Search results for: real time simulator

Authors: Svetlana Bialkova, Marnix van Gisbergen

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Advanced Virtual Reality (VR) technologies offer compelling multisensory and interactive experiences applicable in various fields from education to entertainment. However, serious VR applications within the financial sector are scarce, and managing ‘real’ business services with(in) VR is a challenge inviting further investigation. The current research addresses this challenge, by exploring the key parameters influencing the VR business power and the development of appropriate VR applications in real financial business. We conducted profound investigation of both B2B and B2C needs, and how these could be met. In three studies, we have approached experts from leading international banks (finance to computer specialists), and their (potential) customers. Study 1 included focus group discussions with experts. First, participants could experience different VR devices such as Samsung Gear VR, then a structured discussion was held. The outcomes are analyzed and summarized in a portfolio. Study 2 further used the portfolio analyzer to profile the management of real business services with(in) VR. Again experts participated, where first being introduced with Samsung Gear, then experiencing it and being interviewed. Based on the outcomes, a survey was developed to interview (potential) customers and test ideas created (Study 3). The results suggest that developing proper system architectures to connect people and to connect devices is crucial for building up powerful business with(in) VR. From one side, connecting devices, e.g., pairing mobile Head Mounted Displays for VR with smart-phones and/or wearable technologies would be appropriate way “to have” customers anywhere, anytime with a brand and/or business. Developing VR Apps, providing detailed real time visualization of performance and infrastructure types could enable 3D VR navigation, 3D contents viewing, but also being opportunity for connecting people in collaborative platforms. The outcomes of the current research are summarized in a model which could be applied to unlock the real business power of VR.

Keywords: business power, B2B, B2C, VR applications

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Virginie Hergault, Siham Chebbah, Bertrand Frere

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Following in-house objectives, Central laboratory of Paris police Prefecture conducted a general review on models and Computational Fluid Dynamics (CFD) codes used to simulate pollutant dispersion in the atmosphere. Starting from that review and considering main features of Large Eddy Simulation, Central Laboratory Of Paris Police Prefecture (LCPP) postulates that the Fire Dynamics Simulator (FDS) model, from National Institute of Standards and Technology (NIST), should be well suited for air pollutant dispersion modeling. This paper focuses on the implementation and the evaluation of FDS in the frame of the European COST ES1006 Action. This action aimed at quantifying the performance of modeling approaches. In this paper, the CUTE dataset carried out in the city of Hamburg, and its mock-up has been used. We have performed a comparison of FDS results with wind tunnel measurements from CUTE trials on the one hand, and, on the other, with the models results involved in the COST Action. The most time-consuming part of creating input data for simulations is the transfer of obstacle geometry information to the format required by SDS. Thus, we have developed Python codes to convert automatically building and topographic data to the FDS input file. In order to evaluate the predictions of FDS with observations, statistical performance measures have been used. These metrics include the fractional bias (FB), the normalized mean square error (NMSE) and the fraction of predictions within a factor of two of observations (FAC2). As well as the CFD models tested in the COST Action, FDS results demonstrate a good agreement with measured concentrations. Furthermore, the metrics assessment indicate that FB and NMSE meet the tolerance acceptable.

Keywords: numerical simulations, atmospheric dispersion, cost ES1006 action, CFD model, cute experiments, wind tunnel data, numerical results

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Authors: Shreya Bokare, Sanjay Pawar, Shika Nema

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Growth in cloud applications is generating the tremendous amount of data, building load on traditional storage management systems. Software Defined Storage (SDS) is a new storage management concept becoming popular to handle this large amount of data. CoprHD is one of the open source SDS controller, available for experimentation and development in the storage industry. In this paper, the storage management techniques provided by CoprHD to manage heterogeneous storage platforms are experimented and analyzed. Various storage management parameters such as time to provision, storage capacity measurement, and heterogeneity are experimentally evaluated along with the theoretical expression to prove the completeness of CoprHD controller for storage management.

Keywords: software defined storage, SDS, CoprHD, open source, SMI-S simulator, clarion, Symmetrix

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Authors: Mohamed Mediouni

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Evaluating the performance of a simulator in the CAVE has to be confirmed by encouraging people to live the experience of virtual reality. In this paper, a detailed procedure of recording video is presented. Limitations of the experimental device are firstly exposed. Then, solutions for improving this idea are finally described.

