Search results for: moving object tracking

Authors: Alaa A. Osman, Amgad M. Bayoumy, Ismail El baialy, Osama E. Abdellatif, Essam E. Khallil

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In this paper, a numerical simulation of a finned store separating from a wing-pylon configuration has been studied and validated. A dynamic unstructured tetrahedral mesh approach is accomplished by using three grid sizes to numerically solving the discretized three dimensional, inviscid and compressible Euler equations. The method used for computations of separation of an external store assuming quasi-steady flow condition. Computations of quasi-steady flow have been directly coupled to a six degree-offreedom (6DOF) rigid-body motion code to generate store trajectories. The pressure coefficients at four different angular cuts and time histories of various trajectory parameters and wing pressure distribution during the store separation are compared for every grid size with published experimental data.

Keywords: CFD Modelling, Quasi-steady Flow, Moving-body Trajectories, Transonic Store Separation, Moving-body Trajectories.

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Authors: Miklos Taliga

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In the present case study we examined the development and testing methods of systems that contain safety-critical elements in different industrial fields. Consequentially, we observed the classical object-oriented development and testing environment, as both medical technology and automobile industry approaches the development of safety critical elements that way. Subsequently, we examined model-based development. We introduce the quality parameters that define development and testing. While taking modern agile methodology (scrum) into consideration, we examined whether and to what extent the methodologies we found fit into this environment.

Keywords: Safety-critical elements, quality management, unit verification, model base testing, agile methods, scrum, metamodel, object-oriented programming, field specific modelling, sprint, user story, UML Standard.

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Authors: Fathi Taibi

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The abnormal increase in the number of applications available for download in Android markets is a good indication that they are being reused. However, little is known about their real reusability potential. A considerable amount of these applications is reported as having a poor quality or being malicious. Hence, in this paper, an approach to measure the reusability potential of classes in Android applications is proposed. The approach is not meant specifically for this particular type of applications. Rather, it is intended for Object-Oriented (OO) software systems in general and aims also to provide means to discard the classes of low quality and defect prone applications from being reused directly through inheritance and instantiation. An empirical investigation is conducted to measure and rank the reusability potential of the classes of randomly selected Android applications. The results obtained are thoroughly analyzed in order to understand the extent of this potential and the factors influencing it.

Keywords: Reusability, Software Quality Factors, Software Metrics, Empirical Investigation, Object-Oriented Software, Android Applications.

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Authors: D Sudheer Reddy, N Gopal Reddy, P V Radhadevi, J Saibaba, Geeta Varadan

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Smoothing or filtering of data is first preprocessing step for noise suppression in many applications involving data analysis. Moving average is the most popular method of smoothing the data, generalization of this led to the development of Savitzky-Golay filter. Many window smoothing methods were developed by convolving the data with different window functions for different applications; most widely used window functions are Gaussian or Kaiser. Function approximation of the data by polynomial regression or Fourier expansion or wavelet expansion also gives a smoothed data. Wavelets also smooth the data to great extent by thresholding the wavelet coefficients. Almost all smoothing methods destroys the peaks and flatten them when the support of the window is increased. In certain applications it is desirable to retain peaks while smoothing the data as much as possible. In this paper we present a methodology called as peak-wise smoothing that will smooth the data to any desired level without losing the major peak features.

Keywords: smoothing, moving average, peakwise smoothing, spatialdensity models, planar shape models, wavelets.

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Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: Biophysical data, flexibility of urban, livability, next urbanization, spatial application.

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Authors: Feng Ge, Tiecheng Liu, Song Wang, Joachim Stahl

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This paper presents a novel template-based method to detect objects of interest from real images by shape matching. To locate a target object that has a similar shape to a given template boundary, the proposed method integrates three components: contour grouping, partial shape matching, and boundary verification. In the first component, low-level image features, including edges and corners, are grouped into a set of perceptually salient closed contours using an extended ratio-contour algorithm. In the second component, we develop a partial shape matching algorithm to identify the fractions of detected contours that partly match given template boundaries. Specifically, we represent template boundaries and detected contours using landmarks, and apply a greedy algorithm to search the matched landmark subsequences. For each matched fraction between a template and a detected contour, we estimate an affine transform that transforms the whole template into a hypothetic boundary. In the third component, we provide an efficient algorithm based on oriented edge lists to determine the target boundary from the hypothetic boundaries by checking each of them against image edges. We evaluate the proposed method on recognizing and localizing 12 template leaves in a data set of real images with clutter back-grounds, illumination variations, occlusions, and image noises. The experiments demonstrate the high performance of our proposed method1.

Keywords: Object detection, shape matching, contour grouping.

