Search results for: random forest algorithm

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

Abstract:

Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

Procedia PDF Downloads 524

Authors: Josiane Yaguibou, Ngoy Kishimba, Issiaka V. Coulibaly, Sabrina Pestilli, Falinirina Razanalison, Hantanirina V. Andremanisa

Abstract:

Background In Madagascar modern contraceptive prevalence rate increased from 18% in 2003 to 43% in 2021. Anecdotal evidence suggests that increased use and frequent stock out in public health facilities of male condoms and medroxyprogesterone acetate (MPA) can be related to diverted use of these products. This study analyzed the use of contraceptives and mode of utilization (correct or diverted) at the community level in the period 2019-2023 in Madagascar. Methodology: The study included a literature review, a quantitative survey combined with a qualitative study. It was carried out in 10 regions out of the 23 of the country. Eight regions (Bongolava, Vakinakaratra, Italy, Hautre Matsiatra, Betsiboka, Diana, Sofia and Anosy) were selected based on a study that showed existence of medroxyprogesterone acetate in pigs (MPA). The remaining 2 regions were selected due to high mCPR (Atsimo Andrefana) and to ensure coverage of all geographical zones in the country (Alaotra Mangoro). Sample random method was used, and the sample size was identified at 300 individuals per region. Zonal distribution is based on the urbanization rate for the region. 6 focus group discussions were organized in 3 regions, equally distributed between rural and urban areas. Key findings: Overall, 67% of those surveyed or their partner are currently using contraception. Injectables (MPA) are the most popular choice (33%), followed by implants and male condoms, 12% and 9%, respectively. The majority of respondents use condoms to prevent unwanted pregnancy but also to prevent STDs. Still, 43% of respondents use condoms for other purposes, reaching 52% of respondents in urban areas and 71,2% in the age group 15-18. Diverted use includes hair growth (18.9%), as a toy (18.8%), cleaning the screen of electronic devices (10 %), cleaning shoes (3.1%) and for skincare (1.6%). Injectables are the preferred method of contraception both in rural areas (35%) and urban areas (21.2%). However, diverted use of injectables was confirmed by 4% of the respondents, ranging from 3 % in rural areas to 12% in urban. The diverted use of injectables in pig rearing was to avoid pregnancy and facilitate pig’s growth. Program Implications: The study confirmed the diverted use of some contraceptives. The misuse of male condoms is among the causes of stockouts of products in public health facilities, limiting their availability for pregnancy and STDs prevention. The misuse of injectables in pigs rearing needs to be further studied to learn the full extent of the misuse and eventual implications for meat consumption. The study highlights the importance of including messages on the correct use of products during sensibilization activities. In particular, messages need to address the anecdotal and false effects of male condoms, especially amongst young people. For misuse of injectables is critical to sensibilize farmers and veterinaries on possible negative effects for humans.

Keywords: diverted use, injectables, male condoms, sensibilization

Procedia PDF Downloads 48

Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

Abstract:

Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

Procedia PDF Downloads 157

Authors: Michael Naderhirn, Marco Pavone

Abstract:

Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

Procedia PDF Downloads 230

Authors: Chao-Ton Su, Li-Fei Chen

Abstract:

The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

Procedia PDF Downloads 132

Authors: Foteini Zagklavara, Peter Jimack, Nikil Kapur, Ozz Querin, Harvey Thompson

Abstract:

The invention and development of the Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise their performance of those devices while reducing the total construction and operation costs. The present study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the trade-offs between competing objectives of DNA amplification efficiency and pressure drop to be explored. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a CF μPCR device by performing a series of simulations at a relatively small number of Design of Experiments (DoE) points, with the use of COMSOL Multiphysics 5.4. The values of the objectives are extracted from the CFD solutions, and response surfaces created using the polyharmonic splines and neural networks. After creating the respective response surfaces, genetic algorithm, and a multi-level coordinate search optimisation function are used to locate the optimum design parameters. Both optimisation methods produced similar results for both the neural network and the polyharmonic spline response surfaces. The results indicate that there is the possibility of improving the DNA efficiency by ∼2% in one PCR cycle when doubling the width of the microchannel to 400 μm while maintaining the height at the value of the original design (50μm). Moreover, the increase in the width of the serpentine microchannel is combined with a decrease in its total length in order to obtain the same residence times in all the simulations, resulting in a smaller total substrate volume (32.94% decrease). A multi-objective optimisation is also performed with the use of a Pareto Front plot. Such knowledge will enable designers to maximise the amount of DNA amplified or to minimise the time taken throughout thermal cycling in such devices.

