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Articles 4261 - 4290 of 4370

Full-Text Articles in Artificial Intelligence and Robotics

Optimal Deployment Of Distant Support Jamming Formation Based On Directional Crossover Genetic Algorithm, Jinliang Luo, Jiacai Jin, Wang Lei, Ding Feng Jun 2018

Optimal Deployment Of Distant Support Jamming Formation Based On Directional Crossover Genetic Algorithm, Jinliang Luo, Jiacai Jin, Wang Lei, Ding Feng

Journal of System Simulation

Abstract: Optimal deployment of distant support jamming formation is studied for improving penetration capability of air assault group in air offensive operation. The total detection threats of penetration route are chosen as the performance indicator, and the optimal deployment mode of distant support jamming formation is built. The closed region detection method is used to compute fitness value. The difficult problem of computing detection coverage of radar net under jamming condition is solved by using traditional geometry analytic method. A selective directional crossover genetic algorithm is designed to compute the optimal deployment mode. The simulation results show that the algorithm …

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Modeling And Simulation Of Networked Control Systems Based On Improved Bp Network, Shifeng Li, Zhanzhi Qiu, Liping Fan, Lina Zhao Jun 2018

Modeling And Simulation Of Networked Control Systems Based On Improved Bp Network, Shifeng Li, Zhanzhi Qiu, Liping Fan, Lina Zhao

Journal of System Simulation

Abstract: In the circumstance where both the delay model and the controlled object model were unknown in networked control systems, a class of networked predictive control systems based on improved BP network were studied. For the problem of obtaining the hidden layer nodes number of BP network, a rapid calculation method was proposed. For the problem of avoiding local optimum of BP network, a hybrid learning method was proposed. A off-line BP network model was proposed for coping with the problem of the delay prediction based on the above algorithms. For the problem of the linear …

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Algorithm For Tracking Position And Orientation Of Drug Delivery Capsules In Gastrointestinal Tract, Xudong Guo, Zhengping Lu, Qinfen Jiang, Shuyi Wang, Haipo Cui Jun 2018

Algorithm For Tracking Position And Orientation Of Drug Delivery Capsules In Gastrointestinal Tract, Xudong Guo, Zhengping Lu, Qinfen Jiang, Shuyi Wang, Haipo Cui

Journal of System Simulation

Abstract: To realize an accurate releasing by a drug-delivery capsule in the gastrointestinal tract, a method of magnetic vector detection with angle sensing has been presented to track the capsule in real time; and a prototype of the tracking system has been developed. Based on the fundamentals of spatial distribution of magnetic vector fields, a nonlinear model of tracking is established. An improved artificial bee colony algorithm is studied to solve the magnetic inverse problem. In the improved algorithm, a chaos operator is used to generate an initial population and a sort selection is used to prevent premature convergence. …

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Design Of Mini Folding Electric Scooter Based On Relative Attitude Angle Control, Lijun Jiang, Zhanghong Wu, Shaohui Pan, Zhelin Li, Zhiyong Xiong, Yongqing Fu Jun 2018

Design Of Mini Folding Electric Scooter Based On Relative Attitude Angle Control, Lijun Jiang, Zhanghong Wu, Shaohui Pan, Zhelin Li, Zhiyong Xiong, Yongqing Fu

Journal of System Simulation

Abstract: To help people move conveniently after getting off the public transport in the city, anew mini electric scooter design is proposed. This new scooter uses a smart mobile phone to receive driving intention and owns more efficient, convenient and space-saving folding pattern. A kinematics model of scooter is set up and discussed. A control strategy based on the relative attitude angle, an attitude sensor data consolidation approach based on the complementary filter, a solution to the Euler angle jumping and an estimate method to the wrong operation are proposed. The design is made into a prototype based on …

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Dynamic Blind Source Separation Method Of Bearing Fault Diagnosis Based On Ga-Aw-Pso, Tianqi Zhang, Baoze Ma, Xingzi Qiang, Shengrong Quan Jun 2018

