Search results for: cooling approaches
1656 A Comprehensive Study of Spread Models of Wildland Fires
Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran
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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling
Procedia PDF Downloads 721655 The Global Relationship between the Prevalence of Diabetes Mellitus and Incidence of Tuberculosis: 2000-2012
Authors: Alaa Badawi, Suzan Sayegh, Mohamed Sallam, Eman Sadoun, Mohamed Al-Thani, Muhammad W. Alam, Paul Arora
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Background: The dual burden of tuberculosis (TB) and diabetes mellitus (DM) has increased over the past decade with DM prevalence increasing in countries already afflicted with a high burden of TB. The coexistence of the two conditions presents a serious threat to global public health. Objective: The present study examines the global relationship between the prevalence of DM and the incidence of TB to evaluate their coexistence worldwide and their contribution to one another. Methods: This is an ecological longitudinal study covering the period between years 2000 to 2012. We utilized data from the WHO and World Bank sources and International Diabetes Federation to estimate prevalence of DM (%) and the incidence of TB (per 100,000). Measures of central tendency and dispersion as well as the harmonic mean and linear regression were used for different WHO regions. The association between DM prevalence and TB incidence was examined by quartile of DM prevalence. Results: The worldwide average (±S.D.) prevalence of DM within the study period was 6.6±3.8% whereas TB incidence was 135.0±190.5 per 100,000. DM prevalence was highest in the Eastern Mediterranean (8.3±4.1) and West Pacific (8.2±5.6) regions and lowest in the Africa (3.5±2.6). TB incidence was highest in Africa (313.1±275.9 per 100,000) and South-East Asia (216.7±124.9) and lowest in the European (46.5±68.6) and American (47.2±52.9) regions. Only countries with high DM prevalence (>7.6%) showed a significant positive association with TB incidence (r=0.17, p=0.013). Conclusion: A positive association between DM and TB may exist in some – but not all – world regions, a dual burden that necessitates identifying the nature of this coexistence to assist in developing public health approaches that curb their rising burden.Keywords: diabetes mellitus, tuberculosis, disease burden, global association
Procedia PDF Downloads 4541654 Generation Mechanism of Opto-Acoustic Wave from in vivo Imaging Agent
Authors: Hiroyuki Aoki
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The optoacoustic effect is the energy conversion phenomenon from light to sound. In recent years, this optoacoustic effect has been utilized for an imaging agent to visualize a tumor site in a living body. The optoacoustic imaging agent absorbs the light and emits the sound signal. The sound wave can propagate in a living organism with a small energy loss; therefore, the optoacoustic imaging method enables the molecular imaging of the deep inside of the body. In order to improve the imaging quality of the optoacoustic method, the more signal intensity is desired; however, it has been difficult to enhance the signal intensity of the optoacoustic imaging agent because the fundamental mechanism of the signal generation is unclear. This study deals with the mechanism to generate the sound wave signal from the optoacoustic imaging agent following the light absorption by experimental and theoretical approaches. The optoacoustic signal efficiency for the nano-particles consisting of metal and polymer were compared, and it was found that the polymer particle was better. The heat generation and transfer process for optoacoustic agents of metal and polymer were theoretically examined. It was found that heat generated in the metal particle rapidly transferred to the water medium, whereas the heat in the polymer particle was confined in itself. The confined heat in the small particle induces the massive volume expansion, resulting in the large optoacoustic signal for the polymeric particle agent. Thus, we showed that heat confinement is a crucial factor in designing the highly efficient optoacoustic imaging agent.Keywords: nano-particle, opto-acoustic effect, in vivo imaging, molecular imaging
Procedia PDF Downloads 1211653 Probabilistic Approach to the Spatial Identification of the Environmental Sources behind Mortality Rates in Europe
Authors: Alina Svechkina, Boris A. Portnov
