Search results for: Microsoft Azure Cloud
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 842

Search results for: Microsoft Azure Cloud

152 Chronic wrist pain among handstand practitioners. A questionnaire study.

Authors: Martonovich Noa, Maman David, Alfandari Liad, Behrbalk Eyal.

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Introduction: The human body is designed for upright standing and walking, with the lower extremities and axial skeleton supporting weight-bearing. Constant weight-bearing on joints not meant for this action can lead to various pathologies, as seen in wheelchair users. Handstand practitioners use their wrists as weight-bearing joints during activities, but little is known about wrist injuries in this population. This study aims to investigate the epidemiology of wrist pain among handstand practitioners, as no such data currently exist. Methods: The study is a cross-sectional online survey conducted among athletes who regularly practice handstands. Participants were asked to complete a three-part questionnaire regarding their workout regimen, training habits, and history of wrist pain. The inclusion criteria were athletes over 18 years old who practice handstands more than twice a month for at least 4 months. All data were collected using Google Forms, organized and anonymized using Microsoft Excel, and analyzed using IBM SPSS 26.0. Descriptive statistics were calculated, and potential risk factors were tested using asymptotic t-tests and Fisher's tests. Differences were considered significant when p < 0.05. Results: This study surveyed 402 athletes who regularly practice handstands to investigate the prevalence of chronic wrist pain and potential risk factors. The participants had a mean age of 31.3 years, with most being male and having an average of 5 years of training experience. 56% of participants reported chronic wrist pain, and 14.4% reported a history of distal radial fracture. Yoga was the most practiced form, followed by Capoeira. No significant differences were found in demographic data between participants with and without chronic wrist pain, and no significant associations were found between chronic wrist pain prevalence and warm-up routines or protective aids. Conclusion: The lower half of the body is meant to handle weight-bearing and impact, while transferring the load to upper extremities can lead to various pathologies. Athletes who perform handstands are particularly prone to chronic wrist pain, which affects over half of them. Warm-up sessions and protective instruments like wrist braces do not seem to prevent chronic wrist pain, and there are no significant differences in age or training volume between athletes with and without the condition. Further research is needed to understand the causes of chronic wrist pain in athletes, given the growing popularity of sports and activities that can cause this type of injury.

Keywords: handstand, handbalance, wrist pain, hand and wrist surgery, yoga, calisthenics, circus, capoeira, movement.

Procedia PDF Downloads 61
151 Triangular Libration Points in the R3bp under Combined Effects of Oblateness, Radiation and Power-Law Profile

Authors: Babatunde James Falaye, Shi Hai Dong, Kayode John Oyewumi

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We study the e ffects of oblateness up to J4 of the primaries and power-law density pro file (PDP) on the linear stability of libration location of an in nitesimal mass within the framework of restricted three body problem (R3BP), by using a more realistic model in which a disc with PDP is rotating around the common center of the system mass with perturbed mean motion. The existence and stability of triangular equilibrium points have been explored. It has been shown that triangular equilibrium points are stable for 0 < μ < μc and unstable for μc ≤ μ ≤ 1/2, where c denotes the critical mass parameter. We find that, the oblateness up to J2 of the primaries and the radiation reduces the stability range while the oblateness up to J4 of the primaries increases the size of stability both in the context where PDP is considered and ignored. The PDP has an e ect of about ≈0:01 reduction on the application of c to Earth-Moon and Jupiter-Moons systems. We find that the comprehensive eff ects of the perturbations have a stabilizing proclivity. However, the oblateness up to J2 of the primaries and the radiation of the primaries have tendency for instability, while coecients up to J4 of the primaries have stability predisposition. In the limiting case c = 0, and also by setting appropriate parameter(s) to zero, our results are in excellent agreement with the ones obtained previously. Libration points play a very important role in space mission and as a consequence, our results have a practical application in space dynamics and related areas. The model may be applied to study the navigation and station-keeping operations of spacecraft (in nitesimal mass) around the Jupiter (more massive) -Callisto (less massive) system, where PDP accounts for the circumsolar ring of asteroidal dust, which has a cloud of dust permanently in its wake.