Keywords: PCR, optimisation, microfluidics, COMSOL

Procedia PDF Downloads 147

Authors: Ahmad Shahin, Fadi Chakik, Walid Moudani

Abstract:

Our study is about elaborating a potential solution for a search engine that involves semantic technology to retrieve information and display it significantly. Semantic search engines are not used widely over the web as the majorities are still in Beta stage or under construction. Many problems face the current applications in semantic search, the major problem is to analyze and calculate the meaning of query in order to retrieve relevant information. Another problem is the ontology based index and its updates. Ranking results according to concept meaning and its relation with query is another challenge. In this paper, we are offering a light meta-engine (QESM) which uses Google search, and therefore Google’s index, with some adaptations to its returned results by adding multi-query expansion. The mission was to find a reliable ranking algorithm that involves semantics and uses concepts and meanings to rank results. At the beginning, the engine finds synonyms of each query term entered by the user based on a lexical database. Then, query expansion is applied to generate different semantically analogous sentences. These are generated randomly by combining the found synonyms and the original query terms. Our model suggests the use of semantic similarity measures between two sentences. Practically, we used this method to calculate semantic similarity between each query and the description of each page’s content generated by Google. The generated sentences are sent to Google engine one by one, and ranked again all together with the adapted ranking method (QESM). Finally, our system will place Google pages with higher similarities on the top of the results. We have conducted experimentations with 6 different queries. We have observed that most ranked results with QESM were altered with Google’s original generated pages. With our experimented queries, QESM generates frequently better accuracy than Google. In some worst cases, it behaves like Google.

Keywords: semantic search engine, Google indexing, query expansion, similarity measures

Procedia PDF Downloads 415

Authors: Mikiyas Adugna

Abstract:

Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

Procedia PDF Downloads 46

Authors: Rohini Sharma, Chandan Kumar Sahoo, Rama Krishna Gupta Potnuru

Abstract:

Strong competitive forces and requirements to achieve efficiency are forcing the organizations to realize the necessity and inevitability of change. What's more, the trend does not appear to be abating. Researchers have estimated that about two thirds of change project fails. Empirical evidences further shows that organizations invest significantly in the planned change but people side is accounted for in a token or instrumental way, which is identified as one of the important reason, why change endeavours fail. However, whatever be the reason for change, organizational change readiness must be gauged prior to the institutionalization of organizational change. Hence, in this study the influence of employee voice and employee involvement on organizational change readiness via commitment-to-change is examined, as it is an area yet to be extensively studied. Also, though a recent study has investigated the interrelationship between leadership, organizational change readiness and commitment to change, our study further examined these constructs in relation with employee voice and employee involvement that plays a consequential role for organizational change readiness. Further, integrated conceptual model weaving varied concepts relating to organizational readiness with focus on commitment to change as mediator was found to be an area, which required more theorizing and empirical validation, and this study rooted in an Indian public sector organization is a step in this direction. Data for the study were collected through a survey among employees of Rourkela Steel Plant (RSP), a unit of Steel Authority of India Limited (SAIL); the first integrated Steel Plant in the public sector in India, for which stratified random sampling method was adopted. The schedule was distributed to around 700 employees, out of which 516 complete responses were obtained. The pre-validated scales were used for the study. All the variables in the study were measured on a five-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5)”. Structural equation modeling (SEM) using AMOS 22 was used to examine the hypothesized model, which offers a simultaneous test of an entire system of variables in a model. The study results shows that inter-relationship between employee voice and commitment-to-change, employee involvement and commitment-to-change and commitment-to-change and organizational change readiness were significant. To test the mediation hypotheses, Baron and Kenny’s technique was used. Examination of direct and mediated effect of mediators confirmed that commitment-to-change partially mediated the relation between employee involvement and organizational change readiness. Furthermore, study results also affirmed that commitment-to-change does not mediate the relation between employee involvement and organizational change readiness. The empirical exploration therefore establishes that it is important to harness employee’s valuable suggestions regarding change for building organizational change readiness. Regarding employee involvement, it was found that sharing information and involving people in decision-making, leads to a creation of participative climate, which educes employee commitment during change and commitment-to-change further, fosters organizational change readiness.

Keywords: commitment-to-change, change management, employee voice, employee involvement, organizational change readiness

Procedia PDF Downloads 317

Authors: Houman Tamaddon, Mehrdad Behnia, Masud Behnia

Abstract:

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.