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In line with a rapid increase in pollution sources and enforcement of stricter air pollution regulation, which lowers pollution levels, it becomes more difficult to identify actual risk sources behind the observed morbidity patterns, and new approaches are required to identify potential risks and take preventive actions. In the present study, we discuss a probabilistic approach to the spatial identification of a priori unidentified environmental health hazards. The underlying assumption behind the tested approach is that the observed adverse health patterns (morbidity, mortality) can become a source of information on the geographic location of environmental risk factors that stand behind them. Using this approach, we analyzed sources of environmental exposure using data on mortality rates available for the year 2015 for NUTS 3 (Nomenclature of Territorial Units for Statistics) subdivisions of the European Union. We identified several areas in the southwestern part of Europe as primary risk sources for the observed mortality patterns. Multivariate regressions, controlled by geographical location, climate conditions, GDP (gross domestic product) per capita, dependency ratios, population density, and the level of road freight revealed that mortality rates decline as a function of distance from the identified hazard location. We recommend the proposed approach an exploratory analysis tool for initial investigation of regional patterns of population morbidity patterns and factors behind it.Keywords: mortality, environmental hazards, air pollution, distance decay gradient, multi regression analysis, Europe, NUTS3
Procedia PDF Downloads 1531652 Identification and Prioritisation of Students Requiring Literacy Intervention and Subsequent Communication with Key Stakeholders
Authors: Emilie Zimet
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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.Keywords: identification, student selection, communication, special education, school policy, planning for intervention
Procedia PDF Downloads 441651 Investigating the Impact of Job-Related and Organisational Factors on Employee Engagement: An Emotionally Relevant Approach Based on Psychological Climate and Organisational Emotional Intelligence (OEI)
Authors: Nuno Da Camara, Victor Dulewicz, Malcolm Higgs
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Factors on employee engagement: In particular, although theorists have described the critical role of emotional cognition of the workplace environment as antecedents to employee engagement, empirical research on the impact of emotional cognition on employee engagement is limited. However, previous researchers have typically provided evidence of the link between emotional cognition of the workplace environment and workplace attitudes such as job satisfaction and organisational commitment. This study therefore aims to investigate the impact of emotional cognition of job, role, leader and organisation domains of the work environment – as represented by measures of psychological climate and organizational emotional intelligence (OEI) - on employee engagement. The research is based on a quantitative cross-sectional survey of employees in a UK charity organization (n=174). The research instruments applied include the psychological climate scale, the organisational emotional intelligence questionnaire (OEIQ) and the Utrecht Work Engagement Scale (UWES). The data were analysed using hierarchical regression and partial least squares (PLS) analytical techniques. The results of the study show that both psychological climate and OEI, which represent emotional cognition of job, role, leader and organisation domains in the workplace are significant drivers of employee engagement. In particular, the study found that a sense of contribution and challenge at work are the strongest drivers of vigour, dedication and absorption and highlights the importance of emotionally relevant approaches in furthering our understanding of workplace engagement.Keywords: employee engagement, organisational emotional intelligence, psychological climate, workplace attitudes
Procedia PDF Downloads 4971650 Development of an Interactive Display-Control Layout Design System for Trains Based on Train Drivers’ Mental Models
Authors: Hyeonkyeong Yang, Minseok Son, Taekbeom Yoo, Woojin Park
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Human error is the most salient contributing factor to railway accidents. To reduce the frequency of human errors, many researchers and train designers have adopted ergonomic design principles for designing display-control layout in rail cab. There exist a number of approaches for designing the display control layout based on optimization methods. However, the ergonomically optimized layout design may not be the best design for train drivers, since the drivers have their own mental models based on their experiences. Consequently, the drivers may prefer the existing display-control layout design over the optimal design, and even show better driving performance using the existing design compared to that using the optimal design. Thus, in addition to ergonomic design principles, train drivers’ mental models also need to be considered for designing display-control layout in rail cab. This paper developed an ergonomic assessment system of display-control layout design, and an interactive layout design system that can generate design alternatives and calculate ergonomic assessment score in real-time. The design alternatives generated from the interactive layout design system may not include the optimal design from the ergonomics point of view. However, the system’s strength is that it considers train drivers’ mental models, which can help generate alternatives that are more friendly and easier to use for train drivers. Also, with the developed system, non-experts in ergonomics, such as train drivers, can refine the design alternatives and improve ergonomic assessment score in real-time.Keywords: display-control layout design, interactive layout design system, mental model, train drivers
