Search results for: Curriculum approach

Authors: C. Ardil

Abstract:

In this paper, the comparison of composite programming and compromise programming for the aircraft selection problem is discussed using the multiple criteria decision analysis method. The decision making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as aircraft selection problems. The proposed technique gives more efficient results by extending the composite programming and compromise programming, which are widely used in modeling multiple criteria decisions. The proposed model is applied to a practical decision problem for evaluating and selecting aircraft problems.A selection of aircraft was made based on the proposed approach developed in the field of multiple criteria decision making. The model presented is solved by using the following methods: composite programming, and compromise programming. The importance values of the weight coefficients of the criteria are calculated using the mean weight method. The evaluation and ranking of aircraft are carried out using the composite programming and compromise programming methods. In order to determine the stability of the model and the ability to apply the developed composite programming and compromise programming approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ and q in the first part. The second part of the sensitivity analysis relates to the application of different multiple criteria decision making methods, composite programming and compromise programming. In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient of the ranks obtained was calculated which confirms the applicability of all the proposed approaches.

Keywords: composite programming, compromise programming, additive weighted model, multiplicative weighted model, multiple criteria decision making analysis, MCDMA, aircraft selection

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Authors: Inese Bula

Abstract:

Symbolic dynamics studies dynamical systems on the basis of the symbol sequences obtained for a suitable partition of the state space. This approach exploits the property that system dynamics reduce to a shift operation in symbol space. This shift operator is a chaotic mapping. In this article we show that in the symbol space exist other chaotic mappings.

Keywords: Infinite symbol space, prefix metric, chaotic mapping, generator function, jump mapping.

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Authors: Dongmin Cai, Stephen S-T Yau

Abstract:

Lacking an inherent “natural" dissimilarity measure between objects in categorical dataset presents special difficulties in clustering analysis. However, each categorical attributes from a given dataset provides natural probability and information in the sense of Shannon. In this paper, we proposed a novel method which heuristically converts categorical attributes to numerical values by exploiting such associated information. We conduct an experimental study with real-life categorical dataset. The experiment demonstrates the effectiveness of our approach.

Keywords: Categorical, Clustering, Converting, Information

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: Modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition.

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Authors: Yoshihiro Ochiai

Abstract:

Globin superfamily proteins including myoglobin and hemoglobin, have welcome new members recently, namely, cytoglobin, neuroglobin and globin X, though their physiological functions are still to be addressed. Fish are the excellent models for the study of these globins, but their characteristics have not yet been discussed to date. In the present study, attempts have been made to characterize their structural uniqueness by making use of proteomics approach. This is the first comparative study on the characterization of globin superfamily proteins from fish.

Keywords: Globin, Superfamily, Protein, Fish, Structure

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Authors: S. M. Lee, J. H. Park, H. Y. Jung

Abstract:

This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.

Keywords: Chaotic systems, functional projective H∞ synchronization, LMI.

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Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

Abstract:

We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: Possibility distribution, parameters estimation, Maxmin u/E estimator, fuzzy model identification.

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Authors: M. Govindarajan

Abstract:

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In decision tree approach is most useful in classification problem. With this technique, tree is constructed to model the classification process. There are two basic steps in the technique: building the tree and applying the tree to the database. This paper describes a proposed C5.0 classifier that performs rulesets, cross validation and boosting for original C5.0 in order to reduce the optimization of error ratio. The feasibility and the benefits of the proposed approach are demonstrated by means of medial data set like hypothyroid. It is shown that, the performance of a classifier on the training cases from which it was constructed gives a poor estimate by sampling or using a separate test file, either way, the classifier is evaluated on cases that were not used to build and evaluate the classifier are both are large. If the cases in hypothyroid.data and hypothyroid.test were to be shuffled and divided into a new 2772 case training set and a 1000 case test set, C5.0 might construct a different classifier with a lower or higher error rate on the test cases. An important feature of see5 is its ability to classifiers called rulesets. The ruleset has an error rate 0.5 % on the test cases. The standard errors of the means provide an estimate of the variability of results. One way to get a more reliable estimate of predictive is by f-fold –cross- validation. The error rate of a classifier produced from all the cases is estimated as the ratio of the total number of errors on the hold-out cases to the total number of cases. The Boost option with x trials instructs See5 to construct up to x classifiers in this manner. Trials over numerous datasets, large and small, show that on average 10-classifier boosting reduces the error rate for test cases by about 25%.

Keywords: C5.0, Error Ratio, text mining, training data, test data.

