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

Procedia PDF Downloads 544

Authors: Azza A. Ali, Abeer I. Abd El-Fattah, Shaimaa S. Hussein, Hanan A. Abd El-Samea, Karema Abu-Elfotuh

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Background: Aluminium (Al) represents an environmental risk factor. Exposure to high levels of Al causes neurotoxic effects and different diseases. Vinpocetine is widely used to improve cognitive functions, it possesses memory-protective and memory-enhancing properties and has the ability to increase cerebral blood flow and glucose uptake. Cocoa bean represents a rich source of iron as well as a potent antioxidant. It can protect from the impact of free radicals, reduces stress as well as depression and promotes better memory and concentration. Wheatgrass is primarily used as a concentrated source of nutrients. It contains vitamins, minerals, carbohydrates, amino acids and possesses antioxidant and anti-inflammatory activities. Coenzyme Q10 (CoQ10) is an intracellular antioxidant and mitochondrial membrane stabilizer. It is effective in improving cognitive disorders and has been used as anti-aging. Zinc is a structural element of many proteins and signaling messenger that is released by neural activity at many central excitatory synapses. Objective: To study the role of some nutrients and drugs as Vinpocetine, Cocoa, Wheatgrass, CoQ10 and Zinc against neurotoxicity induced by Al in rats as well as to compare between their potency in providing protection. Methods: Seven groups of rats were used and received daily for three weeks AlCl3 (70 mg/kg, IP) for Al-toxicity model groups except for the control group which received saline. All groups of Al-toxicity model except one group (non-treated) were co-administered orally together with AlCl3 the following treatments; Vinpocetine (20mg/kg), Cocoa powder (24mg/kg), Wheat grass (100mg/kg), CoQ10 (200mg/kg) or Zinc (32mg/kg). Biochemical changes in the rat brain as acetyl cholinesterase (ACHE), Aβ, brain derived neurotrophic factor (BDNF), inflammatory mediators (TNF-α, IL-1β), oxidative parameters (MDA, SOD, TAC) were estimated for all groups besides histopathological examinations in different brain regions. Results: Neurotoxicity and neurodegenerations in the rat brain after three weeks of Al exposure were indicated by the significant increase in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the significant decrease in SOD, TAC, BDNF and confirmed by the histopathological changes in the brain. On the other hand, co-administration of each of Vinpocetine, Cocoa, Wheatgrass, CoQ10 or Zinc together with AlCl3 provided protection against hazards of neurotoxicity and neurodegenerations induced by Al, their protection were indicated by the decrease in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the increase in SOD, TAC, BDNF and confirmed by the histopathological examinations of different brain regions. Vinpocetine and Cocoa showed the most pronounced protection while Zinc provided the least protective effects than the other used nutrients and drugs. Conclusion: Different degrees of protection from neurotoxicity and neuronal degenerations induced by Al could be achieved through the co-administration of some nutrients and drugs during its exposure. Vinpocetine and Cocoa provided the most protection than Wheat grass, CoQ10 or Zinc which showed the least protective effects.

Keywords: aluminum, neurotoxicity, vinpocetine, cocoa, wheat grass, coenzyme Q10, Zinc, rats

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Authors: Heqian Zhao, Huaizhong Shi, Zhongwei Huang, Zhengliang Chen, Ziang Gu, Fei Gao

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Hydraulics mechanics is significantly important in the drilling process of oil or gas exploration, especially for the drill bit. The fluid flows through the nozzles on the bit and generates a water jet to remove the cutting at the bottom hole. In this paper, a simplified bottom hole model is established. The Particle Image Velocimetric (PIV) is used to capture the flow field of the single nozzle. Due to the limitation of the bottom and wellbore, the potential core is shorter than that of the free water jet. The velocity magnitude rapidly attenuates when fluid close to the bottom is lower than about 5 mm. Besides, a vortex zone appears near the middle of the bottom beside the water jet zone. A modified exponential function can be used to fit the centerline velocity well. On the one hand, the results of this paper can provide verification for the numerical simulation of the bottom hole flow field. On the other hand, it also can provide an experimental basis for the hydraulic design of the drill bit.

