Study Forecast Indoor Acoustics. A Case Study: the Auditorium Theatre-Hotel “Casa Tra Noi“

The theatre-auditorium under investigation following the highly reflective characteristics of materials used in it (marble, painted wood, smooth plaster, etc), architectural and structural features of the Protocol and its intended use (very multifunctional: Auditorium, theatre, cinema, musicals, conference room) from the analysis of the statement of fact made by the acoustic simulation software Ramsete and supported by data obtained through a campaign of acoustic measurements of the state of fact made on the spot by a Fonomet Svantek model SVAN 957, appears to be acoustically inadequate. After the completion of the 3D model according to the specifications necessary software used forecast in order to be recognized by him, have made three simulations, acoustic simulation of the state of and acoustic simulation of two design solutions. Improved noise characteristics found in the first design solution, compared to the state in fact consists therefore in lowering Reverberation Time that you turn most desirable value, while the Indicators of Clarity, the Baricentric Time, the Lateral Efficiency, Ratio of Low Tmedia BR and defined the Speech Intelligibility improved significantly. Improved noise characteristics found instead in the second design solution, as compared to first design solution, is finally mostly in a more uniform distribution of Leq and in lowering Reverberation Time that you turn the optimum values. Indicators of Clarity, and the Lateral Efficiency improve further but at the expense of a value slightly worse than the BR. Slightly vary the remaining indices.

Soft Computing based Retrieval System for Medical Applications

With increasing data in medical databases, medical data retrieval is growing in popularity. Some of this analysis including inducing propositional rules from databases using many soft techniques, and then using these rules in an expert system. Diagnostic rules and information on features are extracted from clinical databases on diseases of congenital anomaly. This paper explain the latest soft computing techniques and some of the adaptive techniques encompasses an extensive group of methods that have been applied in the medical domain and that are used for the discovery of data dependencies, importance of features, patterns in sample data, and feature space dimensionality reduction. These approaches pave the way for new and interesting avenues of research in medical imaging and represent an important challenge for researchers.

A New Method of Combined Classifier Design Based on Fuzzy Neural Network

To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).

A Multiagent System for Distributed Systems Management

The demand for autonomous resource management for distributed systems has increased in recent years. Distributed systems require an efficient and powerful communication mechanism between applications running on different hosts and networks. The use of mobile agent technology to distribute and delegate management tasks promises to overcome the scalability and flexibility limitations of the currently used centralized management approach. This work proposes a multiagent system that adopts mobile agents as a technology for tasks distribution, results collection, and management of resources in large-scale distributed systems. A new mobile agent-based approach for collecting results from distributed system elements is presented. The technique of artificial intelligence based on intelligent agents giving the system a proactive behavior. The presented results are based on a design example of an application operating in a mobile environment.

Assamese Numeral Speech Recognition using Multiple Features and Cooperative LVQ -Architectures

A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a microphone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.

The Relevance of Data Warehousing and Data Mining in the Field of Evidence-based Medicine to Support Healthcare Decision Making

Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Study of Compost Maturity during Humification Process using UV-Spectroscopy

The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.

Efficient Real-time Remote Data Propagation Mechanism for a Component-Based Approach to Distributed Manufacturing

Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Piecewise Interpolation Filter for Effective Processing of Large Signal Sets

Suppose KY and KX are large sets of observed and reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori information only on few signals, p  N, from KX but performs better than the known filters based on a priori information on every reference signal from KX? It is shown that the positive answer is achievable under quite unrestrictive assumptions. The device behind the proposed method is based on a special extension of the piecewise linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.

Multilevel Activation Functions For True Color Image Segmentation Using a Self Supervised Parallel Self Organizing Neural Network (PSONN) Architecture: A Comparative Study

The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.

Constraint Active Contour Model with Application to Automated Three-Dimensional Airway Wall Segmentation

For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.

The Service Failure and Recovery in the Information Technology Services

It is important to retain customer satisfaction in information technology services. When a service failure occurs, companies need to take service recovery action to recover their customer satisfaction. Although companies cannot avoid all problems and complaints, they should try to make up. Therefore, service failure and service recovery have become an important and challenging issue for companies. In this paper, the literature and the problems in the information technology services were reviewed. An integrated model of profit driven for the service failure and service recovery was established in view of the benefit of customer and enterprise. Moreover, the interaction between service failure and service recovery strategy was studied, the result of which verified the matching principles of the service recovery strategy and the type of service failure. In addition, the relationship between the cost of service recovery and customer-s cumulative value of service after recovery was analyzed with the model. The result attributes to managers in deciding on appropriate resource allocations for recovery strategies.

