Search results for: distance decay gradient
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2949

Search results for: distance decay gradient

2589 Optical Repeater Assisted Visible Light Device-to-Device Communications

Authors: Samrat Vikramaditya Tiwari, Atul Sewaiwar, Yeon-Ho Chung

Abstract:

Device-to-device (D2D) communication is considered a promising technique to provide wireless peer-to-peer communication services. Due to increasing demand on mobile services, available spectrum for radio frequency (RF) based communications becomes scarce. Recently, visible light communications (VLC) has evolved as a high speed wireless data transmission technology for indoor environments with abundant available bandwidth. In this paper, a novel VLC based D2D communication that provides wireless peer-to-peer communication is proposed. Potential low operating power devices for an efficient D2D communication over increasing distance of separation between devices is analyzed. Optical repeaters (OR) are also proposed to enhance the performance in an environment where direct D2D communications yield degraded performance. Simulation results show that VLC plays an important role in providing efficient D2D communication up to a distance of 1 m between devices. It is also found that the OR significantly improves the coverage distance up to 3.5 m.

Keywords: visible light communication, light emitting diode, device-to-device, optical repeater

Procedia PDF Downloads 455
2588 Utility of Range of Motion Measurements on Classification of Athletes

Authors: Dhiraj Dolai, Rupayan Bhattacharya

Abstract:

In this study, a comparison of Range Of Motion (ROM) of middle and long-distance runners and swimmers has been made. The mobility of the various joints is essential for the quick movement of any sportsman. Knowledge of a ROM helps in preventing injuries, in repeating the movement, and in generating speed and power. ROM varies among individuals, and it is influenced by factors such as gender, age, and whether the motion is performed actively or passively. ROM for running and swimming, both performed with due consideration on speed, plays an important role. The time of generation of speed and mobility of the particular joints are very important for both kinds of athletes. The difficulties that happen during running and swimming in the direction of motion is changed. In this study, data were collected for a total of 102 subjects divided into three groups: control group (22), middle and long-distance runners (40), and swimmers (40), and their ages are between 12 to 18 years. The swimmers have higher ROM in shoulder joint flexion, extension, abduction, and adduction movement. Middle and long-distance runners have significantly greater ROM from Control Group in the left shoulder joint flexion with a 5.82 mean difference. Swimmers have significantly higher ROM from the Control Group in the left shoulder joint flexion with 24.84 mean difference and swimmers have significantly higher ROM from the Middle and Long distance runners in left shoulder flexion with 19.02 mean difference. The picture will be clear after a more detailed investigation.

Keywords: range of motion, runners, swimmers, significance

Procedia PDF Downloads 100
2587 Construal Level Perceptions of Environmental vs. Social Sustainability in Online Fashion Shopping Environments

Authors: Barbara Behre, Verolien Cauberghe, Dieneke Van de Sompel

Abstract:

Sustainable consumption is on the rise, yet it has still not entered the mainstream in several industries, such as the fashion industry. In online fashion contexts, sustainability cues have been used to signal the sustainable benefits of certain garments to promote sustainable consumption. These sustainable cues may focus on the ecological or social dimension of sustainability. Since sustainability, in general, relates to distant, abstract benefits, the current study aims to examine if and how psychological distance may mediate the effects of exposure to different sustainability cues on consumption outcomes. Following the framework of Construal Level Theory of Psychological Distance, reduced psychological distance renders the construal level more concrete, which may influence attitudes and subsequent behavior in situations like fashion shopping. Most studies investigated sustainability as a composite, failing to differentiate between ecological and societal aspects of sustainability. The few studies examining sustainability more in detail uncovered that environmental sustainability is rather perceived in abstract cognitive construal, whereas social sustainability is linked to concrete construal. However, the construal level affiliation of the sustainability dimensions likely is not universally applicable to different domains and stages of consumption, which further suggest a need to clarify the relationships between environmental and social sustainability dimensions and the construal level of psychological distance within fashion brand consumption. While psychological distance and construal level have been examined in the context of sustainability, these studies yielded mixed results. The inconsistent findings of past studies might be due to the context-dependence of psychological distance as inducing construal differently in diverse situations. Especially in a hedonic consumption context like online fashion shopping, the role of visual processing of information could determine behavioural outcomes as linked to situational construal. Given the influence of the mode of processing on psychological distance and construal level, the current study examines the moderating role of verbal versus non-verbal presentation of the sustainability cues. In a 3 (environmental sustainability vs. social sustainability vs. control) x 2 (non-verbal message vs. verbal message) between subjects experiment, the present study thus examines how consumers evaluate sustainable brands in online shopping contexts in terms of psychological distance and construal level, as well as the impact on brand attitudes and buying intentions. The results among 246 participants verify the differential impact of the sustainability dimensions on fashion brand purchase intent as mediated by construal level and perceived psychological distance. The ecological sustainability cue is perceived as more concrete, which might be explained by consumer bias induced by the predominance of pro-environmental sustainability messages. The verbal versus non-verbal presentation of the sustainability cue neither had a significant influence on distance perceptions and construal level nor on buying intentions. This study offers valuable contributions to the sustainable consumption literature, as well as a theoretical basis for construal-level framing as applied in sustainable fashion branding.

