Search results for: branch and bound algorithm.

Authors: Ramadan Fayez Zowaid Hussein

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Exploration geophysics is an applied branch of geophysics, and it is very important to use such a method in Egypt and not just Egypt but in Africa and the Middle East. This research aims to work deeply on the importance of this method, and this paper focuses more on the benefits of the exploration of geophysics and how to apply it to scientific methods. It helps to discover earthquakes and assist in seismology. It also helps to map the surface structure of a region and also magnetic techniques, including aeromagnetic surveys to map magnetic anomalies. This is known that having a great experience in this field as it was very interesting reading a lot and searching about this matter and this technology, and all was found made this fantastic: as the method is existing and we do not use it. It costs a lot, but one believes that this method is very important; for example, in discovering earthquakes, check the surface of the ground easily; it makes us see the surface of the ground clearly so we can find the elements of the earth easily. In conclusion, geophysical exploration use is very important, and it must be highlighted and considered to be discussed in the Middle East, not just in the Middle East but also in Africa.

Keywords: geophysics, magnetic, gravitational, hydrocarbon exploration

Procedia PDF Downloads 89

Authors: Iran Kalbasi, Foroozandeh Zardashti

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Dialectology is a branch of social linguistics that studies systematic language variations. Dialects are the branches of a unique language that have structural, morphological and phonetic differences with each other. In Iran, these dialects and language variations themselves have a lot of cultural loads, and studying them have linguistic and cultural importance. In this study, phonetic structure of two Iranian dialects, Bakhtiyari Lori of Masjedsoleyman and Shushtari in Khuzestan Province of Iran have been surveyed. Its statistical community includes twenty speakers of two dialects. The theoretic bases of this research is based on structuralism. Its data have been collected by interviewing the questionnaire that consist of 3000 words, 410 sentences and 110 complex and simple verbs. These datas are analysed and described synchronically. Then, the phonetic characteristics of these two dialects and standard Persian have been compared. Therefore, we can say that in phonetic level of these two dialects and standard Persian, there are clearly differences.

Keywords: standard language, dialectology, bakhtiyari lori dialect of Masjedsoleyman, Shushtari dialect, vowel, consonant

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Authors: Santhosh Srinivasan, Vipul Garhiya, Shahul Hamid Khan

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Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Single objective mathematical models for a total cost for the entire forward supply chain and reverse chain are considered. Here five different problems are considered by varying the number of facilities for illustration. M-MOGA, Shuffle Frog Leaping algorithm (SFLA) and CPLEX are used for finding the optimal solution for the mathematical model.

Keywords: closed loop supply chain, genetic algorithm, random search, multi period, green supply chain

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Authors: Jan Busch, Maurice Schmidt, Peter Nyhuis

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The change of conditions for production companies in high-wage countries is characterized by the globalization of competition and the transition of a supplier´s to a buyer´s market. The companies need to face the challenges of reacting flexibly to these changes. Due to the significant and increasing degree of automation, assembly has become the most expensive production process. Regarding the reduction of production cost, assembly consequently offers a considerable rationalizing potential. Therefore, an aerodynamic feeding system has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. In former research activities, this system has been enabled to adjust itself using genetic algorithm. The longer the genetic algorithm is executed the better is the feeding quality. In this paper, the relation between the system´s setting time and the feeding quality is observed and a function which enables the user to achieve the minimum of the total feeding time is presented.

Keywords: aerodynamic feeding system, batch size, optimisation, setting time

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Authors: Mohsen Ziaee

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Almost all existing researches on the flowshop scheduling problems focus on the permutation schedules and there is insufficient study dedicated to the general flowshop scheduling problems in the literature, since the modeling and solving of the general flowshop scheduling problems are more difficult than the permutation ones, especially for the large-size problem instances. This paper considers the general flowshop scheduling problem with the objective function of the makespan (F//Cmax). We first find the optimal solution of the problem by solving a mixed integer linear programming model. An efficient heuristic method is then presented to solve the problem. An ant colony optimization algorithm is also proposed for the problem. In order to evaluate the performance of the methods, computational experiments are designed and performed. Numerical results show that the heuristic algorithm can result in reasonable solutions with low computational effort and even achieve optimal solutions in some cases.

