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关键词： 民办高校   计算机类本科   实践教学  

摘要： 本文旨在探索民办高校计算机类本科中的“3+1”应用型人才培养模式。本文概述了“3+1”应用型人才培养模式能有效提升计算机类本科应用型人才的培养的原因,分析了民办高校在实施“3+1”人才培养模式过程中遇到的挑战和问题,提出了改革策略和具体措施。本文还通过学生和企业的反馈评价和改进建议评估了这一模式的实践效果。本文展望了该模式的改进方向和未来发展前景,并强调了深化和创新高等教育教学模式的重要性以及人才培养模式的理论探索和实践创新之间的相互关系。

关键词： Explainable artificial intelligence   Finance   Systematic literature review   Machine learning   Review   G00   L50   MODELS   MARKET   PREDICTION   NETWORKS   FINTECH   RISK  

摘要： Digitalization and technologization affect numerous domains, promising advantages but also entailing risks. Hence, when decision-makers in highly-regulated domains like Finance implement these technological advances-especially Artificial Intelligence-regulators prescribe high levels of transparency, assuring the traceability of decisions for third parties. Explainable Artificial Intelligence (XAI) is of tremendous importance in this context. We provide an overview of current research on XAI in Finance with a systematic literature review screening 2,022 articles from leading Finance, Information Systems, and Computer Science outlets. We identify a set of 60 relevant articles, classify them according to the used XAI methods and goals that they aim to achieve, and provide an overview of XAI methods used in different Finance areas. Areas like risk management, portfolio optimization, and applications around the stock market are well-researched, while anti-money laundering is understudied. Researchers implement both transparent models and post-hoc explainability, while they recently favored the latter.

关键词： PRIP-2023   image analysis   pattern recognition   artificial intelligence   information processing   computer science  

摘要： The main scientific results of the 16th International Conference on Pattern Recognition and Information Processing (PRIP-2023), Minsk, Republic of Belarus, October 2023, are reviewed and analyzed. The history of this series of conferences is outlined, and its significant role in the development of the theory and practice of image analysis, pattern recognition, and artificial intelligence is indicated. A list of articles in the special issue is provided, prepared from reports selected by the PRIP-2023 Program Committee.

关键词： Transfer learning   Bridges   Metalearning   Adaptation models   Computer science   Training   Task analysis   heterogeneous label spaces   selective random walk  

摘要： Transfer learning has been widely used in different scenarios, especially in those lacking enough labeled data. However, most of the existing transfer learning methods are based on the assumption that the source and target domains should share the label space entirely or partially, which greatly limits their application scopes. In this article, a Selective Random Walk (SRW) method for transfer learning in heterogeneous label spaces is proposed to make full use of unlabeled auxiliary data, which acts as a bridge for knowledge transfer from the source domain to the target domain. The proposed SRW method can explicitly identify transfer sequences between source and target instances via auxiliary instances based on random walk techniques. Since not all of the transfer sequences generated by random walk are credible for the target task, the SRW method can learn to weight transfer sequences adaptively. Based on the weights of the transfer sequences, the SRW method leverages knowledge by forcing adjacent data points in the transfer sequence to be similar and making the target data point in the sequence represented by other data points in the same sequence. Experiments show that the SRW method outperforms state-of-the-art models in plenty of transfer learning tasks with heterogeneous label spaces constructed within and across several benchmark datasets.

关键词： Computer science education   Epistemology   Feminist standpoint theory   Inclusivity   Lived experiences   Positionality   Subjectivity  

摘要： In this article, we present a conceptual framework for teaching computer science (CS) to address the unique challenges faced by marginalized groups. The framework is grounded in feminist standpoint theory and describes three key practitioner-focused areas aimed at broadening participation and increasing participation in CS education (CSEd). These principles are 1) Creating dialogic and dialectical relationships with the CS community, 2) Embracing intersectionality in CSEd, and 3) Framing CS education as a lived experience. It also offers a distinct perspective in that it is concerned with how both sides of the dialogue (i.e., the oppressed and the oppressor) grow and change in relation to one another. The strategies, along with the framework detailed in this paper, provide scholars and educators with new avenues for unpacking underrepresentation in CSEd and potential methods to address it.

关键词： Agile software development   computer science   computer science education   course design   design process   instruction   machine learning (ML)   software engineering (SE)  

摘要： Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported ***: ML professionals report that building ML systems is different enough that we need new knowledge about how to infuse ML into software production. For instance, various experts need to be deeply involved with these SE projects, such as business analysts, data scientists, and *** outcomes: The creation of a table detailing and matching industry challenges with course learning objectives, course topics, and related *** design: Course content was derived from interviewing industry professionals with related experience as well as surveying undergraduate SE students. The proposed course style is designed to emulate real-world ML-based ***: Industry-derived content for a pilot undergraduate course has been successfully crafted at the intersection of SE and ML.

