Search results for: Hybrid uncertainty

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: Short term load forecasting, prediction interval, type 2 fuzzy logic systems.

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Authors: Tulika Bhattacharjee, A. K.Chakraborty

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Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow

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Authors: Kristjan Kuhi, Kati K. Kaare, Ott Koppel

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Modern management in most fields is performance based; both planning and implementation of maintenance and operational activities are driven by appropriately defined performance indicators. Continuous real-time data collection for management is becoming feasible due to technological advancements. Outdated and insufficient input data may result in incorrect decisions. When using deterministic models the uncertainty of the object state is not visible thus applying the deterministic models are more likely to give false diagnosis. Constructing structured probabilistic models of the performance indicators taking into consideration the surrounding indicator environment enables to estimate the trustworthiness of the indicator values. It also assists to fill gaps in data to improve the quality of the performance analysis and management decisions. In this paper authors discuss the application of probabilistic graphical models in the road performance measurement and propose a high-level conceptual model that enables analyzing and predicting more precisely future pavement deterioration based on road utilization.

Keywords: Probabilistic graphical models, performance indicators, road performance management, data collection

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Authors: Razan Salem

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Men and women have different approaches towards investing, both in terms of strategies and risk attitudes. This study aims to focus mainly on investigating the financial risk behaviors of Arab women investors and to examine the financial risk tolerance levels of Arab women relative to Arab men investors. Using survey data on 547 Arab men and women investors, the results of Wilcoxon Signed-Rank (One-Sample) test Mann-Whitney U test reveal that Arab women are risk-averse investors and have lower financial risk tolerance levels relative to Arab men. Such findings can be explained by the fact of women's nature and lower investment literacy levels. Further, the current political uncertainty in the Arab region may be considered as another explanation of Arab women’s risk aversion behavior. The study's findings support the existing literature by validating the stereotype of “women are more risk-averse than men” in the Arab region. Overall, when it comes to investment and financial behaviors, women around the world behave similarly.

Keywords: Arab region, financial risk behavior, gender differences, women investors.

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Authors: P. Winzer, E. Massarczyk

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Experts, enterprises and operators expect that the bandwidth request will increase up to rates of 100 to 1,000 Mbps within several years. Therefore the most important question is which technology shall satisfy the future consumer broadband demands. Currently the consensus is, that the fiber technology has the best technical characteristics to achieve such the high bandwidth rates. But fiber technology is so far very cost-intensive and resource consuming. To avoid these investments, operators are concentrating to upgrade the existing copper and hybrid fiber coax infrastructures. This work presents a comparison of the copper and fiber technologies including an overview about the current German broadband market. Both technologies are reviewed in the terms of demand, willingness to pay and economic efficiency in connection with the technical characteristics.

Keywords: Broadband customer demand, fiber development, G.fast, Vectoring, willingness to payfor broadband services

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Authors: Martin Ringdorfer, Martin Horn

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A robust wheel slip controller for electric vehicles is introduced. The proposed wheel slip controller exploits the dynamics of electric traction drives and conventional hydraulic brakes for achieving maximum energy efficiency and driving safety. Due to the control of single wheel traction motors in combination with a hydraulic braking system, it can be shown, that energy recuperation and vehicle stability control can be realized simultaneously. The derivation of a sliding mode wheel slip controller accessing two drivetrain actuators is outlined and a comparison to a conventionally braked vehicle is shown by means of simulation.

Keywords: Wheel slip control, sliding mode control, vehicle dynamics.

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Authors: A. Maddi, A. Guessoum, D. Berkani

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The purpose of this paper is to provide a practical example to the Linear Quadratic Gaussian (LQG) controller. This method includes a description and some discussion of the discrete Kalman state estimator. One aspect of this optimality is that the estimator incorporates all information that can be provided to it. It processes all available measurements, regardless of their precision, to estimate the current value of the variables of interest, with use of knowledge of the system and measurement device dynamics, the statistical description of the system noises, measurement errors, and uncertainty in the dynamics models. Since the time of its introduction, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. For example, to determine the velocity of an aircraft or sideslip angle, one could use a Doppler radar, the velocity indications of an inertial navigation system, or the relative wind information in the air data system. Rather than ignore any of these outputs, a Kalman filter could be built to combine all of this data and knowledge of the various systems- dynamics to generate an overall best estimate of velocity and sideslip angle.

