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关键词： Optimization   Prediction algorithms   Mobile robots   Computer science   Tracking   Cameras   Object detection   Autonomous mobile robots   fractional order difference   template tracking   prediction of moving object position  

摘要： Optimization techniques are nowadays one of the most important branches of computer science due to the limitations of the computing power availability especially in cases of mobile platforms. Algorithms which can be used on such units have to be optimized for memory and computing power. In the paper we focused on optimization techniques for image analysis algorithms by limiting the number of necessary operations. The optimized algorithm has been designed to detect and follow a specified marker, known a priori, and is based on the correlation coefficient match between the acquired template and the current image. The acquired template is taken from the previous processed frame. The match operation is based on Pearson's correlation coefficient, so the whole mechanism is therefore highly demanding in terms of computing power. Optimization is performed mainly using the Region of Interest (ROI) to exclude irrelevant parts of the image. The algorithm is optimized using Grunvald - Letnikov fractional - order backward difference to estimate the position of the marker in a sequence of images. This limits the number of operations required to maintain the precision of the algorithm. Based on the position of the object in previous frames, a fractional order mathematical tool is able to estimate at relatively low cost and with high accuracy the probable position of the object in the incoming image. Here, we explain the workflow of the template detection and following algorithm, as well as the mathematical basis of the fractional order derivative optimization tool. The processor load connected to the optimized algorithm was reduced by over 35%.

摘要： Background of global forum. To explore the nature of computer science and promote the development of computer science discipline, Tsinghua University organized the first global forum during the 60th anniversary of Computer Science in Tsinghua. The forum aimed to bring to- gether the heads/deans of the top computer science departments/schools in the world to discuss the fundamentals of computer science, improve the quality of talent cultivation,

关键词： Codes   Libraries   Recommender systems   Filtering   Measurement   Computer science   Labeling   Classification algorithms   Hybrid recommender systems   multi-label classification   digital libraries   universal decimal classification  

摘要： In this article we present a hybrid approach to recommending the Universal Decimal Classification (UDC) codes for unclassified documents. By recommending UDC codes to librarians, we can provide the decision support as part of a semi-automatic cataloguing process. As current approaches to recommending UDC codes are scarce and limited to certain fields of expertise, our motivation was to create a hybrid approach which covers all fields of expertise within the UDC hierarchy. The cascade hybrid approach combines the BM25 ranking function with a multi-label classifier based on a BERT (Bidirectional Encoder Representations from Transformers) deep neural network architecture. Additionally, lists of the most commonly used UDC codes within a document's origin organization are used as a final content-based filtering method. The BM25 ranking function is used to create an initial list of recommendations. The first cascade step re-ranks the initial list of recommendations using the list of recommendations produced by the multi-label BERT-based classifier. The second cascade step re-ranks the resulting recommendation list from the first cascade step using a list of most commonly used UDC codes within the document's organization. Finally, post-processing steps are applied to obtain the final list of recommended UDC codes. We present in detail the UDC structure, the used text corpus of documents and the functioning of our hybrid recommendation approach. We perform the analysis of the generated recommendation lists for the corpus from the Slovenian Open-Access Infrastructure using the metrics hit-ratio, normalized discounted cumulative gain, mean reciprocal rank and mean average precision. Our hybrid recommendation approach improves reference scores of individual methods for these metrics.

ISBN: (纸本)9781450395687

关键词： Computer science   Neuroscience   SARS-CoV-2   Seismology  

摘要： TheNature Podcastteam select some of their favourite stories from the past 12 months.

关键词： Protocols   Authentication   Radiofrequency identification   Privacy   Servers   Computer science   Internet of Things   Active tags   authentication   privacy   radio-frequency identification   RFID   security   zero-knowledge  

摘要： An RFID system is a contactless automatic identification technology and a solution to many business and personal applications. However, the privacy threats to RFID systems cause significant concerns in real RFID applications. Among the privacy issues in RFID systems, we are particularly interested in designing an RFID authentication protocol that achieves strong indistinguishability-based privacy (ind-privacy) and possesses the zero-knowledge property for active tags. In this article, a zero-knowledge authentication protocol (ZKAP) using quadratic residues is proposed. Then, an indistinguishability-based experiment using random oracles is modeled to prove that the proposed scheme achieves strong ind-privacy against active eavesdroppers. The zero-knowledge property is defined with respect to the tags' private information against dishonest readers, and that property of our ZKAP is proven by constructing a polynomial time simulator that generates a transcript with the same distribution as that of ZKAP. Finally, the proposed protocol is implemented in a Raspberry Pi and a PC, and the performance is evaluated in terms of authentication time. The experimental results demonstrate that our ZKAP achieves its design goals.

关键词： Geometry  

摘要： Here we present our arguments for a more in-depth study of the Boolean cube, which is one of the most important discrete structures. The article contains a case study that analyses how the Boolean cube has been included and explained in more than 80 different sources. However, organized material on the Boolean cube is lacking. We examine and show why the topic of the Boolean cube deserves to be studied in the course on Discrete Structures – a basic part of the Computer Science curriculum. The benefits of mastering such knowledge and programming skills are pointed out. A sample lecture on the n-dimensional Boolean cube (including selected exercises, their answers, hints or solutions) is developed and discussed. It introduces, generalizes and relates many concepts from different subjects in the area of Discrete Mathematics and outside it. So the lecturers can use the sample lecture when teaching those subjects. In this way, all these concepts become more understandable, applicable and useful to the students. The lecture can be taught in a form of presentation or given to the students for "Online self-learning", in order to write homework, or develop a course project related to the topic, etc. All supporting resources to the lecture are available for free use at [8].MSC Codes 68R01, 97N70 Copyright © 2021, The Authors. All rights reserved.

关键词： Computer science education   K12   Literature review  

摘要： Computer science education (CSEd) research within K-12 makes extensive use of empirical studies in which children participate. Insight in the demographics of these children is important for the purpose of understanding the representativeness of the populations included. This literature review studies the demographics of subjects included in K-12 CSEd studies. We have manually inspected the proceedings of three of the main international CSEd conferences: SIGCSE, ITiCSE and ICER, of five years (2014-2018), and selected all papers pertaining to K-12 CSEd experiments. This led to a sample of 134 papers describing 143 studies. We manually read these papers to determine the demographic information that was reported on, investigating the following categories: age/grade, gender, race/ethnic background, location, prior computer science experience, socio-economic status (SES), and disability. Our findings show that children from the United States, boys and children without computer science experience are included most frequently. Race and SES are frequently not reported on, and for race as well as for disabilities there appears a tendency to report these categories only when they deviate from the majority. Further, for several demographic categories different criteria are used to determine them. Finally, most studies take place within schools. These insights can be valuable to correctly interpret current knowledge from K12 CSEd research, and furthermore can be helpful in developing standards for consistent collection and reporting of demographic information in this community.