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Talal H. Alzanki

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This paper presents a hybrid fuzzy logic control strategy for a unicycle trajectory following robot on irregular terrains. In literature, researchers have presented the design of path tracking controllers of mobile robots on non-frictional surface. In this work, the robot is simulated to drive on irregular terrains with contrasting frictional profiles of peat and rough gravel. A hybrid fuzzy logic controller is utilised to stabilise and drive the robot precisely with the predefined trajectory and overcome the frictional impact. The controller gains and scaling factors were optimised using spiral dynamics optimisation algorithm to minimise the mean square error of the linear and angular velocities of the unicycle robot. The robot was simulated on various frictional surfaces and terrains and the controller was able to stabilise the robot with a superior performance that is shown via simulation results.

Keywords: Fuzzy logic control, mobile robot, trajectory tracking, spiral dynamic algorithm.

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Authors: Jehad Al Dallal, Paul Sorenson

Abstract:

An application framework provides a reusable design and implementation for a family of software systems. Application developers extend the framework to build their particular applications using hooks. Hooks are the places identified to show how to use and customize the framework. Hooks define Framework Interface Classes (FICs) and their possible specifications, which helps in building reusable test cases for the implementations of these classes. In applications developed using gray-box frameworks, FICs inherit framework classes or use them without inheritance. In this paper, a test-case generation technique is extended to build test cases for FICs built for gray-box frameworks. A tool is developed to automate the introduced technique.

Keywords: Class testing, object-oriented framework, reusable test case.

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Authors: Siddhartha Bhattacharyya, Paramartha Dutta, Ujjwal Maulik, Prashanta Kumar Nandi

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A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.

Keywords: Beta activation function, fuzzy cardinality, multilayer self organizing neural network, object extraction,

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Authors: Shiuh-Jer Huang, Su-Shean Chen, Sheam-Chyun Lin

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Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.

Keywords: Balance control, speed control, intelligent controller and two wheel inverted pendulum.

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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Authors: Chun-Yao Lee, Yi-Xing Shen, Jung-Cheng Cheng, Yi-Yin Li, Chih-Wen Chang

Abstract:

This paper proposes the method combining artificial neural network (ANN) with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. First, the measurements of wind speed, rotor speed of wind power generator and output power of wind power generator are applied to train artificial neural network and to estimate the wind speed. Second, the method mentioned above is applied to estimate and control the optimal rotor speed of the wind turbine so as to output the maximum power. Finally, the result reveals that the control system discussed in this paper extracts the maximum output power of wind generator within the short duration even in the conditions of wind speed and load impedance variation.

Keywords: Maximum power point tracking, artificial neuralnetwork, particle swarm optimization.

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Authors: Anirban Chowdhury, Sougata Karmakar, Swathi Matta Reddy, Sanjog J., Subrata Ghosh, Debkumar Chakrabarti

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Brand name plays a vital role for in-shop buying behavior of consumers and mutated brand name may affect the selling of leading branded products. In Indian market, there are many products with mutated brand names which are either orthographically or phonologically similar. Due to presence of such products, Indian consumers very often fall under confusion when buying some regularly used stuff. Authors of the present paper have attempted to demonstrate relationship between less attention and false recognition of mutated brand names during a product selection process. To achieve this goal, visual attention study was conducted on 15 male college students using eye-tracker against a mutated brand name and errors in recognition were noted using questionnaire. Statistical analysis of the acquired data revealed that there was more false recognition of mutated brand name when less attention was paid during selection of favorite product. Moreover, it was perceived that eye tracking is an effective tool for analyzing false recognition of brand name mutation.

Keywords: Brand Name Mutation, Consumer Behavior, Visual Attention, Orthography

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Authors: Junior B. N. Adohinzin, Ling Xu

Abstract:

Nitrogen is among the main nutrients encouraging the growth of organic matter and algae which cause eutrophication in water bodies. Therefore, its removal from wastewater has become a worldwide emerging concern. In this research, an innovative Membrane Bioreactor (MBR) system named “moving bed membrane bioreactor (MBMBR)” was developed and investigated under intermittently-aerated mode for simultaneous removal of organic carbon and nitrogen.

Results indicated that the variation of the intermittently aerated duration did not have an apparent impact on COD and NH₄⁺–N removal rate, yielding the effluent with average COD and NH₄⁺–N removal efficiency of more than 92 and 91% respectively. However, in the intermittently aerated cycle of (continuously aeration/0s mix), (aeration 90s/mix 90s) and (aeration 90s/mix 180s); the average TN removal efficiency was 67.6%, 69.5% and 87.8% respectively. At the same time, their nitrite accumulation rate was 4.5%, 49.1% and 79.4% respectively. These results indicate that the intermittently aerated mode is an efficient way to controlling the nitrification to stop at nitrition; and also the length of anoxic duration is a key factor in improving TN removal.

