Search results for: real estate company

Authors: A. Y. Bani Hashim, N. S. A. Ramdan

Abstract:

Inconsistency in manual inspection is real because humans get tired after some time. Recent trends show that automatic inspection is more appealing for mass production inspections. In such as a case, a robot manipulator seems the best candidate to run a dynamic visual inspection. The purpose of this work is to estimate the optimum workspace where a robot manipulator would perform a visual inspection process onto a work piece where a camera is attached to the end effector. The pseudo codes for the planned path are derived from the number of tool transit points, the delay time at the transit points, the process cycle time, and the configuration space that the distance between the tool and the work piece. It is observed that express start and swift end are acceptable in a robot program because applicable works usually in existence during these moments. However, during the mid-range cycle, there are always practical tasks programmed to be executed. For that reason, it is acceptable to program the robot such as that speedy alteration of actuator displacement is avoided. A dynamic visual inspection system using a robot manipulator seems practical for a work piece with a complex shape.

Keywords: Robot manipulator, Visual inspection, Work piece, Trajectory planning.

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Authors: Hyun-Koo Kim, Sagong Kuk, MinKwan Kim, Ho-Youl Jung

Abstract:

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, to effectively extract spotlight of interest, a segmentation process based on automatic multi-level threshold method is applied on the road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process based on light tracking and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with near infrared mono-camera and tested it in the urban and rural roads. Through the test, classification performances are above 97% of true positive rate evaluated on real-time environment. Our method also has good performance in the case of clear, fog and rain weather.

Keywords: Assistance Driving System, Multi-level Threshold Method, Near Infrared Mono Camera, Nighttime Vehicle Detection.

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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Authors: Mohammad Jafarifar

Abstract:

Multiphase Induction Machine (IM) is normally controlled using rotor field oriented vector control. Under phase(s) loss, the machine currents can be optimally controlled to satisfy certain optimization criteria. In this paper we discuss the performance of double manifold sliding mode observer (DM-SMO) in Sensorless control of multiphase induction machine under unsymmetrical condition (one phase loss). This observer is developed using the IM model in the stationary reference frame. DM-SMO is constructed by adding extra feedback term to conventional single mode sliding mode observer (SM-SMO) which proposed in many literature. This leads to a fully convergent observer that also yields an accurate estimate of the speed and stator currents. It will be shown by the simulation results that the estimated speed and currents by the method are very well and error between real and estimated quantities is negligible. Also parameter sensitivity analysis shows that this method is rather robust against parameter variation.

Keywords: Multiphase induction machine, field oriented control, sliding mode, unsymmetrical condition, manifold.

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Authors: Jin Hou, Xia Wang, Fang Xu, Viet Dung Nguyen, Ling Wu

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There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.

Keywords: personalized avatar, mutiple natural luanguage processing, social backgrounds, anmimation, human computer interaction

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Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam

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The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.

Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.

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Authors: Ali Alzaabi, Georges Alquié, Hussain Tassadaq, Ali Seba

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This article presents the developments of efficient algorithms for tablet copies comparison. Image recognition has specialized use in digital systems such as medical imaging, computer vision, defense, communication etc. Comparison between two images that look indistinguishable is a formidable task. Two images taken from different sources might look identical but due to different digitizing properties they are not. Whereas small variation in image information such as cropping, rotation, and slight photometric alteration are unsuitable for based matching techniques. In this paper we introduce different matching algorithms designed to facilitate, for art centers, identifying real painting images from fake ones. Different vision algorithms for local image features are implemented using MATLAB. In this framework a Table Comparison Computer Tool “TCCT" is designed to facilitate our research. The TCCT is a Graphical Unit Interface (GUI) tool used to identify images by its shapes and objects. Parameter of vision system is fully accessible to user through this graphical unit interface. And then for matching, it applies different description technique that can identify exact figures of objects.

