Neural Network Based Approach for Face Detection cum Face Recognition

Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Influence of Axial Magnetic Field on the Electrical Breakdown and Secondary Electron Emission in Plane-Parallel Plasma Discharge

The influence of axial magnetic field (B=0.48 T) on the variation of ionization efficiency coefficient h and secondary electron emission coefficient g with respect to reduced electric field E/P is studied at a new range of plane-parallel electrode spacing (0< d< 20 cm) and different nitrogen working pressure between 0.5-20 Pa. The axial magnetic field is produced from an inductive copper coil of radius 5.6 cm. The experimental data of breakdown voltage is adopted to estimate the mean Paschen curves at different working features. The secondary electron emission coefficient is calculated from the mean Paschen curve and used to determine the minimum breakdown voltage. A reduction of discharge voltage of about 25% is investigated by the applied of axial magnetic field. At high interelectrode spacing, the effect of axial magnetic field becomes more significant for the obtained values of h but it was less for the values of g.

Response of Wax Apple Cultivars by Applied S-Girdling on Fruit Development and Fruit Quality

The study was carried out to evaluated effect of S-gridling on fruit growth and quality of wax apple. The study was laid in Random completed block design with four replicated. Four treatment were applied as follows: S-girdling, fruit thinning plus bagging with 2,4-D sprayed, fruit thinning plus bagging and the control treatment. 2,4D was sprayed at the small bud and petal fall stage. Girdling was applied three week before flowering. The effect of all treatments on fruit growth was measured weekly. Number of flower, fruit set, fruit drop, fruit crack, and fruit quality were recorded. The result indicated that S-girdling, 2,4D application produced the lowest bud drop, fruit drop compared to untreated control. S-girdling improved faster fruit growth producing the best final fruit length and diameter compared to untreated control. S-girdling also markedly enhanced fruit set, fruit weight, and total soluble solid, reduced fruit crack, titratable acidity. On the other hand, it was noticed that with 2,4-D application also increased the fruit growth rate, improved physiological and biochemical characters of fruit than control treatment. It was concluded that S-girdling was recommended as the industry norm to increase fruit set, fruit quality in wax apple. 2,4D application had a distinctive and significant effect on most of the fruit quality characteristics assessed.

Survivability of Verhulst-free Populations under Mutation Accumulation

Stable nonzero populations without random deaths caused by the Verhulst factor (Verhulst-free) are a rarity. Majority either grow without bounds or die of excessive harmful mutations. To delay the accumulation of bad genes or diseases, a new environmental parameter Γ is introduced in the simulation. Current results demonstrate that stability may be achieved by setting Γ = 0.1. These steady states approach a maximum size that scales inversely with reproduction age.

A Stereo Vision System for Top View Book Scanners

This paper proposes a novel stereo vision technique for top view book scanners which provide us with dense 3d point clouds of page surfaces. This is a precondition to dewarp bound volumes independent of 2d information on the page. Our method is based on algorithms, which normally require the projection of pattern sequences with structured light. We use image sequences of the moving stripe lighting of the top view scanner instead of an additional light projection. Thus the stereo vision setup is simplified without losing measurement accuracy. Furthermore we improve a surface model dewarping method through introducing a difference vector based on real measurements. Although our proposed method is hardly expensive neither in calculation time nor in hardware requirements we present good dewarping results even for difficult examples.

Development and Assessment of Measuring/Rehabilitation Device for Myelopathy Patients with Lower Extremity Function

Disordered function of maniphalanx and difficulty with ambulation will occur insofar as a human has a failure in the spinal marrow. Cervical spondylotic myelopathy as one of the myelopathy emanates from not only external factors but also increased age. In addition, the diacrisis is difficult since cervical spondylotic myelopathy is evaluated by a doctor-s neurological remark and imaging findings. As a quantitative method for measuring the degree of disability, hand-operated triangle step test (for short, TST) has formulated. In this research, a full automatic triangle step counter apparatus is designed and developed to measure the degree of disability in an accurate fashion according to the principle of TST. The step counter apparatus whose shape is a low triangle pole displays the number of stepping upon each corner. Furthermore, the apparatus has two modes of operation. Namely, one is for measuring the degree of disability and the other for rehabilitation exercise. In terms of usefulness, clinical practice should be executed before too long.

Real-Time Physics Simulation Packages: An Evaluation Study

This paper includes a review of three physics simulation packages that can be used to provide researchers with a virtual ground for modeling, implementing and simulating complex models, as well as testing their control methods with less cost and time of development. The inverted pendulum model was used as a test bed for comparing ODE, DANCE and Webots, while Linear State Feedback was used to control its behavior. The packages were compared with respect to model creation, solving systems of differential equation, data storage, setting system variables, control the experiment and ease of use. The purpose of this paper is to give an overview about our experience with these environments and to demonstrate some of the benefits and drawbacks involved in practice for each package.

