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关键词： Logic gates   Object detection   Contamination   Task analysis   Saliency detection   Computer science   Image color analysis   Salient object detection   RGB-D images   depth potentiality perception   gated multi-modality attention  

摘要： There are two main issues in RGB-D salient object detection: (1) how to effectively integrate the complementarity from the cross-modal RGB-D data;(2) how to prevent the contamination effect from the unreliable depth map. In fact, these two problems are linked and intertwined, but the previous methods tend to focus only on the first problem and ignore the consideration of depth map quality, which may yield the model fall into the sub-optimal state. In this paper, we address these two issues in a holistic model synergistically, and propose a novel network named DPANet to explicitly model the potentiality of the depth map and effectively integrate the cross-modal complementarity. By introducing the depth potentiality perception, the network can perceive the potentiality of depth information in a learning-based manner, and guide the fusion process of two modal data to prevent the contamination occurred. The gated multi-modality attention module in the fusion process exploits the attention mechanism with a gate controller to capture long-range dependencies from a cross-modal perspective. Experimental results compared with 16 state-of-the-art methods on 8 datasets demonstrate the validity of the proposed approach both quantitatively and qualitatively. https://***/JosephChenHub/DPANet

关键词： 疫情   初中英语   线上教学   未来职业规划  

摘要： 面对2020年初突如其来的新冠疫情,各行各业的人都在用自己的方式为祖国加油助力。作为一线初中英语教育工作者也不能缺席。走出传统课堂教学,进入以"网络虚拟空间"为课堂载体的线上教学,走上荧幕,当上"主播",运用网络课程资源平台进行线上教学。将抗击疫情与英语学科教育相结合,通过客观事实的呈现,让学生了解各行各业对社会发展的重要影响,引导青少年正确认识"职业",关注科学技术的重要性。

关键词： Semantics   Quality of service   Web services   Search engines   Testing   Computer science   Oceans   Acceptance testing   interface compatibility   RESTful service   service discovery   term expansion   unit testing  

摘要： Web API/service technology has been attracting considerable attention and the REST (REpresentational State Transfer) architecture is now widely accepted as mainstream technology. Nonetheless, developing the means by which to discover RESTful Web APIs/services is crucial to the further development of this technology. Unfortunately, existing search engines for RESTful Web APIs/services provide only keyword-based or tag-based search functions. A failure to take into account the semantics and/or characteristics (e.g., their interface compatibility) greatly hampers the ability to find suitable APIs/services. In this study, we propose a novel approach to the discovery of RESTful Web API/services, referred to as Test-Oriented API Search with Semantic Interface Compatibility (TASSIC). This scheme involves expanding the terms of Web API/service documents based on DBpedia and WordNet. Unsuitable APIs/services are then filtered out using a systematic process, as follows: 1) calculation of semantic similarity between a set of candidate APIs/services and a user query, 2) analysis of interface compatibility between candidate APIs/services using the Hungarian Algorithm, 3) invocation of candidate APIs/services to verify functionality and availability, and 4) analysis of similarity between the actual response of the candidate services and the expected response specified in the user query. The proposed TASSIC increases the likelihood of matching APIs/services that are semantically equivalent or similar to user queries. Unit test and acceptance test are used to verify that a set of candidate APIs/services are actually available and that they actually meets user requirements. Experiment results demonstrate the efficacy of TASSIC, the accuracy of which is superior to that of existing methods.

摘要： The article looks at several ways in which computer science topics can be made more accessible to students and librarians alike. They include the use of sophisticated unplugged computing activities such as game play or beadwork, doing book sorting activities and using an app that allows students to program their strategies, and learning block coding to create weavings.

关键词： Hispanic-Serving Institutions   Latinx students   STEM   Computer science  

摘要： Computer science remains one of the least diverse disciplines within STEM. As society becomes more dependent on technology, there should be more diverse representation in the people producing technology. Latinx are underrepresented in the technology sector. In order to understand the lack of diversity in the technology sector it is important to look at diversity efforts in computer science programs at higher education institutions. The purpose of this study was to understand the experiences of Latinx students in computer science programs at Hispanic-Serving Institutions. Focusing on Hispanic-Serving institutions is important given that they educate a large percentage of Latinx college students. The research question guiding this study was: What barriers and supports do Latinx students in computer science experience at Hispanic-Serving Institutions? Data for this study were collected through semi-structured interviews with twelve students from three higher education institutions. The analysis revealed four themes: Navigating College as a First-Generation College Student, Disconnections in Computer Science/Feelings of Inadequacy, On-Campus Relationships and Professional Development for Computer Science Students. This study illustrates how faculty, staff, and peers can best support Latinx students in computer science. The knowledge students shared in this study provides insights into how to create a more inclusive environment in STEM that will promote the success of Latinx computer science students.

关键词： Computer science  

摘要： Trajectories are spatio-temporal data that represent traces of moving objects, such as humans, migrating animals, vehicles, and tropical cyclones. In addition to the geo-location information, a trajectory data often contain other (non-spatial) features describing the states of the moving objects. The time-varying geo-location and state information would collectively characterize a trajectory dataset, which can be harnessed to understand the dynamics of the moving objects. This thesis focuses on the development of efficient and accurate machine learning algorithms for forecasting the future trajectory path and state of a moving object. Although many methods have been developed in recent years, there are still numerous challenges that have not been sufficiently addressed by existing methods, which hamper their effectiveness when applied to critical applications such as hurricane prediction. These challenges include their difficulties in terms of handling concept drifts, error propagation in long-term forecasts, missing values, and nonlinearities in the data. In this thesis, I present a family of online learning algorithms to address these challenges. Online learning is an effective approach as it can efficiently fit new observations while adapting to concept drifts present in the data. First, I proposed an online learning framework called OMuLeT for long-term forecasting of the trajectory paths of moving objects. OMuLeT employs an online learning with restart strategy to incrementally update the weights of its predictive model as new observation data become available. It can also handle missing values in the data using a novel weight renormalization strategy. Second, I introduced the OOR framework to predict the future state of the moving object. Since the state can be represented by ordinal values, OOR employs a novel ordinal loss function to train its model. In addition, the framework was extended to OOQR to accommodate a quantile loss function to improve its predic