Keywords: Aircraft motion, Kalman filter, LQG control, Lateral stability, State estimator.

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Authors: G. Gurguze, I. Turkoglu

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Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: Energy management, mobile robot, robot administration, robot management, robot planning.

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Authors: A. K. Al-Othman, F. S. Al-Fares, K. M. EL-Nagger

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This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: State Estimation, Fuzzy Linear Regression, FuzzyLinear State Estimator (FLSE) and Measurements Uncertainty.

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Authors: Tomi Roinila, Aki Taskinen, Matti Vilkko

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Switched-mode converters play now a significant role in modern society. Their operation are often crucial in various electrical applications affecting the every day life. Therefore, the quality of the converters needs to be reliably verified. Recent studies have shown that the converters can be fully characterized by a set of frequency responses which can be efficiently used to validate the proper operation of the converters. Consequently, several methods have been proposed to measure the frequency responses fast and accurately. Most often correlation-based techniques have been applied. The presented measurement methods are highly sensitive to external errors and system nonlinearities. This fact has been often forgotten and the necessary uncertainty analysis of the measured responses has been neglected. This paper presents a simple approach to analyze the noise and nonlinearities in the frequency-response measurements of switched-mode converters. Coherence analysis is applied to form a confidence interval characterizing the noise and nonlinearities involved in the measurements. The presented method is verified by practical measurements from a high-frequency switchedmode converter.

Keywords: Switched-mode converters, Frequency analysis, CoherenceAnalysis.

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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: Navid Javidtash, Abdolmohamad Davodi, Mojtaba Hakimzadeh, Abdolreza Roozbeh

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Economic dispatch (ED) is considered to be one of the key functions in electric power system operation. This paper presents a new hybrid approach based genetic algorithm (GA) to economic dispatch problems. GA is most commonly used optimizing algorithm predicated on principal of natural evolution. Utilization of chaotic queue with GA generates several neighborhoods of near optimal solutions to keep solution variation. It could avoid the search process from becoming pre-mature. For the objective of chaotic queue generation, utilization of tent equation as opposed to logistic equation results in improvement of iterative speed. The results of the proposed approach were compared in terms of fuel cost, with existing differential evolution and other methods in literature.

Keywords: Economic Dispatch(ED), Optimization, Fuel Cost, Genetic Algorithm (GA).

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Authors: G. S. Ryu, K. T. Koh, H. Y. Kim, G. H. An, D. W. Seo

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Geopolymer mortar is produced by alkaline activation of pozzolanic materials such as fly ground granulated blast-furnace slag (GGBFS) and fly ash (FA). Its unique reaction pathway facilitates rapid strength development in comparison with hydration of ordinary Portland cement (OPC). Geopolymer can be fabricated using various types and dosages of alkali-activator, which effectively gives a wider control over the performance of the final product. The present study investigates the effect of types of precursors and curing conditions on the fresh state and strength development characteristics of geopolymers, thereby comparatively exploring the effect of precursors from various sources of origin. The obtained result showed that the setting time and strength development of the specimens with the identical mix proportion but different precursors displayed significant variations.

Keywords: Alkali-activated material, blast furnace slag, fly ash, Flowability, strength development.

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Authors: Abdul Rashid Husain, Mohamad Noh Ahmad, Abdul Halim Mohd. Yatim

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In this paper, stabilization of an Active Magnetic Bearing (AMB) system with varying rotor speed using Sliding Mode Control (SMC) technique is considered. The gyroscopic effect inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Also, transformation of the AMB dynamic model into a new class of uncertain system shows that this gyroscopic effect lies in the mismatched part of the system matrix. Moreover, the current gain parameter is allowed to be varied in a known bound as an uncertainty in the input matrix. SMC design method is proposed in which the sufficient condition that guarantees the global exponential stability of the reduced-order system is represented in Linear Matrix Inequality (LMI). Then, a new chattering-free control law is established such that the system states are driven to reach the switching surface and stay on it thereafter. The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.

