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关键词： African Americans   Chicago   Economic mobility  

摘要： The City of Chicago is one of the most racially segregated cities in America. This thesis looks at the series of decisions made to create a culture that allowed the policy of hate to be ensconced in the lives of Black Chicagoans for the better part of a century. This culture, deemed in this paper as “Security Culture,” was designed to stagnate Black life and relegate it to the outskirts of not only the city but of upper society. In the midst of the 21st century, the rise of “Cancel Culture”—or attempts to hold controversial statements and action to account—took hold. This study aims to interrogate what effect the trauma of living in Security Culture has caused Black Chicagoans if any and what identity shifts Black people have made to rationalize their upward mobility if earned. To test this theory, a new grading scale was developed, the Compounding Racial Trauma Index Score, that looked at six neighborhoods across the Chicagoland area. Each neighborhood was scored based on metrics of health and wealth. Lastly a series of semi- structured interviews were conducted with people who were born before and after the highway was developed to determine how Security Culture altered their lives and or decisions in Chicago. The results showed that neighborhoods in Chicago are as segregated as ever and neighborhoods with wealthier Black families do not necessarily create environments that foster Black wealth for other Black residents. This as wealthy White families create environments that allow other Whites to create generational wealth. These results suggest and reinforce the theory that Black people form new middle-class identities while also navigating a Security Culture that despite attempts at nullification is still as prolific as ever.

关键词： Software engineering   Computer science   Software fault localization   Software debugging   Causal inference   Machine learning  

摘要： Statistical fault localization (SFL) techniques use execution profiles and success/failure information from software executions, in conjunction with statistical inference, to automatically score program elements based on how likely they are to be faulty. SFL techniques typically employ one type of profile data: coverage data, predicate outcomes, or variable values. In the relatively short history of automated SFL, most proposed techniques are based on statistical relationships between the elements of coverage profiles/spectra and the occurrences of program failures. Valuable information carried by variables has usually been ignored, and far fewer techniques are based on the analysis of variable values. In addition, the vast majority of subject programs used to evaluate techniques have been small programs containing artificial faults (faults created by mutations in code), rather than large programs containing real faults (faults logged by developers), which inhibit the credibility of these techniques. Most SFL techniques measure correlation, rather than causation, between profile values and success/failure, and so, they are subject to confounding bias that distorts the scores they produce. In recent years, techniques using the sound causal inference methodology (Causal Statistical Fault Localization) to adjust for the confounding bias properly have been successfully applied to a wide range of programs and profile data. While these first attempts at causal statistical fault localization have yielded promising results, they have lacked cohesion between the different types of profile data, flexible machine learning models, or large subject programs containing real faults in their empirical evaluation. In my work, I present new insights into the properties and limitations inherent in the SFL literature and their effect on the performance of SFL. Furthermore, I present novel algorithms that use causal inference techniques and flexible machine learning models to integrate

关键词： Computer science  

ISBN: (数字)9783110788105;9783110788198 ISBN: (纸本)9783110787993

摘要： This book provides an up-to-date account of current research in quantum information theory, at the intersection of theoretical computer science, quantum physics, and mathematics. The book confronts many unprecedented theoretical challenges generated by infi nite dimensionality and memory effects in quantum communication. The book will also equip readers with all the required mathematical tools to understand these essential questions.

关键词： Computer science   artificial intelligence   cybernetics  

ISBN: (数字)9788770226462 ISBN: (纸本)9788770226479

摘要： 5G, the emerging technology in mobile communication, is expected to deliver an important and decisive impact on several of the UN’s Sustainable Development Goals where universal accessibility to ICTs remains a serious concern. However, cyber security has emerged as a serious challenge, not least because of the increased accessibility and broader usage with associated vulnerability. Developing countries have additional challenges associated with both the expected faster build-up of accessibility and lack of qualified competencies within cyber security. Discussion of these challenges is the overall theme and motivation for this book. Technical topics discussed in the book include: • 5G in rural networks • Critical infrastructures • Open RAN • Protection of privacy • Cybersecurity and machine learning • Cybersecurity and disaster monitoring

关键词： 诺德功能翻译理论   软件工程文本   英汉翻译   翻译方法  

摘要： 计算机网络技术在人类社会中得到广泛的应用,软件几乎充斥着社会的各行各业。为提高软件在市场中的竞争力,软件开发环节至关重要。然而,在现今软件项目的开发建设过程中,工作量估算在项目管理的过程中得不到足够的重视,同时缺乏系统科学方法的指导。因此,软件工作量估算方法的综述对软件测评从业人员在进行测评方法选择方面具有很大的参考价值。本研究报告以软件工程领域学术论文为研究对象,以诺德功能翻译理论为研究方法,具体分析了词汇、句法、语篇层面的语言特征,以期在功能翻译理论指导下总结出适用于不同语言特征的翻译方法,从而提高软件工程类文本的翻译质量。学术论文属于科技英语的范畴,其主要目的在于使译语读者能无障碍地接受源文本所传达的信息。为实现原文的指称功能,在翻译过程中采用了工具型翻译策略来提高译文可读性。研究表明,针对软件工程学术论文翻译而言,在词汇层面,源文本中多使用术语、缩略词和名词化结构,应分别选取相应的翻译方法以确保译文的准确性;句法层面,语言特征主要表现为被动句和复杂句的频繁使用。分析句子结构后,可通过语态转化、顺序重组使译文符合译语表达习惯;语篇层面,各种衔接手段和连贯手段的使用,使源语文本形成了一个有机整体。翻译时,要根据句子、段落之间的逻辑关系,采取相应翻译方法,使译文内各句在语义和主题上紧密衔接。译者在翻译过程中运用了相应策略和方法最大程度地再现源文本功能,因此,诺德功能翻译理论可以指导软件工程学术论文的翻译。