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Authors: Fayza Obied-Allah

Abstract:

Customer’ needs, quality, and value creation while reducing costs through supply chain management provides challenges and opportunities for companies and researchers. In the light of these challenges, modern ideas must contribute to counter these challenges and exploit opportunities. Therefore, this paper discusses the impact of the quality cost on revenue sharing as a most important incentive to configure business networks. This paper develops the quality cost approach to align with the modern era. It develops a model to measure quality costs which might enable firms to manage revenue sharing in a supply chain. The developed model includes five categories; besides the well-known four categories (namely prevention costs, appraisal costs, internal failure costs, and external failure costs), a new category has been developed in this research as a new vision of the relationship between quality costs and innovations in industry. This new category is Recycle Cost. This paper also examines whether such quality costs in supply chains influence the revenue sharing between partners. Using the author's quality cost model, the relationship between quality costs and revenue sharing among partners is examined using a case study in an Egyptian manufacturing company which is a part of a supply chain. This paper argues that the revenue-sharing proportion allocated to supplier increases as the recycle cost of supplier increases, and the revenue-sharing proportion allocated to manufacturer increases as the prevention and appraisal costs increase, as well as the failure costs, the recycle costs of manufacturer, and the recycle costs of suppliers decrease. However, the results present surprising findings. The purposes of this study are developing quality cost approach and understanding the relationships between quality costs and revenue sharing in supply chains. Therefore, the present study contributes to theory and practice by explaining how the cost of recycling can be combined in quality cost model to better understanding the revenue sharing among partners in supply chains.

Keywords: Quality cost, Recycle cost, Revenue sharing, Supply chain.

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Authors: Ahmed, M., Yasser A., Mahmoud H., Ahmed, A., Abdulla M. S., Nazar, S.

Abstract:

Strut-and-Tie Models (STM) for the design of concrete beams, comprising of struts, ties, nodes as the basic tools, is conceptually simple, but its realization for complex concrete structure is not straightforward and depends on flow of internal forces in the structure. STM technique has won wide acceptance for deep member and shear design. STM technique is a unified approach that considers all load effects (bending, axial, shear, and torsion) simultaneously, not just applicable to shear loading only. The present study is to portray Strut-and-Tie Modeling based on Load-Transfer-Mechanisms as a unified method to analyze, design and detailing for deep and slender concrete beams. Three shear span- effective depth ratio (a/ d) are recommended for the modeling of STM elements corresponding to dominant load paths. The study also discusses the research work conduct on effective stress of concrete, tie end anchorage, and transverse reinforcement demand under different load transfer mechanism. It is also highlighted that to make the STM versatile tool for design of beams applicable to all shear spans, the effective stress of concrete and, transverse reinforcement demand, inclined angle of strut, and anchorage requirements of tie bars is required to be correlated with respect to load transfer mechanism. The country code provisions are to be modified and updated to apply for generalized design of concrete deep and slender member using load transfer mechanism based STM technique. Examples available in literature are reanalyzed with refined STM based on load transfer mechanisms and results are compared. It is concluded from the results that proposed approach will require true reinforcement demand depending on dominant force transfer action in concrete beam.

Keywords: Deep member, Load transfer mechanism, Strut-and-Tie Model, Strut, Truss.

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Authors: Wang Haiyan

Abstract:

This paper attempts to explore the phenomenon of metaphorization in English newspaper headlines from the perspective of pragmatic investigation. With relevance theory as the guideline, this paper makes an explanation of the processing of metaphor with a pragmatic approach and points that metaphor is the stimulus adopted by journalists to achieve optimal relevance in this ostensive communication, as well as the strategy to fulfill their writing purpose.

Keywords: Metaphorization, newspaper, headlines, relevance theory.

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Authors: Maharavo Randrianarivony

Abstract:

The objective is to split a simply connected polygon into a set of convex quadrilaterals without inserting new boundary nodes. The presented approach consists in repeatedly removing quadrilaterals from the polygon. Theoretical results pertaining to quadrangulation of simply connected polygons are derived from the usual 2-ear theorem. It produces a quadrangulation technique with O(n) number of quadrilaterals. The theoretical methodology is supplemented by practical results and CAD surface segmentation.

Keywords: Quadrangulation, simply connected, two-ear theorem.

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Authors: G. Koukiou, V. Anastassopoulos

Abstract:

In this paper a bank of velocity filters is devised to be used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept from velocity filters. Accordingly, velocity filters are built using the spectral signature of each separate moving object. Experimentation reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the velocity are concerned.

Keywords: Velocity filters, filter banks, 3-D FFT.

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Authors: Wang Wen-long, Li Hua, Pan Sha

Abstract:

Eight difference schemes and five limiters are applied to numerical computation of Riemann problem. The resolution of discontinuities of each scheme produced is compared. Numerical dissipation and its estimation are discussed. The result shows that the numerical dissipation of each scheme is vital to improve scheme-s accuracy and stability. MUSCL methodology is an effective approach to increase computational efficiency and resolution. Limiter should be selected appropriately by balancing compressive and diffusive performance.

