Search results for: community based rehabilitation

Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

Procedia PDF Downloads 428

Authors: Elizabeth Crafton, Donald Ott, Teresa Cutright

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Harmful algal blooms (HABs), more notably cyanobacteria-dominated HABs, compromise water quality, jeopardize access to drinking water and are a risk to public health and safety. HABs are representative of ecosystem imbalance largely caused by environmental changes, such as eutrophication, that are associated with the globally expanding human population. Cyanobacteria-dominated HABs are anticipated to increase in frequency, magnitude, and are predicted to plague a larger geographical area as a result of climate change. The weather pattern is important as storm-driven, pulse-input of nutrients have been correlated to cyanobacteria-dominated HABs. The mobilization of aqueous and particulate nutrients and the response of the phytoplankton community is an important relationship in this complex phenomenon. This relationship is most apparent in high-impact areas of adequate sunlight, > 20ᵒC, excessive nutrients and quiescent water that corresponds to ideal growth of HABs. Typically the impact of particulate phosphorus is dismissed as an insignificant contribution; which is true for areas that are not considered high-impact. The objective of this study was to assess the impact of a simulated storm-driven, pulse-input of reactive phosphorus and the response of three different cyanobacteria assemblages (~5,000 cells/mL). The aqueous and particulate sources of phosphorus and changes in HAB were tracked weekly for 4 weeks. The first cyanobacteria composition consisted of Planktothrix sp., Microcystis sp., Aphanizomenon sp., and Anabaena sp., with 70% of the total population being non-diazotrophic and 30% being diazotrophic. The second was comprised of Anabaena sp., Planktothrix sp., and Microcystis sp., with 87% diazotrophic and 13% non-diazotrophic. The third composition has yet to be determined as these experiments are ongoing. Preliminary results suggest that both aqueous and particulate sources are contributors of total reactive phosphorus in high-impact areas. The results further highlight shifts in the cyanobacteria assemblage after the simulated pulse-input. In the controls, the reactors dosed with aqueous reactive phosphorus maintained a constant concentration for the duration of the experiment; whereas, the reactors that were dosed with aqueous reactive phosphorus and contained soil decreased from 1.73 mg/L to 0.25 mg/L of reactive phosphorus from time zero to 7 days; this was higher than the blank (0.11 mg/L). Suggesting a binding of aqueous reactive phosphorus to sediment, which is further supported by the positive correlation observed between total reactive phosphorus concentration and turbidity. The experiments are nearly completed and a full statistical analysis will be completed of the results prior to the conference.

Keywords: Anabaena, cyanobacteria, harmful algal blooms, Microcystis, phosphorous, response surface methodology

Procedia PDF Downloads 149

Authors: Wessam H. Abd-Elsalam, Mona M. Saber, Samar M. Abouelatta

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Non-steroidal anti-inflammatory drugs (NSAIDs) are considered a double edged sword in inflammatory bowel diseases (IBDs). Some studies reported their advantageous effect in decreasing inflammation, and other studies reported that their use is associated with colitis aggravation. This study aimed to use specifically formulated trehalose-based nano-carriers that targets the colon in an attempt to alleviate inflammation caused by NSAIDs. L-α-phosphatidylcholine (PL), trehalose, and transcutol were used to prepare the trehalosomes (THs), which were also loaded with Tenoxicam(TXM) as a model NSAID. To optimize the formulation variables, a full 23 factorial design, using Design-Expert® software, was performed. The optimized formulation composed of trehalose: PL at a weight ratio of 1:1, 377.72 mg transcutol, and sonicated for 4 min, possessed a spherical shape with a size of 268.61 nm and EE% of 97.83% and released 70.22% of its drug content over 24 h. The superior protective action of TXM loaded THs compared to TXM suspension and drug-free THs was shown by the inhibition of the inflammatory biomarkers, namely; IL-1ß, IL-6, and TNF-alpha levels, as well as oxidative stress markers, measured as GSH and MDA. Improved histopathology of the colonic tissue in male New Zealand rabbits also confirmed the superiority of the TXM loaded THs compared to the unformulated drug or the drug free nano-carriers. Our findings highlight the prosperous role of THs in colon targeting and its anti-inflammatory characteristics in guarding against possible NSAIDs-driven exacerbation of colitis.

