Characteristics of Maximum Gliding Endurance Path for High-Altitude Solar UAVs

Gliding during night without electric power is an efficient method to enhance endurance performance of solar aircrafts. The properties of maximum gliding endurance path are studied in this paper. The problem is formulated as an optimization problem about maximum endurance can be sustained by certain potential energy storage with dynamic equations and aerodynamic parameter constrains. The optimal gliding path is generated based on gauss pseudo-spectral method. In order to analyse relationship between altitude, velocity of solar UAVs and its endurance performance, the lift coefficient in interval of [0.4, 1.2] and flight envelopes between 0~30km are investigated. Results show that broad range of lift coefficient can improve solar aircrafts- long endurance performance, and it is possible for a solar aircraft to achieve the aim of long endurance during whole night just by potential energy storage.

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.

An Improved Switching Median filter for Uniformly Distributed Impulse Noise Removal

The performance of an image filtering system depends on its ability to detect the presence of noisy pixels in the image. Most of the impulse detection schemes assume the presence of salt and pepper noise in the images and do not work satisfactorily in case of uniformly distributed impulse noise. In this paper, a new algorithm is presented to improve the performance of switching median filter in detection of uniformly distributed impulse noise. The performance of the proposed scheme is demonstrated by the results obtained from computer simulations on various images.

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.

Power and Delay Optimized Graph Representation for Combinational Logic Circuits

Structural representation and technology mapping of a Boolean function is an important problem in the design of nonregenerative digital logic circuits (also called combinational logic circuits). Library aware function manipulation offers a solution to this problem. Compact multi-level representation of binary networks, based on simple circuit structures, such as AND-Inverter Graphs (AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter Graphs, Reduced Boolean Circuits [8] does exist in literature. In this work, we discuss a novel and efficient graph realization for combinational logic circuits, represented using a NAND-NOR-Inverter Graph (NNIG), which is composed of only two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells. The networks are constructed on the basis of irredundant disjunctive and conjunctive normal forms, after factoring, comprising terms with minimum support. Construction of a NNIG for a non-regenerative function in normal form would be straightforward, whereas for the complementary phase, it would be developed by considering a virtual instance of the function. However, the choice of best NNIG for a given function would be based upon literal count, cell count and DAG node count of the implementation at the technology independent stage. In case of a tie, the final decision would be made after extracting the physical design parameters. We have considered AIG representation for reduced disjunctive normal form and the best of OIG/AOG/AOIG for the minimized conjunctive normal forms. This is necessitated due to the nature of certain functions, such as Achilles- heel functions. NNIGs are found to exhibit 3.97% lesser node count compared to AIGs and OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells than AIGs and OIG/AOG/AOIGs for the various samples considered. We compare the power efficiency and delay improvement achieved by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for various case studies. In comparison with functionally equivalent, irredundant and compact AIGs, NNIGs report mean savings in power and delay of 43.71% and 25.85% respectively, after technology mapping with a 0.35 micron TSMC CMOS process. For a comparison with OIG/AOG/AOIGs, NNIGs demonstrate average savings in power and delay by 47.51% and 24.83%. With respect to device count needed for implementation with static CMOS logic style, NNIGs utilize 37.85% and 33.95% lesser transistors than their AIG and OIG/AOG/AOIG counterparts.

Risk Assessment of Acrylamide Intake from Roasted Potatoes in Latvia

From food consumption surveys has been found that potato consumption comparing to other European countries is one of the highest. Hence acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine acrylamide content and estimate intake of acrylamide from roasted potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile, and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. Time and temperature (210 ± 5°C) was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. estimated intake of acrylamide ranges from 0.012 to 0.496μgkg-1 BW per day.

Face Recognition Using Double Dimension Reduction

In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.

An Approach of Quantum Steganography through Special SSCE Code

Encrypted messages sending frequently draws the attention of third parties, perhaps causing attempts to break and reveal the original messages. Steganography is introduced to hide the existence of the communication by concealing a secret message in an appropriate carrier like text, image, audio or video. Quantum steganography where the sender (Alice) embeds her steganographic information into the cover and sends it to the receiver (Bob) over a communication channel. Alice and Bob share an algorithm and hide quantum information in the cover. An eavesdropper (Eve) without access to the algorithm can-t find out the existence of the quantum message. In this paper, a text quantum steganography technique based on the use of indefinite articles (a) or (an) in conjunction with the nonspecific or non-particular nouns in English language and quantum gate truth table have been proposed. The authors also introduced a new code representation technique (SSCE - Secret Steganography Code for Embedding) at both ends in order to achieve high level of security. Before the embedding operation each character of the secret message has been converted to SSCE Value and then embeds to cover text. Finally stego text is formed and transmits to the receiver side. At the receiver side different reverse operation has been carried out to get back the original information.

