waashk/dblp huggingface dataset:
editorial message: special track on bioinformatics. advances in bioinformatics are providing the foundations for the convergence of agribusiness, healthcare, pharmaceuticals and computing into what promises to be the largest industry in the world, the life sciences industry. a large part of the information to support biology research is available on large number of heterogeneous databases in both structured and unstructured formats. the challenge is to obtain information and knowledge from these databases using innovative computational approaches to support and promote biomedical research. one example of such a computational challenge is in identifying biological pathways using data, information, and knowledge scattered over heterogeneous databases. computational tools using system-theoretic approaches are needed to model metabolic pathways, signal-transduction pathways, genetic regulatory circuits and biological systems modeling. by comparing the genomes and pathways of several species at a high level, we hope to understand how stable biological systems have evolved. over the last few years, microarray data have provided many insights into the transcriptome and into cellular function. these data are now increasingly complemented by mass spectrometry data of the proteome, whose analysis poses new computational challenges.
fite-trt: a high quality translation technique for oov words. we devised a novel statistical technique for the identification of the translation equivalents of source words obtained by transformation rule based translation (trt). the effectiveness of the devised fite (frequency-based identification of translation equivalents) technique was tested using biological and medical cross-lingual spelling variants and oov words in spanish-english and finnish-english trt. for spanish-english, translation recall was 89.2%-91.0% and for finnish-english 71.9%-72.9%. for both language pairs fite-trt achieved high translation precision, i.e., 97.0%-98.8%. the technique also reliably identified native source language words, i.e., source words that cannot be correctly translated by trt. dictionary-based clir augmented with fite-trt performed substantially better than dictionary-based clir where oov keys were kept intact.
support to the management of clinical activities in the context of protocol-based care. in this paper we describe the system smart (supporting medical activities in real-time). the goal of the system is real-time assistance to physicians who execute diagnostic or therapeutic protocols in a clinical context. smart is able to retrieve a protocol from its knowledge base and to monitor its execution step by step for a single patient. different protocols for different patients can be followed at the same time in a health care structure.the prototype realized supports the execution of protocols for evaluating surgical risks. it has been implemented according to the specifications given by the 4th surgical clinic of "policlinico umberto i" and reflects the activities actually performed in that hospital. however, the protocol model defined is general-purpose and we envisage an easy application to other contexts and therefore to the informatization of other protocols.
statistical properties of transactional databases. most of the complexity of common data mining tasks is due to the unknown amount of information contained in the data being mined. the more patterns and corelations are contained in such data, the more resources are needed to extract them. this is confirmed by the fact that in general there is not a single best algorithm for a given data mining task on any possible kind of input dataset. rather, in order to achieve good performances, strategies and optimizations have to be adopted according to the dataset specific characteristics. for example one typical distinction in transactional databases is between sparse and dense datasets. in this paper we consider frequent set counting as a case study for data mining algorithms. we propose a statistical analysis of the properties of transactional datasets that allows for a characterization of the dataset complexity. we show how such characterization can be used in many fields, from performance prediction to optimization.
file system framework for organizing sensor networks. we present a filesystem based framework to support common operations and applications in the sensor networks domain. the framework uses virtual filesystems to encapsulate resources at various levels of the sensor network hierarchy that are exported to clients who can then use common file operations to interact with the network. our approach is scalable, supports concurrent access of sensors and is compatible with lightweight sensor architectures. in this paper we introduce file representation of sensor networks, describe the general architecture used in implementing the framework and illustrate its use in supporting common sensor network operations.
a constraint logic programming approach to 3d structure determination of large protein complexes. the paper describes a novel framework, constructed using constraint logic programming and parallelism, to determine the association between parts of the primary sequence of a protein and &alpha;-helices extracted from 3-dimensional low-resolution descriptions of large protein complexes. the association is determined by extracting constraints from the 3d information, regarding length, relative position, and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. parallelism is employed to enhance performance on large proteins. the framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.
