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11.
Fereshteh Falah Chamasemani Lilly Suriani Affendey Norwati Mustapha Fatimah Khalid 《成像科学杂志》2018,66(3):184-194
Retrieving the most relevant video frames that contain the object specified in a given query (query-by-region) remains a challenging task. Two common challenges of region-based retrieval approaches are to accurately extract or segment object(s) and select a proper matching strategy. This paper addresses these problems by proposing a retrieval approach that uses a new region-based matching technique equipped with an effective object representation method. In the first stage, the proposed approach selects the most informative instances of each object that appeared in the video by utilizing an adapted clustering algorithm over the extracted features. In the retrieval stage, the new matching technique returns the most relevant sequences of video by mapping a given region with those identified representative instances of objects based on their similarity scores. The proposed approach is evaluated on standard datasets and the results demonstrate a 31% improvement in the retrieval performance compared to other state-of-the-art methods. 相似文献
12.
Khalid M. Hosny 《Information Sciences》2010,180(11):2299-3651
A new method is proposed for fast and accurate computation of Zernike moments. This method presents a novel formula for computing exact Zernike moments by using exact complex moments where the exact values of complex moments are computed by mathematical integration of the monomials over digital image pixels. The proposed method is applicable to compute the full set of Zernike moments as well as the subsets of individual order, repetition and an individual moment. A comparison with other conventional methods is performed. The results show the superiority of the proposed method. 相似文献
13.
Visualization and clustering of categorical data with probabilistic self-organizing map 总被引:1,自引:1,他引:0
This paper introduces a self-organizing map dedicated to clustering, analysis and visualization of categorical data. Usually,
when dealing with categorical data, topological maps use an encoding stage: categorical data are changed into numerical vectors
and traditional numerical algorithms (SOM) are run. In the present paper, we propose a novel probabilistic formalism of Kohonen
map dedicated to categorical data where neurons are represented by probability tables. We do not need to use any coding to
encode variables. We evaluate the effectiveness of our model in four examples using real data. Our experiments show that our
model provides a good quality of results when dealing with categorical data. 相似文献
14.
Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin
Zia ul-Haq Salman Tariq Muhammad Ali Khalid Mahmood Asim Daud Rana 《International journal of remote sensing》2016,37(13):3021-3041
This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO2) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO2 from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO2 column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO2 column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO2 column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO2 columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO2. A detailed analysis of volcanic SO2 transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO2 at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO2 enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO2. For the first time, we present significant influence of volcanic SO2 from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO2 levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively. 相似文献
15.
Murad Khan Awais Ahmad Shehzad Khalid Syed Hassan Ahmed Sohail Jabbar Jamil Ahmad 《Multimedia Tools and Applications》2017,76(23):24649-24674
Vertical handover gain significant importance due to the enhancements in mobility models by the Fourth Generation (4G) technologies. However, these enhancements are limited to specific scenarios and hence do not provide support for generic mobility. Similarly, various schemes are proposed based on these mobility models but most of them are suffered from the high packet loss, frequent handovers, too early and late handovers, inappropriate network selection, etc. To address these challenges, a generic vertical handover management scheme for heterogeneous wireless networks is proposed in this article. The proposed scheme works in three phases. In the first phase, a handover triggering approach is designed to identify the appropriate place for initiating handover based on the estimated coverage area of a WLAN access point or cellular base station. In the second phase, fuzzy rule based system is designed to eliminate the inappropriate networks before deciding an optimal network for handover. In the third phase, a network selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. The proposed scheme is tested in a mobility scenario with different speeds of a mobile node ranging from very low to very high. The simulation results are compared with the existing decision models used for network selection and handover triggering approaches. The proposed scheme outperforms these schemes in terms of energy consumption, handover delay and time, packet loss, good put, etc. 相似文献
16.
A steady and laminar convective flow has been numerically simulated in the fully-developed annular region of a finned double-pipe subjected to the constant heat flux boundary condition imposed at the inner-pipe wall. Finite element method has been employed in this study. Friction factor and Nusselt number have been studied as flow characteristics against variations in the ratio of radii of the inner and the outer pipes, the fin height, the fin half angle and the number of fins. The results show significant enhancement in the heat transfer rate in both the cases when sufficient pumping power is available and when it is not. The minimum and maximum increase in the product of friction factor and Reynolds number relative to the finless geometry is more than one time and more than 40 times respectively while gain in the relative value of Nusselt number lies in the range 1–177. This provides an evidence of more than four times enhancement in the heat transfer coefficient relative to that in the pressure loss as a result of extended fin surfaces. 相似文献
17.
Khalid M. Hosny 《Pattern recognition letters》2011,32(6):795-804
Image representation by using polynomial moments is an interesting theme. In this paper, image representation by using orthogonal Gegenbauer function is presented. A novel method for accurate and fast computation of orthogonal Gegenbauer moments is proposed. The accurate values of Gegenbauer moments are obtained by mathematically integrating Gegenbauer polynomials multiplied by their weight functions over the digital image pixels. A novel recurrence formula is derived for the kernel generation. The proposed method removes the numerical approximation errors involved in conventional method. A fast algorithm is proposed to accelerate the moment’s computations. A comparison with the conventional method is performed. The obtained results explain the efficiency and the superiority of the proposed method. 相似文献
18.
Boulahya K Ruiz-González L Parras M González-Calbet JM Nickolsky MS Nicolopoulos S 《Ultramicroscopy》2007,107(6-7):445-452
Two complex perovskite-related structures were solved by ab initio from precession electron diffraction intensities. Structure models were firstly derived from HREM images and than have been confirmed independently using two and three-dimensional sets of precession intensities. Patterson techniques prove to be effective for ab initio structure resolution, specially in case of projections with no overlapping atoms. Quality of precession intensity data may be suitable enough to resolve unknown heavy oxide structures. 相似文献
19.
Mo Chen Xiaojuan Wang Mingshu He Lei Jin Khalid Javeed Xiaojun Wang 《计算机、材料和连续体(英文)》2020,64(2):941-959
Attacks on websites and network servers are among the most critical threats in
network security. Network behavior identification is one of the most effective ways to
identify malicious network intrusions. Analyzing abnormal network traffic patterns and
traffic classification based on labeled network traffic data are among the most effective
approaches for network behavior identification. Traditional methods for network traffic
classification utilize algorithms such as Naive Bayes, Decision Tree and XGBoost.
However, network traffic classification, which is required for network behavior
identification, generally suffers from the problem of low accuracy even with the recently
proposed deep learning models. To improve network traffic classification accuracy thus
improving network intrusion detection rate, this paper proposes a new network traffic
classification model, called ArcMargin, which incorporates metric learning into a
convolutional neural network (CNN) to make the CNN model more discriminative.
ArcMargin maps network traffic samples from the same category more closely while
samples from different categories are mapped as far apart as possible. The metric learning
regularization feature is called additive angular margin loss, and it is embedded in the
object function of traditional CNN models. The proposed ArcMargin model is validated
with three datasets and is compared with several other related algorithms. According to a
set of classification indicators, the ArcMargin model is proofed to have better
performances in both network traffic classification tasks and open-set tasks. Moreover, in
open-set tasks, the ArcMargin model can cluster unknown data classes that do not exist in
the previous training dataset. 相似文献
20.
Aleena Kiran Majid Niaz Akhtar Muhammad Yousaf Khalid Mujassam Batoo Omar M.Aldossary Salman Naeem Khan 《中国稀土学报(英文版)》2021,39(10):1224-1231
Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications. 相似文献