Search results for: Gyro Orientation Measurement Unit (Gyro OMU)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5785

Search results for: Gyro Orientation Measurement Unit (Gyro OMU)

3025 A Convolution Neural Network PM-10 Prediction System Based on a Dense Measurement Sensor Network in Poland

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

Abstract:

PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 149
3024 On-Line Data-Driven Multivariate Statistical Prediction Approach to Production Monitoring

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

Procedia PDF Downloads 356
3023 Wear Particle Analysis from used Gear Lubricants for Maintenance Diagnostics

Authors: Surapol Raadnui

Abstract:

This particular work describes an experimental investigation on gear wear in which wear and pitting were intentionally allowed to occur, namely, moisture corrosion pitting, acid-induced corrosion pitting, hard contaminant-related pitting and mechanical induced wear. A back to back spur gear test rig and a grease lubricated worm gear rig were used. The tests samples of wear debris were collected and assessed through the utilization of an optical microscope in order to correlate and compare the debris morphology to pitting and wear degradation of the worn gears. In addition, weight loss from all test gear pairs were assessed with utilization of statistical design of experiment. It can be deduced that wear debris characteristics from both cases exhibited a direct relationship with different pitting and wear modes. Thus, it should be possible to detect and diagnose gear pitting and wear utilization of worn surfaces, generated wear debris and quantitative measurement such as weight loss.

Keywords: predictive maintenance, worm gear, spur gear, wear debris analysis, problem diagnostic

Procedia PDF Downloads 153
3022 Understanding the Experience of Siblings in Multisystemic Therapy

Authors: Lily Beaumont-Griffin, Philip Reynolds, Helen Pote, Pinder Kaur

Abstract:

Siblings are a key part of the family unit, which Multisystemic Therapy (MST) intervenes, with the aim of reducing antisocial behavior and keeping families together. However, despite operating in multiple countries, including the United States of America, Europe, parts of South America, and the Western Hemisphere, there are only few previous studies on siblings within MST. According to best of authors knowledge neither of these seeks to understand the siblings' experience of the intervention nor their perception of the outcomes. This study utilized semi-structured interviews to understand the experience of seven siblings of children and adolescents who were closed to MST within the last year (2023-2024). Using reflexive thematic analysis, three themes were identified: sibling inclusion by the therapist, sharing responsibility for change, and fostering a safe and supportive environment at home. These themes express that siblings need to have a basic understanding of an intervention to be able to perceive benefits, siblings need help understanding responsibility across the whole family, and that safety is both physical and emotional. Clinical implications, including encouragement of therapists to integrate the siblings in the intervention more, and future research directions around integrating these findings into the development of iterations of MST standard are discussed.

Keywords: siblings, multisystemic therapy, family therapy, experience

Procedia PDF Downloads 47
3021 Servant Leadership for Elder Care in St. Camillus Health Systems, USA

Authors: Anthoni Jeorge

Abstract:

Throughout the history of the world, servant leadership has been researched, and favourable results such as individual, team, and organizational have been linked to the construct. This research paper designates St. Camillus de Lellis, a practitioner of servant leadership and founder of the Ministers of the Sick as a servant leader in his approach to care for the sick. Service is the visible face of his servant leadership. First of all, despite many challenges, St. Camillus de Lellis practiced leadership by the example of compassionate service to the sick. Second, he made service to the sick the highest priority of his life. Third, Camillus displayed servant leadership such that his manner of leadership gave birth to a New School of Service to the Sick. The paper identifies the distinctive dimensions and essential elements which characterized his service-centered leadership. Furthermore, discuss the six major characteristics of a servant leader as set forth by St. Camillus’s life example. The research illustrates the transformational power of servant leadership infield healthcare in general and, in doing so, provides servant leadership seekers ways servant leadership can transform elder care in one’s own field (St. Camillus Health Systems). Thus, it ascertains that servant leadership is best-fit for humanized elder care. Supported by the review of literature, the paper ascertains that Camillus, by identifying himself with the sick, gained deeper insights concerning the pain and suffering of the population. Uniquely drawn from his true grit, Camillus’ service-centered leadership is value-based, people-oriented, and compassion-filled. His way of service to the sick is the prolongation of gestures of mercy and compassion. It is hoped that the results of this study will help health care workers and servant leadership practitioners to humanize elder care and cultivate servant leadership attitude in their health care services to the sick. By incorporating such service-oriented elements into their leadership orientation, health care workers will be true servant leaders of the sick.