Procedia PDF Downloads 2951649 Energy Efficiency and Sustainability Analytics for Reducing Carbon Emissions in Oil Refineries
Authors: Gaurav Kumar Sinha
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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance
Procedia PDF Downloads 221648 Comparing the Effects of Ondansetron and Acupressure in PC6 Point on Postoperative Nausea and Vomiting in Patients Undergone Elective Cesarean Section: A Randomized Clinical Trial
Authors: Nasrin Galehdar, Sedigheh Nadri, Elham Nazari, Isan Darvishi, Abouzar Mohammadi
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Background and aim:Nausea and vomiting are complications of cesarean section. The pharmacological and non-pharmacological approaches were applied to decrease postoperative nausea and vomiting. The aim of the present study was to compare the effects of Ondansetron and acupressure on postoperative nausea and vomiting in patients undergone an elective cesarean section. Materials and method: The study was designed as a randomized clinical trial. A total of 120 patients were allocated to two equal groups. Four mgs of Ondansetron was administered for the Ondansetron group after clamping the umbilical cord. The acupressure bracelets were fastened in the PC6 point for acupressure group for 15 minutes. The patients were monitored in terms of incidence, severity, and episodes of nausea and vomiting. The data obtained were analyzed by SPSS software version 18 with a significance level of 0.05. Results: There was no significant statistical difference in nausea severity among the groups intra-operatively, in the recovery and surgery wards. The incidence and episodes of vomiting were significantly higher in patients undergone acupressure intra-operatively, in the recovery and surgery wards (P< 0.05). No significant effect of acupressure was reported in reducing postoperative nausea and vomiting. Conclusion: No significant effect of acupressure was reported in reducing postoperative nausea and vomiting. Thus, it is suggested to perform the studies with larger size and comparing the effects of acupressure with other antiemetic medications.Keywords: ondansetron, acupressure, nausea, vomiting
Procedia PDF Downloads 1011647 A Mixed-Integer Nonlinear Program to Optimally Pace and Fuel Ultramarathons
Authors: Kristopher A. Pruitt, Justin M. Hill
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The purpose of this research is to determine the pacing and nutrition strategies which minimize completion time and carbohydrate intake for athletes competing in ultramarathon races. The model formulation consists of a two-phase optimization. The first-phase mixed-integer nonlinear program (MINLP) determines the minimum completion time subject to the altitude, terrain, and distance of the race, as well as the mass and cardiovascular fitness of the athlete. The second-phase MINLP determines the minimum total carbohydrate intake required for the athlete to achieve the completion time prescribed by the first phase, subject to the flow of carbohydrates through the stomach, liver, and muscles. Consequently, the second phase model provides the optimal pacing and nutrition strategies for a particular athlete for each kilometer of a particular race. Validation of the model results over a wide range of athlete parameters against completion times for real competitive events suggests strong agreement. Additionally, the kilometer-by-kilometer pacing and nutrition strategies, the model prescribes for a particular athlete suggest unconventional approaches could result in lower completion times. Thus, the MINLP provides prescriptive guidance that athletes can leverage when developing pacing and nutrition strategies prior to competing in ultramarathon races. Given the highly-variable topographical characteristics common to many ultramarathon courses and the potential inexperience of many athletes with such courses, the model provides valuable insight to competitors who might otherwise fail to complete the event due to exhaustion or carbohydrate depletion.Keywords: nutrition, optimization, pacing, ultramarathons
Procedia PDF Downloads 1811646 Geosynthetic Reinforced Unpaved Road: Literature Study and Design Example
Authors: D. Jayalakshmi, S. S. Bhosale
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This paper, in its first part, presents the state-of-the-art literature of design approaches for geosynthetic reinforced unpaved roads. The literature starting since 1970 and the critical appraisal of flexible pavement design by Giroud and Han (2004) and Jonathan Fannin (2006) is presented. The design example is illustrated for Indian conditions. The example emphasizes the results computed by Giroud and Han's (2004) design method with the Indian road congress guidelines by IRC SP 72 -2015. The input data considered are related to the subgrade soil condition of Maharashtra State in India. The unified soil classification of the subgrade soil is inorganic clay with high plasticity (CH), which is expansive with a California bearing ratio (CBR) of 2% to 3%. The example exhibits