Search results for: improved cloud model.

Authors: D. Germanò, D. Plutino, G. Cannistraro

Abstract:

The theatre-auditorium under investigation following the highly reflective characteristics of materials used in it (marble, painted wood, smooth plaster, etc), architectural and structural features of the Protocol and its intended use (very multifunctional: Auditorium, theatre, cinema, musicals, conference room) from the analysis of the statement of fact made by the acoustic simulation software Ramsete and supported by data obtained through a campaign of acoustic measurements of the state of fact made on the spot by a Fonomet Svantek model SVAN 957, appears to be acoustically inadequate. After the completion of the 3D model according to the specifications necessary software used forecast in order to be recognized by him, have made three simulations, acoustic simulation of the state of and acoustic simulation of two design solutions. Improved noise characteristics found in the first design solution, compared to the state in fact consists therefore in lowering Reverberation Time that you turn most desirable value, while the Indicators of Clarity, the Baricentric Time, the Lateral Efficiency, Ratio of Low Tmedia BR and defined the Speech Intelligibility improved significantly. Improved noise characteristics found instead in the second design solution, as compared to first design solution, is finally mostly in a more uniform distribution of Leq and in lowering Reverberation Time that you turn the optimum values. Indicators of Clarity, and the Lateral Efficiency improve further but at the expense of a value slightly worse than the BR. Slightly vary the remaining indices.

Keywords: Indoor, Acoustic, Acoustic simulation

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Authors: Ö. Şenyiğit, A. Çolak

Abstract:

It is of great importance for an architectural student to know the parameters through which he/she can conduct his/her design and makes his/her design effective in architectural education. Therefore; an empirical application study was carried out through the designing activity using the emulation model to support the design and design approaches of architectural students. During the investigation period, studies were done on the basic design elements and principles of the fall semester, and the emulation model, one of the designing methods that constitute the subject of the study, was fictionalized as three phased “recognition-interpretation-application”. As a result of the study, it was observed that when students were given a key method during the design process, their awareness increased and their aspects improved as well.

Keywords: Basic design, design education, design methods, emulation.

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Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: Composite material, crashworthiness, finite element analysis, optimization.

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Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah

Abstract:

Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.

Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.

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Authors: Anju Sharma, Seema Bawa

Abstract:

Resource Discovery in Grids is critical for efficient resource allocation and management. Heterogeneous nature and dynamic availability of resources make resource discovery a challenging task. As numbers of nodes are increasing from tens to thousands, scalability is essentially desired. Peer-to-Peer (P2P) techniques, on the other hand, provide effective implementation of scalable services and applications. In this paper we propose a model for resource discovery in Condor Middleware by using the four axis framework defined in P2P approach. The proposed model enhances Condor to incorporate functionality of a P2P system, thus aim to make Condor more scalable, flexible, reliable and robust.

Keywords: Condor Middleware, Grid Computing, P2P, Resource Discovery.

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: Genetic algorithm, material ordering, project management, project scheduling.

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Authors: Peter Odero Akuon

Abstract:

A rain cell ratio model is proposed that computes attenuation of the smallest rain cell which represents the maximum rain rate value i.e. the cell size when rainfall rate is exceeded 0.01% of the time, R_0.01 and predicts attenuation for other cells as the ratio with this maximum. This model incorporates the dependence of the path factor r on the ellipsoidal path variation of the Fresnel zone at different frequencies. In addition, the inhomogeneity of rainfall is modeled by a rain drop packing density factor. In order to derive the model, two empirical methods that can be used to find rain cell size distribution D_c are presented. Subsequently, attenuation measurements from different climatic zones for terrestrial radio links with frequencies F in the range 7-38 GHz are used to test the proposed model. Prediction results show that the path factor computed from the rain cell ratio technique has improved reliability when compared with other path factor and effective rain rate models, including the current ITU-R 530-15 model of 2013.

Keywords: Packing density of rain drops, prediction model, rain attenuation, rain cell ratio technique.

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Authors: Jaemoon Lim

Abstract:

To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: Chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME.

