Search results for: Dimensionality reduction

Authors: Reza Nadimi, Fariborz Jolai

Abstract:

This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysis techniques, have been proposed as data reduction and classification technique, which can be applied in data envelopment analysis (DEA) technique for reduction input – output data. Numerical results reveal that the new approach shows a good consistency in ranking with DEA.

Keywords: Effectiveness, Decision Making, Data EnvelopmentAnalysis, Factor Analysis

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Authors: J.V.R.Ravindra, M.B.Srinivas,

Abstract:

Accurate modeling of high speed RLC interconnects has become a necessity to address signal integrity issues in current VLSI design. To accurately model a dispersive system of interconnects at higher frequencies; a full-wave analysis is required. However, conventional circuit simulation of interconnects with full wave models is extremely CPU expensive. We present an algorithm for reducing large VLSI circuits to much smaller ones with similar input-output behavior. A key feature of our method, called Frequency Shift Technique, is that it is capable of reducing linear time-varying systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers, RF components and switched-capacitor filters. Reduction is obtained by projecting the original system described by linear differential equations into a lower dimension. Experiments have been carried out using Cadence Design Simulator cwhich indicates that the proposed technique achieves more % reduction with less CPU time than the other model order reduction techniques existing in literature. We also present applications to RF circuit subsystems, obtaining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy.

Keywords: Model order Reduction, RLC, crosstalk

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Authors: Sanjay Singh, M Sathish Kumar, H. S Mruthyunjaya

Abstract:

Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication systems. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. A major drawback of OFDM is the high Peak-to-Average Power Ratio (PAPR) of the transmit signal which can significantly impact the performance of the power amplifier. In this paper we have compared the PAPR reduction performance of Golay and Reed-Muller coded OFDM signal. From our simulation it has been found that the PAPR reduction performance of Golay coded OFDM is better than the Reed-Muller coded OFDM signal. Moreover, for the optimum PAPR reduction performance, code configuration for Golay and Reed-Muller codes has been identified.

Keywords: OFDM, PAPR, Perfect Codes, Golay Codes, Reed-Muller Codes

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Authors: Brigita Altenbaher

Abstract:

In recent years there has been a continuous increase of axle loads, tonnage, train speed and train length which has increased both the productivity in the rail sector and the risk of rail breaks and derailments. On the other hand, the environmental requirements (e.g. noise reduction) for railway operations will become tighter in the future. In our research we developed a new composite material which does not change braking properties, is capable of taking extremely high pressure loads, reduces noise and is environmentally friendly. Part of our research was also the development of technology which will be able to apply this material to the rail. The result of our research was the system which reduces the wear out significantly and almost completely eliminates the squealing noise at the same time, and by using only one special material.

Keywords: Active protection, composite material, lubrication, noise reduction, reduction at source, railway.

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Authors: Myungsook Klassen

Abstract:

Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine its effectiveness as inputs. The feed forward neural network of Levenberg-Marquardt algorithm is applied to perform one step ahead forecasting of NASDAQ and Dow stock prices.

Keywords: Stock Market Prediction, Neural Networks, Levenberg-Marquadt Algorithm, Technical Indexes

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Authors: Souleymane Oumtanaga, Falilu Abudul Kadiri

Abstract:

Internet is without any doubt the fastest and effective mean of communication making it possible to reach a great number of people in the world. It draws its base from exchange points. Indeed exchange points are used to inter-connect various Internet suppliers and operators in order to allow them to exchange traffic and it is with these interconnections that Internet made its great strides. They thus make it possible to limit the traffic delivered via the operators of transits. This limitation allows a significant improvement of the quality of service, a reduction in the latency time just as a reduction of the cost of connection for the final subscriber. Through this article we will show how the installation of an IXP allows an improvement and a diversification of the services just as a reduction of the Internet connection costs.

Keywords: Quality of service, Exchange point, interconnection, Service providers, bandwidth, traffic, routers, routing table.

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Authors: А. V. Panko, Е. V. Ablets, I. G. Kovzun, М. А. Ilyashov

Abstract:

Based upon generalized analysis of modern know-how in the sphere of processing, concentration and purification of iron-ore raw materials (IORM), in particular, the most widespread ferrioxide-silicate materials (FOSM), containing impurities of phosphorus and other elements compounds, noted special role of nanotechnological initiatives in improvement of such processes. Considered ideas of role of nanoparticles in processes of FOSM carbonization with subsequent direct reduction of ferric oxides contained in them to metal phase, as well as in processes of alkali treatment and separation of powered iron from phosphorus compounds. Using the obtained results the wasteless method of solid-phase processing, concentration and purification of IORM and FOSM from compounds of phosphorus, silicon and other impurities was developed and it excels known methods of direct iron reduction from iron ores and metallurgical slimes.

