waashk/dblp huggingface dataset:
performance comparison of flow aware networking (fan) architectures under gridftp traffic. grid networks are large distributed systems that share and virtualize heterogeneous resources. quality of service (qos) is a key and complex issue for grid services provisioning. currently, most grid networks offer best-effort (be) services. thus, qos architectures initially developed for internet such as diffserv (ds) have been adapted to grid environment. since the widespread of internet, many grid networks will be deployed in the years to come over this technology. in this paper, we propose to compare two flow-aware networking (fan) architectures, mainly from the second generation (2gfan). the purpose is to answer the question of which 2gfan architecture performs better under grid traffic. fan is a promising option to ds for qos provisioning in internet networks. ds provides qos differentiation through explicit packet marking and classification whereas fan consist on per-flow admission control and implicit flow differentiation through priority fair queuing. the main difference between the two 2gfan architectures is the fair queuing algorithm. thus; to the knowledge of the authors, this is the first time two priority per-flow fair queuing algorithms are compared under grid traffic. a gridftp session may be seen as a succession of parallel tcp flows with large volumes of data transfers. metrics used are average delay, average goodput and the average rejection rate.
an approach based on metrics for monitoring web accessibility in brazilian municipalities web sites. monitoring and measuring the accessibility of government web sites is an important challenge for regulators and policy makers. moreover, over the next few years, e-government (e-gov) services are expected to expand and it is necessary to ensure access for everyone. in this paper, we present a metric based approach for evaluating municipalities web pages using automatic accessibility evaluation tools. the sampling of the pages was done by the tool e-govmeter, and the accessibility evaluation and generation of the metrics was done by means of an adaptation of the tool hera. the results show that much work should be done to improve the accessibility of brazilian municipalities web sites. although it has limitations, the use of automatically generated accessibility metrics is a powerful tool for helping measuring and monitoring the accessibility of e-gov web sites.
pathological voice discrimination based on entropy measurements. digital signal processing techniques have been used to analyze vocal disorders caused by laryngeal pathologies. laryngoscopical exams commonly used for detection of these diseases are invasive methods that cause discomfort to the patients. because of its noninvasive nature, acoustical analysis of the temporal and spectral features of the voice signal can be used as an auxiliary technique in laringoscopical exams. this analysis may be applied for detection of vocal diseases and the evaluation of the vocal quality of patients subjected to surgical processes or medical treatments in the vocal folds. this work aims at investigating the behavior of entropy measures in disordered voices influenced by the presence of pathologies in the vocal folds. for this purpose, the shannon entropy and the relative entropy are implemented, and their behavior for normal and pathological voices affected by vocal fold edemas is observed. the measurement of the entropy efficiency in discriminating between normal and pathological voices is obtained.
flexible pointer analysis using assign-fetch graphs. we propose a new abstraction for pointer analysis that represents reads and writes to memory instead of traditional points-to relations. compared to points-to graphs, our assign-fetch graph (afg) leads to concise procedure summaries that can be used in any calling context. also, its flexibility supports new analysis techniques with different trade-offs between speed and precision. for efficiency, we build a summary for each procedure that assumes distinct pointers from the environment are not aliased and restore soundness when the summary is used in a context with aliases. we present two pointer analysis techniques based on our afg. the first takes the flow-insensitive view adopted by many authors; the second considers statement ordering. in addition to being more precise, we find that this "flow-aware" analysis runs faster. we conclude with experimental results showing it is practical.
inkteractors: interacting with digital ink. digital inking systems accept pen-based input from the user, process and archive the resulting data as digital ink. however, the reviewing techniques currently available for such systems are limited. in this paper we formalize operators that model the user interaction during digital ink capture. such operators can be applied in situations where it is important to have a customized view of the inking activity. we describe the implementation of a player that allows the user, by selecting the desired operators, to interact with digitally annotated documents while reviewing them.
medical image analysis using mobile devices. mobile devices are increasingly being incorporated onto picture archiving and communication systems (pacs). previous work on medical image access using mobile devices essentially focuses on enabling the visualization of the medical images at the mobile devices. in contrast, we propose and develop a distributed system that allows medical image analysis using mobile devices. as a proof-of-concept, based on our distributed system, we develop a tool for dental implant simulation using mobile devices. we also discuss the perspectives of extending the current system to incorporate computer aided diagnosis (cad) algorithms in it.