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Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

Abstract:

Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, Immersed microelectronics, turbulent natural convection in enclosures.

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Authors: G. Kishor Babu, B. Madhu Kiran

Abstract:

This paper presented an intend scheme of Modular-Multilevel-Converter (MMC) levels for move towering the practical conciliation flanked by the precision and divisional competence. The whole process is standard by a Thevenin-equivalent 133-level MMC model. Firstly the computation scheme of the fundamental limit imitation time step is offered to faithfully represent each voltage level of waveforms. Secondly the earlier industrial Improved Analytic Hierarchy Process (IAHP) is adopted to integrate the relative errors of all the input electrical factors interested in one complete virtual fault on each converter level. Thirdly the stable AC and DC ephemeral condition in virtual faults effects of all the forms stabilize and curve integral stand on the standard form. Finally the optimal MMC level will be obtained by the drown curves and it will give individual weights allowing for the precision and efficiency. And the competence and potency of the scheme are validated by model on MATLAB Simulink.

Keywords: Modular multilevel converter, improved analytic hierarchy process, ac and dc transient, high voltage direct current, voltage sourced converter.

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Authors: A. Javed, K. Djidjeli, J. T. Xing, S. J. Cox

Abstract:

A method for simulating flow around the solid bodies has been presented using hybrid meshfree and mesh-based schemes. The presented scheme optimizes the computational efficiency by combining the advantages of both meshfree and mesh-based methods. In this approach, a cloud of meshfree nodes has been used in the domain around the solid body. These meshfree nodes have the ability to efficiently adapt to complex geometrical shapes. In the rest of the domain, conventional Cartesian grid has been used beyond the meshfree cloud. Complex geometrical shapes can therefore be dealt efficiently by using meshfree nodal cloud and computational efficiency is maintained through the use of conventional mesh-based scheme on Cartesian grid in the larger part of the domain. Spatial discretization of meshfree nodes has been achieved through local radial basis functions in finite difference mode (RBF-FD). Conventional finite difference scheme has been used in the Cartesian ‘meshed’ domain. Accuracy tests of the hybrid scheme have been conducted to establish the order of accuracy. Numerical tests have been performed by simulating two dimensional steady and unsteady incompressible flows around cylindrical object. Steady flow cases have been run at Reynolds numbers of 10, 20 and 40 and unsteady flow problems have been studied at Reynolds numbers of 100 and 200. Flow Parameters including lift, drag, vortex shedding, and vorticity contours are calculated. Numerical results have been found to be in good agreement with computational and experimental results available in the literature.

Keywords: CFD, Meshfree particle methods, Hybrid grid, Incompressible Navier Strokes equations, RBF-FD.

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Authors: Meng Wang, Qi-rui Han

Abstract:

Because of excellent properties, people has paid more attention to SPIHI algorithm, which is based on the traditional wavelet transformation theory, but it also has its shortcomings. Combined the progress in the present wavelet domain and the human's visual characteristics, we propose an improved algorithm based on human visual characteristics of SPIHT in the base of analysis of SPIHI algorithm. The experiment indicated that the coding speed and quality has been enhanced well compared to the original SPIHT algorithm, moreover improved the quality of the transmission cut off.

Keywords: Lifted wavelet transform, SPIHT, Human Visual Characteristics.

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Authors: Chang Liu, Zishu He

Abstract:

Adaptive echo cancellers with two-path algorithm are applied to avoid the false adaptation during the double-talk situation. In the two-path algorithm, several transfer logic solutions have been proposed to control the filter update. This paper presents an improved transfer logic solution. It improves the convergence speed of the two-path algorithm, and allows the reduction of the memory elements and computational complexity. Results of simulations show the improved performance of the proposed solution.

