Search results for: accelerated failure time model

Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

Procedia PDF Downloads 421

Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Mikhail O. Eremin

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Seismic activity around the world is clearly a threat to people's lives, as well as infrastructure and capital construction. It is the instability of the latter to powerful earthquakes that most often causes human casualties. Therefore, during construction it is necessary to take into account the risks of large-scale natural disasters. The task of assessing the risks of natural disasters is one of the most urgent at the present time. The final goal of any study of earthquakes is forecasting. This is especially important for seismically active regions of the planet where earthquakes occur frequently. Gorni Altai is one of such regions. In work, we developed the physical-mathematical model of stress-strain state evolution of loaded geomedium with the purpose of numerical simulation of seismic process accompanying the formation of Chuya-Kuray fault zone Gorni Altay, Russia. We build a structural model on the base of seismotectonic and paleoseismogeological investigations, as well as SRTM-data. Base of mathematical model is the system of equations of solid mechanics which includes the fundamental conservation laws and constitutive equations for elastic (Hooke's law) and inelastic deformation (modified model of Drucker-Prager-Nikolaevskii). An initial stress state of the model correspond to gravitational. Then we simulate an activation of a buried dextral strike-slip paleo-fault located in the basement of the model. We obtain the stages of formation and the structure of Chuya-Kuray fault zone. It is shown that results of numerical simulation are in good agreement with field observations in statistical sense. Simulated seismic process is strongly bound to the faults - lineaments with high degree of inelastic strain localization. Fault zone represents en-echelon system of dextral strike-slips according to the Riedel model. The system of surface lineaments is represented with R-, R'-shear bands, X- and Y-shears, T-fractures. Simulated seismic process obeys the laws of Gutenberg-Richter and Omori. Thus, the model describes a self-similar character of deformation and fracture of rocks and geomedia. We also modified the algorithm of determination of separate slip events in the model due to the features of strain rates dependence vs time.

Keywords: Drucker-Prager model, fault zone, numerical simulation, Riedel bands, seismic process, strike-slip fault

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Authors: Willy Mbenza, Sho Kenjiro

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Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

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Authors: Shah Md. Imran Kabir, Md. Mostafa Ali

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Karnafuli is one of the most important rivers of Bangladesh which is playing a vital role in our national economy. The major sea port of Bangladesh is the Chittagong port located on the right bank of Karnafuli River Bangladesh. Karnafuli river port is considered as the lifeline of the economic activities of the country. Therefore, it is always necessary to keep the river active and live in terms of its navigability. Due to man-made intervention, the river flow becomes interrupted and thereby may cause the change in the river morphology. The specific objective of this study is the application of 2D model to assess different hydrodynamic and morphological characteristics of the river due to normal flow condition and sea level rise condition. The model has been set with the recent bathymetry data collected from CPA hydrography division. For model setup, the river reach is selected between Kalurghat and Khal no-18. Time series discharge and water level data are used as boundary condition at upstream and downstream. Calibration and validation have been carried out with the recent water level data at Khal no-10 and Sadarghat. The total reach length of the river has been divided into four parts to determine different hydrodynamic and morphological assessments like variation of velocity, sediment erosion and deposition and bed level changes also have been studied. This model has been used for the assessment of river response due sediment transport and sea level rise. Model result shows slight increase in velocity. It also changes the rate of erosion and deposition at some location of the selected reach. It is hoped that the result of the model simulation will be helpful to suggest the effect of possible future development work to be implemented on this river.

Keywords: CCHE 2D, hydrodynamic, morphology, sea level rise

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Authors: Rafal Maciag

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Due to the development of the current civilization, one must create suitable models of its pervasive massive phenomena. Such a phenomenon is the digital transformation, which has a substantial number of disciplined, methodical interpretations forming the diversified reflection. This reflection could be understood pragmatically as the current temporal, a local differential state of knowledge. The model of the discursive space is proposed as a model for the analysis and description of this knowledge. Discursive space is understood as an autonomous multidimensional space where separate discourses traverse specific trajectories of what can be presented in multidimensional parallel coordinate system. Discursive space built on the world of facts preserves the complex character of that world. Digital transformation as a discursive space has a relativistic character that means that at the same time, it is created by the dynamic discourses and these discourses are molded by the shape of this space.