Keywords: Iron ores, solid-phase reduction, nanoparticles in reduction and purification of iron from silicon and phosphorus, wasteless method of ores processing.

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Authors: A.O. Ladjedel, B.T.Yahiaoui, C.L.Adjlout, D.O.Imine

Abstract:

In the present paper; an experimental and numerical investigations of drag reduction on a grooved circular cylinder have been performed. The experiments were carried out in closed circuit subsonic wind tunnel (TE44); the pressure distribution on the cylinder was conducted using a TE44DPS differential pressure scanner and the drag forces were measured using the TE81 balance. The display unit is linked to a computer, loaded with DATASLIM software for data analysis and logging of result. The numerical study was performed using the code ANSYS FLUENT solving the Reynolds Averaged Navier-Stokes (RANS) equations. The k-ε and k- ω SST models were tested. The results obtained from the experimental and numerical investigations have showed a reduction in the drag when using longitudinal grooves namely 2 and 6 on the cylinder.

Keywords: Circular cylinder, Drag, grooves, pressure distribution

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Authors: K. Yılmaz, B. Birol, M. N. Sarıdede, E. Yiğit

Abstract:

A bauxite ore can be utilized in Bayer Process, if the mass ratio of Al2O3 to SiO2 is greater than 10. Otherwise, its FexOy and SiO2 content should be removed. On the other hand, removal of TiO2 from the bauxite ore would be beneficial because of both lowering the red mud residue and obtaining a valuable raw material containing TiO2 mineral. In this study, the low grade diasporic bauxite ore of Yalvaç, Isparta, Turkey was roasted under reducing atmosphere and subjected to magnetic separation. According to the experimental results, 800°C for reduction temperature and 20000 Gauss of magnetic intensity were found to be the optimum parameters for removal of iron oxide and rutile from the nonmagnetic ore. On the other hand, 600°C and 5000 Gauss were determined to be the optimum parameters for removal of silica from the non-magnetic ore.

Keywords: Low grade diasporic bauxite, magnetic separation, reduction roasting, separation index.

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Authors: M. Yousefi, N. Nasirzadeh

Abstract:

In this paper, dynamic comparator structure employing two methods for power consumption reduction with applications in low-power high-speed analog-to-digital converters have been presented. The proposed comparator has low consumption thanks to power reduction methods. They have the ability for offset adjustment. The comparator consumes 14.3 μW at 100 MHz which is equal to 11.8 fJ. The comparator has been designed and simulated in 180 nm CMOS. Layouts occupy 210 μm².

Keywords: Comparator, low, power, efficiency.

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Authors: N. Phanthuna, J. Jaturacherdchaiskul, S. Lerdvanittip, S. Auchariyamet

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This paper proposes a particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problems. For the ELD problem in this work, the objective function is to minimize the total fuel cost of all generator units for a given daily load pattern while the main constraints are power balance and generation output of each units. Case study in the test system of 40-generation units with 6 load patterns is presented to demonstrate the performance of PSO in solving the ELD problem. It can be seen that the optimal solution given by PSO provides the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.

Keywords: Particle Swarm Optimization, Economic Load Dispatch, Loss Reduction.

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Authors: Yohei Saika, Yuji Haraguchi

Abstract:

We constructed a method of noise reduction for JPEG-compressed image based on Bayesian inference using the maximizer of the posterior marginal (MPM) estimate. In this method, we tried the MPM estimate using two kinds of likelihood, both of which enhance grayscale images converted into the JPEG-compressed image through the lossy JPEG image compression. One is the deterministic model of the likelihood and the other is the probabilistic one expressed by the Gaussian distribution. Then, using the Monte Carlo simulation for grayscale images, such as the 256-grayscale standard image “Lena" with 256 × 256 pixels, we examined the performance of the MPM estimate based on the performance measure using the mean square error. We clarified that the MPM estimate via the Gaussian probabilistic model of the likelihood is effective for reducing noises, such as the blocking artifacts and the mosquito noise, if we set parameters appropriately. On the other hand, we found that the MPM estimate via the deterministic model of the likelihood is not effective for noise reduction due to the low acceptance ratio of the Metropolis algorithm.

