Search results for: Signal Processing.

Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

Abstract:

In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: Dropwise condensation, textured surface, image processing, watershed.

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Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb

Abstract:

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

Keywords: Autoregressive moving average, coefficients, back propagation, model parameters, neural network, weight.

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Authors: S. K. Khosrowshahi, E. Güler

Abstract:

This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.

Keywords: Image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile.

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Authors: L. Salhi, M. Talbi, A. Cherif

Abstract:

This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standard values thanks to a programmable database. Sounds are collected from normal people and patients, and then classified into two different categories. Speech data base is consists of several pathological and normal voices collected from the national hospital “Rabta-Tunis". Speech processing algorithm is conducted in a supervised mode for discrimination of normal and pathology voices and then for classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Keywords: Formants, Neural Networks, Pathological Voices, Pitch, Wavelet Transform.

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Authors: Malka N. Halgamuge, Toong-Khuan Chan, Priyan Mendis

Abstract:

Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

Keywords: Wireless sensor networks, radio propagation, building monitoring

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Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory organization, parallel processors, serial code, vector processing.

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Authors: Kahil Amar, Boukais Said, Kezmane Ali, Hamizi Mohand, Hannachi Naceur Eddine

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The principle of the seismic performance evaluation methods is to provide a measure of capability for a building or set of buildings to be damaged by an earthquake. The common objective of many of these methods is to supply classification criteria. The purpose of this study is to present a method for assessing the seismic performance of structures, based on Pushover method; we are particularly interested in reinforced concrete frame structures, which represent a significant percentage of damaged structures after a seismic event. The work is based on the characterization of seismic movement of the various earthquake zones in terms of PGA and PGD that is obtained by means of SIMQK_GR and PRISM software and the correlation between the points of performance and the scalar characterizing the earthquakes will developed.

Keywords: Seismic performance, Pushover method, characterization of seismic motion, harmfulness of the seismic signal

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Authors: Miroslav Popelka, Jakub Nožička

Abstract:

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, Real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software.

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Authors: O. S. Omorogiuwa, E. J. Omozusi

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The monitoring of spectrum usage and signal identification, using cognitive radio, is done to identify frequencies that are vacant for reuse. It has been established that ‘internet of things’ device uses secondary frequency which is free, thereby facing the challenge of interference from other users, where some primary frequencies are not being utilised. The design was done by analysing a specific frequency spectrum, checking if all the frequency stations that range from 87.5-108 MHz are presently being used in Benin City, Edo State, Nigeria. From the results, it was noticed that by using Software Defined Radio/Simulink, we were able to identify vacant frequencies in the range of frequency under consideration. Also, we were able to use the significance of energy detection threshold to reuse this vacant frequency spectrum, when the cognitive radio displays a zero output (that is decision H0), meaning that the channel is unoccupied. Hence, the analysis was able to find the spectrum hole and identify how it can be reused.

Keywords: Spectrum, interference, telecommunication, cognitive radio, frequency.

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Authors: Alluri Swaroopa, Lakkakula Venkata Narasimha Prasad

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Alone with fast urbanization in world, traffic control became a big issue in urban construction. Having an efficient and reliable traffic control system is crucial to macro-traffic control. Traffic signal is used to manage conflicting requirement by allocating different sets of mutually compatible traffic movement during distinct time interval. Many approaches have been made proposed to solve this discrete stochastic problem. Recognizing the need to minimize right-of-way impacts while efficiently handling the anticipated high traffic volumes, the proposed alternative system gives effective design. This model allows for increased traffic capacity and reduces delays by eliminating a step in maneuvering through the freeway interchange. The concept proposed in this paper involves construction of bridges and ramps at intersection of four roads to control the vehicular congestion and to prevent traffic breakdown.

Keywords: Bridges, junctions, ramps, urban traffic control.

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Authors: B. O. Ayinmode, I. P. Farai

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The levels of maximum power density of GSM signals in the cities of Lagos, Ibadan and Abuja were studied. Measurements were made with a calibrated hand held spectrum analyzer 200m away from 271 base stations, at 1.2m to the ground level. The maximum GSM 900 signal power density was 139.63μW/m2 in Lagos, 162.49μW/m2 in Ibadan and 5411.26μW/m2 in Abuja. Also, the maximum GSM 1800 signal power density was 296.82μW/m2 in Lagos, 116.82μW/m2 in Ibadan and 1263.00μW/m2 in Abuja. The level of power density of GSM 900 and GSM 1800 signals in the cities of Lagos, Ibadan and Abuja are far less than the recommended value of 4.5W/m2 for GSM 900 and 9.0 W/m2 for GSM 1800 by the ICNRP guideline. It can be concluded that exposure to GSM signals in these cities cannot contribute to the health detriments caused by thermal effects of radiofrequency radiation.

