Search results for: signal variation

Authors: Gareth Baxter

Abstract:

We use a mathematical model of language change to examine two recently observed patterns of language change: one in which most speakers change gradually, following the mean of the community change, and one in which most individuals use predominantly one variant or another, and change rapidly if they change at all. The model is based on Croft’s Utterance Selection account of language change, which views language change as an evolutionary process, in which different variants (different ‘ways of saying the same thing’) compete for usage in a population of speakers. Language change occurs when a new variant replaces an older one as the convention within a given population. The present model extends a previous simpler model to include effects related to speaker aging and interspeaker variation in behaviour. The two patterns of individual change (one more centralized and the other more polarized) were recently observed in historical language changes, and it was further observed that slower changes were more associated with the centralized pattern, while quicker changes were more polarized. Our model suggests that the two patterns of change can be explained by different balances between the preference of speakers to use one variant over another and the degree of accommodation to (propensity to adapt towards) other speakers. The correlation with the rate of change appears naturally in our model, and results from the fact that both differential weighting of variants and the degree of accommodation affect the time for change to occur, while also determining the patterns of change. This work represents part of an ongoing effort to examine phenomena in language change through the use of mathematical models. This offers another way to evaluate qualitative explanations that cannot be practically tested (or cannot be tested at all) in a real-world, large-scale speech community.

Keywords: agent based modeling, cultural evolution, language change, social behavior modeling, social influence

Procedia PDF Downloads 235

Authors: Vimanyu Chadha, Ranganath M. Singari

Abstract:

Drilling composite materials is a frequently practiced machining process during assembling in various industries such as automotive and aerospace. However, drilling of glass fiber reinforced plastic (GFRP) composites is significantly affected by damage tendency of these materials under cutting forces such as thrust force and torque. The aim of this paper is to investigate the influence of the various cutting parameters such as cutting speed and feed rate; subsequently also to study the influence of number of layers on delamination produced while drilling a GFRP composite. A plan of experiments, based on Taguchi techniques, was instituted considering drilling with prefixed cutting parameters in a hand lay-up GFRP material. The damage induced associated with drilling GFRP composites were measured. Moreover, Analysis of Variance (ANOVA) was performed to obtain minimization of delamination influenced by drilling parameters and number layers. The optimum drilling factor combination was obtained by using the analysis of signal-to-noise ratio. The conclusion revealed that feed rate was the most influential factor on the delamination. The best results of the delamination were obtained with composites with a greater number of layers at lower cutting speeds and feed rates.

Keywords: analysis of variance, delamination, design optimization, drilling, glass fiber reinforced plastic composites, Taguchi method

Procedia PDF Downloads 258

Authors: Supriya Patibanda, Xiaopeng Gong, Krishna N. Jonnalagadda, Ralph Abrahams

Abstract:

Yttria stabilized zirconia (YSZ) is used as a top coat in thermal barrier coatings in high-temperature turbine/jet engine applications. The mechanical behaviour of YSZ depends on the microstructural features like crack density and porosity, which are a result of coating method. However, experimentally ascertaining their individual effect is difficult due to the inherent challenges involved like material synthesis and handling. The current work deals with the development of a phenomenological model to replicate the tensile behavior of air plasma sprayed YSZ obtained from experiments. Initially, uniaxial tensile experiments were performed on freestanding YSZ coatings of ~300 µm thick for different crack densities and porosities. The coatings exhibited a nonlinear behavior and also a huge variation in strength values. With the obtained experimental tensile curve as a base and crack density and porosity as prime variables, a phenomenological model was developed using ABAQUS interface with new user material defined employing VUMAT sub routine. The relation between the tensile stress and the crack density was empirically established. Further, a parametric study was carried out to investigate the effect of the individual features on the non-linearity in these coatings. This work enables to generate new coating designs by varying the key parameters and predicting the mechanical properties with the help of a simulation, thereby minimizing experiments.

