Search results for: real output

Authors: Junfeng Yan, Wenkui Hou

Abstract:

Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

Procedia PDF Downloads 377

Authors: Sopio Gogilava, Goga Chakhaia, Levan Tsulukidze, Zurab Laoshvili, Irina Khubulava, Shalva Bosikashvili, Teimuraz Gugushvili

Abstract:

Geoinformatics systems (GIS) integrated computer program RAMMS is widely used for forecasting debris flows and accordingly for the determination of anticipating risks with 85% accuracy. In view of the above, the work introduces new capabilities of the computer program RAMMS, which evaluates the effectiveness of anti-debris flow engineering construction, namely: the possibility of decreasing the expected velocity, kinetic energy, and output cone volume in the Mletiskhevi River. As a result of research has been determined that the anti-debris flow engineering construction designed to reduce the expected debris flow risk in the Mletiskhevi River is an effective environmental protection technology, that's why its introduction is promising.

Keywords: construction, debris flow, geoinformatics systems, program RAMMS

Procedia PDF Downloads 145

Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

Abstract:

Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

Procedia PDF Downloads 577

Authors: K. A. Chinmaya, M. Udaya Bhaskar

Abstract:

Multiphase motor drives are now a day considered for numerous applications due to the advantages that they offer when compared to their three-phase counterparts. Proper modeling of inverters and motors are important in devising an appropriate control algorithm. This paper develops a complete modeling of a five-phase inverter and five-phase space vector modulation schemes which can be used for five-phase motor drives. A novel modified algorithm is introduced which enables the sinusoidal output voltages up to certain voltage value. The waveforms of phase to neutral voltage are compared with the different modulation techniques and also different modulation indexes in terms of Low-order Harmonic (LH) voltage of 3rd and 7th present. A detailed performance evolution of existing and newly modified schemes is done in terms of Total Harmonic Distortion (THD).

Keywords: multi-phase drives, space vector modulation, voltage source inverter, low order harmonic voltages, total harmonic distortion

Procedia PDF Downloads 404

Authors: Titis Indah Adi Rahayu

Abstract:

Angiogenesis is the process of generating new capillary from pre-existing blood vessels. VEGFA is a major regulator in angiogenesis that binds and activates two tyrosine kinase receptors, VEGFR1 (Flt-1) and VEGFR2 (Flk-1/KDR) which regulate pathological and physiological angiogenesis. Disruption of VEGFA and VEGFR2 regulation lead to many diseases. The study of α-Mangostin (derivate of xanthone) as anti-oxidant and anti inflammation has been explored recently and both of them have relation to vasculature however the effect of α-Mangostin in blood vessel formation in healthy tissue in vivo has not been studied. Zebrafish is a powerful model in studying angiogenesis and shared many advantages that is a viable whole animal model for screening small molecules that affect blood vessel formation. Therefore the aim of this study is to evaluate angiogenic activity of α-Mangostin in healthy tissue in vivo in zebrafish embryo in relation of patterning blood vessel. Blood vessel patterning is highly characteristic in the developing of zebrafish embryo and the subintestinal vessel (SIV) can be stained and visualized microscopically as a primary screen for α-Mangostin that effect angiogenesis. The zebrafish embryos are divided into 2 groups. Group one consists of the zebrafish embryos at 1 dpf for 4 days which are tested to α-Mangostin in several concentration 2 µM, 4 µM, 6 µM, 8 µM and 10 µM whereas in group two the zebrafish larva at 4 dpf are exposed to α-Mangostin 1,75 µM, 2,3 µM, 2,9 µM, 3,8 µM dan 5 µM for 2 days. DMSO is served as a control for each group. The level expression of vegfa and vegfr2 are observed quantitatively using real time q-PCR and patterning of SIV are then analized via alkaline phospatase staining. Result shows that the level expression of vegfa and vegfr2 is repressed quantitatively as shown in real time q-PCR in the group of 1-4 days of α-Mangostin exposure where it is increased in the group of 4-6 days of α-Mangostin exposure. The result is then compared to alkaline phospatase staining of SIV using stereo microscope. It indicates that α-Mangostin does not disturb the patterning of SIV formation in zebrafish.