Keywords: Scheme; Limiter, Numerical simulation, Riemannproblem.

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Authors: N. Kumaresan , J. Kavikumar, Kuru Ratnavelu

Abstract:

In this paper, solution of fuzzy differential equation under general differentiability is obtained by simulink. The simulink solution is equivalent or very close to the exact solution of the problem. Accuracy of the simulink solution to this problem is qualitatively better. An illustrative numerical example is presented for the proposed method.

Keywords: Fuzzy differential equation, Generalized differentiability, H-difference and Simulink.

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Authors: Abdellali Kelil, Shengrui Wang, Ryszard Brzezinski

Abstract:

The literature reports a large number of approaches for measuring the similarity between protein sequences. Most of these approaches estimate this similarity using alignment-based techniques that do not necessarily yield biologically plausible results, for two reasons. First, for the case of non-alignable (i.e., not yet definitively aligned and biologically approved) sequences such as multi-domain, circular permutation and tandem repeat protein sequences, alignment-based approaches do not succeed in producing biologically plausible results. This is due to the nature of the alignment, which is based on the matching of subsequences in equivalent positions, while non-alignable proteins often have similar and conserved domains in non-equivalent positions. Second, the alignment-based approaches lead to similarity measures that depend heavily on the parameters set by the user for the alignment (e.g., gap penalties and substitution matrices). For easily alignable protein sequences, it's possible to supply a suitable combination of input parameters that allows such an approach to yield biologically plausible results. However, for difficult-to-align protein sequences, supplying different combinations of input parameters yields different results. Such variable results create ambiguities and complicate the similarity measurement task. To overcome these drawbacks, this paper describes a novel and effective approach for measuring the similarity between protein sequences, called SAF for Substitution and Alignment Free. Without resorting either to the alignment of protein sequences or to substitution relations between amino acids, SAF is able to efficiently detect the significant subsequences that best represent the intrinsic properties of protein sequences, those underlying the chronological dependencies of structural features and biochemical activities of protein sequences. Moreover, by using a new efficient subsequence matching scheme, SAF more efficiently handles protein sequences that contain similar structural features with significant meaning in chronologically non-equivalent positions. To show the effectiveness of SAF, extensive experiments were performed on protein datasets from different databases, and the results were compared with those obtained by several mainstream algorithms.

Keywords: Protein, Similarity, Substitution, Alignment.

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Authors: Mafawez Alharbi, Mahdi Jemmali

Abstract:

E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: Artificial intelligence, architecture, e-learning, software engineering, processing.

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Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: Mohammad Pooyan, Ali Taheri, Morteza Moazami-Goudarzi, Iman Saboori

Abstract:

In this paper we present a novel approach for wavelet compression of electrocardiogram (ECG) signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm. SPIHT algorithm has achieved prominent success in image compression. Here we use a modified version of SPIHT for one dimensional signals. We applied wavelet transform with SPIHT coding algorithm on different records of MIT-BIH database. The results show the high efficiency of this method in ECG compression.

Keywords: ECG compression, wavelet, SPIHT.

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Authors: A. Habibizad Navin, M. Naghian Fesharaki, M. Mirnia, M. Kargar

Abstract:

In this paper we introduce Digital Probability Hyper Digraph for modeling random variable as the hierarchical data-oriented model.

Keywords: Data-Oriented Models, Data Structure, DigitalProbability Hyper Digraph, Random Variable, Statistic andProbability.

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Authors: Mohammad Al Rawajbeh, Ahmad Haboush

Abstract:

The primary aim of the e-government applications is the fast citizen service and the accomplishment of governmental functions. This paper discusses the knowledge management for egovernment development in the needs and role. The paper focused on analyzing the advantages of using knowledge management by using the existing IT technologies to maximize the government functions efficiency. The proposed new approach of providing government services is based on using Knowledge management as a part of e-government system.

Keywords: E-government, knowledge management, e-service, etools, governmental functions.

