Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey)

This study presents a data-driven and semiautomatic classification system carried out by object-based image analysis and fuzzy logic in a selected landslide-prone area in the Western Black Sea region of Turkey. In the first stage, a multiresolution segmentation process was performed using Landsat ETM+ satellite images of the study area. The model was established on 5235 image objects obtained by the segmentation process. A total of 70 landslide locations and 10 input parameters including normalized difference vegetation index, slope angle, curvature, brightness, mean band blue, asymmetry, shape index, length/width ratio, gray level co-occurrence matrix, and mean difference to infrared band were considered in the analyses. Membership functions were used to classify the study area by five fuzzy operators such as “and”, “or”, “mean arithmetic”, “mean geometric”, and “algebraic product”. In order to assess the performances of the so-produced maps, 700 image objects, which were not used in the model, were taken into consideration. Based on the results, the map produced by “fuzzy and” operator performed better than those classified by the other fuzzy operators. The proposed methodology applied in this study may be useful for decision makers, local administrations, and scientists interested in landslides. It may also be useful in landslide-prone areas for planning, management, and regional development purposes.     

An ontology-based framework to support intelligent data analysis of sensor measurements

In the past years, the large availability of sensed data highlighted the need of computer-aided systems that perform intelligent data analysis (IDA) over the obtained data streams. Temporal abstractions (TAs) are key to interpret the principle encoded within the data, but their usefulness depends on an efficient management of domain knowledge. In this article, an ontology-based framework for IDA is presented. It is based on a knowledge model composed by two existing ontologies (Semantic Sensor Network ontology (SSN), SWRL Temporal Ontology (SWRLTO)) and a new developed one: the Temporal Abstractions Ontology (TAO). SSN conceptualizes sensor measurements, thus enabling a full integration with semantic sensor web (SSW) technologies. SWRLTO provides temporal modeling and reasoning. TAO has been designed to capture the semantic of TAs. These ontologies have been aligned through DOLCE Ultra-Lite (DUL) upper ontology, boosting the integration with other domains. The resulting knowledge model has a modular design that facilitates the integration, exchange and reuse of its constitutive parts. The framework is sketched in a chemical plant case study. It is shown how complex temporal patterns that combine several variables and representation schemes can be used to infer process states and/or conditions.     

Scopira: an open source C++ framework for biomedical data analysis applications

In many biomedical research laboratories, data analysis and visualization algorithms are typical prototypes using an interpreted programming language. If performance becomes an issue, they are ported to C and integrated with interpreted systems, not fully utilizing object‐oriented software development. This paper presents an overview of Scopira, an open source C++ framework suitable for biomedical data analysis and visualization. Scopira provides high‐performance end‐to‐end application development features, in the form of an extensible C++ library. This library provides general programming utilities, numerical matrices and algorithms, parallelization facilities, and graphical user interface elements. Copyright © 2008 John Wiley & Sons, Ltd.     

An open source usability maturity model (OS-UMM)

User satisfaction has always been a major factor in the success of software, regardless of whether it is closed proprietary or open source software (OSS). In open source projects, usability aspects cannot be improved unless there are ways to test and measure them. Hence, the increasing popularity of open source projects among novice and non-technical users necessitates a usability evaluation methodology. Consequently, this paper presents a usability maturity model specifically aimed at usability-related issues for open source projects. In particular, the model examines the degree of coordination between open source projects and their usability aspects. The measuring instrument of the model contains factors that have been selected from four of our empirical studies, which examine the perspectives of OSS users, developers, contributors and the industry. In addition to presenting the usability maturity model, this paper discusses assessment questionnaires, a rating methodology and two case studies.     

An MHP framework to provide intelligent personalized recommendations about digital TV contents

Digital Television will bring a significant increase in the amount of channels and programs available to end users, with many more difficulties to find contents appealing to them among a myriad of irrelevant information. Thus, automatic content recommenders should receive special attention in the following years to improve their assistance to users. The current content recommenders have important deficiencies that hamper their wide acceptance. In this paper, we present a new approach for automatic content recommendation that significantly reduces those deficiencies. This approach, based on Semantic Web technologies, has been implemented in the AdVAnced Telematic search of Audiovisual contents by semantic Reasoning tool, a hybrid content recommender that makes extensive use of well‐known standards, such as Multimedia Home Platform, TV‐Anytime and OWL. Also, we have carried out an experimental evaluation, the results of which show that our proposal performs better than other existing approaches. Copyright © 2007 John Wiley & Sons, Ltd.     