Keywords: crack density, finite element method, plasma sprayed coatings, VUMAT

Procedia PDF Downloads 148

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

Abstract:

Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 194

Authors: Mina Hojat Ansari, Kamran Bagheri Lankarani, Mohammad Reza Fattahi, Ali Reza Safarpour

Abstract:

Irritable bowel syndrome (IBS) is a common bowel disorder which is usually diagnosed through the abdominal pain, fecal irregularities and bloating. Alteration in the intestinal microbial composition is implicating to inflammatory and functional bowel disorders which is recently also noted as an IBS feature. Owing to the potential importance of microbiota implication in both efficiencies of the treatment and prevention of the diseases, we examined the association between the intestinal microbiota and different bowel patterns in a cohort of subjects with IBS and healthy controls. Fresh fecal samples were collected from a total of 50 subjects, 30 of whom met the Rome IV criteria for IBS and 20 Healthy control. Total DNA was extracted and library preparation was conducted following the standard protocol for small whole genome sequencing. The pooled libraries sequenced on an Illumina Nextseq platform with a 2 × 150 paired-end read length and obtained sequences were analyzed using several bioinformatics programs. The majority of sequences obtained in the current study assigned to bacteria. However, our finding highlighted the significant microbial taxa variation among the studied groups. The result, therefore, suggests a significant association of the microbiota with symptoms and bowel characteristics in patients with IBS. These alterations in fecal microbiota could be exploited as a biomarker for IBS or its subtypes and suggest the modification of the microbiota might be integrated into prevention and treatment strategies for IBS.

Keywords: irritable bowel syndrome, intestinal microbiota, small whole genome sequencing, fecal samples, Illumina

Procedia PDF Downloads 166

Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

Abstract:

This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

Procedia PDF Downloads 120

Authors: Ahmad Idris, O.A. Uche, Ado Y Abdulfatah

Abstract:

Lateritic soils are found in abundance and are the most common types of soils used in construction of roads and embankments in Nigeria. Strength properties of the soils depend on the amount of compaction applied and the amount of water available in the soil at the time of compaction. In this study, the influence of the compactive effort and that of the amount of water in the soil in the determination of the shear strength properties of lateritic soil was investigated. Lateritic soil sample was collected from an existing borrow pit in Kano, Nigeria and its basic characteristics were determined and the soil was classified according to AASHTO classification method. The soil was then compacted under various compactive efforts and at wide range of moisture contents. The maximum dry density (MDD) and optimum moisture content (OMC) at each compactive effort was determined. Unconfined undrained triaxial test was carried out to determine the shear strength properties of the soil under various conditions of moisture and energy. Preliminary results obtained indicated that the soil is an A-7-5 soil. The final results obtained shows that as the compaction energy is increased, both the cohesion and friction angle increased irrespective of the moisture content used in the compaction. However, when the amount of water in the soil was increased and compaction effort kept constant, only the cohesion of the soil increases while the friction angle shows no any pattern of variation. It was also found that the highest values for cohesion and friction angle were obtained when the soil was compacted at the highest energy and at OMC.

Keywords: laterite, OMC, compaction energy, moisture content

Procedia PDF Downloads 407

Authors: Jan Jezek, Zdenek Pilat, Filip Smatlo, Pavel Zemanek

Abstract:

We present a device that combines fluorescence spectroscopy with fiber optics and dielectrophoretic micromanipulation in PDMS (poly-(dimethylsiloxane)) microfluidic chips. The device allows high speed detection (in the order of kHz) of the fluorescence signal, which is coming from the sample by an inserted optical fiber, e.g. from a micro-droplet flow in a microfluidic chip, or even from the liquid flowing in the transparent capillary, etc. The device uses a laser diode at a wavelength suitable for excitation of fluorescence, excitation and emission filters, optics for focusing the laser radiation into the optical fiber, and a highly sensitive fast photodiode for detection of fluorescence. The device is combined with dielectrophoretic sorting on a chip for sorting of micro-droplets according to their fluorescence intensity. The electrodes are created by lift-off technology on a glass substrate, or by using channels filled with a soft metal alloy or an electrolyte. This device found its use in screening of enzymatic reactions and sorting of individual fluorescently labelled microorganisms. The authors acknowledge the support from the Grant Agency of the Czech Republic (GA16-07965S) and Ministry of Education, Youth and Sports of the Czech Republic (LO1212) together with the European Commission (ALISI No. CZ.1.05/2.1.00/01.0017).