Keywords: libration points, oblateness, power-law density profile, restricted three-body problem

Procedia PDF Downloads 294
150 Transesterification of Waste Cooking Oil for Biodiesel Production Using Modified Clinoptilolite Zeolite as a Heterogeneous Catalyst

Authors: D. Mowla, N. Rasti, P. Keshavarz

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Reduction of fossil fuels sources, increasing of pollution gases emission, and global warming effects increase the demand of renewable fuels. One of the main candidates of alternative fuels is biodiesel. Biodiesel limits greenhouse gas effects due to the closed CO2 cycle. Biodiesel has more biodegradability, lower combustion emissions such as CO, SOx, HC, PM and lower toxicity than petro diesel. However, biodiesel has high production cost due to high price of plant oils as raw material. So, the utilization of waste cooking oils (WCOs) as feedstock, due to their low price and disposal problems reduce biodiesel production cost. In this study, production of biodiesel by transesterification of methanol and WCO using modified sodic potassic (SP) clinoptilolite zeolite and sodic potassic calcic (SPC) clinoptilolite zeolite as heterogeneous catalysts have been investigated. These natural clinoptilolite zeolites were modified by KOH solution to increase the site activity. The optimum biodiesel yields for SP clinoptilolite and SPC clinoptilolite were 95.8% and 94.8%, respectively. Produced biodiesel were analyzed and compared with petro diesel and ASTM limits. The properties of produced biodiesel confirm well with ASTM limits. The density, kinematic viscosity, cetane index, flash point, cloud point, and pour point of produced biodiesel were all higher than petro diesel but its acid value was lower than petro diesel. Finally, the reusability and regeneration of catalysts were investigated. The results indicated that the spent zeolites cannot be reused directly for the transesterification, but they can be regenerated easily and can obtain high activity.

Keywords: biodiesel, renewable fuel, transesterification, waste cooking oil

Procedia PDF Downloads 211
149 Exploring Data Stewardship in Fog Networking Using Blockchain Algorithm

Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

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IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

Procedia PDF Downloads 31
148 Artificial Intelligence Based Predictive Models for Short Term Global Horizontal Irradiation Prediction

Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

Procedia PDF Downloads 251
147 Returning to Work: A Qualitative Exploratory Study of Head and Neck Cancer Survivor Disability and Experience

Authors: Abi Miller, Eleanor Wilson, Claire Diver

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Background: UK Head and Neck Cancer incidence and prevalence were rising related to better treatment outcomes and changed demographics. More people of working-age now survive Head and Neck Cancer. For individuals, work provides income, purpose, and social connection. For society, work increases economic productivity and reduces welfare spending. In the UK, a cancer diagnosis is classed as a disability and more disabled people leave the workplace than non-disabled people. Limited evidence exists on return-to-work after Head and Neck Cancer, with no UK qualitative studies. Head and Neck Cancer survivors appear to return to work less when compared to other cancer survivors. This study aimed to explore the effects of Head and Neck Cancer disability on survivors’ return-to-work experience. Methodologies: This was an exploratory qualitative study using a critical realist approach to carry out semi-structured one-off interviews with Head and Neck Cancer survivors who had returned to work. Interviews were informed by an interview guide and carried out remotely by Microsoft Teams or telephone. Interviews were transcribed verbatim, pseudonyms allocated, and transcripts anonymized. Data were interpreted using Reflexive Thematic Analysis. Findings: Thirteen Head and Neck Cancer survivors aged between 41 -63 years participated in interviews. Three major themes were derived from the data: changed identity and meaning of work after Head and Neck Cancer, challenging and supportive work experiences and impact of healthcare professionals on return-to-work. Participants described visible physical appearance changes, speech and eating challenges, mental health difficulties and psycho-social shifts following Head and Neck Cancer. These factors affected workplace re-integration, ability to carry out work duties, and work relationships. Most participants experienced challenging work experiences, including stigmatizing workplace interactions and poor communication from managers or colleagues, which further affected participant confidence and mental health. Many participants experienced job change or loss, related both to Head and Neck Cancer and living through a pandemic. A minority of participants experienced strategies like phased return, which supported workplace re-integration. All participants, bar one, wanted conversations with healthcare professionals about return-to-work but perceived these conversations as absent. Conclusion: All participants found returning to work after Head and Neck Cancer to be a challenging experience. This appears to be impacted by participant physical, psychological, and functional disability following Head and Neck Cancer, work interaction and work context.

