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.

An Efficient and Secure Solution for the Problems of ARP Cache Poisoning Attacks

The Address Resolution Protocol (ARP) is used by computers to map logical addresses (IP) to physical addresses (MAC). However ARP is an all trusting protocol and is stateless which makes it vulnerable to many ARP cache poisoning attacks such as Man-in-the-Middle (MITM) and Denial of service (DoS) attacks. These flaws result in security breaches thus weakening the appeal of the computer for exchange of sensitive data. In this paper we describe ARP, outline several possible ARP cache poisoning attacks and give the detailed of some attack scenarios in network having both wired and wireless hosts. We have analyzed each of proposed solutions, identify their strengths and limitations. Finally get that no solution offers a feasible solution. Hence, this paper presents an efficient and secure version of ARP that is able to cope up with all these types of attacks and is also a feasible solution. It is a stateful protocol, by storing the information of the Request frame in the ARP cache, to reduce the chances of various types of attacks in ARP. It is more efficient and secure by broadcasting ARP Reply frame in the network and storing related entries in the ARP cache each time when communication take place.

Infrastructure Planning in Scania a Discourse Analytical Approach to the Concepts of Regional Development and Sustainability in the Planning Process

The paper applies a discourse analytical approach to investigate important concepts influencing the infrastructure planning process in the region of Scania in southern Sweden. Two discourses, one concerning regional development and one concerning sustainability are identified, discussed and contrasted. It is argued that the perceptions of problems and their suggested solutions related to transportation are based on specific ideas, in turn dependent on the importance given to certain concepts, such as regional enlargement, Scania as a transit region, the national environmental quality goals and regional attractiveness. These concepts, their underlying meaning structures and their relevance for the infrastructure planning process are analyzed. The handling of conflicting interests in the planning process, and the possible implications this may have is also discussed. The results indicate that the regional development discourse is dominant and although the solutions to the problems caused by transport are framed in similar ways in the two discourses a harmonization between conflicting goals is proving difficult to achieve.

A System of Automatic Speech Recognition based on the Technique of Temporal Retiming

We report in this paper the procedure of a system of automatic speech recognition based on techniques of the dynamic programming. The technique of temporal retiming is a technique used to synchronize between two forms to compare. We will see how this technique is adapted to the field of the automatic speech recognition. We will expose, in a first place, the theory of the function of retiming which is used to compare and to adjust an unknown form with a whole of forms of reference constituting the vocabulary of the application. Then we will give, in the second place, the various algorithms necessary to their implementation on machine. The algorithms which we will present were tested on part of the corpus of words in Arab language Arabdic-10 [4] and gave whole satisfaction. These algorithms are effective insofar as we apply them to the small ones or average vocabularies.

Arabic Word Semantic Similarity

This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.

Locating Critical Failure Surface in Rock Slope Stability with Hybrid Model Based on Artificial Immune System and Cellular Learning Automata (CLA-AIS)

Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Performances Comparison of Neural Architectures for On-Line Speed Estimation in Sensorless IM Drives

The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.

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.

Temporal Change of Fractal Dimension of Explosion Earthquakes and Harmonic Tremors at Semeru Volcano, East Java, Indonesia, using Critical Exponent Method

Fractal analyses of successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were carried out to investigate the dynamical system regarding to their generating mechanism. The explosive eruptions accompanied by explosion earthquakes and following volcanic tremor which are generated by continuous emission of volcanic ash. The fractal dimension of successive event of explosion and harmonic tremor was estimated by Critical Exponent Method (CEM). It was found that the method yield a higher fractal dimension of explosion earthquakes and gradually decrease during the occurrence of harmonic tremor, and can be considerably as correlated complexity of the source mechanism from the variance of fractal dimension.