Depressing Turbine-Generator Supersynchronous Torsional Torques by Using Virtual Inertia

Single-pole switching scheme is widely used in the Extra High Voltage system. However, the substantial negativesequence current injected to the turbine-generators imposes the electromagnetic (E/M) torque of double system- frequency components during the dead time (between single-pole clearing and line reclosing). This would induce supersynchronous resonance (SPSR) torque amplifications on low pressure turbine generator blades and even lead to fatigue damage. This paper proposes the design of a mechanical filter (MF) with natural frequency close to double-system frequency. From the simulation results, it is found that such a filter not only successfully damps the resonant effect, but also has the characteristics of feasibility and compact.

Super Resolution Blind Reconstruction of Low Resolution Images using Wavelets based Fusion

Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation.

Exploring the Application of Knowledge Management Factors in Esfahan University's Medical College

In this competitive age, one of the key tools of most successful organizations is knowledge management. Today some organizations measure their current knowledge and use it as an indicator for rating the organization on their reports. Noting that the universities and colleges of medical science have a great role in public health of societies, their access to newest scientific research and the establishment of organizational knowledge management systems is very important. In order to explore the Application of Knowledge Management Factors, a national study was undertaken. The main purpose of this study was to find the rate of the application of knowledge management factors and some ways to establish more application of knowledge management system in Esfahan University-s Medical College (EUMC). Esfahan is the second largest city after Tehran, the capital city of Iran, and the EUMC is the biggest medical college in Esfahan. To rate the application of knowledge management, this study uses a quantitative research methodology based on Probst, Raub and Romhardt model of knowledge management. A group of 267 faculty members and staff of the EUMC were asked via questionnaire. Finding showed that the rate of the application of knowledge management factors in EUMC have been lower than average. As a result, an interview with ten faculty members conducted to find the guidelines to establish more applications of knowledge management system in EUMC.

Simulated Annealing Algorithm for Data Aggregation Trees in Wireless Sensor Networks and Comparison with Genetic Algorithm

In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.

Detection of Oxidative Stress Induced by Mobile Phone Radiation in Tissues of Mice using 8-Oxo-7, 8-Dihydro-2'-Deoxyguanosine as a Biomarker

We investigated oxidative DNA damage caused by radio frequency radiation using 8-oxo-7, 8-dihydro-2'- deoxyguanosine (8-oxodG) generated in mice tissues after exposure to 900 MHz mobile phone radio frequency in three independent experiments. The RF was generated by a Global System for Mobile Communication (GSM) signal generator. The radio frequency field was adjusted to 25 V/m. The whole body specific absorption rate (SAR) was 1.0 W/kg. Animals were exposed to this field for 30 min daily for 30 days. 24 h post-exposure, blood serum, brain and spleen were removed and DNA was isolated. Enzyme-linked immunosorbent assay (ELISA) was used to measure 8-oxodG concentration. All animals survived the whole experimental period. The body weight of animals did not change significantly at the end of the experiment. No statistically significant differences observed in the levels of oxidative stress. Our results are not in favor of the hypothesis that 900 MHz RF induces oxidative damage.

Image Compression with Back-Propagation Neural Network using Cumulative Distribution Function

Image Compression using Artificial Neural Networks is a topic where research is being carried out in various directions towards achieving a generalized and economical network. Feedforward Networks using Back propagation Algorithm adopting the method of steepest descent for error minimization is popular and widely adopted and is directly applied to image compression. Various research works are directed towards achieving quick convergence of the network without loss of quality of the restored image. In general the images used for compression are of different types like dark image, high intensity image etc. When these images are compressed using Back-propagation Network, it takes longer time to converge. The reason for this is, the given image may contain a number of distinct gray levels with narrow difference with their neighborhood pixels. If the gray levels of the pixels in an image and their neighbors are mapped in such a way that the difference in the gray levels of the neighbors with the pixel is minimum, then compression ratio as well as the convergence of the network can be improved. To achieve this, a Cumulative distribution function is estimated for the image and it is used to map the image pixels. When the mapped image pixels are used, the Back-propagation Neural Network yields high compression ratio as well as it converges quickly.

A Local Statistics Based Region Growing Segmentation Method for Ultrasound Medical Images

This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are consisting of the homogeneity and similarity bounds according to the kernel size. The shape and size of the growing regions depend on this look up table entries. The algorithms are implemented by using connected seeded region growing procedure where each pixel is taken as seed point. The region merging after the region growing also suppresses the high frequency artifacts. The updated merged regions produce the output in formed of segmented image. This algorithm produces the results that are less sensitive to the pixel location and it also allows a segmentation of the accurate homogeneous regions.