Keywords: disability, experience, head and neck cancer, qualitative, return-to-work

Procedia PDF Downloads 91
146 Reducing CO2 Emission Using EDA and Weighted Sum Model in Smart Parking System

Authors: Rahman Ali, Muhammad Sajjad, Farkhund Iqbal, Muhammad Sadiq Hassan Zada, Mohammed Hussain

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Emission of Carbon Dioxide (CO2) has adversely affected the environment. One of the major sources of CO2 emission is transportation. In the last few decades, the increase in mobility of people using vehicles has enormously increased the emission of CO2 in the environment. To reduce CO2 emission, sustainable transportation system is required in which smart parking is one of the important measures that need to be established. To contribute to the issue of reducing the amount of CO2 emission, this research proposes a smart parking system. A cloud-based solution is provided to the drivers which automatically searches and recommends the most preferred parking slots. To determine preferences of the parking areas, this methodology exploits a number of unique parking features which ultimately results in the selection of a parking that leads to minimum level of CO2 emission from the current position of the vehicle. To realize the methodology, a scenario-based implementation is considered. During the implementation, a mobile application with GPS signals, vehicles with a number of vehicle features and a list of parking areas with parking features are used by sorting, multi-level filtering, exploratory data analysis (EDA, Analytical Hierarchy Process (AHP)) and weighted sum model (WSM) to rank the parking areas and recommend the drivers with top-k most preferred parking areas. In the EDA process, “2020testcar-2020-03-03”, a freely available dataset is used to estimate CO2 emission of a particular vehicle. To evaluate the system, results of the proposed system are compared with the conventional approach, which reveal that the proposed methodology supersedes the conventional one in reducing the emission of CO2 into the atmosphere.

Keywords: car parking, Co2, Co2 reduction, IoT, merge sort, number plate recognition, smart car parking

Procedia PDF Downloads 119
145 Decision-Making Strategies on Smart Dairy Farms: A Review

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

Procedia PDF Downloads 162
144 Low-Cost Parking Lot Mapping and Localization for Home Zone Parking Pilot

Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

Procedia PDF Downloads 41
143 Mobile Crowdsensing Scheme by Predicting Vehicle Mobility Using Deep Learning Algorithm

Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

Procedia PDF Downloads 52
142 Systematic Review of Digital Interventions to Reduce the Carbon Footprint of Primary Care

Authors: Anastasia Constantinou, Panayiotis Laouris, Stephen Morris

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Background: Climate change has been reported as one of the worst threats to healthcare. The healthcare sector is a significant contributor to greenhouse gas emissions with primary care being responsible for 23% of the NHS’ total carbon footprint. Digital interventions, primarily focusing on telemedicine, offer a route to change. This systematic review aims to quantify and characterize the carbon footprint savings associated with the implementation of digital interventions in the setting of primary care. Methods: A systematic review of published literature was conducted according to PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, PubMed, and Scopus databases as well as Google scholar were searched using key terms relating to “carbon footprint,” “environmental impact,” “sustainability”, “green care”, “primary care,”, and “general practice,” using citation tracking to identify additional articles. Data was extracted and analyzed in Microsoft Excel. Results: Eight studies were identified conducted in four different countries between 2010 and 2023. Four studies used interventions to address primary care services, three studies focused on the interface between primary and specialist care, and one study addressed both. Digital interventions included the use of mobile applications, online portals, access to electronic medical records, electronic referrals, electronic prescribing, video-consultations and use of autonomous artificial intelligence. Only one study carried out a complete life cycle assessment to determine the carbon footprint of the intervention. It estimate that digital interventions reduced the carbon footprint at primary care level by 5.1 kgCO2/visit, and at the interface with specialist care by 13.4 kg CO₂/visit. When assessing the relationship between travel-distance saved and savings in emissions, we identified a strong correlation, suggesting that most of the carbon footprint reduction is attributed to reduced travel. However, two studies also commented on environmental savings associated with reduced use of paper. Patient savings in the form of reduced fuel cost and reduced travel time were also identified. Conclusion: All studies identified significant reductions in carbon footprint following implementation of digital interventions. In the future, controlled, prospective studies incorporating complete life cycle assessments and accounting for double-consulting effects, use of additional resources, technical failures, quality of care and cost-effectiveness are needed to fully appreciate the sustainable benefit of these interventions

Keywords: carbon footprint, environmental impact, primary care, sustainable healthcare

Procedia PDF Downloads 36
141 Multiscale Hub: An Open-Source Framework for Practical Atomistic-To-Continuum Coupling

Authors: Masoud Safdari, Jacob Fish

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Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

Procedia PDF Downloads 155
140 Monitor Vehicle Speed Using Internet of Things Based Wireless Sensor Network System