Keywords: Acoustic echo cancellation, Echo return lossenhancement (ERLE), Two-path algorithm, Transfer logic

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Authors: M. Tohidi, J. Yang, C. Baniotopoulos

Abstract:

Progressive collapse of buildings typically occurs  when abnormal loading conditions cause local damages, which leads  to a chain reaction of failure and ultimately catastrophic collapse. The  tie force (TF) method is one of the main design approaches for  progressive collapse. As the TF method is a simplified method, further  investigations on the reliability of the method is necessary. This study  aims to develop an improved TF method to design the cross wall  structures for progressive collapse. To this end, the pullout behavior of  strands in grout was firstly analyzed; and then, by considering the tie  force-slip relationship in the friction stage together with the catenary  action mechanism, a comprehensive analytical method was developed.  The reliability of this approach is verified by the experimental results  of concrete block pullout tests and full scale floor-to-floor joints tests  undertaken by Portland Cement Association (PCA). Discrepancies in  the tie force between the analytical results and codified specifications  have suggested the deficiency of TF method, hence an improved  model based on the analytical results has been proposed to address this  concern.

 

Keywords: Cross wall, progressive collapse, ties force method, catenary, analytical.

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Authors: Zhaopeng Xuan, Yuan Bian, C. Cailleaux, Jing Qin, S. Traore

Abstract:

Traditional software engineering allows engineers to propose to their clients multiple specialized software distributions assembled from a shared set of software assets. The management of these assets however requires a trade-off between client satisfaction and software engineering process. Clients have more and more difficult to find a distribution or components based on their needs from all of distributed repositories.

This paper proposes a software engineering for a user-driven software product line in which engineers define a Feature Model but users drive the actual software distribution on demand. This approach makes the user become final actor as a release manager in software engineering process, increasing user product satisfaction and simplifying user operations to find required components. In addition, it provides a way for engineers to manage and assembly large software families.

As a proof of concept, a user-driven software product line is implemented for Eclipse, an integrated development environment. An Eclipse feature model is defined, which is exposed to users on a cloud-based built platform from which clients can download individualized Eclipse distributions.

Keywords: Software Product Line, Model-driven Development, Reverse Engineering and Refactoring, Agile Method

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Authors: O. Hassanein, Sreenatha G. Anavatti, Tapabrata Ray

Abstract:

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy model and adaptive neural fuzzy network (ANFN) model techniques to overcome the uncertain external disturbance and the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according to the back propagation algorithm based upon the error between the identified model and the actual output of the plant. The proposed ANFN model adopts a functional link neural network (FLNN) as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN model is a nonlinear combination of input variables. Fuzzy control system is applied to guide and control the AUV using both adaptive models and mathematical model. Simulation results show the superiority of the proposed adaptive neural fuzzy network (ANFN) model in tracking of the behavior of the AUV accurately even in the presence of noise and disturbance.

Keywords: AUV, AUV dynamic model, fuzzy control, fuzzy modelling, adaptive fuzzy control, back propagation, system identification, neural fuzzy model, FLNN.

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Authors: Ohn Zin Lin, Okka, Cho Cho Myint

Abstract:

It is important to consider the effects of transformers on distribution system because they have the highest impact on system reliability. It is generally said that parallel operation of transformers (POT) can improve the system reliability. However, the estimation approach can be also considered for accuracy. In this paper, we propose a three-state components model and equations to determine the reliability improvement by POT, and cooperation of POT and distributed generation (DG). Based on the proposed model and techniques, the effect of POT is analyzed in four different tests with the consideration of conventional distribution system, distribution automation system (DAS) and DG. According to the results, the reliability is greatly improved by cooperation of POT, DAS and DG. The proposed model and methods are applicable to not only developing countries which have conventional distribution system but also developed countries in which DAS has already installed.

Keywords: Distribution system, reliability, dispersed generator, energy not supply, transformer parallel operation.

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Authors: Sreejith Jayachandran, Mojtaba Ghodsi, Morteza Mohammadzaheri

Abstract:

The modern busy world is running behind new embedded technologies based on computers and software meanwhile some people are unable to monitor their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. In this research, we present a device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. The various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data are collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud and stores it there; the processed digital data are then instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors, and other health staff can collect these data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate these data for awareness of the patient's current health status. Moreover, the system is connected to a GPS module. In emergencies, the concerned team can be positioning the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the Remote Health Monitoring System (RHMS) is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system 11×10×10 cm3 with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured for 100 GBP (British Pound Sterling), and can facilitate the communication between patients and health systems, but also it can be employed for numerous other uses including communication sectors in the aerospace and transportation systems.

