As you surf the Internet, an unprecedented amount of your personal information is being recorded and preserved forever in the digital minds of computers. Seven days a week, twenty-four hours a day, electronic databases are compiling information about you. These algorithms are extensible to tracking collocations of people, which is an objective of homeland defense surveillance. Successful re-identifications are reported for DNA sequences left by hospital patients and for IP addresses left by online consumers. The algorithms differ in the amount of completeness and multiplicity assumed in the data. The algorithms presented herein re-identify individuals based on the uniqueness of trails across unidentified and identified datasets. Exchanged customer lists provide identified data. Shared visit logs provide unidentified data. For example, an online consumer may visit 50 websites and purchase at 5 and another may visit 30 sites and purchase at 7. Intersecting occurrences in these two kinds of data can reveal identities. The 3 novel algorithms presented in this paper perform trail re-identifications by exploiting the fact that some locations also capture explicitly identifying information and subsequently provide the unidentified data and the identified data as separate data releases. This paper extends the concept to "trail re-identification" in which a person is related to a trail of seemingly anonymous and homogenous data left across different locations. Re- identification has historically been associated with data released from a single data holder. ![]() The term "re- identification" refers to correctly relating seemingly anonymous data to explicitly identifying information (such as the name or address) of the person who is the subject of those data. Many falsely believe they cannot be identified. Consider online consumers, who have the IP addresses of their computers logged at each website visited. This paper provides algorithms for learning the identities of individuals from the trails of seemingly anonymous information they leave behind. It achieved an accuracy of 95.86% for Arabic character recognition and 98.5% for English character recognition. Experimental results demonstrate the feasibility of the proposed prototype. Finally, the recognized characters are translated into speech using the text-to-speech (TTS) technology. The attached camera captures the printed Arabic text and passes it to the Arabic OCR system. It is designed as a wearable ring attached to a tiny webcam device. It is based on using a wearable device for a hand finger. In this paper, a real-time Arabic text-reading prototype for VI people is proposed. Recently, VI people prefer mobile devices because of their handiness and accessibility, but they have problems with focusing the mobile camera on the printed material. Current technologies such as flatbed scanners and OCR programs need to scan an entire page. These problems may include text alignment, focus, accuracy, software processing speed, mobility, and efficiency. Visually impaired (VI) people suffer from many difficulties when accessing printed material using existing technologies. ![]() The results also contribute to understanding the emerging market of mobile travel applications, further the proposed framework can be utilized in future studies as a baseline model Besides, Government agencies can benefit from the results of this study when providing mobile application services and distributing information to customers. This research provides some valuable implications for both apps developers and travel-related companies. In contrast, word of mouth has no effect on the intention to use. Results show a positive relationship of intention to use mobile travel applications from 6 constructs including aesthetics, trust, facilitating conditions, financial benefits, perceived usefulness, and perceived enjoyment. The SmartPLS version 3.0 was used to assess 14 hypotheses using 500 surveys. 7 predictors in this study have been carefully selected from previous studies conducted to date in the tourism context, and more specifically in the context of mobile travel applications. This exploratory study aims to investigate the intention to use mobile travel applications in Jordan.
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