Keywords: construal level theory, environmental vs social sustainability, online fashion shopping, sustainable fashion

Procedia PDF Downloads 81
2586 Constructal Enhancement of Fins Design Integrated to Phase Change Materials

Authors: Varun Joshi, Manish K. Rathod

Abstract:

The latent heat thermal energy storage system is a thrust area of research due to exuberant thermal energy storage potential. The thermal performance of PCM is significantly augmented by installation of the high thermal conductivity fins. The objective of the present study is to obtain optimum size and location of the fins to enhance diffusion heat transfer without altering overall melting time. Hence, the constructal theory is employed to eliminate, resize, and re-position the fins. A numerical code based on conjugate heat transfer coupled enthalpy porosity approached is developed to solve Navier-Stoke and energy equation.The numerical results show that the constructal fin design has enhanced the thermal performance along with the increase in the overall volume of PCM when compared to conventional. The overall volume of PCM is found to be increased by half of total of volume of fins. The elimination and repositioning the fins at high temperature gradient from low temperature gradient is found to be vital.

Keywords: constructal theory, enthalpy porosity approach, phase change materials, fins

Procedia PDF Downloads 159
2585 Comparison of Electrical Parameters of Oil-Immersed and Dry-Type Transformer Using Finite Element Method

Authors: U. Amin, A. Talib, S. A. Qureshi, M. J. Hossain, G. Ahmad

Abstract:

The choice evaluation between oil-immersed and dry-type transformers is often controlled by cost, location, and application. This paper compares the electrical performance of liquid- filled and dry-type transformers, which will assist the customer to choose the right and efficient ones for particular applications. An accurate assessment of the time-average flux density, electric field intensity and voltage distribution in an oil-insulated and a dry-type transformer have been computed and investigated. The detailed transformer modeling and analysis has been carried out to determine electrical parameter distributions. The models of oil-immersed and dry-type transformers are developed and solved by using the finite element method (FEM) to compare the electrical parameters. The effects of non-uniform and non-coherent voltage gradient, flux density and electric field distribution on the power losses and insulation properties of transformers are studied in detail. The results show that, for the same voltage and kilo-volt-ampere (kVA) rating, oil-immersed transformers have better insulation properties and less hysteresis losses than the dry-type.

Keywords: finite element method, flux density, transformer, voltage gradient

Procedia PDF Downloads 252
2584 Multi-Vehicle Detection Using Histogram of Oriented Gradients Features and Adaptive Sliding Window Technique

Authors: Saumya Srivastava, Rina Maiti

Abstract:

In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 94
2583 An Optimized Method for 3D Magnetic Navigation of Nanoparticles inside Human Arteries

Authors: Evangelos G. Karvelas, Christos Liosis, Andreas Theodorakakos, Theodoros E. Karakasidis

Abstract:

In the present work, a numerical method for the estimation of the appropriate gradient magnetic fields for optimum driving of the particles into the desired area inside the human body is presented. The proposed method combines Computational Fluid Dynamics (CFD), Discrete Element Method (DEM) and Covariance Matrix Adaptation (CMA) evolution strategy for the magnetic navigation of nanoparticles. It is based on an iteration procedure that intents to eliminate the deviation of the nanoparticles from a desired path. Hence, the gradient magnetic field is constantly adjusted in a suitable way so that the particles’ follow as close as possible to a desired trajectory. Using the proposed method, it is obvious that the diameter of particles is crucial parameter for an efficient navigation. In addition, increase of particles' diameter decreases their deviation from the desired path. Moreover, the navigation method can navigate nanoparticles into the desired areas with efficiency approximately 99%.

