Computing the Loop Bound in Iterative Data Flow Graphs Using Natural Token Flow

Signal processing applications which are iterative in nature are best represented by data flow graphs (DFG). In these applications, the maximum sampling frequency is dependent on the topology of the DFG, the cyclic dependencies in particular. The determination of the iteration bound, which is the reciprocal of the maximum sampling frequency, is critical in the process of hardware implementation of signal processing applications. In this paper, a novel technique to compute the iteration bound is proposed. This technique is different from all previously proposed techniques, in the sense that it is based on the natural flow of tokens into the DFG rather than the topology of the graph. The proposed algorithm has lower run-time complexity than all known algorithms. The performance of the proposed algorithm is illustrated through analytical analysis of the time complexity, as well as through simulation of some benchmark problems.

A Novel Reversible Watermarking Method based on Adaptive Thresholding and Companding Technique

Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.

On the Factors Influencing the Competitiveness of Chinese Service Trade after Entering WTO

Service trade is an important force of influencing economic development. A review on the related literatures is done firstly. Then through the construction of a Diamond Model, the main factors which influence the competitiveness of Chinese service trade are determined. With three competitiveness indexes served as the reference series respectively, the influencing factors served as the comparable series, three grey incidence models are then built up to conduct an empirical analysis on the main factors influencing the competitiveness of service trade after China entering WTO. The result indicates that urbanization level, open degree of service industry and foreign direct investment have larger impacts on Chinese service trade competitiveness, followed in turn by GDP in service industry and human capital, while commodity trade has the minimum impact. Further discussion provides train of thought for the upgrade of Chinese service trade competitiveness.

Social Networks and Absorptive Capacity

The resource-based view of the firm regards knowledge as one of the most important organizational assets and a key strategic resource that contributes unique value to organizations. The acquisition, absorption and internalization of external knowledge are central to an organization-s innovative capabilities. This ability to evaluate, acquire and integrate new knowledge from its environment is referred to as a firm-s absorptive capacity (AC). This research in progress paper explores the link between interorganizational Social Networks (SNs) and a firm-s Absorptive Capacity (AC). Based on an in-depth literature survey of both concepts, four propositions are proposed that explain the link between AC and SNs. These propositions suggest that SNs are key to a firm-s AC. A qualitative research method is proposed to test the set of propositions in the next stage of this research.

Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP) for Recovering Signal

Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Determining the Workability of the New Metallurgical Materials

The aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.

Order Reduction by Least-Squares Methods about General Point ''a''

The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.

Biospeckle Supported Fruit Bruise Detection

This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.

The Relationship of Knowledge Management Practices, Competencies and the Organizational Performance of Government Departments in Malaysia

This paper attempts to highlight the significant role of knowledge management practices (KMP) and competencies in improving the performance and efficiency of public sector organizations. It appears that public sector organizations in developing countries have not received much attention in the research literature of knowledge management and competencies. Therefore, this paper seeks to explore the role of KMP and competencies in achieving superior performance among public sector organizations in Malaysia in the broader perspective. Survey questionnaires were distributed to all Administrative and Diplomatic Officers (ADS) from 28 ministries located in Putrajaya, Malaysia. This paper also examines preliminary empirical results on the relationship between support for knowledge management practices, competencies, and orientation in Malaysia-s public organizations. This paper supports the notion that the practices of knowledge management at the organizational level are a prerequisite for successful organizational performance. In conclusion, the results not only have the potential to contribute theoretically to both management strategy and knowledge management field literature but also to the area of organizational performance.

Particle Swarm Optimization Approach on Flexible Structure at Wiper Blade System

Application of flexible structures has been significantly, increased in industry and aerospace missions due to their contributions and unique advantages over the rigid counterparts. In this paper, vibration analysis of a flexible structure i.e., automobile wiper blade is investigated and controlled. The wiper generates unwanted noise and vibration during the wiping the rain and other particles on windshield which may cause annoying noise in different ranges of frequency. A two dimensional analytical modeled wiper blade whose model accuracy is verified by numerical studies in literature is considered in this study. Particle swarm optimization (PSO) is employed in alliance with input shaping (IS) technique in order to control or to attenuate the amplitude level of unwanted noise/vibration of the wiper blade.