tips: wrapping the sockets api for seamless ip mobility. tips (transparent ip sockets) is a wrapping implementation of specific functions of the bsd sockets api to provide support for transparent ip mobility at the application level. implemented on top of the transport layer it allows udp and tcp communications to be immune to both client and server terminal migration (single and double jump). location independent identification, and lossless data transmissions are provided with reduced overhead. the use of a distributed hash table for keeping terminal location information also allows for scalable operation.
on filtering irrelevant results in peer-to-peer search. to improve peer-to-peer (p2p) search accuracy, we identify multiword entities in user queries using an entity corpus constructed based on n-gram statistics collected from limewire users. we show that by using a statistical function, we can build a reliable corpus and successfully parse each user query to its correct entities. our hypothesis: with entity matching, overall precision can be significantly improved, while only slightly decreasing recall.
a framework for performance evaluation and functional verification in stochastic process algebras. despite its relatively short history, a wealth of formalisms exist for algebraic specification of stochastic systems. the goal of this paper is to give such formalisms a unifying framework for performance evaluation and functional verification. to this end, we propose an approach enabling a provably sound transformation from some existing stochastic process algebras, e.g., pepa and mtipp, to a generic form in the mcrl2 language. this way, we resolve the semantic differences among different stochastic process algebras themselves, on one hand, and between stochastic process algebras and classic ones, such as mcrl2, on the other hand. from the generic form, one can generate a state space and perform various functional and performance-related analyses, as we illustrate in this paper.
scenario oriented program slicing. slicing is an important decomposition technique for program understanding. however, traditional slicing methods tend to produce too large slices for human inspection as modern programs are often huge and static program analyses are hard to be precise enough. one possible solution to such problem could be combining other program decomposition techniques together with program slicing. with such inspiration, this paper proposes a scenario oriented program slicing method to slice programs under specified execution scenarios. the scenarios provide a clear and easy understanding functional decomposition for the system, while the new slicing method can help figure out how a computation is implemented in a given scenario by effectively reducing the amount of code that a user needs to inspect.
the impact of term selection in genre-aware focused crawling. the genre-aware approach to focused crawling aims at crawling pages related to specific topics that can be expressed in terms of both genre and content information. such an approach requires an expert to specify a set of terms that describe the genre and the content of the pages of interest. in this paper, we analyze the impact of term selection on this approach. thus, we have performed an experimental study in which we vary the number of genre and content terms used in focused crawling processes aimed at crawling pages related to syllabi (genre) of computer science courses (subject) and sale offers (genre) of computer equipments (subject). this experimental study showed that a small set of terms selected by an expert is usually enough to produce good results. in addition, we propose and experimentally evaluate a strategy for semi-automatic generation of terms to be used in such an approach. the results of these experiments showed that such a strategy is very effective and provides a means to assist an expert in the task of specifying the sets of required terms.
special track on programming languages: editorial message. the programming languages (pl) track provides researchers and practitioners with a forum to present their ideas and experience in designing new programming concepts and implementing programming languages. it includes the topics of compiling techniques, domain-specific languages, formal semantics and syntax, garbage collection, language design and implementation, languages for modeling, model-driven development and model transformation, new programming language ideas and concepts, new programming paradigms, practical experiences with programming languages, program analysis and verification, program generation and transformation, programming languages from all paradigms (agent-oriented, aspect-oriented, functional, logic, object-oriented, etc.), and visual programming languages.
dependence graphs for verifications of web service compositions with pews. pews is an interface description language for both individual and composed web services. we propose an approach for verifying pews compositions which exploits dependence graphs (equivalent to trace systems). the introduction of a synchronization based on dependence graphs allows more efficient algorithms for testing composition properties.
the qos-mo ontology for semantic qos modeling. this paper presents the qos-mo ontology. this ontology enables the specification of qos requirements for semantic web services and can easily be combined with owl-s in order to fully describe web services. the qos specifications created using the qos-mo ontology may be employed on the design and development of web services and on the publication and discovery of web services on the semantic web.
