The Performance Improvement of Automatic Modulation Recognition Using Simple Feature Manipulation, Analysis of the HOS, and Voted Decision

The use of High Order Statistics (HOS) analysis is expected to provide so many candidates of features that can be selected for pattern recognition. More candidates of the feature can be extracted using simple manipulation through a specific mathematical function prior to the HOS analysis. Feature extraction method using HOS analysis combined with Difference to the Nth-Power manipulation has been examined in application for Automatic Modulation Recognition (AMR) to perform scheme recognition of three digital modulation signal, i.e. QPSK-16QAM-64QAM in the AWGN transmission channel. The simulation results is reported when the analysis of HOS up to order-12 and the manipulation of Difference to the Nth-Power up to N = 4. The obtained accuracy rate of AMR using the method of Simple Decision obtained 90% in SNR > 10 dB in its classifier, while using the method of Voted Decision is 96% in SNR > 2 dB.

Enhancing Student Evaluation Through Student Idol

Since after the historical moment of Malaysia Independence Day on the year of 1957, the government had been trying hard in order to find the most efficient methods in learning. However, it is hard to actually access and evaluate students whom will then be called an excellent student. It because in our realtime student who excellent is only excel in academic. This evaluation become a problem because it not balance in our real life interm of to get an excellent student in whole area in their involvement of curiculum and co-curiculum. To overcome this scenario, we proposed a method called Student Idol to evaluate student through three categories which are academic, co-curiculum and leadership. All the categories have their own merit point. Using this method, student will be evaluated more accurate compared to the previously. So, teacher can easily evaluate their student without having any emotion factor, relation factor and others. As conclustion this method will helps student evaluation more accurate and valid.

Tests for Gaussianity of a Stationary Time Series

One of the primary uses of higher order statistics in signal processing has been for detecting and estimation of non- Gaussian signals in Gaussian noise of unknown covariance. This is motivated by the ability of higher order statistics to suppress additive Gaussian noise. In this paper, several methods to test for non- Gaussianity of a given process are presented. These methods include histogram plot, kurtosis test, and hypothesis testing using cumulants and bispectrum of the available sequence. The hypothesis testing is performed by constructing a statistic to test whether the bispectrum of the given signal is non-zero. A zero bispectrum is not a proof of Gaussianity. Hence, other tests such as the kurtosis test should be employed. Examples are given to demonstrate the performance of the presented methods.

Prospects in Waste Oil Shale Ash Sustainable Valorization

An innovative approach utilizing highly alkaline oil shale waste ash and carbon dioxide gas (CO2), associated with power production, as a resource for production of precipitated calcium carbonate (PCC) is introduced in this paper. The specifics and feasibility of the integrated ash valorization and CO2 sequestration process by indirect aqueous carbonation of lime-consisting ash were elaborated and the main parameters established. Detailed description of the formed precipitates was included. Complimentary carbonation experiments with commercial CaO fine powder were conducted for comparative characterization of the final products obtained on the basis of two different raw materials. Finally, the expected CO2 uptake was evaluated.

Interspecific Variation in Heat Stress Tolerance and Oxidative Damage among 15 C3 Species

The C3 plants are frequently suffering from exposure to high temperature stress which limits the growth and yield of these plants. This study seeks to clarify the physiological mechanisms of heat tolerance in relation to oxidative stress in C3 species. Fifteen C3 species were exposed to prolonged moderately high temperature stress 36/30°C for 40 days in a growth chamber. Chlorophyll fluorescence (Fv/Fm) showed great difference among species at 40 days of the stress. The species showed decreases in Fv/Fm and increases in malondialdehyde (MDA) content under stress condition as well as negative correlation between Fv/Fm and MDA (r = -0.61*) at 40 days of the stress. Hydrogen peroxide (H2O2) content before and after stress in addition to its response under stress showed great differences among species. The results suggest that the difference in heat tolerance among C3 species is closely associated with the ability to suppress oxidative damage but not with the content of reactive oxygen species (ROS) which is regulated by complex network.

E-Learning Platform with SPICE Web Service

When studying electronics, hands-on experience is considered to be very valuable for a better understanding of the concepts of electricity and electronics. Students lacking sufficient time in the lab are often put at disadvantage. A way to overcome this, is by using interactive multimedia in a virtual environment. Instead of proposing another new ad-hoc simulator for e-learning, we propose in this paper an e-learning platform integrating the SPICE simulator as a web service. This enables to make use of all the functions of the de-facto standard simulator SPICE inelectronics when developing new simulations.