关键词： System recovery   Resource management   Petri nets   Process control   Manufacturing systems   Computer science   Tools   Multi-unit resource system (MRS)   Petri net   reconfiguration   robust deadlock control   max-controllability of siphon  

摘要： A multi-unit resource allocation system usually contains several processes and a number of resources with multiple units. Due to the competition for shared resources in these systems, deadlocks may occur. Recently, researchers have shown an increased awareness in deadlock control strategies for such a kind of systems without considering the dynamic changes such as processing failures and rework by using the Petri net paradigm. This article reports a new strategy for deadlock analysis and control in reconfigurable multi-unit resource systems (MRSs). We discuss a generalized class of Petri nets in which each stage of a process may require a number of units of different types of resources to perform a task. In this way, we can model more complex real systems. Thanks to a generalized class of Petri nets, i.e., the system of sequential systems with shared resources ((SR)-R-4), this article proposes an effective integrated strategy for designing robust supervisors for reconfigurable MRSs, and improves an (SR)-R-4 model to achieve a new model, namely a system of sequential systems with shared resources and part-re-entry ((SRP)-R-4), which represents the procedure that a flawed product re-enters a system and is re-processed. We use a siphon-based max-controllability deadlock prevention policy (DPP) to supervise the evolution of the (SRP)-R-4, and present a comprehensive analysis to demonstrate that the controlled (SRP)-R-4 is free of deadlocks. A net analysis tool (INA) is used to test and validate the resulting (SRP)-R-4.

关键词： Argument mining   Computational argumentation   Computational persuasion   Computer science   Natural language processing   Persuasion  

摘要： Opinion formation and persuasion in argumentation have been shown to be affected by three major factors: the argument itself, the source of the argument, and the properties of the audience. Understanding the role of each and the interplay between them is crucial for obtaining insights regarding argument interpretation and argument generation. This is particularly important for building effective argument generation systems that can take both the discourse and the audience characteristics into account. Having such personalized argument generation systems would potentially be helpful to show individuals different viewpoints and help them make a more fair and informed decision on an issue. Even though studies in Social Sciences and Psychology have shown that source and audience effects are essential components of the persuasion process, most research in computational persuasion has focused solely on understanding the characteristics of persuasive language. In this thesis, we make several contributions to understand the relative effect of the source, audience, and language in computational persuasion. We first introduce a large-scale dataset with extensive user information to study these factors' effects simultaneously. Then, we propose models to understand the role of prior beliefs of the audience on their perception of persuasive arguments. We also investigate the role of social interactions and engagement in understanding users' success in online debating over time. We find that the users' prior beliefs and social interactions play an essential role in predicting their success in persuasion. Finally, we explore the importance of incorporating contextual information to predict argument impact and show improvements compared to encoding only the text of the arguments.

关键词： interactive approach   IoT computer science teaching   interactive teaching   computer science  

摘要： The traditional approach to teaching computer system and IOT involves the presentation of a large amount of theoretical and mathematical data and materials to students. The common approach is a theoretical explanation of the principles, on the whiteboard and if possible, with the use of graphical animations. The main issue in this area is raising interactivity and getting collaboration between students on project assignments. In this paper, authors are proposing more interactive approach that could be beneficial to teachers of related subjects. Presented are the results of using software and simulating tools (in combination with Arduino hardware development solution) for teaching collaboratively and interactively courses related to IoT. The paper presents ideas for implementation of practical and experimental project assignments, student engagement and collaboration. The paper also presents the results of authors after applying this approach to one generation of students. The application access with practical assignments gave markedly better results, measured through student engagement, classroom attendance and distribution of student results. In this manner, the students had a better understanding of the basics of the microcontrollers, sensors, IoT and were willing to engage in programming of microcontrollers at the lower level. Students have also shown better results in closely related courses such as the courses of operating systems. In addition, some students continued to use IoT platforms for future projects (in college or practice).

摘要： In the post-9/11 world, Canada has struggled with developing a sentencing regime that effectively punishes and deters defined terrorist activity such as the attack on the Canadian Parliament, the Danforth shootings, the rise of Khalistani and Islamic terrorism, and the Toronto Van Attack. Broadly speaking, the Canadian public still supports capital punishment, but it is unclear whether Canadian prosecutors perceive and view the issue in the same light in their professional and legal capacity. Canadian prosecutors are tasked with seeking sentences that meet criminal justice principles, including the principle of deterrence. Their views on what punishments are just and effective are important, as they have significant and broad discretion in asking the courts to impose sentences. Thus, while Clarence Darrow argued that “We have heard talk of justice. Is there anybody who knows what justice is? No one on earth can measure out justice.”, the criminal justice system functions within the legal fiction that prosecutors can make decisions on what justice can and should be. The present study has used a grounded theory design by collecting data from Canadian prosecutors on their views about capital punishment as it relates to defined terrorist activity and their roles concerning administering justice on behalf of the public. A theme emerging from the interviews was that the general deterrence principle of sentencing was either false or too hard to quantify to make it a meaningful factor in sentencing. This study may contribute to a positive social change by helping develop a theory about how Canadian prosecutors view the role of punishment, their role as prosecutors in the criminal justice system, and how they view the effectiveness of deterrence as it relates to defined terrorist activity and capital punishment.