Search results for: automatic cartography generalization
247 Modeling Breathable Particulate Matter Concentrations over Mexico City Retrieved from Landsat 8 Satellite Imagery
Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa
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In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.Keywords: air quality, modeling pollution, particulate matter, remote sensing
Procedia PDF Downloads 148246 Modelling of Air-Cooled Adiabatic Membrane-Based Absorber for Absorption Chillers Using Low Temperature Solar Heat
Authors: M. Venegas, M. De Vega, N. García-Hernando
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Absorption cooling chillers have received growing attention over the past few decades as they allow the use of low-grade heat to produce the cooling effect. The combination of this technology with solar thermal energy in the summer period can reduce the electricity consumption peak due to air-conditioning. One of the main components, the absorber, is designed for simultaneous heat and mass transfer. Usually, shell and tubes heat exchangers are used, which are large and heavy. Cooling water from a cooling tower is conventionally used to extract the heat released during the absorption and condensation processes. These are clear inconvenient for the generalization of the absorption technology use, limiting its benefits in the contribution to the reduction in CO2 emissions, particularly for the H2O-LiBr solution which can work with low heat temperature sources as provided by solar panels. In the present work a promising new technology is under study, consisting in the use of membrane contactors in adiabatic microchannel mass exchangers. The configuration here proposed consists in one or several modules (depending on the cooling capacity of the chiller) that contain two vapour channels, separated from the solution by adjacent microporous membranes. The solution is confined in rectangular microchannels. A plastic or synthetic wall separates the solution channels between them. The solution entering the absorber is previously subcooled using ambient air. In this way, the need for a cooling tower is avoided. A model of the configuration proposed is developed based on mass and energy balances and some correlations were selected to predict the heat and mass transfer coefficients. The concentration and temperatures along the channels cannot be explicitly determined from the set of equations obtained. For this reason, the equations were implemented in a computer code using Engineering Equation Solver software, EES™. With the aim of minimizing the absorber volume to reduce the size of absorption cooling chillers, the ratio between the cooling power of the chiller and the absorber volume (R) is calculated. Its variation is shown along the solution channels, allowing its optimization for selected operating conditions. For the case considered the solution channel length is recommended to be lower than 3 cm. Maximum values of R obtained in this work are higher than the ones found in optimized horizontal falling film absorbers using the same solution. Results obtained also show the variation of R and the chiller efficiency (COP) for different ambient temperatures and desorption temperatures typically obtained using flat plate solar collectors. The configuration proposed of adiabatic membrane-based absorber using ambient air to subcool the solution is a good technology to reduce the size of the absorption chillers, allowing the use of low temperature solar heat and avoiding the need for cooling towers.Keywords: adiabatic absorption, air-cooled, membrane, solar thermal energy
Procedia PDF Downloads 273245 Lung HRCT Pattern Classification for Cystic Fibrosis Using a Convolutional Neural Network
Authors: Parisa Mansour
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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence
Procedia PDF Downloads 57244 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks
Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin
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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network
Procedia PDF Downloads 124243 Solar PV System for Automatic Guideway Transit (AGT) System in BPSU Main Campus
Authors: Nelson S. Andres, Robert O. Aguilar, Mar O. Tapia, Meeko C. Masangcap, John Denver Catapang, Greg C. Mallari