Keywords: Radiofrequency, power density, radiation exposure, base stations (BTS).

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: Computed tomography, enhancement techniques, increasing contrast, PSNR and MSE.

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Authors: Jyh-Da Wei, Hsin-Chen Tsai

Abstract:

This work presents a novel means of extracting fixedlength parameters from voice signals, such that words can be recognized in linear time. The power and the zero crossing rate are first calculated segment by segment from a voice signal; by doing so, two feature sequences are generated. We then construct an FIR system across these two sequences. The parameters of this FIR system, used as the input of a multilayer proceptron recognizer, can be derived by recursive LSE (least-square estimation), implying that the complexity of overall process is linear to the signal size. In the second part of this work, we introduce a weighting factor λ to emphasize recent input; therefore, we can further recognize continuous speech signals. Experiments employ the voice signals of numbers, from zero to nine, spoken in Mandarin Chinese. The proposed method is verified to recognize voice signals efficiently and accurately.

Keywords: Speech Recognition, FIR system, Recursive LSE, Multilayer Perceptron

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Authors: S. Divya Gnanarathinam, S. Sundaramurthy

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The tremendous increase in the population of the world creates the immediate need for the energy resources. All the people in the world need the sustainable energy resources which have low costs. Solar energy is appraised as one of the main energy resources in warm countries. The areas in the west of India like Rajasthan, Gujarat, etc. are immensely rich in solar energy resources. This paper deals with the development of dual axis solar tracker using Arduino board. Depending on the astronomical estimates of the sun from the GPS and sensor image processing outcomes, a methodology is proposed to locate the position of the sun to obtain the maximum solar energy. Based on the outcomes, the solar tracking system figures out whether to use image processing outcomes or astronomical estimates to attain the maximum efficiency of the solar panel. Finally, the experimental values obtained from the solar tracker for both the sunny and the rainy days are being tabulated.

Keywords: Dual axis solar tracker, Arduino board, LDR sensors, global positioning system.

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Authors: Ehsan Saghapour, Somayeh Zandian

Abstract:

Image segmentation is an important step in image processing. Major developments in medical imaging allow physicians to use potent and non-invasive methods in order to evaluate structures, performance and to diagnose human diseases. In this study, an active contour was used to extract vessel networks from color retina images. Automatic analysis of retina vessels facilitates calculation of arterial index which is required to diagnose some certain retinopathies.

Keywords: Active contour, retinal vessel segmentation, image processing.

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Authors: Carlos Ramirez, Carlos Concha, Benjamin Valdes

Abstract:

Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.

Keywords: Ballistocardiogram, emotions in learning, noninvasive sensors, personalization of learning resources.

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Authors: Liang-Ta Cheng, Ching-Yu Yang

Abstract:

Based on fast discrete cosine transform (FDCT), the authors present a high capacity and high perceived quality method for electrocardiogram (ECG) signal. By using a simple adjusting policy to the 1-dimentional (1-D) DCT coefficients, a large volume of secret message can be effectively embedded in an ECG host signal and be successfully extracted at the intended receiver. Simulations confirmed that the resulting perceived quality is good, while the hiding capability of the proposed method significantly outperforms that of existing techniques. In addition, our proposed method has a certain degree of robustness. Since the computational complexity is low, it is feasible for our method being employed in real-time applications.

Keywords: Data hiding, ECG steganography, fast discrete cosine transform, 1-D DCT bundle, real-time applications.

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Authors: Musa'ed N. Almarshad, Saleh A. Alshebeili, Mourad Barkat

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A challenging problem in radar signal processing is to achieve reliable target detection in the presence of interferences. In this paper, we propose a novel algorithm for automatic censoring of radar interfering targets in log-normal clutter. The proposed algorithm, termed the forward automatic censored cell averaging detector (F-ACCAD), consists of two steps: removing the corrupted reference cells (censoring) and the actual detection. Both steps are performed dynamically by using a suitable set of ranked cells to estimate the unknown background level and set the adaptive thresholds accordingly. The F-ACCAD algorithm does not require any prior information about the clutter parameters nor does it require the number of interfering targets. The effectiveness of the F-ACCAD algorithm is assessed by computing, using Monte Carlo simulations, the probability of censoring and the probability of detection in different background environments.

Keywords: CFAR, Log-normal clutter, Censoring, Probabilityof detection, Probability of false alarm, Probability of falsecensoring.