the unreinforced case and geotextile as reinforcement by varying the rut depth from 25 mm to 100 mm. The present result reveals the base thickness for the unreinforced case from the IRC design catalogs is in good agreement with Giroud and Han (2004) approach for a range of 75 mm to 100 mm rut depth. Since Giroud and Han (2004) method is applicable for both reinforced and unreinforced cases, for the same data with appropriate Nc factor, for the same rut depth, the base thickness for the reinforced case has arrived for the Indian condition. From this trial, for the CBR of 2%, the base thickness reduction due to geotextile inclusion is 35%. For the CBR range of 2% to 5% with different stiffness in geosynthetics, the reduction in base course thickness will be evaluated, and the validation will be executed by the full-scale accelerated pavement testing set up at the College of Engineering Pune (COE), India.Keywords: base thickness, design approach, equation, full scale accelerated pavement set up, Indian condition
Procedia PDF Downloads 1831645 Yawning Computing Using Bayesian Networks
Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube
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Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms
Procedia PDF Downloads 4501644 Competence on Learning Delivery Modes and Performance of Physical Education Teachers in Senior High Schools in Davao
Authors: Juvanie C. Lapesigue
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Worldwide school closures result from a significant public health crisis that has affected the nation and the entire world. It has affected students, educators, educational organizations globally, and many other aspects of society. Academic institutions worldwide teach students using diverse approaches of various learning delivery modes. This paper investigates the competence and performance of physical education teachers using various learning delivery modes, including Distance learning, Blended Learning, and Homeschooling during online distance education. To identify the Gap between their age generation using various learning delivery that affects teachers' preparation for distance learning and evaluates how these modalities impact teachers’ competence and performance in the case of a pandemic. The respondents were the Senior High School teachers of the Department of Education who taught in Davao City before and during the pandemic. Purposive sampling was utilized on 61 Senior High School Teachers in Davao City Philippines. The result indicated that teaching performance based on pedagogy and assessment has significantly affected teaching performance in teaching physical education, particularly those Non-PE teachers teaching physical education subjects. It should be supplied with enhancement training workshops to help them be more successful in preparation in terms of teaching pedagogy and assessment in the following norm. Hence, a proposed unique training design for non-P.E. Teachers has been created to improve the teachers’ performance in terms of pedagogy and assessment in teaching P.E subjects in various learning delivery modes in the next normal.Keywords: distance learning, learning delivery modes, P.E teachers, senior high school, teaching competence, teaching performance
Procedia PDF Downloads 841643 Complicating Representations of Domestic Violence Perpetration through a Qualitative Content Analysis and Socio-Ecological Approach
Authors: Charlotte Lucke
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This study contributes to the body of literature that analyzes and complicates oversimplified and sensationalized representations of trauma and violence through a close examination and complication of representations of perpetrators of domestic violence in the mass media. This study determines the ways the media frames perpetrators of domestic violence through a qualitative content analysis and socio-ecological approach to the perpetration of violence. While the qualitative analysis has not been carried out, through preliminary research, this study hypothesizes that the media represents perpetrators through tropes such as the 'predator' or 'offender,' or as a demonized 'other.' It is necessary to expose and work through such stereotypes because cultivation theory demonstrates that the mass media determines societal beliefs about and perceptions of the world. Thus, representations of domestic violence in the mass media can lead people to believe that perpetrators of violence are mere animals or criminals and overlook the trauma that many perpetrators experience. When the media represents perpetrators as pure evil, monsters, or absolute 'others,' it leaves out the complexities of what moves people to commit domestic violence. By analyzing and placing media representations of perpetrators into conversation with the socio-ecological approach to violence perpetration, this study complicates domestic violence stereotypes. The socio-ecological model allows researchers to consider the way the interplay between individuals and their families, friends, communities, and cultures can move people to act violently. Using this model, along with psychological and psychoanalytic approaches to the etiology of domestic violence, this paper argues that media stereotypes conceal the way people’s experiences of trauma, along with community and cultural norms, perpetuates the cycle of systemic trauma and violence in the home.Keywords: domestic violence, media images, representing trauma, theorising trauma