Keywords: blood flow, morphometric data, vascular tree, Strahler ordering system

Procedia PDF Downloads 258

Authors: Ebenezer Joseph

Abstract:

Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

Procedia PDF Downloads 244

Authors: Farhat Imtiaz, Umar Farooq

Abstract:

In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

Procedia PDF Downloads 126

Authors: Alina Fedossova, Jose Jorge Sierra Molina

Abstract:

SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

Procedia PDF Downloads 298

Authors: Shiv Jyoti Pandey, Shveta Puri, G. M. Bhat, Neha Raina

Abstract:

The Jammu and Kashmir (J&K) region of Northwest Himalaya has a long history of earthquake activity which falls within Seismic Zones IV and V. To know the crustal structure beneath this region, we utilized teleseismic receiver function method. This paper presents the results of the analyses of the teleseismic earthquake waves recorded by 10 seismic observatories installed in the vicinity of major thrusts and faults. The teleseismic waves at epicentral distance between 30o and 90o with moment magnitudes greater than or equal to 5.5 that contains large amount of information about the crust and upper mantle structure directly beneath a receiver has been used. The receiver function (RF) technique has been widely applied to investigate crustal structures using P-to-S converted (Ps) phases from velocity discontinuities. The arrival time of the Ps, PpPs and PpSs+ PsPs converted and reverberated phases from the Moho can be combined to constrain the mean crustal thickness and Vp/Vs ratio. Over 500 receiver functions from 10 broadband stations located in the Jammu & Kashmir region of Northwest Himalaya were analyzed. With the help of H-K stacking method, we determined the crustal thickness (H) and average crustal Vp/Vs ratio (K) in this region. We also used Neighbourhood algorithm technique to verify our results. The receiver function results for these stations show that the crustal thickness under Jammu & Kashmir ranges from 45.0 to 53.6 km with an average value of 50.01 km. The Vp/Vs ratio varies from 1.63 to 1.99 with an average value of 1.784 which corresponds to an average Poisson’s ratio of 0.266 with a range from 0.198 to 0.331. High Poisson’s ratios under some stations may be related to partial melting in the crust near the uppermost mantle. The crustal structure model developed from this study can be used to refine the velocity model used in the precise epicenter location in the region, thereby increasing the knowledge to understand current seismicity in the region.

Keywords: H-K stacking, Poisson’s ratios, receiver function, teleseismic

Procedia PDF Downloads 237

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

Abstract:

Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

Procedia PDF Downloads 98

Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

Abstract:

The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

Procedia PDF Downloads 141

Authors: Zachary Pan

Abstract:

Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

Procedia PDF Downloads 85

Authors: Saikat Majumdar, D. C. Kalita

Abstract:

The Agriculture sector plays an important role in the rural economy of India. It is the backbone of our Indian economy and is the dominant sector in terms of employment and livelihood. Agriculture still contributes significantly to export earnings and is an important source of raw materials as well as of demand for many industrial products particularly fertilizers, pesticides, agricultural implements and a variety of consumer goods, etc. The performance of the agricultural sector influences the growth of Indian economy. According to the 2011 Agricultural Census of India, an estimated 61.5 percentage of rural populations are dependent on agriculture. Proper Agricultural infrastructure has the potential to transform the existing traditional agriculture into a most modern, commercial and dynamic farming system in India through its diffusion of technology. The rate of adoption of modern technology reflects the progress of development in agricultural sector. The adoption of any improved agricultural technology is also dependent on the development of road infrastructure or road network. The present study was consisting of 300 sample farmers out which 150 samples was taken from the developed area and rest 150 samples was taken from underdeveloped area. The samples farmers under develop and underdeveloped areas were collected by using Multistage Random Sampling procedure. In the first stage, North 24 Parganas District have been selected purposively. Then from the district, one developed and one underdeveloped block was selected randomly. In the third phase, 10 villages have been selected randomly from each block. Finally, from each village 15 sample farmers was selected randomly. The extents of adoption of technology in different areas were calculated through various parameters. These are percentage area under High Yielding Variety Cereals, percentage area under High Yielding Variety pulses, area under hybrids vegetables, irrigated area, mechanically operated area, amount spent on fertilizer and pesticides, etc. in both developed and underdeveloped areas of North 24 Parganas District, West Bengal. The percentage area under High Yielding Variety Cereals in the developed and underdeveloped areas was 34.86 and 22.59. 42.07 percentages and 31.46 percentages for High Yielding Variety pulses respectively. In the case the area under irrigation it was 57.66 and 35.71 percent while for the mechanically operated area it was 10.60 and 3.13 percent respectively in developed and underdeveloped areas of North 24 Parganas district, West Bengal. It clearly showed that the extent of adoption of technology was significantly higher in the developed area over underdeveloped area. Better road network system helps the farmers in increasing his farm income, farm assets, cropping intensity, marketed surplus and the rate of adoption of new technology. With this background, an attempt is made in this paper to study the impact of Agricultural Infrastructure on the adoption of modern technology in agriculture in North 24 Parganas District, West Bengal.