Keywords: computational fluid dynamics, CFD, covariance matrix adaptation evolution strategy, discrete element method, DEM, magnetic navigation, spherical particles

Procedia PDF Downloads 112
2582 Investigation of Azol Resistance in Aspergillosis Caused by Gradient Test and Agar Plaque Methods

Authors: Zeynep Yazgan, Gökhan Aygün, Reyhan Çalışkan

Abstract:

Objective: Invasive fungal infections are a serious threat in terms of morbidity and mortality, especially in immunocompromised patients. The most frequently isolated agents are Aspergillus genus fungi, and sensitivity to azoles, which are the first choice in treatment, decreases. In our study, we aimed to investigate the use of the agar plate screening method as a fast, easy, and practical method in determining azole resistance in Aspergillus spp. species. Methods: Our study was conducted with 125 Aspergillus spp. isolates produced from various clinical samples. Aspergillus spp. isolates were identified by conventional methods and azole resistance was determined by gradient test and agar plate screening method. Broth microdilution method was applied to resistant isolates, and CypA-L98H and CypA-M220 mutations in the cyp51A gene were investigated. Results: In our study, 55 A. fumigatus complex (44%), 42 A. flavus (33.6%), 6 A. terreus (5%), 4 A. niger (3%) and 18 Aspergillus spp. (14%) were identified. With the gradient test method, resistance to VOR and POS was detected in 1 (1.8%) of A.fumigatus isolates, and resistance to ITR was detected in 3 (5.45%). With the agar plate method, 1 of the A.fumigatus isolates (1.8%) had VOR, ITR, POS, 1 of the A.terreus isolates (16.7%) had VOR, 1 of the A.niger isolates (25%) had ITR. Resistance to VOR and POS was detected in 2 Aspergillus spp. isolates (11%), and resistance to ITR was detected in 1 (5.6%). Sensitivity and specificity were determined as 100% for VOR and POS in A. fumigatus species, 33.3% and 100% for ITR, respectively, 100% for ITR in A. flavus species, and 100% for ITR and POS in A. terreus species. By broth microdilution method in 7 isolates in which resistance was detected by gradient test and/or agar plate screening method; 1 A.fumigatus resistant to ITR, VOR, POS, 2 A.fumigatus resistant to ITR, 2 Aspergillus spp. ITR, VOR, POS MICs were determined as 2µg/ml and 8µg/ml, 8µg/ml and >32µg/ml, 0.5µg/ml and 4µg/ml, respectively. CypA-L98H mutations were detected in 5 of these isolates, CypA-M220 mutations were detected in 6, and no mutation was detected in 1. CypA-L98H and CypA-M220 mutations were detected in 1 isolate for which resistance was not detected. Conclusion: The need for rapid antifungal susceptibility screening tests is increasing in the treatment of aspergillosis. Although the sensitivity of the agar plate method was determined to be 33.3% for A.fumigatus ITR in our study, its sensitivity and specificity were determined to be 100% for ITR, VOR, and POS in other species. The low sensitivity value detected for A.fumigatus showed that agar plate drug concentrations should be updated in accordance with the latest regulations of EUCAST guidelines. The CypA-L98H and CypA-M220 mutations detected in our study suggested that the distribution of azole resistance-related mutations in different regions in our country should be investigated. In conclusion, it is thought that the agar plate method, which can be easily applied to detect azole resistance, is a fast and practical method in routine use and can contribute to both the determination of effective treatment strategies and the generation of epidemiological data.