Effect of Drought Stress on Nitrogen Components in Corn

An attempt was made to study of nitrogen components response of corn (Zea mays L.) to drought stress. A farm research was done in RCBD as split-plot with four replications in Khorramabad, west Iran. Drought stress levels as irrigation regimes after 75 (control), 100, and 120 (stress) mm cumulative evaporation were in main plots, and four seed corn varieties include 500 (medium maturity), 647, 700, and 704 (long maturity) were as subplots. Soluble protein, nitrate and proline amino acid were measured in shoot and root at flowering stage, and grain yield was measured in harvesting stage. As the drought progressed, the amount of nitrate and proline followed an increasing trend, but soluble protein decreased in shoot and root. The highest amount of nitrate and proline was observed in longer maturity varieties than shorter ones, but decrease yield of long maturity varieties was higher than medium maturity varieties in drought condition, because of long duration of stress.

The Influence of Some Polyphenols on Human Erythrocytes Glutathione S-Transferase Activity

Glutathione S-transferase was purified from human erythrocytes and effects of some polyphenols were investigated on the enzyme activity. The purification procedure was performed on Glutathione-Agarose affinity chromatography after preparation of erythrocytes hemolysate with a yield of 81%. The purified enzyme showed a single band on the SDS-PAGE. The effects of some poliphenolic compounds such as catechin, dopa, dopamine, progallol and catechol were examined on the in vitro GST activity. Catechin was determined to be inhibitor for the enzyme, but others were not effective on the enzyme as inhibitors or activators. IC50 value -the concentration of inhibitor which reduces enzyme activity by 50%- was estimated to be 10 mM. Ki constants were also calculated as 6.38 ± 0,70 mM with GSH substrate, and 3.86 ± 0,78 mM with CDNB substrate using the equations of graphs for the inhibitor, and its inhibition type was determined as non-competitive.

Steady State Thermal Analysis and Design of a Cooling System in an AFPM Motor

In this paper, the steady-state temperature of a sample 500 KW two rotor one stator Non-slotted axial flux permanent magnet motor is calculated using the finite element simulator software package. Due to the high temperature in various parts of the machine, especially at stator winding, a cooling system is designed for the motor and the temperature is recalculated. The results show that the temperature obtained for the parts is within the permissible range.

Antioxidant and Aِntimicrobial Properties of Peptides as Bioactive Components in Beef Burger

Dried soy protein hydrolysate powder was added to the burger in order to enhance the oxidative stability as well as decreases the microbial spoilage. The soybean bioactive compounds (soy protein hydrolysate) as antioxidant and antimicrobial were added at level of 1, 2 and 3 %.Chemical analysis and physical properties were affected by protein hydrolysate addition. The TBA values were significantly affected (P < 0.05) by the storage period and the level of soy protein hydrolysate. All the tested soybean protein hydrolysate additives showed strong antioxidant properties. Samples of soybean protein hydrolysate showed the lowest (P < 0.05) TBA values at each time of storage. The counts of all determined microbiological indicators were significantly (P < 0.05) affected by the addition of the soybean protein hydrolysate. Decreasing trends of different extent were also observed in samples of the treatments for total viable counts, Coliform, Staphylococcus aureus, yeast and molds. Storage period was being significantly (P < 0.05) affected on microbial counts in all samples Staphylococcus aureus were the most sensitive microbe followed by Coliform group of the sample containing protein hydrolysate, while molds and yeast count showed a decreasing trend but not significant (P < 0.05) until the end of the storage period compared with control sample. Sensory attributes were also performed, added protein hydrolysate exhibits beany flavor which was clear about samples of 3% protein hydrolysate.

Low Voltage High Gain Linear Class AB CMOS OTA with DC Level Input Stage

This paper presents a low-voltage low-power differential linear transconductor with near rail-to-rail input swing. Based on the current-mirror OTA topology, the proposed transconductor combines the Flipped Voltage Follower (FVF) technique to linearize the transconductor behavior that leads to class- AB linear operation and the virtual transistor technique to lower the effective threshold voltages of the transistors which offers an advantage in terms of low supply requirement. Design of the OTA has been discussed. It operates at supply voltages of about ±0.8V. Simulation results for 0.18μm TSMC CMOS technology show a good input range of 1Vpp with a high DC gain of 81.53dB and a total harmonic distortion of -40dB at 1MHz for an input of 1Vpp. The main aim of this paper is to present and compare new OTA design with high transconductance, which has a potential to be used in low voltage applications.