Keywords: dielectrophoretic sorting, fiber optics, laser, microfluidic chips, microdroplets, spectroscopy

Procedia PDF Downloads 719

Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

Abstract:

Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score

Procedia PDF Downloads 424

Authors: Akila Tayeb-Benmachiche, Saber-Mustapha Zendaoui, Salah-Eddine Bouaoud, Bachir Zouchoune

Abstract:

The variation of the metal coordination site in π-coordinated polycyclic aromatic hydrocarbons (PAH) corresponds to the haptotropic rearrangement or haptotropic migration in which the metal fragment MLn is considered as the moveable moiety that is shifted between two rings of polycyclic or heteropolycyclic ligands. These structural characteristics and dynamical properties give to this category of transition metal complexes a considerable interest. We have investigated the coordination and the haptotropic shifts of (CO)3Ti and CpV moieties over the phenanthridine aromatic system and according to the metal atom nature. The optimization of (CO)3Ti(PHND) and CpV(PHND), using the Amsterdam Density Functional (ADF) program, without a symmetrical restriction of geometry gives an η6 coordination mode of the C6 and C5N rings, which in turn give rise to a six low-lying deficient 16-MVE of each (CO)3Ti(PHND) and CpV(PHND) structure (three singlet and three triplet state structures for Ti complexes and three triplet and three quintet state structures for V complexes). Thus, the η6–η6 haptotropic migration of the metal fragment MLn from the terminal C6 ring to the central C5N ring has been achieved by a loss of energy. However, its η6–η6 haptotropic migration from central C5N ring to the terminal C6 rings has been accomplished by a gain of energy. These results show the capability of the phenanthridine ligand to adapt itself to the electronic demand of the metal in agreement with the nature of the metal–ligand bonding and demonstrate that this theoretical study can also be applied to large fused π-systems.

Keywords: electronic structure, bonding analysis, density functional theory, coordination chemistry haptotropic migration

Procedia PDF Downloads 301

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

Abstract:

Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

Procedia PDF Downloads 155

Authors: Arka Roy, Chandra Prakash Dubey

Abstract:

Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

Procedia PDF Downloads 212

Authors: R. Vetrimurugan, Terry Lim, M. J. Goodson, R. Nagarajan

Abstract:

This study investigates the cleaning performance of high intensity 360 kHz frequency on the removal of nano-dimensional and sub-micron particles from various surfaces, uniformity of the cleaning tank and run to run variation of cleaning process. The uniformity of the cleaning tank was measured by two different methods i.e 1. ppbTM meter and 2. Liquid Particle Counting (LPC) technique. In the second method, aluminium metal spacer components was placed at various locations of the cleaning tank (such as centre, top left corner, bottom left corner, top right corner, bottom right corner) and the resultant particles removed by 360 kHz frequency was measured. The result indicates that the energy was distributed more uniformly throughout the entire cleaning vessel even at the corners and edges of the tank when megasonic sweeping technology is applied. The result also shows that rinsing the parts with 360 kHz frequency at final rinse gives lower particle counts, hence higher cleaning efficiency as compared to other frequencies. When megasonic sweeping technology is applied each piezoelectric transducers will operate at their optimum resonant frequency and generates stronger acoustic cavitational force and higher acoustic streaming velocity. These combined forces are helping to enhance the particle removal and at the same time improve the overall cleaning performance. The multiple extractions study was also carried out for various frequencies to measure the cleaning potential and asymptote value.

Keywords: power distribution, megasonic sweeping, cavitation intensity, particle removal, laser particle counting, nano, submicron

Procedia PDF Downloads 418

Authors: Jiahe Ru, Yan Pang, Zhaomiao Liu

Abstract:

Necking processes of the Janus droplet generation in the cross-junction microchannels are experimentally and theoretically investigated. The two dispersed phases that are simultaneously shear by continuous phases are liquid paraffin wax and 100cs silicone oil, in which 80% glycerin aqueous solution is used as continuous phases. According to the variation of minimum neck width and thinning rate, the necking process is divided into two stages, including the two-dimensional extrusion and the three-dimensional extrusion. In the two-dimensional extrusion stage, the evolutions of the tip extension length for the two discrete phases begin with the same trend, and then the length of liquid paraffin is larger than silicone oil. The upper and lower neck interface profiles in Janus necking process are asymmetrical when the tip extension velocity of paraffin oil is greater than that of silicone oil. In the three-dimensional extrusion stage, the neck of the liquid paraffin lags behind that of the silicone oil because of the higher surface tension, and finally, the necking fracture position gradually synchronizes. When the Janus droplets pinch off, the interfacial tension becomes positive to drive the neck thinning. The interface coupling of the three phases can cause asymmetric necking of the neck interface, which affects the necking time and, ultimately, the droplet volume. This paper mainly investigates the thinning dynamics of the liquid-liquid interface in confined microchannels. The revealed results could help to enhance the physical understanding of the droplet generation phenomenon.