Keywords: complexity, digital transformation, discourse, discursive space, knowledge

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Authors: Hsin-Yun Lee

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In this study, the pedestrian simulation VISWALK integration and application platform ant algorithms written program made to construct a renovation engineering schedule planning mode. The use of simulation analysis platform construction site when the user running the simulation, after calculating the user walks in the case of construction delays, the ant algorithm to find out the minimum delay time schedule plan, and add volume and unit area deactivated loss of business computing, and finally to the owners and users of two different positions cut considerations pick out the best schedule planning. To assess and validate its effectiveness, this study constructed the model imported floor of a shopping mall floor renovation engineering cases. Verify that the case can be found from the mode of the proposed project schedule planning program can effectively reduce the delay time and the user's walking mall loss of business, the impact of the operation on the renovation engineering facilities in the building to a minimum.

Keywords: pedestrian, renovation, schedule, simulation

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Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

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Authors: A. Bouhaloufa, T. Kadri, S. Zouaoui, A. Belhacene

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To put more durable bridges, it is important to maintain existing structures, rather than investing in new structures. Instead of demolishing the old bridge and replace them with new, we must preserve and upgrade using better methods of diagnosis, auscultation and repair, the interest of this work is to increase the bearing capacity bridges damaged by additional prestressing, this type of reinforcement is growing continuously. In addition to excellent static strength, prestressing also has a very high resistance to fatigue, so it is suitable to solve the problem of failure of the bearing capacity of the bridges. This failure often comes to the development of overloads in quantity and quality, that is our daily traffic has increased and become very complicated, on the other hand its constituents are advanced in weight and speed and therefore almost all old bridges became unable to support the movement of the latter and remain disabled to all these problems. The main purpose of this work includes the following three aspects: - Determination of the main diseases and factors affecting the deterioration of bridges in Algeria, - Evaluation of the bearing capacity of bridges, - Proposal technical reinforcement to improve the bearing capacity of a degraded structure.

Keywords: bridges, repair, auscultation, diagnosis, pathology, additional prestressing

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Authors: Mojtaba Noghabaei, Khashayar Asadi, Kevin Han

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Simultaneous Localization and Mapping (SLAM) technology has recently attracted the attention of construction companies for real-time performance monitoring. To effectively use SLAM for construction performance monitoring, SLAM results should be registered to a Building Information Models (BIM). Registring SLAM and BIM can provide essential insights for construction managers to identify construction deficiencies in real-time and ultimately reduce rework. Also, registering SLAM to BIM in real-time can boost the accuracy of SLAM since SLAM can use features from both images and 3d models. However, registering SLAM with the BIM in real-time is a challenge. In this study, a novel SLAM platform named Model-Based SLAM (MB-SLAM) is proposed, which not only provides automated registration of SLAM and BIM but also improves the localization accuracy of the SLAM system in real-time. This framework improves the accuracy of SLAM by aligning perspective features such as depth, vanishing points, and vanishing lines from the BIM to the SLAM system. This framework extracts depth features from a monocular camera’s image and improves the localization accuracy of the SLAM system through a real-time iterative process. Initially, SLAM can be used to calculate a rough camera pose for each keyframe. In the next step, each SLAM video sequence keyframe is registered to the BIM in real-time by aligning the keyframe’s perspective with the equivalent BIM view. The alignment method is based on perspective detection that estimates vanishing lines and points by detecting straight edges on images. This process will generate the associated BIM views from the keyframes' views. The calculated poses are later improved during a real-time gradient descent-based iteration method. Two case studies were presented to validate MB-SLAM. The validation process demonstrated promising results and accurately registered SLAM to BIM and significantly improved the SLAM’s localization accuracy. Besides, MB-SLAM achieved real-time performance in both indoor and outdoor environments. The proposed method can fully automate past studies and generate as-built models that are aligned with BIM. The main contribution of this study is a SLAM framework for both research and commercial usage, which aims to monitor construction progress and performance in a unified framework. Through this platform, users can improve the accuracy of the SLAM by providing a rough 3D model of the environment. MB-SLAM further boosts the application to practical usage of the SLAM.

Keywords: perspective alignment, progress monitoring, slam, stereo matching.

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Authors: Zohreh Soltani, Seyedmohammadhossein Hosseinian

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Reduction of energy consumption in built infrastructure, through the installation of energy-efficient technologies, is a major approach to achieving sustainability. In practice, the viability of energy efficiency projects strongly depends on the cost reimbursement and profitability. These projects are subject to failure if the actual cost savings do not reimburse the project cost in a timely manner. In such cases, refinancing could be a solution to benefit from the long-term returns of the project if implemented wisely. However, very little is still known about the effect of refinancing options on financial performance of energy efficiency projects. To fill this gap, the present study investigates the financial behavior of energy efficiency projects with focus on refinancing options, such as Leveraged Loans. A System Dynamics (SD) model is introduced, and the model application is presented using an actual case-study data. The case study results indicate that while high-interest start-ups make using Leveraged Loan inevitable, refinancing can rescue the project and bring about profitability. This paper also presents some managerial implications of refinancing energy efficiency projects based on the case-study analysis. Results of this study help implementing financially viable energy efficiency projects, so the community could benefit from their environmental advantages widely.

