Search results for: Automated vehicle
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 931

Search results for: Automated vehicle

541 Exploration of the Communication Area of Infrared Short-Range Communication Systems for Intervehicle Communication

Authors: Wern-Yarng Shieh, Hsin-Chuan Chen, Ti-Ho Wang, Bo-Wei Chen

Abstract:

Infrared communication in the wavelength band 780- 950 nm is very suitable for short-range point-to-point communications. It is a good choice for vehicle-to-vehicle communication in several intelligent-transportation-system (ITS) applications such as cooperative driving, collision warning, and pileup-crash prevention. In this paper, with the aid of a physical model established in our previous works, we explore the communication area of an infrared intervehicle communication system utilizing a typical low-cost cormmercial lightemitting diodes (LEDs) as the emitter and planar p-i-n photodiodes as the receiver. The radiation pattern of the emitter fabricated by aforementioned LEDs and the receiving pattern of the receiver are approximated by a linear combination of cosinen functions. This approximation helps us analyze the system performance easily. Both multilane straight-road conditions and curved-road conditions with various radius of curvature are taken into account. The condition of a small car communicating with a big truck, i.e., there is a vertical mounting height difference between the emitter and the receiver, is also considered. Our results show that the performance of the system meets the requirement of aforementioned ITS applications in terms of the communication area.

Keywords: Dedicated short-range communication (DSRC), infrared communication, intervehicle communication, intelligent transportation system (ITS).

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540 Vision-Based Collision Avoidance for Unmanned Aerial Vehicles by Recurrent Neural Networks

Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: Unmanned aerial vehicle, object tracking, deep learning, collision avoidance.

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539 Validation of Automotive Centrals Using Hardware in the Loop-Body Control Unit and Lights

Authors: Marley Rosa Luciano, Rodney Rezende Saldanha

Abstract:

The race for electrification and the need for innovation to attract customers has led the automotive industry to do something different with vehicles. New emissions control challenges and efficient technological availability are the pillars of creation. The growing demand to upgrade industrial manufacturing systems creates actions that directly impact vehicle production. With this comes the search for new prototyping methods and virtual tools for component testing and validation, and vehicle systems have established themselves. The demand for Electronic Control Units (ECU) is increasing due to the availability of intelligence and safety in today's vehicles, directly affecting their development, performance, and functional testing. In order to keep up with global changes, the automotive industry uses different virtual environments to produce, verify and validate their vehicles and test prototypes used during development. Therefore, in this paper, integration and validation were performed using the Hardware in the Loop (HIL) test platform, focusing on the ECU Body Control Module (BCM). Then, a brief commentary reviews other test medium platforms, such as the Plywood Buck (PWB), and examines the reliability, flexibility, installation time, and cost of the three test platforms, software in the loop (SIL), Model in the loop (MIL), and HIL, to review their benefits, challenges, and issues in use and information to optimize the use of each platform and test medium.

Keywords: Automotive, Electronic Central Unit, xIL, Hardware in the loop.

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538 Financial Ethics: A Review of 2010 Flash Crash

Authors: Omer Farooq, Salman Ahmed Khan, Sadaf Khalid

Abstract:

Modern day stock markets have almost entirely became automated. Even though it means increased profits for the investors by algorithms acting upon the slightest price change in order of microseconds, it also has given birth to many ethical dilemmas in the sense that slightest mistake can cause people to lose all of their livelihoods. This paper reviews one such event that happened on May 06, 2010 in which $1 trillion dollars disappeared from the Dow Jones Industrial Average. We are going to discuss its various aspects and the ethical dilemmas that have arisen due to it.

Keywords: Flash Crash, Market Crash, Stock Market, Stock Market Crash.

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537 Conventional Four Steps Travel Demand Modeling for Kabul New City

Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

Abstract:

This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul New City, planning, policy, urban transportation.

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536 An Effective Decision-Making Strategy Based on Multi-Objective Optimization for Commercial Vehicles in Highway Scenarios

Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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535 On Musical Information Geometry with Applications to Sonified Image Analysis

Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper a theoretical foundation is developed to segment, analyze and associate patterns within audio. We explore this on imagery via sonified audio applied to our segmentation framework. The approach involves a geodesic estimator within the statistical manifold, parameterized by musical centricity. We demonstrate viability by processing a database of random imagery to produce statistically significant clusters of similar imagery content.