Dynamic Blind Source Separation Method Of Bearing Fault Diagnosis Based On Ga-Aw-Pso, Tianqi Zhang, Baoze Ma, Xingzi Qiang, Shengrong Quan

Journal of System Simulation

Abstract: The adaptive particle swarm optimization based on genetic mechanism (GA-AW-PSO) is proposed, aiming at blind source separation for dynamic hybrid bearing signals. The negentropy of separated signal is regarded as an objective function. The inertia weight is adjusted adaptively to reduce the invalid iterations according to the fitness difference. The introduction of genetic mechanism can increase diversity and is helpful for dynamic signal processing. The parameterized representation of orthogonal matrices can reduce the complexity of the algorithm. The simulation results show that the proposed method is superior to traditional blind source separation for the dynamic mechanical hybrid analog signal. …

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Online Synthesis Incremental Data Streams Classification Algorithm, Sanmin Liu, Yuxia Liu Jun 2018

Online Synthesis Incremental Data Streams Classification Algorithm, Sanmin Liu, Yuxia Liu

Journal of System Simulation

Abstract: Online learning is the effective way to solve the sample's non-recurrence in data streams classification, and how to deal with the problem of sample deficiency is the critical point for improving online learning efficiency. According to the mean square error decomposition theory of the model's parameter estimation and the idea of cluster, the new samples are constructed by linear synthesis with the class center and the sample, which can improve the distribution information of sample and reduce the lower bound of parameter value. The online incremental learning is executed and the class center point is continuously updated. Through theory …

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Train Energy Saving Operation Based On Simulated Annealing Algorithm, Liu Wei, Jiaxuan Xu, Peipei Wang, Ruilong Liu, Jingkun Tang Jun 2018

Train Energy Saving Operation Based On Simulated Annealing Algorithm, Liu Wei, Jiaxuan Xu, Peipei Wang, Ruilong Liu, Jingkun Tang

Journal of System Simulation

Abstract: For the timing and energy saving algorithm of urban railway, the train operation iterative process was analyzed by dividing the operation intervals to meet the requirements of the subway trains timing energy saving operation. The differentiation was adopted to establish the train operation iterative model, and as a result the timing energy saving problem was transformed into the solution of train output using coefficient sequence. An optimization solving method based on simulated annealing algorithm was proposed and the algorithm was implemented using MFC program. Three intervals of Shanghai Metro Line 3 were selected and the solution of the train …

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Event-Triggered Non-Fragile H∞ State Estimation For Fuzzy Time-Delay Neural Networks, Yanqin Wang, Weijian Ren Jun 2018

Event-Triggered Non-Fragile H∞ State Estimation For Fuzzy Time-Delay Neural Networks, Yanqin Wang, Weijian Ren

Journal of System Simulation

Abstract: For a class of fuzzy neural networks with randomly occurring time-varying delays and randomly data packet loss, an event-triggered non-fragile H∞ state estimator is designed. The event-triggered condition is introduced to determine whether the signal is transmitted or not, so as to reduce the occupation rate of network resource. Random variables of Gaussian distribution and the multiplicative gain uncertainties are adopted to construct the non-fragile state estimator with randomly occurring gain variations. By constructing Lyapunov function, and via stochastic computation and linear matrix inequality technique, the sufficient conditions for the existence of non-fragile estimators are obtained, which guarantee …

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Emergency Condition Selection Based On Tcp-Nets, Weihong Liu, Zheng Xiao, Cheng Chen, Li Qiao Jun 2018

Emergency Condition Selection Based On Tcp-Nets, Weihong Liu, Zheng Xiao, Cheng Chen, Li Qiao

Journal of System Simulation

Abstract: The representative or relative important emergency conditions need to be selected for making well-directed emergency plans. The quantitative method is normally used to select emergency conditions, but it requires users to specify the weight of every attribute, which does not conform to the users' habit. A qualitative method for emergency condition selection is put forward which includes two steps: for the first step, TCP-nets is adopted to describe users' requirements; and for the second step, the most important emergency conditions are selected based on TCP-nets. The effectiveness of the method is proved, and the efficiency is verified by experiments …