: flash crowds alleviation network. with the rapid spread of information and ubiquitous access of browsers, flash crowd, a sudden, unanticipated surge in the volume of request rates, has become the bane of many internet websites. this paper models and presents fcan, an adaptive cdn network that dynamically optimizes the system structure between peer-to-peer (p2p) and client-server(c/s) configurations to alleviate flash crowds effect. fcan constructs p2p overlay on cache proxy layer to distribute the flash traffic from origin web server. it uses policy-configured dns redirection to route the client requests in balance, and adopts strategy load detection to monitor and react the load changes. our preliminary simulation result shows that the system is overall well behaved, which validates the correctness of our basic design and points the way for the future research.
a hardware extension of the risc microprocessor for attribute grammar evaluation. conventional implementations of attribute grammar (ag) evaluators in embedded systems today, are solely of software nature. a compiler transforms the parser's specification along with the declarative attribute evaluation rules into a behaviorally equivalent procedural program to be executed on the microprocessor. this approach affects the final system's performance as well as the complexity of the final implementation. efforts in presenting hardware implementations of ag evaluators, although efficient enough in terms of performance, are usually fully implemented in hardware and as a consequence restricted to a single application. we exploit hw/sw codesign methods in the effort of presenting a hardware implementation of ag evaluators that is both reprogrammable and increases the desired system's performance. we achieve that by extending a conventional risc microprocessor by combining it with a programmable implementation of a hardware parser to propose a fully programmable ag evaluator that supports the execution of hybrid combinations of declarative-procedural code. the hardware parser increases design efficiency of tree derivations while the risc microprocessor handles the attribute evaluation computations. as a result, performance is increased while design flexibility required in embedded system applications is preserved.
optimizing syntax patterns for discovering protein-protein interactions. we propose a method for automated extraction of protein-protein interactions from scientific text. our system matches sentences against syntax patterns typically describing protein interactions. we define a set of 22 patterns, each a regular expression consisting of anchor positions and parameterizable constraints. this small set is then refined and optimized using a genetic algorithm on a training set. no heuristic definitions are necessary, and the final pattern set can be generated completely without manual curation. our method can be applied to any syntax pattern-based protein-protein interaction system and thus complements related work on building comprehensive sets of such patterns. the application of different fitness-functions during evolution provides an easy way to tune the system either toward precision, recall, or f-measure. we evaluate our system on two samples, one derived from the biocreative corpus, the other from references in the dip. the automatic refinement of patterns adds up to 16% to the precision, and 5% to the recall of our system. we additionally study the impact of a proper protein name recognition, which could improve precision by about 17% and recall by 12%.
a procedure to model the frequency response. modeling the frequency response of a component or system is a suitable approach in different engineering applications in order to analyze its behavior. sometimes it is also very interesting to model actual devices or systems in order to check their performance. in these cases, some measurements (either in the time or in the frequency domain) must be obtained from the devices or systems.a procedure of modeling the frequency response is presented in this paper. a modeling tool has been developed based on this procedure which could be adapted to different engineering applications. some experimental results have been obtained on checking the health of an electrical transformer working in the utility grid.
extended data dependency approach: a robust way of rebuilding database. attack on information systems through electronic media has become epidemic with the explosion of internet technologies and their applications. it is vital to start the assessment and recovery efforts immediately after an attack is detected. in this research, we consider dependency among data items to assess the damage. but the existing data dependency method is extremely limited. therefore, in this paper, we have provided the theory and concepts needed to make this approach more robust and general. these include: classifications of read and write operations, a new definition of transaction and a new representation of the scheduler. based on this developed theory, we have proposed an algorithm for damage assessment and recovery in a database that has suffered from information attack.
the meta-object facility typed. the object managment group's meta-object facility (mof) [9] is a semiformal approach to writing models and metamodels (models of models). the mof was developed to enable systematic model/metamodel interchange and integration. the approach is problematic, unless metamodels are correctly specified: an error in a metamodel specification will propagate throughout instantiating models and final model implementations. an important open question is how to develop provably correct metamodels. this paper outlines a solution to the question, in which the mof meta-modelling approach is formalized within constructive type theory.
