Search results for: Slack Based Measure

Authors: Masoud Saeedi, Shirin Rahimi Kazerooni, Vahid Parvaresh

Abstract:

Validity is an overriding consideration in language testing. If a test score is intended for a particular purpose, this must be supported through empirical evidence. This article addresses the validity of a multiple-choice achievement test (MCT). The test is administered at the end of each semester to decide about students' mastery of a course in general English. To provide empirical evidence pertaining to the validity of this test, two criterion measures were used. In so doing, a Cloze test and a C-test which are reported to gauge general English proficiency were utilized. The results of analyses show that there is a statistically significant correlation among participants' scores on the MCT, Cloze, and Ctest. Drawing on the findings of the study, it can be cautiously deduced that these tests measure the same underlying trait. However, allowing for the limitations of using criterion measures to validate tests, we cannot make any absolute claim as to the validity of this MCT test.

Keywords: C-test, cloze test, multiple-choice test, validity argument.

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Authors: Tarik H. Badi, Amer A. Boushaala

Abstract:

The purpose of this study was to measure the maximal isometric strength and to investigate the effects of different handleheights and elbow angles with respect to Mid. sagittal plane on the pushing and pulling strength in vertical direction. Eight male subjects performed a series of static strength measurement for each subject. The highest isometric strength was found in pulling at shoulder height (S.H.) (Mean = 60.29 lb., SD = 16.78 lb.) and the lowest isometric strength was found also in pulling at elbow height (E.H.) (Mean = 33.06 lb., SD = 6.56 lb.). Although the isometric strengths were higher at S.H than at E.H. for both activities, the maximal isometric strengths were compared statistically. ANOVA was performed. The results of the experiment revealed that there was a significant different between handle heights. However, there were no significant different between angles and activities, also no correlation between grip strength and activities.

Keywords: Pushing and pulling, one arm, vertical direction, isometric strength.

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Authors: Khalid Elasnaoui, Brahim Aksasse, Mohammed Ouanan

Abstract:

In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, Statistical moments, Indexing, Similarity distance, Histograms intersection.

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: Segmentation, color-texture, neural networks, fractal, watershed.

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Authors: Zane Turner, Kevin Labille, Susan Gauch

Abstract:

Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: Lexicon, sentiment analysis, stock movement prediction., computational finance.

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Authors: Hanan Mahmoud Ezzat Mahmoud, Alaa Abd El Fatah Hefnawy

Abstract:

In this paper, we present a system for content-based retrieval of large database of classified satellite images, based on user's relevance feedback (RF).Through our proposed system, we divide each satellite image scene into small subimages, which stored in the database. The modified radial basis functions neural network has important role in clustering the subimages of database according to the Euclidean distance between the query feature vector and the other subimages feature vectors. The advantage of using RF technique in such queries is demonstrated by analyzing the database retrieval results.

Keywords: content-based image retrieval, large database of image, RBF neural net, relevance feedback

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Authors: Manisha Chaudhary, Joydip Dhar, Govind Prasad Sahu

Abstract:

A mathematical model is proposed considering the forest biomass density B(t), density of wood based industries W(t) and density of synthetic industries S(t). It is assumed that the forest biomass grows logistically in the absence of wood based industries, but depletion of forestry biomass is due to presence of wood based industries. The growth of wood based industries depends on B(t), while S(t) grows at a constant rate, independent of B(t). Further there is a competition between W(t) and S(t) according to market demand. The proposed model has four ecologically feasible steady states, namely, E1: forest biomass free and wood industries free equilibrium; E2: wood industries free equilibrium and two coexisting equilibria E∗1 , E∗2 . Behavior of the system near all feasible equilibria is analyzed using the stability theory of differential equations. In the proposed model, the natural depletion rate h1 is a crucial parameter and system exhibits Hopf-bifurcation about the non-trivial equilibrium with respect to h1. The analytical results are verified using numerical simulation.

Keywords: A mathematical model, Competition between wood based and synthetic industries, Hopf-bifurcation, Stability analysis.