Keywords: Aspergillus, agar plate, azole resistance, cyp51A, cypA-L98H, cypA-M220

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2581 Representativity Based Wasserstein Active Regression

Authors: Benjamin Bobbia, Matthias Picard

Abstract:

In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.

Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression

Procedia PDF Downloads 59
2580 Validating Quantitative Stormwater Simulations in Edmonton Using MIKE URBAN

Authors: Mohamed Gaafar, Evan Davies

Abstract:

Many municipalities within Canada and abroad use chloramination to disinfect drinking water so as to avert the production of the disinfection by-products (DBPs) that result from conventional chlorination processes and their consequential public health risks. However, the long-lasting monochloramine disinfectant (NH2Cl) can pose a significant risk to the environment. As, it can be introduced into stormwater sewers, from different water uses, and thus freshwater sources. Little research has been undertaken to monitor and characterize the decay of NH2Cl and to study the parameters affecting its decomposition in stormwater networks. Therefore, the current study was intended to investigate this decay starting by building a stormwater model and validating its hydraulic and hydrologic computations, and then modelling water quality in the storm sewers and examining the effects of different parameters on chloramine decay. The presented work here is only the first stage of this study. The 30th Avenue basin in Southern Edmonton was chosen as a case study, because the well-developed basin has various land-use types including commercial, industrial, residential, parks and recreational. The City of Edmonton has already built a MIKE-URBAN stormwater model for modelling floods. Nevertheless, this model was built to the trunk level which means that only the main drainage features were presented. Additionally, this model was not calibrated and known to consistently compute pipe flows higher than the observed values; not to the benefit of studying water quality. So the first goal was to complete modelling and updating all stormwater network components. Then, available GIS Data was used to calculate different catchment properties such as slope, length and imperviousness. In order to calibrate and validate this model, data of two temporary pipe flow monitoring stations, collected during last summer, was used along with records of two other permanent stations available for eight consecutive summer seasons. The effect of various hydrological parameters on model results was investigated. It was found that model results were affected by the ratio of impervious areas. The catchment length was tested, however calculated, because it is approximate representation of the catchment shape. Surface roughness coefficients were calibrated using. Consequently, computed flows at the two temporary locations had correlation coefficients of values 0.846 and 0.815, where the lower value pertained to the larger attached catchment area. Other statistical measures, such as peak error of 0.65%, volume error of 5.6%, maximum positive and negative differences of 2.17 and -1.63 respectively, were all found in acceptable ranges.

Keywords: stormwater, urban drainage, simulation, validation, MIKE URBAN

Procedia PDF Downloads 271
2579 Spatiotemporal Propagation and Pattern of Epileptic Spike Predict Seizure Onset Zone

Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger

Abstract:

Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.

Keywords: spike propagation, spike pattern, clustering, SOZ

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2578 Instability Index Method and Logistic Regression to Assess Landslide Susceptibility in County Route 89, Taiwan

Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

Abstract:

This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

Procedia PDF Downloads 260
2577 Design and Validation of Different Steering Geometries for an All-Terrain Vehicle

Authors: Prabhsharan Singh, Rahul Sindhu, Piyush Sikka

Abstract:

The steering system is an integral part and medium through which the driver communicates with the vehicle and terrain, hence the most suitable steering geometry as per requirements must be chosen. The function of the chosen steering geometry of an All-Terrain Vehicle (ATV) is to provide the desired understeer gradient, minimum tire slippage, expected weight transfer during turning as these are requirements for a good steering geometry of a BAJA ATV. This research paper focuses on choosing the best suitable steering geometry for BAJA ATV tracks by reasoning the working principle and using fundamental trigonometric functions for obtaining these geometries on the same vehicle itself, namely Ackermann, Anti- Ackermann, Parallel Ackermann. Full vehicle analysis was carried out on Adams Car Analysis software, and graphical results were obtained for various parameters. Steering geometries were achieved by using a single versatile knuckle for frontward and rearward tie-rod placement and were practically tested with the help of data acquisition systems set up on the ATV. Each was having certain characteristics, setup, and parameters were observed for the BAJA ATV, and correlations were created between analytical and practical values.

