Search results for: Image filters

Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

Abstract:

Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: Daehwan Kim, Jaemin Kim, Seongwon Cho, Yongsuk Jang, Sun-Tae Chung, Boo-Gyoun Kim

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AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In case the initial values are a little far distant from the global optimum values, there exists a pretty good possibility that AAM-based face alignment may converge to a local minimum. In this paper, we propose a progressive AAM-based face alignment algorithm which first finds the feature parameter vector fitting the inner facial feature points of the face and later localize the feature points of the whole face using the first information. The proposed progressive AAM-based face alignment algorithm utilizes the fact that the feature points of the inner part of the face are less variant and less affected by the background surrounding the face than those of the outer part (like the chin contour). The proposed algorithm consists of two stages: modeling and relation derivation stage and fitting stage. Modeling and relation derivation stage first needs to construct two AAM models: the inner face AAM model and the whole face AAM model and then derive relation matrix between the inner face AAM parameter vector and the whole face AAM model parameter vector. In the fitting stage, the proposed algorithm aligns face progressively through two phases. In the first phase, the proposed algorithm will find the feature parameter vector fitting the inner facial AAM model into a new input face image, and then in the second phase it localizes the whole facial feature points of the new input face image based on the whole face AAM model using the initial parameter vector estimated from using the inner feature parameter vector obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment algorithm is more robust with respect to pose, illumination, and face background than the conventional basic AAM-based face alignment algorithm.

Keywords: Face Alignment, AAM, facial feature detection, model matching.

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Authors: Firouzeh Keshavarzi

Abstract:

Although a picture can be automatically a graphic work, but especially in the field of graphics and images based on the idea of advertising and graphic design will be prepared and photographers to realize the design using his own knowledge and skills to help does. It is evident that knowledge of photography, photographer and designer of the facilities, fields of reaching a higher level of quality offers. At the same time do not have a graphic designer is also skilled photographer, but can execute your idea may delegate to an expert photographer. Using technology and methods in all fields of photography, graphic art may be applicable. But most of its application in Iran, in works such as packaging, posters, Bill Board, advertising, brochures and catalogs are. In this study, we review how the images and techniques in the chart should be used in Iranian graphic photo what impact has left. Using photography techniques and procedures can be designed and helped advance the goals graphic. Technique could not determine the idea. But what is important to think about design and photography and his creativity can flourish as a tool to be effective graphic designer in mind. Computer software to help it's very promotes creativity techniques shall graphic designer but also it is as a tool. Using images in various fields, especially graphic arts and only because it is not being documented, but applications are beautiful. As to his photographic style from today is graphics. Graphic works try to affect impacts on their audience. Hence the photo as an important factor is attention. The other hand saw the man with the extent of forgiving and understanding people's image, instead of using the word to your files, allows large messages and concepts should be sent in the shortest time. Posters, advertisements, brochures, catalog and packaging products very diverse agricultural, industrial and food could not be self-image. Today, the use of graphic images for a big score and the photos to richen the role graphic design plays a major.

Keywords: Photo, Photography Techniques, Contacts, GraphicDesigner, Visual Communications, Iran.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Zuhair Kadhim Jahanger, S. Joseph Antony

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The available studies in the literature which dealt with the scale effects of strip footings on different sand packing systematically still remain scarce. In this research, the variation of ultimate bearing capacity and deformation pattern of soil beneath strip footings of different widths under plane-strain condition on the surface of loose, medium-dense and dense sand have been systematically studied using experimental and noninvasive methods for measuring microscopic deformations. The presented analyses are based on model scale compression test analysed using Particle Image Velocimetry (PIV) technique. Upper bound analysis of the current study shows that the maximum vertical displacement of the sand under the ultimate load increases for an increase in the width of footing, but at a decreasing rate with relative density of sand, whereas the relative vertical displacement in the sand decreases for an increase in the width of the footing. A well agreement is observed between experimental results for different footing widths and relative densities. The experimental analyses have shown that there exists pronounced scale effect for strip surface footing. The bearing capacity factors Nγ rapidly decrease up to footing widths B=0.25 m, 0.35 m, and 0.65 m for loose, medium-dense and dense sand respectively, after that there is no significant decrease in Nγ. The deformation modes of the soil as well as the ultimate bearing capacity values have been affected by the footing widths. The obtained results could be used to improve settlement calculation of the foundation interacting with granular soil.