Keywords: inflammatory bowel disease, trehalose, trehalosomes, colon targeting

Procedia PDF Downloads 124

Authors: Hooman Dabirmanesh, Attila M. Zsaki

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The toppling failure mode in a rock mass is considerably different from the most common sliding failure type along an existing or an induced slip plane. Block toppling is observed in a rock mass which consists of both a widely-spaced basal cross-joint set and a closely-spaced discontinuity set dipping into the slope. For this case, failure occurs when the structure cannot bear the tensile portion of bending stress, and the columns or blocks overturn by their own weight. This paper presents a particle-based discrete element model of rock blocks subjected to a toppling failure where geometric conditions and interaction among blocks are investigated. A series of parametric studies have been conducted on particles’ size, arrangement and bond contact among of particles which are made the blocks. Firstly, a numerical investigation on a one-block system was verified. Afterward, a slope consisting of multi-blocks was developed to study toppling failure and interaction forces between blocks. The results show that the formation of blocks, especially between the block and basal plane surface, can change the process of failure. The results also demonstrate that the initial configuration of particles used to form the blocks has a significant role in achieving accurate simulation results. The size of particles and bond contacts have a considerable influence to change the progress of toppling failure.

Keywords: block toppling failure, contact interaction, discrete element, particle size, random generation

Procedia PDF Downloads 180

Authors: Betim Bahtiri, B. Arash, R. Rolfes

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Epoxy-based materials are frequently exposed to high-humidity environments in many engineering applications. As a result, their material properties would be degraded by water absorption. A full characterization of the material properties under hygrothermal conditions requires time- and cost-consuming experimental tests. To gain insights into the physics of diffusion mechanisms, atomistic simulations have been shown to be effective tools. Concerning the diffusion of water in polymers, spatial trajectories of water molecules are obtained from molecular dynamics (MD) simulations allowing the interpretation of diffusion pathways at the nanoscale in a polymer network. Conventional MD simulations of water diffusion in amorphous polymers lead to discrepancies at low temperatures due to the short timescales of the simulations. In the proposed model, this issue is solved by using a combined scheme of autonomous basin climbing (ABC) with kinetic Monte Carlo and reactive MD simulations to investigate the diffusivity of water molecules in epoxy resins across a wide range of temperatures. It is shown that the proposed simulation framework estimates kinetic properties of water diffusion in epoxy resins that are consistent with experimental observations and provide a predictive tool for investigating the diffusion of small molecules in other amorphous polymers.

Keywords: epoxy resins, water diffusion, autonomous basin climbing, kinetic Monte Carlo, reactive molecular dynamics

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Authors: M. Wasy Akhtar

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Multi-modal film boiling simulations are carried out on adaptive octree grids. The liquid-vapor interface is captured using the volume-of-fluid framework adjusted to account for exchanges of mass, momentum, and energy across the interface. Surface tension effects are included using a volumetric source term in the momentum equations. The phase change calculations are conducted based on the exact location and orientation of the interface; however, the source terms are calculated using the mixture variables to be consistent with the one field formulation used to represent the entire fluid domain. The numerical model on octree representation of the computational grid is first verified using test cases including advection tests in severely deforming velocity fields, gravity-based instabilities and bubble growth in uniformly superheated liquid under zero gravity. The model is then used to simulate both single and multi-modal film boiling simulations. The octree grid is dynamically adapted in order to maintain the highest grid resolution on the instability fronts using markers of interface location, volume fraction, and thermal gradients. The method thus provides an efficient platform to simulate fluid instabilities with or without phase change in the presence of body forces like gravity or shear layer instabilities.

Keywords: boiling flows, dynamic octree grids, heat transfer, interface capturing, phase change

Procedia PDF Downloads 235

Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: Guanqiao Wang, Hongyang Yu

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There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. There- fore, robots appear more and more frequently in the construction industry. Navigation and positioning are very important tasks for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radiofrequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered, or the error of plastering the wall is large. A new positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.

