Is the Expansion of High-Tech Leaders Possible Within the New EU Members? A Case Study of Ammono S.A. and the High-Tech Financing System in Poland

Innovations, especially technological, are considered key-drivers for sustainable economic growth and competitiveness in the globalised world. As such they should also play an important role in the process of economical convergence inside the EU. Unfortunately, the problem of insufficient innovation performance concerns around half of the EU countries. Poland shows that a lack of a consistent high-tech financing system constitutes a serious obstacle for the development of innovative firms. In this article we will evaluate these questions referring to the example of Ammono S.A., a Polish company established to develop and commercialise an original technology for the production of bulk GaN crystals. We will focus on its efforts to accumulate the financial resources necessary at different stages of its development. The purpose of this article is to suggest possible ways to improve the national innovative system, which would make it more competent in generating high-tech leaders.

New Subband Adaptive IIR Filter Based On Polyphase Decomposition

We present a subband adaptive infinite-impulse response (IIR) filtering method, which is based on a polyphase decomposition of IIR filter. Motivated by the fact that the polyphase structure has benefits in terms of convergence rate and stability, we introduce the polyphase decomposition to subband IIR filtering, i.e., in each subband high order IIR filter is decomposed into polyphase IIR filters with lower order. Computer simulations demonstrate that the proposed method has improved convergence rate over conventional IIR filters.

Antimicrobial Effect of Essential oil of Plant Trigonella focnum greacum on some Bacteria Pathogens

The plant world is the source of many medicines. Recently, researchers have estimated that there are approximately 400,000 plant species worldwide, of which about a quarter or a third have been used by societies for medicinal purposes. The human uses of plants for thousands of years to treat various ailments, in many developing countries, much of the population trust in traditional doctors and their collections of medicinal plants to treat them. Essential oils have many therapeutic properties. In herbal medicine, they are used for their antiseptic properties against infectious diseases of fungal origin, against dermatophytes, those of bacterial origin. The aim of our study is to determine the antimicrobial effect of essential oils of the plant Trigonella focnum greacum on some pathogenic bacteria, it is a medicinal plant used in traditional therapy. The test adopted is based on the diffusion method on solid medium (Antibiogram), this method determines the sensitivity or resistance of a microorganism vis-à-vis the extract studied. Our study reveals that the essential oil of the plant Trigonella focnum greacum has a different effect on the resistance of germs. For staphiloccocus Pseudomonnas aeroginosa and Krebsilla, are moderately sensitive strains, also Escherichia coli and Candida albicans represents a high sensitivity. By against Proteus is a strain that represents a weak sensitivity.

Performance Analysis of MC-SS for the Indoor BPLC Systems

power-line networks are promise infrastructure for broadband services provision to end users. However, the network performance is affected by stochastic channel changing which is due to load impedances, number of branches and branched line lengths. It has been proposed that multi-carrier modulations techniques such as orthogonal frequency division multiplexing (OFDM), Multi-Carrier Spread Spectrum (MC-SS), wavelet OFDM can be used in such environment. This paper investigates the performance of different indoor topologies of power-line networks that uses MC-SS modulation scheme.It is observed that when a branch is added in the link between sending and receiving end of an indoor channel an average of 2.5dB power loss is found. In additional, when the branch is added at a node an average of 1dB power loss is found. Additionally when the terminal impedances of the branch change from line characteristic impedance to impedance either higher or lower values the channel performances were tremendously improved. For example changing terminal load from characteristic impedance (85 .) to 5 . the signal to noise ratio (SNR) required to attain the same performances were decreased from 37dB to 24dB respectively. Also, changing the terminal load from channel characteristic impedance (85 .) to very higher impedance (1600 .) the SNR required to maintain the same performances were decreased from 37dB to 23dB. The result concludes that MC-SS performs better compared with OFDM techniques in all aspects and especially when the channel is terminated in either higher or lower impedances.

MIBiClus: Mutual Information based Biclustering Algorithm

Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.

Closed Form Solution to problem of Calcium Diffusion in Cylindrical Shaped Neuron Cell

Calcium [Ca2+] dynamics is studied as a potential form of neuron excitability that can control many irregular processes like metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and increases the synaptic strength and thus triggers the neurotransmitter release. The modeling and analysis of calcium dynamics in neuron cell becomes necessary for deeper understanding of the processes involved. A mathematical model has been developed for cylindrical shaped neuron cell by incorporating physiological parameters like buffer, diffusion coefficient, and association rate. Appropriate initial and boundary conditions have been framed. The closed form solution has been developed in terms of modified Bessel function. A computer program has been developed in MATLAB 7.11 for the whole approach.