Keywords: leadership, service, healthcare, compassion

Procedia PDF Downloads 164
3020 Enhancing the Bionic Eye: A Real-time Image Optimization Framework to Encode Color and Spatial Information Into Retinal Prostheses

Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

Procedia PDF Downloads 153
3019 Complex Cooling Approach in Microchannel Heat Exchangers Using Solid and Hollow Fins

Authors: Nahum Yustus Godi

Abstract:

A three-dimensional numerical optimisation of combined microchannels with constructal solid, half hollow, and hollow circular fins is documented in this paper. The technique seeks to minimize peak temperature in the entire volume of the microchannel heat sink. The volume and axial length were all fixed, while the width of the microchannel could morph. High-density heat flux was applied at the bottom wall of the microchannel. The coolant employed to remove the heat deposited at the bottom surface of the microchannel was a single-phase fluid (water) in a forced convection laminar condition, and heat transfer was a conjugate problem. The unit cell symmetrical computation domain was discretised, and governing equations were solved using computational fluid dynamic (CFD) code. The results reveal that the combined microchannel with hollow circular fins and solid fins performed better at different Reynolds numbers. The numerical study was validated for the single microchannel without fins and found to be in good agreement with previous studies.

Keywords: constructal fins, complex heat exchangers, cooling technique, numerical optimisation

Procedia PDF Downloads 225
3018 An Investigation of Water Atomizer in Ejected Gas of a Vehicle Engine

Authors: Chun-Wei Liu, Feng-Tsai Weng

Abstract:

People faced pollution threaten in modern age although the standard of exhaust gas of vehicles has been established. The goal of this study is to investigate the effect of water atomizer in a vehicle emission system. Diluted 20% ammonia water was used in spraying system. Micro particles produced by exhausted gas from engine of vehicle which were cumulated through atomized spray in a self-development collector. In experiments, a self-designed atomization model plate and a gas tank controlled by the micro-processor using Pulse Width Modulation (PWM) logic was prepared for exhaust test. The gas from gasoline-engine of vehicle was purified with the model panel collector. A soft well named ANSYS was utilized for analyzing the distribution condition of rejected gas. Micro substance and percentage of CO, HC, CO2, NOx in exhausted gas were investigated at different engine speed, and atomizer vibration frequency. Exceptional results in the vehicle engine emissions measurement were obtained. The temperature of exhausted gas can be decreased 3oC. Micro substances PM10 can be decreased and the percentage of CO can be decreased more than 55% at 2500RPM by proposed system. Value of CO, HC, CO2 and NOX was all decreased when atomizers were used with water.

Keywords: atomizer, CO, HC, NOx, PM2.5

Procedia PDF Downloads 457
3017 Water Leakage Detection System of Pipe Line using Radial Basis Function Neural Network

Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

Abstract:

Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

Procedia PDF Downloads 358
3016 Evaluation Synthesis of Private Sector Engagement in International Development

Authors: Valerie Habbel, Magdalena Orth, Johanna Richter, Steffen Schimko

Abstract:

Cooperation between development actors and the private sector is becoming increasingly important, as it is expected to mobilize additional resources to achieve the Sustainable Development Goals (SDGs), among other things. However, whether the goals of cooperation are achieved has so far only been explored in evaluations and studies of individual projects and instruments. The evaluation synthesis attempts to close this gap by systematically analyzing existing evidence (evaluations and academic studies) from national and international development cooperation on private sector engagement. Overall, the evaluations and studies considered report mainly positive effects on investors and donors, intermediaries, partner countries, and target groups. However, various analyses, including on the quality of the evaluations, point to a positive bias in the results. The evaluation synthesis makes recommendations on the definition of indicators, the measurement and evaluation of impacts and additionality, knowledge management, and the consideration of transaction costs in cooperation with private actors.

