Array DBMS in Environmental Science: Sea Surface Height Data in the Cloud
The Conference on Games (CoG) evolves from the traditional Computational Intelligence and Games (CIG) to bring together leading researchers and practitioners from academia and industry in the field of Games, to discuss recent advances and explore future directions. Games offer a fantastic domain for computational creativity, game design, technology, education, social sciences and, undoubtedly, artificial and computational intelligence. The annual IEEE Conference on Games (IEEE CoG) seeks to share insights and cutting-edge research related to game technologies and design, covering scientific, technical, and engineering aspects of games.
The TSP 2019 Conference is organized by seventeen universities from Czech Rep., Hungary, Turkey, Taiwan, Japan, Slovak Rep., Spain, Bulgaria, France, Slovenia, Croatia, Greece, and Poland, for academics, researchers, and developers and it serves as a premier annual international forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors from the whole Europe, America, Asia, Australia, and Africa. The international expansion motivates the organizers in their effort to providing a platform for exchanging information and experience to help to improve the level and extent of scientific cooperation between university students, academics, and employees of research centers.
The Eleventh International Conference on Advances in Multimedia (MMEDIA 2019), held between March 24, 2019 and March 28, 2019 in Valencia, Spain, continued a series of events presenting recent research results on advances in multimedia, mobile and ubiquitous multimedia and to bring together experts from both academia and industry for the exchange of ideas and discussion on future challenges in multimedia fundamentals, mobile and ubiquitous multimedia, multimedia ontology, multimedia user-centered perception, multimedia services and applications, and mobile multimedia.
Heaps are well-studied fundamental data structures, having myriads of applications, both theoretical and practical. We consider the problem of designing a heap with an “optimal” extract-min operation. Assuming an arbitrary linear ordering of keys, a heap with n elements typically takes O(log n) time to extract the min-imum. Extracting all elements faster is impossible as this would violate the Ω(n log n) bound for comparison-based sorting. It is known, however, that is takes only O(n + k log k) time to sort just k smallest elements out of n given, which prompts that there might be a faster heap, whose extract-min performance depends on the number of elements extracted so far. In this paper we show that is indeed the case. We present a version of heap that performs insert in O(1) time and takes only O(log ∗ n + log k) time to carry out the k-th extraction (where log ∗ denotes the iterated logarithm). All the above bounds are worst-case.
We assess and compare computer science skills among final-year computer science undergraduates (seniors) in four major economic and political powers that produce approximately half of the science, technology, engineering, and mathematics graduates in the world. We find that seniors in the United States substantially outperform seniors in China, India, and Russia by 0.76–0.88 SDs and score comparably with seniors in elite institutions in these countries. Seniors in elite institutions in the United States further outperform seniors in elite institutions in China, India, and Russia by ∼0.85 SDs. The skills advantage of the United States is not because it has a large proportion of high-scoring international students. Finally, males score consistently but only moderately higher (0.16–0.41 SDs) than females within all four countries.