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关键词： CINI   computer science   Information and communication technology   Italy   Pandemic   survey   Task force Covid-19  

摘要： The Covid19 pandemic heavily impacted on our lives, also as academics, triggering a strong reaction that results in vaccines, more effective diagnosis and therapies, pandemic containment policies, etc. A relevant contribution to this success is due to computer science and information technology, by either supporting other disciplines or as the main driver of solutions for, e.g., diagnostics, social distancing and contact tracing. This article reports on the italian computer scientific community activities against the Covid19 pandemic, by analysing the data obtained from a survey taken in May 2020, during the first pandemic wave in Italy, by the Covid19-IT Task Force established by the CINI (National Interuniversity Consortium for IT). The 131 responses thus collected tell us about the spontaneous reaction of such a community, made of several independent initiatives throughout Italy, which has to be kept alive, by for example evolving into more organized forms. © 2021 Associazione Italiana per l'Informatica e il Calcolo Automatico. All rights reserved.

关键词： Bandwidth   Performance evaluation   Tools   Limiting   Linux   Resource management   Computer science   Burstable instance   Cloud   Scheduling   AWS   Credit depletion period   Resource credit   Data-driven predictive analytics  

摘要： Nearly all principal cloud providers now provide burstable instances in their offerings. The main attraction of this type of instance is that it can boost its performance for a limited time to cope with workload variations. Although burstable instances are widely adopted, it is not clear how to efficiently manage them to avoid waste of resources. In this article, we use predictive data analytics to optimize the management of burstable instances. We design CEDULE+, a data-driven framework that enables efficient resource management for burstable cloud instances by analyzing the system workload and latency data. CEDULE+ selects the most profitable instance type to process incoming requests and controls CPU, I/O, and network usage to minimize the resource waste without violating Service Level Objectives (SLOs). CEDULE+ uses lightweight profiling and quantile regression to build a data-driven prediction model that estimates system performance for all combinations of instance type, resource type, and system workload. CEDULE+ is evaluated on Amazon EC2, and its efficiency and high accuracy are assessed through real-case scenarios. CEDULE+ predicts application latency with errors less than 10%, extends the maximum performance period of a burstable instance up to 2.4 times, and decreases deployment costs by more than 50%.

关键词： Databases   Clustering algorithms   Gene expression   Correlation   Sequential analysis   Computer science   Single-cell RNA sequencing   gene set   gene rank   similarity   clustering  

摘要： Single-cell RNA sequencing (scRNA-seq) technology provides quantitative gene expression profiles at single-cell resolution. As a result, researchers have established new ways to explore cell population heterogeneity and genetic variability of cells. One of the current research directions for scRNA-seq data is to identify different cell types accurately through unsupervised clustering methods. However, scRNA-seq data analysis is challenging because of their high noise level, high dimensionality and sparsity. Moreover, the impact of multiple latent factors on gene expression heterogeneity and on the ability to accurately identify cell types remains unclear. How to overcome these challenges to reveal the biological difference between cell types has become the key to analyze scRNA-seq data. For these reasons, the unsupervised learning for cell population discovery based on scRNA-seq data analysis has become an important research area. A cell similarity assessment method plays a significant role in cell clustering. Here, we present BioRank, a new cell similarity assessment method based on annotated gene sets and gene ranks. To evaluate the performances, we cluster cells by two classical clustering algorithms based on the similarity between cells obtained by BioRank. In addition, BioRank can be used by any clustering algorithm that requires a similarity matrix. Applying BioRank to 12 public scRNA-seq datasets, we show that it is better than or at least as well as several popular similarity assessment methods for single cell clustering.

关键词： lynching   lynching legacies   collective violence   violence   slavery   executions  

摘要： Capital punishment in the United States is racialized: those convicted of the murder of Whites are much more likely to receive the death penalty than those convicted for the murder of Blacks. Capital punishment is more commonly practiced in places where lynching of Blacks occurred more frequently and in states in which slavery was legal as of 1860. Accordingly, scholars have debated whether capital punishment reflects a legacy of lynching or a legacy of slavery. Our analysis shows that lynching on its own is a significant predictor of contemporary executions, but that once slavery is accounted for, slavery predicts executions, while lynching does not. We argue that slavery's state-level institutional legacy is central to contemporary capital punishment.

关键词： Women in IT   Relational sensibility   Moral imagination   Positioning   Undergraduate degrees  

摘要： There is extensive literature concerning women's low participation in the technology industry. However, little is known about the relational aspect of women's participation in information technology-related degrees. This study focused mainly on relational sensibility and women's experience as they engage in 4-year undergraduate degrees in computer science (CS) or information technology (IT). Drawing on the theoretical concept of moral imagination the womens' situation is examined;as it is, and how they imagine it could be and should be, as potential life projects are formulated in relation to, and with, others. Data were generated from five semistructured interviews and a focus group discussion with seven women (n = 12 participants). The women in this study enrolled in an undergraduate degree as they were able to solve complex IT problems by themselves and then help others. Further, the self-positioning and the positioning by others created emotional tension and effected the women's relational sensibilities. Most of the women were undecided about their future career in IT because of the lack of transparency and information about what is involved in employment in the field. We argue that moral imagination provides a different perspective to understand women's underrepresentation in the CS and IT fields.