Keywords: agricultural infrastructure, adoption of technology, farm income, road network

Procedia PDF Downloads 89

Authors: Chidiebere C. Agoha, Chukwuebuka N. Onwubuariri, Collins U.amasike, Tochukwu I. Mgbeojedo, Joy O. Njoku, Lawson J. Osaki, Ifeyinwa J. Ofoh, Francis B. Akiang, Dominic N. Anuforo

Abstract:

In order to interpret the airborne magnetic data and evaluate the approximate location, depth, and geometry of the magnetic sources within Obudu area using the standard Euler deconvolution method, very high-resolution aeromagnetic data over the area was acquired, processed digitally and analyzed using Oasis Montaj 8.5 software. Data analysis and enhancement techniques, including reduction to the equator, horizontal derivative, first and second vertical derivatives, upward continuation and regional-residual separation, were carried out for the purpose of detailed data Interpretation. Standard Euler deconvolution for structural indices of 0, 1, 2, and 3 was also carried out and respective maps were obtained using the Euler deconvolution algorithm. Results show that the total magnetic intensity ranges from -122.9nT to 147.0nT, regional intensity varies between -106.9nT to 137.0nT, while residual intensity ranges between -51.5nT to 44.9nT clearly indicating the masking effect of deep-seated structures over surface and shallow subsurface magnetic materials. Results also indicated that the positive residual anomalies have an NE-SW orientation, which coincides with the trend of major geologic structures in the area. Euler deconvolution for all the considered structural indices has depth to magnetic sources ranging from the surface to more than 2000m. Interpretation of the various structural indices revealed the locations and depths of the source bodies and the existence of geologic models, including sills, dykes, pipes, and spherical structures. This area is characterized by intrusive and very shallow basement materials and represents an excellent prospect for solid mineral exploration and development.

Keywords: Euler deconvolution, horizontal derivative, Obudu, structural indices

Procedia PDF Downloads 65

Authors: Onabajo Paul

Abstract:

The testing and assessment of physical fitness of school-aged adolescents in Nigeria has been going on for several decades. Originally, these tests strictly focused on identifying health and physical fitness status and comparing the results of adolescents with others. There is a considerable interest in health and performance fitness of adolescents in which results attained are compared with criteria representing positive health rather than simply on score comparisons with others. Despite the fact that physical education program is being studied in secondary schools and physical activities are encouraged, it is observed that regular assessment of students’ fitness level and health status seems to be scarce or not being done in these schools. The purpose of the study was to assess the heath and performance fitness of adolescents in middle-income schools in Lagos State. A total number of 150 students were selected using the simple random sampling technique. Participants were measured on hand grip strength, sit-up, pacer 20 meter shuttle run, standing long jump, weight and height. The data collected were analyzed with descriptive statistics of means, standard deviations, and range and compared with fitness norms. It was concluded that majority 111(74.0%) of the adolescents achieved the healthy fitness zone, 33(22.0%) were very lean, and 6(4.0%) needed improvement according to the normative standard of Body Mass Index test. For muscular strength, majority 78(52.0%) were weak, 66(44.0%) were normal, and 6(4.0%) were strong according to the normative standard of hand-grip strength test. For aerobic capacity fitness, majority 93(62.0%) needed improvement and were at health risk, 36(24.0%) achieved healthy fitness zone, and 21(14.0%) needed improvement according to the normative standard of PACER test. Majority 48(32.0%) of the participants had good hip flexibility, 38(25.3%) had fair status, 27(18.0%) needed improvement, 24(16.0%) had very good hip flexibility status, and 13(8.7%) of the participants had excellent status. Majority 61(40.7%) had average muscular endurance status, 30(20.0%) had poor status, 29(18.3%) had good status, 28(18.7%) had fair muscular endurance status, and 2(1.3%) of the participants had excellent status according to the normative standard of sit-up test. Majority 52(34.7%) had low jump ability fitness, 47(31.3%) had marginal fitness, 31(20.7%) had good fitness, and 20(13.3%) had high performance fitness according to the normative standard of standing long jump test. Based on the findings, it was concluded that majority of the adolescents had better Body Mass Index status, and performed well in both hip flexibility and muscular endurance tests. Whereas majority of the adolescents performed poorly in aerobic capacity test, muscular strength and jump ability test. It was recommended that to enhance wellness, adolescents should be involved in physical activities and recreation lasting 30 minutes three times a week. Schools should engage in fitness program for students on regular basis at both senior and junior classes so as to develop good cardio-respiratory, muscular fitness and improve overall health of the students.

