New Mitigating Technique to Overcome DDOS Attack

In this paper, we explore a new scheme for filtering spoofed packets (DDOS attack) which is a combination of path fingerprint and client puzzle concepts. In this each IP packet has a unique fingerprint is embedded that represents, the route a packet has traversed. The server maintains a mapping table which contains the client IP address and its corresponding fingerprint. In ingress router, client puzzle is placed. For each request, the puzzle issuer provides a puzzle which the source has to solve. Our design has the following advantages over prior approaches, 1) Reduce the network traffic, as we place a client puzzle at the ingress router. 2) Mapping table at the server is lightweight and moderate.

Analysis of Electrical Installation of a Photovoltaic Power Park in Greece

The scope of this paper is to describe a real electrical installation of renewable energy using photovoltaic cells. The displayed power grid connected network was established in 2007 at area of Northern Greece. The photovoltaic park is composed of 6120 photovoltaic cells able to deliver a total power of 1.101.600 Wp. For the transformation of DC voltage to AC voltage have been used 25 stand alone three phases inverters and for the connection at the medium voltage network of Greek Power Authority have been installed two oil immersed transformer of 630 kVA each one. Due to the wide space area of installation a specific external lightning protection system has been designed. Additionally, due to the sensitive electronics of the control and protection systems of park, surge protection, equipotent bonding and shielding were also of major importance.

Effect of Planting Density on Yield and Yield Components of Safflower Cultivars in Spring Planting

This study carried out to determine the effect of plant densities on some agronomic characteristics of four safflower cultivars in spring planting. The experiment was conducted at Yazd, Iran- using a factorial in a randomized complete block design with four replications. Cultivars were including Arak, IL, Asteria and Local and plant densities were 10, 13.3, 20 and 40 plant/m2. Number of seeds/head, number of heads/plant, HI, 1000-seed weight and seed yield significantly decreased as planting density increased. With increasing planting density, LAI, plant height, first branch height and biological yield increased. The highest seed yield was obtained in 13.3 plant/m2 (2167 kg/ha). There were significant differences between cultivars. Local cv. had higher seed yield than the other cultivars mainly due to higher heads/plant and seeds/head.

Hydrogen from Waste Tyres

Hydrogen is regarded to play an important role in future energy systems because it can be produced from abundant resources and its combustion only generates water. The disposal of waste tyres is a major problem in environmental management throughout the world. The use of waste materials as a source of hydrogen is particularly of interest in that it would also solve a waste treatment problem. There is much interest in the use of alternative feedstocks for the production of hydrogen since more than 95% of current production is from fossil fuels. The pyrolysis of waste tyres for the production of liquid fuels, activated carbons and gases has been extensively researched. However, combining pyrolysis with gasification is a novel process that can gasify the gaseous products from pyrolysis. In this paper, an experimental investigation into the production of hydrogen and other gases from the bench scale pyrolysis-gasification of tyres has been investigated. Experiments were carried using a two stage system consisting of pyrolysis of the waste tyres followed by catalytic steam gasification of the evolved gases and vapours in a second reactor. Experiments were conducted at a pyrolysis temperature of 500 °C using Ni/Al2O3 as a catalyst. The results showed that there was a dramatic increase in gas yield and the potential H2 production when the gasification temperature was increased from 600 to 900 oC. Overall, the process showed that high yields of hydrogen can be produced from waste tyres.

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.

Nonlinear Dynamical Characterization of Heart Rate Variability Time Series of Meditation

Many recent electrophysiological studies have revealed the importance of investigating meditation state in order to achieve an increased understanding of autonomous control of cardiovascular functions. In this paper, we characterize heart rate variability (HRV) time series acquired during meditation using nonlinear dynamical parameters. We have computed minimum embedding dimension (MED), correlation dimension (CD), largest Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV time series of eight Chi and four Kundalini meditation practitioners. The pre-meditation state has been used as a baseline (control) state to compare the estimated parameters. The chaotic nature of HRV during both pre-meditation and meditation is confirmed by MED. The meditation state showed a significant decrease in the value of CD and increase in the value of LLE of HRV, in comparison with premeditation state, indicating a less complex and less predictable nature of HRV. In addition, it was shown that the HRV of meditation state is having highest NLS than pre-meditation state. The study indicated highly nonlinear dynamic nature of cardiac states as revealed by HRV during meditation state, rather considering it as a quiescent state.

Amplification of Compression Waves in Clean and Bubbly Liquid

The theoretical investigation is carried out to describe the effect of increase of pressure waves amplitude in clean and bubbly liquid. The goal of the work is to capture the regime of multiple magnification of acoustic and shock waves in the liquid, which enables to get appropriate conditions to enlarge collapses of micro-bubbles. The influence of boundary conditions and frequency of the governing acoustic field is studied for the case of the cylindrical acoustic resonator. It has been observed the formation of standing waves with large amplitude at resonant frequencies. The interaction of the compression wave with gas and vapor bubbles is investigated for the convergent channel. It is shown theoretically that the chemical reactions, which occur inside gas bubbles, provide additional impulse to the wave, that affect strongly on the collapses of the vapor bubbles

Performance Analysis of the Subgroup Method for Collective I/O

As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.