Keywords: energy efficiency projects, leveraged loan, refinancing, sustainability

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Authors: S. Ajith Kumar, Vaisakh S. Rajan

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In external flows, vortex shedding behind the bluff bodies causes to experience unsteady loads on a large number of engineering structures, resulting in structural failure. Vortex shedding can even turn out to be disastrous like the Tacoma Bridge failure incident. We need to have control over vortex shedding to get rid of this untoward condition by reducing the unsteady forces acting on the bluff body. In circular cylinders, hydrophobic surface in an otherwise no-slip surface is found to be delaying separation and minimizes the effects of vortex shedding drastically. Flow over square cylinder stands different from this behavior as separation can takes place from either of the two corner separation points (front or rear). An attempt is made in this study to numerically elucidate the effect of hydrophobic surface in flow over a square cylinder. A 2D numerical simulation has been done to understand the effects of the slip surface on the flow past square cylinder. The details of the numerical algorithm will be presented at the time of the conference. A non-dimensional parameter, Knudsen number is defined to quantify the slip on the cylinder surface based on Maxwell’s equation. The slip surface condition of the wall affects the vorticity distribution around the cylinder and the flow separation. In the numerical analysis, we observed that the hydrophobic surface enhances the shedding frequency and damps down the amplitude of oscillations of the square cylinder. We also found that the slip has a negative effect on aerodynamic force coefficients such as the coefficient of lift (CL), coefficient of drag (CD) etc. and hence replacing the no slip surface by a hydrophobic surface can be treated as an effective drag reduction strategy and the introduction of hydrophobic surface could be utilized for reducing the vortex induced vibrations (VIV) and is found as an effective method in controlling VIV thereby controlling the structural failures.

Keywords: drag reduction, flow past square cylinder, flow control, hydrophobic surfaces, vortex shedding

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Authors: Justin Zhengjie Tan, Yang Zhao

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Adiabatic Rapid Passage, a popular method of achieving population inversion, is studied in a Rabi dimer model in the presence of noise which acts as a dissipative environment. The integration of the multi-Davydov D2 Ansatz into the time-dependent variational framework enables us to model the intricate quantum system accurately. By influencing the system with a driving field strength resonant with the energy spacing, the probability of adiabatic rapid passage, which is modelled after the Landau Zener model, can be derived along with several other observables, such as the photon population. The effects of a dissipative environment can be reproduced by coupling the system to a common phonon mode. By manipulating the strength and frequency of the driving field, along with the coupling strength of the phonon mode to the qubits, we are able to control the qubits and photon dynamics and subsequently increase the probability of Adiabatic Rapid Passage happening.

Keywords: quantum electrodynamics, adiabatic rapid passage, Landau-Zener transitions, dissipative environment

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Authors: E. D. Paul, O. F. Paul, J. E. Toryila, A. J. Salifu, C. E. Gimba

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Adsorption of Cd2+ ions from aqueous solution by Chitosan, a natural polymer, obtained from a mixture of the exoskeletons of Littorina littorea (Periwinkle) and Achatinoidea (Snail) was studied at varying adsorbent dose, contact time, metal ion concentrations, temperature and pH using batch adsorption method. The equilibrium adsorption isotherms were determined between 298 K and 345 K. The adsorption data were adjusted to Langmuir, Freundlich and the pseudo second order kinetic models. It was found that the Langmuir isotherm model most fitted the experimental data, with a maximum monolayer adsorption of 35.1 mgkg⁻¹ at 308 K. The entropy and enthalpy of adsorption were -0.1121 kJmol⁻¹K⁻¹ and -11.43 kJmol⁻¹ respectively. The Freundlich adsorption model, gave Kf and n values consistent with good adsorption. The pseudo-second order reaction model gave a straight line plot with rate constant of 1.291x 10⁻³ kgmg⁻¹ min⁻¹. The qe value was 21.98 mgkg⁻¹, indicating that the adsorption of Cadmium ion by the chitosan composite followed the pseudo-second order kinetic model.