Keywords: oil and gas, hydraulic mechanic of drilling, PIV, bottom hole

Procedia PDF Downloads 217

Authors: Wang, Kuei-Ing, Jou-Fan Shih

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This study adopts deterrence theory as well as social identities as moderators, and explores their moderating affects on online toxic disinhibition. Survey and Experimental methodologies are applied to test the research model and four hypotheses are developed in this study. The controllability of identity positively influenced the behavior of toxic disinhibition both in experimental and control groups while the fluidity of the identity did not have significant influences on online disinhibition. Punishment certainty, punishment severity as well as social identity negatively moderated the relation between the controllability of the identity and the toxic disinhibition. The result of this study shows that internet users hide their real identities when they behave inappropriately on internet, but once they acknowledge that the inappropriate behavior will be found and punished severely, the inappropriate behavior then will be weakened.

Keywords: seductive properties of internet, online disinhibition, punishment certainty, punishment severity, social identity

Procedia PDF Downloads 512

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 127

Authors: Elisabeth Brandenburg, Robert Woll, Rainer Stark

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This paper presents how smart glasses and voice commands can be used for improving the maintenance process of industrial gas turbines. It presents the process of inspecting a gas turbine’s combustion chamber and how it is currently performed using a set of paper-based documents. In order to improve this process, a portable hands-free process assistance system has been conceived. In the following, it will be presented how the approach of user-centered design and the method of paper prototyping have been successfully applied in order to design a user interface and a corresponding workflow model that describes the possible interaction patterns between the user and the interface. The presented evaluation of these results suggests that the assistance system could help the user by rendering multiple manual activities obsolete, thus allowing him to work hands-free and to save time for generating protocols.

Keywords: paper prototyping, smart glasses, turbine maintenance, user centered design

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Authors: Ricardo Merlo

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The use of simulation as a digital didactic tool allowed students to reproduce the laws of Physics in order to improve their academic performance. The didactic resource of simulation also favored the motivation of most of the young people, depending on the subject of Physics to be developed in the classroom and in that sense, it was significant to know the favorable or unfavorable attitude that the students presented about the use of simulation resources to maximize the anchorage of the contents planned for the different classes developed in the classroom. The different real-time simulation applications that were offered free of charge through the Internet were not presented as a specific resource that could be used in a didactic model, and in that framework, the teachers of Physics at the university level did not apply these resources in a systematic way with the knowledge of the favorable or unfavorable attitude of the students towards these didactic resources. For this reason, this work proposed the design and application of attitude questionnaires to enhance the use of those simulation resources that allowed for improving the quality of the class and the academic performance of the students.

Keywords: physics teaching, attitude, motivation, didactic resources

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Authors: Phornpat Chewasoonthorn, Surat Kwanmuang

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Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. This study developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, This study purposes an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.

Keywords: indoor positioning, ultra-wideband, error correction, Kalman filter

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Authors: Mohammad Sadeghi, Mahdieh Saniee

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Nowadays, development laws have become a major branch of engineering science, laws help humankind achieve his/her basic needs, and it is attracted to the attention of the nations. Therefore, lawyers have been invited to contemplate legislator's approaches respecting legislating countries' economic, social and cultural development plans and to observe the reliance of approaches on two elements of distributive justice and transitional justice in light of legal rationality. Legal rationality in development planning has encountered us with this question that whether a rational approach and existing models in the Iran development planning system approximate us to the goal of development laws respecting the rationalist approach and also regarding wisely decision-making model. The present study will investigate processes, approaches, and damages of development planning in the legislation of country development plans to answer this question.

Keywords: rationality, decision-making process, policymaking, development

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Authors: Alexandra Steed

Abstract:

Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

Procedia PDF Downloads 103

Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

Abstract:

We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

Procedia PDF Downloads 224

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

Procedia PDF Downloads 294

Authors: M. S. Khurram, S. A. Memon, S. Khan

Abstract:

Bed voidage behavior among different flow regimes for Geldart A, B, and D particles (fluid catalytic cracking catalyst (FCC), particle A and glass beads) of diameter range 57-872 μm, apparent density 1470-3092 kg/m³, and bulk density range 890-1773 kg/m³ were investigated in a gas-solid circulating fluidized bed of 0.1 m-i.d. and 2.56 m-height of plexi-glass. Effects of variables (gas velocity, particle properties, and static bed height) were analyzed on bed voidage. The axial voidage profile showed a typical trend along the riser: a dense bed at the lower part followed by a transition in the splash zone and a lean phase in the freeboard. Bed expansion and dense bed voidage increased with an increase of gas velocity as usual. From experimental results, a generalized model relationship based on inverse fluidization number for dense bed voidage from bubbling to fast fluidization regimes was presented.

Keywords: axial voidage, circulating fluidized bed, splash zone, static bed

Procedia PDF Downloads 290