Keywords: all-terrain vehicle, Ackermann, Adams car, Baja Sae, steering geometry, steering system, tire slip, traction, understeer gradient

Procedia PDF Downloads 128
2576 Evaluation of the Power Generation Effect Obtained by Inserting a Piezoelectric Sheet in the Backlash Clearance of a Circular Arc Helical Gear

Authors: Barenten Suciu, Yuya Nakamoto

Abstract:

Power generation effect, obtained by inserting a piezo- electric sheet in the backlash clearance of a circular arc helical gear, is evaluated. Such type of screw gear is preferred since, in comparison with the involute tooth profile, the circular arc profile leads to reduced stress-concentration effects, and improved life of the piezoelectric film. Firstly, geometry of the circular arc helical gear, and properties of the piezoelectric sheet are presented. Then, description of the test-rig, consisted of a right-hand thread gear meshing with a left-hand thread gear, and the voltage measurement procedure are given. After creating the tridimensional (3D) model of the meshing gears in SolidWorks, they are 3D-printed in acrylonitrile butadiene styrene (ABS) resin. Variation of the generated voltage versus time, during a meshing cycle of the circular arc helical gear, is measured for various values of the center distance. Then, the change of the maximal, minimal, and peak-to-peak voltage versus the center distance is illustrated. Optimal center distance of the gear, to achieve voltage maximization, is found and its significance is discussed. Such results prove that the contact pressure of the meshing gears can be measured, and also, the electrical power can be generated by employing the proposed technique.

Keywords: circular arc helical gear, contact problem, optimal center distance, piezoelectric sheet, power generation

Procedia PDF Downloads 143
2575 Determination of Thermal Conductivity of Plaster Tow Material and Kapok Plaster by Numerical Method: Influence of the Heat Exchange Coefficient in Transitional Regime

Authors: Traore Papa Touty

Abstract:

This article presents a numerical method for determining the thermal conductivity of local materials, kapok plaster and tow plaster. It consists of heating the front face of a wall made from these two materials and at the same time insulating its rear face. We simultaneously study the curves of the evolution of the heat flux density as a function of time on the rear face and the evolution of the temperature gradient as a function of time between the heated face and the insulated face. Thermal conductivity is obtained when reaching a steady state when the evolution of the heat flux density and the temperature gradient no longer depend on time. The results showed that the theoretical value of thermal conductivity is obtained when the material has reached its equilibrium state. And the values obtained for different values of the convective exchange coefficients are appreciably equal to the experimental value.

Keywords: thermal conductivity, numerical method, heat exchange coefficient, transitional regime

Procedia PDF Downloads 186
2574 Review of Hydrologic Applications of Conceptual Models for Precipitation-Runoff Process

Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

Abstract:

The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

Procedia PDF Downloads 420
2573 [Keynote Talk]: Existence of Random Fixed Point Theorem for Contractive Mappings

Authors: D. S. Palimkar

Abstract:

Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

Procedia PDF Downloads 247
2572 The Morphology and Flash Flood Characteristics of the Transboundary Khowai River: A Catchment Scale Analysis

Authors: Jonahid Chakder, Mahfuzul Haque

Abstract:

Flash flood is among the foremost disastrous characteristic hazards which cause hampering within the environment and social orders due to climate change across the world. In Northeastern region of Bangladesh faces severe flash floods regularly, Such, the Khowai river is a flash flood-prone river. But until now, there are no previous studies about the flash flood of this river. Farmlands Building resilience, protection of crops & fish enclosures of wetland in Habiganj Haor areas, regional roads, and business establishments were submerged due to flash floods. The flash floods of the Khowai River are frequent events, which happened in 1988, 1998, 2000, 2007, 2017, and 2019. Therefore, this study tries to analyze Khowai river morphology, Precipitation, Water level, Satellite image, and Catchment characteristics: a catchment scale analysis that helps to comprehend Khowai river flash flood characteristics and factors of influence. From precipitation analysis, the finding outcome disclosed the data about flash flood accurate zones at the Khowai district watershed. The morphological analysis workout from satellite image and find out the consequence of sinuosity and gradient of this river. The sinuosity indicates that the Khowai river is an antecedent and a meandering river and a meandering river can’t influence the flash flood of any region, but other factors respond here. It is understood that the Khowai river catchment elevation analysis from DEM is directly influenced. The left Baramura and Right Atharamura anticline of the Khowai basin watershed reflects a major impact on the stratigraphy as an impermeable clay layer and this consequence the water passes downward with the drainage pattern and Tributary. This drainage system, the gradient of tributary and their runoff, and the confluence of water in the pre-monsoon season rise the Khowai river water level which influences flash floods (within six hours of Precipitation).

