Enhancement of Repository Based Agent Framework for Ubiquitous Environment

Author(s):  
Naoya Tatematsu ◽  
Takahiro Uchiya ◽  
Ichi Takumi ◽  
Tetsuo Kinoshita
2021 ◽  
pp. 096100062199641
Author(s):  
Irfan Ali ◽  
Nosheen Fatima Warraich

The purpose of this study is to explore Personal Digital Archiving, and its practices, reasons, and challenges in desktop and in ubiquitous environment such as desktop computers, laptops, mobile phones or smartphones, tablets, and cloud services. Moreover, it is also aimed to develop a model of Personal Digital Archiving process for desktop and ubiquitous devices. This study used Preferred Reporting Items for the Systematic Review and Meta-Analysis guidelines for searching and devising, and inclusion and exclusion criteria. The Search was conducted from selected repositories, databases, and core journals, potentially containing studies related with Personal Digital Archiving. Consequently, 21 studies were included through identification, screening, eligibility, and inclusion of studies process. It was found that people used multiple devices such as mobile phones or smartphones along with other devices. It was established that people had also used cloud services with different devices including computers and smartphones or tablets for Personal Digital Archiving. Five major categories of individuals’ Personal Digital Archiving practices, that is, backup, replication or duplication, reorganizing and updating, cleaning or removing, and migration of information were found. Moreover, emotional motives, technological causes, alternative access, easy retrieval, and task completion were the reasons to adopt Personal Digital Archiving. On the basis of findings of selected studies, researchers developed a four steps model of Personal Digital Archiving process, consisting of initiation, identification, action, and evaluation constructs. Personal Digital Archiving challenges were also identified such as the individuals had to face through the use of desktop and ubiquitous devices including technical, fragmented and overloaded information, lack of training and expertise, and psychological and miscellaneous challenges. Personal Digital Archiving process model is based on the extracted data from studies published worldwide, and it is useful for both desktop and ubiquitous devices with reference to Personal Information Management context. The findings of the study will be helpful for software designers and android application developers to design and develop users’ centered Personal Information Management software.


2015 ◽  
Vol 59 ◽  
pp. 459-467 ◽  
Author(s):  
Michael Yoseph Ricky ◽  
Robin Solala Gulo

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sonia Goel ◽  
Meena Tushir

Purpose In real-world decision-making, high accuracy data analysis is essential in a ubiquitous environment. However, we encounter missing data while collecting user-related data information because of various privacy concerns on account of a user. This paper aims to deal with incomplete data for fuzzy model identification, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features. Design/methodology/approach In this work, authors proposed a three-fold approach for fuzzy model identification in which imputation-based linear interpolation technique is used to estimate missing features of the data, and then fuzzy c-means clustering is used for determining optimal number of rules and for the determination of parameters of membership functions of the fuzzy model. Finally, the optimization of the all antecedent and consequent parameters along with the width of the antecedent (Gaussian) membership function is done by gradient descent algorithm based on the minimization of root mean square error. Findings The proposed method is tested on two well-known simulation examples as well as on a real data set, and the performance is compared with some traditional methods. The result analysis and statistical analysis show that the proposed model has achieved a considerable improvement in accuracy in the presence of varying degree of data incompleteness. Originality/value The proposed method works well for fuzzy model identification method, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features with varying degree of missing data as compared to some well-known methods.


Author(s):  
Satoshi Kurihara ◽  
Kensuke Fukuda ◽  
Toshio Hirotsu ◽  
Shigemi Aoyagi ◽  
Toshihiro Takada ◽  
...  

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