Keywords: scheduling, general flow shop scheduling problem, makespan, heuristic

Procedia PDF Downloads 207

Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

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This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

Procedia PDF Downloads 330

Authors: Pocholo Rodriguez, Anne Bernadine Ocampo, Ian Benedict Chan, Janric Micah Gray

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The state of an electric power system may be classified as either stable or unstable. The borderline of stability is at any condition for which a slight change in an unfavourable direction of any pertinent quantity will cause instability. Voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. The researchers will present an intelligent system using back propagation algorithm that can detect voltage instability and output voltage of a power distribution and classify it as stable or unstable. The researchers’ work is the use of parameters involved in voltage instability as input parameters to the neural network for training and testing purposes that can provide faster detection and monitoring of the power distribution system.

Keywords: back-propagation algorithm, load instability, neural network, power distribution system

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Authors: Christoph Ramsauer, Jaydeep Karandikar, Tony Schmitz, Friedrich Bleicher

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Machining stability is an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the Vienna University of Technology, Vienna, Austria. The recorded data from a milling test cut is used to classify the cut as stable or unstable based on the frequency analysis. The test cut result is fed to a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculates the probability of stability as a function of axial depth of cut and spindle speed and recommends the parameters for the next test cut. The iterative process between two transatlantic locations repeats until convergence to a stable optimal process parameter set is achieved.

Keywords: machining stability, machine learning, sensor, optimization

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Authors: Karolina Wieczorek, Sophie Wiliams

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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

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Authors: Stefania Fortino, Petr Hradil, Timo Avikainen

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Timber bridges have an excellent environmental performance, are economical, relatively easy to build and can have a long service life. However, the durability of these bridges is the main problem because of their exposure to outdoor climate conditions. The moisture content accumulated in wood for long periods, in combination with certain temperatures, may cause conditions suitable for timber decay. In addition, moisture content variations affect the structural integrity, serviceability and loading capacity of timber bridges. Therefore, the monitoring of the moisture content in wood is important for the durability of the material but also for the whole superstructure. The measurements obtained by the usual sensor-based techniques provide hygro-thermal data only in specific locations of the wood components. In this context, the monitoring can be assisted by numerical modelling to get more information on the hygro-thermal response of the bridges. This work presents a hygro-thermal model based on a multi-phase moisture transport theory to predict the distribution of moisture content, relative humidity and temperature in wood. Below the fibre saturation point, the multi-phase theory simulates three phenomena in cellular wood during moisture transfer, i.e., the diffusion of water vapour in the pores, the sorption of bound water and the diffusion of bound water in the cell walls. In the multi-phase model, the two water phases are separated, and the coupling between them is defined through a sorption rate. Furthermore, an average between the temperature-dependent adsorption and desorption isotherms is used. In previous works by some of the authors, this approach was found very suitable to study the moisture transport in uncoated and coated stress-laminated timber decks. Compared to previous works, the hygro-thermal fluxes on the external surfaces include the influence of the absorbed solar radiation during the time and consequently, the temperatures on the surfaces exposed to the sun are higher. This affects the whole hygro-thermal response of the timber component. The multi-phase model, implemented in a user subroutine of Abaqus FEM code, provides the distribution of the moisture content, the temperature and the relative humidity in a volume of the timber deck. As a case study, the hygro-thermal data in wood are collected from the ongoing monitoring of the stress-laminated timber deck of Tapiola Bridge in Finland, based on integrated humidity-temperature sensors and the numerical results are found in good agreement with the measurements. The proposed model, used to assist the monitoring, can contribute to reducing the maintenance costs of bridges, as well as the cost of instrumentation, and increase safety.

Keywords: moisture content, multi-phase models, solar radiation, timber decks, FEM

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Authors: Hae-Yeoun Lee

Abstract:

Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring,which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.

Keywords: cardiac MRI, graph searching, left ventricle segmentation, K-means clustering

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Authors: Hartani Kada, Merah Abdelkader

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Aiming at the high nonlinearities and unmatched uncertainties of the intelligent electric vehicles’ dynamic system, this paper presents a lateral motion control algorithm for intelligent electric vehicles with four in-wheel motors. A fuzzy logic procedure is presented and formulated to realize lateral control in lane change. The vehicle dynamics model and a desired target tracking model were established in this paper. A fuzzy logic controller was designed for integrated active front steering (AFS) and direct yaw moment control (DYC) in order to improve vehicle handling performance and stability, and a fuzzy controller for the automatic steering problem. The simulation results demonstrate the strong robustness and excellent tracking performance of the control algorithm that is proposed.