Development of Machinable Ellipses by NURBS Curves

Owning to the high-speed feed rate and ultra spindle speed have been used in modern machine tools, the tool-path generation plays a key role in the successful application of a High-Speed Machining (HSM) system. Because of its importance in both high-speed machining and tool-path generation, approximating a contour by NURBS format is a potential function in CAD/CAM/CNC systems. It is much more convenient to represent an ellipse by parametric form than to connect points laboriously determined in a CNC system. A new approximating method based on optimum processes and NURBS curves of any degree to the ellipses is presented in this study. Such operations can be the foundation of tool-radius compensation interpolator of NURBS curves in CNC system. All operating processes for a CAD tool is presented and demonstrated by practical models.

Evolutionary Computing Approach for the Solution of Initial value Problems in Ordinary Differential Equations

An evolutionary computing technique for solving initial value problems in Ordinary Differential Equations is proposed in this paper. Neural network is used as a universal approximator while the adaptive parameters of neural networks are optimized by genetic algorithm. The solution is achieved on the continuous grid of time instead of discrete as in other numerical techniques. The comparison is carried out with classical numerical techniques and the solution is found with a uniform accuracy of MSE ≈ 10-9 .

Comparison of Artificial Neural Network and Multivariate Regression Methods in Prediction of Soil Cation Exchange Capacity

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Analysis of Cost Estimation and Payment Systems for Consultant Contracts in the US, Japan, China and the UK

Determining reasonable fees is the main objective of designing the cost estimation and payment systems for consultant contracts. However, project clients utilize different cost estimation and payment systems because of their varying views on the reasonableness of consultant fees. This study reviews the cost estimation and payment systems of consultant contracts for five countries, including the US (Washington State Department of Transportation), Japan (Ministry of Land, Infrastructure, Transport and Tourism), China (Engineering Design Charging Standard) and UK (Her Majesty's Treasure). Specifically, this work investigates the budgeting process, contractor selection method, contractual price negotiation process, cost review, and cost-control concept of the systems used in these countries. The main finding indicates that that project client-s view on whether the fee is high will affect the way he controls it. In the US, the fee is commonly considered to be high. As a result, stringent auditing system (low flexibility given to the consultant) is then applied. In the UK, the fee is viewed to be low by comparing it to the total life-cycle project cost. Thus, a system that has high flexibility in budgeting and cost reviewing is given to the consultant. In terms of the flexibility allowed for the consultant, the systems applied in Japan and China fall between those of the US and UK. Both the US and UK systems are helpful in determining a reasonable fee. However, in the US system, rigid auditing standards must be established and additional cost-audit manpower is required. In the UK system, sufficient historical cost data should be needed to evaluate the reasonableness of the consultant-s proposed fee

Effects of Silicon Oxide Filler Material and Fibre Orientation on Erosive Wear of GF/EP Composites

Materials added to the matrix help improving operating properties of a composite. This experimental study has targeted to investigate this aim where Silicon Oxide particles were added to glass fibre and epoxy resin at an amount of 15% to the main material to obtain a sort of new composite material. Erosive wear behavior of epoxy-resin dipped composite materials reinforced with glass fibre and Silicon Oxide under three different impingement angles (30°, 60° and 90°), three different impact velocities (23, 34 and 53 m/s), two different angular Aluminum abrasive particle sizes (approximately 200 and 400 μm) and the fibre orientation of 45° (45/-45) were investigated. In the test results, erosion rates were obtained as functions of impingement angles, impact velocities, particle sizes and fibre orientation. Moreover, materials with addition of Silicon Oxide filler material exhibited lower wear as compared to neat materials with no added filler material. In addition, SEM views showing worn out surfaces of the test specimens were scrutinized.

Effect of Phosphate Solubilization Microorganisms (PSM) and Plant Growth Promoting Rhizobacteria (PGPR) on Yield and Yield Components of Corn (Zea mays L.)