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Authors: V. Anil Kumar, Abhijit Mitra, S. R. Mahadeva Prasanna

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We analyze the effectivity of different pseudo noise (PN) and orthogonal sequences for encrypting speech signals in terms of perceptual intelligence. Speech signal can be viewed as sequence of correlated samples and each sample as sequence of bits. The residual intelligibility of the speech signal can be reduced by removing the correlation among the speech samples. PN sequences have random like properties that help in reducing the correlation among speech samples. The mean square aperiodic auto-correlation (MSAAC) and the mean square aperiodic cross-correlation (MSACC) measures are used to test the randomness of the PN sequences. Results of the investigation show the effectivity of large Kasami sequences for this purpose among many PN sequences.

Keywords: Speech encryption, pseudo-noise codes, maximallength, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.

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Authors: Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane

Abstract:

In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Keywords: EM algorithm, Magnetic Resonance Imaging, Mathematical morphology, Markov random model.

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Authors: Mamoun F. Al-Mistarihi

Abstract:

We have previously introduced an ultrasonic imaging approach that combines harmonic-sensitive pulse sequences with a post-beamforming quadratic kernel derived from a second-order Volterra filter (SOVF). This approach is designed to produce images with high sensitivity to nonlinear oscillations from microbubble ultrasound contrast agents (UCA) while maintaining high levels of noise rejection. In this paper, a two-step algorithm for computing the coefficients of the quadratic kernel leading to reduction of tissue component introduced by motion, maximizing the noise rejection and increases the specificity while optimizing the sensitivity to the UCA is presented. In the first step, quadratic kernels from individual singular modes of the PI data matrix are compared in terms of their ability of maximize the contrast to tissue ratio (CTR). In the second step, quadratic kernels resulting in the highest CTR values are convolved. The imaging results indicate that a signal processing approach to this clinical challenge is feasible.

Keywords: Volterra Filter, Pulse Inversion, Ultrasonic Imaging, Contrast Agent.

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Authors: V. Sudha, D. Sriram Kumar

Abstract:

In this paper, we present a low complexity hybrid scheme using conventional selective mapping (C-SLM) and clipping algorithms to reduce the high peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal. In the proposed scheme, the input data sequence (X) is divided into two sub-blocks, then clipping algorithm is applied to the first sub-block, whereas C-SLM algorithm is applied to the second sub-block in order to reduce both computational complexity and PAPR. The resultant time domain OFDM signal is obtained by combining the output of two sub-blocks. The simulation results show that the proposed hybrid scheme provides 0.45 dB PAPR reduction gain at CCDF value of 10-2 and 52% of computational complexity reduction when compared to C-SLM scheme at the expense of slight degradation in bit error rate (BER) performance.

Keywords: CCDF, Clipping, OFDM, PAPR, SLM.

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Authors: K. A. Navas, S. Archana Thampy, M. Sasikumar

Abstract:

Medical image data hiding has strict constrains such as high imperceptibility, high capacity and high robustness. Achieving these three requirements simultaneously is highly cumbersome. Some works have been reported in the literature on data hiding, watermarking and stegnography which are suitable for telemedicine applications. None is reliable in all aspects. Electronic Patient Report (EPR) data hiding for telemedicine demand it blind and reversible. This paper proposes a novel approach to blind reversible data hiding based on integer wavelet transform. Experimental results shows that this scheme outperforms the prior arts in terms of zero BER (Bit Error Rate), higher PSNR (Peak Signal to Noise Ratio), and large EPR data embedding capacity with WPSNR (Weighted Peak Signal to Noise Ratio) around 53 dB, compared with the existing reversible data hiding schemes.

Keywords: Biomedical imaging, Data security, Datacommunication, Teleconferencing.

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Authors: Ahmad Munawar

Abstract:

KREISIG is a computer simulation program, firstly developed by Munawar (1994) in Germany to optimize signalized roundabout. The traffic movement is based on the car following theory. Turbine method has been implemented for signal setting. The program has then been further developed in Indonesia to meet the traffic characteristics in Indonesia by adjusting the sensitivity of the drivers. Trial and error method has been implemented to adjust the saturation flow. The saturation flow output has also been compared to the calculation method according to 1997 Indonesian Highway Capacity Manual. It has then been implemented to optimize signalized roundabout at Kleringan roundabout in Malioboro area, Yogyakarta, Indonesia. It is found that this method can optimize the signal setting of this roundabout. Therefore, it is recommended to use this program to optimize signalized roundabout.

Keywords: KREISIG, signalized roundabout, traffic.