Intrapreneurship as a Unique Competitive Advantage

Intrapreneurship, a term used to describe entrepreneurship within existing organizations, has been acknowledged in international literature and practice as a vital element of economic and organizational growth, success and competitiveness and can be considered as a unique competitive advantage. The purpose of the paper is, first, to provide a comprehensive analysis of the concept of intrapreneurship, and, second, to highlight the need for a different approach in the research on the field of intrapreneurship. Concluding, the paper suggests directions for future research.

Limiting Fiber Extensibility as Parameter for Damage in Venous Wall

An inflation–extension test with human vena cava inferior was performed with the aim to fit a material model. The vein was modeled as a thick–walled tube loaded by internal pressure and axial force. The material was assumed to be an incompressible hyperelastic fiber reinforced continuum. Fibers are supposed to be arranged in two families of anti–symmetric helices. Considered anisotropy corresponds to local orthotropy. Used strain energy density function was based on a concept of limiting strain extensibility. The pressurization was comprised by four pre–cycles under physiological venous loading (0 – 4kPa) and four cycles under nonphysiological loading (0 – 21kPa). Each overloading cycle was performed with different value of axial weight. Overloading data were used in regression analysis to fit material model. Considered model did not fit experimental data so good. Especially predictions of axial force failed. It was hypothesized that due to nonphysiological values of loading pressure and different values of axial weight the material was not preconditioned enough and some damage occurred inside the wall. A limiting fiber extensibility parameter Jm was assumed to be in relation to supposed damage. Each of overloading cycles was fitted separately with different values of Jm. Other parameters were held the same. This approach turned out to be successful. Variable value of Jm can describe changes in the axial force – axial stretch response and satisfy pressure – radius dependence simultaneously.

Lattice Boltzmann Simulation of Binary Mixture Diffusion Using Modern Graphics Processors

A highly optimized implementation of binary mixture diffusion with no initial bulk velocity on graphics processors is presented. The lattice Boltzmann model is employed for simulating the binary diffusion of oxygen and nitrogen into each other with different initial concentration distributions. Simulations have been performed using the latest proposed lattice Boltzmann model that satisfies both the indifferentiability principle and the H-theorem for multi-component gas mixtures. Contemporary numerical optimization techniques such as memory alignment and increasing the multiprocessor occupancy are exploited along with some novel optimization strategies to enhance the computational performance on graphics processors using the C for CUDA programming language. Speedup of more than two orders of magnitude over single-core processors is achieved on a variety of Graphical Processing Unit (GPU) devices ranging from conventional graphics cards to advanced, high-end GPUs, while the numerical results are in excellent agreement with the available analytical and numerical data in the literature.

Combined Feature Based Hyperspectral Image Classification Technique Using Support Vector Machines

A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Influence of PLA Film Packaging on the Shelf Life of Soft Cheese Kleo

Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Soft cheese Kleo produced in Latvia was packed in a biodegradable PLA without barrierproperties and VC999 BioPack lidding film PLA, coated with a barrier of pure silicon oxide (SiOx) and in combination with modified atmosphere (MAP) the influence on the shelf life was investigated and compared with some conventional (OPP, PE/PA, PE/OPA and Multibarrier 60) polymer film impact. Modified atmosphere consisted of carbon dioxide CO2 (E 290) 30% and nitrogen N2 (E 941) 70%. The analyzable samples were stored at the temperature of +4.0±0.5 °C up to 32 days- and analyzed before packaging and in the 0, 5th, 11th, 15th, 18th, 22nd, 25th, 29th and 32nd day of storage. The shelf life was extended along to 32 days, good outside appearance and lactic acid aroma was observed.

On the Use of Image Processing Techniques for the Estimation of the Porosity of Textile Fabrics

This paper presents a novel approach to assessing textile porosity by the application of the image analysis techniques. The images of different types of sample fabrics, taken through a microscope when the fabric is placed over a constant light source,transfer the problem into the image analysis domain. Indeed, porosity can thus be expressed in terms of a brightness percentage index calculated on the digital microscope image. Furthermore, it is meaningful to compare the brightness percentage index with the air permeability and the tightness indices of each fabric type. We have experimentally shown that there exists an approximately linear relation between brightness percentage and air permeability indices.

Automatic Segmentation of Lung Areas in Magnetic Resonance Images

Segmenting the lungs in medical images is a challenging and important task for many applications. In particular, automatic segmentation of lung cavities from multiple magnetic resonance (MR) images is very useful for oncological applications such as radiotherapy treatment planning. However, distinguishing of the lung areas is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries. In this paper, we address lung segmentation problem from pulmonary magnetic resonance images and propose an automated method based on a robust regionaided geometric snake with a modified diffused region force into the standard geometric model definition. The extra region force gives the snake a global complementary view of the lung boundary information within the image which along with the local gradient flow, helps detect fuzzy boundaries. The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.