Keywords: adolescents, health-related fitness, performance-related fitness, physical fitness

Procedia PDF Downloads 347

Authors: Itzel Amaro-Estrada, Eduardo Vergara-Rivera, Virginia Juarez-Flores, Mayra Cobaxin-Cardenas, Rosa Estela Quiroz, Jesus F. Preciado, Sergio Rodriguez-Camarillo

Abstract:

Bovine anaplasmosis is an infectious, tick-borne disease caused mainly by Anaplasma marginale; typical signs include anemia, fever, abortion, weight loss, decreased milk production, jaundice, and potentially death. Sick bovine can recover when antibiotics are administered; however, it usually remains as carrier for life, being a risk of infection for susceptible cattle. Anaplasma marginale is an obligate intracellular Gram-negative bacterium with genetic composition highly diverse among geographical isolates. There are currently no vaccines fully effective against bovine anaplasmosis; therefore, the economic losses due to disease are present. Vaccine formulation became a hard task for several pathogens as Anaplasma marginale, but peptide-based vaccines are an interesting proposal way to induce specific responses. Phage-displayed peptide libraries have been proved one of the most powerful technologies for identifying specific ligands. Screening of these peptides libraries is also a tool for studying interactions between proteins or peptides. Thus, it has allowed the identification of ligands recognized by polyclonal antiserums, and it has been successful for the identification of relevant epitopes in chronic diseases and toxicological conditions. Protective immune response to bovine anaplasmosis includes high levels of immunoglobulins subclass G2 (IgG2) but not subclass IgG1. Therefore, IgG2 from the serum of protected bovine can be useful to identify ligands, which can be part of an immunogen for cattle. In this work, phage display random peptide library Ph.D. ™ -12 was incubating with IgG2 or blood sera of immunized bovines against A. marginale as targets. After three rounds of biopanning, several candidates were selected for additional analysis. Subsequently, their reactivity with sera immunized against A. marginale, as well as with positive and negative sera to A. marginale was evaluated by immunoassays. A collection of recognized peptides tested by ELISA was generated. More than three hundred phage-peptides were separately evaluated against molecules which were used during panning. At least ten different peptides sequences were determined from their nucleotide composition. In this approach, three phage-peptides were selected by their binding and affinity properties. In the case of the development of vaccines or diagnostic reagents, it is important to evaluate the immunogenic and antigenic properties of the peptides. Immunogenic in vitro and in vivo behavior of peptides will be assayed as synthetic and as phage-peptide for to determinate their vaccine potential. Acknowledgment: This work was supported by grant SEP-CONACYT 252577 given to I. Amaro-Estrada.

Keywords: bovine anaplasmosis, peptides, phage display, veterinary vaccines

Procedia PDF Downloads 129

Authors: Sanjeev Gupta, Ankit Prabhakar, K. Rajkumar Singh

Abstract:

Sunni Dam Hydroelectric Project (382 MW) is a run of river type development with an underground powerhouse, proposed to harness the hydel potential of river Satluj in Himachal Pradesh, India. The project is located in the inner lesser Himalaya between Dhauladhar Range in the south and the higher Himalaya in the north. The project comprises two large underground caverns, a Powerhouse cavern (171m long, 22.5m wide and 51.2m high) and another transformer hall cavern (175m long, 18.7m wide and 27m high) and the rock pillar between the two caverns is 50m. The highly jointed, fractured, anisotropic rock mass is a key challenge in Himalayan geology for an underground structure. The concern for the stability of rock mass increases when weak/shear zones are encountered in the underground structure. In the Sunni Dam project, 1.7m to 2m thick weak/shear zone comprising of deformed, weak material with gauge has been encountered in powerhouse cavern at 70m having dip direction 325 degree and dip amount 38 degree which also intersects transformer hall at initial reach. The rock encountered in the powerhouse area is moderate to highly jointed, pink quartz arenite belonging to the Khaira Formation, a transition zone comprising of alternate grey, pink & white quartz arenite and shale sequence and dolomite at higher reaches. The rock mass is intersected by mainly 3 joint sets excluding bedding joints and a few random joints. The rock class in powerhouse mainly varies from poor class (class IV) to lower order fair class (class III) and in some reaches, very poor rock mass has also been encountered. To study the stability of the underground structure in weak/shear rock mass, a 3D numerical model analysis has been carried out using RS3 software. Field studies have been interpreted and analysed to derive Bieniawski’s RMR, Barton’s “Q” class and Geological Strength Index (GSI). The various material parameters, in-situ characteristics have been determined based on tests conducted by Central Soil and Materials Research Station, New Delhi. The behaviour of the cavern has been studied by assessing the displacement contours, major and minor principal stresses and plastic zones for different stage excavation sequences. For optimisation of the support system, the stability of the powerhouse cavern with different powerhouse orientations has also been studied. The numerical modeling results indicate that cavern will not likely face stress governed by structural instability with the support system to be applied to the crown and side walls.