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Authors: Jaehwan Kang, Haejung Lee

Abstract:

This paper introduces an automatic voice classification system for the diagnosis of individual constitution based on Sasang Constitutional Medicine (SCM) in Traditional Korean Medicine (TKM). For the developing of this algorithm, we used the voices of 309 female speakers and extracted a total of 134 speech features from the voice data consisting of 5 sustained vowels and one sentence. The classification system, based on a rule-based algorithm that is derived from a non parametric statistical method, presents 3 types of decisions: reserved, positive and negative decisions. In conclusion, 71.5% of the voice data were diagnosed by this system, of which 47.7% were correct positive decisions and 69.7% were correct negative decisions.

Keywords: Voice Classifier, Sasang Constitution Medicine, Traditional Korean Medicine, SCM, TKM.

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Authors: Zehra Sultan

Abstract:

The study is based on the Task-based Language Teaching (TBLT) approach which is found to be very effective in the EFL/ESL classroom. This approach engages learners to acquire the usage of authentic language skills by interacting with the real world through a sequence of pedagogical tasks. The use of technology enhances the effectiveness of this approach. This study throws light on the historical background of TBLT, and its efficacy in the EFL /ESL classroom. In addition, this study precisely talks about the implementation of this approach in the General Foundation Program (GFP) of Muscat College, Oman. It furnishes the list of the pedagogical tasks embedded in the language curriculum of the GFP which are skillfully allied to the College graduate attributes. Moreover, the study also discusses the challenges pertaining to this approach from the point of view of teachers, students and its classroom application. Additionally, the operational success of this methodology is gauged through formative assessments of the GFP which is apparent in the students’ progress.

Keywords: Task-based language teaching, authentic language, communicative approach, real world activities, ESL/EFL activities.

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Authors: B. F. Oliveira, T. I. Gonçalves, M. M. Sousa, S. M. Pimenta, O. F. Ramalho, J. B. Cruz, F. V. Barbosa

Abstract:

The EU Circular Economy action plan, launched in 2020, is one of the major initiatives to promote the transition into a more sustainable industry. The circular economy is a popular concept used by many companies nowadays. Some industries are better forwarded to this reality than others, and the tannery industry is a sector that needs more attention due to its strong environmental impact caused by its dimension, intensive resources consumption, lack of recyclability, and second use of its products, as well as the industrial effluents generated by the manufacturing processes. For these reasons, the zero-waste goal and the European objectives are further being achieved. In this context, a need arises to provide an effective methodology that allows to determine the level of circularity of tannery companies. Regarding the complexity of the circular economy concept, few factories have a specialist in sustainability to assess the company’s circularity or have the ability to implement circular strategies that could benefit the manufacturing processes. Although there are several methodologies to assess circularity in specific industrial sectors, there is not an easy go-to methodology applied in factories aiming for cleaner production. Therefore, a straightforward methodology to assess the level of circularity, in this case of a tannery industry, is presented and discussed in this work, allowing any company to measure the impact of its activities. The methodology developed consists in calculating the Overall Circular Index (OCI) by evaluating the circularity of four key areas -energy, material, economy and social- in a specific factory. The index is a value between 0 and 1, where 0 means a linear economy, and 1 is a complete circular economy. Each key area has a sub-index, obtained through key performance indicators (KPIs) regarding each theme, and the OCI reflects the average of the four sub-indexes. Some fieldwork in the appointed company was required in order to obtain all the necessary data. By having separate sub-indexes, one can observe which areas are more linear than others. Thus, it is possible to work on the most critical areas by implementing strategies to increase the OCI. After these strategies are implemented, the OCI is recalculated to check the improvements made and any other changes in the remaining sub-indexes. As such, the methodology in discussion works through continuous improvement, constantly reevaluating and improving the circularity of the factory. The methodology is also flexible enough to be implemented in any industrial sector by adapting the KPIs. This methodology was implemented in a selected Portuguese small and medium-sized enterprises (SME) tannery industry and proved to be a relevant tool to measure the circularity level of the factory. It was witnessed that it is easier for non-specialists to evaluate circularity and identify possible solutions to increase its value, as well as learn how one action can impact their environment. In the end, energetic and environmental inefficiencies were identified and corrected, increasing the sustainability and circularity of the company. Through this work, important contributions were provided, helping the Portuguese SMEs to achieve the European and UN 2030 sustainable goals.