Keywords: evaluation synthesis, private sector engagement, international development, sustainable development

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3015 A Content Analysis of Sustainability Reporting to Frame the Heterogeneity in Corporate Environment Sustainability Practices

Authors: Venkataraman Sankaranarayanan, Sougata Ray

Abstract:

While extant research has examined many aspects of differential corporate environmental outcomes and behavior, a holistic and integrated view of heterogeneity in corporate environment sustainability (CES) practices remains a puzzle to be fully unraveled – its extent and nature, its relationship to macro or micro level influences, or strategic orientations. Such a perspective would be meaningful for the field given notable strides in CES practices and the corporate social responsibility agenda over the last two decades, in the backdrop of altered global socio-political sensitivities and technological advances. To partly address this gap, this exploratory research adopted a content analysis approach to code patterns in the sustainability disclosures of the 160 largest global firms spread over 8 years. The sample of firms spanned seven industries, nine countries and three continents thereby presenting data rich and diverse enough in several dimensions to be representative of global heterogeneity in CES practices. Through a factor analysis of the coded data, four strategic CES orientations were extracted through the analysis, that effectively straddles most of the variation observed in current CES practices – one that seeks to reduce environmental damage on account of the firm’s operations, another that prioritizes minimalism, a third that focuses on broader ecological status quo, and a final one that champions the ‘business of green’, extending the CES agenda beyond the firm’s boundaries. These environment sustainability strategy orientations are further examined to elicit prominent patterns and explore plausible antecedents.

Keywords: corporate social responsibility, corporate sustainability, environmental management, heterogeneity, strategic orientation

Procedia PDF Downloads 334
3014 A Hybrid Simulation Approach to Evaluate Cooling Energy Consumption for Public Housings of Subtropics

Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

Abstract:

Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

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3013 Use of Structural Family Therapy and Dialectical Behavior Therapy with High-Conflict Couples

Authors: Eman Tadros, Natasha Finney

Abstract:

The following case study involving a high-conflict, Children’s Services Bureau (CSB) referred couple is analyzed and reviewed through an integrated lens of structural family therapy and dialectical behavior therapy. In structural family therapy, normal family development is not characterized by a lack of problems, but instead by families’ having developed a functional structure for dealing with their problems. Whereas, in dialectical behavioral therapy normal family development can be characterized by having a supportive and validating environment, where all family members feel a sense of acceptance and validation for who they are and where they are in life. The clinical case conceptualization highlights the importance of conceptualizing how change occurs within a therapeutic setting. In the current case study, the couple did not only experience high-conflict, but there were also issues of substance use, health issues, and other complicating factors. Clinicians should view their clients holistically and tailor their treatment to fit their unique needs. In this framework, change occurs within the family unit, by accepting each member as they are, while at the same time working together to change maladaptive familial structures.

Keywords: couples, dialectical behavior therapy, high-conflict, structural family therapy

Procedia PDF Downloads 349
3012 Effect of Dietary Supplementation of Ashwagandha (Withania somnifera) on Performance of Commercial Layer Hens

Authors: P. Arun Subhash, B. N. Suresh, M. C. Shivakumar, N. Suma

Abstract:

An experiment was conducted to study the effect of dietary supplementation of ashwagandha (Withania somnifera) root powder on the egg production performance and egg quality in commercial layer birds. A practical type layer diet was prepared as per Bureau of Indian Standards (1992) to serve as the control, and the test diet was prepared by supplementing control diet with ashwagandha powder at 1kg/ton of feed. Each diet was assigned to twenty replicate groups of 5 laying hens each for duration of 84 days. The result revealed that cumulative egg production (%) was comparable between control and test group. The feed consumption and its conversion efficiency were similar among both the groups. The egg weight and egg characteristics viz., yolk index, yolk color, haugh unit score, albumen index, egg shape index and eggshell thickness were also remained similar between both the groups. It was concluded that supplementation of ashwagandha powder at 1kg/ton in layer diets has no beneficial effect on egg production and egg quality parameters.

Keywords: ashwagandha, egg production, egg quality, layers

Procedia PDF Downloads 147
3011 Generation of Automated Alarms for Plantwide Process Monitoring

Authors: Hyun-Woo Cho

Abstract:

Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

Procedia PDF Downloads 252
3010 Planktivorous Fish Schooling Responses to Current at Natural and Artificial Reefs

Authors: Matthew Holland, Jason Everett, Martin Cox, Iain Suthers

Abstract:

High spatial-resolution distribution of planktivorous reef fish can reveal behavioural adaptations to optimise the balance between feeding success and predator avoidance. We used a multi-beam echosounder to record bathymetry and the three-dimensional distribution of fish schools associated with natural and artificial reefs. We utilised generalised linear models to assess the distribution, orientation, and aggregation of fish schools relative to the structure, vertical relief, and currents. At artificial reefs, fish schooled more closely to the structure and demonstrated a preference for the windward side, particularly when exposed to strong currents. Similarly, at natural reefs fish demonstrated a preference for windward aspects of bathymetry, particularly when associated with high vertical relief. Our findings suggest that under conditions with stronger current velocity, fish can exercise their preference to remain close to structure for predator avoidance, while still receiving an adequate supply of zooplankton delivered by the current. Similarly, when current velocity is low, fish tend to disperse for better access to zooplankton. As artificial reefs are generally deployed with the goal of creating productivity rather than simply attracting fish from elsewhere, we advise that future artificial reefs be designed as semi-linear arrays perpendicular to the prevailing current, with multiple tall towers. This will facilitate the conversion of dispersed zooplankton into energy for higher trophic levels, enhancing reef productivity and fisheries.

Keywords: artificial reef, current, forage fish, multi-beam, planktivorous fish, reef fish, schooling

Procedia PDF Downloads 158
3009 Complex Dynamics in a Morphologically Heterogeneous Biological Medium

Authors: Turky Al-Qahtani, Roustem Miftahof

Abstract:

Introduction: Under common assumptions of excitabi-lity, morphological (cellular) homogeneity, and spatial structural anomalies added as required, it has been shown that biological systems are able to display travelling wave dynamics. Being not self-sustainable, existence depends on the electrophysiological state of transmembrane ion channels and it requires an extrinsic/intrinsic periodic source. However, organs in the body are highly multicellular, heterogeneous, and their functionality is the outcome of electro-mechanical conjugation, rather than excitability only. Thus, peristalsis in the gut relies on spatiotemporal myoelectrical pattern formations between the mechanical, represented by smooth muscle cells (SM), and the control, comprised of a chain of primary sensory and motor neurones, components. Synaptically linked through the afferent and efferent pathways, they form a functional unit (FU) of the gut. Aims: These are: i) to study numerically the complex dynamics, and ii) to investigate the possibility of self-sustained myoelectrical activity in the FU. Methods: The FU recreates the following sequence of physiological events: deformation of mechanoreceptors of located in SM; generation and propagation of electrical waves of depolarisation - spikes - along the axon to the soma of the primary neurone; discharge of the primary neurone and spike propagation towards the motor neurone; burst of the motor neurone and transduction of spikes to SM, subsequently producing forces of contraction. These are governed by a system of nonlinear partial and ordinary differential equations being a modified version of the Hodgkin-Huxley model and SM fibre mechanics. In numerical experiments; the source of excitation is mechanical stretches of SM at a fixed amplitude and variable frequencies. Results: Low frequency (0.5 < v < 2 Hz) stimuli cause the propagation of spikes in the neuronal chain and, finally, the generation of active forces by SM. However, induced contractions are not sufficient to initiate travelling wave dynamics in the control system. At frequencies, 2 < v < 4 Hz, multiple low amplitude and short-lasting contractions are observed in SM after the termination of stretching. For frequencies (0.5 < v < 4 Hz), primary and sensory neurones demonstrate strong connectivity and coherent electrical activity. Significant qualitative and quantitative changes in dynamics of myoelectical patterns with a transition to a self-organised mode are recorded with the high degree of stretches at v = 4.5 Hz. Increased rates of deformation lead to the production of high amplitude signals at the mechanoreceptors with subsequent self-sustained excitation within the neuronal chain. Remarkably, the connection between neurones weakens resulting in incoherent firing. Further increase in a frequency of stimulation (v > 4.5 Hz) has a detrimental effect on the system. The mechanical and control systems become disconnected and exhibit uncoordinated electromechanical activity. Conclusion: To our knowledge, the existence of periodic activity in a multicellular, functionally heterogeneous biological system with mechano-electrical dynamics, such as the FU, has been demonstrated for the first time. These findings support the notion of possible peristalsis in the gut even in the absence of intrinsic sources - pacemaker cells. Results could be implicated in the pathogenesis of intestinal dysrythmia, a medical condition associated with motor dysfunction.

Keywords: complex dynamics, functional unit, the gut, dysrythmia

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3008 Exploring Digital Media’s Impact on Sports Sponsorship: A Global Perspective

Authors: Sylvia Chan-Olmsted, Lisa-Charlotte Wolter

Abstract:

With the continuous proliferation of media platforms, there have been tremendous changes in media consumption behaviors. From the perspective of sports sponsorship, while there is now a multitude of platforms to create brand associations, the changing media landscape and shift of message control also mean that sports sponsors will have to take into account the nature of and consumer responses toward these emerging digital media to devise effective marketing strategies. Utilizing the personal interview methodology, this study is qualitative and exploratory in nature. A total of 18 experts from European and American academics, sports marketing industry, and sports leagues/teams were interviewed to address three main research questions: 1) What are the major changes in digital technologies that are relevant to sports sponsorship; 2) How have digital media influenced the channels and platforms of sports sponsorship; and 3) How have these technologies affected the goals, strategies, and measurement of sports sponsorship. The study found that sports sponsorship has moved from consumer engagement, engagement measurement, and consequences of engagement on brand behaviors to micro-targeting one on one, engagement by context, time, and space, and activation and leveraging based on tracking and databases. From the perspective of platforms and channels, the use of mobile devices is prominent during sports content consumption. Increasing multiscreen media consumption means that sports sponsors need to optimize their investment decisions in leagues, teams, or game-related content sources, as they need to go where the fans are most engaged in. The study observed an imbalanced strategic leveraging of technology and digital infrastructure. While sports leagues have had less emphasis on brand value management via technology, sports sponsors have been much more active in utilizing technologies like mobile/LBS tools, big data/user info, real-time marketing and programmatic, and social media activation. Regardless of the new media/platforms, the study found that integration and contextualization are the two essential means of improving sports sponsorship effectiveness through technology. That is, how sponsors effectively integrate social media/mobile/second screen into their existing legacy media sponsorship plan so technology works for the experience/message instead of distracting fans. Additionally, technological advancement and attention economy amplify the importance of consumer data gathering, but sports consumer data does not mean loyalty or engagement. This study also affirms the benefit of digital media as they offer viral and pre-event activations through storytelling way before the actual event, which is critical for leveraging brand association before and after. That is, sponsors now have multiple opportunities and platforms to tell stories about their brands for longer time period. In summary, digital media facilitate fan experience, access to the brand message, multiplatform/channel presentations, storytelling, and content sharing. Nevertheless, rather than focusing on technology and media, today’s sponsors need to define what they want to focus on in terms of content themes that connect with their brands and then identify the channels/platforms. The big challenge for sponsors is to play to the venues/media’s specificity and its fit with the target audience and not uniformly deliver the same message in the same format on different platforms/channels.

Keywords: digital media, mobile media, social media, technology, sports sponsorship

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3007 Measurement of Thermal Protrusion Profile in Magnetic Recording Heads via Wyko Interferometry

Authors: Joseph Christopher R. Ragasa, Paolo Gabriel P. Casas, Nemesio S. Mangila, Maria Emma C. Villamin, Myra G. Bungag

Abstract:

A procedure in measuring the thermal protrusion profiles of magnetic recording heads was developed using a Wyko HD-8100 optical interference-based instrument. The protrusions in the heads were made by the application of a constant power through the thermal flying height controller pads. It was found that the thermally-induced bubble is confined to form in the same head locations, primarily in the reader and writer regions, regardless of the direction of approach of temperature. An application of power to the thermal flying height control pads ranging from 0 to 50 milliWatts showed that the protrusions demonstrate a linear dependence with the supplied power. The efficiencies calculated using this method were compared to that obtained through Guzik and found to be 19.57% greater due to the static testing environment used in the testing.