Keywords: geology, gradient, tributary, drainage, watershed, flash flood

Procedia PDF Downloads 96
2571 Modeling the Impacts of Road Construction on Lands Values

Authors: Maha Almumaiz, Harry Evdorides

Abstract:

Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

Procedia PDF Downloads 244
2570 A Comparative Study of k-NN and MLP-NN Classifiers Using GA-kNN Based Feature Selection Method for Wood Recognition System

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

Abstract:

This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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2569 On the Construction of Lightweight Circulant Maximum Distance Separable Matrices

Authors: Qinyi Mei, Li-Ping Wang

Abstract:

MDS matrices are of great significance in the design of block ciphers and hash functions. In the present paper, we investigate the problem of constructing MDS matrices which are both lightweight and low-latency. We propose a new method of constructing lightweight MDS matrices using circulant matrices which can be implemented efficiently in hardware. Furthermore, we provide circulant MDS matrices with as few bit XOR operations as possible for the classical dimensions 4 × 4, 8 × 8 over the space of linear transformations over finite field F42 . In contrast to previous constructions of MDS matrices, our constructions have achieved fewer XORs.

Keywords: linear diffusion layer, circulant matrix, lightweight, maximum distance separable (MDS) matrix

Procedia PDF Downloads 382
2568 Preferred Character Size for Oblique Angles

Authors: Photjanat Phimnom, Haruetai Lohasiriwat

Abstract:

In today’s world, the LED display has been used for presenting visual information under various circumstances. Such information is an important intermediary in the human information processing. Researchers have been investigated diverse factors that influence this process effectiveness. The letter size is undoubtedly one major factor that has been tested and recommended by many standards and guidelines. However, viewing information on the display from direct perpendicular position is a typical assumption whereas many actual events are required viewing from the angles. This current research aims to study the effect of oblique viewing angle and viewing distance on ability to recognize alphabet, number, and English word. The total of ten participants was volunteered to our 3 x 4 x 4 within subject study. Independent variables include three distance levels (2, 6, and 12 m), four oblique angle (0, 45, 60, 75 degree), and four target types (alphabet, number, short words, and long words). Following the method of constant stimuli we found that the larger oblique angle, ranging from 0 to 75 degree from the line of sight, results in significant higher legibility threshold or larger font size required (p-value < 0.05). Viewing distance factor also shows to have significant effect on the threshold (p-value < 0.05). However, the effect from distance factor is expected to be confounded by the quality of the screen we used in our experiment. Lastly, our results show that single alphabet as well as single number are recognized at significant lower threshold (smaller font size) as compared to both short and long words (p-value < 0.05). Therefore, it is recommended that when designs information to be presented on LED display, understanding of all possible ranges of oblique angle should be taken into account in order to specify the preferred letter size. Additionally, the recommendation of letter size for 100 % readability in our tested conditions is provided in the paper.

Keywords: letter size, oblique angle, viewing distance, legibility threshold

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2567 Optimization Principles of Eddy Current Separator for Mixtures with Different Particle Sizes

Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

Abstract:

The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

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2566 Seismic Base Shear Force Depending on Building Fundamental Period and Site Conditions: Deterministic Formulation and Probabilistic Analysis

Authors: S. Dorbani, M. Badaoui, D. Benouar

Abstract:

The aim of this paper is to investigate the effect of the building fundamental period of reinforced concrete buildings of (6, 9, and 12-storey), with different floor plans: Symmetric, mono-symmetric, and unsymmetric. These structures are erected at different epicentral distances. Using the Boumerdes, Algeria (2003) earthquake data, we focused primarily on the establishment of the deterministic formulation linking the base shear force to two parameters: The first one is the fundamental period that represents the numerical fingerprint of the structure, and the second one is the epicentral distance used to represent the impact of the earthquake on this force. In a second step, with a view to highlight the effect of uncertainty in these parameters on the analyzed response, these parameters are modeled as random variables with a log-normal distribution. The variability of the coefficients of variation of the chosen uncertain parameters, on the statistics on the seismic base shear force, showed that the effect of uncertainty on fundamental period on this force statistics is low compared to the epicentral distance uncertainty influence.

