Evaluation of Aerodynamic Noise Generation by a Generic Side Mirror

The aerodynamic noise radiation from a side view mirror (SVM) in the high-speed airflow is calculated by the combination of unsteady incompressible fluid flow analysis and acoustic analysis. The transient flow past the generic SVM is simulated with variable turbulence model, namely DES Detached Eddy Simulation and LES (Large Eddy Simulation). Detailed velocity vectors and contour plots of the time-varying velocity and pressure fields are presented along cut planes in the flow-field. Mean and transient pressure are also monitored at several points in the flow field and compared to corresponding experimentally data published in literature. The acoustic predictions made using the Ffowcs-Williams-Hawkins acoustic analogy (FW-H) and the boundary element (BEM).

Development of Variable Stepsize Variable Order Block Method in Divided Difference Form for the Numerical Solution of Delay Differential Equations

This paper considers the development of a two-point predictor-corrector block method for solving delay differential equations. The formulae are represented in divided difference form and the algorithm is implemented in variable stepsize variable order technique. The block method produces two new values at a single integration step. Numerical results are compared with existing methods and it is evident that the block method performs very well. Stability regions of the block method are also investigated.

Promoting Mathematical Understanding Using ICT in Teaching and Learning

Information and Communication Technologies (ICT) in mathematical education is a very active field of research and innovation, where learning is understood to be meaningful and grasping multiple linked representation rather than rote memorization, a great amount of literature offering a wide range of theories, learning approaches, methodologies and interpretations, are generally stressing the potentialities for teaching and learning using ICT. Despite the utilization of new learning approaches with ICT, students experience difficulties in learning concepts relevant to understanding mathematics, much remains unclear about the relationship between the computer environment, the activities it might support, and the knowledge that might emerge from such activities. Many questions that might arise in this regard: to what extent does the use of ICT help students in the process of understanding and solving tasks or problems? Is it possible to identify what aspects or features of students' mathematical learning can be enhanced by the use of technology? This paper will highlight the interest of the integration of information and communication technologies (ICT) into the teaching and learning of mathematics (quadratic functions), it aims to investigate the effect of four instructional methods on students- mathematical understanding and problem solving. Quantitative and qualitative methods are used to report about 43 students in middle school. Results showed that mathematical thinking and problem solving evolves as students engage with ICT activities and learn cooperatively.

Design of Digital Differentiator to Optimize Relative Error

It is observed that the Weighted least-square (WLS) technique, including the modifications, results in equiripple error curve. The resultant error as a percent of the ideal value is highly non-uniformly distributed over the range of frequencies for which the differentiator is designed. The present paper proposes a modification to the technique so that the optimization procedure results in lower maximum relative error compared to the ideal values. Simulation results for first order as well as higher order differentiators are given to illustrate the excellent performance of the proposed method.

Using Artificial Neural Network to Forecast Groundwater Depth in Union County Well

A concern that researchers usually face in different applications of Artificial Neural Network (ANN) is determination of the size of effective domain in time series. In this paper, trial and error method was used on groundwater depth time series to determine the size of effective domain in the series in an observation well in Union County, New Jersey, U.S. different domains of 20, 40, 60, 80, 100, and 120 preceding day were examined and the 80 days was considered as effective length of the domain. Data sets in different domains were fed to a Feed Forward Back Propagation ANN with one hidden layer and the groundwater depths were forecasted. Root Mean Square Error (RMSE) and the correlation factor (R2) of estimated and observed groundwater depths for all domains were determined. In general, groundwater depth forecast improved, as evidenced by lower RMSEs and higher R2s, when the domain length increased from 20 to 120. However, 80 days was selected as the effective domain because the improvement was less than 1% beyond that. Forecasted ground water depths utilizing measured daily data (set #1) and data averaged over the effective domain (set #2) were compared. It was postulated that more accurate nature of measured daily data was the reason for a better forecast with lower RMSE (0.1027 m compared to 0.255 m) in set #1. However, the size of input data in this set was 80 times the size of input data in set #2; a factor that may increase the computational effort unpredictably. It was concluded that 80 daily data may be successfully utilized to lower the size of input data sets considerably, while maintaining the effective information in the data set.