Authors: Akber Oumer Abdurezak

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Road traffic accident is a major problem in Ethiopia, resulting in the deaths of many people and potential injuries and crash every year and loss of properties. According to the Federal Transport Authority, one of the main causes of traffic accident and crash in Ethiopia is over speeding. Implementation of different technologies is used to monitor the speed of vehicles in order to minimize accidents and crashes. This research aimed at designing a speed monitoring system to monitor the speed of travelling vehicles and movements, reporting illegal speeds or overspeeding vehicles to the concerned bodies. The implementation of the system is through a wireless sensor network. The proposed system can sense and detect the movement of vehicles, process, and analysis the data obtained from the sensor and the cloud system. The data is sent to the central controlling server. The system contains accelerometer and gyroscope sensors to sense and collect the data of the vehicle. Arduino to process the data and Global System for Mobile Communication (GSM) module for communication purposes to send the data to the concerned body. When the speed of the vehicle exceeds the allowable speed limit, the system sends a message to database as “over speeding”. Both accelerometer and gyroscope sensors are used to collect acceleration data. The acceleration data then convert to speed, and the corresponding speed is checked with the speed limit, and those above the speed limit are reported to the concerned authorities to avoid frequent accidents. The proposed system decreases the occurrence of accidents and crashes due to overspeeding and can be used as an eye opener for the implementation of other intelligent transport system technologies. This system can also integrate with other technologies like GPS and Google Maps to obtain better output.

Keywords: accelerometer, IOT, GSM, gyroscope

Procedia PDF Downloads 48
139 Bridging Livelihood and Conservation: The Role of Ecotourism in the Campo Ma’an National Park, Cameroon

Authors: Gadinga Walter Forje, Martin Ngankam Tchamba, Nyong Princely Awazi, Barnabas Neba Nfornka

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Ecotourism is viewed as a double edge sword for the enhancement of conservation and local livelihood within a protected landscape. The Campo Ma’an National Park (CMNP) adopted ecotourism in its management plan as a strategic axis for better management of the park. The growing importance of ecotourism as a strategy for the sustainable management of CMNP and its environs requires adequate information to bolster the sector. This study was carried out between November 2018 and September 2021, with the main objective to contribute to the sustainable management of the CMNP through suggestions for enhancing the capacity of ecotourism in and around the park. More specifically, the study aimed at; 1) Analyse the governance of ecotourism in the CMNP and its surrounding; 2) Assessing the impact of ecotourism on local livelihood around the CMNP; 3) Evaluating the contribution of ecotourism to biodiversity conservation in and around the CMNP; 4) Evaluate the determinants of ecotourism possibilities in achieving sustainable livelihood and biodiversity conservation in and around the CMNP. Data were collected from both primary and secondary sources. Primary data were obtained from household surveys (N=124), focus group discussions (N=8), and key informant interviews (N=16). Data collected were coded and imputed into SPSS (version 19.0) software and Microsoft Excel spreadsheet for both quantitative and qualitative analysis. Findings from the Chi-square test revealed overall poor ecotourism governance in and around the CMNP, with benefit sharing (X2 = 122.774, p <0.01) and conflict management (X2 = 90.839, p<0.01) viewed to be very poor. For the majority of the local population sampled, 65% think ecotourism does not contribute to local livelihood around CMNP. The main factors influencing the impact of ecotourism around the CMNP on the local population’s livelihood were gender (logistic regression (β) = 1.218; p = 0.000); and level of education (logistic regression (β) = 0.442; p = 0.000). Furthermore, 55.6% of the local population investigated believed ecotourism activities do not contribute to the biodiversity conservation of CMNP. Spearman correlation between socio-economic variables and ecotourism impact on biodiversity conservation indicated relationships with gender (r = 0.200, p = 0.032), main occupation (r = 0.300 p = 0.012), time spent in the community (r = 0.287 p = 0.017), and number of children (r =-0.286 p = 0.018). Variables affecting ecotourism impact on biodiversity conservation were age (logistic regression (β) = -0.683; p = 0.037) and gender (logistic regression (β) = 0.917; p = 0.045). This study recommends the development of ecotourism-friendly policies that can accelerate Public Private Partnership for the sustainable management of the CMNP as a commitment toward good governance. It also recommends the development of gender-sensitive ecotourism packages, with fair opportunities for rural women and more parity in benefit sharing to improve livelihood and contribute more to biodiversity conservation in and around the Park.