Preliminary Study on Fixture Layout Optimization Using Element Strain Energy

The objective of positioning the fixture elements in the fixture is to make the workpiece stiff, so that geometric errors in the manufacturing process can be reduced. Most of the work for optimal fixture layout used the minimization of the sum of the nodal deflection normal to the surface as objective function. All deflections in other direction have been neglected. We propose a new method for fixture layout optimization in this paper, which uses the element strain energy. The deformations in all the directions have been considered in this way. The objective function in this method is to minimize the sum of square of element strain energy. Strain energy and stiffness are inversely proportional to each other. The optimization problem is solved by the sequential quadratic programming method. Three different kinds of case studies are presented, and results are compared with the method using nodal deflections as objective function to verify the propose method.

Research of Potential Cluster Development in Pannonian Croatia

The paper presents an analysis of linkages and structures of co-operation and their intensity like the potential for the establishment of clusters in the Central and Eastern (Pannonian) Croatian. Starting from the theoretical elaboration of the need for entrepreneurs to organize through the cluster model and the terms of their self-actualization, related to the importance of traditional values in terms of benefits, social capital and assess where the company now is, in order to prove the need to create their own identity in terms of clustering. The institutional dimensions of social capital where the public sector has the best role in creating the social structure of clusters, and social dimensions of social capital in terms of trust, cooperation and networking will be analyzed to what extent the trust and coherency are present between companies in the Brod posavina and Pozega slavonia County, expressed through the readiness of inclusion in clusters in the NUTS II region - Central and Eastern (Pannonian) Croatia, as a homogeneous economic entity, with emphasis on limiting factors that stand in the way of greater competitiveness.

Performance Determinants for Convenience Store Suppliers

This paper examines the impact of information and communication technology (ICT) usage, internal relationship, supplier-retailer relationship, logistics services and inventory management on convenience store suppliers- performance. Data was collected from 275 convenience store managers in Malaysia using a set of questionnaire. The multiple linear regression results indicate that inventory management, supplier-retailer relationship, logistics services and internal relationship are predictors of supplier performance as perceived by convenience store managers. However, ICT usage is not a predictor of supplier performance. The study focuses only on convenience stores and petrol station convenience stores and concentrates only on managers. The results provide insights to suppliers who serve convenience stores and possibly similar retail format on factors to consider in improving their service to retailers. The results also provide insights to government in its aspiration to improve business operations of convenience store to consider ways to enhance the adoption of ICT by retailers and suppliers.

Using Data Fusion for Biometric Verification

A wide spectrum of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual person. This paper considers multimodal biometric system and their applicability to access control, authentication and security applications. Strategies for feature extraction and sensor fusion are considered and contrasted. Issues related to performance assessment, deployment and standardization are discussed. Finally future directions of biometric systems development are discussed.

Preliminary Results of In-Vitro Skin Tissue Soldering using Gold Nanoshells and ICG Combination

Laser soldering is based on applying some soldering material (albumin) onto the approximated edges of the cut and heating the solder (and the underlying tissues) by a laser beam. Endogenous and exogenous materials such as indocyanine green (ICG) are often added to solders to enhance light absorption. Gold nanoshells are new materials which have an optical response dictated by the plasmon resonance. The wavelength at which the resonance occurs depends on the core and shell sizes, allowing nanoshells to be tailored for particular applications. The purposes of this study was use combination of ICG and different concentration of gold nanoshells for skin tissue soldering and also to examine the effect of laser soldering parameters on the properties of repaired skin. Two mixtures of albumin solder and different combinations of ICG and gold nanoshells were prepared. A full thickness incision of 2×20 mm2 was made on the surface and after addition of mixtures it was irradiated by an 810nm diode laser at different power densities. The changes of tensile strength σt due to temperature rise, number of scan (Ns), and scan velocity (Vs) were investigated. The results showed at constant laser power density (I), σt of repaired incisions increases by increasing the concentration of gold nanoshells in solder, Ns and decreasing Vs. It is therefore important to consider the tradeoff between the scan velocity and the surface temperature for achieving an optimum operating condition. In our case this corresponds to σt =1800 gr/cm2 at I~ 47 Wcm-2, T ~ 85ºC, Ns =10 and Vs=0.3mms-1.

Clustering Based Formulation for Short Term Load Forecasting

A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.

A Supply Chain Perspective of RFID Systems

Radio Frequency Identification (RFID) initially introduced during WW-II, has revolutionized the world with its numerous benefits and plethora of implementations in diverse areas ranging from manufacturing to agriculture to healthcare to hotel management. This work reviews the current research in this area with emphasis on applications for supply chain management and to develop a taxonomic framework to classify literature which will enable swift and easy content analysis and also help identify areas for future research.

