Search results for: Search Algorithm

Authors: Meiling Yang, Shuguo Xie, Yilong Zhu

Abstract:

Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.

Keywords: Virtual antenna array, DOA, localization, far field.

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Authors: Yayun Hsu, Henry Horng-Shing Lu

Abstract:

This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate crosstalk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds, since biological information is inherently included inside the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: Brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning.

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Authors: Ayman El Ansary, Mohamed Shalaby

Abstract:

The current study describes a multi-objective optimization technique for positioning of houses in a residential neighborhood. The main task is the placement of residential houses in a favorable configuration satisfying a number of objectives. Solving the house layout problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to favorite views). This investigation introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique explores the search space for possible solutions. This study considers two dimensional house planning problems. However, it can be extended to solve three dimensional cases.

Keywords: Evolutionary optimization, Houses planning, Urban modeling, Daylight, Visual Privacy, Residential compounds.

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Authors: Mohammed Ibrahim M, Anupama R.

Abstract:

Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.

Keywords: homogeneity, penumbra, projection histogram, shadow correction

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Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Ruoliang Tang

Abstract:

Heavy biomechanical loads at workplaces may lead to high risks of work-related musculoskeletal disorders (WMSDs). However, there is a lack of investigations on the efficacy of the ergonomic interventions with theoretical frameworks. This study aimed to formulate an Omaha System based remote intervention program on the WMSDs among nurses by systematic literature review, interviews, expert consultation. After screening title and abstract, 11 articles out of the initial search results (i.e., n=1,418) were included, 12 nurses were interviewed, and 10 experts were consulted to review the initial intervention program. Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, (3) revising the on-line training method, (4) editing and proofreading the main text of the initial program, (5) adding quizzes and exercise scales, (6) it was determined that the associated coursework should be announced promptly with multiple follow-up reminders, and (7) removing bodyweight superman exercise, and peaceful/calm meditation. In the end, the final intervention program was developed.

Keywords: Omaha System, nurses, remote intervention, musculoskeletal disease.

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Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar

Abstract:

This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model.

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Authors: Juliana Panova

Abstract:

Severe symptoms, such as dissociation, depersonalization, self-mutilation, suicidal ideations and gestures, are the main reasons for a person to be diagnosed with Borderline Personality Disorder (BPD) and admitted to an inpatient Psychiatric Hospital. However, these symptoms are also indicators of a severe traumatic history as indicated by the extensive research on the topic. Unfortunately patients with such clinical presentation often are treated repeatedly only for their symptomatic behavior, while the main cause for their suffering, the trauma itself, is usually left unaddressed therapeutically. All of the highly structured, replicable, and manualized treatments lack the recognition of the uniqueness of the person and fail to respect his/her rights to experience and react in an idiosyncratic manner. Thus the communicative and adaptive meaning of such symptomatic behavior is missed. Only its pathological side is recognized and subjected to correction and stigmatization, and the message that the person is damaged goods that needs fixing is conveyed once again. However, this time the message would be even more convincing for the victim, because it is sent by mental health providers, who have the credibility to make such a judgment. The result is a revolving door of very expensive hospitalizations for only a temporary and patchy fix. In this way the patients, once victims of abuse and hardship are left invalidated and thus their re-victimization is perpetuated in their search for understanding and help. Keywordsborderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

Keywords: borderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

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Authors: Le-Ren Chang-Chien, Yin-Juin Lin, Chin-Chung Wu

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Utilities use operating reserve for frequency regulation.To ensure that the operating frequency and system security are well maintained, the operating grid codes always specify that the reserve quantity and response rate should meet some prescribed levels. This paper proposes a methodology to evaluate system's contingency reserve for an isolated power network. With the presented algorithm to estimate system's frequency response characteristic, an online allocation of contingency reserve would be feasible to meet the grid codes for contingency operation. Test results from the simulated conditions, and from the actual operating data verify the merits of the proposed methodology to system's frequency control, and security.