Keywords: CAVE, stereoscopics, camera, recording

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti, Kumar Prashant

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper we compare AODV, DSDV, DSR and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyses these routing protocols by extensive simulations in OPNET simulator and show that how pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, data traffic sent, throughput, retransmission attempts.

Keywords: MANET, AODV, DSDV, DSR, ZRP

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Authors: Ankit Kumar Yadav, Nagendra R. Velaga

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Driving under the influence of alcohol impairs the driving performance and increases the crash risks worldwide. The present study investigated the effect of different Blood Alcohol Concentrations (BAC) on the accelerating and braking behaviour of drivers with the help of driving simulator experiments. Eighty-two licensed Indian drivers drove on the rural road environment designed in the driving simulator at BAC levels of 0.00%, 0.03%, 0.05%, and 0.08% respectively. Driving performance was analysed with the help of vehicle control performance indicators such as mean acceleration and mean brake pedal force of the participants. Preliminary analysis reported an increase in mean acceleration and mean brake pedal force with increasing BAC levels. Generalized linear mixed models were developed to quantify the effect of different alcohol levels and explanatory variables such as driver’s age, gender and other driver characteristic variables on the driving performance indicators. Alcohol use was reported as a significant factor affecting the accelerating and braking performance of the drivers. The acceleration model results indicated that mean acceleration of the drivers increased by 0.013 m/s², 0.026 m/s² and 0.027 m/s² for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Results of the brake pedal force model reported that mean brake pedal force of the drivers increased by 1.09 N, 1.32 N and 1.44 N for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Age was a significant factor in both the models where one year increase in drivers’ age resulted in 0.2% reduction in mean acceleration and 19% reduction in mean brake pedal force of the drivers. It shows that driving experience could compensate for the negative effects of alcohol to some extent while driving. Female drivers were found to accelerate slower and brake harder as compared to the male drivers which confirmed that female drivers are more conscious about their safety while driving. It was observed that drivers who were regular exercisers had better control on their accelerator pedal as compared to the non-regular exercisers during drunken driving. The findings of the present study revealed that drivers tend to be more aggressive and impulsive under the influence of alcohol which deteriorates their driving performance. Drunk driving state can be differentiated from sober driving state by observing the accelerating and braking behaviour of the drivers. The conclusions may provide reference in making countermeasures against drinking and driving and contribute to traffic safety.

Keywords: alcohol, acceleration, braking behaviour, driving simulator

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Authors: Van Diem Thi, Mourad Khelifa, Mohammed El Ganaoui, Yann Rogaume

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An efficient numerical method has been developed to incorporate the effects of heat transfer in timber panels on partition walls exposed to real building fires. The procedure has been added to the software package Abaqus/Standard as a user-defined subroutine (UMATHT) and has been verified using both time-and spatially dependent heat fluxes in two- and three-dimensional problems. The aim is to contribute to the development of simulation tools needed to assist structural engineers and fire testing laboratories in technical assessment exercises. The presented method can also be used under the developmental stages of building components to optimize performance in real fire conditions. The accuracy of the used thermal properties and the finite element models was validated by comparing the predicted results with three different available fire tests in literature. It was found that the model calibrated to results from standard fire conditions provided reasonable predictions of temperatures within assemblies exposed to real building fire.

Keywords: Timber panels, heat transfer, thermal properties, standard fire tests

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Authors: Wolfram Jahn, Jose Manuel Munita

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While computational fluid dynamics (CFD) simulations of fire scenarios are commonly used in the design of buildings, less attention has been given to the use of CFD simulations as an operational tool for the fire services. The reason of this lack of attention lies mainly in the fact that CFD simulations typically take large periods of time to complete, and their results would thus not be available in time to be of use during an emergency. Firefighters often face uncertain conditions when entering a building to attack a fire. They would greatly benefit from a technology based on predictive fire simulations, able to assist their decision-making process. The principal constraint to faster CFD simulations is the fine grid necessary to solve accurately the physical processes that govern a fire. This paper explores the possibility of overcoming this constraint and using coarse grid CFD simulations for fire scenarios, and proposes a methodology to use the simulation results in a meaningful way that can be used by the fire fighters during an emergency. Data from real scale compartment fire tests were used to compare CFD fire models with different grid arrangements, and empirical correlations were obtained to interpolate data points into the grids. The results show that the strongly predominant effect of the heat release rate of the fire on the fluid dynamics allows for the use of coarse grids with relatively low overall impact of simulation results. Simulations with an acceptable level of accuracy could be run in real time, thus making them useful as a forecasting tool for emergency response purposes.

