A Two-Phase Mechanism for Agent's Action Selection in Soccer Simulation

Soccer simulation is an effort to motivate researchers and practitioners to do artificial and robotic intelligence research; and at the same time put into practice and test the results. Many researchers and practitioners throughout the world are continuously working to polish their ideas and improve their implemented systems. At the same time, new groups are forming and they bring bright new thoughts to the field. The research includes designing and executing robotic soccer simulation algorithms. In our research, a soccer simulation player is considered to be an intelligent agent that is capable of receiving information from the environment, analyze it and to choose the best action from a set of possible ones, for its next move. We concentrate on developing a two-phase method for the soccer player agent to choose its best next move. The method is then implemented into our software system called Nexus simulation team of Ferdowsi University. This system is based on TsinghuAeolus[1] team that was the champion of the world RoboCup soccer simulation contest in 2001 and 2002.

Cultural Effect on Using New Technologies

One of the main concerns in the Information Technology field is adoption with new technologies in organizations which may result in increasing the usage paste of these technologies.This study aims to look at the issue of culture-s role in accepting and using new technologies in organizations. The study examines the effect of culture on accepting and intention to use new technology in organizations. Studies show culture is one of the most important barriers in adoption new technologies. The model used for accepting and using new technology is Technology Acceptance Model (TAM), while for culture and dimensions a well-known theory by Hofsted was used. Results of the study show significant effect of culture on intention to use new technologies. All four dimensions of culture were tested to find the strength of relationship with behavioral intention to use new technologies. Findings indicate the important role of culture in the level of intention to use new technologies and different role of each dimension to improve adaptation process. The study suggests that transferring of new technologies efforts are most likely to be successful if the parties are culturally aligned.

The Future Regulatory Challenges of Liquidity Risk Management

Liquidity risk management ranks to key concepts applied in finance. Liquidity is defined as a capacity to obtain funding when needed, while liquidity risk means as a threat to this capacity to generate cash at fair costs. In the paper we present challenges of liquidity risk management resulting from the 2007- 2009 global financial upheaval. We see five main regulatory liquidity risk management issues requiring revision in coming years: liquidity measurement, intra-day and intra-group liquidity management, contingency planning and liquidity buffers, liquidity systems, controls and governance, and finally models testing the viability of business liquidity models.

Web Page Watermarking: XML files using Synonyms and Acronyms

Advent enhancements in the field of computing have increased massive use of web based electronic documents. Current Copyright protection laws are inadequate to prove the ownership for electronic documents and do not provide strong features against copying and manipulating information from the web. This has opened many channels for securing information and significant evolutions have been made in the area of information security. Digital Watermarking has developed into a very dynamic area of research and has addressed challenging issues for digital content. Watermarking can be visible (logos or signatures) and invisible (encoding and decoding). Many visible watermarking techniques have been studied for text documents but there are very few for web based text. XML files are used to trade information on the internet and contain important information. In this paper, two invisible watermarking techniques using Synonyms and Acronyms are proposed for XML files to prove the intellectual ownership and to achieve the security. Analysis is made for different attacks and amount of capacity to be embedded in the XML file is also noticed. A comparative analysis for capacity is also made for both methods. The system has been implemented using C# language and all tests are made practically to get the results.

Text-independent Speaker Identification Based on MAP Channel Compensation and Pitch-dependent Features

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Italians- Social and Emotional Loneliness: The Results of Five Studies