Keywords: thermal protrusion profile, magnetic recording heads, wyko interferometry, thermal flying height control

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3006 Influence of Antecedent Soil Moisture on Soil Erosion: A Two-Year Field Study

Authors: Yu-Da Chen, Chia-Chun Wu

Abstract:

The relationship between antecedent soil moisture content and soil erosion is a complicated phenomenon. Some studies confirm the effect of antecedent soil moisture content on soil erosion, but some deny it. Therefore, the objective of this study is to clarify such contradictions through field experiments. This study conducted two-year field observations of soil losses from natural rainfall events on runoff plots with a length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log the soil moisture changes for each rainfall event. A total of 49 effective events were monitored. Results of this study show that antecedent soil moisture content promotes the generation of surface runoff, especially for rainfall events with short duration or lower magnitudes. A positive correlation was found between antecedent soil moisture content and soil loss per unit Rainfall-Runoff Erosivity Index, which indicated that soil with high moisture content is more susceptible to detachment. Once the rainfall duration exceeds 10 hours, the impact from the rainfall duration to soil erosion overwrites, and the effect of antecedent soil moisture is almost negligible.

Keywords: antecedent soil moisture content, soil loss, runoff coefficient, rainfall-runoff erosivity

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3005 Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia

Authors: The Danh Phan

Abstract:

House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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3004 Numerical Performance Evaluation of a Savonius Wind Turbines Using Resistive Torque Modeling

Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

Abstract:

The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

Procedia PDF Downloads 156
3003 Mapping of Geological Structures Using Aerial Photography

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

Abstract:

Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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3002 Fault Detection and Isolation of a Three-Tank System using Analytical Temporal Redundancy, Parity Space/Relation Based Residual Generation

Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

Abstract:

This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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3001 Microstructure Evolution and Pre-transformation Microstructure Reconstruction in Ti-6Al-4V Alloy

Authors: Shreyash Hadke, Manendra Singh Parihar, Rajesh Khatirkar

Abstract:

In the present investigation, the variation in the microstructure with the changes in the heat treatment conditions i.e. temperature and time was observed. Ti-6Al-4V alloy was subject to solution annealing treatments in β (1066C) and α+β phase (930C and 850C) followed by quenching, air cooling and furnace cooling to room temperature respectively. The effect of solution annealing and cooling on the microstructure was studied by using optical microscopy (OM), scanning electron microscopy (SEM), electron backscattered diffraction (EBSD) and x-ray diffraction (XRD). The chemical composition of the β phase for different conditions was determined with the help of energy dispersive spectrometer (EDS) attached to SEM. Furnace cooling resulted in the development of coarser structure (α+β), while air cooling resulted in much finer structure with widmanstatten morphology of α at the grain boundaries. Quenching from solution annealing temperature formed α’ martensite, their proportion being dependent on the temperature in β phase field. It is well known that the transformation of β to α follows Burger orientation relationship (OR). In order to reconstruct the microstructure of parent β phase, a MATLAB code was written using neighbor-to-neighbor, triplet method and Tari’s method. The code was tested on the annealed samples (1066C solution annealing temperature followed by furnace cooling to room temperature). The parent phase data thus generated was then plotted using the TSL-OIM software. The reconstruction results of the above methods were compared and analyzed. The Tari’s approach (clustering approach) gave better results compared to neighbor-to-neighbor and triplet method but the time taken by the triplet method was least compared to the other two methods.