Keywords: CFD, fire simulations, emergency response, forecast

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Authors: Mumtaz Ipek, Burak Erkayman

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Due date is assigned as an input for scheduling problems. At the same time, due date is selected as a decision variable for real time scheduling applications. Correct determination of due dates increases shop floor performance and number of jobs completed on time. This subject has been mentioned widely in the literature. Moreover rules for due date determination have been developed from analytical analysis. When a job arrives to the shop floor, a due date is assigned for delivery. Various due date determination methods are used in the literature. In this study six different due date methods are implemented for a hypothetical dynamic job shop and the performances of the due date methods are compared.

Keywords: scheduling, dynamic job shop, due date assignment, management engineering

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Authors: Jaswinder Singh

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In this paper, comparative analysis is carried out to study the performance of wavelength/time/space optical CDMA codes using two well-known formats; those are CSRZ and DPSK-RZ using RSoft’s OptSIM. The analysis is carried out under the real-like scenario considering the presence of various non-linear effects such as XPM, SPM, SRS, SBS and FWM. Fiber dispersion and the multiple access interference are also considered. The codes used in this analysis are 3-D wavelength/time/space codes. These are converted into 2-D wavelength-time codes so that their requirement of space couplers and fiber ribbons is eliminated. Under the conditions simulated, this is found that CSRZ performs better than DPSK-RZ for fiber-optic CDMA applications.

Keywords: Optical CDMA, Multiple access interference (MAI), CSRZ, DPSK-RZ

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Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

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Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

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Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

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Authors: Ambuj Kumar Gautam, V. Vasu

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This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

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Authors: M. Ramadan, B. Salah

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This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping

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Authors: Sadia Arshad

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The new coronavirus disease or COVID-19 still poses an alarming situation around the world. Modeling based on the derivative of fractional order is relatively important to capture real-world problems and to analyze the realistic situation of the proposed model. Weproposed a mathematical model for the investigation of COVID-19 dynamics in a generalized fractional framework. The new model is formulated in the Caputo sense and employs a nonlinear time-varying transmission rate. The existence and uniqueness solutions of the fractional order derivative have been studied using the fixed-point theory. The associated dynamical behaviors are discussed in terms of equilibrium, stability, and basic reproduction number. For the purpose of numerical implementation, an effcient approximation scheme is also employed to solve the fractional COVID-19 model. Numerical simulations are reported for various fractional orders, and simulation results are compared with a real case of COVID-19 pandemic. According to the comparative results with real data, we find the best value of fractional orderand justify the use of the fractional concept in the mathematical modelling, for the new fractional modelsimulates the reality more accurately than the other classical frameworks.

Keywords: fractional calculus, modeling, stability, numerical solution

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Authors: Qiang Zhang, Xiaojian Hu

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Aiming at the problem of the existing real-time evaluation methods for traffic safety status, a video information-based urban road section traffic safety status evaluation method was established, and the rapid detection method of traffic flow parameters based on video information is analyzed. The concept of the speed dispersion of the road section that affects the traffic safety state of the urban road section is proposed, and the method of evaluating the traffic safety state of the urban road section based on the speed dispersion of the road section is established. Experiments show that the proposed method can reasonably evaluate the safety status of urban roads in real-time, and the evaluation results can provide a corresponding basis for the traffic management department to formulate an effective urban road section traffic safety improvement plan.

