Search results for: shape detection

Authors: Bing Li, Tong Lu, Lei Qiang

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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: Characteristic equation, interface waves, dispersion curves, potential function, Stoneley waves, wave structures.

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: Emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing.

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: Md Shohidul Islam, Jongmyon Kim, Ui-pil Chong

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Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.

Keywords: Medical Image Watermarking (MIW), e-health system, error correction, Hamming code, GPU.

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Authors: Anju Luthra, Rajender Lal, Dhananjoy Shaw

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Participation in games and sports in the contemporary times has become more competing with the developed scientific knowledge, skills and methods, along with the equipment and applied research in the field. In spite of India being a large country having vast resources and potential, its performance in the world of sports on the whole needs sincere attention for better achievements. Beside numerous factors responsible for the dismal performance of a sportsperson, the physique and body composition, including the size, shape and form are known to play a significant role. The present investigation was undertaken to study the specific morphological characteristics of Indian female Track and Field athletes. A total of 300 athletes were randomly selected as sample for the purpose of the study from the six events having 50 athletes in each event including 100m., 400m., Shot Put, Discus Throw, Long Jump and High Jump. The study included body weight, body fat percentage, lean body weight, endomorphy, mesomorphy and ectomorphy as variables. The data were computed statistically by using Mean, Standard Deviation and Analysis of Variance. The post-hoc analysis was conducted where the F-ratio was found to be significant at .05 level. The study concluded that there is a significant difference with regard to the selected variables among the Indian female athletes of different track and field events.

Keywords: Indian female athletes, body composition, morphology, somatotypes, track and field.

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Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

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Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N,N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by flame atomic absorption spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300mg; flow rates 2.0mL min^-1 of solution and 2.0mL min^-1 of eluent (2.0mol L^-1 HNO₃). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H₂O₂. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20μg L^-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531mmol g^-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: Styrofoam waste, Polymeric resin, Preconcentration, Speciation, Cr(III)/Cr(VI) ions, FAAS.

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

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The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: Bonded rubber, quasi-static test, shape factor, apparent Young’s modulus.

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Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: Surface flattening, Strain energy, Minimum energy, approximate implicit method, Fashion design.

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Authors: D. Arjmandi

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The notion of power and gender domination is one of the inseparable aspects of themes in postmodern literature. The reason of its importance has been discussed frequently since the rise of Michel Foucault and his insight into the circulation of power and the transgression of forces. Language and society operate as the basic grounds for the study, as all human beings are bound to the set of rules and norms which shape them in the acceptable way in the macrocosm. How different genders in different positions behave and show reactions to the provocation of social forces and superiority of one another is of great interest to writers and literary critics. Mamet’s works are noticeable for their controversial but timely themes which illustrate human conflicts with the society and greed for power. Many critics like Christopher Bigsby and Harold Bloom have discussed Mamet and his ideas in recent years. This paper is the study of Oleanna, Mamet’s masterpiece about the teacher-student relationship and the circulation of power between a man and woman. He shows the very breakable boundaries in the domination of a gender and the downfall of speech as the consequence of transgression and freedom. The failure of the language the teacher uses and the abuse of his own words by a student who seeks superiority and knowledge are the main subjects of the discussion. Supported by the ideas of Foucault, the language Mamet uses to present his characters becomes the fundamental premise in this study. As a result, language becomes both the means of achievement and downfall.

Keywords: Domination, foucault, language, mamet, oleanna, power, transgression.

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Authors: Oyugi Ngure Robert, Tabitha A. Amollo, Kallen Mulilo Nalyanya

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Nanomaterials have attracted significant attention in research because of their exemplary properties, making them suitable for diverse applications. This paper reports the successful synthesis as well as the structural and optical properties of silver sulfide-reduced graphene oxide (Ag2S-rGO) nanocomposite. The nanocomposite was synthesized by the chemical reduction method. Scanning electron microscopy (SEM) showed that the reduced graphene oxide (rGO) sheets were intercalated within the Ag2S nanoparticles during the chemical reduction process. The SEM images also showed that Ag2S had the shape of nanowires. Further, SEM energy dispersive X-ray (SEM EDX) showed that Ag2S-rGO is mainly composed of C, Ag, O, and S. X-ray diffraction analysis manifested a high crystallinity for the nanowire-shaped Ag2S nanoparticles with a d-spacing ranging between 1.0 Å and 5.2 Å. Thermal gravimetric analysis (TGA) showed that rGO enhances the thermal stability of the nanocomposite. Ag2S-rGO nanocomposite exhibited strong optical absorption in the UV region. The formed nanocomposite is dispersible in polar and non-polar solvents, qualifying it for solution-based device processing. Thus, the surface plasmon resonance effect associated with metallic nanoparticles, strong optical absorption, thermal stability crystallinity and hydrophilicity of the nanocomposite suits it for solar energy conversion applications.

