人脸检测技术的发展和现状研究

对人脸检测所面临的问题进行探讨,分析有关人脸检测问题的研究方法,并对其进行分类和评价。从基于模板的方法、基于肤色模型的方法、基于统计理论的方法三方面进行了阐述。分析各种方法的优缺点,并提出了关于人脸检测问题的进一步研究方向。     

基于支持向量机的图像情感分类

基于颜色对人类情感的影响,采用支持向量机作为分类算法完成天气图像的情感分类。同时,为了提高分类的准确率,采用了全局颜色直方图和局部颜色特征相结合的策略。实验表明,达到了较理想的分类效果。     

Adaptive Erkennung von Software-Entwurfsm?ngeln

Zusammenfassung Die Qualit?t von Software kann je nach Anwendungsgebiet an unterschiedlichen Kriterien gemessen werden. Für grosse Software-Systeme spielen u. a. Kriterien wie Wartbarkeit, Verst?ndlichkeit und Erweiterbarkeit eine wichtige Rolle. Mein Ziel ist es, Entwurfsm?ngel in Software-Systemen zu erkennen und somit „‘schlechte“’ – unverst?ndliche, schwer erweiter- und ?nderbare – Programmstrukturen zu vermeiden. Prominente Entwurfsm?ngel sind z. B. die von Fowler eingeführten Bad Smells in objektorientierten Programmen. Entwurfsm?ngel werden abh?ngig von der Sichtweise und dem Erfahrungsschatz des Suchenden unterschiedlich interpretiert. Ich kombiniere daher bekannte Verfahren zur Erkennung von Entwurfsm?ngeln auf der Basis von Metriken mit maschinellen Lernverfahren. Damit kann Entwurfsmangelerkennung individuellen Sichtweisen angepasst werden. Ich pr?sentiere ein Werkzeug für Java-Programme und zeige die Ergebnisse einer ersten Fallstudie.

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Criteria for software quality measurement depend on the application area. In large software systems criteria like maintainability, comprehensibility and extensibility play an important role. My aim is to identify design flaws in software systems automatically and thus to avoid “bad” – incomprehensible, hardly expandable and changeable – program structures. Depending on the perception and experience of the searching engineer, design flaws are interpreted in a different way. I propose to combine known methods for finding design flaws on the basis of metrics with machine learning mechanisms, such that design flaw detection is adaptable to different views. This paper presents the underlying method, describes an analysis tool for Java programs and shows results of an initial case study.

CR Subject Classification D.1.5,D.2.2,D.2.5,D.2.7,D.2.8,I.2.6     

Persistent Reusable Java Virtual Machine unter z/OS und Linux

Zusammenfassung Die Nutzung von Java zur Entwicklung von Anwendungen für Hochleistungstransaktionssysteme stellt besondere Anforderungen an die Isolation und das Leistungsverhalten in der transaktionalen Ausführung. In dem vorliegenden Beitrag wird eine neuartige Technologie beschrieben, die verbesserte Isolationseigenschaften und eine erhebliche Leistungssteigerung erm?glicht. Die Persistent Reusable Java Virtual Machine erweitert eine normale Java Virtual Machine um gemeinsam genutzte Klassen und um eine Reset-Funktionalit?t, die eine serielle Wiederverwendbarkeit erm?glicht. In einer Benchmark-Untersuchung unter z/OS wurde hiermit ein Performance-Gewinn um einen Faktor 325 im Vergleich mit einer normalen JVM erreicht. Für das Erstellen von Transaktionsanwendungen unter dem Betriebssystem z/OS sind Enterprise Java Beans damit eine ernstzunehmende Alternative zu bisherigen Programmiermodellen.

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The use of Java for the development of new applications in high-end transaction systems generates special isolation and performance requirements. A new technology offering improved isolation and a significant performance improvement is discussed in this article. The Persistent Reusable Java Virtual Machine extends a regular Java Virtual Machine by adding the facility to share classes and by providing a reset functionality, which permits serial reuse of the JVM. A z/OS benchmark demonstrated a performance improvement by a factor of 325, compared to a regular JVM. Thus the use of Enterprise Java Beans has to be considered as a serious alternative when developing new transactional applications under the z/OS operating system.

     

记忆的神话——对《1973年的弹子球》的解读

《1973年的弹子球》是一部寻找的小说。一方面叙述讲述了“我”和“鼠”如何努力摆脱异化．寻求人生的出口；另一方面叙述通过讲述这段往事。也在为自己现在的生活寻找出口。小说蕴涵着作希望人类通过写作获得拯救的美好心愿。     

A machine learning approach to investigating the effects of mathematics dispositions on mathematical literacy

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and psychological dispositions, in an integrated way as part of the same system. Large-scale assessments such as the Programme for International Student Assessment (PISA) provide an accessible and large volume of coherent data, and this gives researchers the opportunity to employ data-driven approaches to gain an overview of the system. For these reasons, we have used machine learning to explore the relationships between psychological dispositions and mathematical literacy in Australian 15-year-olds using the PISA 2012 data set. Our results from this strongly data-driven approach re-affirm the primacy of mathematics self-efficacy and highlight novel complex interactions between mathematics self-efficacy, mathematics anxiety and socio-economic status. In this paper, we demonstrate how education researchers can usefully employ data-driven modelling techniques to find complex non-linear relationships and novel interactions in a multidimensional data set.     

利用VMware虚拟机模拟RAID实验

本文论述了RAID实验在SAN网络基础课程中的重要性,利用VMware虚拟机模拟RAID实验的好处,并给出了实际的实验环境和步骤.     

A systematic analysis of performance measures for classification tasks

This paper presents a systematic analysis of twenty four performance measures used in the complete spectrum of Machine Learning classification tasks, i.e., binary, multi-class, multi-labelled, and hierarchical. For each classification task, the study relates a set of changes in a confusion matrix to specific characteristics of data. Then the analysis concentrates on the type of changes to a confusion matrix that do not change a measure, therefore, preserve a classifier’s evaluation (measure invariance). The result is the measure invariance taxonomy with respect to all relevant label distribution changes in a classification problem. This formal analysis is supported by examples of applications where invariance properties of measures lead to a more reliable evaluation of classifiers. Text classification supplements the discussion with several case studies.     

Concept unification of terms in different languages via web mining for Information Retrieval

For historical and cultural reasons, English phases, especially proper nouns and new words, frequently appear in Web pages written primarily in East Asian languages such as Chinese, Korean, and Japanese. Although such English terms and their equivalences in these East Asian languages refer to the same concept, they are often erroneously treated as independent index units in traditional Information Retrieval (IR). This paper describes the degree to which the problem arises in IR and proposes a novel technique to solve it. Our method first extracts English terms from native Web documents in an East Asian language, and then unifies the extracted terms and their equivalences in the native language as one index unit. For Cross-Language Information Retrieval (CLIR), one of the major hindrances to achieving retrieval performance at the level of Mono-Lingual Information Retrieval (MLIR) is the translation of terms in search queries which can not be found in a bilingual dictionary. The Web mining approach proposed in this paper for concept unification of terms in different languages can also be applied to solve this well-known challenge in CLIR. Experimental results based on NTCIR and KT-Set test collections show that the high translation precision of our approach greatly improves performance of both Mono-Lingual and Cross-Language Information Retrieval.