Keywords: base shear force, fundamental period, epicentral distance, uncertainty, lognormal variables, statistics

Procedia PDF Downloads 294
2565 "Empowering Minds and Unleashing Curiosity: DIY Biotechnology for High School Students in the Age of Distance Learning"

Authors: Victor Hugo Sanchez Rodriguez

Abstract:

Amidst the challenges posed by pandemic-induced lockdowns, traditional educational models have been disrupted. To bridge the distance learning gap, our project introduces an innovative initiative focused on teaching high school students basic biotechnology techniques. We aim to empower young minds and foster curiosity by encouraging students to create their own DIY biotechnology laboratories using easily accessible materials found at home. This abstract outlines the key aspects of our project, highlighting its importance, methodology, and evaluation approach.In response to the pandemic's limitations, our project targets the delivery of biotechnology education at a distance. By engaging students in hands-on experiments, we seek to provide an enriching learning experience despite the constraints of remote learning. The DIY approach allows students to explore scientific concepts in a practical and enjoyable manner, nurturing their interest in biotechnology and molecular biology. Originally designed to assess professional-level research programs, we have adapted the URSSA to suit the context of biotechnology and molecular biology synthesis for high school students. By applying this tool before and after the experimental sessions, we aim to gauge the program's impact on students' learning experiences and skill development. Our project's significance lies not only in its novel approach to teaching biotechnology but also in its adaptability to the current global crisis. By providing students with a stimulating and interactive learning environment, we hope to inspire educators and institutions to embrace creative solutions during challenging times. Moreover, the insights gained from our evaluation will inform future efforts to enhance distance learning programs and promote accessible science education.

Keywords: DIY biotechnology, high school students, distance learning, pandemic education, undergraduate research student self-assessment (URSSA)

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2564 Study of the Transport of ²²⁶Ra Colloidal in Mining Context Using a Multi-Disciplinary Approach

Authors: Marine Reymond, Michael Descostes, Marie Muguet, Clemence Besancon, Martine Leermakers, Catherine Beaucaire, Sophie Billon, Patricia Patrier

Abstract:

²²⁶Ra is one of the radionuclides resulting from the disintegration of ²³⁸U. Due to its half-life (1600 y) and its high specific activity (3.7 x 1010 Bq/g), ²²⁶Ra is found at the ultra-trace level in the natural environment (usually below 1 Bq/L, i.e. 10-13 mol/L). Because of its decay in ²²²Rn, a radioactive gas with a shorter half-life (3.8 days) which is difficult to control and dangerous for humans when inhaled, ²²⁶Ra is subject to a dedicated monitoring in surface waters especially in the context of uranium mining. In natural waters, radionuclides occur in dissolved, colloidal or particular forms. Due to the size of colloids, generally ranging between 1 nm and 1 µm and their high specific surface areas, the colloidal fraction could be involved in the transport of trace elements, including radionuclides in the environment. The colloidal fraction is not always easy to determine and few existing studies focus on ²²⁶Ra. In the present study, a complete multidisciplinary approach is proposed to assess the colloidal transport of ²²⁶Ra. It includes water sampling by conventional filtration (0.2µm) and the innovative Diffusive Gradient in Thin Films technique to measure the dissolved fraction (<10nm), from which the colloidal fraction could be estimated. Suspended matter in these waters were also sampled and characterized mineralogically by X-Ray Diffraction, infrared spectroscopy and scanning electron microscopy. All of these data, which were acquired on a rehabilitated former uranium mine, allowed to build a geochemical model using the geochemical calculation code PhreeqC to describe, as accurately as possible, the colloidal transport of ²²⁶Ra. Colloidal transport of ²²⁶Ra was found, for some of the sampling points, to account for up to 95% of the total ²²⁶Ra measured in water. Mineralogical characterization and associated geochemical modelling highlight the role of barite, a barium sulfate mineral well known to trap ²²⁶Ra into its structure. Barite was shown to be responsible for the colloidal ²²⁶Ra fraction despite the presence of kaolinite and ferrihydrite, which are also known to retain ²²⁶Ra by sorption.