Keywords: biodiversity conservation, Campo Ma’an national park, ecotourism, ecotourism governance, rural livelihoods, protected area management

Procedia PDF Downloads 91
138 Study and Simulation of a Dynamic System Using Digital Twin

Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

Procedia PDF Downloads 117
137 Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network

Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

Procedia PDF Downloads 81
136 Effect of E-Governance and E-Learning Platform on Access to University Education by Public Servants in Nigeria

Authors: Nwamaka Patricia Ibeme, Musa Zakari

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E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

Procedia PDF Downloads 39
135 The Effect of Finding and Development Costs and Gas Price on Basins in the Barnett Shale

Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

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Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

Procedia PDF Downloads 276
134 High Resolution Sandstone Connectivity Modelling: Implications for Outcrop Geological and Its Analog Studies

Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

Procedia PDF Downloads 179
133 Detailed Quantum Circuit Design and Evaluation of Grover's Algorithm for the Bounded Degree Traveling Salesman Problem Using the Q# Language

Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

Procedia PDF Downloads 148
132 An Approach to Building a Recommendation Engine for Travel Applications Using Genetic Algorithms and Neural Networks

Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

Procedia PDF Downloads 141
131 Study of Information Technology Support to Knowledge Sharing in Social Enterprises

Authors: Maria Granados

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Information technology (IT) facilitates the management of knowledge in organisations through the effective leverage of collective experience and knowledge of employees. This supports information processing needs, as well as enables and facilitates sense-making activities of knowledge workers. The study of IT support for knowledge management (KM) has been carried out mainly in larger organisations where resources and competitive conditions can trigger the use of KM. However, there is still a lack of understanding on how IT can support the management of knowledge under different organisational settings influenced by: constant tensions between social and economic objectives, more focus on sustainability than competiveness, limited resources, and high levels of democratic participation and intrinsic motivations among employees. All these conditions are presented in Social Enterprises (SEs), which are normally micro and small businesses that trade to tackle social problems, improve communities, people’s life chances, and the environment. Thus, their importance to society and economies is increasing. However, there is still a need for more understanding of how these organisations operate, perform, innovate and scale-up. This knowledge is crucial to design and provide accurate strategies to enhance the sector and increase its impact and coverage. To obtain a conceptual and empirical understanding of how IT can facilitate KM in the particular organisational conditions of SEs, a quantitative study was conducted with 432 owners and senior members of SEs in UK, underpinned by 21 interviews. The findings demonstrated how IT was supporting more the recovery and storage of necessary information in SEs, and less the collaborative work and communication among enterprise members. However, it was established that SEs were using cloud solutions, web 2.0 tools, Skype and centralised shared servers to manage informally their knowledge. The possible impediments for SEs to support themselves more on IT solutions can be linked mainly to economic and human constraints. These findings elucidate new perspectives that can contribute not only to SEs and SE supporters, but also to other businesses.

Keywords: social enterprises, knowledge management, information technology, collaboration, small firms

Procedia PDF Downloads 247
130 Shape Management Method for Safety Evaluation of Bridge Based on Terrestrial Laser Scanning Using Least Squares

Authors: Gichun Cha, Dongwan Lee, Junkyeong Kim, Aoqi Zhang, Seunghee Park

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All the world are studying the construction technology of double deck tunnel in order to respond to the increasing urban traffic demands and environmental changes. Advanced countries have the construction technology of the double deck tunnel structure. but the domestic country began research on it. Construction technologies are important. But Safety evaluation of structure is necessary to prevent possible accidents during construction. Thus, the double deck tunnel was required the shape management of middle slabs. The domestic country is preparing the construction of double deck tunnel for an alternate route and a pleasant urban environment. Shape management of double deck tunnel has been no research because it is a new attempted technology. The present, a similar study is bridge structure for the shape management. Bridge is implemented shape model using terrestrial laser scanning(TLS). Therefore, we proceed research on the bridge slabs because there is a similar structure of double deck tunnel. In the study, we develop shape management method of bridge slabs using TLS. We select the Test-bed for measurement site. This site is bridge located on Sungkyunkwan University Natural Sciences Campus. This bridge has a total length of 34m, the vertical height of 8.7m from the ground. It connects Engineering Building #1 and Engineering Building #2. Point cloud data for shape management is acquired the TLS and We utilized the Leica ScanStation C10/C5 model. We will confirm the Maximum displacement area of middle slabs using Least-Squares Fitting. We expect to raise stability for double deck tunnel through shape management for middle slabs.