Keywords: Silver sulfide, reduced graphene oxide, nanocomposite, structural properties, optical properties.

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8.

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Authors: Parvinder S. Sandhu, Satish Kumar Dhiman, Anmol Goyal

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Fault-proneness of a software module is the probability that the module contains faults. A correlation exists between the fault-proneness of the software and the measurable attributes of the code (i.e. the static metrics) and of the testing (i.e. the dynamic metrics). Early detection of fault-prone software components enables verification experts to concentrate their time and resources on the problem areas of the software system under development. This paper introduces Genetic Algorithm based software fault prediction models with Object-Oriented metrics. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the classification of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results shows that Genetic algorithm approach can be used for finding the fault proneness in object oriented software components.

Keywords: Genetic Algorithms, Software Fault, Classification, Object Oriented Metrics.

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Authors: Ethar H. Khalil, Bahaa I. Kazem

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In this work a software simulation model has been proposed for two driven wheels mobile robot path planning; that can navigate in dynamic environment with static distributed obstacles. The work involves utilizing Bezier curve method in a proposed N order matrix form; for engineering the mobile robot path. The Bezier curve drawbacks in this field have been diagnosed. Two directions: Up and Right function has been proposed; Probability Recursive Function (PRF) to overcome those drawbacks. PRF functionality has been developed through a proposed; obstacle detection function, optimization function which has the capability of prediction the optimum path without comparison between all feasible paths, and N order Bezier curve function that ensures the drawing of the obtained path. The simulation results that have been taken showed; the mobile robot travels successfully from starting point and reaching its goal point. All obstacles that are located in its way have been avoided. This navigation is being done successfully using the proposed PRF techniques.

Keywords: Mobile robot, path planning, Bezier curve.

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Authors: Okan Özgönenel

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This paper presents the development of a wavelet based algorithm, for distinguishing between magnetizing inrush currents and power system fault currents, which is quite adequate, reliable, fast and computationally efficient tool. The proposed technique consists of a preprocessing unit based on discrete wavelet transform (DWT) in combination with an artificial neural network (ANN) for detecting and classifying fault currents. The DWT acts as an extractor of distinctive features in the input signals at the relay location. This information is then fed into an ANN for classifying fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz laboratory transformer connected to a 380 V power system were simulated using ATP-EMTP. The DWT was implemented by using Matlab and Coiflet mother wavelet was used to analyze primary currents and generate training data. The simulated results presented clearly show that the proposed technique can accurately discriminate between magnetizing inrush and fault currents in transformer protection.

Keywords: Artificial neural network, discrete wavelet transform, fault detection, magnetizing inrush current.

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Authors: Kazuhisa Koda, Tsutomu Kobayashi

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Laura Island, which is located about 50 km away from downtown, is a source of water supply in Majuro atoll, which is the capital of the Republic of the Marshall Islands. Low and flat Majuro atoll has neither river nor lake. It is very important for Majuro atoll to ensure the conservation of its water resources. However, upconing, which is the process of partial rising of the freshwater-saltwater boundary near the water-supply well, was caused by the excess pumping from it during the severe drought in 1998. Upconing will make the water usage of the freshwater lens difficult. Thus, appropriate water usage is required to prevent up coning in the freshwater lens because there is no other water source during drought. Numerical simulation of water usage applying SEAWAT model was conducted at the central part of Laura Island, including the water supply well, which was affected by upconing. The freshwater lens was created as a result of infiltration of consistent average rainfall. The lens shape was almost the same as the one in 1985. 0 of monthly rainfall and variable daily pump discharge were used to calculate the sustainable pump discharge from the water supply well. Consequently, the total amount of pump discharge was increased as the daily pump discharge was increased, indicating that it needs more time to recover from upconing. Thus, a pump standard to reduce the pump intensity is being proposed, which is based on numerical simulation concerning the occurrence of the up-coning phenomenon in Laura Island during the drought.