Keywords: Noise reduction, JPEG-compressed image, Bayesian inference, the maximizer of the posterior marginal estimate

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Authors: Md. Mahmudul Hasan

Abstract:

OFDM systems are known to have a high PAPR (Peak-to-Average Power Ratio) compared with single-carrier systems. In fact, the high PAPR is one of the most detrimental aspects in the OFDM system, as it can cause power degradation (Inband distortion) and spectral spreading (Out-of-band radiation). In this paper, from the foundation of the PAPR analysis an effective method of PAPR reduction has been proposed based on Orthogonal Eigenvector Matrix (OEM) transform. Extensive computer simulations show that a PAPR reduction of up to 4.4 dB can be obtained without introducing in-band distortion or out-of-band radiation in the system.

Keywords: Orthogonal frequency division multiplexing (OFDM), peak-to-average power ratio (PAPR), Orthogonal Eigenvector Matrix (OEM).

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Authors: Mairwen K. Jones, Lynne Harris, Lisa D. Vaccaro

Abstract:

Obsessive-Compulsive Disorder (OCD) is a common and disabling condition. Therapist-delivered treatments that use exposure and response prevention have been found to be very effective in treating OCD, although they are costly and associated with high rates of attrition. Effective treatments that can be made widely available without the need for therapist contact are urgently needed. This case study represents the first published investigation of a self-administered cognitive treatment for OCD in a 50-year old female with a 20 year history of OCD. The treatment evaluation occurred over 27 weeks, including 12 weeks of self-administration of the Danger Ideation Reduction Therapy (DIRT) program. Decreases of between 23% to 33% on measures from pre-treatment to follow-up were observed. Bearing in mind the methodological limitations associated with a case study, we conclude that the results reported here are encouraging and indicate that further research effort evaluating the effectiveness of self-administered DIRT is warranted.

Keywords: Anxiety Treatment, Cognitive Therapy, Danger Ideation Reduction Therapy, Obsessive–Compulsive Disorder, Self- Administered Danger Ideation Reduction Therapy.

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Authors: Rana Yousef, Khalil el Hindi

Abstract:

The behavior of Radial Basis Function (RBF) Networks greatly depends on how the center points of the basis functions are selected. In this work we investigate the use of instance reduction techniques, originally developed to reduce the storage requirements of instance based learners, for this purpose. Five Instance-Based Reduction Techniques were used to determine the set of center points, and RBF networks were trained using these sets of centers. The performance of the RBF networks is studied in terms of classification accuracy and training time. The results obtained were compared with two Radial Basis Function Networks: RBF networks that use all instances of the training set as center points (RBF-ALL) and Probabilistic Neural Networks (PNN). The former achieves high classification accuracies and the latter requires smaller training time. Results showed that RBF networks trained using sets of centers located by noise-filtering techniques (ALLKNN and ENN) rather than pure reduction techniques produce the best results in terms of classification accuracy. The results show that these networks require smaller training time than that of RBF-ALL and higher classification accuracy than that of PNN. Thus, using ALLKNN and ENN to select center points gives better combination of classification accuracy and training time. Our experiments also show that using the reduced sets to train the networks is beneficial especially in the presence of noise in the original training sets.

Keywords: Radial basis function networks, Instance-based reduction, PNN.

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Authors: Cheng-Hsuan Huang, Eric Lee

Abstract:

Electrophoretic motion of a liquid droplet within an uncharged cylindrical pore is investigated theoretically in this study. It is found that the boundary effect in terms of the reduction of droplet mobility (droplet velocity per unit strength of the applied electric field) is very significant when the double layer surrounding the droplet is thick, and diminishes as it gets very thin. Moreover, the viscosity ratio of the ambient fluid to the internal one, σ, is a crucial factor in determining its electrophoretic behavior. The boundary effect is less significant as the viscosity ratio gets high. Up to 70% mobility reduction is observed when this ratio is low (σ = 0.01), whereas only 40% reduction when it is high (σ = 100). The results of this study can be utilized in various fields of biotechnology, such as a biosensor or a lab-on-a-chip device.

Keywords: Cylindrical pore, Electrophoresis, Lab-on-a-chip, Liquid droplet

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Authors: Jaime Carpio-García, Elena Blanco-Fernández, Javier González-Fernández, Daniel Castro-Fresno

Abstract:

Sustainable urban drainage systems (SUDS) are more often used in order to prevent floods, water treatment, fight against pollution, urban heat island effect, and global warming in applications like green roofs, permeable pavements, and others. Furthermore, geosynthetics are also worldwide used as a part of drainage systems in road construction. Geotextiles are an essential part of both, and one of the main geotextile properties in those applications is permeability, whose behavior is not well established along its service life. In this paper, clogging reduction design factors for an estimated service life of 25 years are experimentally obtained for five different geotextiles used in SUDS and roads combined with two different soils and with two pollutants, motor oil, and lime, in order to evaluate chemical clogging, too. The effect of characteristic opening size and other characteristics of the geosynthetics are also discussed in order to give civil engineers, together with the clogging reduction factors, a better long-time design of geotextiles used in their SUDS and roads.

