Search results for: Genetic Algorithm Logistic Regression

Authors: Pushpa B. Patil, Manesh B. Kokare

Abstract:

This paper presents content-based image retrieval (CBIR) frameworks with relevance feedback (RF) based on combined learning of support vector machines (SVM) and AdaBoosts. The framework incorporates only most relevant images obtained from both the learning algorithm. To speed up the system, it removes irrelevant images from the database, which are returned from SVM learner. It is the key to achieve the effective retrieval performance in terms of time and accuracy. The experimental results show that this framework had significant improvement in retrieval effectiveness, which can finally improve the retrieval performance.

Keywords: Image retrieval, relevance feedback, wavelet transform.

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Authors: S.G.Venkatesh, S.K.Ayyaswamy, G.Hariharan

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In this paper, we present a framework to determine Haar solutions of Bratu-type equations that are widely applicable in fuel ignition of the combustion theory and heat transfer. The method is proposed by applying Haar series for the highest derivatives and integrate the series. Several examples are given to confirm the efficiency and the accuracy of the proposed algorithm. The results show that the proposed way is quite reasonable when compared to exact solution.

Keywords: Haar wavelet method, Bratu's problem, boundary value problems, initial value problems, adomain decomposition method.

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Authors: Adnan Al-Smadi, Mahmoud Smadi

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This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.

Keywords: Cepstrum, bicepstrum, third order statistics

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Authors: Andrew Reilly, Nancy A. Rudd

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The appearance management behavior of tanning by gay men is examined through the lens of Impression Formation. The study proposes that body image, self-esteem, and internalized homophobia are connected and affect the motives for engaging in sun, salon, and cosmetic tanning. Motives examined were: to look masculine, to look attractive to (potential) partners, to look attractive in general, to socialize, to meet a peer standard, and for personal satisfaction. Using regression analysis to examine data of 103 gay men who engage in at least one method of tanning, results reveal that components of body image and internalized homophobia–but not self-esteem–are linked to various motives and methods of tanning. These findings support and extend the literature of Impression Formation Theory and provide practitioners in the health and healthrelated fields new avenues to pursue when dealing with diseases related to tanning.

Keywords: Body image, gay men, tanning.

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Authors: Tohru Kawabe

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In this paper, a new model predictive PID controller design method for the slip suppression control of EVs (electric vehicles) is proposed. The proposed method aims to improve the maneuverability and the stability of EVs by controlling the wheel slip ratio. The optimal control gains of PID framework are derived by the model predictive control (MPC) algorithm. There also include numerical simulation results to demonstrate the effectiveness of the method.

Keywords: Model Predictive Control, PID controller, Electric Vehicle, Slip suppression

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Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

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Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS₁ and MS₂), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS₁ is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS₁ is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: Barley, callus, embryo culture, mature embryo.

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Authors: Geeta Sikka, Arvinder Kaur Takkar, Moin Uddin

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Missing data is a persistent problem in almost all areas of empirical research. The missing data must be treated very carefully, as data plays a fundamental role in every analysis. Improper treatment can distort the analysis or generate biased results. In this paper, we compare and contrast various imputation techniques on missing data sets and make an empirical evaluation of these methods so as to construct quality software models. Our empirical study is based on NASA-s two public dataset. KC4 and KC1. The actual data sets of 125 cases and 2107 cases respectively, without any missing values were considered. The data set is used to create Missing at Random (MAR) data Listwise Deletion(LD), Mean Substitution(MS), Interpolation, Regression with an error term and Expectation-Maximization (EM) approaches were used to compare the effects of the various techniques.

Keywords: Missing data, Imputation, Missing Data Techniques.

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Authors: H. Ghanbari, H. Nikbakht, A. Zahedi, M. Ghanbari

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This paper is focusing on designing a control system for wind turbine which can control the speed and output power according to arbitrary algorithm. Reference Tracking Method is used to control the turbine spinning speed in order to increase its output energy.

Keywords: Wind Turbine, Simulink, Reference Tracking Method.

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Authors: Diego Ordonez, Carlos Dafonte, Minia Manteiga, Bernardino Arcayy

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This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition.

Keywords: Neural networks, Self-organizing feature maps, Hierarchicalsystems, Pattern clustering methods.

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Authors: F. Amin, A. H. Jahangir, H. Rasifard

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With the widespread growth of applications of Wireless Sensor Networks (WSNs), the need for reliable security mechanisms these networks has increased manifold. Many security solutions have been proposed in the domain of WSN so far. These solutions are usually based on well-known cryptographic algorithms. In this paper, we have made an effort to survey well known security issues in WSNs and study the behavior of WSN nodes that perform public key cryptographic operations. We evaluate time and power consumption of public key cryptography algorithm for signature and key management by simulation.

Keywords: Wireless Sensor Networks, Security, Public Key Cryptography, Key Management.

