INTRODUCTION TO THE SPECIAL ISSUE ON CASE-BASED REASONING IN THE HEALTH SCIENCES

There has been an explosion of interest in health sciences applications of case-based reasoning (CBR), not only in the traditional CBR in medicine domain, but also in bioinformatics, enabling home health-care technologies, CBR integration, and synergies between CBR and knowledge discovery. This special issue features the best papers from the third workshop on CBR in the health sciences, held at ICCBR-05 in Madrid. It is the third in a series of exciting workshops, the first two of which were held at ICCBR-03, in Trondheim, Norway, and at ECCBR-04, in Madrid, Spain. The nine high-quality papers introduced here represent the research and experience of twenty-two authors working in eight different countries on a wide range of problems and projects. These papers illustrate some of the major trends of current research in CBR in the health sciences, and represent overall an excellent sample of the most recent advances of CBR in the health sciences.     

Older Adults’ Text Entry on Smartphones and Tablets: Investigating Effects of Display Size and Input Method on Acceptance and Performance

This study focuses on older adults’ finger-based text entry on smartphones and tablets. Thirty-two older adults entered Chinese characters with two input methods (typing and handwriting) on touch screens with four display sizes (3.5 in., 5 in., 7 in., 9.7 in.). Their performance, acceptance, preference, and errors were recorded and thus four findings were found. First, on small displays (3.5 in. and 5 in.), handwriting contributed to shorter task completion time, higher perceived ease of use, and higher usage intention than typing, but no difference was observed on large displays (7 in. and 9.7 in.). Second, there is a gap of task completion time and perceived ease of use between 5 in. and 7 in. for typing, whereas there is no gap for handwriting. Third, participants’ preference of 9.7 in. was almost the same as that of 7 in., and their preference of 7 in. was 1.5 times as strong as that of 5 in. Fourth, participants’ finger-based text entry was prone to 13 types of errors. Many of these errors were caused by the mismatch between older adults’ mental models and designers’ mental models.     

Stability of nonlinear hybrid dynamical systems with time delay via sum of squares decomposition

Considering an infinite number of eigenvalues for time delay systems, it is difficult to determine their stability. We have developed a new approach for the stability test of time delay nonlinear hybrid systems. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are found, stability’s analysis of the system is straight-forward. In this paper both delay-independent and delay-dependent stability tests are proposed, based on the construction of appropriate Lyapunov-Krasovskii functionals. The methodology is based on the sum of squares decomposition of multivariate polynomials and the algorithmic construction is achieved through the use of semidefinite programming. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be computationally infeasible to solve. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Finally simulation results show the correctness and validity of the designed method. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors wish to express their thanks to Dr. A. Papachristodoulou and Dr. M. Peet for their helpful comments and suggestions. Mohammad Ali Badamchizadeh was born in Tabriz, Iran, in December 1975. He received the B.S. degree in Electrical Engineering from University of Tabriz in 1998 and the M.Sc. degree in Control Engineering from University of Tabriz in 2001. He received the Ph.D. degree in Control Engineering from University of Tabriz in 2007. He is now an Assistant Professor in the Faculty of Electrical and Computer Engineering at University of Tabriz. His research interests include Hybrid dynamical systems, Stability of systems, Time delay systems, Robot path planning. Sohrab Khanmohammadi received the B.S. degree in Industrial Engineering from Sharif University, Iran in 1977 and the M.Sc. degree in Automatic from University Paul Sabatie, France in 1980 and the Ph.D. degree in Automatic from National University, ENSAE, France in 1983. He is now a Professor of Electrical Engineering at University of Tabriz. His research interests are Fuzzy control, Artificial Intelligence applications in control and simulation on industrial systems and human behavior. Gasem Alizadeh was born in Tabriz, Iran in 1967. He received the B.S. degree in Electrical Engineering from Sharif University, Iran in 1990 and the M.Sc. degree from Khajeh Nasir Toosi University, Iran in 1993 and the Ph.D. degree in Electrical Engineering from Tarbiat Modarres University, Iran in 1998. From 1998, he is a Member of University of Tabriz in Iran. His research interests are robust and optimal control, guidance, navigation and adaptive control. Ali Aghagolzadeh was born in Babol, Iran. He received the B.S. degree in Electrical Engineering in 1985 from University of Tabriz, Tabriz, Iran, and the M.Sc. degree in Electrical Engineering in 1988 from the Illinois Institute of Technology, Chicago, IL. He also attended the School of Electrical Engineering at Purdue University in August 1998 where he was also employed as a part-time research assistant and received the Ph.D. degree in 1991. He is currently an Associate Professor of Electrical Engineering at University of Tabriz, Tabriz, Iran. His research interests include digital signal and image processing, image coding and communication, computer vision, and image analysis.     