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This study focuses on exploring the possibility of using solar PV as an alternative for generating electricity to electrify the AGT System installed in BPSU Main Campus instead of using the power grid. The output of this study gives BPSU the option to invest on solar PV system to pro-actively respond to one of UN’s Sustainable Development Goals of having reliable, sustainable and modern energy sources to reduce energy pollution and climate change impact in the long run. Thus, this study covers the technical as well as the financial studies, which BPSU can also be used to outsource funding from different government agencies. For this study, the electrical design and requirements of the on-going DOST AGT system project are carefully considered. In the proposed design, the AGT station has installed with a rechargeable battery system where the energy harnessed by the solar PV panels installed on the rooftop of the station/NCEA building shall be directed to. The solar energy is then directly supplied to the electric double-layer capacitors (EDLC's) batteries and thus transmitted to other types of equipment in need. When the AGT is not in use, the harnessed energy may be used by NCEA building, thus, lessening the energy consumption of the building from the grid. The use of solar PV system with EDLC is compared with the use of an electric grid for the purpose of electrifying the AGT or the NCEA building (when AGT is not in use). This is to figure how much solar energy are accumulated by the solar PV to accommodate the need for coaches’ motors, lighting, air-conditioning units, door sensor, panel display, etc. The proposed PV Solar design, as well as the data regarding the charging and discharging of batteries and the power consumption of all AGT components, are simulated for optimization, analysis and validation through the use of PVSyst software.Keywords: AGT, Solar PV, railway, EDLC
Procedia PDF Downloads 74242 Environmental Protection by Optimum Utilization of Car Air Conditioners
Authors: Sanchita Abrol, Kunal Rana, Ankit Dhir, S. K. Gupta
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According to N.R.E.L.’s findings, 700 crore gallons of petrol is used annually to run the air conditioners of passenger vehicles (nearly 6% of total fuel consumption in the USA). Beyond fuel use, the Environmental Protection Agency reported that refrigerant leaks from auto air conditioning units add an additional 5 crore metric tons of carbon emissions to the atmosphere each year. The objective of our project is to deal with this vital issue by carefully modifying the interiors of a car thereby increasing its mileage and the efficiency of its engine. This would consequently result in a decrease in tail emission and generated pollution along with improved car performance. An automatic mechanism, deployed between the front and the rear seats, consisting of transparent thermal insulating sheet/curtain, would roll down as per the requirement of the driver in order to optimize the volume for effective air conditioning, when travelling alone or with a person. The reduction in effective volume will yield favourable results. Even on a mild sunny day, the temperature inside a parked car can quickly spike to life-threatening levels. For a stationary parked car, insulation would be provided beneath its metal body so as to reduce the rate of heat transfer and increase the transmissivity. As a result, the car would not require a large amount of air conditioning for maintaining lower temperature, which would provide us similar benefits. Authors established the feasibility studies, system engineering and primarily theoretical and experimental results confirming the idea and motivation to fabricate and test the actual product.Keywords: automation, car, cooling insulating curtains, heat optimization, insulation, reduction in tail emission, mileage
Procedia PDF Downloads 264241 Fuzzy Logic for Control and Automatic Operation of Natural Ventilation in Buildings
Authors: Ekpeti Bukola Grace, Mahmoudi Sabar Esmail, Chaer Issa
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Global energy consumption has been increasing steadily over the last half - century, and this trend is projected to continue. As energy demand rises in many countries throughout the world due to population growth, natural ventilation in buildings has been identified as a viable option for lowering these demands, saving costs, and also lowering CO2 emissions. However, natural ventilation is driven by forces that are generally unpredictable in nature thus, it is important to manage the resulting airflow in order to maintain pleasant indoor conditions, making it a complex system that necessitates specific control approaches. The effective application of fuzzy logic technique amidst other intelligent systems is one of the best ways to bridge this gap, as its control dynamics relates more to human reasoning and linguistic descriptions. This article reviewed existing literature and presented practical solutions by applying fuzzy logic control with optimized techniques, selected input parameters, and expert rules to design a more effective control system. The control monitors used indoor temperature, outdoor temperature, carbon-dioxide levels, wind velocity, and rain as input variables to the system, while the output variable remains the control of window opening. This is achieved through the use of fuzzy logic control tool box in MATLAB and running simulations on SIMULINK to validate the effectiveness of the proposed system. Comparison analysis model via simulation is carried out, and with the data obtained, an improvement in control actions and energy savings was recorded.Keywords: fuzzy logic, intelligent control systems, natural ventilation, optimization