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Authors: Wissam B. Fahed

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Entrepreneurship has become an important and extensively researched concept in business studies. Research on foreign direct investment (FDI) has become widespread due to the growth of FDI and its importance in globalization. Most entrepreneurship studies examined the importance and influence of entrepreneurial orientation in a micro-level context. On the other hand, studies and research concerning FDI used statistical techniques to analyze the effect, determinants, and motives of FDI on a macroeconomic level, ignoring empirical studies on other noneconomic determinants. In order to bridge the gap between the theory and empirical evidence on FDI and the theory and research on entrepreneurship, this study examines the impact of entrepreneurship on inward foreign direct investment. The relationship between entrepreneurship and foreign direct investment is investigated through regression analysis of pooled time-series and cross-sectional data. The results suggest that entrepreneurship has a significant effect on FDI.

Keywords: Entrepreneurship, foreign direct investment, globalization, economic freedom.

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Authors: Christian Mayr, Matthias Ehrlich, Stephan Henker, Karsten Wendt, René Schüffny

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Traditionally, VLSI implementations of spiking neural nets have featured large neuron counts for fixed computations or small exploratory, configurable nets. This paper presents the system architecture of a large configurable neural net system employing a dedicated mapping algorithm for projecting the targeted biology-analog nets and dynamics onto the hardware with its attendant constraints.

Keywords: Large scale VLSI neural net, topology mapping, complex pulse communication.

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of domestic and international trends of image processing for data in UAV (unmanned aerial vehicle) and also explains about UAV and Quadcopter. Overseas examples of image processing using UAV include image processing for totaling the total numberof vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT(scale invariant features transform) matching, and application of median filter and thresholding. In Korea, many studies are underway including visualization of new urban buildings.

Keywords: Image Processing, UAV, Quadcopter, Target detection.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha

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Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.

Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.

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Authors: K.Amrithavarshini, S.Chandrachudeswaran

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This paper presents an idea to improve the efficiency of security checks in airports through the active tracking and monitoring of passengers and staff using OFDM modulation technique and Finger print authentication. The details of the passenger are multiplexed using OFDM .To authenticate the passenger, the fingerprint along with important identification information is collected. The details of the passenger can be transmitted after necessary modulation, and received using various transceivers placed within the premises of the airport, and checked at the appropriate check points, thereby increasing the efficiency of checking. OFDM has been employed for spectral efficiency.

Keywords: Orthogonal Frequency Division Multiplexing, FFT Algorithm, Fingerprint Authentication, Airport Security

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Authors: K .Belhadi, H. Bousselsela, M. Yahia, A. Zidani, S. Benbia

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Sickle cell anemia is a recessive genetic disease caused by the presence in the red blood cell, of abnormal hemoglobin called hemoglobin S. It results from the replacement in the beta chain of the acid glutamic acid by valin at position 6. Topics may be homozygous (SS) or heterozygous (AS) most often asymptomatic. Other mutations result in compound heterozygous: - Synthesis of hemoglobin C mutation in the sixth leucin codon (heterozygous SC); - ß-thalassemia (heterozygous S-ß thalassemia). SS homozygous, heterozygous SC and S- ß -thalassemia are grouped under the major sickle cell syndromes. To make a laboratory diagnosis of hemoglobinopathies in a portion of the population in region of Batna, our study was conducted on 115 patients with suspected sickle cell anemia, all cases have benefited from hematological tests as blood count (count RBC, calculated erythrocyte indices, MCV and MCHC, measuring the hemoglobin concentration) and a biochemical test in this case electrophoresis CAPILLARYS HEMOGLOBIN (E). The results showed: 27 cases of sickle cell anemia were found on 115 suspected cases, 73,03% homozygous sickle cell disease and 59,25% sickle cell trait. Finally, the double heterozygous S/C, represent the incidence rate of 3, 70%.

Keywords: Hemoglobin, sickle cell syndromes, laboratory diagnosis

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Authors: Débora V. Busman, Venerando E. Amaro, Mattheus da C. Prudêncio

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Prognostic studies of the shoreline are of utmost importance for Ponta Negra Beach, located in Natal, Northeastern Brazil, where the infrastructure recently built along the shoreline is severely affected by flooding and erosion. This study compares shoreline predictions using three linear regression methods (LMS, LRR and WLR) and tries to discern the best method for different shoreline position scenarios. The methods have shown erosion on the beach in each of the scenarios tested, even in less intense dynamic conditions. The WLA_A with confidence interval of 95% was the well-adjusted model and calculated a retreat of -1.25 m/yr to -2.0 m/yr in hot spot areas. The change of the shoreline on Ponta Negra Beach can be measured as a negative exponential curve. Analysis of these methods has shown a correlation with the morphodynamic stage of the beach.

Keywords: Coastal Erosion, Prognostic Model, DSAS.

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Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller

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This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.

Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.