Keywords: Membrane bioreactor (MBR), Moving bed biofilm reactor (MBBR), Nutrients removal, Simultaneous nitrification and denitrification.

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Authors: Doraid Dalalah

Abstract:

A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Keywords: Mobile robot, Path Planning, Mesh, Potential field.

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Authors: N. Drir, L. Barazane, M. Loudini

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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.

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Authors: Elhameh Narimani, Mikhail Sorin, Philippe Micheau, Hakim Nesreddine

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Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

Keywords: Coefficient of performance, ejector refrigeration system, exergy efficiency, heat exchangers modeling, moving boundary method.

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Authors: Guoyuan Qi , Yskandar Hamam, Barend Jacobus van Wyk, Shengzhi Du

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The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Keywords: Forecast, model-free predictor, prediction, time series

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Authors: N. Ouldcherchali, M. S. Boucherit, L. Barazane, A. Morsli

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In this study, we proposed two techniques to track the maximum power point (MPPT) of a photovoltaic system. The first is an intelligent control technique, and the second is robust used for variable structure system. In fact the characteristics I-V and P–V of the photovoltaic generator depends on the solar irradiance and temperature. These climate changes cause the fluctuation of maximum power point; a maximum power point tracking technique (MPPT) is required to maximize the output power. For this we have adopted a control by fuzzy logic (FLC) famous for its stability and robustness. And a Siding Mode Control (SMC) widely used for variable structure system. The system comprises a photovoltaic panel (PV), a DC-DC converter, which is considered as an adaptation stage between the PV and the load. The modelling and simulation of the system is developed using MATLAB/Simulink. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or it is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: Fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: F. Rotaru, S. Bejinariu, C. D. Niţâ, R. Luca, I. Pâvâloi, C. Lazâr

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The paper presents a technique suitable in robot vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods are based on the correspondence of image features established at a training step and exactly the same image features extracted at the execution step, for a different object pose. When such a correspondence is not feasible because of the lack of specific features a new method is proposed. In the first step the method computes from two views the 3D pose of feature points. Subsequently, using a registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted at the training phase. The result is a Euclidean transform which have to be used by robot head for reorientation at execution step.

Keywords: features correspondence, registration algorithm, robot vision, triangulation method.

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Authors: Anita Kéri

Abstract:

Higher education marketing has been a widely researched field in recent years. Due to the increasing competition among higher education institutions worldwide, it has become crucial to target foreign students with effective marketing tools. Online marketing tools became central to attracting, retaining, and satisfying the needs of foreign students. Therefore, the aim of the current study is to reveal how the online marketing tools of a Hungarian university are perceived visually by its first-year foreign students, with special emphasis on the university webpage content. Eye-camera tracking and retrospective think aloud interviews were used to measure visual perceptions. Results show that freshmen students remember those online marketing content more that have familiar content on them. Pictures of real-life students and their experiences attract students’ attention more, and they also remember information on these webpage elements more, compared to designs with stock photos. This research uses eye camera tracking in the field of higher education marketing, thereby providing insight into the perception of online higher education marketing for foreign students.

Keywords: Higher education, marketing, eye-camera, visual perception.

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Authors: A. Hol

Abstract:

Electronic mediums such as websites, feeds, blogs and social media sites are on a daily basis influencing our decision making, are improving our productivity and are shaping futures of many consumers and service/product providers. This research identifies that both customers and business providers heavily rely on smart phone applications. Based on this, mobile applications available on iTunes store were studied. It was identified that fruit and vegetable related applications used by consumers can broadly be categorized into purchase applications, diaries, tracking health applications, trip farm location and cooking applications. On the other hand, applications used by farmers can broadly be classified as: weather tracking, pests / fertilizer applications and general social media applications such as Facebook. To blur this farmer-consumer application divide, our research utilizes Context Specific eTransformation Framework and based on it identifies characteristic future consumer-farmer applications will need to have so that the current divide can be narrowed and consequently better farmerconsumer supply chain link established.

Keywords: Smart Phone Applications, SME, Farmers, Consumer, Fruit and Vegetable, Technology, Business Innovation.

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Authors: Alexandre Rabaseda, Emelie Seguin, Marc Doumit

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Human mobility exoskeletons have been in development for several years and are becoming increasingly efficient. Unfortunately, user comfort was not always a priority design criterion throughout their development. To further improve this technology, exoskeletons should operate and deliver assistance without causing discomfort to the user. For this, improvements are necessary from an ergonomic point of view. The device’s control method is important when endeavoring to enhance user comfort. Exoskeleton or rehabilitation device controllers use methods of control called interaction controls (admittance and impedance controls). This paper proposes an extended version of an admittance controller to enhance user comfort. The control method used consists of adding an inner loop that is controlled by a proportional-integral-derivative (PID) controller. This allows the interaction force to be kept as close as possible to the desired force trajectory. The force-tracking admittance controller modifies the actuation force of the system in order to follow both the desired motion trajectory and the desired relative force between the user and the exoskeleton.