Keywords: Geotextiles, drainage, clogging, reduction factor.

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Authors: Pavan S., Sridhar G., Sridhar V.

Abstract:

Super resolution is one of the commonly referred inference problems in computer vision. In the case of images, this problem is generally addressed using a graphical model framework wherein each node represents a portion of the image and the edges between the nodes represent the statistical dependencies. However, the large dimensionality of images along with the large number of possible states for a node makes the inference problem computationally intractable. In this paper, we propose a representation wherein each node can be represented as acombination of multiple regression functions. The proposed approach achieves a tradeoff between the computational complexity and inference accuracy by varying the number of regression functions for a node.

Keywords: Belief propagation, Graphical model, Regression, Super resolution.

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Authors: V. Sudha, D. Sriram Kumar

Abstract:

Orthogonal Frequency Division Multiplexing (OFDM) has been used in many advanced wireless communication systems due to its high spectral efficiency and robustness to frequency selective fading channels. However, the major concern with OFDM system is the high peak-to-average power ratio (PAPR) of the transmitted signal. Some of the popular techniques used for PAPR reduction in OFDM system are conventional partial transmit sequences (CPTS) and clipping. In this paper, a parallel combination/hybrid scheme of PAPR reduction using clipping and CPTS algorithms is proposed. The proposed method intelligently applies both the algorithms in order to reduce both PAPR as well as computational complexity. The proposed scheme slightly degrades bit error rate (BER) performance due to clipping operation and it can be reduced by selecting an appropriate value of the clipping ratio (CR). The simulation results show that the proposed algorithm achieves significant PAPR reduction with much reduced computational complexity.

Keywords: CCDF, OFDM, PAPR, PTS.

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Authors: Daniel Schwarz, Jan Fivaz, Alessia Neuroni

Abstract:

Although digitization is a buzzword in almost every election campaign, the political parties leave voters largely in the dark about their specific positions on digital issues. In the run-up to the 2019 elections in Switzerland, the ‘Digitization Monitor’ project (DMP) was launched in order to change this situation. Within the framework of the DMP, all 4,736 candidates were surveyed about their digital policy positions and values. The DMP is designed as a digital policy supplement to the existing ‘smartvote’ voting advice application. This enabled a direct comparison of the digital policy attitudes according to the DMP with the topics of the ‘smartvote’ questionnaire which are comprehensive in content but mainly related to conventional policy areas. This paper’s main research goal is to analyze and visualize possible differences between conventional and digital policy areas in terms of response patterns between and within political parties. The analysis is based on dimensionality reduction methods (multidimensional scaling and principal component analysis) for the visualization of inter-party differences, and on standard deviation as a measure of variation for the evaluation of intra-party unity. The results reveal that digital issues show a lower degree of inter-party polarization compared to conventional policy areas. Thus, the parties have more common ground in issues on digitization than in conventional policy areas. In contrast, the study reveals a mixed picture regarding intra-party unity. Homogeneous parties show a lower degree of unity in digitization issues whereas parties with heterogeneous positions in conventional areas have more united positions in digital areas. All things considered, the findings are encouraging as less polarized conditions apply to the debate on digital development compared to conventional politics. For the future, it would be desirable if in further countries similar projects to the DMP could emerge to broaden the basis for conclusions.

Keywords: Comparison of political issue dimensions, digital awareness of candidates, digital policy space, party positions on digital issues.

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Authors: E. Livya, G. Anitha, P. Valli

Abstract:

The main objective of aircraft aerodynamics is to enhance the aerodynamic characteristics and maneuverability of the aircraft. This enhancement includes the reduction in drag and stall phenomenon. The airfoil which contains dimples will have comparatively less drag than the plain airfoil. Introducing dimples on the aircraft wing will create turbulence by creating vortices which delays the boundary layer separation resulting in decrease of pressure drag and also increase in the angle of stall. In addition, wake reduction leads to reduction in acoustic emission. The overall objective of this paper is to improve the aircraft maneuverability by delaying the flow separation point at stall and thereby reducing the drag by applying the dimple effect over the aircraft wing. This project includes both computational and experimental analysis of dimple effect on aircraft wing, using NACA 0018 airfoil. Dimple shapes of Semi-sphere, hexagon, cylinder, square are selected for the analysis; airfoil is tested under the inlet velocity of 30m/s and 60m/s at different angle of attack (5˚, 10˚, 15˚, 20˚, and 25˚). This analysis favors the dimple effect by increasing L/D ratio and thereby providing the maximum aerodynamic efficiency, which provides the enhanced performance for the aircraft.