Keywords: 3D analysis, Himalayan geology, shear zone, underground power house

Procedia PDF Downloads 75

Authors: Shirley S. Ho

Abstract:

The advancement and development of social media have inadvertently brought about a new form of bullying – cyberbullying – that transcends across physical boundaries of space. Although extensive research has been conducted in the field of cyberbullying, most of these studies have taken an overwhelmingly empirical angle. Theories guiding cyberbullying research are few. Furthermore, very few studies have explored the association between parental mediation and cyberbullying, with majority of existing studies focusing on cyberbullying victimization rather than perpetration. Therefore, this present study investigates cyberbullying perpetration from a theoretical angle, with a focus on the Theory of Reasoned Action and the Parental Mediation Theory. More specifically, this study examines the direct effects of attitude, subjective norms, descriptive norms, injunctive norms and active mediation and restrictive mediation on cyberbullying perpetration on social media among children and adolescents in Singapore. Furthermore, the moderating role of age on the relationship between parental mediation and cyberbullying perpetration on social media are examined. A self-administered paper-and-pencil nationally-representative survey was conducted. Multi-stage cluster random sampling was used to ensure that schools from all the four (North, South, East, and West) regions of Singapore were equally represented in the sample used for the survey. In all 607 upper primary school children (i.e., Primary 4 to 6 students) and 782 secondary school adolescents participated in our survey. The total average response rates were 69.6% for student participation. An ordinary least squares hierarchical regression analysis was conducted to test the hypotheses and research questions. The results revealed that attitude and subjective norms were positively associated with cyberbullying perpetration on social media. Descriptive norms and injunctive norms were not found to be significantly associated with cyberbullying perpetration. The results also showed that both parental mediation strategies were negatively associated with cyberbullying perpetration on social media. Age was a significant moderator of both parental mediation strategies and cyberbullying perpetration. The negative relationship between active mediation and cyberbullying perpetration was found to be greater in the case of children than adolescents. Children who received high restrictive parental mediation were less likely to perform cyberbullying behaviors, while adolescents who received high restrictive parental mediation were more likely to be engaged in cyberbullying perpetration. The study reveals that parents should apply active mediation and restrictive mediation in different ways for children and adolescents when trying to prevent cyberbullying perpetration. The effectiveness of active parental mediation for reducing cyberbullying perpetration was more in the case of children than for adolescents. Younger children were found to be more likely to respond more positively toward restrictive parental mediation strategies, but in the case of adolescents, overly restrictive control was found to increase cyberbullying perpetration. Adolescents exhibited less cyberbullying behaviors when under low restrictive strategies. Findings highlight that the Theory of Reasoned Action and Parental Mediation Theory are promising frameworks to apply in the examination of cyberbullying perpetration. The findings that different parental mediation strategies had differing effectiveness, based on the children’s age, bring about several practical implications that may benefit educators and parents when addressing their children’s online risk.

Keywords: cyberbullying perpetration, theory of reasoned action, parental mediation, social media, Singapore

Procedia PDF Downloads 241

Authors: Hanan Algarni

Abstract:

Background: Impairment of walking and balance skills has negative impact on functional independence and community participation after stroke. Gait recovery is considered a primary goal in rehabilitation by both patients and physiotherapists. Treadmill training coupled with virtual reality technology is a new emerging approach that offers patients with feedback, open and random skills practice while walking and interacting with virtual environmental scenes. Objectives: To synthesize the evidence around the effects of the VR treadmill training on gait speed and balance primarily, functional independence and community participation secondarily in stroke patients. Methods: Systematic review was conducted; search strategy included electronic data bases: MEDLINE, AMED, Cochrane, CINAHL, EMBASE, PEDro, Web of Science, and unpublished literature. Inclusion criteria: Participant: adult >18 years, stroke, ambulatory, without severe visual or cognitive impartments. Intervention: VR treadmill training alone or with physiotherapy. Comparator: any other interventions. Outcomes: gait speed, balance, function, community participation. Characteristics of included studies were extracted for analysis. Risk of bias assessment was performed using Cochrane's ROB tool. Narrative synthesis of findings was undertaken and summary of findings in each outcome was reported using GRADEpro. Results: Four studies were included involving 84 stroke participants with chronic hemiparesis. Interventions intensity ranged (6-12 sessions, 20 minutes-1 hour/session). Three studies investigated the effects on gait speed and balance. 2 studies investigated functional outcomes and one study assessed community participation. ROB assessment showed 50% unclear risk of selection bias and 25% of unclear risk of detection bias across the studies. Heterogeneity was identified in the intervention effects at post training and follow up. Outcome measures, training intensity and durations also varied across the studies, grade of evidence was low for balance, moderate for speed and function outcomes, and high for community participation. However, it is important to note that grading was done on few numbers of studies in each outcome. Conclusions: The summary of findings suggests positive and statistically significant effects (p<0.05) of VR treadmill training compared to other interventions on gait speed, dynamic balance skills, function and participation directly after training. However, the effects were not sustained at follow up in two studies (2 weeks-1 month) and other studies did not perform follow up measurements. More RCTs with larger sample sizes and higher methodological quality are required to examine the long term effects of VR treadmill effects on function independence and community participation after stroke, in order to draw conclusions and produce stronger robust evidence.