Keywords: Ti-6Al-4V alloy, microstructure, electron backscattered diffraction, parent phase reconstruction

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3000 Skin-to-Skin Contact Simulation: Improving Health Outcomes for Medically Fragile Newborns in the Neonatal Intensive Care Unit

Authors: Gabriella Zarlenga, Martha L. Hall

Abstract:

Introduction: Premature infants are at risk for neurodevelopmental deficits and hospital readmissions, which can increase the financial burden on the health care system and families. Kangaroo care (skin-to-skin contact) is a practice that can improve preterm infant health outcomes. Preterm infants can acquire adequate body temperature, heartbeat, and breathing regulation through lying directly on the mother’s abdomen and in between her breasts. Due to some infant’s condition, kangaroo care is not a feasible intervention. The purpose of this proof-of-concept research project is to create a device which simulates skin-to-skin contact for pre-term infants not eligible for kangaroo care, with the aim of promoting baby’s health outcomes, reducing the incidence of serious neonatal and early childhood illnesses, and/or improving cognitive, social and emotional aspects of development. Methods: The study design is a proof-of-concept based on a three-phase approach; (1) observational study and data analysis of the standard of care for 2 groups of pre-term infants, (2) design and concept development of a novel device for pre-term infants not currently eligible for standard kangaroo care, and (3) prototyping, laboratory testing, and evaluation of the novel device in comparison to current assessment parameters of kangaroo care. A single center study will be conducted in an area hospital offering Level III neonatal intensive care. Eligible participants include newborns born premature (28-30 weeks of age) admitted to the NICU. The study design includes 2 groups: a control group receiving standard kangaroo care and an experimental group not eligible for kangaroo care. Based on behavioral analysis of observational video data collected in the NICU, the device will be created to simulate mother’s body using electrical components in a thermoplastic polymer housing covered in silicone. It will be designed with a microprocessor that controls simulated respiration, heartbeat, and body temperature of the 'simulated caregiver' by using a pneumatic lung, vibration sensors (heartbeat), pressure sensors (weight/position), and resistive film to measure temperature. A slight contour of the simulator surface may be integrated to help position the infant correctly. Control and monitoring of the skin-to-skin contact simulator would be performed locally by an integrated touchscreen. The unit would have built-in Wi-Fi connectivity as well as an optional Bluetooth connection in which the respiration and heart rate could be synced with a parent or caregiver. A camera would be integrated, allowing a video stream of the infant in the simulator to be streamed to a monitoring location. Findings: Expected outcomes are stabilization of respiratory and cardiac rates, thermoregulation of those infants not eligible for skin to skin contact with their mothers, and real time mother Bluetooth to the device to mimic the experience in the womb. Results of this study will benefit clinical practice by creating a new standard of care for premature neonates in the NICU that are deprived of skin to skin contact due to various health restrictions.

Keywords: kangaroo care, wearable technology, pre-term infants, medical design

Procedia PDF Downloads 157
2999 Mobile Microscope for the Detection of Pathogenic Cells Using Image Processing

Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

Abstract:

One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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2998 Estimation of Reservoirs Fracture Network Properties Using an Artificial Intelligence Technique

Authors: Reda Abdel Azim, Tariq Shehab

Abstract:

The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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2997 Simulation and Experimental Study on Tensile Force Measurement of PS Tendons Using an Embedded EM Sensor

Authors: ByoungJoon Yu, Junkyeong Kim, Seunghee Park

Abstract:

The tensile force estimation PS tendons is in great demand on monitoring the structural health condition of PSC girder bridges. Measuring the tensile force of the PS tendons inside the PSC girder using conventional methods is hard due to its location. In this paper, an embedded EM sensor based tensile force estimation of PS tendon was carried out by measuring the permeability of the PS tendons in PSC girder. The permeability is changed due to the induced tensile force by the magneto-elastic effect and the effect then lead to the gradient change of the B-H curve. An experiment was performed to obtain the signals from the EM sensor using three down-scaled PSC girder models. The permeability of PS tendons was proportionally decreased according to the increase of the tensile forces. To verify the experiment results, a simulation of tensile force estimation will be conducted in further study. Consequently, it is expected that both the experiment results and the simulation results increase the accuracy of the tensile force estimation, and then it could be one of the solutions for evaluating the performance of PSC girder.

Keywords: tensile force estimation, embedded EM sensor, PSC girder, EM sensor simulation, cross section loss

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2996 An Analysis of Economical Drivers and Technical Challenges for Large-Scale Biohydrogen Deployment

Authors: Rouzbeh Jafari, Joe Nava

Abstract:

This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

Procedia PDF Downloads 110