Procedia PDF Downloads 117240 A Tool for Facilitating an Institutional Risk Profile Definition
Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan
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This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.Keywords: digital information management, file format, endangerment analysis, fuzzy models
Procedia PDF Downloads 394239 Development of a Sequential Multimodal Biometric System for Web-Based Physical Access Control into a Security Safe
Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran
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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.Keywords: access control, multimodal biometrics, pattern recognition, security safe
Procedia PDF Downloads 323238 Improvement of Microscopic Detection of Acid-Fast Bacilli for Tuberculosis by Artificial Intelligence-Assisted Microscopic Platform and Medical Image Recognition System
Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin
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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.Keywords: TB smears, automated microscope, artificial intelligence, medical imaging
Procedia PDF Downloads 212237 A Real-Time Moving Object Detection and Tracking Scheme and Its Implementation for Video Surveillance System
Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu
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Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance
Procedia PDF Downloads 466236 Autonomous Flight Control for Multirotor by Alternative Input Output State Linearization with Nested Saturations
Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren
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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.Keywords: automatic flight control, input output linearization, multirotor, nested saturations
Procedia PDF Downloads 222235 The Gaps of Environmental Criminal Liability in Armed Conflicts and Its Consequences: An Analysis under Stockholm, Geneva and Rome
Authors: Vivian Caroline Koerbel Dombrowski
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Armed conflicts have always meant the ultimate expression of power and at the same time, lack of understanding among nations. Cities were destroyed, people were killed, assets were devastated. But these are not only the loss of a war: the environmental damage comes to be considered immeasurable losses in the short, medium and long term. And this is because no nation wants to bear that cost. They invest in military equipment, training, technical equipment but the environmental account yet finds gaps in international law. Considering such a generalization in rights protection, many nations are at imminent danger in a conflict if the water will be used as a mass weapon, especially if we consider important rivers such as Jordan, Euphrates and Nile. The top three international documents were analyzed on the subject: the Stockholm Convention (1972), Additional Protocol I to the Geneva Convention (1977) and the Rome Statute (1998). Indeed, some references are researched in doctrine, especially scientific articles, to substantiate with consistent data about the extent of the damage, historical factors and decisions which have been successful. However, due to the lack of literature about this subject, the research tends to be exhaustive. From the study of the indicated material, it was noted that international law - humanitarian and environmental - calls in some of its instruments the environmental protection in war conflicts, but they are generic and vague rules that do not define exactly what is the environmental damage , nor sets standards for measure them. Taking into account the mains conflicts of the century XX: World War II, the Vietnam War and the Gulf War, one must realize that the environmental consequences were of great rides - never deactivated landmines, buried nuclear weapons, armaments and munitions destroyed in the soil, chemical weapons, not to mention the effects of some weapons when used (uranium, agent Orange, etc). Extending the search for more recent conflicts such as Afghanistan, it is proven that the effects on health of the civilian population were catastrophic: cancer, birth defects, and deformities in newborns. There are few reports of nations that, somehow, repaired the damage caused to the environment as a result of the conflict. In the pitch of contemporary conflicts, many nations fear that water resources are used as weapons of mass destruction, because once contaminated - directly or indirectly - can become a means of disguised genocide side effect of military objective. In conclusion, it appears that the main international treaties governing the subject mention the concern for environmental protection, however leave the normative specifications vacancies necessary to effectively there is a prevention of environmental damage in armed conflict and, should they occur, the repair of the same. Still, it appears that there is no protection mechanism to safeguard natural resources and avoid them to become a mass destruction weapon.Keywords: armed conflicts, criminal liability, environmental damages, humanitarian law, mass weapon
