High Dynamic Range Resampling for Software Radio

The classic problem of recovering arbitrary values of a band-limited signal from its samples has an added complication in software radio applications; namely, the resampling calculations inevitably fold aliases of the analog signal back into the original bandwidth. The phenomenon is quantified by the spur-free dynamic range. We demonstrate how a novel application of the Remez (Parks- McClellan) algorithm permits optimal signal recovery and SFDR, far surpassing state-of-the-art resamplers.

A Method to Annotate Programs with High-Level Knowledge of Computation

When programming in languages such as C, Java, etc., it is difficult to reconstruct the programmer's ideas only from the program code. This occurs mainly because, much of the programmer's ideas behind the implementation are not recorded in the code during implementation. For example, physical aspects of computation such as spatial structures, activities, and meaning of variables are not required as instructions to the computer and are often excluded. This makes the future reconstruction of the original ideas difficult. AIDA, which is a multimedia programming language based on the cyberFilm model, can solve these problems allowing to describe ideas behind programs using advanced annotation methods as a natural extension to programming. In this paper, a development environment that implements the AIDA language is presented with a focus on the annotation methods. In particular, an actual scientific numerical computation code is created and the effects of the annotation methods are analyzed.

The Fatigue Damage Accumulation on Systems of Concentrators

Fatigue tests of specimen-s with numerous holes are presented. The tests were made up till fatigue cracks have been created on both sides of the hole. Their extension was stopping with pressed plastic deformation at the mouth of the detected crack. It is shown that the moments of occurrence of cracks on holes are stochastically dependent. This dependence has positive and negative correlation relations. Shown that the positive correlation is formed across of the applied force, while negative one – along it. The negative relationship extends over a greater distance. The mathematical model of dependence area formation is represented as well as the estimating of model parameters. The positive correlation of fatigue cracks origination can be considered as an extension of one main crack. With negative correlation the first crack locates the place of its origin, leading to the appearance of multiple cracks; do not merge with each other.

Study on the Effect of Sulphur, Glucose, Nitrogen and Plant Residues on the Immobilization of Sulphate-S in Soil

In order to evaluate the relationship between the sulphur (S), glucose (G), nitrogen (N) and plant residues (st), sulphur immobilization and microbial transformation were monitored in five soil samples from 0-30 cm of Bastam farmers fields of Shahrood area following 11 treatments with different levels of Sulphur (S), glucose (G), N and plant residues (wheat straw) in a randomized block design with three replications and incubated over 20, 45 and 60 days, the immobilization of SO4 -2-S presented as a percentage of that added, was inversely related to its addition rate. Additions of glucose and plant residues increased with the C-to-S ratio of the added amendments, irrespective of their origins (glucose and plant residues). In the presence of C sources (glucose or plant residues). N significantly increased the immobilization of SO4 -2-S, whilst the effect of N was insignificant in the absence of a C amendment. In first few days the amounts of added SO4 -2-S immobilized were linearly correlated with the amounts of added S recovered in the soil microbial biomass. With further incubation the proportions of immobilized SO4 -2-S remaining as biomass-S decreased. Decrease in biomass-S was thought to be due to the conversion of biomass-S into soil organic-S. Glucose addition increased the immobilization (microbial utilization and incorporation into the soil organic matter) of native soil SO4 -2-S. However, N addition enhance the mineralization of soil organic-S, increasing the concentration of SO4 - 2-S in soil.

Classifier Based Text Mining for Neural Network

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

A Fast Cyclic Reduction Algorithm for A Quadratic Matrix Equation Arising from Overdamped Systems

We are concerned with a class of quadratic matrix equations arising from the overdamped mass-spring system. By exploring the structure of coefficient matrices, we propose a fast cyclic reduction algorithm to calculate the extreme solutions of the equation. Numerical experiments show that the proposed algorithm outperforms the original cyclic reduction and the structure-preserving doubling algorithm.

Application of the Improved QFD Method Case Study: Kitchen Utensils Rack Design

This paper presents an application of the improved QFD method for determining the specifications of kitchen utensils rack. By using the improved method, the subjective nature in original QFD was reduced; particularly in defining the relationship between customer requirement and engineering characteristics. The regression analysis that was used for obtaining the relationship functions between customer requirement and engineering characteristics also accommodated the inaccurateness of the competitive assessment results. The improved method which is represented in the form of a mathematical model had become a formal guidance to allocate the resource for improving the specifications of kitchen utensils rack. The specifications obtained had led to the achievement of the highest feasible customer satisfaction.

