ppxscal/embedding_network huggingface dataset:
Trends in metadata practices: a longitudinal study of collection federation
Authors: Carole L. Palmer, Oksana L. Zavalina, Megan Mustafoff
Venue: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries (2007)

With the increasing focus on interoperability for distributed digital content, resource developers need to take into consideration how they will contribute to large federated collections, potentially at the national and international level. At the same time, their primary objectives are usually to meet the needs of their own institutions and user communities. This tension between local practices and needs and the more global potential of digital collections has been an object of study for the IMLS Digital Collections and Content (IMLS DCC) project. Our practical aim has been to provide integrated access to over 160 IMLS-funded digital collections through a centralized collection registry and metadata repository. During the course of development, the research team has investigated how collections and items can best be represented to meet the needs of local resource developers and aggregators of distributed content, as well as the diverse user communities they may serve. This paper presents results from a longitudinal analysis of IMLS DCC development trends between 2003 and 2006. Changes in metadata applications have not been pronounced. However, multi-scheme use has become less common, and use of Dublin Core remains high, even as recognition of its limitations grows. Locally developed schemes are used as much as MARC, and may be on the increase as new collections are incorporating less traditional library and museum materials, and more interactive and multimedia content. Based on our empirical understanding of metadata use in practice, patterns in new content development, and user community indicators, our research has turned toward identifying metadata relationships between items and collections to preserve context and enhance functionality and usefulness for scholarly user communities.
Sound and precise analysis of web applications for injection vulnerabilities
Authors: Gary Wassermann, Zhendong Su
Venue: Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation (2007)

Web applications are popular targets of security attacks. One common type of such attacks is SQL injection, where an attacker exploits faulty application code to execute maliciously crafted database queries. Bothstatic and dynamic approaches have been proposed to detect or prevent SQL injections; while dynamic approaches provide protection for deployed software, static approaches can detect potential vulnerabilities before software deployment. Previous static approaches are mostly based on tainted information flow tracking and have at least some of the following limitations: (1) they do not model the precise semantics of input sanitization routines; (2) they require manually written specifications, either for each query or for bug patterns; or (3) they are not fully automated and may require user intervention at various points in the analysis. In this paper, we address these limitations by proposing a precise, sound, and fully automated analysis technique for SQL injection. Our technique avoids the need for specifications by consideringas attacks those queries for which user input changes the intended syntactic structure of the generated query. It checks conformance to this policy byconservatively characterizing the values a string variable may assume with a context free grammar, tracking the nonterminals that represent user-modifiable data, and modeling string operations precisely as language transducers. We have implemented the proposed technique for PHP, the most widely-used web scripting language. Our tool successfully discovered previously unknown and sometimes subtle vulnerabilities in real-world programs, has a low false positive rate, and scales to large programs (with approx. 100K loc).
A Modular Architecture for Context Sensing
Authors: Julian Grigera, Andres Fortier, Gustavo Rossi, Silvia Gordillo
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

Due to the technological evolution, context-aware computing is slowly moving from dream to reality. These applications heavily rely in sensing the user's environment and abstracting this information to perform high-level adaptation. While technological issues have been mostly addressed, sensing software is usually built in a handcrafted way, which turns into building ad-hoc solutions for every new application. To solve this problem, we consider that context sensing should be regarded as a software engineering problem and not a simple implementation issue. In this paper we present a software architecture for dealing with context-sensing aspects in a high-level modular way. We show that by using this approach, evolution issues typical of mobile wireless software can be managed easily by replacing or composing software modules without compromising performance.
Method of optimal directions for frame design
Authors: K. Engan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

A frame design technique for use with vector selection algorithms, for example matching pursuits (MP), is presented. The design algorithm is iterative and requires a training set of signal vectors. The algorithm, called method of optimal directions (MOD), is an improvement of the algorithm presented by Engan, Aase and Husoy see (Proc. ICASSP '98, Seattle, USA, p.1817-20, 1998). The MOD is applied to speech and electrocardiogram (ECG) signals, and the designed frames are tested on signals outside the training sets. Experiments demonstrate that the approximation capabilities, in terms of mean squared error (MSE), of the optimized frames are significantly better than those obtained using frames designed by the algorithm of Engan et. al. Experiments show typical reduction in MSE by 20-50%.
Current Status and Future Trends of Nanoscale Technology and Its Impact on Modern Computing, Biology, Medicine and Agricultural Biotechnology
Authors: D. Dutta Majumder, Christian Ulrichs, Debosmita Majumder, Inga Mewis, Ashoke Ranjan Thakur, R. L. Brahmachary, Rajat Banerjee, Ayesha Rahman, Nitai Debnath, Dipankar Seth, Sumistha Das, Indrani Roy, Amrita Ghosh, Prity Sagar, Carsten Schulz, Nguyen Quang Linh, Arunava Goswami
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