Keywords: colloids, mining context, radium, transport

Procedia PDF Downloads 130
2563 Iterative Segmentation and Application of Hausdorff Dilation Distance in Defect Detection

Authors: S. Shankar Bharathi

Abstract:

Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

Procedia PDF Downloads 391
2562 Application of Web Aided Education on Laboratory of the Physics Course

Authors: Nigmet Koklu, Dundar Yener

Abstract:

Recently, distance education that make use of web technology is used widely all around the world to overcome geographical and time based problems in education. Graphics, animation and other auxiliary visual sources help student to understand the subjects easily. Especially some theoretical courses that are quite difficult to understand such as physics and chemistry require visual material for students to understand topics clearly. In this study, physics applications for laboratory of physics course were developed. All facilities of web-based educational technology were used for students in laboratory studies to avoid making mistakes and to learn better physics subjects.

Keywords: physics education, laboratory, web-based education, distance education

Procedia PDF Downloads 478
2561 Effects of Learner-Content Interaction Activities on the Context of Verbal Learning Outcomes in Interactive Courses

Authors: Alper Tolga Kumtepe, Erdem Erdogdu, M. Recep Okur, Eda Kaypak, Ozlem Kaya, Serap Ugur, Deniz Dincer, Hakan Yildirim

Abstract:

Interaction is one of the most important components of open and distance learning. According to Moore, who proposed one of the keystones on interaction types, there are three basic types of interaction: learner-teacher, learner-content, and learner-learner. From these interaction types, learner-content interaction, without doubt, can be identified as the most fundamental one on which all education is based. Efficacy, efficiency, and attraction of open and distance learning systems can be achieved by the practice of effective learner-content interaction. With the development of new technologies, interactive e-learning materials have been commonly used as a resource in open and distance learning, along with the printed books. The intellectual engagement of the learners with the content that is course materials may also affect their satisfaction for the open and distance learning practices in general. Learner satisfaction holds an important place in open and distance learning since it will eventually contribute to the achievement of learning outcomes. Using the learner-content interaction activities in course materials, Anadolu University, by its Open Education system, tries to involve learners in deep and meaningful learning practices. Especially, during the e-learning material design and production processes, identifying appropriate learner-content interaction activities within the context of learning outcomes holds a big importance. Considering the lack of studies adopting this approach, as well as its being a study on the use of e-learning materials in Open Education system, this research holds a big value in open and distance learning literature. In this respect, the present study aimed to investigate a) which learner-content interaction activities included in interactive courses are the most effective in learners’ achievement of verbal information learning outcomes and b) to what extent distance learners are satisfied with these learner-content interaction activities. For this study, the quasi-experimental research design was adopted. The 120 participants of the study were from Anadolu University Open Education Faculty students living in Eskişehir. The students were divided into 6 groups randomly. While 5 of these groups received different learner-content interaction activities as a part of the experiment, the other group served as the control group. The data were collected mainly through two instruments: pre-test and post-test. In addition to those tests, learners’ perceived learning was assessed with an item at the end of the program. The data collected from pre-test and post-test were analyzed by ANOVA, and in the light of the findings of this approximately 24-month study, suggestions for the further design of e-learning materials within the context of learner-content interaction activities will be provided at the conference. The current study is planned to be an antecedent for the following studies that will examine the effects of activities on other learning domains.

Keywords: interaction, distance education, interactivity, online courses

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2560 Advancements in Predicting Diabetes Biomarkers: A Machine Learning Epigenetic Approach

Authors: James Ladzekpo

Abstract:

Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

Procedia PDF Downloads 24