Performance of Compound Enhancement Algorithms on Dental Radiograph Images

The purpose of this research is to compare the original intra-oral digital dental radiograph images with images that are enhanced using a combination of image processing algorithms. Intraoral digital dental radiograph images are often noisy, blur edges and low in contrast. A combination of sharpening and enhancement method are used to overcome these problems. Three types of proposed compound algorithms used are Sharp Adaptive Histogram Equalization (SAHE), Sharp Median Adaptive Histogram Equalization (SMAHE) and Sharp Contrast adaptive histogram equalization (SCLAHE). This paper presents an initial study of the perception of six dentists on the details of abnormal pathologies and improvement of image quality in ten intra-oral radiographs. The research focus on the detection of only three types of pathology which is periapical radiolucency, widen periodontal ligament space and loss of lamina dura. The overall result shows that SCLAHE-s slightly improve the appearance of dental abnormalities- over the original image and also outperform the other two proposed compound algorithms.

A Novel and Green Approach to Produce Nano- Porous Materials Zeolite A and MCM-41 from Coal Fly Ash and their Applications in Environmental Protection

Zeolite A and MCM-41 have extensive applications in basic science, petrochemical science, energy conservation/storage, medicine, chemical sensor, air purification, environmentally benign composite structure and waste remediation. However, the use of zeolite A and MCM-41 in these areas, especially environmental remediation, are restricted due to prohibitive production cost. Efficient recycling of and resource recovery from coal fly ash has been a major topic of current international research interest, aimed at achieving sustainable development of human society from the viewpoints of energy, economy, and environmental strategy. This project reported an original, novel, green and fast methods to produce nano-porous zeolite A and MCM-41 materials from coal fly ash. For zeolite A, this novel production method allows a reduction by half of the total production time while maintaining a high degree of crystallinity of zeolite A which exists in a narrower particle size distribution. For MCM-41, this remarkably green approach, being an environmentally friendly process and reducing generation of toxic waste, can produce pure and long-range ordered MCM-41 materials from coal fly ash. This approach took 24 h at 25 oC to produce 9 g of MCM-41 materials from 30 g of the coal fly ash, which is the shortest time and lowest reaction temperature required to produce pure and ordered MCM-41 materials (having the largest internal surface area) compared to the values reported in the literature. Performance evaluation of the produced zeolite A and MCM-41 materials in wastewater treatment and air pollution control were reported. The residual fly ash was also converted to zeolite Na-P1 which showed good performance in removal of multi-metal ions in wastewater. In wastewater treatment, compared to commercial-grade zeolite A, adsorbents produced from coal fly ash were effective in removing multi heavy metal ions in water and could be an alternative material for treatment of wastewater. In methane emission abatement, the zeolite A (produced from coal fly ash) achieved similar methane removal efficiency compared to the zeolite A prepared from pure chemicals. This report provides the guidance for production of zeolite A and MCM-41 from coal fly ash by a cost-effective approach which opens potential applications of these materials in environmental industry. Finally, environmental and economic aspects of production of zeolite A and MCM-41 from coal fly ash were discussed.

Towards Better Understanding of the Concept of Tacit Knowledge – A Cognitive Approach

Tacit knowledge has been one of the most discussed and contradictory concepts in the field of knowledge management since the mid 1990s. The concept is used relatively vaguely to refer to any type of information that is difficult to articulate, which has led to discussions about the original meaning of the concept (adopted from Polanyi-s philosophy) and the nature of tacit knowing. It is proposed that the subject should be approached from the perspective of cognitive science in order to connect tacit knowledge to empirically studied cognitive phenomena. Some of the most important examples of tacit knowing presented by Polanyi are analyzed in order to trace the cognitive mechanisms of tacit knowing and to promote better understanding of the nature of tacit knowledge. The cognitive approach to Polanyi-s theory reveals that the tacit/explicit typology of knowledge often presented in the knowledge management literature is not only artificial but totally opposite approach compared to Polanyi-s thinking.

Effect Comparison of Speckle Noise Reduction Filters on 2D-Echocardigraphic Images

Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.