Keywords: virtual reality, treadmill, stroke, gait rehabilitation

Procedia PDF Downloads 266

Authors: Merouane Salhi, Mohamed Roudane, Abdelkader Kirad

Abstract:

In this work, we present a new form of characteristics method, which is a technique for solving partial differential equations. Typically, it applies to first-order equations; the aim of this method is to reduce a partial differential equation to a family of ordinary differential equations along which the solution can be integrated from some initial data. This latter developed under the real gas theory, because when the thermal and the caloric imperfections of a gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with the gas parameters. The gas doesn’t stay perfect. Its state equation change and it becomes for a real gas. The presented equations of the characteristics remain valid whatever area or field of study. Here we need have inserted the developed Prandtl Meyer function in the mathematical system to find a new model when the effect of stagnation pressure is taken into account. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation, the thermodynamic parameters and the value of Prandtl Meyer function. However, with the assumptions that Berthelot’s state equation accounts for molecular size and intermolecular force effects, expressions are developed for analyzing the supersonic flow for thermally and calorically imperfect gas. The supersonic parameters depend directly on the stagnation parameters of the combustion chamber. The resolution has been made by the finite differences method using the corrector predictor algorithm. As results, the developed mathematical model used to design 2D minimum length nozzles under effect of the stagnation parameters of fluid flow. A comparison for air with the perfect gas PG and high temperature models on the one hand and our results by the real gas theory on the other of nozzles shapes and characteristics are made.

Keywords: numerical methods, nozzles design, real gas, stagnation parameters, supersonic expansion, the characteristics method

Procedia PDF Downloads 228

Authors: Maciej Szeląg

Abstract:

The changing nature of environmental impacts, in which cement composites are operating, are causing in the structure of the material a number of phenomena, which result in volume deformation of the composite. These strains can cause composite cracking. Cracks are merging by propagation or intersect to form a characteristic structure of cracks known as the cluster cracks. This characteristic mesh of cracks is crucial to almost all building materials, which are working in service loads conditions. Particularly dangerous for a cement matrix is a sudden load of elevated temperature – the thermal shock. Resulting in a relatively short period of time a large value of a temperature gradient between the outer surface and the material’s interior can result in cracks formation on the surface and in the volume of the material. In the paper, in order to analyze the geometry of the cluster cracks of the cement pastes, the image analysis tools were used. Tested were 4 series of specimens made of two different Portland cement. In addition, two series include microsilica as a substitute for the 10% of the cement. Within each series, specimens were performed in three w/b indicators (water/binder): 0.4; 0.5; 0.6. The cluster cracks were created by sudden loading the samples by elevated temperature of 250°C. Images of the cracked surfaces were obtained via scanning at 2400 DPI. Digital processing and measurements were performed using ImageJ v. 1.46r software. To describe the structure of the cluster cracks three stereological parameters were proposed: the average cluster area - A ̅, the average length of cluster perimeter - L ̅, and the average opening width of a crack between clusters - I ̅. The aim of the study was to identify and evaluate the relationships between measured stereological parameters, and the compressive strength and the bulk density of the modified cement pastes. The tests of the mechanical and physical feature have been carried out in accordance with EN standards. The curves describing the relationships have been developed using the least squares method, and the quality of the curve fitting to the empirical data was evaluated using three diagnostic statistics: the coefficient of determination – R2, the standard error of estimation - Se, and the coefficient of random variation – W. The use of image analysis allowed for a quantitative description of the cluster cracks’ geometry. Based on the obtained results, it was found a strong correlation between the A ̅ and L ̅ – reflecting the fractal nature of the cluster cracks formation process. It was noted that the compressive strength and the bulk density of cement pastes decrease with an increase in the values of the stereological parameters. It was also found that the main factors, which impact on the cluster cracks’ geometry are the cement particles’ size and the general content of the binder in a volume of the material. The microsilica caused the reduction in the A ̅, L ̅ and I ̅ values compared to the values obtained by the classical cement paste’s samples, which is caused by the pozzolanic properties of the microsilica.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, microsilica, stereological parameters