Keywords: Active Magnetic Bearing (AMB), Sliding ModeControl (SMC), Linear Matrix Inequality (LMI), mismatcheduncertainty.

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Authors: Salim Istyaq, Mohammad Sarosh Umar

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Today, the mankind is in the stage of development, every day comes with new proposal of technology, in order to secure these types of technology, we also prepare high yielding security modules to conserve these resources. The capacity of human brain to recognize anything is far more than any species; this is all due to our developing cycle of curiosity. In this paper, we proposed a scheme based on graphical password using QR Code which provides more security to the recent online system. It also contains a supportive sound signature. In this system, authentication is done using sequence of images in QR code form. Users select one click-point per image with the help of QR scanner or recognizer. The encoded phrase in a QR code emphasizes the minimum probability of attacking via shoulder surfing or other attacks.

Keywords: Graphical password, QR code, sound signature, image authentication, cued click point.

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Authors: Nasser AlShawaaf, Soo Hee Lee

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Arts globalisation represents a different phenomenon than arts commercialisation which was facilitated by local cultural policies. This study examines the causes and effects of globalisation of art museums in France. Building on art literature, we conducted a literature review of cultural policies. Our findings show that the cultural policies of the French government since the 1980s of cultural democratisation, cultural decentralisation, and implementing market principles on the cultural sector are leading to arts globalisation. Although globalisation is producing economic benefits and enhancing cultural reach, however, the damages include artistic values and creativity, cultural heritage and representation, and the museum itself. Art museums and host cities could overcome negative consequences through a hybrid collection display and develop local collections gradually.

Keywords: Cultural policy, cultural decentralisation, cultural globalisation, art museums, contextual analysis, France.

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Authors: C. Kalamani, K. Paramasivam

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In VLSI, testing plays an important role. Major problem in testing are test data volume and test power. The important solution to reduce test data volume and test time is test data compression. The Proposed technique combines the bit maskdictionary and 2n pattern run length-coding method and provides a substantial improvement in the compression efficiency without introducing any additional decompression penalty. This method has been implemented using Mat lab and HDL Language to reduce test data volume and memory requirements. This method is applied on various benchmark test sets and compared the results with other existing methods. The proposed technique can achieve a compression ratio up to 86%.

Keywords: Bit Mask dictionary, 2n pattern run length code, system-on-chip, SOC, test data compression.

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: Anammox, filter media, kinetics, nitrogen removal.

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Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

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The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which, in turn, are affected by geopolitical uncertainty, oil price volatility and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: Valuation, property rights, information, institutions, trust, salience.

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Authors: G. K. Pandey, D. Ramadasu, I. Banerjee, V. Vinod, G. Padmakumar, V. Prakash, K. K. Rajan

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Detailed thermal hydraulic investigations are very  essential for safe and reliable functioning of liquid metal cooled fast  breeder reactors. These investigations are further more important for  components with complex profile, since there is no direct correlation  available in literature to evaluate the hydraulic characteristics of such  components directly. In those cases available correlations for similar  profile or geometries may lead to significant uncertainty in the  outcome. Hence experimental approach can be adopted to evaluate  these hydraulic characteristics more precisely for better prediction in  reactor core components.  Prototype Fast Breeder Reactor (PFBR), a sodium cooled pool  type reactor is under advanced stage of construction at Kalpakkam,  India. Several components of this reactor core require hydraulic  investigation before its usage in the reactor. These hydraulic  investigations on full scale models, carried out by experimental  approaches using water as simulant fluid are discussed in the paper. 

Keywords: Fast Breeder Reactor, Cavitation, pressure drop, Reactor components.