An open source forensic tool to visualize digital evidence

Visualizing digital evidence in an easy and constructive manner is a major problem because of the advanced techniques for hiding, wiping, encrypting and deleting digital data developed during the last few years. Òo tackle this problem, a system for visualizing digital data in 3-dimensional (3D) mode has been developed. XML was used as a common language to allow fine-grained management of digital data with flexibility and ease. The extensibility of the implementation makes it particularly suitable as a research and development platform in the sector of open source computer forensics tools for the future. This article examines real-life problems that benefit from using this tool in a congenial and constructive manner to validate its key underlining concept. The design decisions that have been taken in producing the system architecture, and the features it supports are elaborated upon. To determine the effectiveness of the tool, an actual case study is presented which examines the results of the tool and why it is necessary to go for an open source model as a standard. The paper concludes with performance measurements of the tool and suggests possible extensions to make the tool even smarter.     

Empirical analysis of search based algorithms to identify change prone classes of open source software

There are numerous reasons leading to change in software such as changing requirements, changing technology, increasing customer demands, fixing of defects etc. Thus, identifying and analyzing the change-prone classes of the software during software evolution is gaining wide importance in the field of software engineering. This would help software developers to judiciously allocate the resources used for testing and maintenance. Software metrics can be used for constructing various classification models which can be used for timely identification of change prone classes. Search based algorithms which form a subset of machine learning algorithms can be utilized for constructing prediction models to identify change prone classes of software. Search based algorithms use a fitness function to find the best optimal solution among all the possible solutions. In this work, we analyze the effectiveness of hybridized search based algorithms for change prediction. In other words, the aim of this work is to find whether search based algorithms are capable for accurate model construction to predict change prone classes. We have also constructed models using machine learning techniques and compared the performance of these models with the models constructed using Search Based Algorithms. The validation is carried out on two open source Apache projects, Rave and Commons Math. The results prove the effectiveness of hybridized search based algorithms in predicting change prone classes of software. Thus, they can be utilized by the software developers to produce an efficient and better developed software.     

An open source program to generate zero-thickness cohesive interface elements

An open source program to generate zero-thickness cohesive interface elements in existing finite element discretizations is presented. This contribution fills the gap in the literature that, to the best of the author’s knowledge, there is no such program exists. The program is useful in numerical modeling of material/structure failure using cohesive interface elements. The program is able to generate one/two dimensional, linear/quadratic cohesive elements (i) at all inter-element boundaries, (ii) at material interfaces and (iii) at grain boundaries in polycrystalline materials. Algorithms and utilization of the program is discussed. Several two dimensional and three dimensional fracture mechanics problems are given including debonding process of material interfaces, multiple delamination of composite structures, crack propagation in polycrystalline structures.     

Beyond free software: An exploration of the business value of strategic open source

The phenomenon of open source software (OSS) has been well studied from the software development perspective, but it has received much less attention from the perspective of business value. Nevertheless, OSS, when viewed as a value creation process rather than ‘free’ software, provides businesses with value through access to knowledge and innovation capacity resident in online communities. This conceptualisation, which we label ‘strategic open source’ requires firms to rethink their strategy and processes as there is a shift in focus from ownership to openness and collaboration with external parties. Nonetheless, the emergence of OSS poses a puzzle for conceptions of organisational theory. Therefore, a theorising process is needed in order to develop a deeper understanding of how value is created and captured with OSS. Using a field study of eleven European firms, this paper explores the creation and capture of business value from strategic open source. The findings reveal that while decision makers look to open innovation initiatives like OSS for value creation and capture, there is still a desire to remain self reliant, resulting in collaborative design (of external innovations) rather than collaborative decision making with value network partners in relation to how such innovations would help create and capture value within firms.     

