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关键词： Controllability   Heuristic algorithms   Approximation algorithms   Laplace equations   Computer science   Greedy algorithms   Dynamic programming   graph algorithms   network topology   strong structural controllability  

摘要： In this article, we study the problem of computing a tight lower bound on the dimension of the strong structurally controllable subspace (SSCS) in networks with Laplacian dynamics. The bound is based on a sequence of vectors containing the distances between leaders (nodes with external inputs) and followers (remaining nodes) in the underlying network graph. Such vectors are referred to as the distance-to-leaders vectors. We give exact and approximate algorithms to compute the longest sequences of distance-to-leaders vectors, which directly provide distance-based bounds on the dimension of SSCS. The distance-based bound is known to outperform the other known bounds (for instance, based on zero-forcing sets), especially when the network is partially strong structurally controllable. Using these results, we discuss an application of the distance-based bound in solving the leader selection problem for strong structural controllability. Further, we characterize strong structural controllability in path and cycle graphs with a given set of leader nodes using sequences of distance-to-leaders vectors. Finally, we numerically evaluate our results on various graphs.

关键词： History   Feature extraction   Wireless fidelity   Social networking (online)   Systematics   Peer-to-peer computing   Computer science   Fraud-agents detection   online lending   Index Terms   empirical study  

摘要： Online Microlending, a new financial service, focuses on small loans without any sort of collateral. It provides more flexible and quicker funding for borrowers, as well as higher interest rates of return. For platforms that provide such services, an essential task is to adequately evaluate each loan's risk so as to minimize the possible financial loss. However, there exists a special group of borrowers, namely fraud-agents, who gain illegal profits from inciting other borrowers to cheat, i.e., they help the high-risk borrowers evade the risk evaluation by crafting fake personal information. The existence of fraud-agents poses a severe threat to the risk management systems and results in a huge financial loss for lending platforms. In this article, we present the first machine learning-based solution to detect fraud-agents in online microlending. The key challenge of this decade-long problem is that it is unclear how to construct effective features from multiple behavior logs such as phone call history, address book, loan history and activity logs of borrowers. To address this problem, we first conduct an empirical study on over 600K borrowers to gain some insights on the adversarial behaviors of fraud-agents comparing to normal borrowers and benign-agents. Based on the study, we are able to design a total of 26 features, falling into four groups, for fraud agent detection. Then, we propose a two-stage detection model to address the challenge of limited number of labeled fraud agent examples. The evaluation results show that our method can achieve a precision of 94.30%. We deploy our method on a real large online microlending platform with 11,953,273 borrowers, and we identify 29,727 fraud-agents from them. The domain experts from the platform confirm that 95.59% of them are real fraud-agents, and have added them to the platform's internal blacklist. We further conduct a measurement study on those fraud-agents to share deeper insights on their adversarial behaviors.

关键词： biology   computer science   robot   artificial life   artificial intelligence   machine learning   evolution  

摘要： The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as "polycomputing"-the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind;rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design princip

关键词： COVID-19   CAPE framework   Capacity   Access   Participation   Experience   underrepresented   underserved   historically marginalized  

摘要： Research Problem. Computer science (CS) education researchers conducting studies that target high school students have likely seen their studies impacted by COVID-19. Interpreting research findings impacted by COVID-19 presents unique challenges that will require a deeper understanding as to how the pandemic has affected underserved and underrepresented students studying or unable to study computing. Research Question. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools based on relative socioeconomic status of a majority of students? Methodology. We used an exploratory sequential mixed methods study to understand the types of impacts high school CS educators have seen in their practice over the past year using the CAPE theoretical dissaggregation framework to measure schools' Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS. Data Collection Procedure. We developed an instrument to collect qualitative data from open-ended questions, then collected data from CS high school educators (n = 21) and coded them across CAPE. We used the codes to create a quantitative instrument. We collected data from a wider set of CS high school educators (n = 185), analyzed the data, and considered how these findings shape research conducted over the last year. Findings. Overall, practitioner perspectives revealed that capacity for CS Funding, Policy & Curriculum in both types of schools grew during the pandemic, while the capacity to offer physical and human resources decreased. While access to extracurricular activities decreased, there was still a significant increase in the number of CS courses offered. Fewer girls took CS courses and attendance decreased. Student learning and engagement in CS courses were significantly impacted, while other noncognitive factors like interest

关键词： Computer science   Databases   Indexing  

摘要： DBLP provides comprehensive and free computer science (CS) bibliographic data to all. But how well does it really cover CS journals? In this article, we compare DBLP's indexed journals with those classified as CS by the leading indexing services today-Web of Science and Scopus.

关键词： Computer and information literacy   Information and communication technology   Arts literacy   Science literacy   Learning transfer theory  

摘要： Since the International Computer and Information Literacy (CIL) was introduced to assess school children's ability of using computers and other information and communications technologies (ICT) for educational purposes, considerable work has been devoted to investigating the ICT-related determinants of students' computer and information literacy. However, there is scant literature on how rural students' CIL could be affected by learning other subjects like arts or sciences. Guided by the theory of learning transfer, this study explores possible learning transfer effects of arts and science literacies on CIL and ICT skills among eighth graders (N = 2821) in China's rural areas. The findings show that arts literacy is positively associated with CIL and ICT skills, while science literacy is positively associated with basic ICT skills but negatively related to advanced ICT skills. Rural students who had a higher family socioeconomic status and better educated parents were more likely to have higher CIL, suggesting the presence of digital disparities. This study provides timely perspectives that help students to master ICT skills and improve computer literacy, including insights for revealing digital disparities among rural students in low-resource settings.

关键词： Games   Informal learning   Social media   Gender studies  

摘要： Computer gameplay and social media are the two most common forms of entertainment in the digital age. Many scholars share the assumption that leisure-time digital consumption is associated with computer science (CS) affinity, but there is a dearth of research evidence for this relationship. Female students generally spend less time on gaming and more time on social media than do male students, so a gender comparison perspective is helpful. Using multinomial logistic regression analysis on a national sample of 10,197 U.S. college students in introductory CS courses, we found that frequent computer gameplay was strongly associated with an increase in the probability of CS career interest relative to a Non-STEM career interest (beta = -0.17, se = 0.06, p < .01) for both male (N = 7214) and female students (N = 2659). In contrast, increased social media use predicted a higher CS career interest relative to a Science/Engineering career interest (beta = 0.12, se = 0.06, p < .05) for female students by 8%, however, a lower interest for male students by 4%.

关键词： Roads   TV   Irrigation   Computer science   Traffic congestion   IEEE transactions   Visualization   Vehicular ad hoc networks   traffic management systems   Traffic Jams   intelligent transportation systems  

摘要： The next generation of smart cities will rely on Intelligent Transport Systems (ITSs) due to the increased complexity and dynamism of traffic caused by continuous urbanization and population growth. The traditional techniques to deal with these challenges are expensive and have a great impact on people's lives and, in this scenario, the introduction of computational and technological solutions is necessary. In order to minimize the problems caused by congestion in urban centers, we present Let Me Know, a traffic management system inspired by the communication among vehicles that allows the request and availability of information related to vehicular traffic. The vehicles request information in order to update a distributed database containing momentary analyzes of road traffic. Through extensive performance analysis, we show our system's ability to reduce traffic congestion with a low impact on the network.