Keywords: indoor plastering robot, navigation, precise positioning, line laser, image processing

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Authors: Javad Izadi, Sahar Majioud

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This study presents an approach of assessing the choice of performance measures of companies in the United Kingdom after the application of IFRS in 2005. The aim of this study is to investigate the effects of IFRS on the choice of performance evaluation methods for UK companies. We analyse through an econometric model the relationship of the dependent variable, the firm’s performance, which is a nominal variable with the independent ones. Independent variables are split into two main groups: the first one is the group of accounting-based measures: Earning per share, return on assets and return on equities. The second one is the group of market-based measures: market value of property plant and equipment, research and development, sales growth, market to book value, leverage, segment and size of companies. Concerning the regression used, it is a multinomial logistic regression performed on a sample of 130 UK listed companies. Our finding shows after IFRS adoption, and companies give more importance to some variables such as return on equities and sales growth to assess their performance, whereas the return on assets and market to book value ratio does not have as much importance as before IFRS in evaluating the performance of companies. Also, there are some variables that have no impact on the performance measures anymore, such as earning per share. This article finding is empirically important for business in subjects related to IFRS and companies’ performance measurement.

Keywords: performance’s Measure, nominal variable, econometric model, evaluation methods

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Madeline V. Henry

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Sex work is a contested subject in academia. Many authors now argue that the practice should be recognized as a legitimate and rationally chosen form of labor, and that decriminalization is necessary to ensure the safety of sex workers and reduce their stigmatization. However, a prevailing argument remains that the work is inherently violent and oppressive and that all sex workers are directly or indirectly coerced into participating in the industry. This argument has been complicated by the recent proliferation of computer-mediated technologies that allow people to conduct sex work without the need to be physically co-present with customers or pimps. One example of this is the practice of ‘camming’, wherein ‘webcam models’ stream themselves stripping and/or performing autoerotic stimulation in an online chat-room for payment. In this presentation, interviews with eight ‘camgirls’ (aged 22-34) will be discussed. Their talk has been analyzed using Foucauldian discourse analysis, focusing on common discursive threads in relation to the work and their subjectivities. It was found that the participants demonstrated appreciation for the lack of physical danger they were in, but emphasized the unique and significant dangers of online-based sex work (their images and videos being recorded and shared without their consent, for example). Participants also argued that their largest concerns were based around stigma, which they claimed remained prevalent despite the decriminalized legal model in Aotearoa/New Zealand (which has been in place for over 14 years). Overall, this project seeks to challenge commonplace academic approaches to sex work, adding further research to support sex workers’ rights and highlighting new issues to consider in a digital environment.

Keywords: camming, sex work, stigma, risk

Procedia PDF Downloads 143

Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

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Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

Procedia PDF Downloads 337

Authors: Foad Vashahi, Shahnaz Rezaei, Jeekeun Lee

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Large Eddy Simulation (LES) was performed on a dual counter rotating axial swirler in a confined rectangular configuration. Grids were constructed based on a primary Reynolds Averaged Navier-Stokes (RANS) simulation and then were refined based on the Kolmogorov length scale. Water as cold flow condition was applied and results were compared via Particle Image Velocimetry (PIV) experimental results. The focus was to investigate the flow behavior within the region before the flare and very close to the exit of the swirler. This region contributes to a highly unsteady flow behavior and requires great attention to enhancing the flame stability in gas turbine combustor and swirl burners. The PVC formation within the central core flow is strongly related to the peaks of pressure or axial velocity spectrum and up to two distinct peaks at the swirler mouth could be observed. Here, spectra analysis in iso-thermal condition inside the swirler where the inner swirler dominates the flow, showed a higher potential of instabilities with three to four distinct peaks where moving forward to the exit of swirler the number of peaks is decreased. In addition to this, the central axis corresponds to no peaks of instabilities while further away in the radial direction, several peaks exist.

Keywords: axial counter rotating swirler, large eddy simulation (LES), precessing vortex core (PVC), power spectral density (PSD)

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 243

Authors: Yang Zheng, Wei Sun

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This paper describes a new approach which can be used to interpret the experimental creep deformation data obtained from miniaturized thin plate bending specimen test to the corresponding uniaxial data based on an inversed application of the reference stress method. The geometry of the thin plate is fully defined by the span of the support, l, the width, b, and the thickness, d. Firstly, analytical solutions for the steady-state, load-line creep deformation rate of the thin plates for a Norton’s power law under plane stress (b → 0) and plane strain (b → ∞) conditions were obtained, from which it can be seen that the load-line deformation rate of the thin plate under plane-stress conditions is much higher than that under the plane-strain conditions. Since analytical solution is not available for the plates with random b-values, finite element (FE) analyses are used to obtain the solutions. Based on the FE results obtained for various b/l ratios and creep exponent, n, as well as the analytical solutions under plane stress and plane strain conditions, an approximate, numerical solutions for the deformation rate are obtained by curve fitting. Using these solutions, a reference stress method is utilised to establish the conversion relationships between the applied load and the equivalent uniaxial stress and between the creep deformations of thin plate and the equivalent uniaxial creep strains. Finally, the accuracy of the empirical solution was assessed by using a set of “theoretical” experimental data.

