Search results for: extended airfoil database

Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Ashraful Alam, Nam Kim, Jae-Hyeung Park

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A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.

Keywords: Aw-SpPC, Expressoin Recognition, Face context, Face Detection, PCA

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: Biometric characters, facial recognition, neural network, OpenCV.

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Authors: S. Shanthi, V. Muralibhaskaran

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Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

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Authors: U. Pangnakorn, S. Kanlaya, C. Kuntha

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Raw wood vinegar was purified by both standing and filtering methods. Toxicity tests were conducted under laboratory conditions by the topical application method (contact poison) and feeding method (stomach poison). Larvicidal activities of wood vinegar at four different concentrations (10, 15, 20, 25 and 30 %) were studied against second instar larvae of housefly (Musca domestica L.). Four replicates were maintained for all treatments and controls. Larval mortality was recorded up to 96 hours and compared with the larval survivability by two methods of larvicidal bioassay. Percent pupation and percent adult emergence were observed in treated M. domestica. The study revealed that the feeding method gave higher efficiency compared with the topical application method. Larval mortality increased with increasing concentration of wood vinegar and the duration of exposure. No mortality was found in treated M. domestica larvae at minimum 10% concentration of wood vinegar through the experiments. The treated larvae were maintained up to pupa and adult emergence. At 30% maximum concentration larval duration was extended to 11 days in M. domestica for topical application method and 9 days for feeding method. Similarly the pupal durations were also increased with increased concentrations (16 and 24 days for topical application method and feeding method respectively at 30% concentration) of the treatments.

Keywords: Housefly (Musca domestica L.), wood vinegar, mortality, topical application, feeding

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

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The problem of frequent pattern discovery is defined as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a database. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages. Such paradigm is inefficient when set of patterns is large and the frequent pattern is long. We suggest a high-level declarative style of programming apply to the problem of frequent pattern discovery. We consider two languages: Haskell and Prolog. Our intuitive idea is that the problem of finding frequent patterns should be efficiently and concisely implemented via a declarative paradigm since pattern matching is a fundamental feature supported by most functional languages and Prolog. Our frequent pattern mining implementation using the Haskell and Prolog languages confirms our hypothesis about conciseness of the program. The comparative performance studies on line-of-code, speed and memory usage of declarative versus imperative programming have been reported in the paper.

Keywords: Frequent pattern mining, functional programming, pattern matching, logic programming.

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Authors: J.S. Ubhi, M.S. Patterh, T.S. Kamal

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Exact expressions for bit-error probability (BEP) for coherent square detection of uncoded and coded M-ary quadrature amplitude modulation (MQAM) using an array of antennas with maximal ratio combining (MRC) in a flat fading channel interference limited system in a Nakagami-m fading environment is derived. The analysis assumes an arbitrary number of independent and identically distributed Nakagami interferers. The results for coded MQAM are computed numerically for the case of (24,12) extended Golay code and compared with uncoded MQAM by plotting error probabilities versus average signal-to-interference ratio (SIR) for various values of order of diversity N, number of distinct symbols M, in order to examine the effect of cochannel interferers on the performance of the digital communication system. The diversity gains and net gains are also presented in tabular form in order to examine the performance of digital communication system in the presence of interferers, as the order of diversity increases. The analytical results presented in this paper are expected to provide useful information needed for design and analysis of digital communication systems with space diversity in wireless fading channels.

Keywords: Cochannel interference, maximal ratio combining, Nakagami-m fading, wireless digital communications.

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Authors: Mohamed Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Aziz, Mona Fawzy Al-Daghma

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Helical piles are widely used as axially and laterally loaded deep foundations. When they are required to resist bearing combined loads (BCLs), such as axial compression and lateral thrust, different behaviour is expected, necessitating further investigation. The aim of the present article is to clarify the behaviour of a single helical pile of different shaft rigidity embedded in cohesionless soil and subjected to simultaneous or successive loading patterns of BCLs. The study was first developed analytically and extended numerically. The numerical analysis using PLAXIS 3D was further verified through a laboratory experimental programme on a set of helical pile models. The results indicate highly interactive effects of the studied parameters, but it is obviously confirmed that the pile performance increases with both the increase of shaft rigidity and the change of BCLs loading pattern from simultaneous to successive. However, it is noted that the increase of vertical load does not always enhance the lateral capacity but may cause a decrement in lateral capacity, as observed with helical piles of flexible shafts. This study provides insightful information for the design of helical piles in structures loaded by complex sequence of forces, wind turbines, and industrial shafts.