Keywords: intelligent transportation system, road traffic safety, video information, vehicle speed dispersion

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Authors: Navah Z. Ratzon, Talia Glick, Iris Manor

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Attention Deficit Hyperactivity Disorder (ADHD) is a chronic disorder that affects the sufferer’s functioning throughout life and in various spheres of activity, including driving. Difficulties in cognitive functioning and executive functions are often part and parcel of the ADHD diagnosis, and thus form a risk factor in driving. Studies examining the effectiveness of intervention programs for improving and rehabilitating driving in typical teenagers have been conducted in relatively small numbers; while studies on similar programs for teenagers with ADHD have been especially scarce. The aim of the present study has been to examine the effectiveness of a metacognitive occupational therapy intervention program for reducing risk factors in driving among teenagers with ADHD. The present study included 37 teenagers aged 17 to 19. They included 23 teenagers with ADHD divided into experimental (11) and control (12) groups; as well as 14 non-ADHD teenagers forming a second control group. All teenagers taking part in the study were examined in the Tel Aviv University driving lab, and underwent cognitive diagnoses and a driving simulator test. Every subject in the intervention group took part in 3 assessment meetings, and two metacognitive treatment meetings. The control groups took part in two assessment meetings with a follow-up meeting 3 months later. In all the study’s groups, the treatment’s effectiveness was tested by comparing monitoring results on the driving simulator at the first and second evaluations. In addition, the driving of 5 subjects from the intervention group was monitored continuously from a month prior to the start of the intervention, a month during the phase of the intervention and another month until the end of the intervention. In the ADHD control group, the driving of 4 subjects was monitored from the end of the first evaluation for a period of 3 months. The study’s findings were affected by the fact that the ADHD control group was different from the two other groups, and exhibited ADHD characteristics manifested by impaired executive functions and lower metacognitive abilities relative to their peers. The study found partial, moderate, non-significant correlations between driving skills and cognitive functions, executive functions, and perceptions and attitudes towards driving. According to the driving simulator test results and the limited sampling results of actual driving, it was found that a metacognitive occupational therapy intervention may be effective in reducing risk factors in driving among teenagers with ADHD relative to their peers with and without ADHD. In summary, the results of the present study indicate a positive direction that speaks to the viability of using a metacognitive occupational therapy intervention program for reducing risk factors in driving. A further study is required that will include a bigger number of subjects, add actual driving monitoring hours, and assign subjects randomly to the various groups.

Keywords: ADHD, driving, driving monitoring, metacognitive intervention, occupational therapy, simulator, teenagers

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Authors: L. Mouzai, M. Bouhadef

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Raindrops and overland flow both are erosive parameters but they do not act by the same way. The overland flow alone tends to shear the soil horizontally and concentrates into rills. In the presence of rain, the soil particles are removed from the soil surface in the form of a uniform sheet layer. In addition to this, raindrops falling on the flow roughen the water and soil surface depending on the flow depth, and retard the velocity, therefore influence shear velocity and Manning’s factor. To investigate this part, agricultural sandy soil, rainfall simulator and a laboratory soil tray of 0.2x1x3 m were the base of this work. Five overland flow depths of 0; 3.28; 4.28; 5.16; 5.60; 5.80 mm were generated under a rainfall intensity of 217.2 mm/h. Sediment concentration control is based on the proportionality of depth/microtopography. The soil loose is directly related to the presence of rain splash on thin sheet flow. The effect of shear velocity on sediment concentration is limited by the value of 5.28 cm/s. In addition to this, the rain splash reduces the soil roughness by breaking the soil crests. The rainfall intensity is the major factor influencing depth and soil erosion. In the presence of rainfall, the shear velocity of the flow is due to two simultaneous effects. The first, which is horizontal, comes from the flow and the second, vertical, is due to the raindrops.

Keywords: flow resistance, laboratory experiments, rainfall simulator, sediment concentration, shear velocity, soil erosion

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Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

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The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

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Authors: Semih Demir, Anil Celebi

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Circuit switched networks widely used until the end of the 20^th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization

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Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: Gylych Jelilov

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This paper investigates the effect of foreign debt on economic growth. Example has been chosen from Africa, Nigeria. By conducting cointegration test we have tested for a long-run relationship between. GDP = Real gross domestic product, EXTDEBT = External debt, INT = Interest rate, CAB = Current account balance, and EXCHR = Real exchange rate over the period 1990 to 2012. It was found out by the study that there is a negative but insignificant relationship between external debt and real gross domestic product. While a positive relationship exists between external debt and economic growth. Also, showed a negative and significant relationship between interest rate and real gross domestic product and there was a positive but insignificant relationship between current account balance and real gross domestic product.