Procedia PDF Downloads 2261642 Enhance Indoor Environment in Buildings and Its Effect on Improving Occupant's Health
Authors: Imad M. Assali
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Recently, the world main problem is a global warming and climate change affecting both outdoor and indoor environments, especially the air quality (AQ) as a result of vast migration of people from rural areas to urban areas. Therefore, cities became more crowded and denser from an irregular population increase, along with increasing urbanization caused many problems for the environment such as increasing the land prices, changes in life style, and the new buildings are not adapted to the climate producing uncomfortable and unhealthy indoor building conditions. As interior environments are the places that create the most intimate relationship with the user. Consequently, the indoor environment quality (IEQ) for buildings became uncomfortable and unhealthy for its occupants. The symptoms commonly associated with poor indoor environment such as itchy, headache, fatigue, and respiratory complaints such as cough and congestion, etc. The symptoms tend to improve over time or even disappear when people are away from the building. Therefore, designing a healthy indoor environment to fulfill human needs is the main concern for architects and interior designer. However, this research explores how occupant expectations and environmental attitudes may influence occupant health and satisfaction within the context of the indoor environment. In doing so, it reviews and contributes to the methods and tools used to evaluate only the indoor environment quality (IEQ) components of building performance. Its main aim is to review the literature on indoor human comfort. This is followed by a review of previous papers published related to human comfort. Finally, this paper will provide possible approaches in design level of healthy buildings.Keywords: sustainable building, indoor environment quality (IEQ), occupant's health, active system, sick building syndrome (SBS)
Procedia PDF Downloads 3441641 Evaluating a Holistic Fitness Program Used by High Performance Athletes and Mass Participants
Authors: Peter Smolianov, Jed Smith, Lisa Chen, Steven Dion, Christopher Schoen, Jaclyn Norberg
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This study evaluated the effectiveness of an experimental training program used to improve performance and health of competitive athletes and recreational sport participants. This holistic program integrated and advanced Eastern and Western methods of prolonging elite sports participation and enjoying lifelong fitness, particularly from China, India, Russia, and the United States. The program included outdoor, gym, and water training approaches focused on strengthening while stretching/decompressing and on full body activation-all in order to improve performance as well as treat and prevent common disorders and pains. The study observed and surveyed over 100 users of the program including recreational fitness and sports enthusiasts as well as elite athletes who competed for national teams of different countries and for Division I teams of National Collegiate Athletic Association in the United States. Different types of sport were studied, including territorial games (e.g., American football, basketball, volleyball), endurance/cyclical (athletics/track and field, swimming), and artistic (e.g., gymnastics and synchronized swimming). Results of the study showed positive effects on the participants’ performance and health, particularly for those who used the program for more than two years and especially in reducing spinal disorders and in enabling to perform new training tasks which previously caused back pain.Keywords: lifelong fitness, injury prevention, prolonging sport participation, improving performance and health
Procedia PDF Downloads 1511640 The Impact of Regulatory Changes on the Development of Mobile Medical Apps
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Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.Keywords: agile, applications, FDA, medical, mobile, regulations, software engineering, standards
Procedia PDF Downloads 3511639 Dispersion Effects in Waves Reflected by Lossy Conductors: The Optics vs. Electromagnetics Approach
Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda
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The study of dispersion phenomena in electromagnetic waves reflected by conductors at infrared and lower frequencies is a topic which finds a number of applications. We aim to explain in this work what are the most relevant ones and how this phenomenon is modeled from both optics and electromagnetics points of view. We also explain here how the amplitude of an electromagnetic wave reflected by a lossy conductor could depend on both the frequency of the incident wave, as well as on the electrical properties of the conductor, and we illustrate this phenomenon with a practical example. The mathematical analysis made by a specialist in electromagnetics or a microwave engineer is apparently very different from the one made by a specialist in optics. We show here how both approaches lead to the same physical result and what are the key concepts which enable one to understand that despite the differences in the equations the solution to the problem happens to be the same. Our study starts with an analysis made by using the complex refractive index and the reflectance parameter. We show how this reflectance has a dependence with the square root of the frequency when the reflecting material is a good conductor, and the frequency of the wave is low enough. Then we analyze the same problem with a less known approach, which is based on the reflection coefficient of the electric field, a parameter that is most commonly used in electromagnetics and microwave engineering. In summary, this paper presents a mathematical study illustrated with a worked example which unifies the modeling of dispersion effects made by specialists in optics and the one made by specialists in electromagnetics. The main finding of this work is that it is possible to reproduce the dependence of the Fresnel reflectance with frequency from the intrinsic impedance of the reflecting media.Keywords: dispersion, electromagnetic waves, microwaves, optics
Procedia PDF Downloads 1191638 Digital Platform for Psychological Assessment Supported by Sensors and Efficiency Algorithms
Authors: Francisco M. Silva
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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare
Procedia PDF Downloads 1161637 Thresholding Approach for Automatic Detection of Pseudomonas aeruginosa Biofilms from Fluorescence in situ Hybridization Images
Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj
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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization
Procedia PDF Downloads 1271636 Dual Drug Piperine-Paclitaxel Nanoparticles Inhibit Migration and Invasion in Human Breast Cancer Cells
Authors: Monika Verma, Renuka Sharma, B. R. Gulati, Namita Singh
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In combination therapy, two chemotherapeutic agents work together in a collaborative action. It has appeared as one of the promising approaches to improve anti-cancer treatment efficacy. In the present investigation, piperine (P-NPS), paclitaxel (PTX NPS), and a combination of both, piperine-paclitaxel nanoparticle (Pip-PTX NPS), were made by the nanoprecipitation method and later characterized by PSA, DSC, SEM, TEM, and FTIR. All nanoparticles exhibited a monodispersed size distribution with a size of below 200 nm, zeta potential ranges from (-30-40mV) and a narrow polydispersity index (>0.3) of the drugs. The average encapsulation efficiency was found to be between 80 and 90%. In vitro release of drugs for nanoparticles was done spectrophotometrically. FTIR and DSC results confirmed the presence of the drug. The Pip-PTX NPS significantly inhibit cell proliferation as compared to the native drugs nanoparticles in the breast cancer cell line MCF-7. In addition, Pip-PTX NPS suppresses cells in colony formation and soft gel agar assay. Scratch migration and Transwell chamber invasion assays revealed that combined nanoparticles reduce the migration and invasion of breast cancer cells. Morphological studies showed that Pip-PTX NPS penetrates the cells and induces apoptosis, which was further confirmed by DNA fragmentation, SEM, and western blot analysis. Taken together, Pip-PTX NPS inhibits cell proliferation, anchorage dependent and anchorage independent cell growth, reduces migration and invasion, and induces apoptosis in cells. These findings support that combination therapy using Pip-PTX NPS represents a potential approach and could be helpful in the future for breast cancer therapy.Keywords: piperine, paclitaxel, breast cancer, apoptosis
Procedia PDF Downloads 911635 Automatic Staging and Subtype Determination for Non-Small Cell Lung Carcinoma Using PET Image Texture Analysis
Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya
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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis
Procedia PDF Downloads 3191634 Evaluating Traffic Congestion Using the Bayesian Dirichlet Process Mixture of Generalized Linear Models
Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig
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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection
Procedia PDF Downloads 2841633 'Critical Performance,' an Arts-Based Method for Exploring HIV-Related Stigma, Social Support, and Access to Care among People Living with HIV/AIDS in Rural China
Authors: Chiao-Wen Lan, David Gere