Keywords: Helical pile, lateral loads. combined loads, cohesionless soil, analytical model, PLAXIS 3D.

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: Continuous query processing, dynamic database, moving object, skyline queries.

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Authors: Martina Kanciruk, Jac W. Andrews, Tyrone Donnon

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The purpose of this study was to determine the significance of maternal smoking for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, smoking, parents, childhood, risk factors. Eighteen studies of maternal smoking during pregnancy and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that maternal smoking during pregnancy is a significant risk factor for overweight and obesity; mothers who smoke during pregnancy are at a greater risk for developing obesity or overweight; the quantity of cigarettes consumed by the mother during pregnancy influenced the odds of offspring overweight and/or obesity. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment.

Keywords: Childhood obesity, overweight, smoking, parents, risk factors.

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Authors: Khalid A. Darabkh, Ala F. Khalifeh, Baraa A. Bathech, Saed W. Sabah

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Despite the fact that Arabic language is currently one of the most common languages worldwide, there has been only a little research on Arabic speech recognition relative to other languages such as English and Japanese. Generally, digital speech processing and voice recognition algorithms are of special importance for designing efficient, accurate, as well as fast automatic speech recognition systems. However, the speech recognition process carried out in this paper is divided into three stages as follows: firstly, the signal is preprocessed to reduce noise effects. After that, the signal is digitized and hearingized. Consequently, the voice activity regions are segmented using voice activity detection (VAD) algorithm. Secondly, features are extracted from the speech signal using Mel-frequency cepstral coefficients (MFCC) algorithm. Moreover, delta and acceleration (delta-delta) coefficients have been added for the reason of improving the recognition accuracy. Finally, each test word-s features are compared to the training database using dynamic time warping (DTW) algorithm. Utilizing the best set up made for all affected parameters to the aforementioned techniques, the proposed system achieved a recognition rate of about 98.5% which outperformed other HMM and ANN-based approaches available in the literature.

Keywords: Arabic speech recognition, MFCC, DTW, VAD.

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Authors: L. C. Moreira, M. Kauffman

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This paper outlines the results of an experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance (or work instructions) of highly customised and high-risk manual operations. The focus is on human operators’ training effectiveness and performance and the aim is to test if such technologies can support enhancing the knowledge retention levels and accuracy of task execution to improve health and safety (H&S). An AR enhanced assembly method is proposed and experimentally tested using a real industrial process as case study for electric vehicles’ (EV) battery module assembly. The experimental results revealed that the proposed method improved the training practices and performance through increases in the knowledge retention levels from 40% to 84%, and accuracy of task execution from 20% to 71%, when compared to the traditional paper-based method. The results of this research validate and demonstrate how emerging technologies are advancing the choice for manual, hybrid or fully automated processes by promoting the XR-assisted processes, and the connected worker (a vision for Industry 4 and 5.0), and supporting manufacturing become more resilient in times of constant market changes.

Keywords: Augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly 4.0, industry 5.0, smart training, battery assembly.

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Authors: Mohammad Heidari

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Horizontal wells are proven to be better producers because they can be extended for a long distance in the pay zone. Engineers have the technical means to forecast the well productivity for a given horizontal length. However, experiences have shown that the actual production rate is often significantly less than that of forecasted. It is a difficult task, if not impossible to identify the real reason why a horizontal well is not producing what was forecasted. Often the source of problem lies in the drilling of horizontal section such as permeability reduction in the pay zone due to mud invasion or snaky well patterns created during drilling. Although drillers aim to drill a constant inclination hole in the pay zone, the more frequent outcome is a sinusoidal wellbore trajectory. The two factors, which play an important role in wellbore tortuosity, are the inclination and side force at bit. A constant inclination horizontal well can only be drilled if the bit face is maintained perpendicular to longitudinal axis of bottom hole assembly (BHA) while keeping the side force nil at the bit. This approach assumes that there exists no formation force at bit. Hence, an appropriate BHA can be designed if bit side force and bit tilt are determined accurately. The Artificial Neural Network (ANN) is superior to existing analytical techniques. In this study, the neural networks have been employed as a general approximation tool for estimation of the bit side forces. A number of samples are analyzed with ANN for parameters of bit side force and the results are compared with exact analysis. Back Propagation Neural network (BPN) is used to approximation of bit side forces. Resultant low relative error value of the test indicates the usability of the BPN in this area.

Keywords: Artificial Neural Network, BHA, Horizontal Well, Stabilizer.