Procedia PDF Downloads 410234 Fuzzy Control of Thermally Isolated Greenhouse Building by Utilizing Underground Heat Exchanger and Outside Weather Conditions
Authors: Raghad Alhusari, Farag Omar, Moustafa Fadel
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A traditional greenhouse is a metal frame agricultural building used for cultivation plants in a controlled environment isolated from external climatic changes. Using greenhouses in agriculture is an efficient way to reduce the water consumption, where agriculture field is considered the biggest water consumer world widely. Controlling greenhouse environment yields better productivity of plants but demands an increase of electric power. Although various control approaches have been used towards greenhouse automation, most of them are applied to traditional greenhouses with ventilation fans and/or evaporation cooling system. Such approaches are still demanding high energy and water consumption. The aim of this research is to develop a fuzzy control system that minimizes water and energy consumption by utilizing outside weather conditions and underground heat exchanger to maintain the optimum climate of the greenhouse. The proposed control system is implemented on an experimental model of thermally isolated greenhouse structure with dimensions of 6x5x2.8 meters. It uses fans for extracting heat from the ground heat exchanger system, motors for automatic open/close of the greenhouse windows and LED as lighting system. The controller is integrated also with environmental condition sensors. It was found that using the air-to-air horizontal ground heat exchanger with 90 mm diameter and 2 mm thickness placed 2.5 m below the ground surface results in decreasing the greenhouse temperature of 3.28 ˚C which saves around 3 kW of consumed energy. It also eliminated the water consumption needed in evaporation cooling systems which are traditionally used for cooling the greenhouse environment.Keywords: automation, earth-to-air heat exchangers, fuzzy control, greenhouse, sustainable buildings
Procedia PDF Downloads 122233 Innovative Design Considerations for Adaptive Spacecraft
Authors: K. Parandhama Gowd
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Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.Keywords: satellites, low earth orbit (LEO), medium earth orbit (MEO), geostationary earth orbit (GEO), self-organizing control system, anti-satellite weapons (ASAT), orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems (AOCS), command and data handling (CDH)
Procedia PDF Downloads 285232 Pattern the Location and Area of Earth-Dumping Stations from Vehicle GPS Data in Taiwan
Authors: Chun-Yuan Chen, Ming-Chang Li, Xiu-Hui Wen, Yi-Ching Tu
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The objective of this study explores GPS (Global Positioning System) applied to trace construction vehicles such as trucks or cranes, help to pattern the earth-dumping stations of traffic construction in Taiwan. Traffic construction in this research is defined as the engineering of high-speed railways, expressways, and which that distance more than kilometers. Audit the location and check the compliance with regulations of earth-dumping stations is one of important tasks in Taiwan EPA. Basically, the earth-dumping station was known as one source of particulate matter from air pollution during construction process. Due to GPS data can be analyzed quickly and be used conveniently, this study tried to find out dumping stations by modeling vehicles tracks from GPS data during work cycle of construction. The GPS data updated from 13 vehicles related to an expressway construction in central Taiwan. The GPS footprints were retrieved to Keyhole Markup Language (KML) files so that can pattern the tracks of trucks by computer applications, the data was collected about eight months- from Feb. to Oct. in 2017. The results of GPS footprints identified dumping station and outlined the areas of earthwork had been passed to the Taiwan EPA for on-site inspection. Taiwan EPA had issued advice comments to the agency which was in charge of the construction to prevent the air pollution. According to the result of this study compared to the commonly methods in inspecting environment by manual collection, the GPS with KML patterning and modeling method can consumes less time. On the other hand, through monitoring the GPS data from construction vehicles could be useful for administration to development and implementation of strategies in environmental management.Keywords: automatic management, earth-dumping station, environmental management, Global Positioning System (GPS), particulate matter, traffic construction
Procedia PDF Downloads 157231 Performance Evaluation of the CareSTART S1 Analyzer for Quantitative Point-Of-Care Measurement of Glucose-6-Phosphate Dehydrogenase Activity
Authors: Haiyoung Jung, Mi Joung Leem, Sun Hwa Lee
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Background & Objective: Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a genetic abnormality that results in an inadequate amount of G6PD, leading to increased susceptibility of red blood cells to reactive oxygen species and hemolysis. The present study aimed to evaluate the careSTARTTM S1 analyzer for measuring G6PD activity to hemoglobin (Hb) ratio. Methods: Precision for G6PD activity and hemoglobin measurement was evaluated using control materials with two levels on five repeated runs per day for five days. The analytic performance of the careSTARTTM S1 analyzer was compared with spectrophotometry in 40 patient samples. Reference ranges suggested by the manufacturer were validated in 20 healthy males and females each. Results: The careSTARTTM S1 analyzer demonstrated precision of 6.0% for low-level (14~45 U/dL) and 2.7% for high-level (60~90 U/dL) control in G6PD activity, and 1.4% in hemoglobin (7.9~16.3 u/g Hb). A comparison study of G6PD to Hb ratio between the careSTARTTM S1 analyzer and spectrophotometry showed an average difference of 29.1% with a positive bias of the careSTARTTM S1 analyzer. All normal samples from the healthy population were validated for the suggested reference range for males (≥2.19 U/g Hb) and females (≥5.83 U/g Hb). Conclusion: The careSTARTTM S1 analyzer demonstrated good analytical performance and can replace the current spectrophotometric measurement of G6PD enzyme activity. In the aspect of the management of clinical laboratories, it can be a reasonable option as a point-of-care analyzer with minimal handling of samples and reagents, in addition to the automatic calculation of the ratio of measured G6PD activity and Hb concentration, to minimize any clerical errors involved with manual calculation.Keywords: POCT, G6PD, performance evaluation, careSTART
Procedia PDF Downloads 58230 Effect of Threshold Configuration on Accuracy in Upper Airway Analysis Using Cone Beam Computed Tomography
Authors: Saba Fahham, Supak Ngamsom, Suchaya Damrongsri
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Objective: The objective is to determine the optimal threshold of Romexis software for the airway volume and minimum cross-section area (MCA) analysis using Image J as a gold standard. Materials and Methods: A total of ten cone-beam computed tomography (CBCT) images were collected. The airway volume and MCA of each patient were analyzed using the automatic airway segmentation function in the CBCT DICOM viewer (Romexis). Airway volume and MCA measurements were conducted on each CBCT sagittal view with fifteen different threshold values from the Romexis software, Ranging from 300 to 1000. Duplicate DICOM files, in axial view, were imported into Image J for concurrent airway volume and MCA analysis as the gold standard. The airway volume and MCA measured from Romexis and Image J were compared using a t-test with Bonferroni correction, and statistical significance was set at p<0.003. Results: Concerning airway volume, thresholds of 600 to 850 as well as 1000, exhibited results that were not significantly distinct from those obtained through Image J. Regarding MCA, employing thresholds from 400 to 850 within Romexis Viewer showed no variance from Image J. Notably, within the threshold range of 600 to 850, there were no statistically significant differences observed in both airway volume and MCA analyses, in comparison to Image J. Conclusion: This study demonstrated that the utilization of Planmeca Romexis Viewer 6.4.3.3 within threshold range of 600 to 850 yields airway volume and MCA measurements that exhibit no statistically significant variance in comparison to measurements obtained through Image J. This outcome holds implications for diagnosing upper airway obstructions and post-orthodontic surgical monitoring.Keywords: airway analysis, airway segmentation, cone beam computed tomography, threshold
Procedia PDF Downloads 34229 EQMamba - Method Suggestion for Earthquake Detection and Phase Picking
Authors: Noga Bregman
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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves
Procedia PDF Downloads 22228 Design of a Small Mobile PV Driven RO Water Desalination Plant to be Deployed at the North West Coast of Egypt
Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar
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Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt
Procedia PDF Downloads 562227 A Review on Benzo(a)pyrene Emission Factors from Biomass Combustion
Authors: Franziska Klauser, Manuel Schwabl, Alexander Weissinger, Christoph Schmidl, Walter Haslinger, Anne Kasper-Giebl