Keywords: bridge slabs, least squares, safety evaluation, shape management method, terrestrial laser scanning

Procedia PDF Downloads 217
129 Comparison of Blockchain Ecosystem for Identity Management

Authors: K. S. Suganya, R. Nedunchezhian

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In recent years, blockchain technology has been found to be the most significant discovery in this digital era, after the discovery of the Internet and Cloud Computing. Blockchain is a simple, distributed public ledger that contains all the user’s transaction details in a block. The global copy of the block is then shared among all its peer-peer network users after validation by the Blockchain miners. Once a block is validated and accepted, it cannot be altered by any users making it a trust-free transaction. It also resolves the problem of double-spending by using traditional cryptographic methods. Since the advent of bitcoin, blockchain has been the backbone for all its transactions. But in recent years, it has found its roots and uses in many fields like Smart Contracts, Smart City management, healthcare, etc. Identity management against digital identity theft has become a major concern among financial and other organizations. To solve this digital identity theft, blockchain technology can be employed with existing identity management systems, which maintain a distributed public ledger containing details of an individual’s identity containing information such as Digital birth certificates, Citizenship number, Bank details, voter details, driving license in the form of blocks verified on the blockchain becomes time-stamped, unforgeable and publicly visible for any legitimate users. The main challenge in using blockchain technology to prevent digital identity theft is ensuring the pseudo-anonymity and privacy of the users. This survey paper will exert to study the blockchain concepts, consensus protocols, and various blockchain-based Digital Identity Management systems with their research scope. This paper also discusses the role of Blockchain in COVID-19 pandemic management by self-sovereign identity and supply chain management.

Keywords: blockchain, consensus protocols, bitcoin, identity theft, digital identity management, pandemic, COVID-19, self-sovereign identity

Procedia PDF Downloads 98
128 An Audit to Look at the Management of Paediatric Peri Orbital Cellulitis in a District General Hospital, Emergency Department

Authors: Ruth Green, Samantha Milton, Rinal Desai

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Background/Aims: Eye pain/swelling/redness is a common presentation to Barnet General Hospital (a district general hospital), pediatric emergency department, and is managed by both the pediatric and emergency teams. The management of each child differs dramatically depending on the healthcare professional who reviews them. There also appears to be confusion in diagnosis between periorbital cellulitis, pre-septal cellulitis, and orbital cellulitis. Pre septal cellulitis refers to an inflammation of the eyelids and soft tissue anterior to the orbital septum. In contrast, orbital cellulitis is a serious, rapidly progressive infection of soft tissues located posterior to the orbital septum. Pre-septal cellulitis is more prevalent and less serious than orbital cellulitis, although it may be part of a continuous spectrum if untreated. Pre-septal cellulitis should there be diagnosed and treated urgently to prevent spread to the septum. For the purpose of the audit, the term periorbital cellulitis has been used as an umbrella term for all spectrums of this infection. The audit aimed to look at, how as a whole, the department is diagnosing and managing orbital and pre-septal cellulitis. Gold Standard: Patients of the same age and diagnosis should be treated with the same medication, advice, and follow-up. Method: Data was collected retrospectively from pediatric patients ( < 18years) who attended the emergency department from June 2019 to February 2020 who had been coded as pre-septal cellulitis, periorbital cellulitis, orbital cellulitis, or eye pain/swelling/redness. Demographics, signs and symptoms, management, and follow-up were recorded for all patients with any of the diagnoses of pre-septal, periorbital, or orbital cellulitis. A Microsoft Excel spreadsheet was used to record the anonymised data. Results: There were vast discrepancies in the diagnosis, management, and follow-up of patients with periorbital cellulitis. Conclusion/Discussion: The audit concluded there is no uniform approach to managing periorbital cellulitis in Barnet General Hospital Paediatric Emergency Department. Healthcare professionals misdiagnosed conjunctivitis as periorbital cellulitis, and adequate steps did not appear to be documented on excluding red flag signs and symptoms of patients presenting. There was no consistency in follow-up, with some patients having timely phone reviews or clinical reviews for mild symptoms. Advice given by the staff was appropriate, and patients did return when symptoms got worse and were treated accordingly. Plan: Given the inconsistency, a gold standard care pathway or local easily accessible clinical guideline can be developed to help with the diagnosis and management of periorbital cellulitis. Along with this, a teaching session can be carried out for the staff of the pediatric team and emergency department to disseminate the teaching. Following the introduction of a guideline and teaching sessions, patients notes can be re-reviewed to check improvement in patient care.

Keywords: periorbital cellulitis, preseptal cellulitis, orbital cellulitis, erythematous eyelid

Procedia PDF Downloads 107
127 The Relationship between Osteoporosis-Related Knowledge and Physical Activity among Women Age over 50 Years