Keywords: adsorption, chitosan, littorina littorea, achatinoidea, natural polymer

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Authors: Sahar Shahsavaripour Ghazanfarpour

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As our daily life depends on quality of built services by systems and using devices in our environment; so education and model of software′s quality will be so important. By daily growth in software′s systems and using them so much, progressing process and requirements′ evaluation in primary level of progress especially architecture level in software get more important. Modern driver architecture changes an in dependent model of a level into some specific models that their purpose is reducing number of software changes into an executive model. Process of designing software engineering is mid-automated. The needed quality attribute in designing architecture and quality attribute in representation are in architecture models. The main problem is the relationship between needs, and elements in some aspect with implicit models and input sources in process. It’s because there is no detection ability. The MART profile is use to describe real-time properties and perform plat form modeling.

Keywords: MDA, DW, OMG, UML, AKB, software architecture, ontology, evaluation

Procedia PDF Downloads 475

Authors: Salman Hussam

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As a monitoring system to manage employees' time and employers' business, this system (logger) will monitor the employees at work and will announce them if they spend too much time on social media (even if they are using proxy it will catch them). In this way, people will spend less time at work and more time with family.

Keywords: clients, employees, employers, family, monitoring, systems, social media, time

Procedia PDF Downloads 475

Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Fadwa Jewilli

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A sudden leak of a 6-inch gas line pipe after being in service for one year was observed. The pipe had been designed to transport dry gas. The failure had taken place in 6 o’clock position at the stage discharge of the flow process. Laboratory investigations were conducted to find out the cause of the pipe rupture. Visual and metallographic observations confirmed that the pipe split was due to a crack initiated in circumferential and then turned into longitudinal direction. Sever wall thickness reduction was noticed on the internal pipe surface. Scanning electron microscopy observations at the fracture surface revealed features of ductile fracture mode. Corrosion product analysis showed the traces of iron carbonate and iron sulphate. The laboratory analysis resulted in the conclusion that the pipe failed due to the effect of wet fluid (condensate) caused severe wall thickness dissolution resulted in pipe could not stand the continuation at in-service working condition.

Keywords: gas line pipe, corrosion prediction ductile fracture, ductile fracture, failure analysis

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Iacopo Carnacina, Mohammad Keshtpoor, Richard Yablonsky

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Non-structural protection measures against flooding are becoming increasingly popular flood risk mitigation strategies. In particular, coastal flood insurance impacts not only private citizens but also insurance and reinsurance companies, who may require it to retain solvency and better understand the risks they face from a catastrophic coastal flood event. In this context, a framework is presented here to assess the risk for coastal flooding across the UK. The area has a long history of catastrophic flood events, including the Great Flood of 1953 and the 2013 Cyclone Xaver storm, both of which led to significant loss of life and property. The current framework will leverage a technology based on a hydrodynamic model (Delft3D Flexible Mesh). This flexible mesh technology, coupled with a calibration technique, allows for better utilisation of computational resources, leading to higher resolution and more detailed results. The generation of a stochastic set of extra tropical cyclone (ETC) events supports the evaluation of the financial losses for the whole area, also accounting for correlations between different locations in different scenarios. Finally, the solution shows a detailed analysis for the Thames River, leveraging the information available on flood barriers and levees. Two realistic disaster scenarios for the Greater London area are simulated: In the first scenario, the storm surge intensity is not high enough to fail London’s flood defences, but in the second scenario, London’s flood defences fail, highlighting the potential losses from a catastrophic coastal flood event.

Keywords: storm surge, stochastic model, levee failure, Thames River

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Authors: Victor Birikorang Danquah

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Ghana's primary energy supply is heavily reliant on petroleum, biomass, and hydropower. Currently, Ghana gets its energy from hydropower (Akosombo and Bui), thermal power plants powered by crude oil, natural gas, and diesel, solar power, and imports from La Cote d'Ivoire. Until the early 2000s, large hydroelectric dams dominated Ghana's electricity generation. Due to unreliable weather patterns, Ghana increased its reliance on thermal power. However, thermal power contributes the highest percentage in terms of electricity generation in Ghana and is predominantly supplied by Independent Power Producers (IPPs). Ghana's electricity industry operates the corporate utility model as its business model. This model is typically' vertically integrated,' with a single corporation selling the majority of power generated by its generation assets to its retail business, which then sells the electricity to retail market consumers. The corporate utility model has a straightforward value proposition that is based on increasing the number of energy units sold. The unit volume business model drives the entire energy value chain to increase throughput, locking system users into unsustainable practices. This report uses the qualitative research approach to explore the electricity industry in Ghana. There is a need for increasing renewable energy, such as wind and solar, in electricity generation. The research recommends two critical business models for the penetration of renewable energy in Ghana's power sector. The first model is the peer-to-peer electricity trading model, which relies on a software platform to connect consumers and generators in order for them to trade energy directly with one another. The second model is about encouraging local energy generation, incentivizing optimal time-of-use behaviour, and allowing any financial gains to be shared among the community members.

