waashk/dblp huggingface dataset:
weaving models in conflict detection specifications. increasingly, model driven development is being accepted as the new vision for designing software. in fact, shifting the focus from a code-centric standpoint to a model-centric one enables a better specification and understanding of domain specific concerns. since a software system undergoes to several refinement steps during its life cycle, last years have witnessed a growing demand for model versioning support. in this respect, the operation of merging different modifications and the related conflict management are of crucial relevance. usually, diverging modifications are detected by assuming a predefined set of situations; however, not always it is possible to predict all the problems since they cannot be detected only syntactically. hence, in this position paper it is proposed to leverage conflict detection and resolution by adopting design-oriented descriptions endowed with custom conflict specifications.
frequent pattern mining for kernel trace data. operating systems engineers have developed tracing tools that log details about process execution at the kernel level. these tools make it easier to understand the actual execution that takes place on real systems. unfortunately, uncovering certain types of useful information in kernel trace data is nearly impossible through manual inspection of a trace log. to detect interesting interprocess communication patterns and other recurring runtime execution patterns in operating system trace logs, we employ data mining techniques, in particular, frequent pattern mining. we present a framework for mining kernel trace data, making use of frequent pattern mining in conjunction with special considerations for the temporal characteristics of kernel trace data. we report our findings using our framework to isolate processes responsible for systemic problems on a linux system and demonstrate our framework is versatile and efficient.
towards security monitoring patterns. runtime monitoring is performed during system execution to detect whether the system's behaviour deviates from that described by requirements. to support this activity we have developed a monitoring framework that expresses the requirements to be monitored in event calculus - a formal temporal first order language. following an investigation of how this framework could be used to monitor security requirements, in this paper we propose patterns for expressing three basic types of such requirements, namely confidentiality, integrity and availability. these patterns aim to ease the task of specifying confidentiality, integrity and availability requirements in monitorable forms by non-expert users. the paper illustrates the use of these patterns using examples of an industrial case study.
a relative cost model for xquery. xquery is a functional query language for xml. we propose a relative xquery cost model that is able to estimate the performance gain during source level transformation. this research facilitates the evaluation of various rewriting techniques without introducing real engines. the cost model consists of simple recursive functions based on functional language constructs. they are determined using formal semantics and other known efficient algorithms. analytic comparison of costs between expressions before and after transformation is possible in an engine-independent manner. the relativity of the model allows uninterpreted components within, which do not affect the mathematical proof of the comparison. moreover, it can be tailored to reflect engine specific evaluation strategies such as the order of evaluation of operands.
worldsens: a fast and accurate development framework for sensor network applications. in this article, we present worldsens, a fast and accurate development framework for sensor network applications. world-sens offers an integrated platform for the design, development, performance evaluation and profiling of applications. it relies on two simulators, wsnet and wsim, which are used throughout the application design and implementation, from the high level design choices to the implementation validation. wsnet is a modular event-driven wireless network simulator while wsim is a full platform hardware simulator which takes the target binary code as input and uses instruction cycles as time reference. wsnet and wsim can be used in conjunction to offer a distributed simulation of sensor networks with instruction and radio byte accuracy.
dual proximity neighbour selection method for peer-to-peer-based discovery service. in this paper, we propose a new, dual method for self-optimization of a pervasive, dht-based discovery service. this method addresses the topology mismatch problem. on one hand, it selects close neighbours based on static, readily available information (the ip addresses of the nodes) and thus does not require costly periodic probing of many nodes. on the other hand, it enables the overlay network to optimize its topology in run-time in a cost-effective manner. we prove the effectiveness of our method by statistical and experimental verification.
a self-organizing neural network for detecting novelties. in order to detect new events, a system must support on-line learning, adapting to pattern dynamic characteristics. studies of such adaptation have originated the novelty detection area, which aims at identifying unexpected or unknown patterns. these researches have motivated this work to propose the on-line and unsupervised self-organizing novelty detection (sonde) neural network. in this network, the creation of new neurons points out novelties. experiments evaluated the influence of sonde parameters and their capability to detect novelty events. these evaluations considered the datasets biomed, all-aml leukemia and dlbcl. results are compared to others from gwr.