Authors: P. Tardi, B. Szilagyi, A. Makai, P. Acs, M. Hock, M. Jaromi

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Osteoporosis is becoming a major public health problem, particularly in postmenopausal women, as the incidence of this disease is getting higher. Nowadays, one of the most common chronic musculoskeletal diseases is osteoporosis. Osteoporosis-related knowledge is an important contributor to prevent or to treat osteoporosis. The most important strategies to prevent or treat the disease are increasing the level of physical activity at all ages, cessation of smoking, reduction of alcohol consumption, adequate dietary calcium, and vitamin D intake. The aim of the study was to measure the osteoporosis-related knowledge and physical activity among women age over 50 years. For the measurements, we used the osteoporosis questionnaire (OPQ) to examine the disease-specific knowledge and the global physical activity questionnaire (GPAQ) to measure the quantity and quality of the physical activity. The OPQ is a self-administered 20-item questionnaire with five categories: general information, risk factors, investigations, consequences, and treatment. There are four choices per question (one of them is the 'I do not know'). The filler gets +1 for a good answer, -1 point for a bad answer, and 0 for 'I do not know' answer. We contacted with 326 women (63.08 ± 9.36 year) to fill out the questionnaires. Descriptive analysis was carried out, and we calculated Spearman's correlation coefficient to examine the relationship between the variables. Data were entered into Microsoft Excel, and all statistical analyses were performed using SPSS (Version 24). The participants of the study (n=326) reached 8.76 ± 6.94 points on OPQ. Significant (p < 0.001) differences were found in the results of OPQ according to the highest level of education. It was observed that the score of the participants with osteoporosis (10.07 ± 6.82 points) was significantly (p=0.003) higher than participants without osteoporosis (9.38 ± 6.66 points) and the score of those women (6.49 ± 6.97 points) who did not know that osteoporosis exists in their case. The GPAQ results showed the sample physical activity in the dimensions of vigorous work (479.86 ± 684.02 min/week); moderate work (678.16 ± 804.5 min/week); travel (262.83 ± 380.27 min/week); vigorous recreation (77.71 ± 123.46 min/week); moderate recreation (115.15 ± 154.82 min/week) and total weekly physical activity (1645.99 ± 1432.88 min/week). Significant correlations were found between the osteoporosis-related knowledge and the physical activity in travel (R=0.21; p < 0.001), vigorous recreation (R=0.35; p < 0.001), moderate recreation (R=0.35; p < 0.001), total vigorous minutes/week (R=0.15; p=0.001) and total moderate minutes/week (R=0.13; p=0.04) dimensions. According to the results that were achieved, the highest level of education significantly determines osteoporosis-related knowledge. Physical activity is an important contributor to prevent or to treat osteoporosis, and it showed a significant correlation with osteoporosis-related knowledge. Based on the results, the development of osteoporosis-related knowledge may help to improve the level of physical activity, especially recreation. Acknowledgment: Supported by the ÚNKP-20-1 New National Excellence Program of The Ministry for Innovation and Technology from the Source of the National Research, Development and Innovation Fund.

Keywords: osteoporosis, osteoporosis-related knowledge, physical activity, prevention

Procedia PDF Downloads 87
126 Mobi Navi Tour for Rescue Operations

Authors: V. R. Sadasivam, M. Vipin, P. Vineeth, M. Sajith, G. Sathiskumar, R. Manikandan, N. Vijayarangan

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Global positioning system technology is what leads to such things as navigation systems, GPS tracking devices, GPS surveying and GPS mapping. All that GPS does is provide a set of coordinates which represent the location of GPS units with respect to its latitude, longitude and elevation on planet Earth. It also provides time, which is accurate. The tracking devices themselves come in different flavors. They will contain a GPS receiver, and GPS software, along with some way of transmitting the resulting coordinates. GPS in mobile tend to use radio waves to transmit their location to another GPS device. The purpose of this prototype “Mobi Navi Tour for Rescue Operation” timely communication, and lightning fast decision-making with a group of people located in different places with a common goal. Timely communication and tracking the people are a critical issue in many situations, environments. Expedited can find missing person by sending the location and other related information to them through mobile. Information must be drawn from the caller and entered into the system by the administrator or a group leader and transferred to the group leader. This system will locate the closest available person, a group of people working in an organization/company or vehicle to determine availability and their position to track them. Misinformation cannot lead to the wrong decision in the rapidly paced environment in a normal and an abnormal situation. In “Mobi Navi Tour for Rescue Operation” we use Google Cloud Messaging for android (GCM) which is a service that helps developers send data from servers to their android applications on android devices. The service provides a simple, lightweight mechanism that servers can use to tell mobile applications to contact the server directly, to fetch updated application or user data.