Evaluation of Edge Configuration in Medical Echo Images Using Genetic Algorithms

Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Accounting for SMEs – How Important is Size in Choosing between Global and Local Standards?

There is limited evidence from various countries about the possible impact of various criteria to be used to determine the scope of the IFRS for SMEs issued in 2009 and, research is needed in this area. We provide evidence from Romania, an emerging economy member of the European Union. The aim of this paper is to analyze in a local setting if size is a relevant factor for deciding between local and global standards for SMEs. Our results indicate that size is a moderate indicator of the existence of possible users interested in financial statements and that there is a difference between the scopes of the standard determined on various criteria.. Also, we suggest that the international exposure is quite reduced in the case of SMEs, but is sufficient to suggest that at least some SMEs would benefit from international comparability of financial statements

Social, Group and Individual Mind extracted from Rule Bases of Multiple Agents

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Policy Management Framework for Managing Enterprise Policies

Policy management in organizations became rising issue in the last decade. It’s because of today’s regulatory requirements in the organizations. To manage policies in large organizations is an imperative work. However, major challenges facing organizations in the last decade is managing all the policies in the organization and making them an active documents rather than simple (inactive) documents stored in computer hard drive or on a shelf. Because of this challenge, organizations need policy management program. This policy management program can be either manual or automated. This paper presents suggestions towards managing policies in organizations. As well as possible policy management solution or program to be utilized, manual or automated. The research first examines the models and frameworks used for managing policies from various perspectives in the literature of the research area/domain. At the end of this paper, a policy management framework is proposed for managing enterprise policies effectively and in a simplified manner.

Impact of the Amendments of Malaysian Code of Corporate Governance (2007) on Governance of GLCs and Performance

The study aims to investigate the impact on board and audit committee characteristics and firm performance before and after the revision of MCCG (2007) on GLCs over the period 2005-2010. We used Return on Assets (ROA) as a proxy for firm performance. The data consists of two groups; data collected before and after the amendments of MCCG (2007). Findings show that boards of directors with accounting / finance qualifications (BEXP) are statistically significant with performance for period before the amendments. As for audit committee members with accounting or finance qualifications (ACEXP), correlation results indicate a negative association and non-significant results for the years before amendments. However, the years after the amendments show positive relationship with highly significant correlations (1%) to ROA. This indicates that the amendments of MCCG 2007 on the audit committee members- literacy in accounting have impacted the governance structures and performance of GLCs.

A New Empirical Expression of the Breakdown Voltage for Combined Variations of Temperature and Pressure

In aircraft applications, according to the nature of electrical equipment its location may be in unpressurized area or very close to the engine; thus, the environmental conditions may change from atmospheric pressure to less than 100 mbar, and the temperature may be higher than the ambient one as in most real working conditions of electrical equipment. Then, the classical Paschen curve has to be replotted since these parameters may affect the discharge ignition voltage. In this paper, we firstly investigate the domain of validity of two corrective expressions on the Paschen-s law found in the literature, in case of changing the air environment and known as Peek and Dunbar corrections. Results show that these corrections are no longer valid for combined variation of temperature and pressure. After that, a new empirical expression for breakdown voltage is proposed and is validated in the case of combined variations of temperature and pressure.

Technology Readiness Index (TRI) among USM Distance Education Students According to Age

This paper reports the findings of a research conducted to evaluate the ownership and usage of technology devices within Distance Education students- according to their age. This research involved 45 Distance Education students from USM Universiti Sains Malaysia (DEUSM) as its respondents. Data was collected through questionnaire that had been developed by the researchers based on some literature review. The data was analyzed to find out the frequencies of respondents agreements towards ownership of technology devices and the use of technology devices. The findings shows that all respondents own mobile phone and majority of them reveal that they use mobile on regular basis. The student in the age 30-39 has the heist ownership of the technology devices.

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.

Model of High-Speed Train Energy Consumption

In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Texture Characterization Based on a Chandrasekhar Fast Adaptive Filter

In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.