Keywords: Contingency, frequency control, operating reserve.

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Authors: Moataz M. Naguib, Hatem Khater, A. Baith Mohamed

Abstract:

MARS is a shared-key (symmetric) block cipher algorithm supporting 128-bit block size and a variable key size of between 128 and 448 bits. MARS has a several rounds of cryptographic core that is designed to take advantage of the powerful results for improving security/performance tradeoff over existing ciphers. In this work, a new function added to improve the ciphering process it is called, Meta-Morphic function. This function use XOR, Rotating, Inverting and No-Operation logical operations before and after encryption process. The aim of these operations is to improve MARS cipher process and makes a high confusion criterion for the Ciphertext.

Keywords: AES, MARS, Metamorphic, Cryptography, Block Cipher.

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Authors: Ibrahim El rube'

Abstract:

In this paper, a method for matching image segments using triangle-based (geometrical) regions is proposed. Triangular regions are formed from triples of vertex points obtained from a keypoint detector (SIFT). However, triangle regions are subject to noise and distortion around the edges and vertices (especially acute angles). Therefore, these triangles are expanded into parallelogramshaped regions. The extracted image segments inherit an important triangle property; the invariance to affine distortion. Given two images, matching corresponding regions is conducted by computing the relative affine matrix, rectifying one of the regions w.r.t. the other one, then calculating the similarity between the reference and rectified region. The experimental tests show the efficiency and robustness of the proposed algorithm against geometrical distortion.

Keywords: Image matching, key point detection, affine invariant, triangle-shaped segments.

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Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: Artificial neural network, back-propagation, tide data, training algorithm.

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Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

Abstract:

We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial Tree Drawing, Real-Time Visualization, Angular Coordinates, Large Trees.

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Authors: Marzieh Dosti, Alireza Nazemi

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In this paper, the telegraph equation is solved numerically by cubic B-spline quasi-interpolation .We obtain the numerical scheme, by using the derivative of the quasi-interpolation to approximate the spatial derivative of the dependent variable and a low order forward difference to approximate the temporal derivative of the dependent variable. The advantage of the resulting scheme is that the algorithm is very simple so it is very easy to implement. The results of numerical experiments are presented, and are compared with analytical solutions by calculating errors L2 and L∞ norms to confirm the good accuracy of the presented scheme.

Keywords: Cubic B-spline, quasi-interpolation, collocation method, second-order hyperbolic telegraph equation.

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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Authors: Nisar Ahmed Memon, Anwar Majid Mirza, S.A.M. Gilani

Abstract:

Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. This paper presents the problem of inaccurate lung segmentation as observed in algorithms presented by researchers working in the area of medical image analysis. The different lung segmentation techniques have been tested using the dataset of 19 patients consisting of a total of 917 images. We obtained datasets of 11 patients from Ackron University, USA and of 8 patients from AGA Khan Medical University, Pakistan. After testing the algorithms against datasets, the deficiencies of each algorithm have been highlighted.

Keywords: Computer Aided Diagnosis (CAD), MathematicalMorphology, Medical Image Analysis, Region Growing, Segmentation, Thresholding,

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Authors: Mitko Veta, Tomislav Kartalov, Zoran Ivanovski

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Organization of video databases is becoming difficult task as the amount of video content increases. Video classification based on the content of videos can significantly increase the speed of tasks such as browsing and searching for a particular video in a database. In this paper, a content-based videos classification system for the classes indoor and outdoor is presented. The system is intended to be used on a mobile platform with modest resources. The algorithm makes use of the temporal redundancy in videos, which allows using an uncomplicated classification model while still achieving reasonable accuracy. The training and evaluation was done on a video database of 443 videos downloaded from a video sharing service. A total accuracy of 87.36% was achieved.