Keywords: Harris Extraction and SIFT Matching

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Authors: Maryam Hsaini, Mostafa Nouri-Baygi

Abstract:

A critical problem in wireless sensor networks is limited battery and memory of nodes. Therefore, each node in the network could maintain only a subset of its neighbors to communicate with. This will increase the battery usage in the network because each packet should take more hops to reach its destination. In order to tackle these problems, spanner graphs are defined. Since each node has a small degree in a spanner graph and the distance in the graph is not much greater than its actual geographical distance, spanner graphs are suitable candidates to be used for the topology of a wireless sensor network. In this paper, we study Yao graphs and their behavior for a randomly selected set of points. We generate several random point sets and compare the properties of their Yao graphs with the complete graph. Based on our data sets, we obtain several charts demonstrating how Yao graphs behave for a set of randomly chosen point set. As the results show, the stretch factor of a Yao graph follows a normal distribution. Furthermore, the stretch factor is in average far less than the worst case stretch factor proved for Yao graphs in previous results. Furthermore, we use Yao graph for a realistic point set and study its stretch factor in real world.

Keywords: Wireless sensor network, spanner graph, Yao Graph.

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Authors: Wajeeh Daher, Nimer Baya'a

Abstract:

High Order Thinking Skills (HOTS) are suggested today as essential for the cognitive development of students and as preparing them for real life skills. Teachers are encouraged to use HOTS activities in the classroom to help their students develop higher order skills and deep thinking. So it is essential to prepare preservice teachers to write and use HOTS activities for their students. This paper describes a model for integrating HOTS activities with GeoGebra in pre-service teachers’ preparation. This model describes four aspects of HOTS activities and working with them: activity components, preparation procedure, strategies and processes used in writing a HOTS activity and types of the HOTS activities. In addition, the paper describes the pre-service teachers' difficulties in preparing and working with HOTS activities, as well as their perceptions regarding the use of these activities and GeoGebra in the mathematics classroom. The paper also describes the contribution of a HOTS activity to pupils' learning of mathematics, where this HOTS activity was prepared and taught by one pre-service teacher.

Keywords: Higher order thinking, HOTS activities, pre-service teachers, teachers' preparation.

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Authors: Parisa Shooshtari, Gelareh Mohamadi, Behnam Molaee Ardekani, Mohammad Bagher Shamsollahi

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EEG signal is one of the oldest measures of brain activity that has been used vastly for clinical diagnoses and biomedical researches. However, EEG signals are highly contaminated with various artifacts, both from the subject and from equipment interferences. Among these various kinds of artifacts, ocular noise is the most important one. Since many applications such as BCI require online and real-time processing of EEG signal, it is ideal if the removal of artifacts is performed in an online fashion. Recently, some methods for online ocular artifact removing have been proposed. One of these methods is ARMAX modeling of EEG signal. This method assumes that the recorded EEG signal is a combination of EOG artifacts and the background EEG. Then the background EEG is estimated via estimation of ARMAX parameters. The other recently proposed method is based on adaptive filtering. This method uses EOG signal as the reference input and subtracts EOG artifacts from recorded EEG signals. In this paper we investigate the efficiency of each method for removing of EOG artifacts. A comparison is made between these two methods. Our undertaken conclusion from this comparison is that adaptive filtering method has better results compared with the results achieved by ARMAX modeling.

Keywords: Ocular Artifacts, EEG, Adaptive Filtering, ARMAX

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Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique

Abstract:

Simulation and modelling of Unmanned Aerial Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade, as next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.

Keywords: aerospace, flight control, FlightGear, communication, Simulink

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Authors: M. Kamal Elbokl, Negadi Kheira

Abstract:

Risk Evaluation is an important step in protecting your workers and your business, as well as complying with the law. It helps you focus on the risks that really matter in your workplace – the ones with the potential to cause real harm. We are in this paper introduce basics of risk assessment then we mention some of ways to risk evaluation by computer especially Monte Carlo simulation and Microsoft project.

We use Program Evaluation and Review Technique (PERT) to deal with Risks in Industrial Facilities in Evaluation and Assessment for this risk. Using PERT Technique in Microsoft Project by the PERT toolbar and using PERTMASTER Program with Primavera Program we evaluate many hazards and make calculations for that by mathematical equation to make right decisions. We define and calculate risk factor and risk severity to ranking the type of the risk then dealing with it using in that many ways like probability computation, curves, and tables. By introducing variables in the equation of functions in computer programs we calculate the risk in the time and the cost in general case and then mention some examples in industrial facilities field.

Keywords: Risk, Industrial Facilities, PERT, Monte Carlo Simulation.