Keywords: Embedded Technology, Telemonitoring system, Microcontroller, Arduino UNO, Cloud storage, GPS, RHMS, Remote Health Monitoring System, Alert system.

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Authors: R. Ziaie Moayed, E. Ghanbari Alamouty

Abstract:

Deep soil mixing is one of the improvement methods in geotechnical engineering which is widely used in soft soils. This article investigates the consolidation behavior of a soft clay soil which is improved by soil-cement column (SCC) by numerical modeling using Plaxis2D program. This behavior is simulated under vertical static and cyclic load which is applied on the soil surface. The static load problem is the simulation of a physical model test in an axisymmetric condition which uses a single SCC in the model center. The results of numerical modeling consist of settlement of soft soil composite, stress on soft soil and column, and excessive pore water pressure in the soil show a good correspondence with the test results. The response of soft soil composite to the cyclic load in vertical direction also compared with the static results. Also the effects of two variables namely the cement content used in a SCC and the area ratio (the ratio of the diameter of SCC to the diameter of composite soil model, a) is investigated. The results show that the stress on the column with the higher value of a, is lesser compared with the stress on other columns. Different rate of consolidation and excessive pore pressure distribution is observed in cyclic load problem. Also comparing the results of settlement of soil shows higher compressibility in the cyclic load problem.

Keywords: Area ratio, consolidation behavior, cyclic load, numerical modeling, soil-cement column.

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Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

Abstract:

Structural inspection activities are necessary to ensure the correct functioning of infrastructures. UAV techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. In this paper, a methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of RGB and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: Aerial thermography, data processing, drone, low-cost, point cloud.

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Authors: Chris Ewe, Naoum Jamous, Holger Schrödl

Abstract:

Like most entrepreneurs, data center operators pursue goals such as profit-maximization, improvement of the company’s reputation or basically to exist on the market. Part of those aims is to guarantee a given quality of service. Quality characteristics are specified in a contract called the service level agreement. Central part of this agreement is non-functional properties of an IT service. The system availability is one of the most important properties as it will be shown in this paper. To comply with availability requirements, data center operators can use virtualization technologies. A clear model to assess the effect of virtualization functions on the parts of a data center in relation to the system availability is still missing. This paper aims to introduce a basic model that shows these connections, and consider if the identified effects are positive or negative. Thus, this work also points out possible disadvantages of the technology. In consequence, the paper shows opportunities as well as risks of data center virtualization in relation to system availability.

Keywords: Availability, cloud computing IT service, quality of service, service level agreement, virtualization.

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Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

Abstract:

We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: Air pollution, dispersion, emissions, line sources, road traffic, urban transport.

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Authors: Vasilij Djackov, Tomas Zapnickas, Evgenii Iamshchikov, Lukas Norkevicius, Rima Mickeviciene, Larisa Vasiljeva

Abstract:

In this paper, the resistance and pitching values of the test of an electric ferry are presented. The research was carried out in the open flow channel of Klaipėda University with a multi-axis dynamometer. The received model resistance values were recalculated to the real vessel and the preliminary chosen propulsion unit power was compared. After analyzing the results of the pitching of the model, it was concluded that the shape of the hull needs to be further improved, taking into account the possible uneven weight distribution at the ends of the ferry. Further investigation of the hull of the electric ferry is recommended, including experiments with various water depths and activation of propulsion units.

Keywords: Electrical ferry, model tests, open flow channel, pitching, resistance.

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

Abstract:

In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer. 

Keywords: Surface hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness.