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Authors: M. Sedighizadeh, A. Rezazadeh

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Movable power sources of proton exchange membrane fuel cells (PEMFC) are the important research done in the current fuel cells (FC) field. The PEMFC system control influences the cell performance greatly and it is a control system for industrial complex problems, due to the imprecision, uncertainty and partial truth and intrinsic nonlinear characteristics of PEMFCs. In this paper an adaptive PI control strategy using neural network adaptive Morlet wavelet for control is proposed. It is based on a single layer feed forward neural networks with hidden nodes of adaptive morlet wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. The proposed method is applied to a typical 1 KW PEMFC system and the results show the proposed method has more accuracy against to MLP (Multi Layer Perceptron) method.

Keywords: Adaptive Control, Morlet Wavelets, PEMFC.

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

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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: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: Academic identity, embodied learning, digitized lecture, performance coaching.

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Authors: Seulbi Choi, Hyunchul Ahn

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Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users.

Keywords: Recommender system, collaborative filtering, text mining, review mining.

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Authors: Amir Azizi, Amir Yazid B. Ali, Loh Wei Ping

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Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Keywords: Bayesian inference, Uncertainty modeling, Monte Carlo Markov chain, Gibbs sampling, Production throughput

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.

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Authors: Wondwosen Teshome B.

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The major aim of this paper is to investigate the opposition politics in Africa. The paper also examines the status and the role, the contributions and the weaknesses of opposition1 political parties in Africa, particularly in transitional democracies that emerged in the 1990s. In Africa, many of the opposition parties appear or become active only during an election, and disappear when the election is over. It is found out that most of the opposition parties in Africa are established around the personalities of individuals, lack internal democracy, suffer from inter-party and intra-party conflicts, have severe shortage of finance, and lack strong base and experience. Their weaknesses also include bad organization and weak connection with the popular constituencies. The paper concludes that most of the weaknesses of the African opposition parties emanate from the incumbents- hostile policies, which are mostly aimed at fragmenting and weakening the opposition groups.

Keywords: Africa, Hybrid regime, Incumbent party, Neopatrimonialsim, Opposition party, Political party, Pseudo-democracy.

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Authors: Do Hoai Nam, Keiko Udo, Akira Mano

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This paper presents the combination of different precipitation data sets and the distributed hydrological model, in order to examine the flood runoff reproductivity of scattered observation catchments. The precipitation data sets were obtained from observation using rain-gages, satellite based estimate (TRMM), and numerical weather prediction model (NWP), then were coupled with the super tank model. The case study was conducted in three basins (small, medium, and large size) located in Central Vietnam. Calculated hydrographs based on ground observation rainfall showed best fit to measured stream flow, while those obtained from TRMM and NWP showed high uncertainty of peak discharges. However, calculated hydrographs using the adjusted rainfield depicted a promising alternative for the application of TRMM and NWP in flood modeling for scattered observation catchments, especially for the extension of forecast lead time.

Keywords: Flood forecast, rainfall-runoff model, satellite rainfall estimate, numerical weather prediction, quantitative precipitation forecasting.

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: Linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control.

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Authors: Dharmveer Singh Rajput , P. K. Singh, Mahua Bhattacharya

Abstract:

Clustering in high dimensional space is a difficult problem which is recurrent in many fields of science and engineering, e.g., bioinformatics, image processing, pattern reorganization and data mining. In high dimensional space some of the dimensions are likely to be irrelevant, thus hiding the possible clustering. In very high dimensions it is common for all the objects in a dataset to be nearly equidistant from each other, completely masking the clusters. Hence, performance of the clustering algorithm decreases. In this paper, we propose an algorithmic framework which combines the (reduct) concept of rough set theory with the k-means algorithm to remove the irrelevant dimensions in a high dimensional space and obtain appropriate clusters. Our experiment on test data shows that this framework increases efficiency of the clustering process and accuracy of the results.

Keywords: High dimensional clustering, sub-space, k-means, rough set, discernibility matrix.

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