Keywords: PIV, granular mechanics, scale effect, upper bound analysis.

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Authors: A. Breda, C. Cruz

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The role of images/illustrations in communicating meanings and triggering emotions assumes an increasingly relevant role in contemporary texts, regardless of the age group for which they are intended or the nature of the texts that host them. It is no coincidence that children's books are full of illustrations and that the image/text ratio decreases as the age group grows. The vast majority of children's books can be considered as multimodal texts containing text and images/illustrations, interacting with each other, to provide the young reader with a broader and more creative understanding of the book's narrative. This interaction is very diverse, ranging from images/illustrations that are not essential for understanding the storytelling to those that contribute significantly to the meaning of the story. Usually, these books are also read by adults, namely by parents, educators, and teachers who act as mediators between the book and the children, explaining aspects that are or seem to be too complex for the child's context. It should be noted that there are books labeled as children's books, that are clearly intended for both children and adults. In this work, following a qualitative and interpretative methodology based on written productions, participant observation, and field notes, we will describe the perceptions of future teachers of the 1st cycle of basic education, attending a master’s degree at a Portuguese university, about the role of the image in literary and non-literary texts, namely in mathematical texts, and how these can constitute precious resources for emotional regulation and for the design of creative didactic situations. The analysis of the collected data allowed us to obtain evidence regarding the evolution of the participants' perception regarding the crucial role of images in children's literature, not only as an emotional regulator for young readers but also as a creative source for the design of meaningful didactical situations, crossing other scientific areas, other than the mother tongue, namely mathematics.

Keywords: Children’s literature, emotions, multimodal texts, soft skills.

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Authors: Rajib Kumar Jha, P.K.Biswas, B.N.Chatterji

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In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.

Keywords: Completion Number, Maximum Independent subset, Partial complements, Partial self complementary.

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Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: Aerial image, land-cover, LiDAR, soil fertility degradation.

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Authors: Sangeeta Mandal, Rajib Kar, Durbadal Mandal, Sakti Prasad Ghoshal

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In this paper, an optimal design of linear phase digital high pass finite impulse response (FIR) filter using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA) has been presented. In the design process, the filter length, pass band and stop band frequencies, feasible pass band and stop band ripple sizes are specified. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for digital filter design. Given the filter specifications to be realized, the PSO-CFIWA algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristic. In this paper, for the given problem, the designs of the optimal FIR high pass filters of different orders have been performed. The simulation results have been compared to those obtained by the well accepted algorithms such as Parks and McClellan algorithm (PM), genetic algorithm (GA). The results justify that the proposed optimal filter design approach using PSOCFIWA outperforms PM and GA, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

Keywords: FIR Filter; PSO-CFIWA; PSO; Parks and McClellanAlgorithm, Evolutionary Optimization Technique; MagnitudeResponse; Convergence; High Pass Filter

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Authors: Umesh Ghanekar

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As the performance of the filtering system depends upon the accuracy of the noise detection scheme, in this paper, we present a new scheme for impulse noise detection based on two levels of decision. In this scheme in the first stage we coarsely identify the corrupted pixels and in the second stage we finally decide whether the pixel under consideration is really corrupt or not. The efficacy of the proposed filter has been confirmed by extensive simulations.

Keywords: Impulse detection, noise removal, image filtering.