Keywords: Circular economy, circularity index, sustainability, tannery industry, zero-waste.

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Authors: MK Lee, JS Hong, SM Sin, HU Oh

Abstract:

Heat pipes are used to control the thermal problem for electronic cooling. It is especially difficult to dissipate heat to a heat sink in an environment in space compared to earth. For solving this problem, in this study, the Poiseuille (Po) number, which is the main measure of the performance of a heat pipe, is studied by CFD; then, the heat pipe performance is verified with experimental results. A heat pipe is then fabricated for a spatial environment, and an in-house code is developed. Further, a heat pipe subsystem, which consists of a heat pipe, MLI (Multi Layer Insulator), SSM (Second Surface Mirror), and radiator, is tested and correlated with the TMM (Thermal Mathematical Model) through a commercial code. The correlation results satisfy the 3K requirement, and the generated thermal model is verified for application to a spatial environment.

Keywords: CFD, Heat pipe, Radiator, Space.

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Authors: King Kuok Kuok, Po Chan Chiu

Abstract:

Floods are natural phenomena, which may turn into disasters causing widespread damage, health problems and even deaths. Nowadays, floods had become more serious and more frequent due to climatic changes. During flooding, discharge measurement still can be taken by standing on the bridge across the river using portable measurement instrument. However, it is too dangerous to get near to the river especially during high flood. Therefore, this study employs Particle Image Velocimetry (PIV) as a tool to measure the surface flow velocity. PIV is a image processing technique to track the movement of water from one point to another. The PIV codes are developed using Matlab. In this study, 18 ping pong balls were scattered over the surface of the drain and images were taken with a digital SLR camera. The images obtained were analyzed using the PIV code. Results show that PIV is able to produce the flow velocity through analyzing the series of images captured.

Keywords: Particle Image Velocimetry, flow velocity, surface flow.

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Authors: Zane Turner, Kevin Labille, Susan Gauch

Abstract:

Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: Computational finance, sentiment analysis, sentiment lexicon, stock movement prediction.

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

Abstract:

This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: Vehicle classification, signal processing, road traffic model, magnetic sensing.

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Authors: Ruilian Zhao, Ling Lin

Abstract:

MM-Path, an acronym for Method/Message Path, describes the dynamic interactions between methods in object-oriented systems. This paper discusses the classifications of MM-Path, based on the characteristics of object-oriented software. We categorize it according to the generation reasons, the effect scope and the composition of MM-Path. A formalized representation of MM-Path is also proposed, which has considered the influence of state on response method sequences of messages. .Moreover, an automatic MM-Path generation approach based on UML Statechart diagram has been presented, and the difficulties in identifying and generating MM-Path can be solved. . As a result, it provides a solid foundation for further research on test cases generation based on MM-Path.

Keywords: MM-Path, Message Sequence, Object-Oriented Integration Testing, Response Method Sequence, UML Statechart Diagram.

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Authors: Ajoy Kumar Das, Prasenjit Dey

Abstract:

Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nanoparticles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: Forced convection, Square cylinder, nanofluid, neural network.

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Authors: Hatam H. Ali, Mohd Shahrizal Sunar, Hoshang Kolivand, Mohd Azhar Bin M. Arsad

Abstract:

Rendering light shafts is one of the important topics in computer gaming and interactive applications. The methods and models that are used to generate light shafts play crucial role to make a scene more realistic in computer graphics. This article discusses the image-based shadows and geometric-based shadows that contribute in generating volumetric shadows and light shafts, depending on ray tracing, radiosity, and ray marching technique. The main aim of this study is to provide researchers with background on a progress of light scattering methods so as to make it available for them to determine the technique best suited to their goals. It is also hoped that our classification helps researchers find solutions to the shortcomings of each method.