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Authors: Biao Ma, Jikai Liu, Man Chen, Jianpeng Wu, Liyong Wang, Changsong Zheng

Abstract:

Proposing an appropriate control strategy is an effective and practical way to address the overheat problems of the wet multi-plate clutch in Direct Shift Gearbox under the long-time creeping condition. To do so, the temperature variation of the wet multi-plate clutch is investigated firstly by establishing a thermal resistance model for the gearbox cooling system. To calculate the generated heat flux and predict the clutch temperature precisely, the friction torque model is optimized by introducing an improved friction coefficient, which is related to the pressure, the relative speed and the temperature. After that, the heat transfer model and the reasonable friction torque model are employed by the vehicle powertrain model to construct a comprehensive co-simulation model for the Direct Shift Gearbox (DSG) vehicle. A creeping control strategy is then proposed and, to evaluate the vehicle performance, the safety temperature (250 ℃) is particularly adopted as an important metric. During the creeping process, the temperature of two clutches is always under the safety value (250 ℃), which demonstrates the effectiveness of the proposed control strategy in avoiding the thermal failures of clutches.

Keywords: Creeping control strategy, direct shift gearbox, temperature variation, wet clutch.

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Authors: Yizhen Zhao, Adam S. Z. Belloum, Gonc¸alo Maia da Costa, Zhiming Zhao

Abstract:

Machine learning has evolved from an area of academic research to a real-world applied field. This change comes with challenges, gaps and differences exist between common practices in academic environments and the ones in production environments. Following continuous integration, development and delivery practices in software engineering, similar trends have happened in machine learning (ML) systems, called MLOps. In this paper we propose a framework that helps to streamline and introduce best practices that facilitate the ML lifecycle in an industrial setting. This framework can be used as a template that can be customized to implement various machine learning experiments. The proposed framework is modular and can be recomposed to be adapted to various use cases (e.g. data versioning, remote training on Cloud). The framework inherits practices from DevOps and introduces other practices that are unique to the machine learning system (e.g.data versioning). Our MLOps practices automate the entire machine learning lifecycle, bridge the gap between development and operation.

Keywords: Cloud computing, continuous development, data versioning, DevOps, industrial setting, MLOps, machine learning.

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Authors: S. I. Abu Alasal, M. M. Esbeih, E. R. Fayyad, R. S. Gharaibeh, M. Z. Ali, A. A. Freewan, M. M. Jamhawi

Abstract:

This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: Meshes, Point Clouds, Surface Reconstruction Protocols, 3D Reconstruction.

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

Abstract:

The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: Clustering algorithm, potential function, speech signal, the UBSS model.

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Authors: Manssour A. Abdulsalam Bin Miskeen, Ahmed Mohamed Alhodairi, Riza Atiq Abdullah Bin O. K. Rahmat

Abstract:

In the planning point of view, it is essential to have mode choice, due to the massive amount of incurred in transportation systems. The intercity travellers in Libya have distinct features, as against travellers from other countries, which includes cultural and socioeconomic factors. Consequently, the goal of this study is to recognize the behavior of intercity travel using disaggregate models, for projecting the demand of nation-level intercity travel in Libya. Multinomial Logit Model for all the intercity trips has been formulated to examine the national-level intercity transportation in Libya. The Multinomial logit model was calibrated using nationwide revealed preferences (RP) and stated preferences (SP) survey. The model was developed for deference purpose of intercity trips (work, social and recreational). The variables of the model have been predicted based on maximum likelihood method. The data needed for model development were obtained from all major intercity corridors in Libya. The final sample size consisted of 1300 interviews. About two-thirds of these data were used for model calibration, and the remaining parts were used for model validation. This study, which is the first of its kind in Libya, investigates the intercity traveler’s mode-choice behavior. The intercity travel mode-choice model was successfully calibrated and validated. The outcomes indicate that, the overall model is effective and yields higher precision of estimation. The proposed model is beneficial, due to the fact that, it is receptive to a lot of variables, and can be employed to determine the impact of modifications in the numerous characteristics on the need for various travel modes. Estimations of the model might also be of valuable to planners, who can estimate possibilities for various modes and determine the impact of unique policy modifications on the need for intercity travel.

Keywords: Multinomial logit model, improved intercity transport, intercity mode-choice behavior, disaggregate analysis.

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Authors: C. A. Barros, Ana P. Barroso

Abstract:

Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: Automotive industry, Industry 4.0, internet of things, IATF 16949:2016, measurement system analysis.

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