This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Fi...This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.展开更多
In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mo...In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.展开更多
The construction industry, known for its low productivity, is increasingly utilising software and mobile apps to enhance efficiency. However, more comprehensive research is needed to understand the effectiveness of th...The construction industry, known for its low productivity, is increasingly utilising software and mobile apps to enhance efficiency. However, more comprehensive research is needed to understand the effectiveness of these technology applications. The PRISMA principles utilised a scoping review methodology to ascertain pertinent studies and extract significant findings. From 2013 onwards, articles containing data on mobile applications or software designed to enhance productivity in the construction sector were obtained from multiple databases, including Emerald Insight, Science Direct, IEEE Xplore, and Google Scholar. After evaluating 2604 articles, 30 were determined to be pertinent to the study and were subsequently analysed for the review. The review identified five key themes: effectiveness, benefits, successful implementation examples, obstacles and limitations, and a comprehensive list of software and mobile apps. In addition, 71 software and mobile apps have shown potentially how these technologies can improve communication, collaboration, project management, real-time collaboration, document management, and on-the-go project information and estimating processes in the construction industry, increasing efficiency and productivity. The findings highlight the potential of these technologies such as Automation, Radio-Frequency Identification (RFID), Building Information Modeling (BIM), Augmented Reality (AR), Virtual Reality (VR), and Internet of Things (IoT) to improve efficiency and communication in the construction industry. Despite challenges such as cost, lack of awareness, resistance to change, compatibility concerns, human resources, technological and security concerns and licensing issues, the study identifies specific mobile applications and software with the potential to enhance efficiency significantly, improve productivity and streamline workflows. The broader societal impacts of construction software and mobile app development include increased efficiency, job creation, and sustainability.展开更多
To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors a...To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.展开更多
The security of mobile agent directly decides its usage width in e-commerce. Especially, to protect users＇ private information is becoming more important now and future. So an anonymous mobile agent security mechanis...The security of mobile agent directly decides its usage width in e-commerce. Especially, to protect users＇ private information is becoming more important now and future. So an anonymous mobile agent security mechanism with the secure authentication infrastructure based on PKI （public key infrastructure） is proposed in the paper. The multi-agent system is programmed by java language and every agent must register itself in CA （certificate authority） before working in the net and express his legit identity which is temptly produced and used only once. The CA ensures the legal of all agents＇ identity which take part in communicaiton or trade. And every user agent identity only is used once which makes other agents cannot decipher users＇ private information. The security mechanism of the multi-agent system implements anonymity, integrity, data confidentiality of mobile agent based on the MH（multiple hop） integrity protection regard to PKI limit.展开更多
This paper analyzed the service supply chain of the domestic industry, tourist industry, information service industry in the mobile e-business environment, according to the function of different participators in suppl...This paper analyzed the service supply chain of the domestic industry, tourist industry, information service industry in the mobile e-business environment, according to the function of different participators in supply chain and their relationship between each other, this paper obtained different patterns of different industry in the mobile e-commerce environment.展开更多
Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based ter...Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based termination of cached apps is a widely adopted approach when free space of the main memory is running low.However,the LRUbased cached app termination does not distinguish between frequently or infrequently used apps.The app launch performance degrades if LRU terminates frequently used apps.Recent studies have suggested the potential of using users’app usage patterns to predict the next app launch and address the limitations of the current least recently used(LRU)approach.However,existing methods only focus on predicting the probability of the next launch and do not consider how soon the app will launch again.In this paper,we present a new approach for predicting future app launches by utilizing the relaunch distance.We define the relaunch distance as the interval between two consecutive launches of an app and propose a memory management based on app relaunch prediction(M2ARP).M2ARP utilizes past app usage patterns to predict the relaunch distance.It uses the predicted relaunch distance to determine which apps are least likely to be launched soon and terminate them to improve the efficiency of the main memory.展开更多