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Authors: F. S. Al-Anzi, M. Sarfraz, A. Elmi, A. R. Khan

Abstract:

Researchers are responding to the environmental challenges of Kuwait in localized, innovative, effective and economic ways. One of the vital and significant examples of the natural challenges is lack or water and desertification. In this research, the project team focuses on redesigning a prototype, using Value Engineering Methodology, which would provide similar functionalities to the well-known technology of Waterboxx kits while reducing the capital and operational costs and simplifying the process of manufacturing and usability by regular farmers. The design employs used tires and recycled plastic sheets as raw materials. Hence, this approach is going to help not just fighting desertification but also helping in getting rid of ever growing huge tire dumpsters in Kuwait, as well as helping in avoiding hazards of tire fires yielding in a safer and friendlier environment. Several alternatives for implementing the prototype have been considered. The best alternative in terms of value has been selected after thorough Function Analysis System Technique (FAST) exercise has been developed. A prototype has been fabricated and tested in a controlled simulated lab environment that is being followed by real environment field testing. Water and soil analysis conducted on the site of the experiment to cross compare between the composition of the soil before and after the experiment to insure that the prototype being tested is actually going to be environment safe. Experimentation shows that the design was equally as effective as, and may exceed, the original design with significant savings in cost. An estimated total cost reduction using the VE approach of 43.84% over the original design. This cost reduction does not consider the intangible costs of environmental issue of waste recycling which many further intensify the total savings of using the alternative VE design. This case study shows that Value Engineering Methodology can be an important tool in innovating new designs for reducing costs.

Keywords: Desertification, functional analysis, scrap tires, value engineering, waste recycling, water irrigation rationing.

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Authors: B. Rezaei, G. R. Boroun, M. Abdolmaleki

Abstract:

The bound state energy of three quark systems is studied in the framework of a non- relativistic spin independent phenomenological model. The hyper- spherical coordinates are considered for the solution this system. According to Jacobi coordinate, we determined the bound state energy for (uud) and (ddu) quark systems, as quarks are flavorless mass, and it is restrict that choice potential at low and high range in nucleon bag for a bound state.

Keywords: Adiabatic expansion, grand angular momentum, binding energy, perturbation, baryons.

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Authors: Mou-Yuan Liao, Chien-Wei Wu, Chien-Hua Lin

Abstract:

Process capability index Cpk is the most widely used index in making managerial decisions since it provides bounds on the process yield for normally distributed processes. However, existent methods for assessing process performance which constructed by statistical inference may unfortunately lead to fine results, because uncertainties exist in most real-world applications. Thus, this study adopts fuzzy inference to deal with testing of Cpk . A brief score is obtained for assessing a supplier’s process instead of a severe evaluation.

Keywords: Process capability analysis, quality control.

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Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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Authors: Byung Ki Kim, Ho Min Jung, Jae-Bong Yoo, Wan Yeon Lee, Chan Young Park, Young Woong Ko

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In this paper, we present a novel approach to location system under indoor environment. The key idea of our work is accurate distance estimation with cricket-based location system using A* algorithm. We also use magnetic sensor for detecting obstacles in indoor environment. Finally, we suggest how this system can be used in various applications such as asset tracking and monitoring.

Keywords: Cricket, Indoor Location Tracking, Mobile Robot, Localization.

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Authors: Ayse Okvuran

Abstract:

Creative drama which interconnects with the concepts of play, theatre, animation and role playing is a field which can only be learnt and expressed through experiencing. This study about assessment of the drama teaching in preschools by children was conducted in 3 preschools in Ankara with participation of 12 children of 6 ages who had taken drama learning courses. Qualitative research approach and semi-structured interviewing technique were employed. The results of the study indicated that all of 12 children defined drama as a game and entertainment.

Keywords: Creative drama, preschoolers, drama courses

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Authors: Lili Wang, Meng Hu

Abstract:

In this paper, based on almost periodic functional hull theory and M-matrix theory, some sufficient conditions are established for the existence and uniqueness of positive almost periodic solution for a class of BAM neural networks with time-varying delays. An example is given to illustrate the main results.

Keywords: Delayed BAM neural networks, Hull theorem, Mmatrix, Almost periodic solution, Global exponential stability.

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Authors: Rashmi Priyadarshini, S. R. N. Reddy, R. M. Mehra

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This paper presents one of the best applications of wireless sensor network for campus Monitoring. With the help of PIR sensor, temperature sensor and humidity sensor, effective utilization of energy resources has been implemented in one of rooms of Sharda University, Greater Noida, India. The RISC microcontroller is used here for analysis of output of sensors and providing proper control using ZigBee protocol. This wireless sensor module presents a tremendous power saving method for any campus

Keywords: PIC microcontroller, wireless sensor network, ZigBee.

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Authors: Gideon Avigad, Amiram Moshaiov, Neima Brauner

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An IEC technique is described for a multi-objective search of conceptual solutions. The survivability of solutions is influenced by both model-based fitness and subjective human preferences. The concepts- preferences are articulated via a hierarchy of sub-concepts. The suggested method produces an objectivesubjective front. Academic example is employed to demonstrate the proposed approach.

Keywords: Conceptual solution, engineering design, hierarchical planning, multi-objective search, problem reduction.

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