Keywords: angiogenesis, Danio rerio, α-Mangostin, SIV, vegfa, vegfr2

Procedia PDF Downloads 342

Authors: Mahesh M. Patil, K. A. Anu-Appaiah

Abstract:

Overweight and obesity is a serious medical problem, increasing in prevalence, and affecting millions worldwide. Investigators have been trying from decades to articulate the burden of obesity and related risk factors. To answer this problem, we suggest a new therapeutic anti-obesity compounds from Garcinia xanthochymus fruit. However, there is little published scientific information on non-hydroxycitric acid Garcinia species. Our findings include biochemical characterization of the fruit; in vivo toxicity and bio-efficacy study of G. xanthochymus in high fat diet wistar rat model. We observed that Garcinia pericarp is a rich source of organic acids, polyphenols, mono- (40.63%) and poly-unsaturated fatty acids (16.45%; omega-3: 10.02%). Toxicological studies have showed that Garcinia is safe and had no observed adverse effect level up to 400 mg/kg/day. Body weight and food intake was significantly (P<0.05) reduced in oral gavage treated rats (sonicated Garcinia powder) in 13 weeks. Subcutaneous fat was significantly (P<0.05) reduced in Garcinia treated rats. Hepatocytes significantly (p<0.05) overexpressed sterol regulatory element binding protein 2, liver X receptor- α, liver X receptor- β, lipoprotein lipase and monoacylglycerol lipase. Fatty acid binding protein 1 and peroxisome proliferator activated receptor- α were down regulated as assessed by real time qPCR. Currently our research is focused on the adipocyte obesity related gene expressions, effect of Garcinia on 3T3-adipocyte cell lines and high fat diet induced mice model. This in vivo pre-clinical data suggests that G. xanthochymus may have clinical utility for the treatment of obesity. However, further studies are required to establish its potency.

Keywords: Garcinia xanthochymus, anti-obesity, high fat diet, real time qPCR

Procedia PDF Downloads 252

Authors: Muhammad Yousaf Sadiq

Abstract:

The complexity arises in defining the construction quality due to its perception, based on inherent market conditions and their requirements, the diversified stakeholders itself and their desired output. An quantitative survey based approach was adopted in this constructive study. A questionnaire-based survey was conducted for the assessment of construction Quality perception and expectations in the context of quality improvement technique. The survey feedback of professionals of the leading construction organizations/companies of Pakistan construction industry were analyzed. The financial capacity, organizational structure, and construction experience of the construction firms formed basis for their selection. The quality perception was found to be project-scope-oriented and considered as an excess cost for a construction project. Any quality improvement technique was expected to maximize the profit for the employer, by improving the productivity in a construction project. The study is beneficial for the construction professionals to assess the prevailing construction quality perception and the expectations from implementation of any quality improvement technique in construction projects.

Keywords: construction quality, expectation, improvement, perception

Procedia PDF Downloads 476

Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

Abstract:

A 1 kW power factor correction boost converter with an active snubber cell is presented in this paper. In the converter, the main switch turns on under zero voltage transition (ZVT) and turns off under zero current transition (ZCT) without any additional voltage or current stress. The auxiliary switch turns on and off under zero current switching (ZCS). Besides, the main diode turns on under ZVS and turns off under ZCS. The output current and voltage are controlled by the PFC converter in wide line and load range. The simulation results of converter are obtained for 1 kW and 100 kHz. One of the most important feature of the given converter is that it has direct power transfer as well as excellent soft switching techniques. Also, the converter has 0.99 power factor with the sinusoidal input current shape.

Keywords: power factor correction, direct power transfer, zero-voltage transition, zero-current transition, soft switching

Procedia PDF Downloads 962

Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

Procedia PDF Downloads 85

Authors: Aristeidis Samitas, Stathis Polyzos

Abstract:

As the UK and the EU prepare to start negotiations for Brexit, it is important for both sides to comprehend the full extent of the consequences of this process. In this paper, we employ an object oriented simulation framework in order to test for the short-term and long-term effects of Brexit on both sides of the Channel. The relative strength of the UK economy and the banking sector vis-à-vis the EU is taken under consideration. Our results confirm predictions in the relevant literature regarding the output cost of Brexit, with particular emphasis on the EU. Furthermore, we show that financial stability is also an important issue on both sides, with the banking system suffering significant losses, particularly over the longer term. Our findings suggest that policymakers should be extremely careful in handling Brexit negotiations, making sure to consider dynamic effects that may be caused by UK bank assets moving to the EU after Brexit. The model results show that, as the UK banking system loses its assets, the end state of the UK economy is deteriorated while the end state of EU economy is improved.