Effect of Bentonite on the Properties of Liquid Insulating Oil

Bentonitic material from South Aswan, Egypt was evaluated in terms of mineral-ogy and chemical composition as bleaching clay in refining of transformer oil before and after acid activation and thermal treatment followed by acid leaching using HCl and H2SO4 for different contact times. Structural modification and refining power of bento-nite were investigated during modification by means of X-ray diffraction and infrared spectroscopy. The results revealed that the activated bentonite could be used for refining of transformer oil. The oil parameters such as; dielectric strength, viscosity and flash point had been improved. The dielectric breakdown strength of used oil increased from 29 kV for used oil treated with unactivated bentonite to 74 kV after treatment with activated bentonite. Kinematic Viscosity changed from 19 to 11 mm2 /s after treatment with activated bentonite. However, flash point achieved 149 ºC.

Dynamics of Functional Composition of a Brazilian Tropical Forest in Response to Drought Stress

The aim of this study was to examine the dynamics of functional composition of a non flooded Amazonian forest in response to drought stress in terms of diameter growth, recruitment and mortality. The survey was carried out in the continuous forest of the Biological dynamics of forest fragments project 90 km outside the city of Manaus, state of Amazonas Brazil. All stems >10 cm dbh where identified to species level and monitored in 18 one hectare permanent sample plots from 1981 to 2004.For statistical analysis all species where aggregated in three ecological guilds. Two distinct drought events occurred in 1983 and 1997. Results showed that more early successional species performed better than later successional ones. Response was significant for both events but for the 1997 event this was more pronounced possibly because of the fact that the event was in the middle of the dry rather than the wet period as was the 1983 one.

The Citizen Participation in Preventing Illegal Drugs Program in Bangkok, Thailand

The purposes of this research were to study the citizen participation in preventing illegal drugs in one of a poor and small community of Bangkok, Thailand and to compare the level of participation and concern of illegal drugs problem by using demographic variables. This paper drew upon data collected from a local citizens survey conducted in Bangkok, Thailand during summer of 2012. A total of 200 respondents were elicited as data input for, and one way ANOVA test. The findings revealed that the overall citizen participation was in the level of medium. The mean score showed that benefit from the program was ranked as the highest and the decision to participate was ranked as second while the follow-up of the program was ranked as the lowest. In terms of the difference in demographic such as gender, age, level of education, income, and year of residency, the hypothesis testing’s result disclosed that there were no difference in their level of participation. However, difference in occupation showed a difference in their level of participation and concern which was significant at the 0.05 confidence level.

Concept Indexing using Ontology and Supervised Machine Learning

Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

A Distributed Weighted Cluster Based Routing Protocol for Manets

Mobile ad-hoc networks (MANETs) are a form of wireless networks which do not require a base station for providing network connectivity. Mobile ad-hoc networks have many characteristics which distinguish them from other wireless networks which make routing in such networks a challenging task. Cluster based routing is one of the routing schemes for MANETs in which various clusters of mobile nodes are formed with each cluster having its own clusterhead which is responsible for routing among clusters. In this paper we have proposed and implemented a distributed weighted clustering algorithm for MANETs. This approach is based on combined weight metric that takes into account several system parameters like the node degree, transmission range, energy and mobility of the nodes. We have evaluated the performance of proposed scheme through simulation in various network situations. Simulation results show that proposed scheme outperforms the original distributed weighted clustering algorithm (DWCA).

Doping Profile Measurement and Characterization by Scanning Capacitance Microscope for PocketImplanted Nano Scale n-MOSFET

This paper presents the doping profile measurement and characterization technique for the pocket implanted nano scale n-MOSFET. Scanning capacitance microscopy and atomic force microscopy have been used to image the extent of lateral dopant diffusion in MOS structures. The data are capacitance vs. voltage measurements made on a nano scale device. The technique is nondestructive when imaging uncleaved samples. Experimental data from the published literature are presented here on actual, cleaved device structures which clearly indicate the two-dimensional dopant profile in terms of a spatially varying modulated capacitance signal. Firstorder deconvolution indicates the technique has much promise for the quantitative characterization of lateral dopant profiles. The pocket profile is modeled assuming the linear pocket profiles at the source and drain edges. From the model, the effective doping concentration is found to use in modeling and simulation results of the various parameters of the pocket implanted nano scale n-MOSFET. The potential of the technique to characterize important device related phenomena on a local scale is also discussed.

