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关键词： Groundwater management   Groundwater monitoring   Groundwater modelling   Computer science   Free and open source software  

摘要： National governments and international organizations such as the European Commission, are promoting the increased use of information and communication technologies to assist scientists in the "mining" of knowledge. A typical workflow for a hydrogeologist consists of investigating and reporting hydrogeological processes in a study area, from data collection to model-based analysis. While hydrogeologists may feel insufficiently skilled to undertake the self-automatizing and digitizing process, the digitalization of the aforementioned workflow can be easily obtained by means of agile and parsimonious methodologies based on free and open-source software, and by using existing standards. This route is demonstrated for the digitalization of a vadose-zone monitoring system, where a large number of raw data related to water infiltration through the vadose zone are collected. The main aspects of the proposed methodology are a structured database (DB) where field data are stored, and a Python script to manage and process the available data. The structured DB was designed to store data recorded by field sensors and to generate inputs to run a transfer-function-based model to simulate percolation to the water table. Field data and model outputs were also exploited to automatically generate summary reports, like plots and table statistics. The proposed methodology can be generalized to other hydrogeological processes and case studies, as it is based on commonly available standards, basic knowledge of data-storage and data-management, and elementary programming skills to connect the different components of its suite.

摘要： In the aftermath of the killing of George Floyd and other Black Americans, the world has risen up in pain and anguish to condemn social injustice and racism that has systematically impacted the lives of people of color. Many of you have shared your outrage and impatience regarding lack of diversity in our profession, structural racism in our American culture that leads to inequities, and the need for a lasting systemic change. You have asked for implicit bias training, cultural humility, and frank conversations. You have asked us to look internally as individual members and as an organization. And you have asked us to listen.

关键词： Computer science   Electrical engineering   Mathematics   Physics   Bayesian method   Chaotic sequence   Cognitive radio   Compressive sensing   Spectrum sensing   Toeplitz matrix  

摘要： To satisfy the growing spectrum demands of emerging wireless applications, cognitive radios have been considered as a viable option. It enables dynamic spectrum access opportunistically using wideband spectrum sensing (WSS) methods to discover the temporarily free frequency bands. WSS requires a high-speed analog-to-digital converter (ADC), which has high power consumption and hardware complexity. Improving the power consumption and hardware complexity of the ADC is one of the existing challenges in energy-constrained applications. To alleviate this problem, we propose compressive sensing (CS) in maximum-minimum subband energy detection method to sense the wideband spectrum by utilizing the sparse nature of spectrum occupancy with the minimal possible number of measurements. The CS method uses Fourier Transform and chaotic sequence in designing the measurement matrix to achieve both determinacy and randomness. The Bayesian method is used to reconstruct the signal from the available measurements. From the reconstructed signal, the maximum-minimum subband energy detection (ED) method is used to decide whether the primary user (PU) is absent or present in a particular frequency band. The simulation results show that the proposed CS-based maximum-minimum subband energy detection approach improves the probability of detection by 7.5% compared to the conventional maximum-minimum subband energy detection method of spectrum sensing. The proposed spectrum sensing method is simple and robust to noise uncertainty and signal strength variations.

关键词： Environmental science   Computer science   Geography   Land use planning   Land use change   Urban growth   Machine learning   Urban planning   Modeling   Artificial intelligence   Cellular Automata   Markov Chain  

摘要： Urban growth and land-use change are a few of many puzzling factors affecting our future cities. Creating a precise simulation for future land change is a challenging process that requires temporal and spatial modeling. Many recent studies developed and trained models to predict urban expansion patterns using Artificial Intelligence (AI). This study aims to enhance the simulation capability of Cellular Automata Markov Chain (CA-MC) model in predicting changes in land-use. This study integrates the Artificial Neural Network (ANN) into CA-MC to incorporate several driving forces that highly impact land-use change. The research utilizes different socio-economic, spatial, and environmental variables (slope, distance to road, distance to urban centers, distance to commercial, density, elevation, and land fertility) to generate potential transition maps using ANN Data-driven model. The generated maps are fed to CA-MC as additional inputs. We calibrated the original CA-MC and our models for 2015 cross-comparing simulated maps and actual maps obtained for Irbid city, Jordan in 2015. Validation of our model was assessed and compared to the CA-MC model using Kappa indices including the agreement in terms of quantity and location. The results elucidated that our model with an accuracy of 90.04% substantially outperforms CA-MC (86.29%) model. The improvement we obtained from integrating ANN with CA-MC suggested that the influence imposed by the driving force was necessary to be taken into account for more accurate prediction. In addition to the improved model prediction, the predicted maps of Irbid for the years 2021 and 2027 will guide local authorities in the development of management strategies that balance urban expansion and protect agricultural regions. This will play a vital role in sustaining Jordan's food security.