Experimental Evaluation of Drilling Damage on the Strength of Cores Extracted from RC Buildings

Concrete strength evaluated from compression tests on cores is affected by several factors causing differences from the in-situ strength at the location from which the core specimen was extracted. Among the factors, there is the damage possibly occurring during the drilling phase that generally leads to underestimate the actual in-situ strength. In order to quantify this effect, in this study two wide datasets have been examined, including: (i) about 500 core specimens extracted from Reinforced Concrete existing structures, and (ii) about 600 cube specimens taken during the construction of new structures in the framework of routine acceptance control. The two experimental datasets have been compared in terms of compression strength and specific weight values, accounting for the main factors affecting a concrete property, that is type and amount of cement, aggregates' grading, type and maximum size of aggregates, water/cement ratio, placing and curing modality, concrete age. The results show that the magnitude of the strength reduction due to drilling damage is strongly affected by the actual properties of concrete, being inversely proportional to its strength. Therefore, the application of a single value of the correction coefficient, as generally suggested in the technical literature and in structural codes, appears inappropriate. A set of values of the drilling damage coefficient is suggested as a function of the strength obtained from compressive tests on cores.

Nonlinear Fuzzy Tracking Real-time-based Control of Drying Parameters

The highly nonlinear characteristics of drying processes have prompted researchers to seek new nonlinear control solutions. However, the relation between the implementation complexity, on-line processing complexity, reliability control structure and controller-s performance is not well established. The present paper proposes high performance nonlinear fuzzy controllers for a real-time operation of a drying machine, being developed under a consistent match between those issues. A PCI-6025E data acquisition device from National Instruments® was used, and the control system was fully designed with MATLAB® / SIMULINK language. Drying parameters, namely relative humidity and temperature, were controlled through MIMOs Hybrid Bang-bang+PI (BPI) and Four-dimensional Fuzzy Logic (FLC) real-time-based controllers to perform drying tests on biological materials. The performance of the drying strategies was compared through several criteria, which are reported without controllers- retuning. Controllers- performance analysis has showed much better performance of FLC than BPI controller. The absolute errors were lower than 8,85 % for Fuzzy Logic Controller, about three times lower than the experimental results with BPI control.

Identify Features and Parameters to Devise an Accurate Intrusion Detection System Using Artificial Neural Network

The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.

Active Packaging Influence on Shelf Life Extension of Sliced Wheat Bread

The research object was wheat bread. Experiments were carried out at the Faculty of Food Technology of the Latvia University of Agriculture. An active packaging in combination with modified atmosphere (MAP, CO2 60% and N2 40%) was examined and compared with traditional packaging in air ambiance. Polymer Multibarrier 60, PP and OPP bags were used. Influence of iron based oxygen absorber in sachets of 100 cc obtained from Mitsubishi Gas Chemical Europe Ageless® was tested on the quality during the shelf of wheat bread. Samples of 40±4 g were packaged in polymer pouches (110 mm x 120 mm), hermetically sealed by MULTIVAC C300 vacuum chamber machine, and stored in room temperature +21.0±0.5 °C. The physiochemical properties – weight losses, moisture content, hardness, pH, colour, changes of atmosphere content (CO2 and O2) in headspace of packs, and microbial conditions were analysed before packaging and in the 7th, 14th, 21st and 28th days of storage.

Two New Low Power High Performance Full Adders with Minimum Gates

with increasing circuits- complexity and demand to use portable devices, power consumption is one of the most important parameters these days. Full adders are the basic block of many circuits. Therefore reducing power consumption in full adders is very important in low power circuits. One of the most powerconsuming modules in full adders is XOR/XNOR circuit. This paper presents two new full adders based on two new logic approaches. The proposed logic approaches use one XOR or XNOR gate to implement a full adder cell. Therefore, delay and power will be decreased. Using two new approaches and two XOR and XNOR gates, two new full adders have been implemented in this paper. Simulations are carried out by HSPICE in 0.18μm bulk technology with 1.8V supply voltage. The results show that the ten-transistors proposed full adder has 12% less power consumption and is 5% faster in comparison to MB12T full adder. 9T is more efficient in area and is 24% better than similar 10T full adder in term of power consumption. The main drawback of the proposed circuits is output threshold loss problem.

Application of Whole Genome Amplification Technique for Genotype Analysis of Bovine Embryos

In recent years, there has been an increasing interest toward the use of bovine genotyped embryos for commercial embryo transfer programs. Biopsy of a few cells in morulla stage is essential for preimplantation genetic diagnosis (PGD). Low amount of DNA have limited performing the several molecular analyses within PGD analyses. Whole genome amplification (WGA) promises to eliminate this problem. We evaluated the possibility and performance of an improved primer extension preamplification (I-PEP) method with a range of starting bovine genomic DNA from 1-8 cells into the WGA reaction. We optimized a short and simple I-PEP (ssI-PEP) procedure (~3h). This optimized WGA method was assessed by 6 loci specific polymerase chain reactions (PCRs), included restriction fragments length polymorphism (RFLP). Optimized WGA procedure possesses enough sensitivity for molecular genetic analyses through the few input cells. This is a new era for generating characterized bovine embryos in preimplantation stage.