The application of IT in organisations: Some trends and issues

Abstract

This paper describes some trends and issues in the application of information technology in organisations. Technology trends are outlined in the areas of computing power, telecommunications, networking, software and standards. Some trends in the applications of IT are described with respect to developments in information systems and office automation. Some differences in the likely role of IT in the industrialised and developing countries are discussed. The second half of the paper deals with issues in the management of IT applications in organisations, and issues are identified as being political, organisational and social in nature in addition to technical. A social systems framework is proposed for the analysis of these issues. Some specific IT issues are then discussed involving alternative stakeholder perspectives, the analysis of decision making processes, the process of consultation and communication and the organisational impacts of IT applications.     

Food security problems in sub-Saharan Africa: Operations Research as a tool of analysis

For many years, the author has been involved in teaching and research in the use of Operations Research as a tool of analysis to study food security problems in sub‐Saharan Africa, in particular, grass root problems of poor farmers. The paper presents an introduction to the way Operations Research methods have been applied in case studies and research projects, and discusses in retrospect the author's views on the strengths and limitations of the application of Operations Research. The paper has in particular been written for people who are not familiar with applications of Operations Research in agriculture, and are interested to learn about its potential usefulness in practice. The retrospective part is largely based on food security studies in e.g. Tanzania, Burkina Faso, Bénin, Togo and Eritrea and on participation in several interdisciplinary research programmes in Africa.     

符号网络链接预测算法研究综述

符号网络链接预测包括网络结构上两个节点间未知链接的可能性预测与符号预测两方面,其相关研究对于分析和理解符号网络的拓扑结构、功能及演化行为具有十分重要的意义,在个性化推荐、态度预测、蛋白质交互作用研究等领域有着重大的应用价值。文中综述了符号网络链接预测问题的研究成果,介绍了相关概念、符号网络的理论基础、常用符号网络数据集以及预测精度评价标准;将目前主要的符号网络链接预测算法按照设计思路分为有监督学习与无监督学习两大类,详细阐述了每种算法的主要思想;归纳总结了符号网络链接预测问题的特点和规律,讨论了目前存在的问题并指出了面临的挑战和未来可能的发展方向。这能为信息学、生物学、社会学等领域的相关研究人员提供有益参考。     

The use of pattern recognition methods in tasks of biomedical diagnostics and forecasting

Questions of use of pattern recognition methods in medical tasks are discussed. The Recognition program system is presented, which contains a variety of pattern recognition and cluster analysis methods. Some methods based on voting by a system of regularities are discussed in more detail. An example of solved tasks of hysteromyoma relapse forecasting is given. The text was submitted by the authors in English. Yuri Ivanovich Zhuravlev. Born in Voronezh on January 14, 1935. In 1957, graduated from Moscow State University. Doctor of physics and mathematics since 1965, professor since 1967, and an academician of the RAS since 1992. Deputy director of the Dorodnicyn Computing Center of the RAS, chair of the Mathematics Department of the RAS, head of the Chair of Moscow State University, and editor in chief of Pattern Recognition and Image Analysis. Foreign member of the Spanish Royal Academy of Sciences, the National Academy of Sciences of Ukraine, and the European Academy of Sciences. Winner of the Lenin and Lomonosov prizes. Main fields of scientific interest: mathematical logic; control systems theory; the mathematical theory of pattern recognition, image analysis, and forecasting; operation research; and artificial intelligence. Developed such new lines of research as the theory of local optimization algorithms, algorithms of estimate calculation, and the algebraic theory of recognition algorithms. Oleg Valentinovich Senko. Born in Salavat, Bashkortostan, in 1957. In 1981, graduated from the Moscow Institute of Physical Technology; in 1985–1989, took graduate courses, receiving a PhD in 1990. Senior researcher, Dorodnicyn Computing Center, RAS. Doctor of physics and mathematics since 2007. Scientific interests: data mining, mathematical models of pattern recognition, classification and forecasting, and practical applications in medicine and other fields. Vladimir Vasilievich Ryazanov. Graduated from the Moscow Institute of Physical Technology in 1973 and completed graduate courses at the Computing Center of the USSR Academy of Sciences in 1976. Received a PhD in 1977 in computer science and the degree of professor in 1994 (“Applications of Mathematical Methods, Mathematical Modeling, and Computers in Scientific Research”). At the Dorodnicyn Computing Center of the RAS since 1976. Head of the Situations Recognition Sector in the Department of Recognition Problems and Combinatorial Analysis. Author of approximately 150 papers. Scientific interests: data mining; mathematical models of pattern recognition; classification and forecasting; optimization of recognition and classification models; learning; synthesis of optimal collective solutions in the problem of classification; creation of intelligent program systems for data analysis and recognition; and practical applications in technology, medicine, and industry. Anna Victorovna Kuznetsova. Born in Samara (Kuibyshev) in 1961. In 1986 graduated from the Second Moscow Medical Institute. In 1991–1994, took graduate courses, receiving a PhD in biology in 1995. Senior researcher, Emanuel Institute of Biochemical Physics. Scientific interests: pattern recognition, intellectual methods of data analysis, and development of diagnostic and forecasting algorithms in medicine and biological and medical applications in medicine and other fields. Mikhail Afanasievich Botwin. Born in the village of Rashevka of Poltava oblast in Ukraine in 1941. Doctor of medical sciences and Professor of the Sechenov Moscow Medical Academy. Scientific interests: hysteromyoma: pathogenesis, diagnostics, influence on pregnancy, aperiodicities of birth activity, methods of treatment.     