Subjective loneliness describes people who feel a disagreeable or unacceptable lack of meaningful social relationships, both at the quantitative and qualitative level. The studies to be presented tested an Italian 18-items self-report loneliness measure, that included items adapted from scales previously developed, namely a short version of the UCLA (Russell, Peplau and Cutrona, 1980), and the 11-items Loneliness scale by De Jong-Gierveld & Kamphuis (JGLS; 1985). The studies aimed at testing the developed scale and at verifying whether loneliness is better conceptualized as a unidimensional (so-called 'general loneliness') or a bidimensional construct, namely comprising the distinct facets of social and emotional loneliness. The loneliness questionnaire included 2 singleitem criterion measures of sad mood, and social contact, and asked participants to supply information on a number of socio-demographic variables. Factorial analyses of responses obtained in two preliminary studies, with 59 and 143 Italian participants respectively, showed good factor loadings and subscale reliability and confirmed that perceived loneliness has clearly two components, a social and an emotional one, the latter measured by two subscales, a 7-item 'general' loneliness subscale derived from UCLA, and a 6–item 'emotional' scale included in the JGLS. Results further showed that type and amount of loneliness are related, negatively, to frequency of social contacts, and, positively, to sad mood. In a third study data were obtained from a nation-wide sample of 9.097 Italian subjects, 12 to about 70 year-olds, who filled the test on-line, on the Italian web site of a large-audience magazine, Focus. The results again confirmed the reliability of the component subscales, namely social, emotional, and 'general' loneliness, and showed that they were highly correlated with each other, especially the latter two. Loneliness scores were significantly predicted by sex, age, education level, sad mood and social contact, and, less so, by other variables – e.g., geographical area and profession. The scale validity was confirmed by the results of a fourth study, with elderly men and women (N 105) living at home or in residential care units. The three subscales were significantly related, among others, to depression, and to various measures of the extension of, and satisfaction with, social contacts with relatives and friends. Finally, a fifth study with 315 career-starters showed that social and emotional loneliness correlate with life satisfaction, and with measures of emotional intelligence. Altogether the results showed a good validity and reliability in the tested samples of the entire scale, and of its components.

An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique

The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system.

Review of a Real-Time Infectious Waste Management System Using QR Code

In the management of industrial waste, conversion from the use of paper invoices to electronic forms is currently under way in developed countries. Difficulties in such computerization include the lack of synchronization between the actual goods and the corresponding data managed by the server. Consequently, a system which utilizes the incorporation of a QR code in connection with the waste material has been developed. The code is read at each stage, from discharge until disposal, and progress at each stage can be easily reported. This system can be linked with Japanese public digital authentication service of waste, taking advantage of its good points, and can be used to submit reports to the regulatory authorities. Its usefulness was confirmed by a verification test, and put into actual practice.

Into the Bank Lending Channel of SEE: Greek Banks- Buffering Effects

This paper tries to shed light on the existence of a bank lending channel (BLC) in South Eastern European countries (SEE). Based on a VAR framework we test the responsiveness of credit supply to monetary policy shocks. By compiling a new data set and using the reserve requirement ratio, among others, as the policy instrument we measure the effectiveness of the BLC and the buffering effect of the banks in the SEE countries. The results indicate that loan supply is significantly affected by shifts in monetary policy, when demand factors are controlled. Furthermore, by analyzing the effect of the Greek banks in the region we conclude that Greek banks do buffer the negative effects of monetary policy transmission. By having a significant market share of the SEE-s banking markets we argue that Greek banks influence positively the economic growth of SEE countries.

An Efficient Obstacle Detection Algorithm Using Colour and Texture

This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.

Implementation of RC5 Block Cipher Algorithm for Image Cryptosystems

This paper examines the implementation of RC5 block cipher for digital images along with its detailed security analysis. A complete specification for the method of application of the RC5 block cipher to digital images is given. The security analysis of RC5 block cipher for digital images against entropy attack, bruteforce, statistical, and differential attacks is explored from strict cryptographic viewpoint. Experiments and results verify and prove that RC5 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC5 block cipher algorithm.

Investigation of the Effectiveness of Siloxane Hydrophobic Injection for Renovation of Damp Brick Masonry

Experimental investigation of the effect of hydrophobic injection on siloxane basis on the properties of oldfashioned type of ceramic brick is presented in the paper. At the experimental testing, the matrix density, total open porosity, pore size distribution, sorptivity, water absorption coefficient, sorption and desorption isotherms are measured for the original, as well as the hydrophobic-injection treated brick. On the basis of measured data, the functionality of the hydrophobic injection for the moisture ingress prevention into the studied ceramic brick is assessed.