关键词： Bibliometrics   Academic recruitment   Research productivity   Citations   H-index  

摘要： Due to its quantitative nature, bibliometrics is becoming increasingly popular among policy makers for academic hiring and career promotions. In this article, we quantitatively assess the impact that the granularity level in the classification of scientific areas would entail on research evaluation based on bibliometric indicators. We use as a case study the Italian national habilitation system (ASN), which classifies faculty members according to their academic discipline and relies on journal counts, citations, and h-indices as a basis for promoting tenure track researchers to associate professors and associate to full professors. The assessment checks whether the individual indicators of a researcher are above a certain threshold, e.g., the median over the population of researchers working in the same discipline. Our investigation focuses on two related, rather broad disciplines: computer science and computer engineering. We show that the ASN practice of using the same thresholds for all members of a scientific discipline can favor certain sub-communities that are characterized by higher bibliometric indicators, and disfavor others. We report evidence that up to 30% of Italian faculty members of certain sub-communities would see their indicators drop below the threshold, thus becoming not eligible for promotion, if the ASN were conducted on a more accurate, fine-grained classification. Conversely, in the same scenario, up to 11% of faculty members, in different sub-communities, would see their indicators rise above the threshold, granting them eligibility. Our data set includes 1685 authors, 89,185 distinct publications, and 262,286 author-publication pairs.

关键词： Computer science   Mental health   Racism   Area level racism   Presidential election   Structural racism   Sentiment analysis   Election   Trump   Time-series analysis  

摘要： Purpose: The purpose was to use Twitter to conduct online surveillance of negative sentiment towards Mexicans and Hispanics during the 2016 United States presidential election, and to examine its relationship with mental well-being in this targeted group at the population level. Methods: Tweets containing the terms Mexican(s) and Hispanic(s) were collected within a 20-week period of the 2016 United States presidential election (November 9th 2016). Sentiment analysis was used to capture percent negative tweets. A time series lag regression model was used to examine the association between percent count of negative tweets mentioning Mexicans and Hispanics and percent count of worry among Hispanic Gallup poll respondents. Results: Of 2,809,641 tweets containing terms Mexican(s) and Hispanic(s), 687,291 tweets were negative. Among 8,314 Hispanic Gallup respondents, a mean of 33.5% responded to be worried on a daily basis. A significant lead time of 1 week was observed, showing that negative tweets mentioning Mexicans and Hispanics appeared to forecast daily worry among Hispanics by 1 week. Conclusion: Surveillance of online negative sentiment towards racially vulnerable population groups can be captured using social media. This has potential to identify early warning signals for symptoms of mental well-being among targeted groups at the population level.

关键词： Computer science   equity   secondary education   teacher professional development  

摘要： Effective and equitable CS teaching is contingent on teachers' robust understanding of equity issues in CS classrooms. To this end, this study examined high school teachers' perceptions of equity during their participation in a CS teacher certificate program over two years. The participants are from various disciplines and from schools that serve under-represented students. Using a qualitative approach, we conducted content analysis of the teachers' written reflections and responses to semi-structured interviews. Based on the justice-centered framework, we analyzed the major themes that emerged from the content analysis. The findings provide insights into high school CS teachers' understanding of equity, the strategies that teachers use to address equity issues, and how teachers interpret the causes of inequities in CS classrooms. This research presents frameworks for examining teachers' conceptualizations of equity and can inform the implementation of future professional development programs for CS teachers.

关键词： Information systems  

摘要： In this research, we posit the importance of including Computer Science topics in undergraduate Information Systems courses. A review of the existing literature has mentioned the importance of learning some Computer Science topics for an Information Systems career. Unfortunately, we have not found a consensus that could push this initiative. There is a set of concepts that Information Systems students should acquire from Computer Science or at least have a solid background in these areas. Therefore, we propose a set of courses from Computer Science that, we believe, should be considered in an Information Systems education. © 2020 Association for Computing Machinery. All rights reserved.

关键词： Computer science   Face detection   Face tracking   Depth camera   Digital signage  

摘要： Digital signage is widely utilized in digital-out-of-home (DOOH) advertising for marketing and business. Recently, the combination of the digital camera and digital signage enables the advertiser to gather the audience demographic for audience measurement. Audience measurement is useful for the advertiser to understand the audience's behavior and improve their business strategies. When an audience is facing the digital display, the vision-based DOOH system will process the audience's face and broadcast a personalized advertisement. Most of the digital signage is available in an uncontrolled environment of public areas. Thus, it poses two main challenges for the vision-based DOOH system to track the audience's movement, which are multiple adjacent faces and occlusion by passer-by. In this paper, a new framework is proposed to combine the digital signage with a depth camera for tracking multi-face in the three-dimensional (3D) environment. The proposed framework extracts the audience's face centroid position (x, y) and depth information (z) and plots into the aerial map to simulate the audience's movement that is corresponding to the real-world environment. The advertiser can further measure the advertising effectiveness through the audience's behavior.