Applying and combining three different aspect Mining Techniques

Understanding a software system at source-code level requires understanding the different concerns that it addresses, which in turn requires a way to identify these concerns in the source code. Whereas some concerns are explicitly represented by program entities (like classes, methods and variables) and thus are easy to identify, crosscutting concerns are not captured by a single program entity but are scattered over many program entities and are tangled with the other concerns. Because of their crosscutting nature, such crosscutting concerns are difficult to identify, and reduce the understandability of the system as a whole. In this paper, we report on a combined experiment in which we try to identify crosscutting concerns in the JHotDraw framework automatically. We first apply three independently developed aspect mining techniques to JHotDraw and evaluate and compare their results. Based on this analysis, we present three interesting combinations of these three techniques, and show how these combinations provide a more complete coverage of the detected concerns as compared to the original techniques individually. Our results are a first step towards improving the understandability of a system that contains crosscutting concerns, and can be used as a basis for refactoring the identified crosscutting concerns into aspects. M. Ceccato is a PhD student in ITC-irst in Trento, Italy. He received his degree in Software Engineering from the University of Padova, Italy, in 2003. The master thesis concerned the Re-engineering of an existing big-sized data warehouse application. The project was developed in the Information Technology department in Alcoa Servizi. His research interests are on source code analysis and manipulation, especially for the the migration of object-oriented code to aspect-oriented programming. He collaborates with King’s College London and Loyola College in Maryland on the automatic support for this migration process. He has been involved in the organization and in the program committee of a number of AOP-related events, such as Late Workshop, in Chicago (2005) and in Bonn, Germany (2006), held within the major Aspect Oriented Programming conference (AOSD) and 3rd European Workshop on Aspects in Software (EWAS’06) in Enschede, The Netherlands. Marius Marin is a Ph.D. researcher in the Software Evolution Reseach Laboratory at Delft University of Technology, the Netherlands. He was granted an engineering degree by the Technical University of Civil Engineering, Bucharest, in 2000, and Licentiate in Economic Computer Science from the Academy of Economic Studies, Bucharest, in 2002. Before starting his Ph.D. studies, he worked as a software engineer in industry. His main research interests are in the area of reverse engineering, software modularization and modeling, and aspect-oriented software development. He is the main author of the publicly available aspect mining tool FINT and he publishes at international conferences in the aforementioned topics. He has been involved in program- and organizing committees of several workshops related to aspect mining. Kim Mens obtained his Ph.D. in Computer Science at the Vrije Universiteit Brussel, on “architectural conformance checking,” for which he used a declarative meta-programming approach. After his Ph.D. he became a full-time professor (chargé de cours) at the Université catholique de Louvain-la-Neuve (UCL). In addition to his current interest in logic meta-programming and intensional views, Kim Mens is one of the originators of the reuse contracts technique for automatically detecting conflicts in evolving software. He has been formally involved in several research networks related to software evolution. He has a strong interest in object-oriented and aspect-oriented software development and has actively participated in the organization of several workshops and conferences on those topics. He combines all these different research interests under the common denominator of co-evolution (between source code and earlier life-cycle software artifacts). Other research topics that fit this common theme and in which he is interested are software architecture, software maintenance, reverse engineering, software transformation, software restructuring and renovation, aspect mining and evolution of aspect programs. L. Moonen is an assistant professor in the Software Evolution Research Lab at Delft University of Technology and a researcher at the Centre for Mathematics and Computer Science (CWI), the Netherlands. His research interests are the design and development of advanced program analysis tools and techniques that support development, maintenance and evolution of large software systems. Concrete topics include the reverse engineering and exploration of views on software systems and their use for understanding and assessing software quality attributes such as evolvability, reliability and security. Dr. Moonen received an MSc (cum laude, Computer Science, 1996) and PhD (Computer Science, 2002) from the University of Amsterdam. He is one of the founders of the Software Improvement Group, a company that specializes in tools and consultancy to help organizations solve their legacy problems. He publishes regularly at, and serves on organizing-, steering- and program committees of, international workshops and conferences on reverse engineering (WCRE), source code analysis (SCAM), software maintenance (ICSM), program understanding (ICPC), reengineering (CSMR), aspect mining (Dagstuhl 06302, TEAM) and software security (CoBaSSA). Paolo Tonella is a senior researcher at ITC-irst, Trento, Italy. He received his laurea degree cum laude in Electronic Engineering from the University of Padova, Italy, in 1992, and his Ph.D. degree in Software Engineering from the same University, in 1999, with the thesis “Code Analysis in Support to Software Maintenance.” Since 1994 he has been a full time researcher of the Software Engineering group at ITC-irst. He participated in several industrial and European Community projects on software analysis and testing. He is the author of “Reverse Engineering of Object Oriented Code,” Springer, 2005. His current research interests include reverse engineering, aspect oriented programming, empirical studies, Web applications and testing. Tom Tourwé obtained the degree of Licentiate in Computer Science in 1997 and Ph.D. in Science in 2002 at the Vrije Universiteit Brussel. He is currently associated to the Centrum voor Wiskunde en Informatica, based in Amsterdam, The Netherlands, where he works as a post- doctoral researcher in the Ideals project. His main research interests lie in the broad area of software engineering, and include aspect-oriented software evolution and re-engineering in particular. He published several peer-reviewed articles on these topics in international journals and conferences, and organised a number of workshops on those themes.     