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Authors: S. Amirhassan Monadjemi, Narges Zarrabi, Naser Neamatbakhsh

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As days go by, we hear more and more about HIV, Ebola, Bird Flu and other dreadful viruses which were unknown a few decades ago. In both detecting and fighting viral diseases ordinary methods have come across some basic and important difficulties. Vaccination is by a sense introduction of the virus to the immune system before the occurrence of the real case infection. It is very successful against some viruses (e.g. Poliomyelitis), while totally ineffective against some others (e.g. HIV or Hepatitis-C). On the other hand, Anti-virus drugs are mostly some tools to control and not to cure a viral disease. This could be a good motivation to try alternative treatments. In this study, some key features of possible physical-based alternative treatments for viral diseases are presented. Electrification of body parts or fluids (especially blood) with micro electric signals with adjusted current or frequency is also studied. The main approach of this study is to find a suitable energy field, with appropriate parameters that are able to kill or deactivate viruses. This would be a lengthy, multi-disciplinary research which needs the contribution of virology, physics, and signal processing experts. It should be mentioned that all the claims made by alternative cures researchers must be tested carefully and are not advisable at the time being.

Keywords: Alternative Cure, Viral disease, HIV, signals, energy filed.

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Authors: Sung Ho Ha, Seong Hyeon Joo, Eun Kyung Kwon

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Until recently, researchers have developed various tools and methodologies for effective clinical decision-making. Among those decisions, chest pain diseases have been one of important diagnostic issues especially in an emergency department. To improve the ability of physicians in diagnosis, many researchers have developed diagnosis intelligence by using machine learning and data mining. However, most of the conventional methodologies have been generally based on a single classifier for disease classification and prediction, which shows moderate performance. This study utilizes an ensemble strategy to combine multiple different classifiers to help physicians diagnose chest pain diseases more accurately than ever. Specifically the ensemble strategy is applied by using the integration of decision trees, neural networks, and support vector machines. The ensemble models are applied to real-world emergency data. This study shows that the performance of the ensemble models is superior to each of single classifiers.

Keywords: Diagnosis intelligence, ensemble approach, data mining, emergency department

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: Compliance Course, Corporate Training, Learner Behaviours, xAPI.

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Authors: Hsu-Yung Cheng, Victor Gau, Chih-Wei Huang, Jenq-Neng Hwang, Chih-Chang Yu

Abstract:

In order to achieve better road utilization and traffic efficiency, there is an urgent need for a travel information delivery mechanism to assist the drivers in making better decisions in the emerging intelligent transportation system applications. In this paper, we propose a relayed multicast scheme under heterogeneous networks for this purpose. In the proposed system, travel information consisting of summarized traffic conditions, important events, real-time traffic videos, and local information service contents is formed into layers and multicasted through an integration of WiMAX infrastructure and Vehicular Ad hoc Networks (VANET). By the support of adaptive modulation and coding in WiMAX, the radio resources can be optimally allocated when performing multicast so as to dynamically adjust the number of data layers received by the users. In addition to multicast supported by WiMAX, a knowledge propagation and information relay scheme by VANET is designed. The experimental results validate the feasibility and effectiveness of the proposed scheme.

Keywords: Intelligent Transportation Systems, RelayedMulticast, WiMAX, Vehicular Ad hoc Networks (VANET).

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

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In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Keywords: Distributes estimation, sensor networks, adaptive filter, IDLMS.

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: Parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems.

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Authors: Parviz Fattahi

Abstract:

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a Pareto approach to solve the multi objective flexible job shop scheduling problems is proposed. The objectives considered are to minimize the overall completion time (makespan) and total weighted tardiness (TWT). An effective simulated annealing algorithm based on the proposed approach is presented to solve multi objective flexible job shop scheduling problem. An external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the solution process. Numerical examples are used to evaluate and study the performance of the proposed algorithm. The proposed algorithm can be applied easily in real factory conditions and for large size problems. It should thus be useful to both practitioners and researchers.

Keywords: Flexible job shop, Scheduling, Hierarchical approach, simulated annealing, tabu search, multi objective.