In order to study the effect of phosphate solubilization microorganisms (PSM) and plant growth promoting rhizobacteria (PGPR) on yield and yield components of corn Zea mays (L. cv. SC604) an experiment was conducted at research farm of Sari Agricultural Sciences and Natural Resources University, Iran during 2007. Experiment laid out as split plot based on randomized complete block design with three replications. Three levels of manures (consisted of 20 Mg.ha-1 farmyard manure, 15 Mg.ha-1 green manure and check or without any manures) as main plots and eight levels of biofertilizers (consisted of 1-NPK or conventional fertilizer application; 2-NPK+PSM+PGPR; 3 NP50%K+PSM+PGPR; 4- N50%PK+PSM +PGPR; 5-N50%P50%K+PSM+ PGPR; 6-PK+PGPR; 7- NK+PSM and 8-PSM+PGPR) as sub plots were treatments. Results showed that farmyard manure application increased row number, ear weight, grain number per ear, grain yield, biological yield and harvest index compared to check. Furthermore, using of PSM and PGPR in addition to conventional fertilizer applications (NPK) could improve ear weight, row number and grain number per row and ultimately increased grain yield in green manure and check plots. According to results in all fertilizer treatments application of PSM and PGPR together could reduce P application by 50% without any significant reduction of grain yield. However, this treatment could not compensate 50% reduction of N application.

Seed Treatment during Germination in Linseed to Overcome Salt and Drought Stresses (Linum usitatissimum L.)

Evaluation of crop plants resistance to environmental stresses specially in germination stage is a critical factor in their selection in different conditions of cultivation. Therefore use of a procedure in controllable situation can help to evaluate plants reaction to stress quickly and precisely. In order to study germination characteristics of flax in water and salinity stress conditions were conducted two laboratories experimental. The two experimental were conducted in 4-replicant completing random design for salinity and water stress. The treatment, for salinity and water stress was three potential (zero, 40, 80 mM) of NaCl and three potential (zero, -2, -4 bar) of PEG respectively. Germination percentage and rate, in addition to Radical and plumule length and dry-weight and plumule/Radical ration were measured. All of characteristics reduce under water stress conditions. salinity stress significant reduce germination rate and Radical and plumule length of flax seeds. Hydropriming and osmopriming significant increased germination rate, plumule length and plumule/Radical ration ration of flax seeds. But germination percentage and Radical and plumule dry weight significant increased only in hydropriming treat. Hydropriming and osmopriming could not be used to improved germination under saline and drought stress. But has more tolerance in salinity and drought stress in flax by less reduce in Radical and plumule length under saline and drought stress.

Biochemical and Multiplex PCR Analysis of Toxic Crystal Proteins to Determine Genes in Bacillus thuringiensis Mutants

The Egyptian Bacillus thuringiensis isolate (M5) produce crystal proteins that is toxic against insects was irradiated with UV light to induce mutants. Upon testing 10 of the resulting mutants for their toxicity against cotton leafworm larvae, the three mutants 62, 64 and 85 proved to be the most toxic ones. Upon testing these mutants along with their parental isolate by SDS-PAGE analysis of spores-crystals proteins as well as vegetative cells proteins, new induced bands appeared in the three mutants by UV radiation and also they showed disappearance of some other bands as compared with the wild type isolate. Multiplex PCR technique, with five sets of specific primers, was used to detect the three types of cryI genes cryIAa, cryIAb and cryIAc. Results showed that these three genes exist, as distinctive bands, in the wild type isolate (M5) as well as in mutants 62 and 85, while the mutant 64 had two distinctive bands of cryIAb and cryIAc genes, and a faint band of cryI Aa gene. Finally, these results revealed that mutant 62 is considered as the promising mutant since it is UV resistant, highly toxic against Spodoptera littoralis and active against a wide range of Lepidopteran insects.

Probabilistic Bayesian Framework for Infrared Face Recognition

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Tuning of Power System Stabilizers in a Multi- Machine Power System using C-Catfish PSO

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The proposed algorithm is evaluated on a two-area, 4- machines system. The robustness of the proposed algorithm is verified on this system under different operating conditions and applying a three-phase fault. The nonlinear time-domain simulation results and some performance indices show the effectiveness of the proposed controller in damping power system oscillations and this novel optimization algorithm is compared with particle swarm optimization (PSO).