Mobile learning is the general trend of the times and the inevitable choice for the reform and development of college English teaching.This article attempts to use blended learning theory,mobile learning theory,and in...Mobile learning is the general trend of the times and the inevitable choice for the reform and development of college English teaching.This article attempts to use blended learning theory,mobile learning theory,and instructional design theory as a guide.In many English mobile learning apps,Superstar Learning Link is used as an example to design an online and offline blended teaching mode.It proposes thinking expansion and interaction in pre-class stage.Consolidation of input and outputoriented process are during class and evaluation and sublimation are made after class.The essay is aimed to break the boundaries between traditional teaching and mobile learning,combining synchronous learning with personalized learning in order to improve comprehensive levels of English.展开更多
Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collec...Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collected via a Web-based survey. Data analysis of this study can be divided into two stages. In the first stage, a descriptive statistical analysis was conducted based on a sample of 612 respondents. In the second stage, the correlation among content originality, user experience and satisfaction was analyzed based on a sample of 377 mobile news apps users. Findings: Results of the first stage showed that social media and mobile news apps were the most important tools for users to access news, and different types of media were playing complementary roles in information transmission. Users held a positive attitude toward their mobile news reading experience and they described news they read on mobile apps with such words as "interesting", "instant", "positive", "profound", and "ironic". Results of the second stage confirmed our hypothesis that content originality and user experience both had positive impacts on user satisfaction.Research limitations: The questionnaires were distributed entirely online, so the sample may not be representative of the general population being studied and thus undermine the reliability and generalization of the findings to some extent. Moreover, this study adopted only one method(survey) and more methods such as interviews can be used to improve the accuracy of the results.Practical implications: The findings of this study can not only provide insights into a better understanding of users’ mobile reading behavior, but also help mobile information service providers attract more users.Originality/value: This is one of the first studies to explore the effects of content originality and user experience on online news readers’ satisfaction with the mobile apps service.展开更多
基金Phased Research Key Project of Shanghai China Vocational Education Association“Research on Digital Transformation Path of Vocational Education Driven by AIGC from the Perspective of New Quality Productivity”,Phased Research Project of Shanghai Computer Industry Association“The Reform and Exploration of Cross-border E-commerce Talent Cultivation in Vocational Colleges from the Perspective of Industry Education Integration”(Project No.sctakt202404)。
文摘This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.
文摘In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user comments.However, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.
文摘The construction industry, known for its low productivity, is increasingly utilising software and mobile apps to enhance efficiency. However, more comprehensive research is needed to understand the effectiveness of these technology applications. The PRISMA principles utilised a scoping review methodology to ascertain pertinent studies and extract significant findings. From 2013 onwards, articles containing data on mobile applications or software designed to enhance productivity in the construction sector were obtained from multiple databases, including Emerald Insight, Science Direct, IEEE Xplore, and Google Scholar. After evaluating 2604 articles, 30 were determined to be pertinent to the study and were subsequently analysed for the review. The review identified five key themes: effectiveness, benefits, successful implementation examples, obstacles and limitations, and a comprehensive list of software and mobile apps. In addition, 71 software and mobile apps have shown potentially how these technologies can improve communication, collaboration, project management, real-time collaboration, document management, and on-the-go project information and estimating processes in the construction industry, increasing efficiency and productivity. The findings highlight the potential of these technologies such as Automation, Radio-Frequency Identification (RFID), Building Information Modeling (BIM), Augmented Reality (AR), Virtual Reality (VR), and Internet of Things (IoT) to improve efficiency and communication in the construction industry. Despite challenges such as cost, lack of awareness, resistance to change, compatibility concerns, human resources, technological and security concerns and licensing issues, the study identifies specific mobile applications and software with the potential to enhance efficiency significantly, improve productivity and streamline workflows. The broader societal impacts of construction software and mobile app development include increased efficiency, job creation, and sustainability.
文摘To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.