An associate constraint network approach to extract multi-lingual information for crime analysis

International crime and terrorism have drawn increasing attention in recent years. Retrieving relevant information from criminal records and suspect communications is important in combating international crime and terrorism. However, most of this information is written in languages other than English and is stored in various locations. Information sharing between countries therefore presents the challenge of cross-lingual semantic interoperability. In this work, we propose a new approach – the associate constraint network – to generate a cross-lingual concept space from a parallel corpus, and benchmark it with a previously developed technique, the Hopfield network. The associate constraint network is a constraint programming based algorithm, and the problem of generating the cross-lingual concept space is formulated as a constraint satisfaction problem. Nodes and arcs in an associate constraint network represent extracted terms from parallel corpora and their associations. Constraints are defined for the nodes in the associate constraint network, and node consistency and network satisfaction are also defined. Backmarking is developed to search for a feasible solution. Our experimental results show that the associate constraint network outperforms the Hopfield network in precision, recall and efficiency. The cross-lingual concept space that is generated with this method can assist crime analysts to determine the relevance of criminals, crimes, locations and activities in multiple languages, which is information that is not available in traditional thesauri and dictionaries.     

An open source Java web application to build self-contained web GIS sites

This work describes OWGIS, an open source Java web application that creates Web GIS sites by automatically writing HTML and JavaScript code. OWGIS is configured by XML files that define which layers (geographic datasets) will be displayed on the websites. This project uses several Open Geospatial Consortium standards to request data from typical map servers, such as GeoServer, and is also able to request data from ncWMS servers. The latter allows for the displaying of 4D data stored using the NetCDF file format (widely used for storing environmental model datasets). Some of the features available on the sites built with OWGIS are: multiple languages, animations, vertical profiles and vertical transects, color palettes, color ranges, and the ability to download data. OWGIS main users are scientists, such as oceanographers or climate scientists, who store their data in NetCDF files and want to analyze, visualize, share, or compare their data using a website.     

高分辨率遥感影像中提取复杂道路的新方法

从遥感影像中提取具有弱边缘线的道路具有相当大的难度,在综合了相位编组和动态规划两种原理的记错上,提出了针对这一问题的新方法。首先借鉴相位编组原理形成边缘线支持区并对其进行连接;然后利用动态规划方法从支持区中检测出边缘线并对这些线进行平滑;最后连接由边缘线构成的道路段,得出道路提取结果。实验表明,该方法可以较好地提取出无清晰连续边缘线的道路,对于边缘对比度较大的道路则可取得更为令人满意的结果。     

An agglomerative segmentation framework for non-convex regions within uterine cervix images

The National Cancer Institute has collected a large database of uterine cervix images termed “cervigrams”, for cervical cancer screening research. Tissues of interest within the cervigram, in particular the lesions, are of varying sizes and of complexnon-convex shapes. The tissues possess similar color features and their boundaries are not always clear. The main objective of the current work is to provide a segmentation framework for tissues of interest within the cervix, that can cope with these difficulties in an unsupervised manner and with a minimal number of parameters.     

An automated,objective and open source tool for stream threshold selection and upstream riparian corridor delineation

The extraction of stream networks from digital elevation models (DEMs) and delineation of upstream riparian corridors (URCs) for stream sampling points (SSPs) are frequently used techniques in freshwater and environmental research. Selection of an accumulation threshold (AT) for stream extraction and delineation of URCs are often done manually. Two algorithms are introduced in this paper that allow for automated AT selection and URC delineation. ATs are selected to yield the highest overlap of DEM-derived and traditionally mapped streams as well as to assure extraction of all mapped streams from DEMs. URCs are delineated after snapping SSPs to DEM-derived streams. The new tool showed similar or better performance than comparable algorithms and is freely available, interfacing the open source software packages R and GRASS GIS. It will improve the extraction of stream networks and the assessment of magnitude and scale of effects from riparian stressors (e.g. landuse) on freshwater ecosystems.     