Socio-Demographic Status and Arrack Drinking Patterns among Muslim, Hindu, Santal and Oraon Communities in Rasulpur Union,Bangladesh: A Cross-Cultural Perspective

Arrack is one of the forms of alcoholic beverage or liquor which is produced from palm or date juice and commonly consumed by the lower social class of all religious/ethnic communities in the north-western villages of Bangladesh. The purpose of the study was to compare arrack drinking patterns associated with socio-demographic status among the Muslim, Hindu, Santal, and Oraon communities in the Rasulpur union of Bangladesh. A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89, Oraon n-90) selected by cluster random sampling were interviewed by ADP (Arrack Drinking Pattern) questionnaire. The results of Pearson Chi-Squire test revealed that arrack drinking patterns were significantly differed among the Muslim, Hindu, Santal, and Oraon communities- drinkers. In addition, the results of Spearman-s bivariate correlation coefficients also revealed that sociodemographic characteristics of the communities- drinkers were the significantly positive and negative associations with the arrack drinking patterns in the Rasulpur union, Bangladesh. The study suggests that further cross-cultural researches should be conducted on the consequences of arrack drinking patterns on the communities- drinkers.

Multilevel Classifiers in Recognition of Handwritten Kannada Numerals

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Modeling and Simulations of Complex Low- Dimensional systems: Testing the Efficiency of Parallelization

The deterministic quantum transfer-matrix (QTM) technique and its mathematical background are presented. This important tool in computational physics can be applied to a class of the real physical low-dimensional magnetic systems described by the Heisenberg hamiltonian which includes the macroscopic molecularbased spin chains, small size magnetic clusters embedded in some supramolecules and other interesting compounds. Using QTM, the spin degrees of freedom are accurately taken into account, yielding the thermodynamical functions at finite temperatures. In order to test the application for the susceptibility calculations to run in the parallel environment, the speed-up and efficiency of parallelization are analyzed on our platform SGI Origin 3800 with p = 128 processor units. Using Message Parallel Interface (MPI) system libraries we find the efficiency of the code of 94% for p = 128 that makes our application highly scalable.

Recognition of Noisy Words Using the Time Delay Neural Networks Approach

This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Spread Spectrum Image Watermarking for Secured Multimedia Data Communication

Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.

Study of Temperature Changes in Fars Province

Climate change is a phenomenon has been based on the available evidence from a very long time ago and now its existence is very probable. The speed and nature of climate parameters changes at the middle of twentieth century has been different and its quickness more than the before and its trend changed to some extent comparing to the past. Climate change issue now regarded as not only one of the most common scientific topic but also a social political one, is not a new issue. Climate change is a complicated atmospheric oceanic phenomenon on a global scale and long-term. Precipitation pattern change, fast decrease of snowcovered resources and its rapid melting, increased evaporation, the occurrence of destroying floods, water shortage crisis, severe reduction at the rate of harvesting agricultural products and, so on are all the significant of climate change. To cope with this phenomenon, its consequences and events in which public instruction is the most important but it may be climate that no significant cant and effective action has been done so far. The present article is included a part of one surrey about climate change in Fars. The study area having annually mean temperature 14 and precipitation 320 mm .23 stations inside the basin with a common 37 year statistical period have been applied to the meteorology data (1974-2010). Man-kendal and change factor methods are two statistical methods, applying them, the trend of changes and the annual mean average temperature and the annual minimum mean temperature were studied by using them. Based on time series for each parameter, the annual mean average temperature and the mean of annual maximum temperature have a rising trend so that this trend is clearer to the mean of annual maximum temperature.

Study on Carbonation Process of Several Types of Advanced Lime-Based Plasters

In this paper, study on carbonation process of several types of advanced plasters on lime basis is presented. The movement of carbonation head was measured by colorimetric method using phenolphtalein. The rate of carbonation was accessed also by gravimetric method. Samples of studied materials were placed into the climatic chamber for simulation of environment with high concentration of CO2. The particular samples were on all lateral sides and on the bottom side provided by epoxy resin in order to arrange 1-D transport of CO2 into the studied samples. The carbonation rates of particular materials pointed to the time dependence of diffusion process of CO2 for all the studied plasters. From the quantitative point of view, the carbonation of advanced modified plasters was much faster than for the reference lime plaster, what is beneficial for the practical application of the tested newly developed materials.

Investigation of Buoyant Parameters of k-ε Turbulence Model in Gravity Stratified Flows

Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stress Model (ASM). In order to account for turbulent scalar fluxes, general gradient diffusion hypothesis has been used along with Boussinesq gradient diffusion hypothesis with a variable turbulent Schmidt number and additional empirical constant c3ε.To simulate buoyant flow domain a 2D vertical numerical model (WISE, Width Integrated Stratified Environments), based on Reynolds- Averaged Navier-Stokes (RANS) equations, has been deployed and the model has been further developed for different k-ε turbulence closures. Results are compared against measured laboratory values of a saline gravity current to explore the efficient turbulence model.

Chattering Phenomenon Supression of Buck Boost DC-DC Converter with Fuzzy Sliding Modes Control

This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The performances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.

A Cumulative Learning Approach to Data Mining Employing Censored Production Rules (CPRs)

Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Spectrum Sensing Based On the Cyclostationarity of PU Signals in High Traffic Environments

In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.

Middle East towards Incubator Benefits: Case Studies

In the context of business incubation (BI) as strategic enablers, this paper critically reviews the literature relating to the strategic benefits of BI in the Middle East. The taxonomy of BI benefits in the strategic elements on 1) type, 2) financial model, 3) services, 4) objectives, 5) number of clients, 6) number of graduates, and 7) jobs creation. Understanding the importance of BI benefits can be significant in the economic development although most incubators lead to diversify the economy. Thus, taxonomies of the benefits of BI are produced from both the academic literature and published case studies. In this way, a classification of strategic benefits elements as they relate to incubators has been developed to provide a greater understanding of the benefits needed to obtain a specific element. The result of this paper is Business incubators is aimed entrepreneurship, jobs creation, research commercialization and profitable enterprises in Middle Eastern countries.