Keywords: neck interface, interface coupling, janus droplets, multiphase flow

Procedia PDF Downloads 128

Authors: Ankush Verma, Rohit Bishist

Abstract:

The present investigation was carried out at different locations of Shimla and Kinnaur district and nutrient analysis was done in the laboratory of Department of Silviculture and Agroforestry, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Distt. Solan, Himachal Pradesh during 2019-2020 with the objectives to study the seasonal variation in the nutritive value of different Quercus species and to study the farmers’ preference rating of fodder tress species. From each location leaf samples were collected at 3 months interval from each Quercus spp. The findings of the present study revealed that the nutritional traits of leaves of different Quercus species varied among different seasons throughout the year. The dry matter (61.12 to 64.99%), ether extract (4.07 to 4.42%), crude fibre (34.38 to 37.85%), neutral detergent fibre (57.70 to 61.54%), acid detergent fibre (44.64 to 48.51%), total ash (3.57 to 3.91%), acid insoluble ash (44.64 to 48.51%) and calcium (1.31 to 1.53%) increased with the maturity in the leaves of different Quercus species. While, crude protein (9.10 to 10.61%), nitrogen free extract (44.73 to 47.41%), organic matter (96.09 to 96.43%), and phosphorus (0.16 to 0.31%) decreased with the advancing maturity in the leaves of different Quercus species. Maximum mean values for dry matter (65.05%), ether extract (4.45%), crude fibre (40.82%), neutral detergent fibre (61.48%), acid detergent fibre (48.44%), and organic matter (96.67%) among different Quercus species were recorded in Quercus ilex, while, Maximum mean values for crude protein (10.54%), nitrogen free extract (50.53%), total ash (4.05%), acid insoluble ash (0.59%), calcium (1.61%) and phosphorus (0.40%) were recorded in Quercus leucotrichophora.

Keywords: nutritional evaluation, fodder species, crude protein, carbohydrates

Procedia PDF Downloads 88

Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

Procedia PDF Downloads 163

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

Abstract:

Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

Procedia PDF Downloads 339

Authors: Shu Tao

Abstract:

Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

Procedia PDF Downloads 369

Authors: Sayed Ahmed El Sayed, Osama M. Mesalhy, Mohamed A. Abdelatief

Abstract:

A numerical study has been conducted to clarify fluid flow characteristics, pressure distributions, and skin friction coefficient over a wing-shaped tubes bundle in staggered arrangement with the placement of longitudinal fins (LF) at downstream position of the tube. The air-side Rea were at 1.8 x 103 to 9.7 x 103. The tubes bundle were employed with various fin height [hf] and fin thickness (δ) from (2 mm ≤ hf ≤ 12 mm) and (1.5 mm ≤ δ ≤ 3.5 mm) respectively at the considered Rea range. The flow pattern around the staggered wing-shaped tubes bundle was predicted using the commercial CFD FLUENT 6.3.26 software package. The distribution of average skin friction coefficient around wing-shaped tubes bundle is studied. Correlation of pressure drop coefficient Pdc and skin friction coefficient (Cf) in terms of Rea, design parameters for the studied cases were presented. Results indicated that the values of Pdc for hf = 6 mm are lower than these of NOF and hf = 2 mm by about 11 % and 13 % respectively for considered Rea range. Cf decreases as Rea increases. LFTH with hf = 6 mm offers lower form drag than that with hf = 12 mm and that of NOF. The lowest values of the pumping power are achieved for arrangements of hf = 6 mm for the considered Rea range. δ has negligible effect on skin friction coefficient, while has a slightly variation in ∆Pa. The wing-shaped tubes bundle heat exchanger with hf = 6 mm has the lowest values of ∆Pa, Pdc, Cf, and pumping power and hence the best performance comparing with the other bundles. Comparisons between the experimental and numerical results of the present study and those obtained by similar previous studies showed good agreements.