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Authors: Dr. L.K. Singh, Dr. R. M. L, Riktesh Srivastava

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How to efficiently assign system resource to route the Client demand by Gateway servers is a tricky predicament. In this paper, we tender an enhanced proposal for autonomous recital of Gateway servers under highly vibrant traffic loads. We devise a methodology to calculate Queue Length and Waiting Time utilizing Gateway Server information to reduce response time variance in presence of bursty traffic. The most widespread contemplation is performance, because Gateway Servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system.

Keywords: Gateway Server, G/M/1 Queuing Model.

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Authors: Daniele Baldacci, Remo Pareschi

Abstract:

Augmented Reality and Augmented Intelligence are radically changing information technology. The path that starts from the keyboard and then, passing through milestones such as Siri, Alexa and other vocal avatars, reaches a more fluid and natural communication with computers, thus converting the dichotomy between man and machine into a harmonious interaction, now heads unequivocally towards a new IT paradigm, where holographic computing will play a key role. The OLOS® platform contributes substantially to this trend in that it infuses computers with human features, by transferring the gestures and expressions of persons of flesh and bones to anthropomorphic holographic interfaces which in turn will use them to interact with real-life humans. In fact, we could say, boldly but with a solid technological background to back the statement, that OLOS® gives reality to an altogether new entity, placed at the exact boundary between nature and technology, namely the holographic human being. Holographic humans qualify as the perfect carriers for the virtual reincarnation of characters handed down from history and tradition. Thus, they provide for an innovative and highly immersive way of experiencing our cultural heritage as something alive and pulsating in the present.

Keywords: Human-computer interfaces, holographic simulation, digital cinematography, interactive museum exhibits.

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Authors: RajPal Garg, Kapil Sharma, Rajive Kumar, R. K. Garg

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This paper presents a computational methodology based on matrix operations for a computer based solution to the problem of performance analysis of software reliability models (SRMs). A set of seven comparison criteria have been formulated to rank various non-homogenous Poisson process software reliability models proposed during the past 30 years to estimate software reliability measures such as the number of remaining faults, software failure rate, and software reliability. Selection of optimal SRM for use in a particular case has been an area of interest for researchers in the field of software reliability. Tools and techniques for software reliability model selection found in the literature cannot be used with high level of confidence as they use a limited number of model selection criteria. A real data set of middle size software project from published papers has been used for demonstration of matrix method. The result of this study will be a ranking of SRMs based on the Permanent value of the criteria matrix formed for each model based on the comparison criteria. The software reliability model with highest value of the Permanent is ranked at number – 1 and so on.

Keywords: Matrix method, Model ranking, Model selection, Model selection criteria, Software reliability models.

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Authors: Aleksandra Chiniaeva

Abstract:

The following paper describes the activity of national and international parliamentary assemblies of the European region in protection and promotion of human rights. It may be said that parliamentarians have a “double mandate” — as members of the international assembly and of their respective national parliaments. In other words, parliamentarization at both international and national level provides a situation for parliamentarians, where they link people, national governments and international organizations. The paper is aimed towards demonstrating that the activity of the main international parliamentary assemblies of the European region have a real positive impact on the human rights situation in the European region. In addition, the paper describes the assemblies that include protection of human rights in their Agenda as one of the main subjects: the EP, the PACE, the OSCE PA and the IPA CIS. Co-operation activities such as joint election observation; participation in inter-parliamentary associations, such as the IPU; conclusion agreements allow assemblies to provide observation of human right situation in the states that are not members of the particular organization and as consequence make their impact broader.

Keywords: Human rights, International parliamentary assembly, IPU, EP, PACE, OSCE, IPA CIS, international election observation.

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Authors: Maohai Li, Bingrong Hong, Zesu Cai, Ronghua Luo

Abstract:

This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark position estimation and update is also implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem, and introducing the evolution strategies (ES) for avoiding particle impoverishment. The 3D natural point landmarks are structured with matching Scale Invariant Feature Transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-Tree in the time cost of O(log2 N). Experiment results on real robot in our indoor environment show the advantages of our methods over previous approaches.

Keywords: Mobile robot, simultaneous localization and mapping, Rao-Blackwellised particle filter, evolution strategies, scale invariant feature transform.