selecting beam directions in radiotherapy with an evolutionary algorithm. radiotherapy treatment planning aims at delivering high doses in the target volume while taking care to do not overdose other organs at risk. thus, it is an important issue to design a process for finding out ideal balances between those contradictory goals. in this paper a multi-objective programming model and a transgenetic algorithm are proposed for the 3d conformal radiotherapy treatment design. the algorithm is compared with a multi-objective genetic algorithm. results of a computational experiment are reported for four real cases.
supporting multimedia capture in mobile computing environments through a peer-to-peer platform. we present a p2p-based multimedia ubiquitous capture platform tailored to support co-located collaborative work.
compressing electrocardiogram signals using parameterized wavelets. a compression method, based on the choice of a wavelet that matches the electrocardiogram signal to be compressed, is proposed in this paper. the scaling filter that minimizes the distortion of the compressed signal are used to determine the wavelet. the scaling filter is used to generate the coefficients of projection of the ecg signal in the scaling and wavelet subspaces, and only the most significant coefficients are retained. coding methods are applied to the retained coefficients in order to improve the compression.
privacy-preserving link discovery. link discovery is a process of identifying association(s) among different entities included in a complex network structure. these association(s) may represent any interaction among entities, for example between people or even bank accounts. the need for link discovery arises in many applications including law enforcement, counter-terrorism, social network analysis, intrusion detection, and fraud detection. given the sensitive nature of information that can be revealed from link discovery, privacy is a major concern from the perspective of both individuals and organizations. for example in the context of financial fraud detection, linking transaction may reveal sensitive information about other individuals not involved in any fraud. in this paper, we propose an approach for link discovery in a privacy-preserving manner. we show how the problem can be reduced to finding the transitive closure of a graph. a secure split-matrix multiplication protocol based on secure scalar product computations is proposed to find the transitive closure. we analyze the performance and usability of the proposed approach.
a language-independent, open-vocabulary system based on hmms for recognition of ultra low resolution words. in this paper, we introduce and evaluate a system capable of recognizing ultra low resolution words extracted from images such as those frequently embedded on web pages. the design of the system has been driven by the following constraints. first, the system has to recognize small font sizes where antialiasing and resampling procedures have been applied. such procedures add noise on the patterns and complicate any a priori segmentation of the characters. second, the system has to be able to recognize any words in an open vocabulary setting, potentially mixing different languages. finally, the training procedure must be automatic, i.e. without requesting to extract, segment and label manually a large set of data. these constraints led us to an architecture based on ergodic hmms where states are associated to the characters. we also introduce several improvements of the performance increasing the order of the emission probability estimators and including minimum and maximum duration constraints on the character models. the proposed system is evaluated on different font sizes and families, showing good robustness for sizes down to 6 points.
st-guide: a framework for the implementation of automatic clinical guidelines. this paper presents st-guide, a state/transition approach to the representation of computer interpretable clinical guidelines for primary and secondary care. details of the representation language, which is based on finite state machines, and the execution model are presented. we claim that because it is geared towards primary care clinical guidelines, specially for chronic diseases, the representation language is simpler than general guideline representation languages that have been proposed in the literature. guidelines for tuberculosis, hepatitis c, hypertension, and the treatment of germ cell cancer in children were implemented in st-guide.
enterprise architecture governance: the need for a business-to-it approach. the importance of enterprise architecture is not only understood in corporate is/it departments. the numerous usage potentials for corporate planning as well as for compliance management, business continuity management, risk management etc. are successively discovered by the business side. in order to provide an aligned support instrument for is/it departments as well as business units and the corporate center, enterprise architecture management has to be anchored in is/it as well as in business. clear and effective governance is required to assure consistency and timeliness of enterprise architecture process outputs. based on a business-to-it approach to enterprise architecture, governance practices in industry are analyzed, and initial findings are consolidated which contribute to design requirements for effective enterprise architecture governance.
a pattern-driven security process for soa applications. soa enables the design of flexible and modular software applications that can be used in a crossorganization context. unfortunately, those qualities have a negative impact on the security of the software application. in this paper, we investigate the production of secure soa applications. in particular, we provide an approach to build secure soa applications that takes into account the new security issues introduced by the complexity of soa-based applications. we build upon two different approaches to secure soa applications: model-driven development and the use of security patterns.