Keywords: longitudinal fins, skin friction, flow characteristics, FLUENT, wing-shaped tubes

Procedia PDF Downloads 539

Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

Procedia PDF Downloads 229

Authors: Raymond Feng, Shadi Ghiasi

Abstract:

An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

Procedia PDF Downloads 61

Authors: M. Rodionov, Z. Dedovets

Abstract:

The article describes the theoretical concept of teaching secondary school students proof demonstration skills in mathematics. It describes in detail different levels of mastery of the concept of proof-which correspond to Piaget’s idea of there being three distinct and progressively more complex stages in the development of human reflection. Lessons for each level contain a specific combination of the visual-figurative components and deductive reasoning. It is vital at the transition point between levels to carefully and rigorously recalibrate teaching to reflect the development of more complex reflective understanding. This can apply even within the same age range, since students will develop at different speeds and to different potential. The authors argue that this requires an aware and adaptive approach to lessons to reflect this complexity and variation. The authors also contend that effective teaching which enables students to properly understand the implementation of proof arguments must develop specific competences. These are: understanding of the importance of completeness and generality in making a valid argument; being task focused; having an internalised locus of control and being flexible in approach and evaluation. These criteria must be correlated with the systematic application of corresponding methodologies which are best likely to achieve success. The particular pedagogical decisions which are made to deliver this objective are illustrated by concrete examples from the existing secondary school mathematics courses. The proposed theoretical concept formed the basis of the development of methodological materials which have been tested in 47 secondary schools.

Keywords: education, teaching of mathematics, proof, deductive reasoning, secondary school

Procedia PDF Downloads 242

Authors: Feten Chihi, Gabriella Varga

Abstract:

The world's most prevalent waste management strategy is landfills. However, it grew more difficult due to a lack of acceptable waste sites. In order to develop larger landfills and extend their lifespan, the purpose of this article is to expand the capacity of the construction by varying the slope's inclination and to examine its effect on the safety factor. The capacity change with tilt is mathematically determined. Using a new probabilistic calculation method that takes into account the heterogeneity of waste layers, the safety factor for various slope angles is examined. To assess the effect of slope variation on the overall safety of landfills, over a hundred computations were performed for each angle. It has been shown that capacity increases significantly with increasing inclination. Passing from 1:3 to 2:3 slope angles and from 1:3 to 1:2 slope angles, the volume of garbage that can be deposited increases by 40 percent and 25 percent, respectively, of the initial volume. The results of the safety factor indicate that slopes of 1:3 and 1:2 are safe when the standard method (homogenous waste) is used for computation. Using the new approaches, a slope with an inclination of 2:3 can be deemed safe, despite the fact that the calculation does not account for the safety-enhancing effect of daily cover layers. Based on the study reported in this paper, the malty layered nonhomogeneous calculating technique better characterizes the safety factor. As it more closely resembles the actual state of landfills, the employed technique allows for more flexibility in design parameters. This work represents a substantial advance in limiting both safe and economical landfills.

Keywords: landfill, municipal solid waste, slope inclination, capacity, safety factor

Procedia PDF Downloads 186

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

Procedia PDF Downloads 71

Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

Abstract:

Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

Procedia PDF Downloads 58

Authors: Nicholas Reinicke, Brennan Borlaug, Matthew Moniot

Abstract:

The COVID-19 pandemic has resulted in a significant change in driving behavior as people respond to the new environment. However, existing methods for analyzing driver behavior, such as travel surveys and travel demand models, are not suited for incorporating abrupt environmental disruptions. To address this, we analyze a set of high-resolution trip data and introduce two new metrics for quantifying driving behavioral shifts as a function of time, allowing us to compare the time periods before and after the pandemic began. We apply these metrics to the Denver, Colorado metropolitan statistical area (MSA) to demonstrate the utility of the metrics. Then, we present a case study for comparing two distinct MSAs, Louisville, Kentucky, and Des Moines, Iowa, which exhibit significant differences in the makeup of their labor markets. The results indicate that although the regions of study exhibit certain unique driving behavioral shifts, emerging trends can be seen when comparing between seemingly distinct regions. For instance, drivers in all three MSAs are generally shown to have spent more time at residential locations and less time in workplaces in the time period after the pandemic started. In addition, workplaces that may be incompatible with remote working, such as hospitals and certain retail locations, generally retained much of their pre-pandemic travel activity.