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Background and Significance: Performance has a rich history of imparting information and encouraging reflection, yet there is a paucity of literature on applying performance as a method of analysis and not as a medium for health education. This study aimed to apply ethnodrama strategies to the issue of HIV-related stigma in rural China and to use a critical performance as a vehicle for communication of health research. Methods: The program, titled 'STOP STIGMA,' included dance, narratives and original quotes from people living with HIV/AIDS in China, and spectacle such as photographs, set, and props corresponding to the history of HIV in rural China. Results: The performance represented a step away from a completely textual interpretation of data towards a theatrical style that begins to privilege what arts-based research scholars Rossiter and colleagues have termed 'an embodied, theatrical representation of data.' It offered an opportunity to deliver individual and collective stories that represent how HIV-positive people experience living with HIV/AIDS in China, which could play an integral part in the formulation of actions to effect change. Discussion: This method of communicating health research has implications for fostering dialogue among researchers, community members, and medical practitioners. Although arts-based approaches are not new to the scientific community, the integration of dance, video, ethnodrama, and sciences provides opportunities to innovate in non-traditional research dissemination and communication.Keywords: health communication, HIV/AIDS, stigma, vulnerable populations
Procedia PDF Downloads 1101632 Authentic Visual Resources for the Foreign Language Classroom
Authors: O. Yeret
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Visual resources are all around us, especially in today's media-driven world, which gravitates, more and more, towards the visual. As a result, authentic resources, such as television advertisements, become testaments – authentic cultural materials – that reflect the landscape of certain groups and communities during a specific point in time. Engaging language students with popular advertisements can provide a great opportunity for developing cultural awareness, a component that is sometimes overlooked in the foreign language classroom. This paper will showcase practical examples of using Israeli Television Ads in various Modern Hebrew language courses. Several approaches for combining the study of language and culture, through the use of advertisements, will be included; for example, targeted assignments based on students' proficiency levels, such as: asking to recognize vocabulary words and answer basic information questions, as opposed to commenting on the significance of an ad and analyzing its particular cultural elements. The use of visual resources in the language classroom does not only enable students to learn more about the culture of the target language, but also to combine their language skills. Most often, interacting with an ad requires close listening and some reading (through captions or other data). As students analyze the ad, they employ their writing and speaking skills by answering questions in text or audio form. Hence, these interactions are able to elicit complex language use across the four domains: listening, speaking, writing, and reading. This paper will include examples of practical assignments that were developed for several Modern Hebrew language courses, together with the specific advertisements and questions related to them. Conclusions from the process and recent feedback notes received from students regarding the use of visual resources will be mentioned as well.Keywords: authentic materials, cultural awareness, second language acquisition, visual resources
Procedia PDF Downloads 1041631 Performance Evaluation and Comparison between the Empirical Mode Decomposition, Wavelet Analysis, and Singular Spectrum Analysis Applied to the Time Series Analysis in Atmospheric Science
Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier
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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and comparedKeywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis
Procedia PDF Downloads 981630 High-Rises and Urban Design: The Reasons for Unsuccessful Placemaking with Residential High-Rises in England
Authors: E. Kalcheva, A. Taki, Y. Hadi
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High-rises and placemaking is an understudied combination which receives more and more interest with the proliferation of this typology in many British cities. The reason for studying three major cities in England: London, Birmingham and Manchester, is to learn from the latest advances in urban design in well-developed and prominent urban environment. The analysis of several high-rise sites reveals the weaknesses in urban design of contemporary British cities and presents an opportunity to study from the implemented examples. Therefore, the purpose of this research is to analyze design approaches towards creating a sustainable and varied urban environment when high-rises are involved. The research questions raised by the study are: what is the quality of high-rises and their surroundings; what facilities and features are deployed in the research area; what is the role of the high-rise buildings in the placemaking process; what urban design principles are applicable in this context. The methodology utilizes observation of the researched area by structured questions, developed by the author to evaluate the outdoor qualities of the high-rise surroundings. In this context, the paper argues that the quality of the public realm around the high-rises is quite low, missing basic but vital elements such as plazas, public art, and seating, along with landscaping and pocket parks. There is lack of coherence, the rhythm of the streets is often disrupted, and even though the high-rises are very aesthetically appealing, they fail to create a sense of place on their own. The implications of the study are that future planning can take into consideration the critique in this article and provide more opportunities for urban design interventions around high-rise buildings in the British cities.Keywords: high-rises, placemaking, urban design, townscape