Keywords: Indoor/outdoor, video classification, imageclassification

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Authors: Aurelian Octavian Ciucâ, Ioan Bitir-Istrate, Mircea Scripcariu

Abstract:

The rapidly increasing costs of power line extensions and fossil fuel, combined with the desire to reduce carbon dioxide emissions pushed the development of hybrid power system suited for remote locations, the purpose in mind being that of autonomous local power systems. The paper presents the suggested solution for a “high penetration" hybrid power system, it being determined by the location of the settlement and its “zero policy" on carbon dioxide emissions. The paper focuses on the technical solution and the power flow management algorithm of the system, taking into consideration local conditions of development.

Keywords: Renewable energy, hybrid power system, wind turbine, photovoltaic panels, bio-diesel cogeneration, bio-fuel.

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Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

Abstract:

The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: Auto tuning, balanced robot, closed loop identification, subspace identification.

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Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani

Abstract:

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.

Keywords: Face Detection, Genetic Algorithms, Sparse Feature.

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Authors: E. Inzunza-González, C. Cruz-Hernández, R. M. López-Gutiérrez, E. E. García-Guerrero, L. Cardoza- Avendaño, H. Serrano-Guerrero

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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.

Keywords: Asymmetric cryptography, Prime number, Publickey, Private-key, Software.

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Authors: Yasunori Sugita, Toshinori Yoshikawa, Naoyuki Aikawa

Abstract:

Variable digital filters are useful for various signal processing and communication applications where the frequency characteristics, such as fractional delays and cutoff frequencies, can be varied. In this paper, we propose a design method of variable FIR digital filters with an approximate linear phase characteristic in the passband. The proposed variable FIR filters have some large attenuation in stopband and their large attenuation can be varied by spectrum parameters. In the proposed design method, a quasi-equiripple characteristic can be obtained by using an iterative weighted least square method. The usefulness of the proposed design method is verified through some examples.

Keywords: Weighted Least Squares Approximation, Variable FIR Filters, Low-Delay, Quasi-Equiripple

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Authors: B. M. Mohan, Sanjeeb Kumar Kar

Abstract:

In this paper a unified approach via block-pulse functions (BPFs) or shifted Legendre polynomials (SLPs) is presented to solve the linear-quadratic-Gaussian (LQG) control problem. Also a recursive algorithm is proposed to solve the above problem via BPFs. By using the elegant operational properties of orthogonal functions (BPFs or SLPs) these computationally attractive algorithms are developed. To demonstrate the validity of the proposed approaches a numerical example is included.

Keywords: Linear quadratic Gaussian control, linear quadratic estimator, linear quadratic regulator, time-invariant systems, orthogonal functions, block-pulse functions, shifted legendre polynomials.

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Authors: Norsinnira Zainul Azlan, Hiroshi Yamaura

Abstract:

This paper presents a new adaptive impedance control strategy, based on Function Approximation Technique (FAT) to compensate for unknown non-flat environment shape or time-varying environment location. The target impedance in the force controllable direction is modified by incorporating adaptive compensators and the uncertainties are represented by FAT, allowing the update law to be derived easily. The force error feedback is utilized in the estimation and the accurate knowledge of the environment parameters are not required by the algorithm. It is shown mathematically that the stability of the controller is guaranteed based on Lyapunov theory. Simulation results presented to demonstrate the validity of the proposed controller.

Keywords: Adaptive impedance control, Function Approximation Technique (FAT), impedance control, unknown environment position.

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Authors: Vai Kuong Sin

Abstract:

Non-isothermal stagnation-point flow with consideration of thermal radiation is studied numerically. A set of partial differential equations that governing the fluid flow and energy is converted into a set of ordinary differential equations which is solved by Runge-Kutta method with shooting algorithm. Dimensionless wall temperature gradient and temperature boundary layer thickness for different combinaton of values of Prandtl number Pr and radiation parameter NR are presented graphically. Analyses of results show that the presence of thermal radiation in the stagnation-point flow is to increase the temperature boundary layer thickness and decrease the dimensionless wall temperature gradient.