Procedia PDF Downloads 238

Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

Abstract:

Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

Procedia PDF Downloads 479

Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

Procedia PDF Downloads 146

Authors: W. Staiano, S. Marcora

Abstract:

Introduction: It has been proposed that acute negative effect of mental fatigue (MF) could potentially become a training stimulus for the brain (Brain endurance training (BET)) to adapt and improve its ability to attenuate MF states during sport competitions. Purpose: The aim of this study was to test the efficacy of 6 weeks of BET on cognitive and cycling tests in a group of well-trained subjects. We hypothesised that combination of BET and standard physical training (SPT) would increase cognitive capacity and cycling performance by reducing rating of perceived exertion (RPE) and increase resilience to fatigue more than SPT alone. Methods: In a randomized controlled trial design, 26 well trained participants, after a familiarization session, cycled to exhaustion (TTE) at 80% peak power output (PPO) and, after 90 min rest, at 65% PPO, before and after random allocation to a 6 week BET or active placebo control. Cognitive performance was measured using 30 min of STROOP coloured task performed before cycling performance. During the training, BET group performed a series of cognitive tasks for a total of 30 sessions (5 sessions per week) with duration increasing from 30 to 60 min per session. Placebo engaged in a breathing relaxation training. Both groups were monitored for physical training and were naïve to the purpose of the study. Physiological and perceptual parameters of heart rate, lactate (LA) and RPE were recorded during cycling performances, while subjective workload (NASA TLX scale) was measured during the training. Results: Group (BET vs. Placebo) x Test (Pre-test vs. Post-test) mixed model ANOVA’s revealed significant interaction for performance at 80% PPO (p = .038) or 65% PPO (p = .011). In both tests, groups improved their TTE performance; however, BET group improved significantly more compared to placebo. No significant differences were found for heart rate during the TTE cycling tests. LA did not change significantly at rest in both groups. However, at completion of 65% TTE, it was significantly higher (p = 0.043) in the placebo condition compared to BET. RPE measured at ISO-time in BET was significantly lower (80% PPO, p = 0.041; 65% PPO p= 0.021) compared to placebo. Cognitive results in the STROOP task showed that reaction time in both groups decreased at post-test. However, BET decreased significantly (p = 0.01) more compared to placebo despite no differences accuracy. During training sessions, participants in the BET showed, through NASA TLX questionnaires, constantly significantly higher (p < 0.01) mental demand rates compared to placebo. No significant differences were found for physical demand. Conclusion: The results of this study provide evidences that combining BET and SPT seems to be more effective than SPT alone in increasing cognitive and cycling performance in well trained endurance participants. The cognitive overload produced during the 6-week training of BET can induce a reduction in perception of effort at a specific power, and thus improving cycling performance. Moreover, it provides evidence that including neurocognitive interventions will benefit athletes by increasing their mental resilience, without affecting their physical training load and routine.

Keywords: cognitive training, perception of effort, endurance performance, neuro-performance

Procedia PDF Downloads 109

Authors: Dipak Sen, Rajdeep Ghosh

Abstract:

This paper presents a computational study of steady state three dimensional very high turbulent flow and heat transfer characteristics in a constant temperature-surfaced circular duct fitted with 900 hemispherical inline baffles. The computations are based on realizable k-ɛ model with standard wall function considering the finite volume method, and the SIMPLE algorithm has been implemented. Computational Study are carried out for Reynolds number, Re ranging from 80000 to 120000, Prandtl Number, Pr of 0.73, Pitch Ratios, PR of 1,2,3,4,5 based on the hydraulic diameter of the channel, hydrodynamic entry length, thermal entry length and the test section. Ansys Fluent 15.0 software has been used to solve the flow field. Study reveals that circular pipe having baffles has a higher Nusselt number and friction factor compared to the smooth circular pipe without baffles. Maximum Nusselt number and friction factor are obtained for the PR=5 and PR=1 respectively. Nusselt number increases while pitch ratio increases in the range of study; however, friction factor also decreases up to PR 3 and after which it becomes almost constant up to PR 5. Thermal enhancement factor increases with increasing pitch ratio but with slightly decreasing Reynolds number in the range of study and becomes almost constant at higher Reynolds number. The computational results reveal that optimum thermal enhancement factor of 900 inline hemispherical baffle is about 1.23 for pitch ratio 5 at Reynolds number 120000.It also shows that the optimum pitch ratio for which the baffles can be installed in such very high turbulent flows should be 5. Results show that pitch ratio and Reynolds number play an important role on both fluid flow and heat transfer characteristics.

Keywords: friction factor, heat transfer, turbulent flow, circular duct, baffle, pitch ratio

Procedia PDF Downloads 362