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Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

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Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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Authors: E. Ceyhan, A. Kahraman, M. Önder, M.K. Ateş, S. Karadaş, R. Topak, M.A. Avcı

Abstract:

The experimental design was 4 x 5 factorial with three replications in fully controlled research greenhouse in Department of Soil Sciences and Plant Nutrition, Faculty of Agriculture, University of Selcuk in the year of 2009. Determination of tolerant chickpea genotypes to drought was made in the research. Additionally, sophisticated effects of drought on plant growth and development, biochemical and physical properties or physical defense mechanisms were presented. According to the results, the primary genotypes were Ilgın YP (0.0063 g/gh) for leaf water capacity, 22235 70.44(%) for relative water content, 22159 (82.47%) for real water content, 22159 (5.03 mg/l) for chlorophyll a+b, Ilgın YP (125.89 nmol H2O2.dak-1/ mg protein-1) for peroxidase, Yunak YP (769.67 unit/ mg protein-1) for superoxide dismutase, Seydişehir YP (16.74 μg.TA-1) for proline, Gökçe (80.01 nmol H2O2.dak-1/ mg protein-1) for catalase. Consequently, all the genotypes increased their enzyme activity depending on the increasing of drought stress consider with the effects of drought stress on leaf enzyme activity. Chickpea genotypes are increasing enzyme activity against to drought stress.

Keywords: Chickpea, drought, enzyme, tolerance to drought

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Authors: Marius Mosoarca, Victor Gioncu, Ovidiu Cosma

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Historic religious buildings located in seismic areas have developed different failure mechanisms. Simulation of failure modes is done with computer programs through a nonlinear dynamic analysis or simplified using the method of failure blocks. Currently there are simulation methodologies of failure modes based on the failure rigid blocks method only for Roman Catholic churches type. Due to differences of shape in plan, elevation and construction systems between Orthodox churches and Catholic churches, for the first time there were initiated researches in the development of this simulation methodology for Orthodox churches. In this article are presented the first results from the researches. The theoretical results were compared with real failure modes recorded at an Orthodox church from Banat region, severely damaged by earthquakes in 1991. Simulated seismic response, using a computer program based on finite element method was confirmed by cracks after earthquakes. The consolidation of the church was made according to these theoretical results, realizing a rigid floor connecting all the failure blocks.

Keywords: Dinamic analysis, failure mechanism, rigid blocks seismic simulation.

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Authors: Lee Bih Ni, Kiu Su Na

Abstract:

This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: A second language, Chinese language teaching, immersion teaching, instructional strategies.

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Authors: S. Dhahri, A. Zitouni, H. Chaouch, R. Tourki

Abstract:

This paper presents an adaptive motion estimator that can be dynamically reconfigured by the best algorithm depending on the variation of the video nature during the lifetime of an application under running. The 4 Step Search (4SS) and the Gradient Search (GS) algorithms are integrated in the estimator in order to be used in the case of rapid and slow video sequences respectively. The Full Search Block Matching (FSBM) algorithm has been also integrated in order to be used in the case of the video sequences which are not real time oriented. In order to efficiently reduce the computational cost while achieving better visual quality with low cost power, the proposed motion estimator is based on a Variable Block Size (VBS) scheme that uses only the 16x16, 16x8, 8x16 and 8x8 modes. Experimental results show that the adaptive motion estimator allows better results in term of Peak Signal to Noise Ratio (PSNR), computational cost, FPGA occupied area, and dissipated power relatively to the most popular variable block size schemes presented in the literature.

Keywords: H264, Configurable Motion Estimator, VariableBlock Size, PSNR, Dissipated power.

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Authors: A. Pereira, S. Haffner, L. V. Gasperin

Abstract:

This paper presents two simplified models to determine nodal voltages in power distribution networks. These models allow estimating the impact of the installation of reactive power compensations equipments like fixed or switched capacitor banks. The procedure used to develop the models is similar to the procedure used to develop linear power flow models of transmission lines, which have been widely used in optimization problems of operation planning and system expansion. The steady state non-linear load flow equations are approximated by linear equations relating the voltage amplitude and currents. The approximations of the linear equations are based on the high relationship between line resistance and line reactance (ratio R/X), which is valid for power distribution networks. The performance and accuracy of the models are evaluated through comparisons with the exact results obtained from the solution of the load flow using two test networks: a hypothetical network with 23 nodes and a real network with 217 nodes.

Keywords: Distribution network models, distribution systems, optimization, power system planning.

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