an inference system for detecting firewall filtering rules anomalies. firewalls are crucial equipments for protecting private networks. however by only deploying firewalls, administrators are far from securing their enterprises networks. bad configurations may cause serious security breaches and network vulnerabilities. in particular, conflicting filtering rules lead to block legitimate traffic or to accept unwanted packets. we present in this paper a new classification method to detect overlaps between packet filters within one firewall. our method processes a set of filtering rules that have a variable number of fields. a field has a range of values, represented by an interval or a variable length bit string, that may intersect with the corresponding field ranges of other rules. in order to detect overlaps we organize the conditions of each filtering rule in such a way that we can quickly separate non overlapping rules. this strategy allows us to avoid considering the entire rule header in many cases.
replica identification using genetic programming. identifying and handling replicas are important to guarantee the quality of the information made available by modern data storage services. there has been a large investment from companies and governments in the development of effective methods for removing replicas from large databases. typically, this investment has produced significant results, since cleaned replica-free databases not only allow the retrieval of higher-quality information but also lead to a more concise data representation and to potential savings in computational time and resources to process and maintaining this data. in this paper, we propose a gp-based approach to automatic replica identification that combines evidence based on the data content in order to find a similarity function that is able to identify whether two entries in a repository are replicas or not. as shown by our experiments, our approach outperforms an svm-based method used as baseline by at least 6.5%. moreover, the suggested functions are computationally less demanding since they use fewer evidence. in addition, our approach is capable to automatically adapt to any given replica identification boundary.
brain registration and subtraction - improved localization for spect analysis (b.r.a.s.i.l.): a computer-aided diagnosis in epilepsy tool kit. surgery is an important option in the treatment of patients with medically intractable epilepsy. traditional techniques for the localization of the epileptogenic zone (ez), e.g. surface electroencephalography (eeg) and magnetic resonance (mr) imaging, allow accurate localization in a significant number of epileptic patients. besides, in many situations, the single photon emission computed tomography (spect) images have played a very important role in ez localization. however, the identification of the ez based on the visual interpretation side-by-side of the ictal and periictal images is in general a difficult task. to improve spect analysis, computational techniques have been developed focusing on the registration and fusion of ictal and periictal spect images. the combination of image registration and subtraction of spect images can improve the selective detection of brain regions with functional activation during epileptic seizures. the proposed methodology shown high sensitivity to detect hyperperfusion higher than 10%, in this article we apresents the techniques implemented, the methodology used to test and some initial results obtained with our own developed software b.r.a.s.i.l. ("brain registration and subtraction: improved localization for spect analysis").
checking the alignment of value-based business models and it functionality. business--it alignment is an ongoing activity of high importance for the success of a business. this is a hard task, especially in the context of value webs in which multiple businesses collaborate with each other to reach a common goal. value models, as the outcome of the value web exploration phase, represent solutions for business people, but not for software engineers. the latter ones have to come up with a blueprint for the implementation at application level. this can have two faces: either there are no systems at all and everything needs to be designed from scratch, or it is desired to use as many existing systems as possible. in the latter case, on which we focus in this paper, it must be checked which functionality existing systems should provide and whether they are usable for the given value web context. this affords several design activities, as well as checking consistency between different models. our approach can be viewed as an alignment checking method and also as a gap analysis, in case existing systems miss a given functionality.
integrating functional metrics, cocomo ii and earned value analysis for software projects using pmbok. nowadays, function point and use case point metrics have been largely adopted in the software industry to measure the size of the development work of the project. metrics should be used in conjunction with estimating techniques such as cocomo. there has been an increasing interest in monitoring and controlling project performance. earned value analysis present itself as an easy-to-understand technique that helps to monitor and control project's performance. this article presents a sequence of steps which allows the integration of software functional sizing metrics, cocomo ii and earned value analysis in the processes recommended by the pmbok for planning and controlling software development projects. the goal of such a sequence of steps is to help project managers to plan, monitor and control software development projects using the pmbok and software functional metrics. the two metrics were chosen as the basic units due to their large acceptance by industry. cocomo is a technique largely adopted in the software engineering area. a case study using an actual software project data was undertaken to evaluate our proposal. an add-in for microsoft project tool was developed to support that such a sequence of steps can be automated and integrated.