Keywords: android, gps, tour, communication, service

Procedia PDF Downloads 373
125 Adaptable Regulatory Oversight and Safety Awareness Regime: An Experience-Based Contribution Towards Sustainability in a Changing Railway Environment

Authors: Peaceman Sopazi, Mabila Mathebula, John Smallwood

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Recent health and safety (H&S) concerns and their resultant impact on railway operations, namely, the severe acute respiratory syndrome (SARS) or collectively known as SARS-CoV-2 (Covid-19) pandemic and the Fourth Industrial Revolution (4IR), which have dominated public discourse, brought into question as to whether, or not, some aspects of how we have so far managed safety oversight as railway regulatory bodies and operators will remain relevant in a changing railway environment. Railway practitioners have generally found themselves between a proverbial rock and a hard place by being confronted by emerging challenges which have brought along great opportunities for sustainability. As witnesses and participants to the progressively introduced railway safety management, and transformation regimes, this paper attempts to share gathered field experience on adaptable regulatory oversight and safety awareness. The discourse is approached from a South African context but also with an informed perspective of what seems to work and what usually does not. The authors share their own multi and transdisciplinary experience coupled with insights they have gained as researchers of global trends in general safety management and specific aspects of railway safety management, for sustainability. In addition to sharing a largely experience-based methodology for survival, suggestions are offered for consideration as a way of keeping the railway safety management discourse alive as practitioners navigate a new path which is shrouded in a cloud of untold uncertainty. The authors further believe that the right timing for the implementation of the proposed suggestions in this paper will produce beneficial outcomes. Finally, the paper will identify areas that are still open for further investigation for and by researchers and practitioners alike.

Keywords: health & safety management, safety awareness, railway safety management, railway systems sustainability

Procedia PDF Downloads 145
124 3D Dentofacial Surgery Full Planning Procedures

Authors: Oliveira M., Gonçalves L., Francisco I., Caramelo F., Vale F., Sanz D., Domingues M., Lopes M., Moreia D., Lopes T., Santos T., Cardoso H.

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The ARTHUR project consists of a platform that allows the virtual performance of maxillofacial surgeries, offering, in a photorealistic concept, the possibility for the patient to have an idea of the surgical changes before they are performed on their face. For this, the system brings together several image formats, dicoms and objs that, after loading, will generate the bone volume, soft tissues and hard tissues. The system also incorporates the patient's stereophotogrammetry, in addition to their data and clinical history. After loading and inserting data, the clinician can virtually perform the surgical operation and present the final result to the patient, generating a new facial surface that contemplates the changes made in the bone and tissues of the maxillary area. This tool acts in different situations that require facial reconstruction, however this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. Being developed a cloud based solution, with mobile support, the tool aims to reduce the decision time window of patient. Because the current simulations are not realistic or, if realistic, need time due to the need of building plaster models, patient rates on decision, rely on a long time window (1,2 months), because they don’t identify themselves with the presented surgical outcome. On the other hand, this planning was performed time based on average estimated values of the position of the maxilla and mandible. The team was based on averages of the facial measurements of the population, without specifying racial variability, so the proposed solution was not adjusted to the real individual physiognomic needs.

Keywords: 3D computing, image processing, image registry, image reconstruction

Procedia PDF Downloads 173
123 A Study on the Korean Connected Industrial Parks Smart Logistics It Financial Enterprise Architecture

Authors: Ilgoun Kim, Jongpil Jeong

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Recently, a connected industrial parks (CIPs) architecture using new technologies such as RFID, cloud computing, CPS, Big Data, 5G 5G, IIOT, VR-AR, and ventral AI algorithms based on IoT has been proposed. This researcher noted the vehicle junction problem (VJP) as a more specific detail of the CIPs architectural models. The VJP noted by this researcher includes 'efficient AI physical connection challenges for vehicles' through ventilation, 'financial and financial issues with complex vehicle physical connections,' and 'welfare and working conditions of the performing personnel involved in complex vehicle physical connections.' In this paper, we propose a public solution architecture for the 'electronic financial problem of complex vehicle physical connections' as a detailed task during the vehicle junction problem (VJP). The researcher sought solutions to businesses, consumers, and Korean social problems through technological advancement. We studied how the beneficiaries of technological development can benefit from technological development with many consumers in Korean society and many small and small Korean company managers, not some specific companies. In order to more specifically implement the connected industrial parks (CIPs) architecture using the new technology, we noted the vehicle junction problem (VJP) within the smart factory industrial complex and noted the process of achieving the vehicle junction problem performance among several electronic processes. This researcher proposes a more detailed, integrated public finance enterprise architecture among the overall CIPs architectures. The main details of the public integrated financial enterprise architecture were largely organized into four main categories: 'business', 'data', 'technique', and 'finance'.

Keywords: enterprise architecture, IT Finance, smart logistics, CIPs

Procedia PDF Downloads 137