Effect of Ginger and L-Carnitine on the Reproductive Performance of Male Rats

In this study, we investigated the effects of ginger and L-carnitine on the reproductive performance of male rats with respect to semen parameters, male sex hormones and the testicular antioxidant system. A total of sixty mature male albino rats were divided into four groups of fifteen rats. The control group received saline, whereas the other three groups received ginger (100 mg kg-1 d- 1.), L-carnitine (150 mg kg-1 d-1.) or a combination of both ginger (100 mg kg-1 d-1.) and L-carnitine (150 mg kg-1 d-1.) via a stomach tube daily for one month. At the end of the treatment period, the rats were sacrificed, and their sperm characteristics (count, motility and viability), antioxidant enzyme factors levels (reduced glutathione, catalase, superoxide dismutase and total antioxidant capacity) and sex hormone levels (testosterone, Follicle stimulating hormone(FSH) and luteinizing hormone (LH) were analysed. Our results showed that the three experimental treatments improved sperm parameters, antioxidant enzyme activity and testosterone hormone levels; the most pronounced positive effects were observed in the group that received a combination of both ginger and L-carnitine. Therefore, the administration of a combination of ginger and L-carnitine may be beneficial for improving male sexual performance.

ROC Analysis of PVC Detection Algorithm using ECG and Vector-ECG Charateristics

ECG analysis method was developed using ROC analysis of PVC detecting algorithm. ECG signal of MIT-BIH arrhythmia database was analyzed by MATLAB. First of all, the baseline was removed by median filter to preprocess the ECG signal. R peaks were detected for ECG analysis method, and normal VCG was extracted for VCG analysis method. Four PVC detecting algorithm was analyzed by ROC curve, which parameters are maximum amplitude of QRS complex, width of QRS complex, r-r interval and geometric mean of VCG. To set cut-off value of parameters, ROC curve was estimated by true-positive rate (sensitivity) and false-positive rate. sensitivity and false negative rate (specificity) of ROC curve calculated, and ECG was analyzed using cut-off value which was estimated from ROC curve. As a result, PVC detecting algorithm of VCG geometric mean have high availability, and PVC could be detected more accurately with amplitude and width of QRS complex.

Named Entity Recognition using Support Vector Machine: A Language Independent Approach

Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.

Feature Extraction for Surface Classification – An Approach with Wavelets

Surface metrology with image processing is a challenging task having wide applications in industry. Surface roughness can be evaluated using texture classification approach. Important aspect here is appropriate selection of features that characterize the surface. We propose an effective combination of features for multi-scale and multi-directional analysis of engineering surfaces. The features include standard deviation, kurtosis and the Canny edge detector. We apply the method by analyzing the surfaces with Discrete Wavelet Transform (DWT) and Dual-Tree Complex Wavelet Transform (DT-CWT). We used Canberra distance metric for similarity comparison between the surface classes. Our database includes the surface textures manufactured by three machining processes namely Milling, Casting and Shaping. The comparative study shows that DT-CWT outperforms DWT giving correct classification performance of 91.27% with Canberra distance metric.

Construction of Attitude Reference Benchmark for Test of Star Sensor Based on Precise Timing

To satisfy the need of outfield tests of star sensors, a method is put forward to construct the reference attitude benchmark. Firstly, its basic principle is introduced; Then, all the separate conversion matrixes are deduced, which include: the conversion matrix responsible for the transformation from the Earth Centered Inertial frame i to the Earth-centered Earth-fixed frame w according to the time of an atomic clock, the conversion matrix from frame w to the geographic frame t, and the matrix from frame t to the platform frame p, so the attitude matrix of the benchmark platform relative to the frame i can be obtained using all the three matrixes as the multiplicative factors; Next, the attitude matrix of the star sensor relative to frame i is got when the mounting matrix from frame p to the star sensor frame s is calibrated, and the reference attitude angles for star sensor outfield tests can be calculated from the transformation from frame i to frame s; Finally, the computer program is finished to solve the reference attitudes, and the error curves are drawn about the three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│. The analysis on each loop and the final simulating results manifest that the method by precise timing to acquire the absolute reference attitude is feasible for star sensor outfield tests.

Solution of Optimal Reactive Power Flow using Biogeography-Based Optimization

Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.

The Performance of Predictive Classification Using Empirical Bayes

This research is aimed to compare the percentages of correct classification of Empirical Bayes method (EB) to Classical method when data are constructed as near normal, short-tailed and long-tailed symmetric, short-tailed and long-tailed asymmetric. The study is performed using conjugate prior, normal distribution with known mean and unknown variance. The estimated hyper-parameters obtained from EB method are replaced in the posterior predictive probability and used to predict new observations. Data are generated, consisting of training set and test set with the sample sizes 100, 200 and 500 for the binary classification. The results showed that EB method exhibited an improved performance over Classical method in all situations under study.