矿用IP广播对讲系统设计

提出了一种本质安全型矿用IP广播对讲系统的设计方案,详细介绍了该系统的结构组成、主要功能和主要设备的设计。该系统基于煤矿现有的以太环网传输平台和TCP/IP协议,综合应用计算机、网络、VOIP、嵌入式系统等技术将语音信号转换成标准的IP包在以太网上传输,系统连接简单,布线方便,传输距离远,音质好,稳定可靠。该系统除具备传统的广播功能外,还可以实现双向扩音对讲功能,为煤矿安全生产调度、安全避险和应急救援提供了有力的保障。     

Contour tracking on ultrasound sequences of vascular images

Simple vascular measurements on sequences of echographic images can be used to quantify important indexes of cardiovascular risk. The measurement of the intima-media thickness and the characterization of the endothelial function are but two examples. Real-time image processing systems would be helpful to automatically track, locate, and discriminate vascular structures through image sequences. Many algorithms have been developed to accomplish this task and they are generally based on the application of a mathematical operator at the points of a starting contour and on an iterative procedure that brings the starting contour to the final contour. In this paper, the performances of a mathematical operator that exploits both temporal and spatial information are compared to those of an operator that only exploits spatial information. The paper shows that, in general, when tracking contours on image sequences and when two or more gray-level discontinuities are present and close to each other, as in the case of arteries, both operators should be used in sequence. The text was submitted by the authors in English. Marcello Demi was born in Cecina, Italy, in 1956. He graduated in Electronic Engineering from the University of Florence, Italy in 1985. He is currently head of the Computer Vision Group at the CNR Institute of Clinical Physiology in Pisa and he teaches a course on Medical Image Processing at the faculty of Applied Physics, University of Pisa. His research interests are image processing systems and filtering schemes inspired by the early stages of biological vision systems. He has 80 scientific publications and his objective is the development of common projects with people who work in the area of biological vision for the purpose of both understanding biological vision and developing image processing systems. Elisabetta Bianchini was born in Lucca, Italy, in 1975. She received the degree in Electronic Engineering from the University of Pisa, Italy, in 2004. Since 2004 she is junior research at CNR, the Italian National Research Council, at the DSP lab in IFC (Institute of Clinical Physiology). Her field of interest is image processing and in particular development of methods for the assessment of indices of cardiovascular risk from ultrasound images. She is author or co-author of 14 scientific publications in international journals and conference proceedings. Francesco Faita was born in 1973 in La Spezia (Italy). In 2001 he graduated from Università degli Studi di Pisa obtaining the degree of Electronic Engineer. Since 2001, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in Computer Vision, in particular in the field of ultrasound image motion estimation. A major focus of his research in the last years has been development of clinically applicable automated techniques for cardiovascular analysis and prediction of disease progression. He is author or co-author of 58 scientific publications in international journals and conference proceedings. Viencenzo Gemignani was born in 1969, in Viareggio (Italy). In 1995, he graduated in Electronic Engineering from the University of Pisa. Since 1996, he has been working at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests are in diagnostic ultrasound, realtime image analysis and non-invasive patient monitoring systems. He teaches a course on DSP processors at the Faculty of Engineering, University of Pisa. He is author or coauthor of 40 scientific publications in international journals and conference proceedings and is co-inventor of 4 patents in the field of ultrasonic image processing.     

A new method of embedded fourth order with four stages to study raster CNN simulation