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Authors: Manish K. Khandelwal, P. Bera, A. Chakrabarti

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This article presents a numerical study of the doublediffusive mixed convection in a vertical channel filled with porous medium by using non-equilibrium model. The flow is assumed fully developed, uni-directional and steady state. The controlling parameters are thermal Rayleigh number (RaT ), Darcy number (Da), Forchheimer number (F), buoyancy ratio (N), inter phase heat transfer coefficient (H), and porosity scaled thermal conductivity ratio (γ). The Brinkman-extended non-Darcy model is considered. The governing equations are solved by spectral collocation method. The main emphasize is given on flow profiles as well as heat and solute transfer rates, when two diffusive components in terms of buoyancy ratio are in favor (against) of each other and solid matrix and fluid are thermally non-equilibrium. The results show that, for aiding flow (RaT = 1000), the heat transfer rate of fluid (Nuf ) increases upto a certain value of H, beyond that decreases smoothly and converges to a constant, whereas in case of opposing flow (RaT = -1000), the result is same for N = 0 and 1. The variation of Nuf in (N, Nuf )-plane shows sinusoidal pattern for RaT = -1000. For both cases (aiding and opposing) the flow destabilize on increasing N by inviting point of inflection or flow separation on the velocity profile. Overall, the buoyancy force have significant impact on the non-Darcy mixed convection under LTNE conditions.

Keywords: buoyancy ratio, mixed convection, non-Darcy model, thermal non-equilibrium

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Authors: Z. Honarvar, M. Farhoodi, M. R. Khani, S. Shojaee-Aliabadi

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The purpose of the present study was to evaluate carboxymethyl cellulose (CMC) coated polypropylene (PP) films containing Zataria multiflora (ZEO) essential oils (4%) as an antimicrobial packaging for chicken breast stored at 4 °C. To increase PP film hydrophilicity, it was treated by atmospheric cold plasma prior to coating by CMC. Then, different films including PP, PP/CMC, PP/CMC containing 4% of ZEO were used for the chicken meat packaging in vapor phase. Total viable count and pseudomonads population and oxidative (TBA) changes of the chicken breast were analyzed during shelf life. Results showed that the shelf life of chicken meat kept in films containing ZEO improved from three to nine days compared to the control sample without any direct contact with the film. Study of oxygen barrier properties of bilayer film without essential oils (0.096 cm³ μm/m² d kPa) in comparison with PP film (416 cm³ μm/m² d kPa) shows that coating of PP with CMC significantly reduces oxygen permeation of the obtained packaging (P<0.05), which reduced aerobic bacteria growth. Chemical composition of ZEO was also evaluated by gas chromatography–mass spectrometry (GC–MS), and this shows that thymol was the main antimicrobial and antioxidant component of the essential oil. The results revealed that PP/CMC containing ZEO has good potential for application as active food packaging in indirect contact which would also improve sensory properties of product.

Keywords: Shelf life, chicken breast, polypropylene, carboxymethyl cellulose, essential oil.

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Authors: Y. R. Li, Y. Y. Wang

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After allowing direct flights from Mainland China to Taiwan, Chinese tourists increased according to Tourism Bureaustatistics. There are from 0.19 to 2 million tourists from 2008 to 2011. Mainland China has become the main source of Taiwan developing tourism industry. Taiwanese government should know more about comments from Chinese tourists to Taiwan in order toproperly market Taiwan tourism and enhance the overall quality of tourism. In order to understand Chinese visitors’ comments, this study adopts content analysis to analyze electronic word-of-mouth on Web. This study collects 375 blog articles of Chinese tourists from Ctrip.com as a database during 2009 to 2011. Through the qualitative data analysis the traveling destination imagesis divided into seven dimensions, such as senic spots, shopping, food and beverages, accommodations, transportation, festivals and recreation activities. Finally, this study proposes some practical managerial implication to know both positive and negative images of the seven dimensions from Chinese tourists, providing marketing strategies and suggestions to traveling agency industry.

Keywords: Destination Image, Content Analysis, Electronic Word-of-Mouth.

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Authors: Frank Emmert Streib

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The classification of the protein structure is commonly not performed for the whole protein but for structural domains, i.e., compact functional units preserved during evolution. Hence, a first step to a protein structure classification is the separation of the protein into its domains. We approach the problem of protein domain identification by proposing a novel graph theoretical algorithm. We represent the protein structure as an undirected, unweighted and unlabeled graph which nodes correspond the secondary structure elements of the protein. This graph is call the protein graph. The domains are then identified as partitions of the graph corresponding to vertices sets obtained by the maximization of an objective function, which mutually maximizes the cycle distributions found in the partitions of the graph. Our algorithm does not utilize any other kind of information besides the cycle-distribution to find the partitions. If a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. As stop criterion, we calculate numerically a significance level which indicates the stability of the predicted partition against a random rewiring of the protein graph. Hence, our algorithm terminates automatically its iterative application. We present results for one and two domain proteins and compare our results with the manually assigned domains by the SCOP database and differences are discussed.