Corporate Environmentalism: A Case Study in the Czech Republic

This study examines perception of environmental approach in small and medium-sized enterprises (SMEs) – the process by which firms integrate environmental concern into business. Based on a review of the literature, the paper synthesizes focus on environmental issues with the reflection in a case study in the Czech Republic. Two themes of corporate environmentalism are discussed – corporate environmental orientation and corporate stances toward environmental concerns. It provides theoretical material on greening organizational culture that is helpful in understanding the response of contemporary business to environmental problems. We integrate theoretical predictions with empirical findings confronted with reality. Scales to measure these themes are tested in a survey of managers in 229 Czech firms. We used the process of in-depth questioning. The research question was derived and answered in the context of the corresponding literature and conducted research. A case study showed us that environmental approach is variety different (depending on the size of the firm) in SMEs sector. The results of the empirical mapping demonstrate Czech company’s approach to environment and define the problem areas and pinpoint the main limitation in the expansion of environmental aspects. We contribute to the debate for recognition of the particular role of environmental issues in business reality.

Transport and Fate of Copper in Soils

The presence of toxic heavy metals in industrial effluents is one of the serious threats to the environment. Heavy metals such as Cadmium, Chromium, Lead, Nickel, Zinc, Mercury, Copper, Arsenic are found in the effluents of industries such as foundries, electroplating, petrochemical, battery manufacturing, tanneries, fertilizer, dying, textiles, metallurgical and metal finishing. Tremendous increase of industrial copper usage and its presence in industrial effluents has lead to a growing concern about the fate and effects of Copper in the environment. Percolation of industrial effluents through soils leads to contamination of ground water and soils. The transport of heavy metals and their diffusion into the soils has therefore, drawn the attention of the researchers. In this study, an attempt has been made to delineate the mechanisms of transport and fate of copper in terrestrial environment. Column studies were conducted using perplex glass square column of dimension side 15 cm and 1.35 m long. The soil samples were collected from a natural drain near Mohali (India). The soil was characterized to be poorly graded sandy loam. The soil was compacted to the field dry density level of about 1.6 g/cm3. Break through curves for different depths of the column were plotted. The results of the column study indicated that the copper has high tendency to flow in the soils and fewer tendencies to get absorbed on the soil particles. The t1/2 estimates obtained from the studies can be used for design copper laden wastewater disposal systems.

A New Variant of RC4 Stream Cipher

RC4 was used as an encryption algorithm in WEP(Wired Equivalent Privacy) protocol that is a standardized for 802.11 wireless network. A few attacks followed, indicating certain weakness in the design. In this paper, we proposed a new variant of RC4 stream cipher. The new version of the cipher does not only appear to be more secure, but its keystream also has large period, large complexity and good statistical properties.

A Novel Multiple Valued Logic OHRNS Modulo rn Adder Circuit

Residue Number System (RNS) is a modular representation and is proved to be an instrumental tool in many digital signal processing (DSP) applications which require high-speed computations. RNS is an integer and non weighted number system; it can support parallel, carry-free, high-speed and low power arithmetic. A very interesting correspondence exists between the concepts of Multiple Valued Logic (MVL) and Residue Number Arithmetic. If the number of levels used to represent MVL signals is chosen to be consistent with the moduli which create the finite rings in the RNS, MVL becomes a very natural representation for the RNS. There are two concerns related to the application of this Number System: reaching the most possible speed and the largest dynamic range. There is a conflict when one wants to resolve both these problem. That is augmenting the dynamic range results in reducing the speed in the same time. For achieving the most performance a method is considere named “One-Hot Residue Number System" in this implementation the propagation is only equal to one transistor delay. The problem with this method is the huge increase in the number of transistors they are increased in order m2 . In real application this is practically impossible. In this paper combining the Multiple Valued Logic and One-Hot Residue Number System we represent a new method to resolve both of these two problems. In this paper we represent a novel design of an OHRNS-based adder circuit. This circuit is useable for Multiple Valued Logic moduli, in comparison to other RNS design; this circuit has considerably improved the number of transistors and power consumption.