Keywords: bending, creep, thin plate, materials engineering

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Authors: Vince Liégeois

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Language of immediacy and distance: Within their discourse theory, Koch & Oesterreicher establish a distinction between a language of immediacy and a language of distance. The former refers to those discourses which are oriented more towards a spoken norm, whereas the latter entails discourses oriented towards a written norm, regardless of whether they are realised phonically or graphically. This means that an utterance can be realised phonically but oriented more towards the written language norm (e.g., a scientific presentation or eulogy) or realised graphically but oriented towards a spoken norm (e.g., a scribble or chat messages). Research desiderata: The methodological approach from Koch & Oesterreicher has often been criticised for not providing a corpus-linguistic methodology, which makes it difficult to work with quantitative data or address large text collections within this research paradigm. Consequently, the Koch & Oesterreicher approach has difficulties gaining ground in those research areas which rely more on corpus linguistic research models, like text linguistics and LSP-research. A combinatory approach: Accordingly, we want to establish a combinatory approach with corpus-based linguistic methodology. To this end, we propose to (i) include data about the context of an utterance (e.g., monologicity/dialogicity, familiarity with the speaker) – which were called “conditions of communication” in the original work of Koch & Oesterreicher – and (ii) correlate the linguistic phenomenon at the centre of the inquiry (e.g., evaluation markers) to a group of linguistic phenomena deemed typical for either distance- or immediacy-language. Based on these two parameters, linguistic phenomena and texts could then be mapped on an immediacy-distance continuum. Pilot study: To illustrate the benefits of this approach, we will conduct a pilot study on evaluation phenomena in French television weather reports, a form of domain-sensitive discourse which has often been cited as an example of a “text genre”. Within this text genre, we will look at so-called “evaluation markers,” e.g., fixed strings like bad weather, stifling hot, and “no luck today!”. These evaluation markers help to communicate the coming weather situation towards the lay audience but have not yet been studied within the Koch & Oesterreicher research paradigm. Accordingly, we want to figure out whether said evaluation markers are more typical for those weather reports which tend more towards immediacy or those which tend more towards distance. To this aim, we collected a corpus with different kinds of television weather reports,e.g., as part of the news broadcast, including dialogue. The evaluation markers themselves will be studied according to the explained methodology, by correlating them to (i) metadata about the context and (ii) linguistic phenomena characterising immediacy-language: repetition, deixis (personal, spatial, and temporal), a freer choice of tense and right- /left-dislocation. Results: Our results indicate that evaluation markers are more dominantly present in those weather reports inclining towards immediacy-language. Based on the methodology established above, we have gained more insight into the working of evaluation markers in the domain-sensitive text genre of (television) weather reports. For future research, it will be interesting to determine whether said evaluation markers are also typical for immediacy-language-oriented in other domain-sensitive discourses.

Keywords: corpus-based linguistics, evaluation markers, language of immediacy and distance, weather reports

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Authors: Felix Jr. Garde, Eric Augustus Tingatinga

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Most analysis procedures of reinforced concrete (RC) slabs are based on elastic theory. When subjected to large forces, however, slabs deform beyond elastic range and the study of their behavior and performance require nonlinear analysis. This paper presents a numerical model to simulate nonlinear behavior of RC slabs using rigid body-spring discrete element method. The proposed slab model composed of rigid plate elements and nonlinear springs is based on the yield line theory which assumes that the nonlinear behavior of the RC slab subjected to transverse loads is contained in plastic or yield-lines. In this model, the displacement of the slab is completely described by the rigid elements and the deformation energy is concentrated in the flexural springs uniformly distributed at the potential yield lines. The spring parameters are determined from comparison of transverse displacements and stresses developed in the slab obtained using FEM and the proposed model with assumed homogeneous material. Numerical models of typical RC slabs with varying geometry, reinforcement, support conditions, and loading conditions, show reasonable agreement with available experimental data. The model was also shown to be useful in investigating dynamic behavior of slabs.

