Opto-Mechanical Characterization of Aspheric Lenses from the Hybrid Method

Aspheric optical components are an alternative to the use of conventional lenses in the implementation of imaging systems for the visible range. Spherical lenses are capable of producing aberrations. Therefore, they are not able to focus all the light into a single point. Instead, aspherical lenses correct aberrations and provide better resolution even with compact lenses incorporating a small number of lenses. Metrology of these components is very difficult especially when the resolution requirements increase and insufficient or complexity of conventional tools requires the development of specific approaches to characterization. This work is part of the problem existed because the objectives are the study and comparison of different methods used to measure surface rays hybrid aspherical lenses.

Software to Encrypt Messages Using Public-Key Cryptography

In this paper the development of a software to encrypt messages with asymmetric cryptography is presented. In particular, is used the RSA (Rivest, Shamir and Adleman) algorithm to encrypt alphanumeric information. The software allows to generate different public keys from two prime numbers provided by the user, the user must then select a public-key to generate the corresponding private-key. To encrypt the information, the user must provide the public-key of the recipient as well as the message to be encrypted. The generated ciphertext can be sent through an insecure channel, so that would be very difficult to be interpreted by an intruder or attacker. At the end of the communication, the recipient can decrypt the original message if provide his/her public-key and his/her corresponding private-key.

Effect of Corrosion on Hydrocarbon Pipelines

The demand of hydrocarbons has increased the construction of pipelines and the protection of the physical and mechanical integrity of the already existing infrastructure. Corrosion is the main reason of failures in the pipeline and it is mostly produced by acid (HCOOCH3). In this basis, a CFD code was used, in order to study the corrosion of internal wall of hydrocarbons pipeline. In this situation, the corrosion phenomenon shows a growing deposit, which causes defect damages (welding or fabrication) at diverse positions along the pipeline. The solution of the pipeline corrosion is based on the diminution of the Naphthenic acid.

Investigation of Tearing in Hydroforming Process with Analytical Equations and Finite Element Method

Today, Hydroforming technology provides an attractive alternative to conventional matched die forming, especially for cost-sensitive, lower volume production, and for parts with irregular contours. In this study the critical fluid pressures which lead to rupture in the workpiece has been investigated by theoretical and finite element methods. The axisymmetric analysis was developed to investigate the tearing phenomenon in cylindrical Hydroforming Deep Drawing (HDD). By use of obtained equations the effect of anisotropy, drawing ratio, sheet thickness and strain hardening exponent on tearing diagram were investigated.

Effect of Commercial or Bovine Yeasts on the Performance and Blood Variables of Broiler Chickens Intoxicated with Aflatoxins

The effects of commercial or bovine yeasts on the performance and blood variables of broiler chickens intoxicated with aflatoxin were investigated in broilers. Four hundred eighty broilers (Arbor Acres; 3-wk-old) were randomly assigned to 4 groups. Each group (120 broiler chickens) was further randomly divided into 6 replicates of 20 chickens. The treatments were control diet without additives (treatment 1), 250 ppb AFB1 (treatment 2), commercial yeast, Saccharomyces cerevisiae, (CY 2.5 x 107 CFU/g) + 250 ppb AFB1 (treatment 3) and bovine yeast, Saccharomyces cerevisiae, (BY 2.5 x 107 CFU/g + 250 ppb AFB1 (treatment 4). Complete randomized design (CRD) was used in the experiment. Feed consumption and body weight were recorded at every five-day period. On day 42, carcass compositions were determined from 30 birds per treatment. While chicks were sacrificed, 3-4 ml blood sample was taken and stored frozen at (-20°C) for serum chemical analysis to determine effects of consumption of diets on blood chemistry (total protein, albumin, glucose, urea, cholesterol and triglycerides). There were no significant differences in ADFI among the treatments(P>0.05). However, BWG, FCR and mortality were highly significantly different (P

SIP Authentication Scheme using ECDH

SIP (Session Initiation Protocol), using HTML based call control messaging which is quite simple and efficient, is being replaced for VoIP networks recently. As for authentication and authorization purposes there are many approaches and considerations for securing SIP to eliminate forgery on the integrity of SIP messages. On the other hand Elliptic Curve Cryptography has significant advantages like smaller key sizes, faster computations on behalf of other Public Key Cryptography (PKC) systems that obtain data transmission more secure and efficient. In this work a new approach is proposed for secure SIP authentication by using a public key exchange mechanism using ECC. Total execution times and memory requirements of proposed scheme have been improved in comparison with non-elliptic approaches by adopting elliptic-based key exchange mechanism.