Keywords: Mobility assistive device, exoskeleton, force-tracking admittance controller, user comfort.

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Authors: A. Sarchami, N. Ashgriz, M. Kwee

Abstract:

Threedimensional numerical simulations are conducted on a full scale CANDU Moderator and Transient variations of the temperature and velocity distributions inside the tank are determined. The results show that the flow and temperature distributions inside the moderator tank are three dimensional and no symmetry plane can be identified.Competition between the upward moving buoyancy driven flows and the downward moving momentum driven flows, results in the formation of circulation zones. The moderator tank operates in the buoyancy driven mode and any small disturbances in the flow or temperature makes the system unstable and asymmetric. Different types of temperature fluctuations are noted inside the tank: (i) large amplitude are at the boundaries between the hot and cold (ii) low amplitude are in the core of the tank (iii) high frequency fluctuations are in the regions with high velocities and (iv) low frequency fluctuations are in the regions with lower velocities.

Keywords: Bruce, Fluctuations, Numerical, Temperature, Thermal hydraulics

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Authors: Nhon Van Do, Nam Hoai Le, Vien Chan Luong

Abstract:

The Model for Knowledge Base of Computational Objects (KBCO model) has been successfully applied to represent the knowledge of human like Plane Geometry, Physical, Calculus. However, the original model cannot easyly apply in inorganic chemistry field because of the knowledge specific problems. So, the aim of this article is to introduce how we extend the Computional Object (Com-Object) in KBCO model, kinds of fact, problems model, and inference algorithms to develop a program for solving problems in inorganic chemistry. Our purpose is to develop the application that can help students in their study inorganic chemistry at schools. This application was built successful by using Maple, C# and WPF technology. It can solve automatically problems and give human readable solution agree with those writting by students and teachers.

Keywords: artificial intelligence, automated problem solving, knowledge base system, knowledge representation, reasoning strategy, education software/educational applications.

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Authors: Jehad Al Dallal, Paul Sorenson

Abstract:

An application framework provides a reusable design and implementation for a family of software systems. Frameworks are introduced to reduce the cost of a product line (i.e., family of products that share the common features). Software testing is a time consuming and costly ongoing activity during the application software development process. Generating reusable test cases for the framework applications at the framework development stage, and providing and using the test cases to test part of the framework application whenever the framework is used reduces the application development time and cost considerably. Framework Interface Classes (FICs) are classes introduced by the framework hooks to be implemented at the application development stage. They can have reusable test cases generated at the framework development stage and provided with the framework to test the implementations of the FICs at the application development stage. In this paper, we conduct a case study using thirteen applications developed using three frameworks; one domain oriented and two application oriented. The results show that, in general, the percentage of the number of FICs in the applications developed using domain frameworks is, on average, greater than the percentage of the number of FICs in the applications developed using application frameworks. Consequently, the reduction of the application unit testing time using the reusable test cases generated for domain frameworks is, in general, greater than the reduction of the application unit testing time using the reusable test cases generated for application frameworks.

Keywords: FICs, object-oriented framework, object-orientedframework application, software testing.

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Authors: Kamil Aida-zade, C. Ardil

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In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.

Keywords: dynamic objects, ordinary differential equations, multipoint unshared edge conditions, quadratic programming, conditions shift

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Authors: Javad Khazaei, Rick S. Blum

Abstract:

Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: Consensus tracking, distributed control, model-free control, sparse identification of dynamical systems.

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Authors: M Nayeripour, H. Khorsand, A. Roosta, T. Niknam, E. Azad

Abstract:

Series compensators have been used for many years, to increase the stability and load ability of transmission line. They compensate retarded or advanced volt drop of transmission lines by placing advanced or retarded voltage in series with them to compensate the effective reactance, which cause to increase load ability of transmission lines. In this paper, two method of fuzzy controller, based on power reference tracking and impedance reference tracking have been developed on TCSC controller in order to increase load ability and improving power oscillation damping of system. In these methods, fire angle of thyristors are determined directly through the special Rule-bases with the error and change of error as the inputs. The simulation results of two area four- machines power system show the good performance of power oscillation damping in system. Comparison of this method with classical PI controller shows the increasing speed of system response in power oscillation damping.

Keywords: TCSC, Two area network, Fuzzy controller, Power oscillation damping.

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