This study is to examine the effects of some significant factors on consumers' willingness to pay( WTP) for digital music via the moderating variables of music affinity and the deterrence effect of the legislation...This study is to examine the effects of some significant factors on consumers' willingness to pay( WTP) for digital music via the moderating variables of music affinity and the deterrence effect of the legislation. Based on 517 Chinese respondents with access to digital music,using the multiple liner regression model,this study indicates that free ideology,perceived benefits of free downloading,perceived benefits of paid downloading,subjective norm,habit strength have direct influence on WTP,and music affinity and the deterrence effect of the legislation have moderating effects. This study contributes theoretically to research on Chinese consumers' WTP for digital music and offers practical recommendations for the digital music charging system setup.展开更多
Communication is important for providing intelligent services in connected vehicles.Vehicles must be able to communicate with different places and exchange information while driving.For service operation,connected veh...Communication is important for providing intelligent services in connected vehicles.Vehicles must be able to communicate with different places and exchange information while driving.For service operation,connected vehicles frequently attempt to download large amounts of data.They can request data downloading to a road side unit(RSU),which provides infrastructure for connected vehicles.The RSU is a data bottleneck in a transportation system because data traffic is concentrated on the RSU.Therefore,it is not appropriate for a connected vehicle to always attempt a high speed download from the RSU.If the mobile network between a connected vehicle and an RSU has poor connection quality,the efficiency and speed of the data download from the RSU is decreased.This problem affects the quality of the user experience.Therefore,it is important for a connected vehicle to connect to an RSU with consideration of the network conditions in order to try to maximize download speed.The proposed method maximizes download speed from an RSU using a machine learning algorithm.To collect and learn from network data,fog computing is used.A fog server is integrated with the RSU to perform computing.If the algorithm recognizes that conditions are not good for mass data download,it will not attempt to download at high speed.Thus,the proposed method can improve the efficiency of high speed downloads.This conclusion was validated using extensive computer simulations.展开更多
With the emergence and further development of the digital library, the approaches of information acquisition correspondingly change a lot. This paper makes a statistical analysis on the journal downloading and citatio...With the emergence and further development of the digital library, the approaches of information acquisition correspondingly change a lot. This paper makes a statistical analysis on the journal downloading and citation behaviors under the digital environment conceived by the National Science Library(NSL), Chinese Academy of Sciences(CAS). It can be seen that the development of digital resources has influenced scientific research behaviors. For example, the large quantity of full-text downloading will maintain; the trend of journal downloading behaviors is basically same as the journal citation behavior; journals with large quantity of full-text downloading also boast the high cited times, and vice versa. Furthermore, authors make a linear regression analysis, with the journal downloading amount as the independent variable and journal cited times as dependent variable. Then they also prove the positive correlation between the journal downloading and citation behaviors by means of Pearson's correlation coefficient formula.展开更多
App store provides rich information for software vendors and customers to understand the market of mobile applications. However, app store analysis don’t consider some vital factors such as version number, app descri...App store provides rich information for software vendors and customers to understand the market of mobile applications. However, app store analysis don’t consider some vital factors such as version number, app description and app name currently. In this paper we propose an approach that App Store Analysis can be used to predict app downloads. We use data mining to extract app name and description and app rank information etc. from the Wandoujia App Store and AppCha App Store. We use questionnaire and sentimentanalysis to quantify some app nonnumeric information. We revealed strong correlations app name score, app rank, app rating with app downloads by Spearman’s rank correlation analysis respectively. Finally, we establish a multiple nonlinear regression model which app downloads defined as dependent variable and three relevant attributes defined as independent variable. On average, 59.28 % of apps in Wandoujia App Store and 66.68 % of apps in AppCha App Store can be predicted accurately within threshold which error rate is 25 %. One can observe the more detailed classification of app store, the more accurate for regression modeling to predict app downloads. Our approach can help app developers to notice and optimize the vital factors which influence app downloads.展开更多
Free Download Manager（以下简称FDM）是一款免费的多点续传下载及管理的软件．支持HTTP、HTTPS and FTP的下载功能．支持多线程下载、计划任务下载．支持以目录列表查看。更绝的是，FDM还是可以下载整个网站的内容，用户可以设定下载...Free Download Manager（以下简称FDM）是一款免费的多点续传下载及管理的软件．支持HTTP、HTTPS and FTP的下载功能．支持多线程下载、计划任务下载．支持以目录列表查看。更绝的是，FDM还是可以下载整个网站的内容，用户可以设定下载子目录的层次深度．理论上可下载超过1000层的子目录网页和图像等内容。展开更多
The recent advances in wireless communication technology enable high-speed vehicles to download data from roadside units(RSUs). However, the data download volume of individual vehicle is rather restricted due to high ...The recent advances in wireless communication technology enable high-speed vehicles to download data from roadside units(RSUs). However, the data download volume of individual vehicle is rather restricted due to high mobility and limited transmission range of vehicles, bringing users poor performance. To address this issue, we exploit the combination of both clustering and carry-and-forward schemes in this paper. Our scheme coordinates the cooperation of multiple infrastructures, cluster formation in the same direction and data forwarding of reverse vehicles to facilitate the target vehicle to download large-size content in dark areas. The process of data dissemination and achievable data download volume are then derived and analyzed theoretically. Finally, we conduct extensive simulations to verify the performance of the proposed scheme. Results show significant benefits of the proposed scheme in terms of increasing data download volume and throughput.展开更多
文摘This study is to examine the effects of some significant factors on consumers' willingness to pay( WTP) for digital music via the moderating variables of music affinity and the deterrence effect of the legislation. Based on 517 Chinese respondents with access to digital music,using the multiple liner regression model,this study indicates that free ideology,perceived benefits of free downloading,perceived benefits of paid downloading,subjective norm,habit strength have direct influence on WTP,and music affinity and the deterrence effect of the legislation have moderating effects. This study contributes theoretically to research on Chinese consumers' WTP for digital music and offers practical recommendations for the digital music charging system setup.