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Authors: Jason Chien-Hsun Tseng, Nguyen Dong-Thai Dao, Chong-Ching Chang

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A novel PDE solver using the multidimensional wave digital filtering (MDWDF) technique to achieve the solution of a 2D seismic wave system is presented. In essence, the continuous physical system served by a linear Kirchhoff circuit is transformed to an equivalent discrete dynamic system implemented by a MD wave digital filtering (MDWDF) circuit. This amounts to numerically approximating the differential equations used to describe elements of a MD passive electronic circuit by a grid-based difference equations implemented by the so-called state quantities within the passive MDWDF circuit. So the digital model can track the wave field on a dense 3D grid of points. Details about how to transform the continuous system into a desired discrete passive system are addressed. In addition, initial and boundary conditions are properly embedded into the MDWDF circuit in terms of state quantities. Graphic results have clearly demonstrated some physical effects of seismic wave (P-wave and S–wave) propagation including radiation, reflection, and refraction from and across the hard boundaries. Comparison between the MDWDF technique and the finite difference time domain (FDTD) approach is also made in terms of the computational efficiency.

Keywords: Seismic Wave Propagation, Multi-dimension WaveDigital Filters, Partial Differential Equations.

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Authors: Yen San Yong, Hock Woon Hon

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An algorithm for estimating the disparity of objects of interest is proposed. This algorithm uses image shifting and overlapping area to estimate the disparity value; thereby depth of the objects of interest can be obtained. The algorithm is able to perform at different levels of accuracy. However, as the accuracy increases the processing speed decreases. The algorithm is tested with static stereo images and sequence of stereo images. The experimental results are presented in this paper.

Keywords: stereo vision, binocular parallax

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Authors: M.H. Ahmad Fadzil, Esa Prakasa, Hurriyatul Fitriyah, Hermawan Nugroho, Azura Mohd Affandi, S.H. Hussein

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Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.

Keywords: psoriasis, roughness algorithm, polynomial surfacefitting.

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: ANN, DWT, GLCM, KNN, ROI, artificial neural networks, discrete wavelet transform, gray-level co-occurrence matrix, k-nearest neighbor, region of interest.

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Authors: Lise P. Labéjof, Raiza S. P. Bizerra, Galileu B. Costa, Thaísa B. dos Santos

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This report presents an alternative technique of application of contrast agent in vivo, i.e. before sampling. By this new method the electron micrograph of tissue sections have an acceptable contrast compared to other methods and present no artifact of precipitation on sections. Another advantage is that a small amount of contrast is needed to get a good result given that most of them are expensive and extremely toxic.

Keywords: Image quality, Microscopy research, Staining technique, Ultrathin section.

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Authors: Md. Khademul Islam Molla, Akimasa Sumi, M. Sayedur Rahman

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The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Keywords: Empirical mode decomposition, instantaneous frequency, Hilbert spectrum, Chi-square distribution, anthropogenic impact.

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Authors: M. A. Gad, A. Z. Al-Herrawy

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Microsporidia comprises various pathogenic species can infect humans by means of water. Moreover, chlorine disinfection of drinking-water has limitations against this protozoan pathogen. A total of 48 water samples were collected from two drinking water treatment plants having two different filtration systems (slow sand filter and rapid sand filter) during one year period. Samples were collected from inlet and outlet of each plant. Samples were separately filtrated through nitrocellulose membrane (142 mm, 0.45 µm), then eluted and centrifuged. The obtained pellet from each sample was subjected to DNA extraction, then, amplification using genus-specific primer for microsporidia. Each microsporidia-PCR positive sample was performed by two species specific primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis. The results of the present study showed that the percentage of removal for microsporidia through different treatment processes reached its highest rate in the station using slow sand filters (100%), while the removal by rapid sand filter system was 81.8%. Statistically, the two different drinking water treatment plants (slow and rapid) had significant effect for removal of microsporidia. Molecular identification of microsporidia-PCR positive samples using two different primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis showed the presence of the two pervious species in the inlet water of the two stations, while Encephalitozoon intestinalis was detected in the outlet water only. In conclusion, the appearance of virulent microsporidia in treated drinking water may cause potential health threat.

Keywords: Removal, efficacy, microsporidia, drinking water treatment plants, PCR.

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Authors: J. K. Khare, Abhay Kumar Sharma, Ajay Tiwari, Amol A. Talankar

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Powder metallurgy (P/M) is the only economic way to produce porous parts/products. P/M can produce near net shape parts hence reduces wastage of raw material and energy, avoids various machining operations. The most vital use of P/M is in production of metallic filters and self lubricating bush bearings and siding surfaces. The porosity of the part can be controlled by varying compaction pressure, sintering temperature and composition of metal powder mix. The present work is aimed for experimental analysis of friction and wear properties of self lubricating copper and tin bush bearing. Experimental results confirm that wear rate of sintered component is lesser for components having 10% tin by weight percentage. Wear rate increases for high tin percentage (experimented for 20% tin and 30% tin) at same sintering temperature. Experimental results also confirms that wear rate of sintered component is also dependent on sintering temperature, soaking period, composition of the preform, compacting pressure, powder particle shape and size. Interfacial friction between die and punch, between inter powder particles, between die face and powder particle depends on compaction pressure, powder particle size and shape, size and shape of component which decides size & shape of die & punch, material of die & punch and material of powder particles.

Keywords: Interfacial friction, porous bronze bearing, sintering temperature, wear rate.

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Authors: Lai-Fen Yang

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In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.

Keywords: Visual culture, contemporary, visual spectacle.

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Authors: Khalide Jbilou

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In the present paper, we propose numerical methods for solving the Stein equation AXC - X - D = 0 where the matrix A is large and sparse. Such problems appear in discrete-time control problems, filtering and image restoration. We consider the case where the matrix D is of full rank and the case where D is factored as a product of two matrices. The proposed methods are Krylov subspace methods based on the block Arnoldi algorithm. We give theoretical results and we report some numerical experiments.

Keywords: IEEEtran, journal, LATEX, paper, template.

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The root mean square errors (RMSE) between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: Neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition.

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Authors: Mario Gonzalez, David Dominguez, Francisco B. Rodriguez

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An attractor neural network on the small-world topology is studied. A learning pattern is presented to the network, then a stimulus carrying local information is applied to the neurons and the retrieval of block-like structure is investigated. A synaptic noise decreases the memory capability. The change of stability from local to global attractors is shown to depend on the long-range character of the network connectivity.

Keywords: Hebbian learning, image recognition, small world, spatial information.

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Authors: Mohammad Pooyan, Ali Taheri, Morteza Moazami-Goudarzi, Iman Saboori

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In this paper we present a novel approach for wavelet compression of electrocardiogram (ECG) signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm. SPIHT algorithm has achieved prominent success in image compression. Here we use a modified version of SPIHT for one dimensional signals. We applied wavelet transform with SPIHT coding algorithm on different records of MIT-BIH database. The results show the high efficiency of this method in ECG compression.

Keywords: ECG compression, wavelet, SPIHT.

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Authors: Laura X. Martinez, Andrés F. Rodríguez, Ruth A. Catacoli

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One of the most important factors for air pollution is that the concentrations of PM₁₀ maintain a constant trend, with the exception of some places where that frequently surpasses the allowed ranges established by Colombian legislation. The community that surrounds the Universidad Libre Bogotá is inhabited by a considerable number of students and workers, all of whom are possibly being exposed to PM₁₀ for long periods of time while on campus. Thus, the chemical characterization of PM₁₀ found in the ambient air at the Universidad Libre Bogotá was identified as a problem. A Hi-Vol sampler and EPA Test Method 5 were used to determine if the quality of air is adequate for the human respiratory system. Additionally, quartz fiber filters were utilized during sampling. Samples were taken three days a week during a dry period throughout the months of November and December 2015. The gravimetric analysis method was used to determine PM₁₀ concentrations. The chemical characterization includes non-conventional carcinogenic pollutants. Atomic absorption spectrophotometry (AAS) was used for the determination of metals and VOCs were analyzed using the FTIR (Fourier transform infrared spectroscopy) method. In this way, concentrations of PM₁₀, ranging from values of 13 µg/m³ to 66 µg/m³, were obtained; these values were below standard conditions. This evidence concludes that the PM₁₀ concentrations during an exposure period of 24 hours are lower than the values established by Colombian law, Resolution 610 of 2010; however, when comparing these with the limits set by the World Health Organization (WHO), these concentrations could possibly exceed permissible levels.

Keywords: Air quality, atomic absorption spectrophotometry, Fourier transform infrared spectroscopy, particulate matter.

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Authors: Yash Pal, A.Swarup, Bhim Singh

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This paper presents a novel control strategy of a threephase four-wire Unified Power Quality (UPQC) for an improvement in power quality. The UPQC is realized by integration of series and shunt active power filters (APFs) sharing a common dc bus capacitor. The shunt APF is realized using a thee-phase, four leg voltage source inverter (VSI) and the series APF is realized using a three-phase, three leg VSI. A control technique based on unit vector template technique (UTT) is used to get the reference signals for series APF, while instantaneous sequence component theory (ISCT) is used for the control of Shunt APF. The performance of the implemented control algorithm is evaluated in terms of power-factor correction, load balancing, neutral source current mitigation and mitigation of voltage and current harmonics, voltage sag and swell in a three-phase four-wire distribution system for different combination of linear and non-linear loads. In this proposed control scheme of UPQC, the current/voltage control is applied over the fundamental supply currents/voltages instead of fast changing APFs currents/voltages, there by reducing the computational delay and the required sensors. MATLAB/Simulink based simulations are obtained, which support the functionality of the UPQC. MATLAB/Simulink based simulations are obtained, which support the functionality of the UPQC.

Keywords: Power Quality, UPQC, Harmonics, Load Balancing, Power Factor Correction, voltage harmonic mitigation, currentharmonic mitigation, voltage sag, swell

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Authors: Yuji Kageyama, Shin Nagata, Tatsuya Takino, Izuru Nomura, Hiroyuki Kamata

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In previous study, technique to estimate a self-location by using a lunar image is proposed.We consider the improvement of the conventional method in consideration of FPGA implementationin this paper. Specifically, we introduce Artificial Bee Colony algorithm for reduction of search time.In addition, we use fixed point arithmetic to enable high-speed operation on FPGA.

Keywords: SLIM, Artificial Bee Colony Algorithm, Location Estimate.

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

Abstract:

The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: Bottom elevation, multi-view stereo, river, structure-from-motion.

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Authors: Mihaela Popescu, Alexandru Bitoleanu, Mircea Dobriceanu

Abstract:

The proper selection of the AC-side passive filter interconnecting the voltage source converter to the power supply is essential to obtain satisfactory performances of an active power filter system. The use of the LCL-type filter has the advantage of eliminating the high frequency switching harmonics in the current injected into the power supply. This paper is mainly focused on analyzing the influence of the interface filter parameters on the active filtering performances. Some design aspects are pointed out. Thus, the design of the AC interface filter starts from transfer functions by imposing the filter performance which refers to the significant current attenuation of the switching harmonics without affecting the harmonics to be compensated. A Matlab/Simulink model of the entire active filtering system including a concrete nonlinear load has been developed to examine the system performances. It is shown that a gamma LC filter could accomplish the attenuation requirement of the current provided by converter. Moreover, the existence of an optimal value of the grid-side inductance which minimizes the total harmonic distortion factor of the power supply current is pointed out. Nevertheless, a small converter-side inductance and a damping resistance in series with the filter capacitance are absolutely needed in order to keep the ripple and oscillations of the current at the converter side within acceptable limits. The effect of change in the LCL-filter parameters is evaluated. It is concluded that good active filtering performances can be achieved with small values of the capacitance and converter-side inductance.

Keywords: Active power filter, LCL filter, Matlab/Simulinkmodeling, Passive filters, Transfer function.

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Authors: Suprijanto, Linda Sari, Vebi Nadhira , IGN. Merthayasa. Farida I.M

Abstract:

Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.

Keywords: Multimodal Emotion Detection, EEG, Facial Image, Optical Flow, compass mapping, Brain Wave

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Authors: Sarisa Pinkham, Kanyarat Bussaban

Abstract:

The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.

Keywords: Daily rainfall, Image processing, Approximation, Pixel value data.

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