求取真实运动矢量的一种算法

针对物体基视频编码与分割应用,提出了求取特征区域真实运动矢量的一种算法。首先,利用运动检测器将图像序列的每一帧分割成静止区域与运动区域。然后只对运动区域进行运动估计。为了克服传统块匹配法的固有缺点,本文算法采用变尺寸块匹配法,大的均匀区用大方块,运动物体的边缘区用小方块;在进行块匹配搜索期间,在易误匹配的区域,为了不遗漏真实的运动矢量,先按照ＭＡＥ准则预选出多个候选运动矢量,尽可能保证真实的运动矢量包含其中,接着再根据相邻块运动矢量的相关性,从多个候选运动矢量中选出一个比较可靠的运动矢量。实验结果表明,该算法产生的运动矢量真实可靠,而且一致性好,可用于识别可靠的运动区域。     

An approach to measuring influence and cognitive similarity in computer-mediated communication

While many explanations of influence have been proposed there is still debate over which is correct even though most are supported by empirical evidence. This uncertainty has been attributed to there being too little evidence of real-world influence networks, and an inability to separate influence from cognitive similarity, that is, a pre-existing like-mindedness, attitude or way of thinking shared among participants. This paper proposes theme resonance, a new metric for measuring both influence and cognitive similarity between and among participants in the same online conversation. Theme resonance is derived from two textual content analysis systems: Centering Resonance Analysis and qualitative thematic modeling. The use of theme resonance is demonstrated by constructing influence networks using online conversations in ten weblogs, allowing the propagation of new conversational themes to be traced from initiator though subsequent propagators. A method of separating influence from like-mindedness is also demonstrated. Depending on the metric chosen influence and its susceptibility were found both to be opposite ends of the same spectrum, and distinct attributes. In either case the majority of blog participants are close to the low end of each characteristic. However, those at the higher ends are shown to be easily and distinctly identified.     

R2P: An open source hardware and software modular approach to robot prototyping

Rapid prototyping is a key aspect for the development of innovative robotic applications. A modular, platform-based, approach is the way to obtain this result. Modular approaches are common for software development, but hardware is still crafted often re-inventing solutions every time. As a consequence, the resources that should be invested in the development of a new robot get often drained by the implementation of a physical, working prototype to test the application idea. To overcome this problem, we propose R2P (Rapid Robot Prototyping), a framework to implement real-time, high-quality architectures for robotic systems with off-the-shelf basic modules (e.g., sensors, actuators, and controllers), integrating hardware and software, which can be assembled in a plug-and-play way. R2P provides hardware modules, a protocol for real-time communication, a middleware to connect components as well as tools to support the development of software on the modules. R2P aims at dramatically reduce time and efforts required to build a prototype robot, making it possible to focus the resources on the development of new robotic applications instead of struggling on their implementation. This enables also people with experience in a specific application domain, but with little technical background, to actively participate in the development of new robotic applications. R2P is open-source both in its software and hardware to promote its diffusion among the robotics community and novel business models that will substantially reduce the costs to design a new robotic product.     

一种基于语义分析的汉语语音识别纠错方法

汉语语音识别的研究越来越重视与语言处理的结合,语音识别已经不是单纯的语音信号处理。N-gram语言模型应用到语音识别系统中,大大增强了系统的正确率和稳定性,但它也有其自身的局限性,使得语音识别出现许多语法和语义的错误结果。本文分析了语音识别产生语音和文字方面的错误的原因和类型,在概念层次网络语言模型的基础上提出了一种基于语句语义分析和混淆音矩阵的语音识别纠错方法。通过三个发音人、5万字的声音语料和216句实验语句的纠错测试,本文的纠错系统在纠正语义搭配型错误方面有比较好的表现,可克服N-gram语言模型带来的一些缺陷。本文提出的纠错方法还可以融合到语音识别系统中,以便更好地为语音识别的纠错处理服务。     

Seeing eye to eye? An exploratory study of free open source software users’ perceptions

This study develops a typology that permits the classification of free open source software (FOSS) users into market segments. Based on the typology the nature and extent of perception differences between core FOSS users and FOSS users in other market segments is examined. Significant perception differences are observed between users in different market segments. Consequently, the potential barriers to FOSS adoption are identified and recommendations that may drive greater FOSS adoption are proposed.