Keywords: business model innovation, electricity generation, renewable energy, solar energy, sustainability, wind energy

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges faced by MLDB system at the piston foundry plant due to interruption in supply of water. For the MLDB system to work in Model, two sub-units must be connected to the robotic main unit. The system cannot function without robotics and water supply by the fan (WSF). Insufficient water supply is the cause of system failure. The system operates at top performance using two sub-units. If one sub-unit fails, the system capacity is reduced. Priority of repair is given to the main unit i.e. Robotic and WSF. To solve the problem, semi-Markov process and regenerative point technique are used. Relevant graphs are also included to particular case.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: M. Paraipan, V. M. Javadova, S. I. Tyutyunnikov

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The concept of energy amplifier or accelerator driven system (ADS) involves the use of a particle accelerator coupled with a nuclear reactor. The accelerated particle beam generates a supplementary source of neutrons, which allows the subcritical functioning of the reactor, and consequently a safe exploitation. The harder neutron spectrum realized ensures a better incineration of the actinides. The almost generalized opinion is that the optimal beam for ADS is represented by protons with energy around 1 GeV (gigaelectronvolt). In the present work, a systematic analysis of the energy gain for proton beams with energy from 0.5 to 3 GeV and ion beams from deuteron to neon with energies between 0.25 and 2 AGeV is performed. The target is an assembly of metallic U-Pu-Zr fuel rods in a bath of lead-bismuth eutectic coolant. The rods length is 150 cm. A beryllium converter with length 110 cm is used in order to maximize the energy released in the target. The case of a linear accelerator is considered, with a beam intensity of 1.25‧10¹⁶ p/s, and a total accelerator efficiency of 0.18 for proton beam. These values are planned to be achieved in the European Spallation Source project. The energy gain G is calculated as the ratio between the energy released in the target to the energy spent to accelerate the beam. The energy released is obtained through simulation with the code Geant4. The energy spent is calculating by scaling from the data about the accelerator efficiency for the reference particle (proton). The analysis concerns the G values, the net power produce, the accelerator length, and the period between refueling. The optimal energy for proton is 1.5 GeV. At this energy, G reaches a plateau around a value of 8 and a net power production of 120 MW (megawatt). Starting with alpha, ion beams have a higher G than 1.5 GeV protons. A beam of 0.25 AGeV(gigaelectronvolt per nucleon) ⁷Li realizes the same net power production as 1.5 GeV protons, has a G of 15, and needs an accelerator length 2.6 times lower than for protons, representing the best solution for ADS. Beams of ¹⁶O or ²⁰Ne with energy 0.75 AGeV, accelerated in an accelerator with the same length as 1.5 GeV protons produce approximately 900 MW net power, with a gain of 23-25. The study of the evolution of the isotopes composition during irradiation shows that the increase in power production diminishes the period between refueling. For a net power produced of 120 MW, the target can be irradiated approximately 5000 days without refueling, but only 600 days when the net power reaches 1 GW (gigawatt).

Keywords: accelerator driven system, ion beam, electrical power, energy gain

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Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

Abstract:

Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Aly Elshafei, Daniela Romano

Abstract:

With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: Issam Jebreen, Eman Al-Qbelat

Abstract:

Outsourcing software development projects can be challenging, and there are several common challenges that organizations face. A study was conducted with a sample of 46 papers on outsourcing challenges, and the results show that there are several common challenges faced by organizations when outsourcing software development projects. Poor outsourcing relationship was identified as the most significant challenge, with 35% of the papers referencing it. Lack of quality was the second most significant challenge, with 33% of the papers referencing it. Language and cultural differences were the third most significant challenge, with 24% of the papers referencing it. Non-competitive price was another challenge faced by organizations, with 21% of the papers referencing it. Poor coordination and communication were also identified as a challenge, with 21% of the papers referencing it. Opportunistic behavior, lack of contract negotiation, inadequate user involvement, and constraints due to time zone were also challenges faced by organizations. Other challenges faced by organizations included poor project management, lack of technical capabilities, vendor employee high turnover, poor requirement specification, IPR issues, poor management of budget, schedule, and delay, geopolitical and country instability, the difference in development methodologies, failure to manage end-user expectations, and poor monitoring and control. In conclusion, outsourcing software development projects can be challenging, but organizations can mitigate these challenges by selecting the right outsourcing partner, having a well-defined contract and clear communication, having a clear understanding of the requirements, and implementing effective project management practices.

Keywords: software outsourcing, vendor, outsourcing challenges, quality model, continent, country, global outsourcing, IT workforce outsourcing.

Procedia PDF Downloads 72