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Benzo(a)pyrene (BaP) is the most widely investigated representative of Polycyclic Aromatic Hydrocarbons (PAH) as well as one of the most toxic compounds in this group. Since 2013 in the European Union a limit value for BaP concentration in the ambient air is applied, which was set to a yearly average value of 1 ng m-3. Several reports show that in some regions, even where industry and traffic are of minor impact this threshold is regularly exceeded. This is taken as proof that biomass combustion for heating purposes contributes significantly to BaP pollution. Several investigations have been already carried out on the BaP emission behavior of biomass combustion furnaces, mostly focusing on a certain aspect like the influences from wood type, of operation type or of technology type. However, a superior view on emission patterns of BaP from biomass combustion and the aggregation of determined values also from recent studies is not presented so far. The combination of determined values allows a better understanding of the BaP emission behavior from biomass combustion. In this work the review conclusions are driven from the combination of outcomes from different publication. In two examples it was shown that technical progress leads to 10 to 100 fold lower BaP emission from modern furnaces compared to old technologies of equivalent type. It was also indicated that the operation with pellets or wood chips exhibits clearly lower BaP emission factors compared to operation with log wood. Although, the BaP emission level from automatic furnaces is strongly impacted by the kind of operation. This work delivers an overview on BaP emission factors from different biomass combustion appliances, from different operation modes and from the combustion of different fuel and wood types. The main impact factors are depicted, and suggestions for low BaP emission biomass combustion are derived. As one result possible investigation fields concerning BaP emissions from biomass combustion that seem to be most important to be clarified are suggested.Keywords: benzo(a)pyrene, biomass, combustion, emission, pollution
Procedia PDF Downloads 349226 Development of an Aerosol Protection Capsule for Patients with COVID-19
Authors: Isomar Lima da Silva, Aristeu Jonatas Leite de Oliveira, Roberto Maia Augusto
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Biological isolation capsules are equipment commonly used in the control and prevention of infectious diseases in the hospital environment. This type of equipment, combined with pre-established medical protocols, contributes significantly to the containment of highly transmissible pathogens such as COVID-19. Due to its hermetic isolation, it allows more excellent patient safety, protecting companions and the health team. In this context, this work presents the development, testing, and validation of a medical capsule to treat patients affected by COVID-19. To this end, requirements such as low cost and easy handling were considered to meet the demand of people infected with the virus in remote locations in the Amazon region and/or where there are no ICU beds and mechanical ventilators for orotracheal intubation. Conceived and developed in a partnership between SAMEL Planos de Saúde and Instituto Conecthus, the device entitled "Vanessa Capsule" was designed to be used together with the NIV protocol (non-invasive ventilation), has an automatic exhaust system and filters performing the CO2 exchange, in addition to having BiPaps ventilatory support equipment (mechanical fans) in the Cabin Kit. The results show that the degree of effectiveness in protecting against infection by aerosols, with the protection cabin, is satisfactory, implying the consideration of the Vanessa capsule as an auxiliary method to be evaluated by the health team. It should also be noted that the medical observation of the evaluated patients found that the treatment against the COVID-19 virus started earlier with non-invasive mechanical ventilation reduces the patient's suffering and contributes positively to their recovery, in association with isolation through the Vanessa capsule.Keywords: COVID-19, mechanical ventilators, medical capsule, non-invasive ventilation
Procedia PDF Downloads 76225 Quantitative, Preservative Methodology for Review of Interview Transcripts Using Natural Language Processing
Authors: Rowan P. Martnishn
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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding
Procedia PDF Downloads 14224 Development of Electronic Services in Georgia: Analysis of Current Situation
Authors: Dato Surmanidze, Dato Antadze, Tornike Partenadze