Fuzzy Logic Based Improved Range Free Localization for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

An Improved Illumination Normalization based on Anisotropic Smoothing for Face Recognition

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates the intensity contrast of the original image, and incurs less sharp edges. The proposed method in this paper improves the previous anisotropic smoothing-based illumination normalization method so that it increases the intensity contrast and enhances the edges while diminishing the effect of illumination variations. Due to the result of these improvements, face images preprocessed by the proposed illumination normalization method becomes to have more distinctive feature vectors (Gabor feature vectors) for face recognition. Through experiments of face recognition based on Gabor feature vector similarity, the effectiveness of the proposed illumination normalization method is verified.

Robust Digital Cinema Watermarking

With the advent of digital cinema and digital broadcasting, copyright protection of video data has been one of the most important issues. We present a novel method of watermarking for video image data based on the hardware and digital wavelet transform techniques and name it as “traceable watermarking" because the watermarked data is constructed before the transmission process and traced after it has been received by an authorized user. In our method, we embed the watermark to the lowest part of each image frame in decoded video by using a hardware LSI. Digital Cinema is an important application for traceable watermarking since digital cinema system makes use of watermarking technology during content encoding, encryption, transmission, decoding and all the intermediate process to be done in digital cinema systems. The watermark is embedded into the randomly selected movie frames using hash functions. Embedded watermark information can be extracted from the decoded video data. For that, there is no need to access original movie data. Our experimental results show that proposed traceable watermarking method for digital cinema system is much better than the convenient watermarking techniques in terms of robustness, image quality, speed, simplicity and robust structure.

Network Intrusion Detection Design Using Feature Selection of Soft Computing Paradigms

The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users- activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information from the original high dimensional database. Next, we design an intrusion detection method to solve the problems of uncertainty caused by limited and ambiguous information. In the experiments, we choose six UCI databases and DARPA KDD99 intrusion detection data set as our evaluation tools. Empirical studies indicate that our feature selection algorithm is capable of reducing the size of data set. Our intrusion detection method achieves a better performance than those of participating intrusion detectors.

Entrepreneurial Activity - Indicator of Regional Development in Croatia

Given that entrepreneurship is a very significant factor of regional development, it is necessary to approach systematically the development with measures of regional politics. According to international classification The Nomenclature of Territorial Units for Statistics (NUTS II), there are three regions in Croatia. The indicators of entrepreneurial activities on the national level of Croatia are analyzed in the paper, taking into consideration the results of referent research. The level of regional development is shown based on the analysis of entrepreneurs- operations. The results of the analysis show a very unfavorable situation in entrepreneurial activities on the national level of Croatia. The origin of this situation is to be found in the surroundings with an expressed inequality of regional development, which is caused by the non-existence of a strategically directed regional policy. In this paper recommendations which could contribute to the reduction of regional inequality in Croatia, have been made.

A New Proxy Signature Scheme As Secure As ElGamal Signature

Proxy signature helps the proxy signer to sign messages on behalf of the original signer. It is very useful when the original signer (e.g. the president of a company) is not available to sign a specific document. If the original signer can not forge valid proxy signatures through impersonating the proxy signer, it will be robust in a virtual environment; thus the original signer can not shift any illegal action initiated by herself to the proxy signer. In this paper, we propose a new proxy signature scheme. The new scheme can prevent the original signer from impersonating the proxy signer to sign messages. The proposed scheme is based on the regular ElGamal signature. In addition, the fair privacy of the proxy signer is maintained. That means, the privacy of the proxy signer is preserved; and the privacy can be revealed when it is necessary.

Meta Random Forests

Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.

Role of Director's Philosophical Approach in Cinematographic Expression

The original idea for a feature film may come from a writer, director or a producer. Director is the person responsible for the creative aspects, both interpretive and technical, of a motion picture production in a film. Director may be shot discussing his project with his or her cowriters, members of production staff, and producer, and director may be shown selecting locales or constructing sets. All these activities provide, of course, ways of externalizing director-s ideas about the film. A director sometimes pushes both the film image and techniques of narration to new artistic limits, but main responsibility of director is take the spectator to an original opinion in his philosophical approach. Director tries to find an artistic angle in every scene and change screenplay into an effective story and sets his film on a spiritual and philosophical base.