Procedia PDF Downloads 3151629 Learning Dynamic Representations of Nodes in Temporally Variant Graphs
Authors: Sandra Mitrovic, Gaurav Singh
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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.Keywords: churn prediction, dynamic networks, node2vec, auto-encoders
Procedia PDF Downloads 3051628 Synthesis, Characterization, and Application of Novel Trihexyltetradecyl Phosphonium Chloride for Extractive Desulfurization of Liquid Fuel
Authors: Swapnil A. Dharaskar, Kailas L. Wasewar, Mahesh N. Varma, Diwakar Z. Shende
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Owing to the stringent environmental regulations in many countries for production of ultra low sulfur petroleum fractions intending to reduce sulfur emissions results in enormous interest in this area among the scientific community. The requirement of zero sulfur emissions enhances the prominence for more advanced techniques in desulfurization. Desulfurization by extraction is a promising approach having several advantages over conventional hydrodesulphurization. Present work is dealt with various new approaches for desulfurization of ultra clean gasoline, diesel and other liquid fuels by extraction with ionic liquids. In present paper experimental data on extractive desulfurization of liquid fuel using trihexyl tetradecyl phosphonium chloride has been presented. The FTIR, 1H-NMR, and 13C-NMR have been discussed for the molecular confirmation of synthesized ionic liquid. Further, conductivity, solubility, and viscosity analysis of ionic liquids were carried out. The effects of reaction time, reaction temperature, sulfur compounds, ultrasonication, and recycling of ionic liquid without regeneration on removal of dibenzothiphene from liquid fuel were also investigated. In extractive desulfurization process, the removal of dibenzothiophene in n-dodecane was 84.5% for mass ratio of 1:1 in 30 min at 30OC under the mild reaction conditions. Phosphonium ionic liquids could be reused five times without a significant decrease in activity. Also, the desulfurization of real fuels, multistage extraction was examined. The data and results provided in present paper explore the significant insights of phosphonium based ionic liquids as novel extractant for extractive desulfurization of liquid fuels.Keywords: ionic liquid, PPIL, desulfurization, liquid fuel, extraction
Procedia PDF Downloads 5981627 The Effectiveness of Traditional Music as Therapy and Alternative to Traditional Forms of Therapy in Treatment of Anxiety and Depression
Authors: Helen Johnson-Egemba
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This paper will discuss the current effectiveness of music therapy for a range of conditions, such as depression and anxiety. Indeed, traditional forms of therapy have often been effective in treating various mental and physical health conditions. However, they are not with their limitations. Music therapy, on the other hand, is a non-invasive and cost-effective alternative that can produce similar or even better results. Music therapy can produce longer-lasting results. The research also highlights the underlying mechanisms of traditional music therapy, such as its complementary treatment. A systematic review of existing literature was conducted to gather relevant studies and establish a comprehensive understanding of the topic. Various research methods, including experimental studies, qualitative research, surveys, were utilized to explore the therapeutic potential of traditional music interventions. The findings reveal that traditional music therapy shows promise in managing anxiety and depression symptoms, with positive outcomes impacting brain activity, emotions, and stress regulation. The outcomes of this study contribute to evidence-based practice, providing insights for clinicians and therapists to incorporate traditional music therapy into their treatment approaches. Furthermore, the research promotes awareness and acceptance of traditional music as a legitimate and effective therapeutic intervention for anxiety and depression, potentially enhancing access to alternative and complementary treatment options. Overall, this study demonstrates the potential benefits of traditional music therapy in addressing anxiety and depression, offering valuable implications for mental health care and improving the well-being of individuals struggling with these conditions.Keywords: anxiety, effectiveness, depression, traditional music, therapy, treatment
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