Topographic Arrangement of 3D Design Components on 2D Maps by Unsupervised Feature Extraction

As a result of the daily workflow in the design development departments of companies, databases containing huge numbers of 3D geometric models are generated. According to the given problem engineers create CAD drawings based on their design ideas and evaluate the performance of the resulting design, e.g. by computational simulations. Usually, new geometries are built either by utilizing and modifying sets of existing components or by adding single newly designed parts to a more complex design. The present paper addresses the two facets of acquiring components from large design databases automatically and providing a reasonable overview of the parts to the engineer. A unified framework based on the topographic non-negative matrix factorization (TNMF) is proposed which solves both aspects simultaneously. First, on a given database meaningful components are extracted into a parts-based representation in an unsupervised manner. Second, the extracted components are organized and visualized on square-lattice 2D maps. It is shown on the example of turbine-like geometries that these maps efficiently provide a wellstructured overview on the database content and, at the same time, define a measure for spatial similarity allowing an easy access and reuse of components in the process of design development.

Efficiency of Different GLR Test-statistics for Spatial Signal Detection

In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.

Drag models for Simulation Gas-Solid Flow in the Bubbling Fluidized Bed of FCC Particles

In the current work, a numerical parametric study was performed in order to model the fluid mechanics in the riser of a bubbling fluidized bed (BFB). The gas-solid flow was simulated by mean of a multi-fluid Eulerian model incorporating the kinetic theory for solid particles. The bubbling fluidized bed was simulated two dimensionally by mean of a Computational Fluid Dynamic (CFD) commercial software package, Fluent. The effects of using different inter-phase drag function (the drag model of Gidaspow, Syamlal and O-Brien and the EMMS drag model) on the model predictions were evaluated and compared. The results showed that the drag models of Gidaspow and Syamlal and O-Brien overestimated the drag force for the FCC particles and predicted a greater bed expansion in comparison to the EMMS drag model.

Multi-Enterprise Tie and Co-Operation Mechanism in Mexican Agro Industry SME's

The aim of this paper is to explain what a multienterprise tie is, what evidence its analysis provides and how does the cooperation mechanism influence the establishment of a multienterprise tie. The study focuses on businesses of smaller dimension, geographically dispersed and whose businessmen are learning to cooperate in an international environment. The empirical evidence obtained at this moment permits to conclude the following: The tie is not long-lasting, it has an end; opportunism is an opportunity to learn; the multi-enterprise tie is a space to learn about the cooperation mechanism; the local tie permits a businessman to alternate between competition and cooperation strategies; the disappearance of a tie is an experience of learning for a businessman, diminishing the possibility of failure in the next tie; the cooperation mechanism tends to eliminate hierarchical relations; the multienterprise tie diminishes the asymmetries and permits SME-s to have a better position when they negotiate with large companies; the multi-enterprise tie impacts positively on the local system. The collection of empirical evidence was done trough the following instruments: direct observation in a business encounter to which the businesses attended in 2003 (202 Mexican agro industry SME-s), a survey applied in 2004 (129), a questionnaire applied in 2005 (86 businesses), field visits to the businesses during the period 2006-2008 and; a survey applied by telephone in 2008 (55 Mexican agro industry SME-s).

Molecular Docking Studies of Mycobacterium tuberculosis RNA Polymerase β Subunit (rpoB) Receptor

Tuberculosis (TB) is a bacterial infectious disease caused by the obligate human pathogen, Mycobacterium tuberculosis. Multidrug-resistant tuberculosis (MDR-TB) is a global reality that threatens tuberculosis control. Resistance to antibiotic Rifampicin, occurs in 95% of cases through nucleotide substitutions in an 81-bp core region of the rpoB i.e; beta subunit of DNA dependant RNA polymerase. In this paper, we studied the Rifampicin-rpoB receptor interactions In silico. First, homology modeling was performed to obtain the three dimensional structure of Mycobacterium rpoB. Sixty analogs of Rifampicin were prepared using Marvin sketch software. Both original Rifampicin and the analogs were docked with rpoB and energy values were obtained. Out of sixty analogs, 43 analogs had lesser energy values than conventional Rifampicin and hence are predicted to have greater binding affinity to rpoB. Thus, this study offers a route for the development of Rifampicin analogs against multi drug resistant Mycobacterium rpoB.

Automotive 3-Microphone Noise Canceller in a Frequently Moving Noise Source Environment

A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.

Determinants of Enterprise Risk Management Adoption: An Empirical Analysis of Malaysian Public Listed Firms

Purpose:This paper aims to gain insights to the influential factors of ERM adoptions by public listed firms in Malaysia. Findings:The two factors of financial leverage and auditor type were found to be significant influential factors for ERM adoption. In other words the findings indicated that firms with higher financial leverage and with a Big Four auditor are more likely to have a form of ERM framework in place. Originality/Value:Since there are relatively few studies conducted in this area and specially in developing economies like Malaysia, this study will broaden the scope of literature by providing novel empirical evidence.

Searching for Similar Informational Articles in the Internet Channel

In terms of total online audience, newspapers are the most successful form of online content to date. The online audience for newspapers continues to demand higher-quality services, including personalized news services. News providers should be able to offer suitable users appropriate content. In this paper, a news article recommender system is suggested based on a user-s preference when he or she visits an Internet news site and reads the published articles. This system helps raise the user-s satisfaction, increase customer loyalty toward the content provider.