关键词： Environment   Sustainability   Artificial intelligence   Computer science  

摘要： Artificial Intelligence (AI) has become an important area to tackle most environmental sustainability issues such as biodiversity, energy, transportation and water management. Biodiversity research has developed machine learning or natural language processing solutions to predict ecosystem services. Artificial intelligence applica-tions and machine learning models have been increasingly used for predicting and optimizing water resource conservation. Area neural network, expert systems, pattern recognition, and fuzzy logic models are the main focus areas in energy. Applications of computer vision and decision support were found in transportation. Timely monitoring of interventions is required to improve environmental sustainability.

关键词： Task analysis   Semantics   Visualization   Monte Carlo methods   Supervised learning   Computer science   Annotations   Textbook question answering   multi-modality   diagram understanding  

摘要： Textbook Question Answering (TQA) is the task of answering diagram and non-diagram questions given large multi-modal contexts consisting of abundant text and diagrams. Deep text understandings and effective learning of diagram semantics are important for this task due to its specificity. In this paper, we propose a Weakly Supervised learning method for TQA (WSTQ), which regards the incompletely accurate results of essential intermediate procedures for this task as supervision to develop Text Matching (TM) and Relation Detection (RD) tasks and then employs the tasks to motivate itself to learn strong text comprehension and excellent diagram semantics respectively. Specifically, we apply the result of text retrieval to build positive as well as negative text pairs. In order to learn deep text understandings, we first pre-train the text understanding module of WSTQ on TM and then fine-tune it on TQA. We build positive as well as negative relation pairs by checking whether there is any overlap between the items/regions detected from diagrams using object detection. The RD task forces our method to learn the relationships between regions, which are crucial to express the diagram semantics. We train WSTQ on RD and TQA simultaneously, i.e., multitask learning, to obtain effective diagram semantics and then improve the TQA performance. Extensive experiments are carried out on CK12-QA and AI2D to verify the effectiveness of WSTQ. Experimental results show that our method achieves significant accuracy improvements of 5.02% and 4.12% on test splits of the above datasets respectively than the current state-of-the-art baseline. We have released our code on https://***/dr-majie/WSTQ.

ISBN: (纸本)9781478015567;9781478022800

摘要： In The Emancipation Circuit Thulani Davis provides asweeping rethinking of Reconstruction by tracing how the fourmillion people newly freed from bondage created...

关键词： 死刑   大清律例   中华法治   治外法权   礼教之争  

摘要： 大清死刑在近两百年中外法制讨论中被极其夸张地烙上滥用、残酷的专政印记，最终造成晚清诸仕为迎列强而开法律西化之路。然而，法制不文明仅是西方夺取商业利益和治外法权，发动鸦片战争的借口，其根源在于法律帝国主义、尊孔禁令后的文明之争。将乾隆五年版《大清律例》中的死罪条文拆分成691种具体规定，解析死刑的分布格局和立法逻辑。多种策略分析后发现，死罪主要是杂犯、监候等基本不杀条文；律文立决条款只占10.27%,过半死罪由例文规定且立决率更高；立决以斩刑为主，绞刑以监候为主；死罪集中在刑律的人身犯罪，以伤亡侵财等加重结果为前提；立决只能是故意犯罪，死刑种类与尊卑、再犯、主犯及严重程度有关。正确看待《大清律例》传承了唐明律的高超立法技术，认识大清死刑中的律例关系、礼法合一、宽严相济，有助于重建和弘扬中华法治文明。

关键词： Community colleges   Computer science education   Empirical research   Equity in STEM education  

摘要： This study aimed to understand the identity and attitude of students enrolled in computer science (CS) or programming-related course at community colleges nationwide. This study quantitatively evaluation data for estimating the relationships between students’ identity and attitudes toward computer science with prior programming experience and other demographic factors. I distributed the survey to community college faculty of computer science programs nationwide. Questions for this study were adapted from the Computing Attitude Survey developed by Weibe, Williams, Yang,&Miller (2003). Using two robust quantitative statistical methodologies, I investigated the correlations and predictability of previous programming experience, gender, race, and age with participants' attitudes toward computer science. This study drew its inspiration from prior works of Dorn and Tew (2015) and Chen, Haduong, Brennan, Sonnert, and Sadler (2018), whose studies looked at previous experiences in programming with a favorable attitude toward computer science. The primary independent variable was a students’ prior programming experience. Under evaluation, the dependent variables were students' programming experience and demographic characteristics such as race, gender, and age. This investigation showed a significant association between programming experience and attitude toward computer science. Among the demographic variables evaluated, students' racial identity was the only factor found highly correlated with attitudes toward computer science. Future work will consider the association between participants' accumulated college credit hours and specific programming language effects on computer science attitudes.