Keywords: fuzzy logic, lateral control, AFS, DYC, electric car technology, longitudinal control, lateral motion

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Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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Authors: Quy Dang Nguyen, Reza Nakhaie Jazar

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The paper investigates vibration dynamics of tire-road separation for a quarter-car model; this separation model is developed to be close to the real situation considering the tire is able to separate from the ground plane. A set of piecewise linear mathematical models is developed and matches the in-contact and no-contact states to be considered as mother models for further investigations. The bound dynamics are numerically simulated in the time response and phase portraits. The separation analysis may determine which values of suspension parameters can delay and avoid the no-contact phenomenon, which results in improving ride comfort and eliminating the potentially dangerous oscillation. Finally, model verification is carried out in the MSC-ADAMS environment.

Keywords: quarter-car vibrations, tire-road separation, separation analysis, separation dynamics, ride comfort, ADAMS validation

Procedia PDF Downloads 93

Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

Procedia PDF Downloads 598

Authors: Totok R. Biyanto, Arif T. Mardianto, M. Farid R. R., Luthfi Machmudi, kandi mulakasti

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The main objective of this research is optimizing the electrocoagulation process design as a post-treatment for biologically vinasse effluent process. The first principle model with three independent variables that affect the energy consumption of electrocoagulation process i.e. current density, electrode distance, and time of treatment process are chosen as optimized variables. The process condition parameters were determined with the value of pH, electrical conductivity, and temperature of vinasse about 6.5, 28.5 mS/cm, 52 oC, respectively. Aluminum was chosen as the electrode material of electrocoagulation process. Duelist algorithm was used as optimization technique due to its capability to reach a global optimum. The optimization results show that the optimal process can be reached in the conditions of current density of 2.9976 A/m2, electrode distance of 1.5 cm and electrolysis time of 119 min. The optimized energy consumption during process is 34.02 Wh.

Keywords: optimization, vinasse effluent, electrocoagulation, energy consumption

Procedia PDF Downloads 470

Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

Procedia PDF Downloads 113

Authors: Mikhail O. Eremin

Abstract:

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: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

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Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud Ccomputing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 479

Authors: Junling Li, Fang Meng, Yichun Zhang

Abstract:

Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

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Authors: S. Yunus, A. Suratman, N. Mohamad Nor, M. Othman

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This paper presents the measurement and simulation results by Finite Element Method (FEM) for earth resistance (R_DC) for interconnected vertical ground rod configurations. The soil resistivity was measured using the Wenner four-pin Method, and R_DC was measured using the Fall of Potential (FOP) method, as outlined in the standard. Genetic Algorithm (GA) is employed to interpret the soil resistivity to that of a 2-layer soil model. The same soil resistivity data that were obtained by Wenner four-pin method were used in FEM for simulation. This paper compares the results of R_DC obtained by FEM simulation with the real measurement at field site. A good agreement was seen for R_DC obtained by measurements and FEM. This shows that FEM is a reliable software to be used for design of earthing systems. It is also found that the parallel rod system has a better performance compared to a similar setup using a grid layout.

Keywords: earthing system, earth electrodes, finite element method, genetic algorithm, earth resistances

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Authors: Oumaima Ben Abderrahim, Mohamed Houcine Elhedhili, Leila Saidane

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In this paper, we propose a trust management system based on clustering architecture for the social internet of things called TMBCO-SIOT. The proposed model integrates numerous factors such as direct and indirect trust; transaction factor; precaution factor; and social modeling of trust. The novelty of our approach can be summed up in two aspects. The first aspect concerns the architecture based on the community of interest (CoT) where each community is headed by an administrator (admin). However, the second aspect is the trust management system that tries to prevent On-Off attacks and mitigates dishonest recommendations using the k-means algorithm and guarantor things. The effectiveness of the proposed system is proved by simulation against malicious nodes.