Keywords: Shaft of lights, realistic images, image-based, and geometric-based.

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Authors: M. Razak, A. Jusoh, A. Zakaria

Abstract:

This paper presents an on-going research work on the implementation of feature-based machining via macro programming. Repetitive machining features such as holes, slots, pockets etc can readily be encapsulated in macros. Each macro consists of methods on how to machine the shape as defined by the feature. The macro programming technique comprises of a main program and subprograms. The main program allows user to select several subprograms that contain features and define their important parameters. With macros, complex machining routines can be implemented easily and no post processor is required. A case study on machining of a part that comprised of planar face, hole and pocket features using the macro programming technique was carried out. It is envisaged that the macro programming technique can be extended to other feature-based machining fields such as the newly developed STEP-NC domain.

Keywords: Feature-based machining, CNC, Macro, STEP-NC.

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: Enhanced ideal gas molecular movement, ideal gas molecular movement, model updating method, probability-based damage detection, uncertainty quantification.

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Authors: Myung-Won Lee, Keun-Chang Kwak

Abstract:

This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation.

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Authors: Chutchada Nusai, Yoshimi Suzuki, Haruaki Yamazaki

Abstract:

Selecting the word translation from a set of target language words, one that conveys the correct sense of source word and makes more fluent target language output, is one of core problems in machine translation. In this paper we compare the 3 methods of estimating word translation probabilities for selecting the translation word in Thai – English Machine Translation. The 3 methods are (1) Method based on frequency of word translation, (2) Method based on collocation of word translation, and (3) Method based on Expectation Maximization (EM) algorithm. For evaluation we used Thai – English parallel sentences generated by NECTEC. The method based on EM algorithm is the best method in comparison to the other methods and gives the satisfying results.

Keywords: Machine translation, EM algorithm.

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Authors: R. Estrada, A. Henriquez, R. Becerra, C. Laguna

Abstract:

Spatial Augmented Reality is a variation of Augmented Reality where the Head-Mounted Display is not required. This variation of Augmented Reality is useful in cases where the need for a Head-Mounted Display itself is a limitation. To achieve this, Spatial Augmented Reality techniques substitute the technological elements of Augmented Reality; the virtual world is projected onto a physical surface. To create an interactive spatial augmented experience, the application must be aware of the spatial relations that exist between its core elements. In this case, the core elements are referred to as a projection system and an input system, and the process to achieve this spatial awareness is called system calibration. The Spatial Augmented Reality system is considered calibrated if the projected virtual world scale is similar to the real-world scale, meaning that a virtual object will maintain its perceived dimensions when projected to the real world. Also, the input system is calibrated if the application knows the relative position of a point in the projection plane and the RGB-depth sensor origin point. Any kind of projection technology can be used, light-based projectors, close-range projectors, and screens, as long as it complies with the defined constraints; the method was tested on different configurations. The proposed procedure does not rely on a physical marker, minimizing the human intervention on the process. The tests are made using a Kinect V2 as an input sensor and several projection devices. In order to test the method, the constraints defined were applied to a variety of physical configurations; once the method was executed, some variables were obtained to measure the method performance. It was demonstrated that the method obtained can solve different arrangements, giving the user a wide range of setup possibilities.

Keywords: Color depth sensor, human computer interface, interactive surface, spatial augmented reality.

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Authors: Daniela I. Borissova, Ivan C. Mustakerov, Evgeni D. Bantutov

Abstract:

Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules  satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm. 

Keywords: Night vision devices, design modeling, software architecture, web-based system.