Keywords: Sonification, musical information geometry, image content extraction, automated quantification, audio segmentation, pattern recognition.

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534 Real-World PM, PN and NOx Emission Differences among DOC+CDPF Retrofit Diesel-, Diesel- and Natural Gas-Fueled Buses

Authors: Zhiwen Yang, Jingyuan Li, Zhenkai Xie, Jian Ling, Jiguang Wang, Mengliang Li

Abstract:

To reflect the influence of after-treatment system retrofit and natural gas-fueled vehicle replace on exhaust emissions emitted by urban buses, a portable emission measurement system (PEMS) was employed herein to conduct real driving emission measurements. This study investigated the differences in particle number (PN), particle mass (PM), and nitrogen oxides (NOx) emissions from a China IV diesel bus retrofitted by catalyzed diesel particulate filter (CDPF), a China IV diesel bus, and a China V natural gas bus. The results show that both tested diesel buses possess markedly advantages in NOx emission control when compared to the lean-burn natural gas bus equipped without any NOx after-treatment system. As to PN and PM, only the DOC+CDPF retrofitting diesel bus exhibits enormous benefits on emission control related to the natural gas bus, especially the normal diesel bus. Meanwhile, the differences in PM and PN emissions between retrofitted and normal diesel buses generally increase with the increase in vehicle specific power (VSP). Furthermore, the differences in PM emissions, especially those in the higher VSP ranges, are more significant than those in PN. In addition, the maximum peak PN particle size (32 nm) of the retrofitted diesel bus was significantly lower than that of the normal diesel bus (100 nm). These phenomena indicate that the CDPF retrofitting can effectively reduce diesel bus exhaust particle emissions, especially those with large particle sizes.

Keywords: CDPF, diesel, natural gas, real-world emissions.

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533 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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532 Mobile Assembly of Electric Vehicles: Decentralized, Low-Invest and Flexible

Authors: Achim Kampker, Kai Kreiskoether, Johannes Wagner, Sarah Fluchs

Abstract:

The growing speed of innovation in related industries requires the automotive industry to adapt and increase release frequencies of new vehicle derivatives which implies a significant reduction of investments per vehicle and ramp-up times. Emerging markets in various parts of the world augment the currently dominating established main automotive markets. Local content requirements such as import tariffs on final products impede the accessibility of these micro markets, which is why in the future market exploitation will not be driven by pure sales activities anymore but rather by setting up local assembly units. The aim of this paper is to provide an overview of the concept of decentralized assembly and to discuss and critically assess some currently researched and crucial approaches in production technology. In order to determine the scope in which complementary mobile assembly can be profitable for manufacturers, a general cost model is set up and each cost driver is assessed with respect to varying levels of decentralization. One main result of the paper is that the presented approaches offer huge cost-saving potentials and are thus critical for future production strategies. Nevertheless, they still need to be further exploited in order for decentralized assembly to be profitable for companies. The optimal level of decentralization must, however, be specifically determined in each case and cannot be defined in general.

Keywords: Automotive assembly, e-mobility, production technology, small series assembly.

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531 Real Time Control Learning Game - Speed Race by Learning at the Wheel - Development of Data Acquisition System

Authors: Κonstantinos Kalovrektis, Chryssanthi Palazi

Abstract:

Schools today face ever-increasing demands in their attempts to ensure that students are well equipped to enter the workforce and navigate a complex world. Research indicates that computer technology can help support learning, implementation of various experiments or learning games, and that it is especially useful in developing the higher-order skills of critical thinking, observation, comprehension, implementation, comparison, analysis and active attention to activities such as research, field work, simulations and scientific inquiry. The ICT in education supports the learning procedure by enabling it to be more flexible and effective, create a rich and attractive training environment and equip the students with knowledge and potential useful for the competitive social environment in which they live. This paper presents the design, the development, and the results of the evaluation analysis of an interactive educational game which using real electric vehicles - toys (material) on a toy race track. When the game starts each student selects a specific vehicle toy. Then students are answering questionnaires in the computer. The vehicles' speed is related to the percentage of right answers in a multiple choice questionnaire (software). Every question has its own significant value depending of the different level of questionnaire. Via the developed software, each right or wrong answers in questionnaire increase or decrease the real time speed of their vehicle toys. Moreover the rate of vehicle's speed increase or decrease depends on the difficulty level of each question. The aim of the work is to attract the student’s interest in a learning process and also to improve their scores. The developed real time game was tested using independent populations of students of age groups: 8-10, 11-14, 15-18 years. Standard educational and statistical analysis tools were used for the evaluation analysis of the game. Results reveal that students using the developed real time control game scored much higher (60%) than students using a traditional simulation game on the same questionnaire. Results further indicate that student's interest in repeating the developed real time control gaming was far higher (70%) than the interest of students using a traditional simulation game.

Keywords: Real time game, sensor, learning games, LabVIEW

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530 Computational Analysis of the MembraneTargeting Domains of Plant-specific PRAF Proteins

Authors: Ewa Wywial, Shaneen M. Singh

Abstract:

The PRAF family of proteins is a plant specific family of proteins with distinct domain architecture and various unique sequence/structure traits. We have carried out an extensive search of the Arabidopsis genome using an automated pipeline and manual methods to verify previously known and identify unknown instances of PRAF proteins, characterize their sequence and build 3D structures of their individual domains. Integrating the sequence, structure and whatever little known experimental details for each of these proteins and their domains, we present a comprehensive characterization of the different domains in these proteins and their variant properties.

Keywords: PRAF proteins, homology modeling, Arabidopsisthaliana

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529 Laban Movement Analysis Using Kinect

Authors: Ran Bernstein, Tal Shafir, Rachelle Tsachor, Karen Studd, Assaf Schuster

Abstract:

Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban Movement Analysis, Kinect, Machine Learning.

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528 Grid Artifacts Suppression in Computed Radiographic Images

Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when digital image is resized on a diagnostic monitor. In this paper we propose an automated grid artifactsdetection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: Computed radiography, grid artifacts, image filtering.

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527 A Calibration Device for Force-Torque Sensors

Authors: Nicolay Zarutskiy, Roman Bulkin

Abstract:

The paper deals with the existing methods of force-torque sensor calibration with a number of components from one to six, analyzed their advantages and disadvantages, the necessity of introduction of a calibration method. Calibration method and its constructive realization are also described here. A calibration method allows performing automated force-torque sensor calibration both with selected components of the main vector of forces and moments and with complex loading. Thus, two main advantages of the proposed calibration method are achieved: the automation of the calibration process and universality.

Keywords: Automation, calibration, calibration device, calibration method, force-torque sensors.

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526 Discovery of Production Rules with Fuzzy Hierarchy

Authors: Fadl M. Ba-Alwi, Kamal K. Bharadwaj

Abstract:

In this paper a novel algorithm is proposed that integrates the process of fuzzy hierarchy generation and rule discovery for automated discovery of Production Rules with Fuzzy Hierarchy (PRFH) in large databases.A concept of frequency matrix (Freq) introduced to summarize large database that helps in minimizing the number of database accesses, identification and removal of irrelevant attribute values and weak classes during the fuzzy hierarchy generation.Experimental results have established the effectiveness of the proposed algorithm.

Keywords: Data Mining, Degree of subsumption, Freq matrix, Fuzzy hierarchy.

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525 Auto Rickshaw Impacts with Pedestrians: A Computational Analysis of Post-Collision Kinematics and Injury Mechanics

Authors: A. J. Al-Graitti, G. A. Khalid, P. Berthelson, A. Mason-Jones, R. Prabhu, M. D. Jones

Abstract:

Motor vehicle related pedestrian road traffic collisions are a major road safety challenge, since they are a leading cause of death and serious injury worldwide, contributing to a third of the global disease burden. The auto rickshaw, which is a common form of urban transport in many developing countries, plays a major transport role, both as a vehicle for hire and for private use. The most common auto rickshaws are quite unlike ‘typical’ four-wheel motor vehicle, being typically characterised by three wheels, a non-tilting sheet-metal body or open frame construction, a canvas roof and side curtains, a small drivers’ cabin, handlebar controls and a passenger space at the rear. Given the propensity, in developing countries, for auto rickshaws to be used in mixed cityscapes, where pedestrians and vehicles share the roadway, the potential for auto rickshaw impacts with pedestrians is relatively high. Whilst auto rickshaws are used in some Western countries, their limited number and spatial separation from pedestrian walkways, as a result of city planning, has not resulted in significant accident statistics. Thus, auto rickshaws have not been subject to the vehicle impact related pedestrian crash kinematic analyses and/or injury mechanics assessment, typically associated with motor vehicle development in Western Europe, North America and Japan. This study presents a parametric analysis of auto rickshaw related pedestrian impacts by computational simulation, using a Finite Element model of an auto rickshaw and an LS-DYNA 50th percentile male Hybrid III Anthropometric Test Device (dummy). Parametric variables include auto rickshaw impact velocity, auto rickshaw impact region (front, centre or offset) and relative pedestrian impact position (front, side and rear). The output data of each impact simulation was correlated against reported injury metrics, Head Injury Criterion (front, side and rear), Neck injury Criterion (front, side and rear), Abbreviated Injury Scale and reported risk level and adds greater understanding to the issue of auto rickshaw related pedestrian injury risk. The parametric analyses suggest that pedestrians are subject to a relatively high risk of injury during impacts with an auto rickshaw at velocities of 20 km/h or greater, which during some of the impact simulations may even risk fatalities. The present study provides valuable evidence for informing a series of recommendations and guidelines for making the auto rickshaw safer during collisions with pedestrians. Whilst it is acknowledged that the present research findings are based in the field of safety engineering and may over represent injury risk, compared to “Real World” accidents, many of the simulated interactions produced injury response values significantly greater than current threshold curves and thus, justify their inclusion in the study. To reduce the injury risk level and increase the safety of the auto rickshaw, there should be a reduction in the velocity of the auto rickshaw and, or, consideration of engineering solutions, such as retro fitting injury mitigation technologies to those auto rickshaw contact regions which are the subject of the greatest risk of producing pedestrian injury.

Keywords: Auto Rickshaw, finite element analysis, injury risk level, LS-DYNA, pedestrian impact.

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524 Travel Time Model for Cylinder Type Parking System

Authors: Jing Zhang, Jie Chen

Abstract:

In this paper, we mainly analyze an automated parking system where the storage and retrieval requests are performed by a tower crane. In this parking system, the S/R crane which is located at the middle of the bottom of the cylinder parking area can rotate in both clockwise and counterclockwise and three kinds of movements can be done simultaneously. We develop some mathematical travel time models for the single command cycle under the random storage assignment using the characteristics of this system. Finally, we compare these travel models with discrete case and it is shown that these travel models display a good satisfactory performance.

Keywords: Parking system, travel time model, tower crane.

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523 Lung Nodule Detection in CT Scans

Authors: M. Antonelli, G. Frosini, B. Lazzerini, F. Marcelloni

Abstract:

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

Keywords: computer assisted diagnosis, medical imagesegmentation, shape recognition.

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522 Ghost Frequency Noise Reduction through Displacement Deviation Analysis

Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

Abstract:

Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: Displacement deviation analysis, gear whine, ghost frequency, sound quality.

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521 Non-Rigid Registration of Medical Images Using an Automated Method

Authors: Panos Kotsas

Abstract:

This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.

Keywords: Medical image, non-rigid, registration.

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520 Automating Test Activities: Test Cases Creation, Test Execution, and Test Reporting with Multiple Test Automation Tools

Authors: Loke Mun Sei

Abstract:

Software testing has become a mandatory process in assuring the software product quality. Hence, test management is needed in order to manage the test activities conducted in the software test life cycle. This paper discusses on the challenges faced in the software test life cycle, and how the test processes and test activities, mainly on test cases creation, test execution, and test reporting is being managed and automated using several test automation tools, i.e. Jira, Robot Framework, and Jenkins.

Keywords: Test automation tools, test case, test execution, test reporting.