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Authors: Vishal Awasthi, Krishna Raj

Abstract:

Unwanted side effects because of spectral aliasing and spectral imaging during signal processing would be the major concern over the sampling rate alteration. Multirate-multistage implementation of digital filter could come about a large computational saving than single rate filter suitable for sample rate conversion. This implementation can further improve through high-level architectural transformation in circuit level. Reallocating registers and  relocating flip-flops across logic gates through retiming certainly a prominent sequential transformation technology, that optimize hardware circuits to achieve faster clocking speed without affecting the functionality. In this paper, we proposed an efficient compensated cascade Integrator comb (CIC) decimation filter structure that analyze the consequence of filter order variation which has a retimed FIR filter being compensator while using the cutset retiming technique and achieved an improvement in the passband droop by 14% to 39%, in computation time by 38.04%, 25.78%, 12.21%, 6.69% and 4.44% and reduction in path delay by 62.27%, 72%, 86.63%, 91.56% and 94.42% of 3, 6, 8, 12 and 24 order filter respectively than the non-retimed CIC compensation filter.

Keywords: Multirate Filtering, CIC decimation filter, Compensation theory, Retiming, Retiming algorithm, Filter order, Synchronous dataflow graph.

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Authors: H. S. Lim, M. Z. MatJafri, K. Abdullah, N. Mohd. Saleh

Abstract:

Retrieval of the surface reflectance is important in the remotely sensed data analysis to obtain the atmospheric reflectance or atmospheric correction. The relationship between visible and mid infrared reflectance over land was investigated and developed in this study. The surface reflectances of the two visible bands were measured using a handheld spectroradiometer collected around Penang Island. In this study, we use the assumption that the 2.1 μm band is not affected by aerosol and it is transparent to most aerosol types (except dust). Therefore the satellite observed signal is the same as the surface signal in 2.1 μm band. The correlation between the surface reflectance measured by the spectroradiometer in the blue and red region and the 2.1 μm observed by the satellite has been established. We investigate five dates of Landsat TM scenes in this study. The finding obtained by this study indicates that the surface reflectance can be retrieved from the 2.1 μm band.

Keywords: Surface Reflectance, Landsat TM, Aerosol, Spectroradiometer.

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Authors: Sung-Wook Shin, Sung-Taek Chung

Abstract:

Hand grip strength has been utilized as an indicator to evaluate the motor ability of hands, responsible for performing multiple body functions. It is, however, difficult to evaluate other factors (other than hand muscular strength) utilizing the hand grip strength only. In this study, we analyzed the motor ability of hands using EMG and the hand grip strength, simultaneously in order to evaluate concentration, muscular strength reaction time, instantaneous muscular strength change, and agility in response to visual reaction. In results, the average time (and their standard deviations) of muscular strength reaction EMG signal and hand grip strength was found to be 209.6 ± 56.2 ms and 354.3 ± 54.6 ms, respectively. In addition, the onset time which represents acceleration time to reach 90% of maximum hand grip strength, was 382.9 ± 129.9 ms.

Keywords: Hand grip strength, EMG, visual reaction, endurance.

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Authors: A.Goel, M. Agrawal, P. Gupta Poddar

Abstract:

Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.

Keywords: Orthogonal frequency division multiplexing (OFDM), Peak-to-average power ratio (PAPR), Selected mapping (SLM), Side information (SI)

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Authors: P. Manivannan, M. Rajasimman

Abstract:

Response surface methodology was used for quantitative investigation of water and solids transfer during osmotic dehydration of beetroot in aqueous solution of salt. Effects of temperature (25 – 45oC), processing time (30–150 min), salt concentration (5–25%, w/w) and solution to sample ratio (5:1 – 25:1) on osmotic dehydration of beetroot were estimated. Quadratic regression equations describing the effects of these factors on the water loss and solids gain were developed. It was found that effects of temperature and salt concentrations were more significant on the water loss than the effects of processing time and solution to sample ratio. As for solids gain processing time and salt concentration were the most significant factors. The osmotic dehydration process was optimized for water loss, solute gain, and weight reduction. The optimum conditions were found to be: temperature – 35oC, processing time – 90 min, salt concentration – 14.31% and solution to sample ratio 8.5:1. At these optimum values, water loss, solid gain and weight reduction were found to be 30.86 (g/100 g initial sample), 9.43 (g/100 g initial sample) and 21.43 (g/100 g initial sample) respectively.

Keywords: Optimization, Osmotic dehydration, Beetroot, saltsolution, response surface methodology

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Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

Abstract:

The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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