Keywords: Stagnation-point flow, Similarity solution, Thermal radiation.

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Authors: Shiann-Shiun Jeng, Jia-Ming Chen, Hong-Zong Lin, Chen-Wan Tsung

Abstract:

For cognitive radio networks, there is a major spectrum sensing problem, i.e. dynamic spectrum management. It is an important issue to sense and identify the spectrum holes in cognitive radio networks. The first-order derivative scheme is usually used to detect the edge of the spectrum. In this paper, a novel spectrum sensing technique for cognitive radio is presented. The proposed algorithm offers efficient edge detection. Then, simulation results show the performance of the first-order derivative scheme and the proposed scheme and depict that the proposed scheme obtains better performance than does the first-order derivative scheme.

Keywords: cognitive radio, Spectrum Sensing, wavelet, edgedetection

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Authors: Rooholah Hasanizadeh, Saadan Zokaei

Abstract:

Energy efficient protocol design is the aim of current researches in the area of sensor networks where limited power resources impose energy conservation considerations. In this paper we care for Medium Access Control (MAC) protocols and after an extensive literature review, two adaptive schemes are discussed. Of them, adaptive-rate MACs which were introduced for throughput enhancement show the potency to save energy, even more than adaptive-power schemes. Then we propose an allocation algorithm for getting accurate and reliable results. Through a simulation study we validated our claim and showed the power saving of adaptive-rate protocols.

Keywords: Adaptive-rate, adaptive-power, MAC protocol, energy efficiency, sensor networks.

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Authors: Mamoun F. Abdel-Hafez

Abstract:

In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.

Keywords: Estimation and filtering, Statistical data analysis, Faultdetection and identification.

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Authors: Harsh Vikram Singh, S. P. Singh, Anand Mohan

Abstract:

This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage-s DCT coefficient probability plots, thus making the presence of hidden data statistically undetectable. In addition the proposed method does not compromise on hiding capacity. When compared to the generic block DCT based data-hiding scheme, our method found more robust against a variety of image manipulating attacks such as filtering, blurring, JPEG compression etc.

Keywords: Information Security, Robust Steganography, Steganalysis, Pareto Probability Distribution function.

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Authors: Krishnamoorthy R, Rajavijayalakshmi K, Punidha R

Abstract:

In this paper, a near lossless image coding scheme based on Orthogonal Polynomials Transform (OPT) has been presented. The polynomial operators and polynomials basis operators are obtained from set of orthogonal polynomials functions for the proposed transform coding. The image is partitioned into a number of distinct square blocks and the proposed transform coding is applied to each of these individually. After applying the proposed transform coding, the transformed coefficients are rearranged into a sub-band structure. The Embedded Zerotree (EZ) coding algorithm is then employed to quantize the coefficients. The proposed transform is implemented for various block sizes and the performance is compared with existing Discrete Cosine Transform (DCT) transform coding scheme.

Keywords: Near-lossless Coding, Orthogonal Polynomials Transform, Embedded Zerotree Coding

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Authors: M.H. Djavareshkian, A. Esmaeli

Abstract:

A pressure-based implicit procedure to solve Navier- Stokes equations on a nonorthogonal mesh with collocated finite volume formulation is used to simulate flow around the smart and conventional flaps of spoiler under the ground effect. Cantilever beam with uniformly varying load with roller support at the free end is considered for smart flaps. The boundedness criteria for this procedure are determined from a Normalized Variable diagram (NVD) scheme. The procedure incorporates es the k -ε eddyviscosity turbulence model. The method is first validated against experimental data. Then, the algorithm is applied for turbulent aerodynamic flows around a spoiler section with smart and conventional flaps for different attack angle, flap angle and ground clearance where the results of two flaps are compared.

Keywords: Smart spoiler, Ground Effect, Flap, Aerodynamic coefficients, Race car.

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