Keywords: economic growth, foreign debt, Nigeria, sustainable development, economic stability

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Dalia G. Aseel

Abstract:

The potato (Solanum tubersum, L.) has become one of the major vegetable crops in Egypt and all over the world. Potato leafroll virus(PLRV) was observed on potato plants collected from different governorates in Egypt. Three cultivars, Spunta, Diamont, and Cara, infected with PLRV were collected; RNA was extracted and subjected to Real-Time PCR using the coat protein gene primers. The results showed that the expression of the coat protein was 39.6-fold, 12.45-fold, and 47.43-fold, respectively, for Spunta, Diamont, and Cara cultivars. Differential Display Polymerase Chain Reaction (DD-PCR) using pathogenesis-related protein 1 (PR-1), β-1,3-glucanases (PR-2), chitinase (PR-3), peroxidase (POD), and polyphenol oxidase (PPO) forward primers for pathogenesis-related proteins (PR). The obtained data revealed different banding patterns depending on the viral type and the region of infection. Regarding PLRV, 58 up-regulated and 19 down-regulated genes were detected. Sequence analysis of the up-and down-regulated genes revealed that infected plants were observed in comparison with the healthy control. Sequence analysis of the up-regulated gene was performed, and the encoding sequence analysis showed that the obtained genes include: induced stolen tip protein. On the other hand, two down-regulated genes were identified: disease resistance RPP-like protein and non-specific lipid-transfer protein. In this study, the expressions of PR-1, PR-2, PR-3, POD, and PPO genes in the infected leaves of three potato cultivars were estimated by quantitative real-time PCR. We can conclude that the PLRV-infection of potato plants inhibited the expression of the five PR genes. On the contrary, infected leaves by PLRV elevated the expression of some defense genes. This interaction may also induce and/or suppress the expression of some genes responsible for the plant's defense mechanisms.

Keywords: PLRV, pathogenesis-related proteins (PRs), DD-PCR, sequence, real-time PCR

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Authors: Jean Berger, Mohamed Barkaoui

Abstract:

Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

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Authors: Pedro P. Drumond, Priscilla M. Moura, Marcia M. L. P. Coelho

Abstract:

The purpose of On-site Stormwater Detention (OSD) system is to promote the detention of addition stormwater runoff caused by impervious areas, in order to maintain the peak flow the same as the pre-urbanization condition. In recent decades, these systems have been built in many cities around the world. However, its real efficiency continues to be unknown due to the lack of research, especially with regard to monitoring its real performance. Thus, this study aims to compare the water level monitoring data of an OSD built in Belo Horizonte/Brazil with the results of theoretical methods simulations, usually adopted in OSD design. There were made two theoretical simulations, one using the Rational Method and Modified Puls method and another using the Soil Conservation Service (SCS) method and Modified Puls method. The monitoring data were obtained with a water level sensor, installed inside the reservoir and connected to a data logger. The comparison of OSD performance was made for 48 rainfall events recorded from April/2015 to March/2017. The comparison of maximum water levels in the OSD showed that the results of the simulations with Rational/Puls and SCS/Puls methods were, on average 33% and 73%, respectively, lower than those monitored. The Rational/Puls results were significantly higher than the SCS/Puls results, only in the events with greater frequency. In the events with average recurrence interval of 5, 10 and 200 years, the maximum water heights were similar in both simulations. Also, the results showed that the duration of rainfall events was close to the duration of monitored hydrograph. The rising time and recession time of the hydrographs calculated with the Rational Method represented better the monitored hydrograph than SCS Method. The comparison indicates that the real discharge coefficient value could be higher than 0.61, adopted in Puls simulations. New researches evaluating OSD real performance should be developed. In order to verify the peak flow damping efficiency and the value of the discharge coefficient is necessary to monitor the inflow and outflow of an OSD, in addition to monitor the water level inside it.

Keywords: best management practices, on-site stormwater detention, source control, urban drainage

Procedia PDF Downloads 175