Keywords: Banking Crises, Brexit, Financial Stability, VBanking

Procedia PDF Downloads 280

Authors: U. Chattaraj, D. Meena

Abstract:

Growth of traffic brings various negative effects, such as road accidents. To avoid such problems, a model is developed for the purpose of highway safety. In such areas, fuzzy logic is the most well-known simulation in the larger field. A model is accomplished for hilly and steep terrain based on Fuzzy Inference System (FIS), for which output is super elevation and input data is horizontal radius, vertical gradient, accident rate (AR). This result shows that the system can be efficaciously applied as for highway safety tool distinguishing hazards components correlated to the characteristics of the highway and has a great influence to the making of decision for accident precaution in transportation models. From this model, a positive relationship between geometric elements, accident rate, and super elevation is also identified.

Keywords: accident rate, fuzzy inference system, fuzzy logic, gradient, radius, super elevation

Procedia PDF Downloads 217

Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

Abstract:

The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

Procedia PDF Downloads 189

Authors: Beulah Rani Inbanathan

Abstract:

In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

Procedia PDF Downloads 87

Authors: Youcef Serhane, Abdelkrim Bouzaza, Dominique Wolbert, Aymen Amin Assadi

Abstract:

Throughout history, the use of chemical weapons is not exclusive to combats between army corps; some of these weapons are also found in very targeted intelligence operations (political assassinations), organized crime, and terrorist organizations. To improve the speed of action, important technological devices have been developed in recent years, in particular in the field of protection and decontamination techniques to better protect and neutralize a chemical threat. In order to assess certain protective, decontaminating technologies or to improve medical countermeasures, tests must be conducted. In view of the great toxicity of toxic chemical agents from (real) wars, simulants can be used, chosen according to the desired application. Here, we present an investigation about using a photocatalytic filtering reactor (PFR) for highly contaminated environments containing diethyl sulfide (DES). This target pollutant is used as a simulant of CWA, namely of Yperite (Mustard Gas). The influence of the inlet concentration (until high concentrations of DES (1200 ppmv, i.e., 5 g/m³ of air) has been studied. Also, the conversion rate was monitored under different relative humidity and different flow rates (respiratory flow - standards: ISO / DIS 8996 and NF EN 14387 + A1). In order to understand the efficacity of pollutant neutralization by PFR, a kinetic model based on the Langmuir–Hinshelwood (L–H) approach and taking into account the mass transfer step was developed. This allows us to determine the adsorption and kinetic degradation constants with no influence of mass transfer. The obtained results confirm that this small configuration of reactor presents an extremely promising way for the use of photocatalysis for treatment to deal with highly contaminated environments containing real chemical warfare agents. Also, they can give birth to an individual protection device (an autonomous cartridge for a gas mask).

Keywords: photocatalysis, photocatalytic filtering reactor, diethylsulfide, chemical warfare agents

Procedia PDF Downloads 105

Authors: Abdar Ali, Rizwan Ullah, Zahid Ullah

Abstract:

This paper focuses on the study of DC-to-DC converters, which are suitable for low-voltage high-power applications. The output voltages generated by renewable energy sources such as photovoltaic arrays and fuel cell stacks are generally low and required to be increased to high voltage levels. Development of DC-to-DC converters, which provide high step-up voltage conversion ratios with high efficiencies and low voltage stresses is one of the main issues in the development of renewable energy systems. A procedure for three converters-conventional DC-to-DC converter, interleaved boost converter, and isolated flyback based converter, is illustrated for a given set of specifications. The selection among the converters for the given application is based on the voltage conversion ratio, efficiency, and voltage stresses.

Keywords: flyback converter, interleaved boost, photovoltaic array, fuel cell, switch stress, voltage conversion ratio, renewable energy

Procedia PDF Downloads 597

Authors: H. A. Jawan

Abstract:

This review describes the models of environmental-related crack propagation of aluminum alloys (7xxx) during the last few decades. Acknowledge on effects of different factors on the susceptibility to SCC permits to propose valuable mechanisms on crack advancement. The reliable mechanism of cracking give a possibility to propose the optimum chemical composition and thermal treatment conditions resulting in microstructure the most suitable for real environmental condition and stress state.