Keywords: Airfoil, Boundary layer, Dimple effect, Flow separation, Stall reduction.

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Authors: Hamed Vahdat Nejad, Hameed Reza Pourreza, Hasan Ebrahimi

Abstract:

A new fuzzy filter is presented for noise reduction of images corrupted with additive noise. The filter consists of two stages. In the first stage, all the pixels of image are processed for determining noisy pixels. For this, a fuzzy rule based system associates a degree to each pixel. The degree of a pixel is a real number in the range [0,1], which denotes a probability that the pixel is not considered as a noisy pixel. In the second stage, another fuzzy rule based system is employed. It uses the output of the previous fuzzy system to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Experimental results are obtained to show the feasibility of the proposed filter. These results are also compared to other filters by numerical measure and visual inspection.

Keywords: Additive noise, Fuzzy logic, Image processing, Noise reduction.

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Authors: Nicolás H. Beltrán, Manuel A. Duarte-Mermoud, Víctor A. Soto, Sebastián A. Salah, and Matías A. Bustos

Abstract:

Results of Chilean wine classification based on the information provided by an electronic nose are reported in this paper. The classification scheme consists of two parts; in the first stage, Principal Component Analysis is used as feature extraction method to reduce the dimensionality of the original information. Then, Radial Basis Functions Neural Networks is used as pattern recognition technique to perform the classification. The objective of this study is to classify different Cabernet Sauvignon, Merlot and Carménère wine samples from different years, valleys and vineyards of Chile.

Keywords: Feature extraction techniques, Pattern recognitiontechniques, Principal component analysis, Radial basis functionsneural networks, Wine classification.

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Authors: Mohana Sundaram Muthuvalu, Jumat Sulaiman

Abstract:

In this paper, application of the complexity reduction approach based on half- and quarter-sweep iteration concepts with Jacobi iterative method for solving composite trapezoidal (CT) algebraic equations is discussed. The performances of the methods for CT algebraic equations are comparatively studied by their application in solving linear Fredholm integral equations of the second kind. Furthermore, computational complexity analysis and numerical results for three test problems are also included in order to verify performance of the methods.

Keywords: Complexity reduction approach, Composite trapezoidal scheme, Jacobi method, Linear Fredholm integral equations

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Authors: V. Sudha, D. Sriram Kumar

Abstract:

In this paper, we present a low complexity hybrid scheme using conventional selective mapping (C-SLM) and clipping algorithms to reduce the high peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal. In the proposed scheme, the input data sequence (X) is divided into two sub-blocks, then clipping algorithm is applied to the first sub-block, whereas C-SLM algorithm is applied to the second sub-block in order to reduce both computational complexity and PAPR. The resultant time domain OFDM signal is obtained by combining the output of two sub-blocks. The simulation results show that the proposed hybrid scheme provides 0.45 dB PAPR reduction gain at CCDF value of 10-2 and 52% of computational complexity reduction when compared to C-SLM scheme at the expense of slight degradation in bit error rate (BER) performance.

Keywords: CCDF, Clipping, OFDM, PAPR, SLM.

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Authors: L. Della Ragione, G. Meccariello

Abstract:

In recent years in Italy the progress of the automobile industry, in the field of reduction of emissions values, is very remarkable. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. In this paper we dealt with the problem of describing a quantitatively approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars.

Keywords: Air pollution, Driving cycles, GPS signal.

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Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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Authors: Sanjay Singh, M Sathish Kumar, H. S Mruthyunjaya

Abstract:

Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication system. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. However the price paid for this high spectral efficiency and less intensive equalization is low power efficiency. OFDM signals are very sensitive to nonlinear effects due to the high Peak-to-Average Power Ratio (PAPR), which leads to the power inefficiency in the RF section of the transmitter. This paper investigates the effect of PAPR reduction on the performance parameter of multicarrier communication system. Performance parameters considered are power consumption of Power Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier efficiency, SNR of DAC and BER performance of the system. From our analysis it is found that irrespective of PAPR reduction technique being employed, the power consumption of PA and DAC reduces and power amplifier efficiency increases due to reduction in PAPR. Moreover, it has been shown that for a given BER performance the requirement of Input-Backoff (IBO) reduces with reduction in PAPR.

Keywords: BER, Crest Factor (CF), Digital-to-Analog Converter(DAC), Input-Backoff (IBO), Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), PowerAmplifier efficiency, SNR

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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