Keywords: Graph partitioning, unweighted graph, protein domains.

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Authors: J. C. M. Santos, J. C. A. Sousa, A. J. Rubio, L. S. Soletti, F. Gasparotto, N. U. Yamaguchi

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Magnetic graphene has received widespread attention for their capability of water and wastewater treatment, which has been attracted many researchers in this field. A bibliometric analysis based on the Web of Science database was employed to analyze the global scientific outputs of magnetic graphene for water treatment until the present time (2012 to 2017), to improve the understanding of the research trends. The publication year, place of publication, institutes, funding agencies, journals, most cited articles, distribution outputs in thematic categories and applications were analyzed. Three major aspects analyzed including type of pollutant, treatment process and composite composition have further contributed to revealing the research trends. The most relevant research aspects of the main technologies using magnetic graphene for water treatment were summarized in this paper. The results showed that research on magnetic graphene for water treatment goes through a period of decline that might be related to a saturated field and a lack of bibliometric studies. Thus, the result of the present work will lead researchers to establish future directions in further studies using magnetic graphene for water treatment.

Keywords: Composite, graphene oxide, nanomaterials, scientometrics.

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Authors: Hanan Ahmed-Hosni Mahmoud, Nadia Al-Ghreimil

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In-place sorting algorithms play an important role in many fields such as very large database systems, data warehouses, data mining, etc. Such algorithms maximize the size of data that can be processed in main memory without input/output operations. In this paper, a novel in-place sorting algorithm is presented. The algorithm comprises two phases; rearranging the input unsorted array in place, resulting segments that are ordered relative to each other but whose elements are yet to be sorted. The first phase requires linear time, while, in the second phase, elements of each segment are sorted inplace in the order of z log (z), where z is the size of the segment, and O(1) auxiliary storage. The algorithm performs, in the worst case, for an array of size n, an O(n log z) element comparisons and O(n log z) element moves. Further, no auxiliary arithmetic operations with indices are required. Besides these theoretical achievements of this algorithm, it is of practical interest, because of its simplicity. Experimental results also show that it outperforms other in-place sorting algorithms. Finally, the analysis of time and space complexity, and required number of moves are presented, along with the auxiliary storage requirements of the proposed algorithm.

Keywords: Auxiliary storage sorting, in-place sorting, sorting.

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Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik

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We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.

Keywords: Noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping.

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Authors: Haleem K. Hussain, Liu Gui Wei, Zhang Lian Zhen, Yongxue Li

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It is necessary to evaluate the bridges conditions and strengthen bridges or parts of them. The reinforcement necessary due to some reasons can be summarized as: First, a changing in use of bridge could produce internal forces in a part of structural which exceed the existing cross-sectional capacity. Second, bridges may also need reinforcement because damage due to external factors which reduced the cross-sectional resistance to external loads. One of other factors could listed here its misdesign in some details, like safety of bridge or part of its.This article identify the design demands of Qing Shan bridge located in is in Heilongjiang Province He gang - Nen Jiang Road 303 provincial highway, Wudalianchi area, China, is an important bridge in the urban areas. The investigation program was include the observation and evaluate the damage in T- section concrete beams , prestressed concrete box girder bridges section in additional evaluate the whole state of bridge includes the pier , abutments , bridge decks, wings , bearing and capping beam, joints, ........etc. The test results show that the bridges in general structural condition are good. T beam span No 10 were observed, crack extended upward along the ribbed T beam, and continue to the T beam flange. Crack width varying between 0.1mm to 0.4mm, the maximum about 0.4mm. The bridge needs to be improved flexural bending strength especially at for T beam section.

Keywords: Field investigation, prestressed concrete box girder, maintenance, Qing Shan Bridge

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Martina Kanciruk, Jac W. Andrews, Tyrone Donnon

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The purpose of this study was to determine the significance of history of obesity for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, family history, parents, childhood, risk factors. Eleven studies of family history and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that family history of obesity is a significant risk factor of overweight and /or obesity in offspring; risk for offspring overweight and/or obesity associated with family history varies depending of the family members included in the analysis; and when family history of obesity is present, the offspring are at greater risk for developing obesity or overweight. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment.