A new Runge-Kutta （PK） fourth order with four stages embedded method with error control is presentea m this paper for raster simulation in cellular neural network （CNN） environment. Through versatile algorithm, single layer/raster CNN array is implemented by incorporating the proposed technique. Simulation results have been obtained, and comparison has also been carried out to show the efficiency of the proposed numerical integration algorithm. The analytic expressions for local truncation error and global truncation error are derived. It is seen that the RK-embedded root mean square outperforms the RK-embedded Heronian mean and RK-embedded harmonic mean.     

Human factors in quality management

This article shows the results of research regarding the importance and the role of human factors in quality management in production enterprises. In creating the concept of systematizations of human factors in quality management an anthropocentrism rule was accepted and resulting from it a category of life quality. Acceptance of this rule led to a multiaspect and comprehensive approach to human factors in quality management. An interpretation of the notion of quality was made, adequate to needs, goals, and requirements of a human. Additionally, a cybernetic model of quality management system was elaborated. Human factors was exhibited in the manager's and executor's roles in quality management systems in enterprise as well as to the roles of creators, producers, and users (customers) in product life cycles. An existence of human factors in ISO norms regarding quality management, work safety, and hygiene management and environment management was also shown. The objective of this article is a comprehensive identification and systematization of aspects of human factors in quality management. © 2008 Wiley Periodicals, Inc.     

Mapping the vegetation changes in giant panda habitat using Landsat remotely sensed data

Since the 1950s, with national policy changes and socio-economic development, the habitat of the giant pandas has altered accordingly. This can also be inferred from the population changes of the giant pandas as reported in three national surveys. Thus, monitoring the changes in giant panda habitat and then taking appropriate action would be a valuable contribution to giant panda protection. In this paper, using existing habitats and potential habitats of the giant pandas as the study area, multitemporal remotely sensed data from the three national surveys are used as the data source. The land cover of the study area is mapped by the maximum likelihood classification (MLC) method. The overall accuracy and kappa statistics for the resulting classification are 0.8 and 90%, respectively. The results reveal that the current status of the giant panda habitat is very good. Between 1974 and 1989, because of deforestation in the area, the giant panda habitat deteriorated considerably; the total area of broadleaved forests, coniferous forests, mixed coniferous and deciduous broadleaved forests and shrubs decreased from 62.03% to 57.40% in the study area. However, from 1989 to 2002, due to the conservation policies put into action, the giant panda habitat recovered to some extent; the total area of broadleaved forests, coniferous forests, mixed coniferous and deciduous broadleaved forests and shrubs increased from 57.40% to 60.68% in the study area. However, conditions are different among the mountain systems. Taking into account only the total of broadleaved forests, coniferous forests, mixed coniferous and deciduous broadleaved forests and shrubs, in the Minshan mountain system, the forest cover changed from 57.70% in 1974 to 56.74% in 1989 and to 56.30% in 2002, which can be regarded as stable. In the Qinling mountain system, forested areas changed from 70.05% in 1974 to 66.93% in 1989 and to 67.17% in 2002, which reveals little change in this area. In the Qionglai mountain system, forested areas changed from 72.84% in 1974 to 71.53% in 1989 and to 73.22% in 2002; therefore, an increase can be noted in this area. In the Xiangling mountain system, forested areas also increased from 50.81% in 1974 to 50.20% in 1989 and to 53.15% in 2002. In the Liangshan mountain system, forested areas changed from 68.43% in 1974 to 55.81% in 1989 and to 60.07% in 2002. These results are in accordance with the giant panda population changes in different mountain systems. Thus, the best way to improve the threatened status of the panda population is to protect the current habitat and the potential habitat.     

