What if we could travel without passport? First sight to blockchain-based identity management in tourism

Blockchain technology, as a distributed digital ledger, enables users to control their credentials without being breached by third parties. From a tourism perspective, it allows tourists to pass through checkpoints and/or bookings without waiting and having to go through third-party transactions. Hence, this paper aims to discuss traditional identity management (IdM) system challenges and what blockchain might offer as a counterpoint to conventional travel experiences within th

Device profiling analysis in Device-Aware Network

As more and more devices with a variety of capabilities are Internet-capable, device independence becomes a big issue when we would like the information that we request to be correctly displayed. This thesis introduces and compares how existing standards create a profile that describes the device capabilities to achieve the goal of device independence. After acknowledging the importance of device independence, this paper utilizes the idea to introduce a Device-Aware Network (DAN). DAN provides the infrastructure support for device-content compatibility matching for data transmission. We identify the major components of the DAN architecture and issues associated with providing this new network service. A Device-Aware Network will improve the network's efficiency by preventing unusable data from consuming host and network resources. The device profile is the key issue to achieve this goal.http://archive.org/details/deviceprofilingn109451301Captain, Taiwan ArmyApproved for public release; distribution is unlimited

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Optical character recognition (OCR) is a technology to digitize a paper-based document to digital form. This research studies the extraction of the characters from a Thai vehicle registration certificate via a Google Cloud Vision API and a Tesseract OCR. The recognition performance of both OCR APIs is also examined. The 84 color image files comprised three image sizes/resolutions and five image characteristics. For suitable image type comparison, the greyscale and binary image are converted from color images. Furthermore, the three pre-processing techniques, sharpening, contrast adjustment, and brightness adjustment, are also applied to enhance the quality of image before applying the two OCR APIs. The recognition performance was evaluated in terms of accuracy and readability. The results showed that the Google Cloud Vision API works well for the Thai vehicle registration certificate with an accuracy of 84.43%, whereas the Tesseract OCR showed an accuracy of 47.02%. The highest accuracy came from the color image with 1024×768 px, 300dpi, and using sharpening and brightness adjustment as pre-processing techniques. In terms of readability, the Google Cloud Vision API has more readability than the Tesseract. The proposed conditions facilitate the possibility of the implementation for Thai vehicle registration certificate recognition system