Keywords: RC slab, nonlinear behavior, yield line theory, rigid body-spring discrete element method

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Authors: Abhishek Agarwal, Manoj Sarda, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

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Propagation of fire through a non-air conditioned railway compartment is studied by virtue of numerical simulations. Simultaneous computational fire dynamics equations, such as Navier-Stokes, lumped species continuity, overall mass and energy conservation, and heat transfer are solved using finite volume based (for radiation) and finite difference based (for all other equations) solver, Fire Dynamics Simulator (FDS). A single coupe with an eight berth occupancy is used to establish the numerical model, followed by the selection of a three coupe system as the fundamental unit of the locomotive compartment. Heat Release Rate Per Unit Area (HRRPUA) of the initial fire is varied to consider a wide range of compartmental fires. Parameters, such as air inlet velocity relative to the locomotive at the windows, the level of interaction with the ambiance and closure of middle berth are studied through a wide range of numerical simulations. Almost all the loss of lives and properties due to fire breakout can be attributed to the direct or indirect exposure to flames or to the inhalation of toxic gases and resultant suffocation due to smoke and soot. Therefore, the temporal stature of fire and smoke are reported for each of the considered cases which can be used in the present or extended form to develop guidelines to be followed in case of a fire breakout.

Keywords: fire dynamics, flame propagation, locomotive fire, soot flow pattern, non-air-conditioned coaches

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Eric Awich Ochen

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The end of the conflict in Northern Uganda in 2006 brought about an opportunity for the youth to return to their original home and contribute to the peace building and development process of their communities. Post-conflict is used here to refer to the post-armed conflict situation and activities of rebels of Joseph Kony in northern Uganda. While the rebels remain very much active in the Sudan and Central African Republic, in Uganda the last confrontations occurred around 2006 or earlier, and communities have returned to their homes and began the process of rebuilding their lives. It is argued that socio-economic reconstruction is at the heart of peacebuilding and sustenance of positive peace in the aftermath of conflict, as it has a bearing on post-conflict stability and good governance. We recognize that several post-conflict interventions within Northern Uganda have targeted women and children with a strong emphasis on family socio-economic empowerment and capacity building, including access to micro finance. The aim of this study was to examine the participation of the youth in post-conflict peace building and development in Northern Uganda by assessing the breadth and width of their engagement and the stages of programming cycle that they are involved in, interrogating the space for participation and how they are facilitating or constraining participation. It was further aimed at examining the various dimensions of participation at play in Northern Uganda and where this fits within the conceptual debates on peace building and development in the region. Supporting young people emerging out of protracted conflict to re-establish meaningful socio-economic engagements and livelihoods is fundamental to their participation in the affairs of the community. The study suggests that in the post-conflict development context of Northern Uganda, participation has rarely been disaggregated or differentiated by sectors or groups. Where some disaggregation occurs, then the main emphasis has always been on either women or children. It appears therefore that little meaningful space has thus been created for young people to engage and participate in peace building initiatives within the region. In other cases where some space is created for youth participation, this has been in pre-conceived programs or interventions conceived by the development organizations with the youth or young people only invited to participate at particular stages of the project implementation cycle. Still within the implementation of the intervention, the extent to which young people participate is bounded, with little power to influence the course of the interventions or make major decisions. It is thus visible that even here young people mainly validate and legitimize what are predetermined processes only act as pawns in the major chess games played by development actors (dominant peace building partners). This paper, therefore, concludes that the engagement of the youth in post-conflict peace building has been quite problematic and tokenistic and has not given the adequate youth space within which they could ably participate and express themselves in the ensuing interventions.

Keywords: youth, conflict, peace building, participation

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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Authors: Carolina Silva Ansélmo