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Cooperative Target Recognition With Multiple Features Judgment, Guopeng Sun, Xiangyang Hao, Zhenjie Zhang, Pengrui Yan Jun 2018

Cooperative Target Recognition With Multiple Features Judgment, Guopeng Sun, Xiangyang Hao, Zhenjie Zhang, Pengrui Yan

Journal of System Simulation

Abstract: For solving cooperative target recognition problem in visual navigation, a fast and accurate algorithm based on progressive judgment of multiple features is proposed. The image is processed and judged by multiple features including image contours, Hu moment invariants and FAST corners. The non-target areas are eliminated and the real targets are obtained. In the process, algorithm is improved and some accelerated strategies are adopted to meet real-time requirements. Experiments show that the proposed algorithm can identify cooperative target robustly and adaptively with different distances, different angles and environment disturbance.

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Test Data Compression Scheme For Fast Search Best Rational Approximate Fraction, Haifeng Wu, Wenfa Zhan, Yifei Cheng Jun 2018

Test Data Compression Scheme For Fast Search Best Rational Approximate Fraction, Haifeng Wu, Wenfa Zhan, Yifei Cheng

Journal of System Simulation

Abstract: Rapid growth of test data volume becomes a major factor for test time and manufacturing cost increasing. To reduce test data volume, a code-based compression scheme with fast search best rational approximate fraction is presented. The run-length data is converted into floating point numbers; and the equal best rational approximate fractions of floating point numbers is searched quickly; the appearing law of run-length data in the form of integer numerator and integer denominator is stored instead of storing run-length data directly. This scheme is compatible with traditional code-based methods. It also has simple compression and decompression protocol, good compression …

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Route Planning For Vessel Based On Dynamic Complexity Map, Zhe Du, Yuanqiao Wen, Huang Liang, Chunhui Zhou, Changshi Xiao Jun 2018

Route Planning For Vessel Based On Dynamic Complexity Map, Zhe Du, Yuanqiao Wen, Huang Liang, Chunhui Zhou, Changshi Xiao

Journal of System Simulation

Abstract: Aiming at multiple mobile objects in complex navigation environment, a route planning method based on the dynamic complexity map is proposed. According to the theory of complexity measurement, a dynamic complexity map is established. By taking advantage of the idea of A * algorithm, the complexity value is taken as an actual cost and the Euclidean Distance from current point to the target is taken as a heuristic costs. Considering the ship dimensions, the channel boundary constraint function is added. The experimental results show that on the premises of satisfying the constraint of ship dimensions, the planned route …

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Effect Of Interfacial Curvature On Drag Reduction Of Superhydrophobic Microchannels, Chunxi Li, Zhang Shuo, Xuemin Ye Jun 2018

Effect Of Interfacial Curvature On Drag Reduction Of Superhydrophobic Microchannels, Chunxi Li, Zhang Shuo, Xuemin Ye

Journal of System Simulation

Abstract: The two-dimensional fluid flow in superhydrophobic microchannels with transverse grooves was numerically simulated with Fluent to investigate the impact of the liquid-gas interface curvature on the effective slip behavior in the laminar regime. The effects of shear-free fraction, normalized periodic cell length and Reynolds number on the normalized slip length and pressure drop reduction are also examined. The results show that as protrusion angle increases, the normalized slip length and pressure drop reduction exhibit with single-hump variations. When θ=θopt, increments in the normalized slip length and pressure drop reduction tend to be greater as shear-free …

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Imu Single-Axis Rotation Method And Error Analysis Of Modulation Inertial Navigation System, Sun Wei, Ruibao Li, Zhang Yuan, Yang Dan Jun 2018

Imu Single-Axis Rotation Method And Error Analysis Of Modulation Inertial Navigation System, Sun Wei, Ruibao Li, Zhang Yuan, Yang Dan

Journal of System Simulation

Abstract: Aiming at the problem that inertial device bias has an influence on the improvement of system precision, a single axis error modulation scheme whose sensitive axis is misalignment with rotation axis which can continuously rotate in clockwise and counterclockwise is proposed. Based on the same level precision of inertial components in IMU, the IMU is installed on rotation mechanism with non-coincidence. The symmetric part of inertial device deviation can be compensated by the positive and negative cancellation of the device deviation in the rotation axis direction and the rotation modulation in the vertical plane of the rotary axis. The …