Keywords: microstructure, environmental, propagation, mechanism

Procedia PDF Downloads 418

Authors: Osama Aziz, Hamza Ahmad, Muhibur Rahman

Abstract:

The performance of wireless communication systems has been suggested to be improved by UWB MIMO antenna systems. However, creating a successful UWB MIMO antenna is a difficult undertaking that calls for resolving a number of design issues, including radiation efficiency, size, and frequency range. This study's primary objective is to create a novel, highly effective, small-sized, ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna and investigate its potential applications in body-centric communication. Two radiating elements, shared ground plane, circular stubs, and t-shaped isolation elements are used to achieve the MIMO antenna. Outstanding multiplexing efficiency, significant peak gain across the entire UWB frequency spectrum, extremely low mutual coupling (S21=-16 dB), high diversity gain (DG>9), and low envelop correlation are achieved. The proposed antenna will be one of the promising candidates for body centric communication.

Keywords: UWB communication, UWB MIMO antennas, body-centric communication, diversity gain

Procedia PDF Downloads 75

Authors: T. Sanches, K. Bousson

Abstract:

As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

Procedia PDF Downloads 138

Authors: Abdon Choque-Rivero

Abstract:

The Jacobi system with the Dirichlet boundary condition is considered on a half-line lattice when the coefficients are real valued. The inverse problem of recovery of the coefficients from various data sets containing the so-called transmission eigenvalues is analyzed. The Marchenko method is utilized to solve the corresponding inverse problem.

Keywords: inverse scattering, discrete system, transmission eigenvalues, Marchenko method

Procedia PDF Downloads 144

Authors: Rui Wu

Abstract:

In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

Procedia PDF Downloads 108

Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

Abstract:

The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

Procedia PDF Downloads 324

Authors: Guram Esakia, Giorgi Goguadze

Abstract:

The following paper is written due to overview the concept of R2P, this new dimension in International Relations field. Paper contains the general description of previously mentioned concept, its advantages and disadvantages. We also compare each other R2P and“humanitarian intervention“, trying to make clear division between these two approaches in conflict solution. There is also discussed R2P in real action, successful one in Libya and yet failed in Syria. Essay doesn’t claim to be the part of scientific chain and is based only on personal subjection as well on information gathered from various scholars and UN resolutions.

Keywords: the concept of R2P, humanitarian intervention, Libya, Syria

Procedia PDF Downloads 278

Authors: Guillaume Craveur

Abstract:

This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

Procedia PDF Downloads 303

Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

Abstract:

Different transportation modes have key operational advantages and disadvantages, providing a variety of different transport options to users and passengers. This paper reviews key variables for the competition between air transport and other transport modes. The aim of this paper is to review the competition between air transport and other transport modes, providing results in terms of perceived cost for the users, for destinations high competitiveness for all transport modes. The competitor analysis variables include the cost and time outputs for each transport option, highlighting the level of competitiveness on high demanded Origin-Destination corridors. The case study presents the output of a such analysis for the OD corridor in Greece that connects the Capital city (Athens) with the second largest city (Thessaloniki) and the different transport modes have been considered (air, train, road). Conventional wisdom is to present an easy to handle tool for planners, managers and decision makers towards pricing policy effectiveness and demand attractiveness, appropriate to use for other similar cases.

Keywords: competitor analysis, transport economics, transport generalized cost, quantitative modelling

Procedia PDF Downloads 247

Authors: Sead A. Bakheet, Salah M. Elkoum, Asharaf A. Almaghribi

Abstract:

Disturbance defined as activity that malfunction, intrusion, or interruption. We have to look around for the source of the disturbance affecting the inputs and outputs of engineering projects, take the necessary actions to control them. In this paper we will present and discuss a production system consisting of three elements, inputs, the production process and outputs. The production process which we chose is the production of large diameter pre-stressed concrete cylinder pipes (out puts), in reality, the outputs are the starting points of the operation (laying the concrete pipes for transporting drinkable water). The main objective also to address the controlling methods of the natural resources and raw materials (basic inputs), study the disturbances affecting them as well as the output quality. The importance of making the right decision, which effect the final product quality will be summarized. Finally, we will address the proposals regarding the managing of secure water supply to the customers.