Keywords: Freshwater lens, islands, numerical simulation, sustainable water use.

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Authors: Rachid Zentar, Mokrane Bala, Pascal Boustingorry

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The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.

Keywords: Crushed aggregates, intrinsic viscosity, packing density, rolled aggregates, slump, yield stress of concrete.

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Authors: M. S. El-Asfoury, M. A. El-Hadek

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The complex shape of the human pelvic bone was successfully imaged and modeled using finite element FE processing. The bone was subjected to quasi-static and dynamic loading conditions simulating the effect of both weight gain and impact. Loads varying between 500 – 2500 N (~50 – 250 Kg of weight) was used to simulate 3D quasi-static weight gain. Two different 3D dynamic analyses, body free fall at two different heights (1 and 2 m) and forced side impact at two different velocities (20 and 40 Km/hr) were also studied. The computed resulted stresses were compared for the four loading cases, where Von Misses stresses increases linearly with the weight gain increase under quasi-static loading. For the dynamic models, the Von Misses stress history behaviors were studied for the affected area and effected load with respect to time. The normalization Von Misses stresses with respect to the applied load were used for comparing the free fall and the forced impact load results. It was found that under the forced impact loading condition an over lapping behavior was noticed, where as for the free fall the normalized Von Misses stresses behavior was found to nonlinearly different. This phenomenon was explained through the energy dissipation concept. This study will help designers in different specialization in defining the weakest spots for designing different supporting systems.

Keywords: Pelvic Bone, Static and Dynamic Analysis, Three- Dimensional Finite Element Analysis.

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Authors: R. Gary Black, Abolhassan Astaneh-Asl

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The International Building Code (IBC) and the  California Building Code (CBC) both recognize four basic types of  steel seismic resistant frames; moment frames, concentrically braced  frames, shear walls and eccentrically braced frames. Based on  specified geometries and detailing, the seismic performance of these  steel frames is well understood. In 2011, the authors designed an  innovative steel braced frame system with tapering members in the  general shape of a branching tree as a seismic retrofit solution to an  existing four story “lift-slab” building. Located in the seismically  active San Francisco Bay Area of California, a frame of this  configuration, not covered by the governing codes, would typically  require model or full scale testing to obtain jurisdiction approval.  This paper describes how the theories, protocols, and code  requirements of eccentrically braced frames (EBFs) were employed  to satisfy the 2009 International Building Code (IBC) and the 2010  California Building Code (CBC) for seismically resistant steel frames  and permit construction of these nonconforming geometries.

 

Keywords: Eccentrically Braced Frame, Lift Slab Construction, Seismic Retrofit, Shear Link, Steel Design.

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Authors: Huafeng Wang, Yunhong Wang, Yuan Cao

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During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.

Keywords: Face recognition, video-based, survey

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Authors: Peter Drotar, Juraj Gazda, Pavol Galajda, Dusan Kocur

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The study in this paper underlines the importance of correct joint selection of the spreading codes for uplink of multicarrier code division multiple access (MC-CDMA) at the transmitter side and detector at the receiver side in the presence of nonlinear distortion due to high power amplifier (HPA). The bit error rate (BER) of system for different spreading sequences (Walsh code, Gold code, orthogonal Gold code, Golay code and Zadoff-Chu code) and different kinds of receivers (minimum mean-square error receiver (MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD)) is compared by means of simulations for MC-CDMA transmission system. Finally, the results of analysis will show, that the application of MSF-MUD in combination with Golay codes can outperform significantly the other tested spreading codes and receivers for all mostly used models of HPA.

Keywords: HPA, MC-CDMA, microstatistic filter, multi-user receivers, PAPR.

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Authors: B. Bagheri Nakhjavanlo, T. J. Ellis, P. Raoofi, J. Dehmeshki

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This paper presents a customized deformable model for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic aneurysm is the need to overcome problems associated with intensity inhomogeneities and image noise. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A Gaussian kernel function in the level set formulation, which extracts the local intensity information, aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets. The results indicate the method is more effective than other approaches in coping with intensity inhomogeneities.

