Abstract This work is an attempt to address some issues related to practical hardware realization of power attack-resistant chaos-based encryption schemes. First, we introduce a new two-dimensional chaotic map based on a modified logistic-tent map. The proposed map has a very wide range of sustained chaotic and hyper-chaotic behavior over its large key parameters space. The presented map is practically realized using a digital field programmable gate array. Experimental validation of the map’s enhanced chaotic behavior is provided. Then the map is employed to efficiently generate chaotic clock signals appropriate for reliable image encryption applications. A proposed image encryption scheme which is driven by the generated chaotic clock signals is designed. The immunity against the powerful correlation power analysis attack is achieved in the proposed image encryption scheme even in the case when some secret key parameters of the encryption process are leaked. The present study paves the way to further explore how to build efficient chaos-based encryption schemes immune to other types of well-known effective attacks.

Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this article, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations. We present a new interactive application that provides an alignment overview of all the translations and their correspondences in parallel with smooth zooming and panning capability to integrate distant and close reading within the same view. We provide a range of filtering and selection options to customize the alignment overview as well as focus on specific subsets. Selection and filtering are responsive to expert user preferences and update the analytical text metrics interactively. Also, we introduce a customized view for close reading which preserves the history of selections and the alignment overview state and enables backtracing and re-examining them. Finally, we present a new Term-Level Comparisons view (TLC) to compare and convey relative term weighting in the context of an alignment. Our visual design is guided by, used and evaluated by a domain expert specialist in German translations of Shakespeare.

Visualization, as a vibrant field for researchers, practitioners, and higher educational institutions, is growing and evolving very rapidly. Tremendous progress has been made since 1987, the year often cited as the beginning of data visualization as a distinct field. As such, the number of visualization resources and the demand for those resources are increasing at a very fast pace. We present a collection of open visualization resources for all those with an interest in interactive data visualization and visual analytics. Because the number of resources is so large, we focus on collections of resources, of which there are already very many ranging from literature collections to collections of practitioner resources. We develop a novel classification of visualization resource collections based on the resource type, e.g. literature-based, web-based, etc. The result is a helpful overview and details-on-demand of many useful resources. The collection offers a valuable jump-start for those seeking out data visualization resources from all backgrounds spanning from beginners such as students to teachers, practitioners, and researchers wishing to create their own advanced or novel visual designs.

Digital humanities and translation scholars utilize off-the-shelf tools to align multiple related translations. These tools generally rely solely on domain expert knowledge and do not exploit the recent advancements in computational linguistics and text mining. This paper presents AlignVis, a visual tool that provides a semi-automatic alignment framework to align multiple translations. It presents the results of using text similarity measurements and enables the user to create, verify, and edit alignments using a novel visual interface. The design consists of three main components: the alignment editor canvas, the post-edit area, and the user options panel. AlignVis exploits both close and distant reading and is designed to help digital humanities and translation scholars enhance the process of text alignment for multiple translations. The design of AlignVis is driven by iterative discussions with the domain expert which resulted in five benefits: presenting an overview of the aligned translations, support for multiple alignments, enhancement and acceleration of the alignment process, alignment refinement, and testing different similarity measurements. We evaluate AlignVis with domain expert feedback and a comparison with a standard alignment tool and computational and visual alignment tools.