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519 An Application of Path Planning Algorithms for Autonomous Inspection of Buried Pipes with Swarm Robots

Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

Abstract:

This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: Autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem.

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518 A Comparative Study of Medical Image Segmentation Methods for Tumor Detection

Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

Abstract:

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: Features extraction, image segmentation, medical images, tumour detection.

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517 Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System

Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

Abstract:

The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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516 Rear Seat Belt Use in Developing Countries: A Case Study from the United Arab Emirates

Authors: Salaheddine Bendak, Sara S. Alnaqbi

Abstract:

The seat belt is a vital tool in improving traffic safety conditions and minimising injuries due to traffic accidents. Most developing countries are facing a big problems associated with the human and financial losses due to traffic accidents. One way to minimise these losses is the use of seat belts by passengers both in the front and rear seats of a vehicle; however, at the same time, close to nothing is known about the rates of seat belt utilisation among rear seat passengers in many developing countries. Therefore, there is a need to estimate these rates in order to know the extent of this problem and how people interact with traffic safety measures like seat belts and find demographic characteristics that contribute to wearing or non-wearing of seat belts with the aim of finding solutions to improve wearing rates. In this paper, an observational study was done to gather data on restraints use in motor vehicle rear seats in eight observational stations in a rapidly developing country, the United Arab Emirates (UAE), and estimate a use rate for the whole country. Also, a questionnaire was used in order to study demographic characteristics affecting the wearing of seatbelts in rear seats. Results of the observational study showed that the overall wearing/usage rate was 12.3%, which is considered very low when compared to other countries. Survey results show that single, male, less educated passengers from Arab and South Asian backgrounds use seat belts reportedly less than others. Finally, solutions are put forward to improve this wearing rate based on the results of this study.

Keywords: Seat belts, traffic crashes, United Arab Emirates, rear seats.

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515 Markov Random Field-Based Segmentation Algorithm for Detection of Land Cover Changes Using Uninhabited Aerial Vehicle Synthetic Aperture Radar Polarimetric Images

Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

Abstract:

The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: Coupled Markov random field, environment, object-based analysis, Polarimetric SAR images.

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514 Statistical Analysis and Impact Forecasting of Connected and Autonomous Vehicles on the Environment: Case Study in the State of Maryland

Authors: Alireza Ansariyar, Safieh Laaly

Abstract:

Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates Connected and Autonomous Vehicles (CAVs) fuel consumption and air pollutants including Carbon Monoxide (CO), Particulate Matter (PM), and Nitrogen Oxides (NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: Connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models.

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513 Elimination of Redundant Links in Web Pages– Mathematical Approach

Authors: G. Poonkuzhali, K.Thiagarajan, K.Sarukesi

Abstract:

With the enormous growth on the web, users get easily lost in the rich hyper structure. Thus developing user friendly and automated tools for providing relevant information without any redundant links to the users to cater to their needs is the primary task for the website owners. Most of the existing web mining algorithms have concentrated on finding frequent patterns while neglecting the less frequent one that are likely to contain the outlying data such as noise, irrelevant and redundant data. This paper proposes new algorithm for mining the web content by detecting the redundant links from the web documents using set theoretical(classical mathematics) such as subset, union, intersection etc,. Then the redundant links is removed from the original web content to get the required information by the user..

Keywords: Web documents, Web content mining, redundantlink, outliers, set theory.

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512 Ocean Wave Kinetic Energy Harvesting System for Automated Sub Sea Sensors

Authors: Amir Anvar, Dong Yang Li

Abstract:

This paper presents an overview of the Ocean wave kinetic energy harvesting system. Energy harvesting is a concept by which energy is captured, stored, and utilized using various sources by employing interfaces, storage devices, and other units. Ocean wave energy harvesting in which the kinetic and potential energy contained in the natural oscillations of Ocean waves are converted into electric power. The kinetic energy harvesting system could be used for a number of areas. The main applications that we have discussed in this paper are to how generate the energy from Ocean wave energy (kinetic energy) to electric energy that is to eliminate the requirement for continual battery replacement.

Keywords: Energy harvesting, power system, oceanic, sensors, autonomous.

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