Energy Map Construction using Adaptive Alpha Grey Prediction Model in WSNs

Wireless Sensor Networks can be used to monitor the physical phenomenon in such areas where human approach is nearly impossible. Hence the limited power supply is the major constraint of the WSNs due to the use of non-rechargeable batteries in sensor nodes. A lot of researches are going on to reduce the energy consumption of sensor nodes. Energy map can be used with clustering, data dissemination and routing techniques to reduce the power consumption of WSNs. Energy map can also be used to know which part of the network is going to fail in near future. In this paper, Energy map is constructed using the prediction based approach. Adaptive alpha GM(1,1) model is used as the prediction model. GM(1,1) is being used worldwide in many applications for predicting future values of time series using some past values due to its high computational efficiency and accuracy.

Simulation of Propagation of Cos-Gaussian Beam in Strongly Nonlocal Nonlinear Media Using Paraxial Group Transformation

In this paper, propagation of cos-Gaussian beam in strongly nonlocal nonlinear media has been stimulated by using paraxial group transformation. At first, cos-Gaussian beam, nonlocal nonlinear media, critical power, transfer matrix, and paraxial group transformation are introduced. Then, the propagation of the cos-Gaussian beam in strongly nonlocal nonlinear media is simulated. Results show that beam propagation has periodic structure during self-focusing effect in this case. However, this simple method can be used for investigation of propagation of kinds of beams in ABCD optical media.

A Video-based Algorithm for Moving Objects Detection at Signalized Intersection

Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Use of Time-Depend Effects for Mixing and Separation of the Two-Phase Flows

The paper shows some ability to manage two-phase flows arising from the use of unsteady effects. In one case, we consider the condition of fragmentation of the interface between the two components leads to the intensification of mixing. The problem is solved when the temporal and linear scale are small for the appearance of the developed mixing layer. Showing that exist such conditions for unsteady flow velocity at the surface of the channel, which will lead to the creation and fragmentation of vortices at Re numbers of order unity. Also showing that the Re is not a criterion of similarity for this type of flows, but we can introduce a criterion that depends on both the Re, and the frequency splitting of the vortices. It turned out that feature of this situation is that streamlines behave stable, and if we analyze the behavior of the interface between the components it satisfies all the properties of unstable flows. The other problem we consider the behavior of solid impurities in the extensive system of channels. Simulated unsteady periodic flow modeled breaths. Consider the behavior of the particles along the trajectories. It is shown that, depending on the mass and diameter of the particles, they can be collected in a caustic on the channel walls, stop in a certain place or fly back. Of interest is the distribution of particle velocity in frequency. It turned out that by choosing a behavior of the velocity field of the carrier gas can affect the trajectory of individual particles including force them to fly back.

Proportion and Particle Size Distribution of Fine Aggregates Extracted From the Drained Binder in a Binder Drainage Test

Binder drainage test is widely used to set an upper limit to the design binder content of porous asphalt. However, the presence of high amount of fine particles in the drained binder may affect the accuracy of the test result. This paper presents a study to characterize the composition and particle size distribution of fine particles accumulated in the drained binder. Fine aggregates and filler in the drained binder were extracted using a suitable solvent. Then, wet and dry sieve analysis was carried out to identify the actual composition of the extracted fine aggregates and filler. From the results, almost half of the drained binder consisted of fine aggregates and this significantly affects the accuracy of the design binder content of porous asphalt mix. This simple finding highlights the importance of taking into account the presence of fine aggregates in the calculation of drained binder.

Use of Semantic Networks as Learning Material and Evaluation of the Approach by Students

This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.