文摘Communication is important for providing intelligent services in connected vehicles.Vehicles must be able to communicate with different places and exchange information while driving.For service operation,connected vehicles frequently attempt to download large amounts of data.They can request data downloading to a road side unit(RSU),which provides infrastructure for connected vehicles.The RSU is a data bottleneck in a transportation system because data traffic is concentrated on the RSU.Therefore,it is not appropriate for a connected vehicle to always attempt a high speed download from the RSU.If the mobile network between a connected vehicle and an RSU has poor connection quality,the efficiency and speed of the data download from the RSU is decreased.This problem affects the quality of the user experience.Therefore,it is important for a connected vehicle to connect to an RSU with consideration of the network conditions in order to try to maximize download speed.The proposed method maximizes download speed from an RSU using a machine learning algorithm.To collect and learn from network data,fog computing is used.A fog server is integrated with the RSU to perform computing.If the algorithm recognizes that conditions are not good for mass data download,it will not attempt to download at high speed.Thus,the proposed method can improve the efficiency of high speed downloads.This conclusion was validated using extensive computer simulations.
文摘With the emergence and further development of the digital library, the approaches of information acquisition correspondingly change a lot. This paper makes a statistical analysis on the journal downloading and citation behaviors under the digital environment conceived by the National Science Library(NSL), Chinese Academy of Sciences(CAS). It can be seen that the development of digital resources has influenced scientific research behaviors. For example, the large quantity of full-text downloading will maintain; the trend of journal downloading behaviors is basically same as the journal citation behavior; journals with large quantity of full-text downloading also boast the high cited times, and vice versa. Furthermore, authors make a linear regression analysis, with the journal downloading amount as the independent variable and journal cited times as dependent variable. Then they also prove the positive correlation between the journal downloading and citation behaviors by means of Pearson's correlation coefficient formula.
文摘App store provides rich information for software vendors and customers to understand the market of mobile applications. However, app store analysis don’t consider some vital factors such as version number, app description and app name currently. In this paper we propose an approach that App Store Analysis can be used to predict app downloads. We use data mining to extract app name and description and app rank information etc. from the Wandoujia App Store and AppCha App Store. We use questionnaire and sentimentanalysis to quantify some app nonnumeric information. We revealed strong correlations app name score, app rank, app rating with app downloads by Spearman’s rank correlation analysis respectively. Finally, we establish a multiple nonlinear regression model which app downloads defined as dependent variable and three relevant attributes defined as independent variable. On average, 59.28 % of apps in Wandoujia App Store and 66.68 % of apps in AppCha App Store can be predicted accurately within threshold which error rate is 25 %. One can observe the more detailed classification of app store, the more accurate for regression modeling to predict app downloads. Our approach can help app developers to notice and optimize the vital factors which influence app downloads.
文摘Free Download Manager（以下简称FDM）是一款免费的多点续传下载及管理的软件．支持HTTP、HTTPS and FTP的下载功能．支持多线程下载、计划任务下载．支持以目录列表查看。更绝的是，FDM还是可以下载整个网站的内容，用户可以设定下载子目录的层次深度．理论上可下载超过1000层的子目录网页和图像等内容。
基金supported by the National Natural Science Foundation of China under Grant No.61571350Key Research and Development Program of Shaanxi(Contract No.2017KW-004,2017ZDXM-GY-022)the 111 Project(B08038)
文摘The recent advances in wireless communication technology enable high-speed vehicles to download data from roadside units(RSUs). However, the data download volume of individual vehicle is rather restricted due to high mobility and limited transmission range of vehicles, bringing users poor performance. To address this issue, we exploit the combination of both clustering and carry-and-forward schemes in this paper. Our scheme coordinates the cooperation of multiple infrastructures, cluster formation in the same direction and data forwarding of reverse vehicles to facilitate the target vehicle to download large-size content in dark areas. The process of data dissemination and achievable data download volume are then derived and analyzed theoretically. Finally, we conduct extensive simulations to verify the performance of the proposed scheme. Results show significant benefits of the proposed scheme in terms of increasing data download volume and throughput.