a table-form extraction with artefact removal. we present a novel methodology for extracting the structure of handwritten filled table-forms. the method identifies the table-form line intersections, detecting and correcting wrong intersections produced by faulty line segments or by table artefacts. examples of artefacts are overlapping data, broken segments, and smudges. a novel method for artefact identification and deletion is also proposed. the last step performs the extraction of table-form cells. a database of 350 table-form images was used for evaluation, showing that the artefact identification method improves the performance of the table-forms structure extractor. the proposed approach reached a success rate of 85%.
mining and processing category ranking. as more and more data are becoming accessible, a naive retrieval of such data may often result in too many answers, as we commonly call "information overload".
fca-based approach for mining contextualized folksonomy. we present a novel approach to build the contextualized folksonomy and concept hieracrhies from tags of blogosphere based on formal concept analysis. our approach is based on the assumption that if a blog has the relationships with others, they would use the similar set of tags. we collect the sample data from blogosphere randomly and then build the concept hierarchies on the basis of the inclusion relations(tags) between the extensions(bloggers). we propose the formalization of the contextualized folksonomy in terms of formal concept analysis and show how our approach can be used to create the contextualized folksonmy for blogosphere. we evaluate our approach by considering an already existing tags of blogosphere.
an approach to evaluating structural pattern conformance of uml models. this paper describes an approach to evaluating the structural conformance of a uml class diagram to a design pattern. a design pattern is specified in an extension of the uml that defines the pattern as a family of models. a pattern specification consists of a set of pattern roles where a role specifies the properties of a pattern participant. the approach uses a divide-and-conquer method to evaluate pattern conformance. in the approach a pattern and the model being evaluated are decomposed into blocks. then, the model blocks are evaluated for conformance to the role blocks in the pattern. when all individual role blocks are satisfied by the model blocks, the pattern as a whole is considered to evaluate the entire conformance of the model. a major benefit of this approach is the support for variations of pattern realizations through the notion of pattern roles. we illustrate the approach using the visitor pattern and a price calculator, and demonstrate a prototype tool that supports the approach.
exploiting types for improved schema mapping. schema mapping in life sciences is complicated by several factors - heterogeneity and non-standard naming of scientific objects. traditional mapping techniques fail completely in many instances. this article suggests that exploiting type information and heuristic layout mining help map schemas in life science applications. in some cases, this method appears to be only approach that makes mapping possible in this area.
a connected component labeling algorithm for grayscale images and application of the algorithm on mammograms. a new algorithm for connected component labeling is presented in this paper. this algorithm requires only one scan through an image for labeling connected components. once this algorithm encounters a starting pixel of a component, it completely traces all the contour pixels and all internal pixels of that particular component. this algorithm recognizes components one at a time in the image while scanning in raster order. this property will be very useful in areas such as image matching, image registration and content-based information retrieval etc. this algorithm is also capable of extracting contour pixels of an image and storing them in the order of clock-wise direction which will provide very useful information in many applications. also this algorithm assigns consecutive label numbers for different components and hence needs a minimum number of labels. as our main research is on mammography image analysis for diagnosing breast cancers, we applied this algorithm to mammograms and measured performance of the algorithm in terms of processing time. this will be a useful algorithm in medical image analysis as a preprocessing tool.
graph-based text representation and knowledge discovery. for information retrieval and text-mining, a robust scalable framework is required to represent the information extracted from documents and enable visualization and query of such information. one very widely used model is the vector space model which is based on the bag-of-words approach. however, it suffers from the fact that it loses important information about the original text, such as information about the order of the terms in the text or about the frontiers between sentences or paragraphs. in this paper, we propose a graph-based text representation, which is capable of capturing (i) term order (ii) term frequency (iii) term co-occurrence (iv) term context in documents. we also apply the graph model into our text mining task, which is to discover unapparent associations between two and more concepts (e.g. individuals) from a large text corpus. counterterrorism corpus is used to evaluate the performance of various retrieval models, which demonstrates feasibility and effectiveness of graphic text representation in information retrieval and text mining.