Keywords: COVID-19, driver behavior, GPS data, signal analysis, telework

Procedia PDF Downloads 111

Authors: M. Solairaju, Nithin J. Thomas, S. Ganesan

Abstract:

Each and every rotating part of a machine element consists of bearings within its structure. In particular, the rolling element bearings such as cylindrical roller bearing and deep groove ball bearings are frequently used. Improper handling, excessive loading, improper lubrication and sealing cause bearing damage. Hence health monitoring of bearings is an important aspect for radiation pattern of bearing vibration is computed using the dipole model. Sound pressure level for defect-free and race defect the prolonged life of machinery and auto motives. This paper presents modeling and analysis of Acoustic response of deep groove ball bearing with localized race defects. Most of the ball bearings, especially in machine tool spindles and high-speed applications are pre-loaded along an axial direction. The present study is carried out with axial preload. Based on the vibration response, the orbit motion of the inner race is studied, and it was found that the oscillation takes place predominantly in the axial direction. Simplified acoustic is estimated. Acoustic response shows a better indication in identifying the defective bearing. The computed sound signal is visualized in diagrammatic representation using Symmetrised Dot Pattern (SDP). SDP gives better visual distinction between the defective and defect-free bearing

Keywords: bearing, dipole, noise, sound

Procedia PDF Downloads 294

Authors: Arvind Mittal, Rajesh Gupta

Abstract:

Influence of heat input on the micro structure and mechanical properties of shield metal arc welded of duplex stainless steel UNSNO.S-31803 has been investigated. Three heat input combinations designated as low heat (0.675 KJ/mm), medium heat (0.860 KJ/mm) and high heat (1.094 KJ/mm) and weld joints made using these combinations were subjected to micro structural evaluations and tensile and impact testing so as to analyze the effect of thermal arc energy on the micro structure and mechanical properties of these joints. The result of this investigation shows that the joints made using low heat input exhibited higher tensile strength than those welded with medium and high heat input. Heat affected zone of welded joint made with medium heat input has austenitic ferritic grain structure with some patchy austenite provide high toughness. Significant grain coarsening was observed in the heat affected zone (HAZ) of medium and high heat input welded joints, whereas low heat input welded joint shows the fine grain structure in the heat affected zone with small amount of dendritic formation and equiaxed grain structure where inner zone indicates slowly cooled grains in the direction of heat dissipation. This is the main reason for the observable changes of tensile properties of weld joints welded with different arc energy inputs.

Keywords: microstructure, mechanical properties, shield metal arc welded, duplex stainless steel

Procedia PDF Downloads 279

Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

Abstract:

Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

Procedia PDF Downloads 397

Authors: K. Raja Rajan, D. Nagarajan

Abstract:

Bored cast in-situ pile is a popular choice amongst consultant and contractor due to the ability to adjust the pile length suitably in case if any variation found in the actual geological strata. Bangladesh geological strata are dominated by silt content. Design is normally based on field test such as Standard Penetration test N-values. Initially, pile capacity estimated through static formula with co-relation of N-value and angle of internal friction. Initial pile load test was conducted in order to validate the geotechnical parameters assumed in design. Initial pile load test was conducted on 1.5m diameter bored cast in-situ pile. Kentledge method is used to load the pile for 2.5 times of its working load. Initially, safe working load of pile has been estimated as 570T, so test load is fixed to 1425T. Max load applied is 777T for which the settlement reached around 155mm which is more than 10% of diameter of piles. Pile load test results was not satisfactory and compelled to increase the pile length approximately 20% of its total length. Due to unpredictable geotechnical parameters, length of each pile has been increased which is having a major impact on the project cost and as well as in project schedule. Extra bore holes have been planned along with lab test results in order to redefine the assumed geotechnical parameters. This article presents detailed design assumptions of geotechnical parameters in the design stage and the results of pile load test which made to redefine the assumed geotechnical properties.

Keywords: end bearing, pile load test, settlement, shaft friction

Procedia PDF Downloads 265