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Authors: J. Lonska, V. Boronenko

Abstract:

The result of process of territory-s development is the territory-s state of development (TSoD), which is pointed towards the provision and improvement of people-s life conditions. The authors offer to measure the TSoD according to their own developed model. Using the available statistical data regarding the values of model-s elements, the authors empirically show which element mainly determines the TSoD. The findings of the research showed that the key elements of the TSoD are the “Material welfare of people" and “People-s health". Performing a deeper statistical analysis of correlation between these elements, it turned out that it is not so necessary for a country to be bent on trying to increase the material growth of a territory, because a relatively high index of life expectancy at birth could be ensured also by much more modest material resources. On the other hand, the economical feedback of longer lifespan within countries with lower material performance is also relatively low.

Keywords: Development indices, health, territory's state of development, wealth.

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Authors: Suzan Wedyan

Abstract:

Associative classification (AC) is a data mining approach that combines association rule and classification to build classification models (classifiers). AC has attracted a significant attention from several researchers mainly because it derives accurate classifiers that contain simple yet effective rules. In the last decade, a number of associative classification algorithms have been proposed such as Classification based Association (CBA), Classification based on Multiple Association Rules (CMAR), Class based Associative Classification (CACA), and Classification based on Predicted Association Rule (CPAR). This paper surveys major AC algorithms and compares the steps and methods performed in each algorithm including: rule learning, rule sorting, rule pruning, classifier building, and class prediction.

Keywords: Associative Classification, Classification, Data Mining, Learning, Rule Ranking, Rule Pruning, Prediction.

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Authors: Yang Weiping, Zhang Zhilong, Zhang Yan, Chen Zengping

Abstract:

Infrared focal plane arrays (IRFPA) sensors, due to their high sensitivity, high frame frequency and simple structure, have become the most prominently used detectors in military applications. However, they suffer from a common problem called the fixed pattern noise (FPN), which severely degrades image quality and limits the infrared imaging applications. Therefore, it is necessary to perform non-uniformity correction (NUC) on IR image. The algorithms of non-uniformity correction are classified into two main categories, the calibration-based and scene-based algorithms. There exist some shortcomings in both algorithms, hence a novel non-uniformity correction algorithm based on non-linear fit is proposed, which combines the advantages of the two algorithms. Experimental results show that the proposed algorithm acquires a good effect of NUC with a lower non-uniformity ratio.

Keywords: Non-uniformity correction, non-linear fit, two-point correction, temporal Kalman filter.

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Authors: Claudiu N.Musat

Abstract:

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.

Keywords: Clustering, layout, k-means, spam.

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Authors: Minsun Kim, Ki-Sun Choi, Hyun-Jee Lee, Young-Chan You

Abstract:

There is no reinforcement example for the renovation of the vertical and horizontal extension to existing building structures which is a shear wall type in apartment units in Korea. Among these existing structures, the structures which are shear wall type are rare overseas, while Korea has many shear wall apartment units. Recently, in Korea, a few researchers are trying to confirm the possibility of the vertical extension in existing building with shear walls. This study evaluates the possibility of the renovation by applying performance-based seismic design to existing buildings with shear walls in the analysis phase of the structure. In addition, force-based seismic design, used by general structural engineers in Korea, is carried out to compare the amount of reinforcement of walls, which is a main component of wall structure. As a result, we suggest that performance-based design obtains more economical advantages than force-based seismic design.

Keywords: Vertical extension, performance-based design, renovation, shear wall structure, structural analysis.

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Authors: Lili Sun, Hua Wang

Abstract:

As privacy becomes a major concern for consumers and enterprises, many research have been focused on the privacy protecting technology in recent years. In this paper, we present a comprehensive approach for usage access control based on the notion purpose. In our model, purpose information associated with a given data element specifies the intended use of the subjects and objects in the usage access control model. A key feature of our model is that it allows when an access is required, the access purpose is checked against the intended purposes for the data item. We propose an approach to represent purpose information to support access control based on purpose information. Our proposed solution relies on usage access control (UAC) models as well as the components which based on the notions of the purpose information used in subjects and objects. Finally, comparisons with related works are analyzed.

Keywords: Purpose, privacy, access control, authorization

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Authors: C. Pislaru, A. Shebani

Abstract:

This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the KMeans clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: System identification, Nonlinear system, Neural networks, RBF neural network.

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