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A Qualitative Research On Marketing And Sales In The Artificial Intelligence Age, Yin Yang, Keng Siau May 2018

A Qualitative Research On Marketing And Sales In The Artificial Intelligence Age, Yin Yang, Keng Siau

Research Collection School Of Computing and Information Systems

The age of artificial intelligence is here! Artificial Intelligence, robotics, machine learning, and automation are impacting the field of marketing and sales in an unprecedented way. In this study, the qualitative research methodology will be used to better understand the revolution and evolution of marketing and sales field in the AI age. Multiple case studies will be performed in various marketing and sales units in different organizations. This research is of value to both academics and practitioners as it aims to provide a detailed analysis and documentation of the changes in marketing and sales functionalities and job markets as AI …

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Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels Apr 2018

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …

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Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen Apr 2018

Findings Of A User Study Of Automatically Generated Personas, Joni Salminen, Haewoon Kwak, Jisun An, Soon-Gyo Jung, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We report findings and implications from a semi-naturalistic user study of a system for Automatic Persona Generation (APG) using large-scale audience data of an organization's social media channels conducted at the workplace of a major international corporation. Thirteen participants from a range of positions within the company engaged with the system in a use case scenario. We employed a variety of data collection methods, including mouse tracking and survey data, analyzing the data with a mixed method approach. Results show that having an interactive system may aid in keeping personas at the forefront while making customer-centric decisions and indicate that …

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Design And Implementation Of An Artificial Neural Network Controller For Quadrotor Flight In Confined Environment, Ahmed Mekky Apr 2018

Design And Implementation Of An Artificial Neural Network Controller For Quadrotor Flight In Confined Environment, Ahmed Mekky

Mechanical & Aerospace Engineering Theses & Dissertations

Quadrotors offer practical solutions for many applications, such as emergency rescue, surveillance, military operations, videography and many more. For this reason, they have recently attracted the attention of research and industry. Even though they have been intensively studied, quadrotors still suffer from some challenges that limit their use, such as trajectory measurement, attitude estimation, obstacle avoidance, safety precautions, and land cybersecurity. One major problem is flying in a confined environment, such as closed buildings and tunnels, where the aerodynamics around the quadrotor are affected by close proximity objects, which result in tracking performance deterioration, and sometimes instability. To address this …

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Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak Mar 2018

Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak

Research Collection School Of Computing and Information Systems

To more effectively convey relevant information to end users of persona profiles, we conducted a user study consisting of 29 participants engaging with three persona layout treatments. We were interested in confusion engendered by the treatments on the participants, and conducted a within-subjects study in the actual work environment, using eye-tracking and talk-aloud data collection. We coded the verbal data into classes of informativeness and confusion and correlated it with fixations and durations on the Areas of Interests recorded by the eye-tracking device. We used various analysis techniques, including Mann-Whitney, regression, and Levenshtein distance, to investigate how confused users differed …

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Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu Mar 2018

Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

The feasibility of using vibration energy harvesting (VEH) as an energy-efficient receiver for short-range acoustic data communication has been investigated recently. When data was encoded in acoustic signal within the energy harvesting frequency band and transmitted through a speaker, a VEH receiver was capable of decoding the data by processing the harvested energy signal. Although previous work created new opportunities for simultaneous energy harvesting and communication using the same hardware, the communication makes annoying sounds as the energy harvesting frequency band lies within the sensitive region of human auditory system. In this work, we present a novel modulation scheme to …

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Vision-Based Assistive Indoor Localization, Feng Hu Feb 2018

Vision-Based Assistive Indoor Localization, Feng Hu

Dissertations, Theses, and Capstone Projects

An indoor localization system is of significant importance to the visually impaired in their daily lives by helping them localize themselves and further navigate an indoor environment. In this thesis, a vision-based indoor localization solution is proposed and studied with algorithms and their implementations by maximizing the usage of the visual information surrounding the users for an optimal localization from multiple stages. The contributions of the work include the following: (1) Novel combinations of a daily-used smart phone with a low-cost lens (GoPano) are used to provide an economic, portable, and robust indoor localization service for visually impaired people. (2) …