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Public online services in Georgia are concentrated on main target segments: public administration, business, population, non-governmental and other interested organizations. Therefore, the strategy of digital Georgia is focused on providing G2C, G2B/B2G, G2NGO and G2G services. In G2C framework sophisticated and high-technological online services have been developed in order to provide passports, identity cards, documentations concerning residence and civil acts (birth, marriage, divorce, child adoption, change of name and surname, death, etc) as well as other services. Websites like my.gov.ge and sda.gov.ge have distance services like electronic application, processing and decision making. In line with international standards automatic services like electronic tenders, product catalogues, invoices and payment have been developed. This creates better investment climate for foreign companies in Georgia in the framework of G2B politics. The website mybusiness.gov.ge creates better conditions for local business. Among electronic services is e-NRMS (electronic system for national resource management) which was introduced by the Ministry of Finance of Georgia. The system was created in order to ensure management of national resources by state and business organizations. It is integrated with bank services and provides G2C, G2B and B2G representatives with electronic services. Also a portal meteo.gov.ge was created which gives electronic services concerning air, geological, environmental and pollution issues. Also worknet.gov.ge should be mentioned which is an electronic hub of information management for employers and employees. The information portal of labor market will facilitate receipt of information, its analysis and delivery to interested people like employers and employees. However, nowadays it’s been two years that only employees portal is activated. Therefore, awareness about the portal, its competitiveness and success is undermined.Keywords: electronic services, public administration, information technology, information society
Procedia PDF Downloads 260223 Application of Rapidly Exploring Random Tree Star-Smart and G2 Quintic Pythagorean Hodograph Curves to the UAV Path Planning Problem
Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães
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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart
Procedia PDF Downloads 162222 Comparison of the Results of a Parkinson’s Holter Monitor with Patient Diaries, in Real Conditions of Use: A Sub-Analysis of the MoMoPa-EC Clinical Trial
Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez
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Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.Keywords: Parkinson, sensor, motor fluctuations, dyskinesia
Procedia PDF Downloads 217221 MRI Quality Control Using Texture Analysis and Spatial Metrics
Authors: Kumar Kanudkuri, A. Sandhya
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Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy
Procedia PDF Downloads 153220 Bridge Members Segmentation Algorithm of Terrestrial Laser Scanner Point Clouds Using Fuzzy Clustering Method
Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park
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3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)
Procedia PDF Downloads 224219 Alignment and Antagonism in Flux: A Diachronic Sentiment Analysis of Attitudes towards the Chinese Mainland in the Hong Kong Press
Authors: William Feng, Qingyu Gao
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Despite the extensive discussions about Hong Kong’s sentiments towards the Chinese Mainland since the sovereignty transfer in 1997, there has been no large-scale empirical analysis of the changing attitudes in the mainstream media, which both reflect and shape sentiments in the society. To address this gap, the present study uses an optimised semantic-based automatic sentiment analysis method to examine a corpus of news about China from 1997 to 2020 in three main Chinese-language newspapers in Hong Kong, namely Apple Daily, Ming Pao, and Oriental Daily News. The analysis shows that although the Hong Kong press had a positive emotional tone toward China in general, the overall trend of sentiment was becoming increasingly negative. Meanwhile, the alignment and antagonism toward China have both increased, providing empirical evidence of attitudinal polarisation in the Hong Kong society. Specifically, Apple Daily’s depictions of China have become increasingly negative, though with some positive turns before 2008, whilst Oriental Daily News has consistently expressed more favourable sentiments. Ming Pao maintained an impartial stance toward China through an increased but balanced representation of positive and negative sentiments, with its subjectivity and sentiment intensity growing to an industry-standard level. The results provide new insights into the complexity of sentiments towards China in the Hong Kong press and media attitudes in general in terms of the “us” and “them” positioning by explicating the cross-newspaper and cross-period variations using an enhanced sentiment analysis method which incorporates sentiment-oriented and semantic role analysis techniques.Keywords: media attitude, sentiment analysis, Hong Kong press, one country two systems
Procedia PDF Downloads 96218 Parameters Identification and Sensitivity Study for Abrasive WaterJet Milling Model
Authors: Didier Auroux, Vladimir Groza
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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization
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