Keywords: Childhood obesity, overweight, family history, risk factors, meta-analysis.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Copy detection, Adjacent pixel intensity difference quantization (APIDQ), DC image, Histogram feature.

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Authors: Abdallah S. Abdallah, A. Lynn Abbott, Mohamad Abou El-Nasr

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This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Keywords: Face detection, skin color segmentation, self-organizingmap.

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Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

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One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: Energy-efficient buildings. energy management systems, government buildings, JENOSYS.

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Authors: Zaza Tabagari, Zaza Sanikidze, George Giorgobiani

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Abovepresented work deals with the new scope of application of information and communication technologies for the improvement of the election process in the biased environment. We are introducing a new concept of construction of the information-communication system for the election participant. It consists of four main components: Software, Physical Infrastructure, Structured Information and the Trained Stuff. The Structured Information is the bases of the whole system and is the collection of all possible events (irregularities among them) at the polling stations, which are structured in special templates, forms and integrated in mobile devices.The software represents a package of analytic modules, which operates with the dynamic database. The application of modern communication technologies facilities the immediate exchange of information and of relevant documents between the polling stations and the Server of the participant. No less important is the training of the staff for the proper functioning of the system. The e-training system with various modules should be applied in this respect. The presented methodology is primarily focused on the election processes in the countries of emerging democracies.It can be regarded as the tool for the monitoring of elections process by the political organization(s) and as one of the instruments to foster the spread of democracy in these countries.

Keywords: ICT, elections, structured information, dynamic databases, e-training.

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Authors: Abhishek Agarwal, Manoj Sarda, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

Abstract:

Propagation of fire through a non-air conditioned railway compartment is studied by virtue of numerical simulations. Simultaneous computational fire dynamics equations, such as Navier-Stokes, lumped species continuity, overall mass and energy conservation, and heat transfer are solved using finite volume based (for radiation) and finite difference based (for all other equations) solver, Fire Dynamics Simulator (FDS). A single coupe with an eight berth occupancy is used to establish the numerical model, followed by the selection of a three coupe system as the fundamental unit of the locomotive compartment. Heat Release Rate Per Unit Area (HRRPUA) of the initial fire is varied to consider a wide range of compartmental fires. Parameters, such as air inlet velocity relative to the locomotive at the windows, the level of interaction with the ambiance and closure of middle berth are studied through a wide range of numerical simulations. Almost all the loss of lives and properties due to fire breakout can be attributed to the direct or indirect exposure to flames or to the inhalation of toxic gases and resultant suffocation due to smoke and soot. Therefore, the temporal stature of fire and smoke are reported for each of the considered cases which can be used in the present or extended form to develop guidelines to be followed in case of a fire breakout.

Keywords: Fire dynamics, flame propagation, locomotive fire, soot flow pattern.

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Authors: Christina A. van Hal, Xiaoqian Jiang, Luyao Chen, Yan Chu, Robert D. Jolly, Yaobin Lin, Jitian Zhao, Kang Lin Hsieh

Abstract:

The COVID-19 Literature Summary App, now live on the university website, was created for the primary purpose of enabling academicians and clinicians to quickly sort through the vast array of recent coronavirus publications by topics of interest. Multiple methods of summarizing and sorting the manuscripts were created. A summary page introduces the application function and capabilities, while an interactive map provides daily updates on infection, death, and recovery rates. A page with a pivot table allows publication sorting by topic, with an interactive data table that allows sorting topics by columns, as wells as the capability to view abstracts. Additionally, publications may be sorted by the medical topics they cover. We used the CORD-19 database to compile lists of publications. The data table can sort binary variables, allowing the user to pick desired publication topics, such as papers that describe COVID-19 symptoms. The application is primarily designed for use by researchers but can be used by anybody who wants a faster and more efficient means of locating papers of interest. 

Keywords: COVID-19, literature summary, information retrieval, snorkel

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Authors: Chang, Chun-Lang, Liu, Chun-Kai

Abstract:

This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimization, the weight of each factor is calculated and obtained. In the meantime, Excel VBA and Case Based Reasoning are combined and adopted to evaluate the system. Results show no significant difference found through Genetic Algorithm Logistic Regression and Particle Swarm Optimization with over 97% accuracy in both methods. Both ROC areas are above 0.87. This study can provide critical reference to medical personnel as clinical assessment to effectively enhance medical care quality and efficiency, prevent unnecessary waste, and provide practical advantages to resource allocation to medical institutes.

Keywords: Total knee replacement, Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization.

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Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad

Abstract:

In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.

Keywords: Reliability, availability Gumbel-Hougaard family copula, MTTF, internet data center.

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