关键词： Cryptography   Legislation   Telecommunication Security   Beautiful Mathematics   Cutting Edge Areas   Computer Science   Digital Era   Single Day   Cryptography Conference   Election Security   Legislation   Regulating Encryption   Mathematical Constructions   Efficient Encryption Schemes   Privacy   Data Centers   Voting   Legislation   Mathematics   Encryption   Internet  

摘要： Cryptography as a field of study is exciting because it brings together beautiful mathematics and many cutting-edge areas of computer science and engineering to find solutions that touch all aspects of life in a digital era. In a single day at a cryptography conference, one can hear talks on election security and legislation on regulating encryption, new mathematical constructions that might yield more efficient encryption schemes, how to wirelessly hack a Tesla and drive away without the key, how Google secures communication between its data centers, and how to build a more private blockchain.

关键词： Crowdsensing   Games   Sensors   Task analysis   Social networking (online)   Wireless communication   Computer science   Socially-aware crowdsensing   multi-leader multi-follower game   incentive scheme   reward design  

摘要： The mobile crowdsensing paradigm facilitates a broad range of emerging sensing applications by leveraging ubiquitous mobile users to cooperatively perform certain sensing tasks with their smart devices. As this paradigm involves data collection from users, the issue of designing rewards to incentivize users is fundamentally important to ensure participation in crowdsensing. In this paper, we revisit this issue in the context of socially-aware crowdsensing which integrates crowdsensing into social networks. For example, in healthcare-based crowdsensing services, the fun of tracking daily nutrition information for a certain user can be promoted by comparing her nutritional information with that contributed and shared by her socially-connected friends. To be more general and practical, we study the incentive mechanisms in presence of multiple crowdsensing service providers and multiple users. Understanding the behaviors of users and service providers in socially-aware crowdsensing is of paramount importance for incentive mechanisms. With this focus, we propose a multi-leader and multi-follower Stackelberg game approach to model the strategic interactions among service providers and users, where the social influence of users and the strategic interconnections of service providers are jointly and formally integrated into the game modeling. Through backward induction methods, we theoretically prove the existence and uniqueness of the Stackelberg equilibrium. We conduct extensive simulations to investigate game equilibrium properties, and the real-world dataset is applied to evaluate and demonstrate the performance effectiveness of the proposed game model.

关键词： Metadata  

摘要： Under optimistic projection models, gender parity is forecast to be reached after 2100.

关键词： Correlation   Data models   Robustness   Web pages   Cybernetics   Computer science   STEM   Commonality   ensemble classification   individuality   multilabel learning   multiview learning  

摘要： In multiview multilabel learning, each object is represented by several heterogeneous feature representations and is also annotated with a set of discrete nonexclusive labels. Previous studies typically focus on capturing the shared latent patterns among multiple views, while not sufficiently considering the diverse characteristics of individual views, which can cause performance degradation. In this article, we propose a novel approach [individuality- and commonality-based multiview multilabel learning (ICM2L)] to explicitly explore the individuality and commonality information of multilabel multiple view data in a unified model. Specifically, a common subspace is learned across different views to capture the shared patterns. Then, multiple individual classifiers are exploited to explore the characteristics of individual views. Next, an ensemble strategy is adopted to make a prediction. Finally, we develop an alternative solution to jointly optimize our model, which can enhance the robustness of the proposed model toward rare labels and reinforce the reciprocal effects of individuality and commonality among heterogeneous views, and thus further improve the performance. Experiments on various real-word datasets validate the effectiveness of ICM2L against the state-of-the-art solutions, and ICM2L can leverage the individuality and commonality information to achieve an improved performance as well as to enhance the robustness toward rare labels.

关键词： Computer vision   Construction health and safety   Safety science   Safety culture   Safety Climate, Hazard   Safety management system   Digital technologies   Automation  

摘要： Recent years have seen growing interests in developing and applying computer vision technologies to solve safety problems in the construction industry. Despite the technological advancements, there is no research that exams the theoretical links between computer vision technology and safety science and management. Thus, the objectives of this paper are to: (1) investigate the current status of applying computer vision technology to construction safety, (2) examine the links between computer vision applications and key research themes of construction safety, (3) discuss the theoretical challenges of applying computer vision to construction safety, and (4) recommend future research directions. A five-step review approach was adopted to search and analyze peer-reviewed academic journal articles. A three-level computer vision development framework was proposed to categorized computer vision applications in the construction industry. The links between computer vision and three main safety research traditions: safety management system, behavior-based safety program, and safety culture, were discussed. The results suggest that the majority of past efforts were focused on object recognition, object tracking, and action recognition, with limited research focused on recognizing unsafe behavior. There are even fewer studies aimed at developing vision-based safety assessment and prediction systems. Based on the review findings, four future research directions are suggested: (1) develop and test a behavioral-cues-based safety climate measure, (2) develop safety behavior datasets, (3) develop a formal hazard identification and assessment model, and (4) develop criteria to evaluate the real impacts of vision-based technologies on safety performance.