Keywords: Abdominal and thoracic aortic aneurysms, intensityinhomogeneity, level sets, local fitting binary.

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Authors: Shimal Das, Dibyendu Ghoshal

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Fractal based digital image compression is a specific technique in the field of color image. The method is best suited for irregular shape of image like snow bobs, clouds, flame of fire; tree leaves images, depending on the fact that parts of an image often resemble with other parts of the same image. This technique has drawn much attention in recent years because of very high compression ratio that can be achieved. Hybrid scheme incorporating fractal compression and speedup techniques have achieved high compression ratio compared to pure fractal compression. Fractal image compression is a lossy compression method in which selfsimilarity nature of an image is used. This technique provides high compression ratio, less encoding time and fart decoding process. In this paper, fractal compression with quad tree and DCT is proposed to compress the color image. The proposed hybrid schemes require four phases to compress the color image. First: the image is segmented and Discrete Cosine Transform is applied to each block of the segmented image. Second: the block values are scanned in a zigzag manner to prevent zero co-efficient. Third: the resulting image is partitioned as fractals by quadtree approach. Fourth: the image is compressed using Run length encoding technique.

Keywords: Fractal coding, Discrete Cosine Transform, Iterated Function System (IFS), Affine Transformation, Run length encoding.

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Authors: Mehdi Modabberifar, Milad Roodi, Ehsan Souri

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In recent years, honeycomb fiber reinforced plastic (FRP) sandwich panels have been increasingly used in various industries. Low weight, low price and high mechanical strength are the benefits of these structures. However, their mechanical properties and behavior have not been fully explored. The objective of this study is to conduct a combined numerical-statistical investigation of honeycomb FRP sandwich beams subject to torsion load. In this paper, the effect of geometric parameters of sandwich panel on maximum shear strain in both face and core and angle of torsion in a honeycomb FRP sandwich structures in torsion is investigated. The effect of Parameters including core thickness, face skin thickness, cell shape, cell size, and cell thickness on mechanical behavior of the structure were numerically investigated. Main effects of factors were considered in this paper and regression equations were derived. Taguchi method was employed as experimental design and an optimum parameter combination for the maximum structure stiffness has been obtained. The results showed that cell size and face skin thickness have the most significant impacts on torsion angle, maximum shear strain in face and core.

Keywords: Finite element, honeycomb FRP sandwich panel, torsion, civil engineering.

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.

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Authors: O. Ikpotokin

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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: Bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics.

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: Hydrological characteristic, land and climate, runoff discharge, streamflow.

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Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: Wen-Shyong Tzou, Chih-Ching Huang, Chin-Hwa Hu, Ying-Tsang Lo, Tun-Wen Pai, Chia-Yin Chiang, Chung-Hao Li, Hong-Jyuan Jian

Abstract:

Plasmin plays an important role in the human circulatory system owing to its catalytic ability of fibrinolysis. The immediate injection of plasmin in patients of strokes has intrigued many scientists to design vectors that can transport plasmin to the desired location in human body. Here we predict the structure of human plasmin and investigate the interaction of plasmin with the gold-nanoparticle. Because the crystal structure of plasminogen has been solved, we deleted N-terminal domain (Pan-apple domain) of plasminogen and generate a mimic of the active form of this enzyme (plasmin). We conducted a simulated annealing process on plasmin and discovered a very large conformation occurs. Kringle domains 1, 4 and 5 had been observed to leave its original location relative to the main body of the enzyme and the original doughnut shape of this enzyme has been transformed to a V-shaped by opening its two arms. This observation of conformational change is consistent with the experimental results of neutron scattering and centrifugation. We subsequently docked the plasmin on the simulated gold surface to predict their interaction. The V-shaped plasmin could utilize its Kringle domain and catalytic domain to contact the gold surface. Our findings not only reveal the flexibility of plasmin structure but also provide a guide for the design of a plasmin-gold nanoparticle.

Keywords: Docking, gold nanoparticle, molecular simulation, plasmin.

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Authors: Mongkorn Klingajay, Tawatchai Jitson

Abstract:

The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.

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