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关键词： Capital punishment   Legal decision-making   Racial inequities   Systemic bias  

摘要： Most judicial, regulatory, and administrative systems, at least formally, are concerned with the fairness and transparency of their decisions concerning the public. Fairness and transparency of criminal justice operations are critical to creating trust in the legal system and assuring people that the larger social system is legitimate and worthy of support. However, deviations from objective and fair decision-making can be concealed when key actors who are responsible for deciding outcomes in their organizations are also responsible for collecting, assembling, evaluating, and presenting the information on which their decisions are based. Under these conditions such systems are at risk of what we term "endogenous system bias," where data are acquired and altered in ways to justify desired outcomes that are neither fair nor transparent. The purpose of this paper is to: (1) develop a general model of decision-making constraints that can produce endogenous system bias, (2) review research on endogenous system bias at two key decision stages in one institution: the criminal justice system and (3) conduct an empirical examination of the potential effect of endogenous system bias on law enforcement investigations and prosecutorial charging in a sample of criminal homicide cases in the USA. Implications for law, policy, and social scientific methodology are discussed.

关键词： Fuzzy logic  

摘要： Criminalistics is another name for forensic science. It uses science in a criminal investigation as governed by judicial criteria of acceptable, relevant, and admissible evidence and criminal procedure. Forensic science has been around for a long time and has seen considerable changes, from fingerprint identification to DNA analysis and digital forensics. The study focuses on the most critical technologies in forensic science, then deconstructs numerous computer vision, image processing, and fuzzy logic methodologies in the large subject of forensic research. It also addresses the prospects for using the technology in approaches ranging from biometric identification to a 3D reconstruction of a crime scene. To some extent, adopting the numerous methodologies outlined in the paper helps overcome the disadvantages and challenges of traditional forensics procedures. Furthermore, some constraints are taken into account. For example, in various ways, the primary evidence is pre-processed and translated to an intermediate or more lucid form before the crux algorithms are applied. As a result, there is still plenty of room for research in this subject, such as developing solid algorithms, making the technology accept raw data, etc. If utilized correctly, forensic science technology has the potential to affect a paradigm shift in the criminal justice system. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Databases   Teamwork   Task analysis   Education   Proposals   Data models   Computer science   Learning competencies   peer evaluation   project-based learning (PBL)   teamwork  

摘要： Team project-based learning (TPBL) combines two learning techniques: 1) project-based learning (PBL) and 2) teamwork. This combination leverages the learning outcomes of both methods and places students in a real work situation where they must develop and solve a real project while working as a team. TPBL has been used in two advanced database subjects in Jaume I University (UJI)'s Computer Science degree program. This learning method was used for four years (academic years from 2018/2019 to 2021/2022) with positive outcomes. This study presents the project development, which includes teamwork formation, activities, timetable, and exercised learning competencies (both soft and specific). Further, the project's results were evaluated from three different perspectives: 1) teamwork evaluation by teammates;2) students' opinions on the subject and project;and 3) subject final grades.

关键词： Optimization   Evolutionary computation   Computer science   Transforms   Software engineering   Taxonomy   Systematics   Multiobjectivization via decomposition (MVD)   multiobjectivization via helper-objectives (MHOs)   multiobjectivization via scalarizing functions (MSFs)   multiobjectivization  

摘要： Multiobjectivization has emerged as a new promising paradigm to solve single-objective optimization problems (SOPs) in evolutionary computation, where an SOP is transformed into a multiobjective optimization problem (MOP) and solved by an evolutionary algorithm to find the optimal solutions of the original SOP. The transformation of an SOP into an MOP can be done by adding helper-objective(s) into the original objective, decomposing the original objective into multiple subobjectives, or aggregating subobjectives of the original objective into multiple scalar objectives. Multiobjectivization bridges the gap between SOPs and MOPs by transforming an SOP into the counterpart MOP, through which multiobjective optimization methods manage to attain superior solutions of the original SOP. Particularly, using multiobjectivization to solve SOPs can reduce the number of local optima, create new search paths from local optima to global optima, attain more incomparability solutions, and/or improve solution diversity. Since the term "multiobjectivization" was coined by Knowles et al. in 2001, this subject has accumulated plenty of works in the last two decades, yet there is a lack of systematic and comprehensive survey of these efforts. This article presents a comprehensive multifacet survey of the state-of-the-art multiobjectivization methods. Particularly, a new taxonomy of the methods is provided in this article and the advantages, limitations, challenges, theoretical analyses, benchmarks, applications, as well as future directions of the multiobjectivization methods are discussed.

关键词： Formal epistemology   Economics   Computer science   Mechanism design   Rationality   Game theory  

摘要： This article connects recent work in formal epistemology to work in economics and computer science. Analysing the Dutch Book Arguments, Epistemic Utility Theory and Objective Bayesian Epistemology we discover that formal epistemologists employ the same argument structure as economists and computer scientists. Since similar approaches often have similar problems and have shared solutions, opportunities for cross-fertilisation abound.

关键词： Executions   Sound   Silence   Emotions   Death   Resistance  

摘要： A robust literature addresses the historical transformation of executions, but it does so without attention to sound. To help us understand how the audible aspects of executions impacted these transformations, we develop a concept we call sonic flaws. Sonic flaws are characterized neither by their loudness nor their nuisance quality. Rather, sonic flaws are sounds that not only intrude upon but also undermine the social settings in which they are heard. As transgressions of not only the sonic but also the moral order, the notion of sonic flaws also captures sonic conflicts and resistances by sonic means. Based on an analysis of newspaper accounts of executions in the nineteenth and early twentieth century, we identify the construction of sonic flaws around three different types of sounds: sounds of emotions, sounds of death, and sounds of resistance. Most importantly, we show how managerial efforts to address sonic flaws turned the execution into a space guided by middle-class sensibilities and dominated by an aspiration for silence.

关键词： Symmetry groups   Geometry   Patterns   Computer science   Design analysis  

摘要： This research investigates how different symmetry group patterns influence the perception of an image interpreted by perforation of a planar material. To evaluate perception of perforated image, digital image processing tools (quantitative evaluation) and experts' opinion (qualitative evaluation) are applied with both results approaches summarized.

关键词： Computer science   Ethics   Law   Qualifications   Pensions   Data protection   Decision making  

摘要： Over the last 7 years arguing about matters of computer science in the legal system, the author has encountered a large number of incorrect technical propositions, advanced by asserted "IT experts." This article explores the wider ethical issues that arise from this situation and proposes a pathway for the computer science community to resolve the underlying problems.

关键词： Machine learning algorithms   Data science   Prediction algorithms   Education   Machine learning   Computer science   Data models   Artificial intelligence   cognitive psychology   cognitive bias   domain neglect   machine learning  

摘要： Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect bias and is discussed in this article from the cognitive psychology perspective. Background: ML algorithms are common components in electrical engineering, computer science, and data science curricula. Learning ML is challenging not only due to its complex mathematical and algorithmic aspects, but also due to: 1) the complexity of using these algorithms in the context of real-life situations correctly and 2) the comprehension of related social and ethical issues. Research Question: To what extent do students fail to correctly interpret the performance of ML algorithms due to the domain neglect bias and how can this bias be explained? Methodology: A questionnaire containing two questions was designed, in which the participants were asked to compare the performance of ML algorithms in the contexts of different application domains. The questions were designed to trigger the domain neglect bias which in turn, allowed quantification of its prevalence. Findings: One third of the students failed to recognize the outperforming ML algorithm due to the domain neglect bias. Educators should note this bias and develop new pedagogical methods for teaching ML performance in order to mitigate the bias.

关键词： STEM   Computer science   Career choice   Systematic mapping  

摘要： STEM disciplines are considered essential for human development, and they are associated with low unemployment rates and good economic prospects. However, many countries are faced with the problem of too few STEM graduates, which raises the question of why more students do not choose STEM majors. This study presents a systematic mapping of studies published prior to 2021 in Web of Science or Scopus in order to examine the research trends on the factors that cause students to choose a career in Computer Science, or more generically, in the STEM fields. These factors have been identified and classified in 3 categories: Environmental factors, Social influencers and Personal factors. The categories are made up of 4 levels of subcategories. We analyzed (1) the countries in which the study was conducted, (2) the characteristics of the study and (3) the frameworks used. The results show that the bulk of the studies were conducted in developed countries, mainly in North America and Europe. The frameworks most commonly used in the studies are Expectancy-Value Theory and Social Cognitive Career Theory, and consequently, the most commonly studied factors for STEM degrees are those related to personal psychological factors. For Computer Science degrees, the most frequently studied factor is career prospects. On the other hand, a small number of studies on the impact of social media on the choice of studies in the technology field were detected. Among the studies analyzed, there is great interest in determining the factors that specifically affect women and the differences between men and women, especially in studies dealing with the Computer Sciences. Furthermore, there are few studies that analyze the effect of informal educational experiences among women. Given that this kind of experiences has become very popular in recent years among women, future research should analyze their impact on the choice of STEM studies. Taking into account the current relevance of the social medi