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Authors: A.F. Salarashayeri, M. Siosemarde

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Hydraulic conductivity is one parameter important for predicting the movement of water and contaminants dissolved in the water through the soil. The hydraulic conductivity is measured on soil samples in the lab and sometimes tests carried out in the field. The hydraulic conductivity has been related to soil particle diameter by a number of investigators. In this study, 25 set of soil samples with sand texture. The results show approximately success in predicting hydraulic conductivity from particle diameters data. The following relationship obtained from multiple linear regressions on data (R2 = 0.52): Where d10, d50 and d60, are the soil particle diameter (mm) that 10%, 50% and 60% of all soil particles are finer (smaller) by weight and Ks, saturated hydraulic conductivity is expressed in m/day. The results of regression analysis showed that d10 play a more significant role with respect to Ks, saturated hydraulic conductivity (m/day), and has been named as the effective parameter in Ks calculation.

Keywords: hydraulic conductivity, particle diameter, particle-size distribution and soil

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari

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Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Eigen Face, Multidimensional, Matching, PCA.

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Authors: Davod Zaravi, Habib Rostami, Alireza Malahzaheh, S. S. Mortazavi

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In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.

Keywords: Text extraction, colored cover sheet, wavelet threshold, region of interest.

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Authors: Aimen Batool Bint-E-Rashid, Huma Irfan

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This research aims to investigate the role of social media (Snapchat, Facebook, Twitter, etc.) in our daily lives and its implication on our everyday routine in the form of stressors. The study has been validated by a social media survey with 150 social media users belonging to various age groups. The study explores how social media can make an individual anti-social in his or her life offline. To explain the phenomenon, we have proposed and evaluated a model based on social media usage and stressors including burnout and social overload. Results, through correlation and regression tests, have revealed that with increase in social media usage, social overload and burnout also increases. Evidence for the fact that excessive social media usage causes social overload and burnout has been provided in the study.

Keywords: Burnout, emotional exhaustion, fatigue, stressors, social networking, social media, social overload.

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Authors: Wang Xingbo

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Computation of determinant in the form |I-X| is primary and fundamental because it can help to compute many other determinants. This article puts forward a time-reducible approach to compute determinant |I-X|. The approach is derived from the Newton’s identity and its time complexity is no more than that to compute the eigenvalues of the square matrix X. Mathematical deductions and numerical example are presented in detail for the approach. By comparison with classical approaches the new approach is proved to be superior to the classical ones and it can naturally reduce the computational time with the improvement of efficiency to compute eigenvalues of the square matrix.

Keywords: Algorithm, determinant, computation, eigenvalue, time complexity.

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

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This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets.

Keywords: Human motion recognition, Discriminative LMA features, random forest, features reduction.

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Authors: Minyoung Eom, Yoonsik Choe

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In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords: DCT, Descriptor, EHD, MPEG7.

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Authors: Takashi Yamauchi, Anju Sudo, Yoshihiko Tanno

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Recently, it has been suggested that thought control strategies aimed at controlling unwanted thoughts may be used to cope with paranoid thoughts in both clinical and nonclinical samples. The current study aims to examine the type of thought control strategies that were associated with the frequency of paranoid thoughts in nonclinical samples. A total of 159 Japanese undergraduate students completed the two scales–the Paranoia Checklist and the Thought Control Questionnaire. A hierarchical multiple regression analysis demonstrated that worry-based control strategies were associated with paranoid thoughts, whereas distraction- and social-based control strategies were inversely associated with paranoid thoughts. Our findings suggest that in a nonclinical population, worry-based strategies may be especially maladaptive, whereas distraction- and social-based strategies may be adaptive to paranoid thoughts.

Keywords: Nonclinical population, paranoid thoughts, thoughtcontrol strategies.

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Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).

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Authors: Wided Guezguez, Nahla Ben Amor

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This paper proposes a new decision making approch based on quantitative possibilistic influence diagrams which are extension of standard influence diagrams in the possibilistic framework. We will in particular treat the case where several expert opinions relative to value nodes are available. An initial expert assigns confidence degrees to other experts and fixes a similarity threshold that provided possibility distributions should respect. To illustrate our approach an evaluation algorithm for these multi-source possibilistic influence diagrams will also be proposed.

Keywords: influnece diagram, decision making, graphical decision models, influence diagrams, possibility theory.

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Authors: Edward Paul Guillen, Diego Alejandro Chacon

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The VoIP networks as alternative method to traditional PSTN system has been implemented in a wide variety of structures with multiple protocols, codecs, software and hardware–based distributions. The use of cryptographic techniques let the users to have a secure communication, but the calculate throughput as well as the QoS parameters are affected according to the used algorithm. This paper analyzes the VoIP throughput and the QoS parameters with different commercial encryption methods. The measurement–based approach uses lab scenarios to simulate LAN and WAN environments. Security mechanisms such as TLS, SIAX2, SRTP, IPSEC and ZRTP are analyzed with μ-LAW and GSM codecs.

Keywords: VoIP, Secure VoIP, Throughput Analysis, VoIP QoS evaluation

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