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Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini Jan 2018

Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini

Electronic Theses and Dissertations

Social (or Sociable) robots are designed to interact with people in a natural and interpersonal manner. They are becoming an integrated part of our daily lives and have achieved positive outcomes in several applications such as education, health care, quality of life, entertainment, etc. Despite significant progress towards the development of realistic social robotic agents, a number of problems remain to be solved. First, current social robots either lack enough ability to have deep social interaction with human, or they are very expensive to build and maintain. Second, current social robots have yet to reach the full emotional and social …

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Energy Slices: Benchmarking With Time Slicing, Katarina Grolinger, Hany F. Elyamany, Wilson Higashino, Miriam Am Capretz, Luke Seewald Jan 2018

Energy Slices: Benchmarking With Time Slicing, Katarina Grolinger, Hany F. Elyamany, Wilson Higashino, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Benchmarking makes it possible to identify low-performing buildings, establishes a baseline for measuring performance improvements, enables setting of energy conservation targets, and encourages energy savings by creating a competitive environment. Statistical approaches evaluate building energy efficiency by comparing measured energy consumption to other similar buildings typically using annual measurements. However, it is important to consider different time periods in benchmarking because of differences in their consumption patterns. For example, an office can be efficient during the night, but inefficient during operating hours due to occupants’ wasteful behavior. Moreover, benchmarking studies often use a single regression model for different building categories. …

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Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery Jan 2018

Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery

Doctoral Dissertations

"The rapid progress and development in machine-learning algorithms becomes a key factor in determining the future of humanity. These algorithms and techniques were utilized to solve a wide spectrum of problems extended from data mining and knowledge discovery to unsupervised learning and optimization. This dissertation consists of two study areas. The first area investigates the use of reinforcement learning and adaptive critic design algorithms in the field of power grid control. The second area in this dissertation, consisting of three papers, focuses on developing and applying clustering algorithms on biomedical data. The first paper presents a novel modelling approach for …

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Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez Jan 2018

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

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Review Of Deep Learning Methods In Robotic Grasp Detection, Shehan Caldera, Alexander Rassau, Douglas Chai Jan 2018

Review Of Deep Learning Methods In Robotic Grasp Detection, Shehan Caldera, Alexander Rassau, Douglas Chai

Research outputs 2014 to 2021

For robots to attain more general-purpose utility, grasping is a necessary skill to master. Such general-purpose robots may use their perception abilities to visually identify grasps for a given object. A grasp describes how a robotic end-effector can be arranged to securely grab an object and successfully lift it without slippage. Traditionally, grasp detection requires expert human knowledge to analytically form the task-specific algorithm, but this is an arduous and time-consuming approach. During the last five years, deep learning methods have enabled significant advancements in robotic vision, natural language processing, and automated driving applications. The successful results of these methods …

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Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan Jan 2018

Resource Optimization In Wireless Sensor Networks For An Improved Field Coverage And Cooperative Target Tracking, Husam Sweidan

Dissertations, Master's Theses and Master's Reports

There are various challenges that face a wireless sensor network (WSN) that mainly originate from the limited resources a sensor node usually has. A sensor node often relies on a battery as a power supply which, due to its limited capacity, tends to shorten the life-time of the node and the network as a whole. Other challenges arise from the limited capabilities of the sensors/actuators a node is equipped with, leading to complication like a poor coverage of the event, or limited mobility in the environment. This dissertation deals with the coverage problem as well as the limited power and …

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Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum Jan 2018

Crop Height Estimation With Unmanned Aerial Vehicles, Carrick Detweiler, David Anthony, Sebastian Elbaum

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two-dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed …

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Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi Jan 2018

Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi

Electronic Theses and Dissertations

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …

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Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr Dec 2017

Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr

Journal of International Technology and Information Management

The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …

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