supporting reconfigurable object distribution for customized web applications. in current practice, web applications are tightly coupled with the platforms that a particular service provider intends to support and the execution scenario envisioned at the design time. the resulting applications do not adapt well to all clients and runtime execution contexts. the goal of our research is to develop methods and software to support recon-figurable distributed applications which can be customized to specific requirements. we view a web application as a composition of actors, i.e. distributed active objects, and apply techniques of generative programming to develop a virtual application framework which separates the logic of objects from aspects relevant to object distribution on different platforms. we describe actorspec, a specification system allowing programmers to express desired object distribution and assisting application generators to produce highly customized versions of an application. the resulting flexibility facilitates the development of customizable web applications on an increasingly complex web infrastructure.
a model for managing collections of patterns. data mining algorithms are now able to efficiently deal with huge amount of data. various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. in many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could impact their business. nevertheless, those users are often overwhelmed by the large quantity of patterns extracted in such a situation. moreover, some privacy issues, or some commercial one may lead the users not to be able to mine the data by themselves. thus, the users may not have the possibility to perform many experiments integrating various constraints in order to focus on specific patterns they would like to extract. post processing of patterns may be an answer to that drawback. thus, in this paper we present a framework that could allow end users to manage collections of patterns. we propose to use an efficient data structure on which some algebraic operators may be used in order to retrieve or access patterns in pattern bases.
featherweight wrap java. we present an extension for a java like language with a mechanism for dynamically extending object behaviors. our approach consists in moving the addition of new features from class (static) level to object (dynamic) level: the basic features of entities (representing their structure) are separated from the additional ones (wrapper classes whose instances represent run-time added behaviors). at run-time, these entities can be dynamically composed by instantiating wrapper objects which are attached to basic entities. we formalize our extension by adding the new constructs to featherweight java; the core language so extended (featherweight wrap java) is type safe.
preattentive processing: using low-level vision psychology to encode information in visualisations. this paper explores the effects of two preattentive visual features, closure and depth, when performing the preattentive task of boundary detection. testing was performed on human subjects and the data was collected using a preattentive perception experiment. the post experimental questionnaire allowed subjects to indicate their estimate of the usefulness of each preattentive visual feature. the results indicate that both depth and closure are effective when performing boundary detection task. however, depth proved to be a more dominant than closure.
an mda approach to develop systems based on components and aspects. model-driven development and aspect oriented software development offer excellent support to modular reasoning, which can be used to develop component-based systems favouring a better software evolution. a development process based on model driven architecture (mda) to integrate components and aspects is presented in this paper. in order to do this, a uml profile to model systems based on components and aspects is suggested. then a set of model-to-model transformations at design level including the weaving among components and aspects, allow us to obtain the final system based on uml profile for the corba component model. the ccm code for the final systems is obtained by a model-to-code transformation. a specific tool (eclipse plugin) has been developed to support the software development based on aspect component based software development (acbse).
decentralized authorization and data security in web content delivery. the fast development of web services, or more broadly, service-oriented architectures (soas), has prompted more organizations to move contents and applications out to the web. softwares on the web allow one to enjoy a variety of services, for example translating texts into other languages and converting a document from one format to another. in this paper, we address the problem of maintaining data integrity and confidentiality in web content delivery when dynamic content modifications are needed. we propose a flexible and scalable model for secure content delivery based on the use of roles and role certificates to manage web intermediaries. the proxies coordinate themselves in order to process and deliver contents, and the integrity of the delivered content is enforced using a decentralized strategy. to achieve this, we utilize a distributed role lookup table and a role-number based routing mechanism. we give an efficient secure protocol, ideliver, for content processing and delivery, and also describe a method for securely updating role lookup tables. our solution also applies to the security problem in web-based workflows, for example maintaining the data integrity in automated trading, contract authorization, and supply chain management in large organizations.
square: scalable quorum-based atomic memory with local reconfiguration. internet-scale applications require more and more resources to satisfy the unpredictable clients needs. specifically, such applications must ensure quality of service despite bursts of load. distributed dynamic self-organized systems present an inherent adaptiveness that can face unpredictable bursts of load. nevertheless quality of service, and more particularly data consistency, remains hardly achievable in such systems since participants (i.e., nodes) can crash, leave, and join the system at arbitrary time. atomic consistency guarantees that any read operation returns the last written value of a data and is generalizable to data composition. to guarantee atomic consistency in message-passing model, mutually intersecting sets (a.k.a. quorums) of nodes are used. the solution presented here, namely square, uses self-adaptiveness and load-balancing to provide atomic consistency in large-scale dynamic distributed systems. this paper presents the square algorithm and uses extensive simulation to show it achieves its desirable properties.