A New Face Detection Technique using 2D DCT and Self Organizing Feature Map

This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

An Empirical Analysis of Earnings Management in Australia

This is a comprehensive large-sample study of Australian earnings management. Using a sample of 4,844 firm-year observations across nine Australia industries from 2000 to 2006, we find substantial corporate earnings management activity across several Australian industries. We document strong evidence of size and return on assets being primary determinants of earnings management in Australia. The effects of size and return on assets are also found to be dominant in both income-increasing and incomedecreasing earnings manipulation. We also document that that periphery sector firms are more likely to involve larger magnitude of earnings management than firms in the core sector.

A Discrete Filtering Algorithm for Impulse Wave Parameter Estimation

This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.

Necessity of Risk Management of Various Industry-Associated Pollutants(Case Study of Gavkhoni Wetland Ecosystem)

Since the beginning of human history, human activities have caused many changes in the environment. Today, a particular attention should be paid to gaining knowledge about water quality of wetlands which are pristine natural environments rich in genetic reserves. If qualitative conditions of industrial areas (in terms of both physicochemical and biological conditions) are not addressed properly, they could cause disruption in natural ecosystems, especially in rivers. With regards to the quality of water resources, determination of pollutant sources plays a pivotal role in engineering projects as well as designing water quality control systems. Thus, using different methods such as flow duration curves, dischargepollution load model and frequency analysis by HYFA software package, risk of various industrial pollutants in international and ecologically important Gavkhoni wetland is analyzed. In this study, a station located at Varzaneh City is used as the last station on Zayanderud River, from where the river water is discharged into the wetland. Results showed that elements- concentrations often exceeded the allowed level and river water can endanger regional ecosystem. In addition, if the river discharge is managed on Q25 basis, this basis can lower concentrations of elements, keeping them within the normal level.

Significance of Splitting Method in Non-linear Grid system for the Solution of Navier-Stokes Equation

Solution to unsteady Navier-Stokes equation by Splitting method in physical orthogonal algebraic curvilinear coordinate system, also termed 'Non-linear grid system' is presented. The linear terms in Navier-Stokes equation are solved by Crank- Nicholson method while the non-linear term is solved by the second order Adams-Bashforth method. This work is meant to bring together the advantage of Splitting method as pressure-velocity solver of higher efficiency with the advantage of consuming Non-linear grid system which produce more accurate results in relatively equal number of grid points as compared to Cartesian grid. The validation of Splitting method as a solution of Navier-Stokes equation in Nonlinear grid system is done by comparison with the benchmark results for lid driven cavity flow by Ghia and some case studies including Backward Facing Step Flow Problem.

Application of Extreme Learning Machine Method for Time Series Analysis

In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.

Recycling Organic Waste in Suan Sunandha Rajabhat University as Compost

This research aimed to study on the potential of recycling organic waste in Suan Sunandha Rajabhat University as compost. In doing so, the composition of solid waste generated in the campus was investigated while physical and chemical properties of organic waste were analyzed in order to evaluate the portion of waste suitable for recycling as compost. As a result of the study, it was found that (1) the amount of organic waste was averaged at 299.8 kg/day in which mixed food wastes had the highest amount of 191.9 kg/day followed by mixed leave & yard wastes and mixed fruit & vegetable wastes at the amount of 66.3 and 41.6 kg/day respectively; (2) physical and chemical properties of organic waste in terms of moisture content was between 69.54 to 78.15%, major elements for plant as N, P and K were 0.14 to 0.17%, 0.46 to 0.52% and 0.16 to 0.18% respectively, and carbon/nitrogen ratio (C/N) was about 15:1 to 17.5:1; (3) recycling organic waste as compost was designed by aerobic decomposition using mixed food wastes : mixed leave & yard wastes : mixed fruit & vegetable wastes at the portion of 3:2:1 by weight in accordance with the potential of their amounts and their physical and chemical properties.

Transfer Function of Piezoelectric Material

The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.