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Airports are demand-generating poles that affect the flow of traffic around them. The airport access system must be fast, convenient, and adequately planned, considering its potential users. An airport with good ground access conditions can provide the user with a more satisfactory access experience. When several transport options are available, service providers must understand users' preferences and the expected quality of service. The present study focuses on airport access in a comparative scenario between bus, private vehicle, subway, taxi and urban mobility transport applications to São Paulo/Guarulhos International Airport. The objectives are (i) to identify the factors that influence the choice, (ii) to measure Willingness to Pay (WTP), and (iii) to estimate the market share for each modal. The applied method was Adaptive Choice-based Conjoint Analysis (ACBC) technique using Sawtooth Software. Conjoint analysis, rooted in Utility Theory, is a survey technique that quantifies the customer's perceived utility when choosing alternatives. Assessing user preferences provides insights into their priorities for product or service attributes. An additional advantage of conjoint analysis is its requirement for a smaller sample size compared to other methods. Furthermore, ACBC provides valuable insights into consumers' preferences, willingness to pay, and market dynamics, aiding strategic decision-making to provide a better customer experience, pricing, and market segmentation. In the present research, the ACBC questionnaire had the following variables: (i) access time to the boarding point, (ii) comfort in the vehicle, (iii) number of travelers together, (iv) price, (v) supply power, and (vi) type of vehicle. The case study questionnaire reached 213 valid responses considering the scenario of access from the São Paulo city center to São Paulo/Guarulhos International Airport. As a result, the price and the number of travelers are the most relevant attributes for the sample when choosing airport access. The market share of the selection is mainly urban mobility transport applications, followed by buses, private vehicles, taxis and subways.

Keywords: adaptive choice-based conjoint analysis, ground access to airport, market share, willingness to pay

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

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Authors: A. J. Julius, E. Imoagene, O. A. Ganiyu

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The purpose of this study is to estimate the economic value of the services and functions rendered by the forest landscape using a conditional logit model. For this study, attributes and levels of forest landscape were chosen; specifically, attributes include topographical forest type, forest type, forest density, recreational factor (side trip, accessibility of valley), and willingness to participate (WTP). Based on these factors, 48 choices sets with balanced and orthogonal form using statistical analysis system (SAS) 9.1 was adopted. The efficiency of the questionnaire was 6.02 (D-Error. 0.1), and choice set and socio-economic variables were analyzed. To reduce the cognitive load of respondents, the 48 choice sets were divided into 4 types in the questionnaire, so that respondents could respond to 12 choice sets, respectively. The study populations were citizens from seven metropolitan cities including Ibadan, Ilorin, Osogbo, etc. and annual WTP per household was asked by using the interview questionnaire, a total of 267 copies were recovered. As a result, Oshogbo had 0.45, and the statistical similarities could not be found except for urban forests, forest density, recreational factor, and level of WTP. Average annual WTP per household for forest landscape was 104,758 Naira (Nigerian currency) based on the outcome from this model, total economic value of the services and functions enjoyed from Nigerian forest landscape has reached approximately 1.6 trillion Naira.

Keywords: economic valuation, urban cities, services, forest landscape, logit model, nigeria

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Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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Authors: Benedetta Caglioti

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The ecclesiastical complex of San Paolo in Ferrara represents a monument of great historical, religious and architectural importance. Its long and articulated story, over time, is already manifested by the mere reading of its planimetric and altimetric configuration, apparently unitary but, in reality, marked by modifications and repeated additions, even of high quality. It follows, in terms of protection, restoration and enhancement, a commitment of due respect for how the ancient building was built and enriched over its centuries of life. Hence a rigorous methodological approach, while being aware of the fact that every monument, in order to live and make use of the indispensable maintenance, must always be enjoyed and visited, therefore it must enjoy, in the right measure and compatibly with its nature, the possibility of improvements and functional, distributive, technological adjustments and related to the safety of people and things. The methodological approach substantiates the different elements of the project (such as distribution functionality, safety, structural solidity, environmental comfort, the character of the site, building and urban planning regulations, financial resources and materials, the same organization methods of the construction site) through the guiding principles of restoration, defined for a long time: the 'minimum intervention,' the 'recognisability' or 'distinguishability' of old and new, the Physico-chemical and figurative 'compatibility,' the 'durability' and the, at least potential, 'reversibility' of what is done, leading to the definition of appropriate "critical choices." The project tackles, together with the strictly functional ones, also the directly conservative and restoration issues, of a static, structural and material technology nature, with special attention to precious architectural surfaces, In order to ensure the best architectural quality through conscious enhancement, the project involves a redistribution of the interior and service spaces, an accurate lighting system inside and outside the church and a reorganization of the adjacent urban space. The reorganization of the interior is designed with particular attention to the issue of accessibility for people with disabilities. To accompany the community to regain possession of the use of the church's own space, already in its construction phase, the project proposal has hypothesized a permeability and flexibility in the management of the works such as to allow the perception of the found Monument to gradually become more and more familiar at the citizenship. Once the interventions have been completed, it is expected that the Church of San Paolo, second in importance only to the Cathedral, from which it is a few steps away, will be inserted in an already existing circuit of use of the city which over the years has systematized the different aspects of culture, the environment and tourism for the creation of greater awareness in the perception of what Ferrara can offer in cultural terms.