关键词： Vehicles   Pricing   Charging stations   Vehicle dynamics   Urban areas   Computer science   Training   Data-driven   electric vehicle   for-hire vehicle   fairness   deep reinforcement learning  

摘要： With the worldwide mobility electrification initiative to reduce air pollution and energy security, more and more for-hire vehicles are being replaced with electric ones. A key difference between gas for-hire vehicles and electric for-hire vehicles (EFHV) is their energy replenishment mechanisms, i.e., refueling or charging, which is reflected in two aspects: (i) much longer charging processes versus much shorter refueling processes and (ii) time-varying electricity prices versus time-invariant gasoline prices during a day. The complicated charging issues (e.g., long charging time and dynamic charging pricing) potentially reduce the daily operation time and profits of EFHVs, and also cause overcrowded charging stations during some off-peak charging pricing periods. Motivated by a set of findings obtained from a data-driven investigation and field studies, in this paper, we design a fairness-aware vehicle displacement system called FairMove to jointly optimize the overall profit efficiency and profit fairness of EFHV drivers by considering both the passenger travel demand and vehicle charging demand. We first formulate the EFHV displacement problem as a Markov decision problem, and then we present a fairness-aware multi-agent actor-critic approach to tackle this problem. More importantly, we implement and evaluate FairMove with real-world streaming data from the Chinese city Shenzhen, including GPS data and transaction data from over 20,100 EFHVs, coupled with the data of 123 charging stations, which constitute, to our knowledge, the largest EFHV network in the world. Extensive experimental results show that our fairness-aware FairMove effectively improves the profit efficiency and profit fairness of the EFHV fleet by 26.9% and 54.8%, respectively. It also improves the charging station utilization fairness by 38.4%.

关键词： Load management   Switches   Delays   Receivers   Load modeling   Computer science   Transport protocols   Datacenter   lossless networks   load balancing  

摘要： Various datacenter network (DCN) load balancing schemes have been proposed in the past decade. Unfortunately, most of these solutions designed for lossy DCNs do not work well for Priority Flow Control (PFC) enabled lossless DCNs, primarily due to the reason that the individual congestion signals used in these solutions, e.g., link load, queue length, Round Trip Time (RTT) and Explicit Congestion Notification (ECN), may not be able to correctly or timely reflect the hop-by-hop PFC pausing. This paper first reveals the above problems via extensive experiments, and then based on the insights learned, we present Proteus, a PFC-aware load balancing scheme that is resilient to PFC pausing by exploring a combination of multi-level congestion signals. At its heart, Proteus leverages RTT-level signals (i.e., RTT and link utilization) to detect path status for initial routing decision, and exploits sub-RTT level signal (i.e., cumulative sojourn time) to reflect instantaneous PFC pausing and make timely rerouting choices based on the idea of better-late-than-never. We have implemented Proteus in the hardware programmable switch. Our testbed experiments as well as large-scale simulations show that Proteus can effectively handle PFC pausing under realistic workloads and achieve up to 35%, 31%, 28%, 22% and 46%, 42%, 34%, 29% better average FCT and 99(th) percentile FCT than CONGA, DRILL, Hermes and MP-RDMA, respectively.

关键词： Death penalty   Capital punishment   Global historical data   Dataset   CAPITAL-PUNISHMENT   ABOLITION   POLICY  

摘要： The death penalty is a unique form of punishment as it is the most consequential penalty with no options for reversibility. Politically, it is a highly controversial form of punishment, the usage of which varies strongly between and within countries over time. Existing databases on death penalty usage generally cover a time period from the 1950s and onwards. In this article, we introduce a new database that covers the period 1800-2022 for all currently independent countries in the world. We provide a yearly categorization of death penalty status as well as changes of the status. In descriptive analyses, we show how the new data provides a more comprehensive picture of the development of death penalty trends worldwide. The database provides researchers with new opportunities to study the death penalty from a variety of perspectives.

关键词： Solid modeling   Mathematical models   Psychology   Computer science   Production   Dynamics   Sociology   Dynamic models   paradox of information access   polarization   social networks   OPINION DYNAMICS   SOCIAL-INFLUENCE  

摘要： This article derives a new nonlinear stochastic model of the evolution of human beliefs that demonstrates how an increase in democratized information production and sharing, combined with consumers' confirmation bias and natural bias for outlying content, results in increased polarization. The model shows that the evolution of human beliefs can be approximated by a nonlinear diffusion-drift equation, in which systematic psychological biases contribute to drift, whereas other random influences contribute to diffusion. The nonlinear formulation predicts a growth in polarization that is attributable to increasing information production and sharing. While the core contribution is analytical, an anecdotal model parameter fitting empirical data is also presented. Specifically, we show that our model closely predicts the changing and increasingly polarized distribution of ideology of members of the US congress over the last quarter century (taken as an approximate proxy for shifts in the US population ideology), when we take the mobile-phone penetration curve as a proxy for the democratization of information access. The model suggests that escaping the polarizing forces in the age of information access may be an uphill battle.