svd-based collaborative filtering with privacy. collaborative filtering (cf) techniques are becoming increasingly popular with the evolution of the internet. such techniques recommend products to customers using similar users' preference data. the performance of cf systems degrades with increasing number of customers and products. to reduce the dimensionality of filtering databases and to improve the performance, singular value decomposition (svd) is applied for cf. although filtering systems are widely used by e-commerce sites, they fail to protect users' privacy. since many users might decide to give false information because of privacy concerns, collecting high quality data from customers is not an easy task. cf systems using these data might produce inaccurate recommendations. in this paper, we discuss svd-based cf with privacy. to protect users' privacy while still providing recommendations with decent accuracy, we propose a randomized perturbation-based scheme.
fitting standard software to non-standard organisations. this paper investigates the increasing trend within organisations and institutions of adopting pre-built, standardised management and administrative computer systems. the particular focus is on enterprise resource planning (erp) systems in the context of higher education, and the further development of university specific functionality - the 'campus management' (cm) module. we investigate this software as it adapted to the needs of a university in the uk (whom we are calling 'big_civic') and a potential global market. drawing on ideas from the sociology of science and technology we argue that in order to understand the 'dependability' and 'fit' (we tentatively conflate these two terms) of such systems we should attempt to study their 'biographies': this is the process of describing artefacts as they move around and are adapted and redefined according to the needs of each new place.
stochastic scheduling of active support vector learning algorithms. active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. in the past, simple active learning algorithms like random learning and query learning have been proposed for the design of support vector machine (svm) classifiers. in random learning, examples are chosen randomly, while in query learning examples closer to the current separating hyperplane are chosen at each learning step. however, it is observed that a better scheme would be to use random learning in the initial stages (more exploration) and query learning in the final stages (more exploitation) of learning. here we present two novel active sv learning algorithms which use adaptive mixtures of random and query learning. one of the proposed algorithms is inspired by online decision problems, and involves a hard choice among the pure strategies at each step. the other extends this to soft choices using a mixture of instances recommended by the individual pure strategies. both strategies handle the exploration-exploitation trade-off in an efficient manner. the efficacy of the algorithms is demonstrated by experiments on benchmark datasets.
geographical information recognition and visualization in texts written in various languages. in this paper, we describe a system that recognises place names in natural language text and produces geographic maps and animations showing the geographical coverage of texts about a certain subject as it changes over time. as the system is built to analyse texts in many different languages, it restricts the usage of linguistic analysis tools to the minimum. instead, it relies on a gazetteer containing place names in different languages and uses heuristics for disambiguation purposes.
dspxplore: design space exploration methodology for an embedded dsp core. high mask and production costs for the newest cmos silicon technologies increase the pressure to develop hardware platforms useable for different applications or variants of the same application. to provide flexibility for these platforms the need on software programmable embedded processors is increasing. to close the gap concerning consumed silicon area and power dissipation between optimized hardware implementations and software based solutions, it is necessary to adapt the subsystem of the embedded processor to application specific requirements. dspxplore can be used to explore the design space of risc based embedded core architectures. at an early stage of the project the main architectural requirements of the application code can be identified in order to meet the area and power dissipation requirements. during the development process dspxplore supports fine-tuning of the subsystem architecture (e.g. modifications of the binary coding of instructions). dspxplore is part of a development project for a configurable dsp core.
the intensity level reduction in radiation therapy. in this paper, we study an interesting intensity level reduction (ilr) problem, which is crucial for solving the "step-and-shoot" delivery planning problem in intensity-modulated radiation therapy (imrt). imrt aims to deliver a highly conformal radiation dose to a target tumor while sparing the surrounding normal tissues. effective intensity level reduction approaches significantly reduce the patient's exposure under the radiation and improve the treatment efficiency. we propose a new intensity level reduction method for step-and-shoot delivery planning, and further model the intensity level reduction problem as computing a set of shortest monotone paths (smps) in certain specific geometric graphs, called multi-column graphs, of pseudo-polynomial sizes. based on a judicious characterization of the intrinsic geometric structures of the graphs, we develop a novel graph pruning scheme and compute the smps without explicitly constructing the graphs, yielding an efficient o(mn logn) time algorithm for solving the intensity level reduction problem on an intensity map (specifying a radiation dose prescription) of size m x n.
domotic house gateway. this paper presents a domotic house gateway capable of seamlessly interacting with different devices from heterogeneous domotic systems and appliances. such a gateway also provides the possibility to automate device cooperation through an embedded rule-based engine, which can be dynamically and automatically updated to accommodate necessities and anticipate users' actions. some practical applications will show the effectiveness of the system.
aspect oriented programming for a component-based real life application: a case study. aspect oriented programming, a relatively new programming paradigm, earned the scientific community's attention. the paradigm is already evaluated for traditional oop and component-based software development with remarkable results. however, most of the published work, while of excellent quality, is mostly theoretical or involves evaluation of aop for research oriented and experimental software. unlike the previous work, this study considers the aop paradigm for solving real-life problems, which can be faced in any commercial software. we evaluate aop in the development of a high-performance component-based web-crawling system, and compare the process with the development of the same system without aop. the results of the case study mostly favor the aspect oriented paradigm.
a relational approach to the capture of dicom files for grid-enabled medical imaging databases. the standard for digital imaging and communications in medicine (dicom) specifies a non-proprietary digital imaging format, file structure and data interchange protocols for the transfer of biomedical images and non-image data related to such images--it is a specification of the components that are required in order to achieve inter-operability between biomedical imaging computer systems. in this paper we describe how a grid-enabled medical imaging database---ediamond--employs an object-relational approach to the storage of dicom files. although the work described has been carried out within the context of a particular mammography related project, the underlying principles are applicable to other medical imaging systems dealing either with other modalities or with other diseases.
automatically discovering design patterns and assessing concern separations for applications. in this paper we present a tool that assists in the automated analysis of a java application, aimed at two purposes: (i) identifying class structure and, within this, micro-architectures that conform to known design patterns; (ii) providing visual representations of classes, concerns and their relationships. this affords a more abstract view of the analysed application, letting its structure emerge more clearly and its components be separately understood. as a result, it becomes easier for developers to assess whether well-known desirable characteristics, notably those favouring modularity and concern separation, or rather bad design choices, have been incorporated into the application.the proposed approach can be helpful both within the undertaking of a new development effort, and reverse engineering of an existing application in view of its evolution.
protecting sensitive patient data via query modification. it is well understood that a conflict between functionality and confidentiality exists within the context of medical research databases: while patients' rights must be preserved, restricting access to data can reduce the value of the data that is available to the researcher. as such, limiting access so that confidentiality is preserved without reducing functionality more than is necessary should be a key aim of every designer of medical research databases. in this paper we investigate the application of query modification for the protection of sensitive patient data with a view to preserving functionality as much as possible. the work has been conducted within the context of the e-diamond research project.
distributed query adaptation and its trade-offs. adaptive query processing in large distributed systems has seen increasing importance due to the rising environmental fluctuations in a growing internet. we describe ginga, an adaptive query processing engine that combines proactive (compile-time) alternative query plan generation with reactive (run-time) monitoring of network delays. the core of ginga approach is the notion of adaptation space and mechanisms for coordinating and integrating different kinds of query adaptation. an adaptation space consists of a set of adaptation triggers and a set of adaptation cases associated with the triggers. each adaptation case describes a specific adaptation opportunity of the query execution when changes to the runtime environment are detected. our experimental results show that ginga query adaptation can achieve significant performance improvements (up to 40% of response time gain) for processing distributed queries over the internet.
towards model-based generation of self-priming and self-checking conformance tests for interactive systems. this paper describes a model-based approach to generate conformance tests for interactive applications. our method builds on existing work to address generation of: (1) small yet effective set of test frames for testing individual operations, (2) a set up sequence that brings the system under test in an appropriate state for a test frame (self-priming), (3) a verification sequence for expected output and state changes (self-checking), and, (4) negative test cases in the presence of exceptions. our method exploits a novel mutation scheme applied to operations specified as pre-, and postconditions on parameters and state variables; a set of novel abstraction techniques which result in a compact finite state automaton; and search techniques to automatically generate the set up and verification sequences. we illustrate our method with a simple atm application.