Keywords: disturbances, management, inputs, outputs, decision

Procedia PDF Downloads 62

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

Abstract:

Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

Procedia PDF Downloads 146

Authors: Karolina Wieczorek, Sophie Wiliams

Abstract:

Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

Procedia PDF Downloads 102

Authors: M. P. Nanda Kumar, K. Dheeraj

Abstract:

The design of a feedback controller, so as to minimize a given performance criterion, for a general non-linear dynamical system is difficult; if not impossible. But for a large class of non-linear dynamical systems, the open loop control that minimizes a performance criterion can be obtained using calculus of variations and Pontryagin’s minimum principle. In this paper, the open loop optimal trajectories, that minimizes a given performance measure, is used to train the neural network whose inputs are state variables of non-linear dynamical systems and the open loop optimal control as the desired output. This trained neural network is used as the feedback controller. In other words, attempts are made here to solve the “inverse optimal control problem” by using the state and control trajectories that are optimal in an open loop sense.

Keywords: inverse optimal control, radial basis function, neural network, controller design

Procedia PDF Downloads 554

Authors: A. Camões, M. Ferreira Dias, M. Amorim

Abstract:

In recent years, the social economy is increasingly seen as a viable means to address social problems. Social enterprises, as well as public projects and initiatives targeted to meet social purposes, offer organizational models that assume heterogeneity, flexibility and adaptability to the ‘real world and real problems’. Despite the growing popularity of social initiatives, decision makers still face a paucity in what concerns the available models and tools to adequately assess its sustainability, and its impacts, notably the nature of its contribution to economic growth. This study was carried out at the local level, by analyzing the social impact initiatives and projects promoted by the Municipality of Albergaria-a-Velha (Câmara Municipal de Albergaria-a-Velha -CMA), a municipality of 25,000 inhabitants in the central region of Portugal. This work focuses on the challenges related to the qualifications and employability of citizens, which stands out as one of the key concerns in the Portuguese economy, particularly expressive in the context of small-scale cities and inland territories. The study offers a characterization of the Municipality, its socio-economic structure and challenges, followed by an exploratory analysis of multiple sourced data, collected from the CMA's documental sources as well as from privileged informants. The purpose is to conduct detailed analysis of the CMA's social projects, aimed at characterizing its potential impact for the model of qualifications and employability of the citizens of the Municipality. The study encompasses a discussion of the socio-economic profile of the municipality, notably its asymmetries, the analysis of the social projects and initiatives, as well as of data derived from inquiry actors involved in the implementation of the social projects and its beneficiaries. Finally, the results obtained with the Better Life Index will be included. This study makes it possible to ascertain if what is implicit in the literature goes to the encounter of what one experiences in reality.

Keywords: measurement, municipalities, social economy, social impact

Procedia PDF Downloads 134

Authors: C. von Essen

Abstract:

This study outlines and evaluates a constructivist design approach to the creation of educational video on postgraduate business degree programmes. Many online courses are tapping into the educational affordances of video, as this form of online learning has the potential to create rich, multimodal experiences. And yet, in many learning contexts video is still being used to transmit instruction to passive learners, rather than promote learner engagement and knowledge creation. Constructivism posits the notion that learning is shaped as students make connections between their experiences and ideas. This paper pivots on the following research question: how can we design educational video in ways which promote constructivist learning and stimulate analytic viewing? By exploring and categorizing over two thousand educational videos created since 2014 for over thirty postgraduate courses in business, economics, mathematics and statistics, this paper presents and critically reflects on a taxonomy of video styles and features. It links the pedagogical intent of video – be it concept explanation, skill demonstration, feedback, real-world application of ideas, community creation, or the cultivation of course narrative – to specific presentational characteristics such as visual effects including diagrammatic and real-life graphics and aminations, commentary and sound options, chronological sequencing, interactive elements, and presenter set-up. The findings of this study inform a framework which captures the pedagogical, technological and production considerations instructional designers and educational media specialists should be conscious of when planning and preparing the video. More broadly, the paper demonstrates how learning theory and technology can coalesce to produce informed and pedagogical grounded instructional design choices. This paper reveals how crafting video in a more conscious and critical manner can produce powerful, new educational design.

Keywords: educational video, constructivism, instructional design, business education

Procedia PDF Downloads 236