Herpes Simplex Virus Type I Infection of Mice Testis and Effect on Fertility

The objective of current issue was to develop a model of testicular herpes simplex virus (HSV) type I infection for assessment of viral effect on fertility. 56 male mice were inoculated intraperitoneally with different concentrations of HSV on 8 day post partum. It was revealed that the optimal dose was 100 plaque forming units per mice as it provided testicular infection in 100% of survivors. HSV proteins were detected both in somatic and germ cells (spermatogonia, spermatocytes, spermatides). Although DNA load in testis was descending from 3 to 28 days post infection only 12.5% of infected males had offspring after mating with uninfected females comparing to 87.5% in control (p=0.012). These results are the first direct evidence for HSV impact in male sterility. Prepuberal mice appeared to be a suitable model for investigation of pathogenesis of virus-associated fertility disorders.

Investigation into the Bond between CFRP and Steel Plates

The use of externally bonded Carbon Fiber Reinforced Polymer (CFRP) reinforcement has proven to be an effective technique to strengthen steel structures. An experimental study on CFRP bonded steel plate with double strap joint has been conducted and specimens are tested under tensile loadings. An empirical model has been developed using stress-based approach to predict ultimate capacity of the CFRP bonded steel structure. The results from the model are comparable with the experimental result with a reasonable accuracy.

From Experiments to Numerical Modeling: A Tool for Teaching Heat Transfer in Mechanical Engineering

In this work the numerical simulation of transient heat transfer in a cylindrical probe is done. An experiment was conducted introducing a steel cylinder in a heating chamber and registering its surface temperature along the time during one hour. In parallel, a mathematical model was solved for one dimension transient heat transfer in cylindrical coordinates, considering the boundary conditions of the test. The model was solved using finite difference method, because the thermal conductivity in the cylindrical steel bar and the convection heat transfer coefficient used in the model are considered temperature dependant functions, and both conditions prevent the use of the analytical solution. The comparison between theoretical and experimental results showed the average deviation is below 2%. It was concluded that numerical methods are useful in order to solve engineering complex problems. For constant k and h, the experimental methodology used here can be used as a tool for teaching heat transfer in mechanical engineering, using mathematical simplified models with analytical solutions.

Automatic Recognition of Emotionally Coloured Speech

Emotion in speech is an issue that has been attracting the interest of the speech community for many years, both in the context of speech synthesis as well as in automatic speech recognition (ASR). In spite of the remarkable recent progress in Large Vocabulary Recognition (LVR), it is still far behind the ultimate goal of recognising free conversational speech uttered by any speaker in any environment. Current experimental tests prove that using state of the art large vocabulary recognition systems the error rate increases substantially when applied to spontaneous/emotional speech. This paper shows that recognition rate for emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances.

Fuzzy Logic Speed Controller with Reduced Rule Base for Dual PMSM Drives

Dual motor drives fed by single inverter is purposely designed to reduced size and cost with respect to single motor drives fed by single inverter. Previous researches on dual motor drives only focus on the modulation and the averaging techniques. Only a few of them, study the performance of the drives based on different speed controller other than Proportional and Integrator (PI) controller. This paper presents a detailed comparative study on fuzzy rule-base in Fuzzy Logic speed Controller (FLC) for Dual Permanent Magnet Synchronous Motor (PMSM) drives. Two fuzzy speed controllers which are standard and simplified fuzzy speed controllers are designed and the results are compared and evaluated. The standard fuzzy controller consists of 49 rules while the proposed controller consists of 9 rules determined by selecting the most dominant rules only. Both designs are compared for wide range of speed and the robustness of both controllers over load disturbance changes is tested to demonstrate the effectiveness of the simplified/reduced rulebase.

Detecting Remote Protein Evolutionary Relationships via String Scoring Method

The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.

An Approach for Reducing the Computational Complexity of LAMSTAR Intrusion Detection System using Principal Component Analysis

The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.

Variable Step-Size Affine Projection Algorithm With a Weighted and Regularized Projection Matrix

This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.