Keywords: IoT, trust management system, attacks, trust, dishonest recommendations, K-means algorithm

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Authors: Sven Krabbenhoft, Kristian Krabbenhoft, Lars Damkilde

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The problem of determining the bearing capacity of a strip foundation located near a slope of infinite height has been dealt with by several authors. Very often in practical problems the slope is of limited height, and furthermore the resulting load may be inclined at an angle to the horizontal, and in such cases the bearing capacity of the footing cannot be found using the existing methods. The present work comprises finite element based upper- and lower-bound calculations, using the geotechnical software OptumG2 to investigate the effect of the slope height and horizontal forces on the total bearing capacity, both without and with using superposition as presupposed in the traditional bearing capacity equation. The results for friction angles 30, 35 and 40 degrees, slope inclinations 1:2, 1:3 and 1:4, for selfweight and surcharge are given as charts showing the slope inclination factors suitable for design.

Keywords: footings, bearing capacity, slopes, cohesionnless soil

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Authors: Taehan Bae

Abstract:

In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

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Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

Abstract:

Operations, maintenance and reliability of wind turbines have received much attention over the years due to rapid expansion of wind farms. This paper explores early fault diagnosis scale technique based on a unique scheme of a 5MW wind turbine system that is optimized by genetic algorithm to be very sensitive to faults and resilient to disturbances. A quantitative model based analysis is pragmatic for primary fault diagnosis monitoring assessment to minimize downtime mostly caused by components breakdown and exploit productivity consistency. Simulation results are computed validating the wind turbine model which demonstrates system performance in a practical application of fault type examples. The results show the satisfactory effectiveness of the applied performance investigated in a Matlab/Simulink/Gatool environment.

Keywords: disturbance robustness, fault monitoring and detection, genetic algorithm, observer technique

Procedia PDF Downloads 381

Authors: Zs. Csanádi, A. Szabó Nagy, J. Szabó, J. Erdős

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The main objective of this study was to assess the annual concentration and seasonal variation of benzo(a)pyrene (BaP) associated with PM10 in an urban site of Győr and in a rural site of Sarród in the sampling period of 2008–2012. A total of 280 PM10 aerosol samples were collected in each sampling site and analyzed for BaP by gas chromatography method. The BaP concentrations ranged from undetected to 8 ng/m3 with the mean value of 1.01 ng/m3 in the sampling site of Győr, and from undetected to 4.07 ng/m3 with the mean value of 0.52 ng/m3 in the sampling site of Sarród, respectively. Relatively higher concentrations of BaP were detected in samples collected in both sampling sites in the heating seasons compared with non-heating periods. The annual mean BaP concentrations were comparable with the published data of different other Hungarian sites.

Keywords: air quality, benzo(a)pyrene, PAHs, polycyclic aromatic hydrocarbons

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Authors: Weigao. Wu, Stefano. Utili

Abstract:

Based on the kinematic approach of limit analysis, a full set of upper bound solutions for the stability of homogeneous rock slopes subjected to tension cracks are obtained. The generalized Hoek-Brown failure criterion is employed to describe the non-linear strength envelope of rocks. In this paper, critical failure mechanisms are determined for cracks of known depth but unspecified location, cracks of known location but unknown depth, and cracks of unspecified location and depth. It is shown that there is a nearly up to 50% drop in terms of the stability factors for the rock slopes intersected by a tension crack compared with intact ones. Tables and charts of solutions in dimensionless forms are presented for ease of use by practitioners.

Keywords: Hoek-Brown failure criterion, limit analysis, rock slope, tension cracks

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Authors: Gupta Rajesh, Paudel Sagar, Sharma Utkarsh, Singh Amit Kumar

Abstract:

Thermal stratification has drawn much attention because of the malfunctions at various nuclear plants in U.S.A that raised significant safety concerns. The concerns due to this phenomenon relate to thermal stresses in branch pipes connected to the reactor coolant system piping. This stress limits the lifetime of the piping system, and even leading to penetrating cracks. To assess origin of valve damage in the pipeline, it is essential to determine the effect of turbulence penetration on valve leakage; since stratified flow is generally generated by turbulent penetration or valve leakage. As a result, we concluded with the help of coupled fluent-structural analysis that the pipe with less turbulence has less chance of failure there by requiring less maintenance.

Keywords: nuclear reactor coolant system, thermal stratification, turbulent penetration, coupled fluent-structural analysis, Von-Misses stress

Procedia PDF Downloads 293