Because of the rapid growth of head-mounted displays and 5G networking deployment,360-degree video has become increasingly popular.To generate the real experience of a virtual environment,360-degree videos require an ...Because of the rapid growth of head-mounted displays and 5G networking deployment,360-degree video has become increasingly popular.To generate the real experience of a virtual environment,360-degree videos require an ultrahigh resolution and frame rate to cover an omnidirectional view.These two prerequisites impose challenges for the transmission bandwidth and storage capacity of 360-degree video streaming.To reduce bandwidth and storage waste while providing a good immersive experience,we propose an optimized viewport-adaptive 360-degree video streaming method using high-efficiency video coding tiling,motion-constrained tile sets and MPEG dynamic adaptive streaming over HTTP spatial relationship description.The paper describes the rigorous design of the optimized system,which can assign different bitrates to different tiles in the viewport.The experimental results show that the proposed streaming system compares favourably with existing methods in terms of bitrate savings and storage capacity reduction.展开更多
Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology...Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology.However,traditional variance estimator is highly affected in the presence of extreme values.So this paper initially,proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics(L-location,Lscale,L-CV)and auxiliary information.It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than adapted ones.Artificial data is considered for assessing the performance of the proposed estimators.We also demonstrated an application related to apple fruit for purposes of the article.Using artificial and real data sets,percentage relative efficiency(PRE)of the proposed class of estimators with respect to adapted ones are calculated.The PRE results indicate to the superiority of the proposed class over adapted ones in the presence of extreme values.In this manner,the proposed class of estimators could be applied over an expansive range of survey sampling whenever auxiliary information is available in the presence of extreme values.展开更多
An investigation has been carried out to understand the contamination characteristics of roadside dust in the industrial area of Islamabad, Pakistan. The amounts of Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu,...An investigation has been carried out to understand the contamination characteristics of roadside dust in the industrial area of Islamabad, Pakistan. The amounts of Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Pb,Zn, Ga, As, Se and Cd were determined from 95 roadside dust samples collected along the Islamabad industrial area using Proton Induced X-ray Emission(PIXE). The results indicated that concentrations of all elements,except Cd, in the roadside dust were significant. The results of the enrichment factor show that the elementary composition of the roadside dust could be categorized as soil elements from the crust of the earth and elements from anthropogenic pollution. The high enrichment factors imply that elements such Cr, Cu, Pb, Zn, As, Se,Cd, Ni, Co and S came from anthropogenic activities. The source of metal contamination was identified using multivariate statistical analysis. It has been concluded that Ca, Sc, Ti, V, Mn and Fe mainly originate from crustal sources; Cr, Cu, Ni, Pb, Zn and Ga are associated with point-sources from industrial pollution/traffic;and S, Cl, K, As and Se are mainly related to oil/coal combustion.展开更多
Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the pr...Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values,and thus its results cannot be relied on.Finding momentum from Koyuncu’s recent work,the present paper focuses first on proposing two classes of variance estimators based on linear moments(L-moments),and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments(L-location,L-cv,L-variance).Three populations are taken into account to assess the efficiency of the new estimators.The first and second populations are concerned with artificial data,and the third populations is concerned with real data.The percentage relative efficiency of the proposed estimators over existing ones is evaluated.In the presence of extreme values,our findings depict the superiority and high efficiency of the proposed classes over traditional classes.Hence,when auxiliary data is available along with extreme values,the proposed classes of estimators may be implemented in an extensive variety of sampling surveys.展开更多
This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard refe...This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials（SRMs） were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 Me V obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.展开更多
基金Supported by funding (100%) from the Department of Science and Technology, New Delhi through the Fast Track Young Scientist Project Award to Dr. Imtiyaz Murtaza, No. SR/FTP/LS-A-91/2001
基金National Natural Science Foundation of China,Grant/Award Numbers:61967012,61866022,61861027。
文摘Because of the rapid growth of head-mounted displays and 5G networking deployment,360-degree video has become increasingly popular.To generate the real experience of a virtual environment,360-degree videos require an ultrahigh resolution and frame rate to cover an omnidirectional view.These two prerequisites impose challenges for the transmission bandwidth and storage capacity of 360-degree video streaming.To reduce bandwidth and storage waste while providing a good immersive experience,we propose an optimized viewport-adaptive 360-degree video streaming method using high-efficiency video coding tiling,motion-constrained tile sets and MPEG dynamic adaptive streaming over HTTP spatial relationship description.The paper describes the rigorous design of the optimized system,which can assign different bitrates to different tiles in the viewport.The experimental results show that the proposed streaming system compares favourably with existing methods in terms of bitrate savings and storage capacity reduction.
基金The authors are grateful to the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for funding this study through the research groups program under project number R.G.P.2/67/41.Ibrahim Mufrah Almanjahie received the grant.
文摘Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology.However,traditional variance estimator is highly affected in the presence of extreme values.So this paper initially,proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics(L-location,Lscale,L-CV)and auxiliary information.It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than adapted ones.Artificial data is considered for assessing the performance of the proposed estimators.We also demonstrated an application related to apple fruit for purposes of the article.Using artificial and real data sets,percentage relative efficiency(PRE)of the proposed class of estimators with respect to adapted ones are calculated.The PRE results indicate to the superiority of the proposed class over adapted ones in the presence of extreme values.In this manner,the proposed class of estimators could be applied over an expansive range of survey sampling whenever auxiliary information is available in the presence of extreme values.
文摘An investigation has been carried out to understand the contamination characteristics of roadside dust in the industrial area of Islamabad, Pakistan. The amounts of Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Pb,Zn, Ga, As, Se and Cd were determined from 95 roadside dust samples collected along the Islamabad industrial area using Proton Induced X-ray Emission(PIXE). The results indicated that concentrations of all elements,except Cd, in the roadside dust were significant. The results of the enrichment factor show that the elementary composition of the roadside dust could be categorized as soil elements from the crust of the earth and elements from anthropogenic pollution. The high enrichment factors imply that elements such Cr, Cu, Pb, Zn, As, Se,Cd, Ni, Co and S came from anthropogenic activities. The source of metal contamination was identified using multivariate statistical analysis. It has been concluded that Ca, Sc, Ti, V, Mn and Fe mainly originate from crustal sources; Cr, Cu, Ni, Pb, Zn and Ga are associated with point-sources from industrial pollution/traffic;and S, Cl, K, As and Se are mainly related to oil/coal combustion.
基金The authors thank the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for funding this study through the research groups program under Project Number R.G.P.1/64/42.Ishfaq Ahmad and Ibrahim Mufrah Almanjahie received the grant.
文摘Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values,and thus its results cannot be relied on.Finding momentum from Koyuncu’s recent work,the present paper focuses first on proposing two classes of variance estimators based on linear moments(L-moments),and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments(L-location,L-cv,L-variance).Three populations are taken into account to assess the efficiency of the new estimators.The first and second populations are concerned with artificial data,and the third populations is concerned with real data.The percentage relative efficiency of the proposed estimators over existing ones is evaluated.In the presence of extreme values,our findings depict the superiority and high efficiency of the proposed classes over traditional classes.Hence,when auxiliary data is available along with extreme values,the proposed classes of estimators may be implemented in an extensive variety of sampling surveys.
文摘This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials（SRMs） were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 Me V obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.