Keywords: conservation, accessibility, regeneration, urban space

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Authors: Jian-Na Zhang, Xiao-Li Chen, Si-Jian Li

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Objective: In order to investigate current status on knowledge of disaster prevention and reduction in rural pupils, to explore education method on disaster prevention and reduction for rural pupils. Method: A questionnaire was designed based on literature review. Convenient sampling was used in the survey. The questionnaire survey was conducted among 180 students from Huodehong town central primary school which located in Ludian county of Zhaotong city in Yunnan province, where 6.5 magnitude earthquake happened in 2014. The result indicated that the pupils’ knowledge and skills on disaster prevention and reduction relevant poor. The source for them to obtain the knowledge of disaster prevention and reduction included TV (68.9%), followed by their parents (43.9%), while only 24.4% of knowledge is from the teachers. The scores about different natural disaster are ranking in descending order: earthquake (5.39 ±1.27), floods (3.77 ±1.17); debris flow (2.81 ±1.05), family fire (2.16± 0.96). And the disaster experience did not help the pupils enhance the knowledge reserves. There is no statistical significance (P > 0.05) in knowledge scores of disaster prevention and reduction between experienced and non-experienced group. Conclusion: The local disaster experiences did not draw the attention of parents and schools. Knowledge popularization of disaster for local pupils is extremely urgent. It is necessary to take advantage of more mediums to popularize the knowledge and skills about disaster prevention and reduction, for example, family education, school education, newspapers, brochures, etc. The training courses on disaster prevention and reduction which are based on the characteristics of the local rural pupils and the characteristics of the local disasters would be useful.

Keywords: rural, pupils, disaster prevention and reduction knowledge, popularization

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Authors: Vinod K. Singh, S. G. Chung

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The degree of structuration of Busan clays at the mouth of Nakdong River mouth was highly influenced by the depositional environment, i.e., flow of the river stream, marine regression, and transgression during the sedimentation process. As a result, the geotechnical properties also varies along the depth with change in degree of structuration. Thus, the in-situ tests such as cone penetration test (CPT) could not be used to predict various geotechnical properties properly by using the conventional empirical methods. In this paper, the shear wave velocity (Vs) was measured from the field using the seismic dilatometer. The Vs was also measured in the laboratory from high quality undisturbed and remolded samples using bender element method to evaluate the degree of structuration. The degree of structuration was quantitatively defined by the modulus ratio of undisturbed to remolded soil samples which is found well correlated with the normalized void ratio (e0/eL) where eL is the void ratio at the liquid limit. It is revealed that the empirical method based on laboratory results incorporating e0/eL can predict Vs from the field more accurately. Thereafter, the CPT based empirical method was developed to estimate the shear wave velocity taking the effect of structuration in the consideration. The developed method was found to predict shear wave velocity reasonably for Busan clays.

Keywords: level of structuration, normalized modulus, normalized void ratio, shear wave velocity, site characterization

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Authors: Reza Moslemi, Sebastien Perrier

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Water infrastructure deterioration can result in increased operational costs owing to increased repair needs and non-revenue water and consequently cause a reduced level of service and customer service satisfaction. Various water main condition assessment technologies have been introduced to the market in order to evaluate the level of pipe deterioration and to develop appropriate asset management and pipe renewal plans. One of the challenges for any condition assessment and inspection program is to determine the percentage of the water network and the combination of pipe segments to be inspected in order to obtain a meaningful representation of the status of the entire water network with a desirable level of accuracy. Traditionally, condition assessment has been conducted by selecting pipes based on age or location. However, this may not necessarily offer the best approach, and it is believed that by using a smart sampling methodology, a better and more reliable estimate of the condition of a water network can be achieved. This research investigates three different sampling methodologies, including random, stratified, and systematic. It is demonstrated that selecting pipes based on the proposed clustering and sampling scheme can considerably improve the ability of the inspected subset to represent the condition of a wider network. With a smart sampling methodology, a smaller data sample can provide the same insight as a larger sample. This methodology offers increased efficiency and cost savings for condition assessment processes and projects.

Keywords: condition assessment, pipe degradation, sampling, water main

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Authors: Neha Ahirwar

Abstract:

In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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