基金Supported by the National Natural Science Foun-dation of China (50077007) the Youth Teacher Foundation ofNorth China Electric Power University (20051101)
文摘The security of mobile agent directly decides its usage width in e-commerce. Especially, to protect users＇ private information is becoming more important now and future. So an anonymous mobile agent security mechanism with the secure authentication infrastructure based on PKI （public key infrastructure） is proposed in the paper. The multi-agent system is programmed by java language and every agent must register itself in CA （certificate authority） before working in the net and express his legit identity which is temptly produced and used only once. The CA ensures the legal of all agents＇ identity which take part in communicaiton or trade. And every user agent identity only is used once which makes other agents cannot decipher users＇ private information. The security mechanism of the multi-agent system implements anonymity, integrity, data confidentiality of mobile agent based on the MH（multiple hop） integrity protection regard to PKI limit.
文摘This paper analyzed the service supply chain of the domestic industry, tourist industry, information service industry in the mobile e-business environment, according to the function of different participators in supply chain and their relationship between each other, this paper obtained different patterns of different industry in the mobile e-commerce environment.
基金This work was supported in part by the National Research Foundation of Korea(NRF)Grant funded by the Korea Government(MSIT)under Grant 2020R1A2C100526513in part by the R&D Program for Forest Science Technology(Project No.2021338C10-2323-CD02)provided by Korea Forest Service(Korea Forestry Promotion Institute).
文摘Recently,various mobile apps have included more features to improve user convenience.Mobile operating systems load as many apps into memory for faster app launching and execution.The least recently used(LRU)-based termination of cached apps is a widely adopted approach when free space of the main memory is running low.However,the LRUbased cached app termination does not distinguish between frequently or infrequently used apps.The app launch performance degrades if LRU terminates frequently used apps.Recent studies have suggested the potential of using users’app usage patterns to predict the next app launch and address the limitations of the current least recently used(LRU)approach.However,existing methods only focus on predicting the probability of the next launch and do not consider how soon the app will launch again.In this paper,we present a new approach for predicting future app launches by utilizing the relaunch distance.We define the relaunch distance as the interval between two consecutive launches of an app and propose a memory management based on app relaunch prediction(M2ARP).M2ARP utilizes past app usage patterns to predict the relaunch distance.It uses the predicted relaunch distance to determine which apps are least likely to be launched soon and terminate them to improve the efficiency of the main memory.
基金“Design and Practice of Blended Teaching Model in College English Based on Mobile Learning App”,the“Thirteenth Five-Year Plan”project on Education and Science of Heilongjiang Province in 2018(Project Number:GJC1318030)。
文摘Mobile learning is the general trend of the times and the inevitable choice for the reform and development of college English teaching.This article attempts to use blended learning theory,mobile learning theory,and instructional design theory as a guide.In many English mobile learning apps,Superstar Learning Link is used as an example to design an online and offline blended teaching mode.It proposes thinking expansion and interaction in pre-class stage.Consolidation of input and outputoriented process are during class and evaluation and sublimation are made after class.The essay is aimed to break the boundaries between traditional teaching and mobile learning,combining synchronous learning with personalized learning in order to improve comprehensive levels of English.
文摘Purpose: This study aims to explore whether content originality and user experience have positive effects on online news readers’ satisfaction with the mobile apps service.Design/methodology/approach: Data was collected via a Web-based survey. Data analysis of this study can be divided into two stages. In the first stage, a descriptive statistical analysis was conducted based on a sample of 612 respondents. In the second stage, the correlation among content originality, user experience and satisfaction was analyzed based on a sample of 377 mobile news apps users. Findings: Results of the first stage showed that social media and mobile news apps were the most important tools for users to access news, and different types of media were playing complementary roles in information transmission. Users held a positive attitude toward their mobile news reading experience and they described news they read on mobile apps with such words as "interesting", "instant", "positive", "profound", and "ironic". Results of the second stage confirmed our hypothesis that content originality and user experience both had positive impacts on user satisfaction.Research limitations: The questionnaires were distributed entirely online, so the sample may not be representative of the general population being studied and thus undermine the reliability and generalization of the findings to some extent. Moreover, this study adopted only one method(survey) and more methods such as interviews can be used to improve the accuracy of the results.Practical implications: The findings of this study can not only provide insights into a better understanding of users’ mobile reading behavior, but also help mobile information service providers attract more users.Originality/value: This is one of the first studies to explore the effects of content originality and user experience on online news readers’ satisfaction with the mobile apps service.
