l This book evolved from the ARCADE evaluation exercise that started in 1995. The project's goal is to evaluate alignment systems for parallel texts, i. e. , texts accompanied by their translation. Thirteen teams from various places around the world have participated so far and for the first time, some ten to fifteen years after the first alignment techniques were designed, the community has been able to get a clear picture of the behaviour of alignment systems. Several chapters in this book describe the details of competing systems, and the last chapter is devoted to the description of the evaluation protocol and results. The remaining chapters were especially commissioned from researchers who have been major figures in the field in recent years, in an attempt to address a wide range of topics that describe the state of the art in parallel text processing and use. As I recalled in the introduction, the Rosetta stone won eternal fame as the prototype of parallel texts, but such texts are probably almost as old as the invention of writing. Nowadays, parallel texts are electronic, and they are be­ coming an increasingly important resource for building the natural language processing tools needed in the "multilingual information society" that is cur­ rently emerging at an incredible speed. Applications are numerous, and they are expanding every day: multilingual lexicography and terminology, machine and human translation, cross-language information retrieval, language learning, etc.

Research on spatial cognition is a rapidly evolving interdisciplinary enterprise for the study of spatial representations and cognitive spatial processes, be they real or abstract, human or machine. Spatial cognition brings together a variety of - search methodologies: empirical investigations on human and animal orientation and navigation; studies of communicating spatial knowledge using language and graphical or other pictorial means; the development of formal models for r- resenting and processing spatial knowledge; and computer implementations to solve spatial problems, to simulate human or animal orientation and navigation behavior, or to reproduce spatial communication patterns. These approaches can interact in interesting and useful ways: Results from empirical studies call for formal explanations both of the underlying memory structures and of the processes operating upon them; we can develop and - plement operational computer models obeying the relationships between objects and events described by the formal models; we can empirically test the computer models under a variety of conditions, and we can compare the results to the - sults from the human or animal experiments. A disagreement between these results can provide useful indications towards the re nement of the models.

Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation.

This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis, and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning creates the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing.

Recently, remote sensing and GIS techniques have gained increasing importance for rapid urbanization, the expansion of urban growth, and the enlargement of populations, due to the application of artificial intelligence, machine learning, and deep learning algorithms. This Special Issue aims to present the state-of-the-art research on optics, SAR, hyperspectral images, and GIS techniques for monitoring urban area environments corresponding to changes in times using publicly available and commercial datasets such as satellite and UAV data.

The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.*
The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: