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关键词： computer science approach   crime scene investigation   evidence   Fingerprint   forensic science  

摘要： Biometry is essential when it comes to personal identification and verification in forensic applications, and the fingerprint is one of the most commonly used biometric features in the field of biometric identification. To detect fingerprints at the crime scene, to collect and transfer fingerprints in a way not to modify its nature, to make appropriate enhancements without causing loss of data on fingerprints, to preserve and store fingerprints are complex processes. Appropriate realization of these processes is essential for crime scene investigation. This study analyses and evaluates the crime scene investigation in a detailed way from a computer science perspective with a special focus on fingerprints, and whole process is divided into three components. In light of the studies conducted in the literature, 14 main problems that are encountered in the realization of these three components have been identified and criticized. Afterwards, the disciplines supported by forensic science, and the components that compose the crime scene are evaluated on the basis of four basic challenges encountered in the processes. Finally, to overcome 14 problems and four challenges, six technology-supported solutions are presented. [ABSTRACT FROM AUTHOR]

关键词： Optimization   Benchmark testing   Computational efficiency   Estimation   Dimensionality reduction   Evolutionary computation   Computer science   Cooperative coevolution (CC)   dynamic grouping (DyG) strategy   large scale global optimization (LSGO)   nonseparable problems   DIFFERENTIAL EVOLUTION   ALGORITHMS  

摘要： The cooperative coevolution (CC) framework achieves a promising performance in solving large scale global optimization problems. The framework encounters difficulties on nonseparable problems, where variables interact with each other. Using the static grouping methods, variables will be theoretically grouped into one big subcomponent, whereas the random grouping strategy endures low efficiency. In this paper, a dynamic CC framework is proposed to tackle the challenge. The proposed framework works in a computationally efficient manner, in which the computational resources are allocated to a series of elitist subcomponents consisting of superior variables. First, a novel estimation method is proposed to evaluate the contribution of variables using the historical information of the best overall fitness. Based on the contribution and the interaction information, a dynamic grouping strategy is conducted to construct the dynamic subcomponent that evolves in the next evolutionary period. The constructed subcomponents are different from each other, and therefore the required parameters to control the optimization of each subcomponent vary a lot in each evolutionary period. A stage-by-stage parameter adaptation strategy is proposed to adapt the optimizer to the dynamic optimization environment. Experimental results indicate that the proposed framework achieves competitive results compared with the state-of-the-art CC frameworks.

关键词： Evaluation of CAL systems   Interactive learning environments   Programming and programming languages   Secondary education   Teaching/leaming strategies   LEARNING ANALYTICS  

摘要： Block-based programming languages are becoming increasingly common in introductory computer science classrooms across the K-12 spectrum. One justification for the use of block-based environments in formal educational settings is the idea that the concepts and practices developed using these introductory tools will prepare learners for future computer science learning opportunities. This view is built on the assumption that the attitudinal and conceptual learning gains made while working in the introductory block-based environments will transfer to conventional text-based programming languages. To test this hypothesis, this paper presents the results of a quasi-experimental classroom study in which programming novices spent five-week using either a block-based or text-based programming environment. After five weeks in the introductory tool, students transitioned to Java, a conventional text-based programming language. The study followed students for 10 weeks after the transition. Over the course of the 15-week study, attitudinal and conceptual assessments were administered and student-authored programs were collected. Conceptual learning, attitudinal shifts, and changes in programming practices were analyzed to evaluate how introductory modality impacted learners as they transitioned to a professional, text-based programming language. The findings from this study build on earlier work that found a difference in performance on content assessments after the introductory portion of the study (Weintrop & Wilensky, 2017a). This paper shows the difference in conceptual learning that emerged after five weeks between the block-based and text-based conditions fades after 10 weeks in Java. No differences in programming practices were found between the two conditions while working in Java. Likewise, differences in attitudinal measures that emerged after working in the introductory environments also faded after 10 weeks in Java, resulting in no difference between the conditions

关键词： Computer science   Latent semantic analysis   Eye gaze tracking   Eye gaze tracking applications   Research trends   TRACKING  

摘要： Eye gaze tracking has been used to study the influence of visual stimuli on consumer behavior and attentional processes. Eye gaze tracking techniques have made substantial contributions in advertisement design, human computer interaction, virtual reality and disease diagnosis. Eye gaze estimation is considered critical for prediction of human attention, and hence indispensable for better understanding human activities. In this paper, Latent Semantic Analysis is used to develop an information model for identifying emerging research trends within eye gaze estimation techniques. An exhaustive collection of 423 titles and abstracts of research papers published during 2005-2018 were used. Five major research areas and ten research trends were classified based upon this study.

摘要： Modern computing is based in large part on an important abstraction called the von Neumann model. In this model, the program consists of a series of instructions stored in memory. The computing hardware performs the program by executing the instructions in sequential order. This basic model constitutes a contract that allows software developers to construct programs based on a simple, easy to understand execution model while delegating the details of the execution of those instructions to the hardware. Yale Patt and his colleagues have been responsible for pioneering new approaches to the design of computer systems that achieve increased performance by automatically identifying instructions that can be performed in parallel. This approach allows us to preserve the model of sequential execution while reaping the performance benefits associated with concurrency.

关键词： Query processing   Finance   Big Data   Data acquisition   Histograms   Computer science   Data integration   approximate query processing   synopsis   sampling   bounded error  

摘要： OLAP is a core functionality in database systems and the performance is crucial to enable on-time decisions. However, OLAP queries are rather time consuming, especially on large datasets, and traditional exact solutions usually cannot meet the high-performance requirement. Recently, approximate query processing (AQP) has been proposed to enable approximate OLAP. However, existing AQP methods have some limitations. First, they may involve unacceptable errors on skewed data (e.g., long-tail distribution). Second, they require to store large amount of data and have no significant performance improvement. Third, they only support a small subset of SQL aggregation queries. To overcome these limitations, we propose a bounded approximate query processing framework ${\mathtt {BAQ}}$BAQ. Given a predefined error bound and a set of queries, ${\mathtt {BAQ}}$BAQ judiciously selects high-quality samples from the data to generate a unified synopsis offline, and then uses the synopsis to answer online queries. Compared with existing methods, ${\mathtt {BAQ}}$BAQ has the following salient features. (1) ${\mathtt {BAQ}}$BAQ does not need to generate a synopsis for each query while it only generates a unified synopsis, and thus ${\mathtt {BAQ}}$BAQ has much smaller synopsis. (2) ${\mathtt {BAQ}}$BAQ achieves much smaller error than existing studies. Specifically, ${\mathtt {BAQ}}$BAQ can provide deterministic approximate results (i.e., the estimated query results must be within the error bound with 100 percent confidence) for SQL aggregation queries that do not contain selection conditions on numerical columns. For queries with selection conditions on numerical columns, we propose effective grouping-based techniques and the estimated results are also within the error bound in practice. Experimental results on both real and synthetic datasets show that ${\mathtt {BAQ}}$BAQ significantly outperforms state-of-the-art approaches. For example, on a Microsoft production dataset (a real da

摘要： The article focuses on the implementation by Wyoming public schools of a curriculum that places computer science among the major subjects to study at the elementary level. Topics covered include the aims of the computer science standards drafted by a team of statewide education professionals, the two roles of the Wyoming Department of Education in implementing the curriculum standard, and goals of the standard for various grade levels.

关键词： Subspace constraints   Strips   Binary trees   Computational modeling   Software testing   Computer science   Adaptive random testing (ART)   orthogonal recursive bisection   partition testing   random testing (RT)   restricted random testing   PROPORTIONAL SAMPLING STRATEGY   SOFTWARE   PARTITION   ALGORITHMS  

摘要： One goal of software testing may be the identification or generation of a series of test cases that can detect a fault with as few test executions as possible. Motivated by insights from research into failure-causing regions of input domains, the even-spreading (even distribution) of tests across the input domain has been identified as a useful heuristic to more quickly find failures. This finding has encouraged a shift in focus from traditional random testing (RT) to its enhancement, adaptive random testing (ART), which retains the randomness of test input selection, but also attempts to maintain a more evenly distributed spread of test inputs across the input domain. Given that there are different ways to achieve the even distribution, several different ART methods and approaches have been proposed. This paper presents a new ART method, called ART by orthogonal recursive bisection (ART-ORB), which explores the advantages of repeated geometric bisection of the input domain, combined with restriction regions, to evenly spread test inputs. Experimental results show a better performance in terms of fewer test executions than RT to find failures. Compared with other ART methods, ART-ORB has comparable performance (in terms of required test executions), but incurs lower test input selection overheads, especially in higher dimensional input space. It is recommended that ART-ORB can be used in testing situations involving expensive test input execution.

摘要： Michael Posner pioneered the cognitive revolution in psychology, showing how the human mind-brain can be componentially analyzed using subtractive analysis of reaction time. Applying this logic to brain imaging, he subsequently founded the field of human cognitive neuroscience. His work on attention showed how attention could be automatic or controlled, and his techniques for assessing individual differences in attention have been widely applied, including in the study of human development.

摘要： As the twenty-first century progresses, the influence of race, ethnicity, gender, and class in crime and punishment continues to be a pressing and polemic issue. With various antisocial control movements taking place, particularly in response to the Trump administration, the nature of crime and punishment is once again being redefined nationally and abroad. As in the past, this new punitive cycle of social control has revived support for what many consider to be the sanction of last resort: capital punishment. But executions, and capital punishment in general, are not directly governed by crime trends. Rather, the simultaneous interaction of historical and contemporary legacies, conflictive race and ethnic relations, and the influence of various extralegal factors like citizenship, nationality, language, accent, skin color, and economics influence the use of such punishment. The history of the death penalty in the United States is a story shaped and reshaped by the race and ethnicity of the offender and victim, and further fused by other intertwining factors at different points in time and geography. But because of the traditional adoption of a racially dichotomous black/white approach in investigating capital punishment, little is actually known about the experiences of executed Mexicans and other Latinos. As such, to debunk historical myths about the effects of race and ethnicity in capital punishment in the United States one needs to document the Mexican and Latino experiences which have been left out of the pages of history.