Rotation Invariant Face Recognition Based on Hybrid LPT/DCT Features

The recognition of human faces, especially those with different orientations is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation invariant face recognition using Log-Polar Transform and Discrete Cosine Transform combined features. The rotation invariant feature extraction for a given face image involves applying the logpolar transform to eliminate the rotation effect and to produce a row shifted log-polar image. The discrete cosine transform is then applied to eliminate the row shift effect and to generate the low-dimensional feature vector. A PSO-based feature selection algorithm is utilized to search the feature vector space for the optimal feature subset. Evolution is driven by a fitness function defined in terms of maximizing the between-class separation (scatter index). Experimental results, based on the ORL face database using testing data sets for images with different orientations; show that the proposed system outperforms other face recognition methods. The overall recognition rate for the rotated test images being 97%, demonstrating that the extracted feature vector is an effective rotation invariant feature set with minimal set of selected features.

Estimating Shortest Circuit Path Length Complexity

When binary decision diagrams are formed from uniformly distributed Monte Carlo data for a large number of variables, the complexity of the decision diagrams exhibits a predictable relationship to the number of variables and minterms. In the present work, a neural network model has been used to analyze the pattern of shortest path length for larger number of Monte Carlo data points. The neural model shows a strong descriptive power for the ISCAS benchmark data with an RMS error of 0.102 for the shortest path length complexity. Therefore, the model can be considered as a method of predicting path length complexities; this is expected to lead to minimum time complexity of very large-scale integrated circuitries and related computer-aided design tools that use binary decision diagrams.

A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT

Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied to each block. By concatenating the first singular values (SV) of adjacent blocks of the normalized image, a SV block is obtained. DCT is then carried out on the SV blocks to produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency band of a SVD-DCT block by imposing a particular relationship between two pseudo-randomly selected DCT coefficients. An adaptive frequency mask is used to adjust local watermark embedding strength. Watermark extraction involves mainly the inverse process. The watermark extracting method is blind and efficient. Experimental results show that the quality degradation of watermarked image caused by the embedded watermark is visually transparent. Results also show that the proposed scheme is robust against various image processing operations and geometric attacks.

Noise Depressed in a Micro Stepping Motor

An investigation of noise in a micro stepping motor is considered to study in this article. Because of the trend towards higher precision and more and more small 3C (including Computer, Communication and Consumer Electronics) products, the micro stepping motor is frequently used to drive the micro system or the other 3C products. Unfortunately, noise in a micro stepped motor is too large to accept by the customs. To depress the noise of a micro stepped motor, the dynamic characteristics in this system must be studied. In this article, a Visual Basic (VB) computer program speed controlled micro stepped motor in a digital camera is investigated. Karman KD2300-2S non-contract eddy current displacement sensor, probe microphone, and HP 35670A analyzer are employed to analyze the dynamic characteristics of vibration and noise in a motor. The vibration and noise measurement of different type of bearings and different treatment of coils are compared. The rotating components, bearings, coil, etc. of the motor play the important roles in producing vibration and noise. It is found that the noise will be depressed about 3~4 dB and 6~7 dB, when substitutes the copper bearing with plastic one and coats the motor coil with paraffin wax, respectively.

Skew Detection Technique for Binary Document Images based on Hough Transform

Document image processing has become an increasingly important technology in the automation of office documentation tasks. During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithm for layout analysis and character recognition are generally very sensitive to the page skew. Hence, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method is presented for binary document images. The method considered the some selected characters of the text which may be subjected to thinning and Hough transform to estimate skew angle accurately. Several experiments have been conducted on various types of documents such as documents containing English Documents, Journals, Text-Book, Different Languages and Document with different fonts, Documents with different resolutions, to reveal the robustness of the proposed method. The experimental results revealed that the proposed method is accurate compared to the results of well-known existing methods.

Pineapple Maturity Recognition Using RGB Extraction

Pineapples can be classified using an index with seven levels of maturity based on the green and yellow color of the skin. As the pineapple ripens, the skin will change from pale green to a golden or yellowish color. The issues that occur in agriculture nowadays are to do with farmers being unable to distinguish between the indexes of pineapple maturity correctly and effectively. There are several reasons for why farmers cannot properly follow the guideline provide by Federal Agriculture Marketing Authority (FAMA) and one of reason is that due to manual inspection done by experts, there are no specific and universal guidelines to be adopted by farmers due to the different points of view of the experts when sorting the pineapples based on their knowledge and experience. Therefore, an automatic system will help farmers to identify pineapple maturity effectively and will become a universal indicator to farmers.

Face Texture Reconstruction for Illumination Variant Face Recognition

In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.