Signal Generator Circuit Carrying Information as Embedded Features from Multi-Transducer Signals

A novel circuit for generating a signal embedded with features about data from three sensors is presented. This suggested circuit is making use of a resistance-to-time converter employing a bridge amplifier, an integrator and a comparator. The second resistive sensor (Rz) is transformed into duty cycle. Another bridge with varying resistor, (Ry) in the feedback of an OP AMP is added in series to change the amplitude of the resulting signal in a proportional relationship while keeping the same frequency and duty cycle representing proportional changes in resistors Rx and Rz already mentioned. The resultant output signal carries three types of information embedded as variations of its frequency, duty cycle and amplitude.

Development of an Infrared Thermography Method with CO2 Laser Excitation, Applied to Defect Detection in CFRP

This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.

Content Based Image Retrieval of Brain MR Images across Different Classes

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.

Real Power Generation Scheduling to Improve Steady State Stability Limit in the Java-Bali 500kV Interconnection Power System

This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.

Cloud Computing: Changing Cogitation about Computing

Cloud Computing is a new technology that helps us to use the Cloud for compliance our computation needs. Cloud refers to a scalable network of computers that work together like Internet. An important element in Cloud Computing is that we shift processing, managing, storing and implementing our data from, locality into the Cloud; So it helps us to improve the efficiency. Because of it is new technology, it has both advantages and disadvantages that are scrutinized in this article. Then some vanguards of this technology are studied. Afterwards we find out that Cloud Computing will have important roles in our tomorrow life!

Adaptive Kernel Filtering Used in Video Processing

In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.

Extraction of Symbolic Rules from Artificial Neural Networks

Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, such as breast cancer, iris, diabetes, and season classification problems, demonstrate the effectiveness of the proposed approach with good generalization ability.

Study of Features for Hand-printed Recognition

The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM.

The Roles of Natural and Anthropogenic Factors of Ecological State in the Lake Peipsi

In this paper we discuss the problems of the long-term management policy of Lake Peipsi and the roles of natural and anthropogenic factors in the ecological state of the lake. The reduction of the pollution during the last 15 years could not give significant changes of the chemical composition of the water, what implicates the essential role that natural factors have on the ecological state of lake. One of the most important factors having impact on the hydrochemical cycles and ecological state is the hydrological regime which is clearly expressed in L. Peipsi. The absence on clear interrelations of climate cycles and nutrients suggest that complex abiotic and biotic interactions, which take place in the lake ecosystem, plays a significant role in the matter circulation mechanism within lake.

Removal of Hydrogen Sulphide from Air by Means of Fibrous Ion Exchangers

The removal of hydrogen sulphide is required for reasons of health, odour problems, safety and corrosivity problems. The means of removing hydrogen sulphide mainly depend on its concentration and kind of medium to be purified. The paper deals with a method of hydrogen sulphide removal from the air by its catalytic oxidation to elemental sulphur with the use of Fe-EDTA complex. The possibility of obtaining fibrous filtering materials able to remove small concentrations of H2S from the air were described. The base of these materials is fibrous ion exchanger with Fe(III)- EDTA complex immobilized on their functional groups. The complex of trivalent iron converts hydrogen sulphide to elemental sulphur. Bivalent iron formed in the reaction is oxidized by the atmospheric oxygen, so complex of trivalent iron is continuously regenerated and the overall process can be accounted as pseudocatalytic. In the present paper properties of several fibrous catalysts based on ion exchangers with different chemical nature (weak acid,weak base and strong base) were described. It was shown that the main parameters affecting the process of catalytic oxidation are:concentration of hydrogen sulphide in the air, relative humidity of the purified air, the process time and the content of Fe-EDTA complex in the fibres. The data presented show that the filtering layers with anion exchange package are much more active in the catalytic processes of hydrogen sulphide removal than cation exchanger and inert materials. In the addition to the nature of the fibres relative air humidity is a critical factor determining efficiency of the material in the air purification from H2S. It was proved that the most promising carrier of the Fe-EDTA catalyst for hydrogen sulphide oxidation are Fiban A-6 and Fiban AK-22 fibres.

Evaluation of State of the Art IDS Message Exchange Protocols

During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.