Geographical distribution of global greening trends and their climatic correlates: 1982–1998

We examined trends in vegetation activity at the global scale from 1982 to 1998 using a recently developed satellite‐based vegetation index in conjunction with a gridded global climate dataset. Vegetation greening trends were observed in the northern high latitudes, the northern middle latitudes, and parts of the tropics and subtropics. Temperature, and in particular spring warming, was the primary climatic factor associated with greening in the northern high latitudes and western Europe. Temperature trends also explained greening in the US Pacific Northwest, tropical and subtropical Africa, and eastern China. Precipitation was a strong correlate of greening in fragmented regions only. Decreases in greenness in southern South America, southern Africa, and central Australia were strongly correlated to both increases in temperature and decreases in precipitation. Over vast areas globally, strong positive trends in greenness exhibited no correlation with trends in either temperature or precipitation. These areas include the eastern United States, the African tropics and subtropics, most of the Indian subcontinent, and south‐east Asia. Thus, for large areas of land that are undergoing greening, there appears to be no climatic correlate. Globally, greening trends are a function of both climatic and non‐climatic factors, such as forest regrowth, CO₂ enrichment, woody plant proliferation, and trends in agricultural practices.     

Interoperability requirements for automated manufacturing systems in construction

Multi-disciplinary software interoperability in the Architecture, Engineering, Construction and Operations industry is becoming a new and widely adopted business culture. Technical advances in interoperability architectures, frameworks, methods and standards during the last decade resulted in higher maturity of product and process models. Mature models, in effect, enable data exchange by an increasing number of software applications in the industry. This establishes trust in data exchange and results in the lower cost impact of inefficient interoperability. The negative cost impact increases with advancing life-cycle phase, from planning and design phase to construction phase and to operation and maintenance phase. Interoperability in the planning and design phase is most mature and well published, while interoperability in the construction phase and for automated manufacturing is less researched. This paper reviews state-of-the art automated manufacturing systems in construction and researches interoperability requirements for automated construction in context of the entire building lifecycle. Our research is based on experimental free-form clay building, designed with embedded simple HVAC components, and manufactured with additive layer technology. Conclusions provide valuable results for interoperability research and practice in construction projects with automated manufacturing systems in place.     

轻量级大数据运算系统Helius

针对Spark数据集不可变,以及Java虚拟机（JVM）依赖环境引起的代码执行、内存管理、数据序列化/反序列化等开销过多的不足,采用C/C++语言,设计并实现了一种轻量级的大数据运算系统--Helius。Helius支持Spark的基本操作,同时允许数据集整体修改;同时,Helius利用C/C++优化内存管理和网络传输,并采用stateless worker机制简化分布式计算平台的容错恢复过程。实验结果显示：5次迭代中,Helius运行PageRank算法的时间仅为Spark的25.12%~53.14%,运行TPCH Q6的时间仅为Spark的57.37%;在PageRank迭代1次的基础上,运行在Helius系统下时,master节点IP接收和发送数据量约为运行于Spark系统的40%和15%,而且200 s的运行过程中,Helius占用的总内存约为Spark的25%。实验结果与分析表明,与Spark相比,Helius具有节约内存、不需要序列化和反序列化、减少网络交互以及容错简单等优点。     

Rudiments of rough sets

Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops, and international conferences in recent years. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets in their programs. Rough set theory has led to many interesting applications and extensions. It seems that the rough set approach is fundamentally important in artificial intelligence and cognitive sciences, especially in research areas such as machine learning, intelligent systems, inductive reasoning, pattern recognition, mereology, knowledge discovery, decision analysis, and expert systems. In the article, we present the basic concepts of rough set theory and point out some rough set-based research directions and applications.