a protocol to preserve a code of conduct. to fight community abuse, we introduce in this paper a set of simple, yet powerful, trust protocols, aimed at enforcing on a p2p network a boolean code of conduct verifiable by the network agents themselves. having a boolean code of conduct which honest agents never violate allows effective enforcing of it. a formal model for trust protocol definition and analysis is also defined, and properties of these protocols are formally defined and proved according to this model.
a weighted cache replacement policy for location dependent data in mobile environments. developing widely useful mobile computing applications presents difficult challenges. on one hand, mobile users demand intuitive user interfaces, fast response times, and deep relevant content. on the other hand, mobile devices have limited processing, storage, power, display, and communication resources. caching frequently accessed data items on the mobile client is an effective technique to improve the system performance in mobile environment. due to cache size limitation, the choice of cache replacement technique to find a suitable subset of items for eviction from cache becomes important. in this paper, we propose a new cache replacement policy for location dependent data in mobile environment. the proposed policy selects the predicted region based on client's movement and uses it to calculate the weighted data distance of an item. this makes the policy adaptive to client's movement pattern and provides importance to the regions around client's position. this is unlike earlier policies that consider the directional/non-directional data distance only. we call our policy the weighted predicted region based cache replacement policy (wprrp). simulation results show that the proposed policy significantly improves the system performance in comparison to previous schemes in terms of cache hit ratio.
semantic deep web: automatic attribute extraction from the deep web data sources. "deep web" refers to the rich information and data hidden in backend databases, etc., that search engines or web crawlers cannot access. it is mostly accessible through manual query interfaces. this paper introduces the semantic deep web, utilizing an ontology to determine relevance of query interface attributes to access the deep web. in addition, we present a novel approach to automatically extracting attributes from query interfaces in order to address the current limitations in accessing deep web data sources. our automatic attribute extraction method (1) identifies attributes that are used by query web page designers, called programmer viewpoint attributes, and (2) attributes that are presented as labels to users, called user viewpoint attributes. an ontology enriches the candidate query attributes by providing synonyms and by supporting the attributes used by designers and users. our experimental results in several e-commerce domains show that the attributes obtained by our algorithm compare favorably with manually determined attributes to be used for deep web queries.
evaluation of the qos of crash-recovery failure detection. crash failure detection is a key topic in fault tolerance, and it is important to be able to assess the qos of failure detection services. most previous work on crash failure detectors has been based on the crash-stop or fail-free assumption. in this paper we study and model a crash-recovery service which has the ability to recover from the crash state. we analyse the qos bounds for such a crash-recovery failure detection service. our results show that the dependability metrics of the monitored service will have an impact on the qos of the failure detection service. our results are corroborated by simulation results, showing bounds on the qos.
a preliminary design for digital forensics analysis of terabyte size data sets. digital forensics is computationally intensive and current analysis systems do not handle the multiple terabyte size data sets that are now becoming a major issue for analysis. for these data sets, raid file system analysis, parallel computing, collaboration, and visualization will be essential. here we outline the preliminary design for a parallel digital forensics framework that is being developed to handle multiple terabyte size data set analysis.
on-the-fly data integration models for biological databases. the web is a universal repository of information where there is an excellent opportunity to exploit the integration of online biological resources for knowledge discovery. a major challenge is to support the effective flow of information among the sources and services on the web and their interconnection with legacy systems that are designed to operate with traditional relational databases. to address this problem, a possible strategy is to combine information from disparate data sources and display it in a single integrated framework to the user without having to populate local databases. this is called online or on-the-fly data integration. bioxbase is a user-centric biological query system which extracts user requested query information over internet from multiple biological sources and organizes a wide variety of information into a homogeneous unified view to the user after data is cleaned, processed and integrated. bioxbase system has improved the results retrieved approximately by 30% compared to a system that has only a local database. the bioxbase system is further enhanced by 20% while combining the results of both biomap (a local database) and bioxbase (on the fly system), making the results more significant in biological domain. the results were validated by statistical methods such as precision, recall and power-law degree distribution analysis.