Nanoscale technologies have gone from being just an ambitious concept to being a rapidly advancing area of interdisciplinary science with immense practical importance. Feynman's vision on nanoscience provided great impetus to the development of nanophysics, nanochemistry, nanoelectronics and nanotechnology in general [1]. High resolution microscopic devices such as scanning tunneling microscope, transmission electron microscope and atomic force microscope etc. in mid- 1980s allowed researchers to see individual atoms on surfaces and arrange them at will [2, 3]. The authors (nanobiologists, computer scientists, biotechnologists and material scientists) will attempt to provide a review of the state of the art in the field of nanoscale technologies and its impact on various fields of research like computation, basic biology, medicine and agricultural biotechnology. Imprints of memory mechanisms [3] in living systems operating at different levels (e.g. biochemical, immunological and neuronal) has provided inputs to design and fabricate `bioinspired' nanoelectronic devices suitable for various applications. Several examples of such nanoscale technology based frameworks and devices will be presented in the scenario of their potential role in the development of future nanoscale technologies. Nanoscale technologies might finally revolutionize computational intelligence and thinking. The power and limits of computing processes govern the intelligence, knowledge acquisition and thinking process of human and machine. Present computational methods and models provide us courage to study the problem, but these tools are not yet sufficient to answer the following riddles of machine intelligence- What can computers do better than humans? What can humans do better than computers? And the most important one- what is computable? The authors will try to present evidences that will show bio-inspired nanoscale technologies might gain the power in helping us to go deeper into these challenges of research in future.
A toolkit approach to partially connected operation
Authors: Dan Duchamp
Venue: Proceedings of the annual conference on USENIX Annual Technical Conference (1997)

Partially connected operation is the circumstance in which the communication link between two computers is intermittent, either by choice or because of failure. This paper describes the design and performance of a user level toolkit that is suited to accessing the home directory of a partially connected user in a bandwidth-efficient manner. Compared to custom file systems for partially connected operation, the toolkit is easier to deploy and provides extra degrees of flexibility because it runs at user level and uses the local file system for its cache. The toolkit makes it possible for unaltered clients to access NFS file systems exported by unaltered servers. The maintenance of consistency between client and server is automatic provided that certain assumptions are upheld, the primary one being that sharing is limited in such a way that there is a "single locus of update." That is, for extended periods, updates are applied either to the client's cache or directly to the server, but not to both simultaneously. This pattern of use is typical of a user's home directory. Performance is the disadvantage of user level operation. The client's cache is managed by a "caching tool" that services every file system operation and this redirection increases latency substantially.
Speaker and gender normalization for continuous-density hidden Markov models
Authors: A. Acero, Xuedong Huang
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

We describe a speaker-cluster normalization algorithm that we applied to both gender-normalization and speaker-normalization. To achieve parameter sharing the acoustic space is partitioned into classes. A maximum likelihood approach has been proposed under which the data between the distribution mean and its corresponding acoustic class is mostly speaker-independent, whereas the means of the acoustic classes are mostly speaker-dependent. When applied to gender-normalization the error rate reduction approaches that of a gender-dependent system but with half the number of parameters. For a speaker-normalized system, a 30% decrease in error rate was obtained in a batch recognition experiment in a context-dependent continuous-density HMM system.
Worst-case design and margin for embedded SRAM
Authors: Robert Aitken, Sachin Idgunji
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

An important aspect of Design for Yield for embedded SRAM is identifying the expected worst case behavior in order to guarantee that sufficient design margin is present. Previously, this has involved multiple simulation corners and extreme test conditions. It is shown that statistical concerns and device variability now require a different approach, based on work in Extreme Value Theory. This method is used to develop a lower-bound for variability-related yield in memories.
Finding interesting summaries in genspace graphs
Authors: Liqiang Geng
Venue:  (2005)

Online analytical processing (OLAP) and data mining are two important data analysis methods. To improve the functionality of OLAP systems, summary mining aims to find interesting summaries for a data set. In this thesis, we introduce a summary mining architecture, called GenSpace summary mining (GSSM), based on belief revision. Under this framework, a user's beliefs are represented by the user's estimated probability distribution (or estimates) for records in summaries. The summaries are organized in a graphical structure called a GenSpace graph. The GenSpace graph contains information about the conceptual levels of the summaries, the observed probability distributions of records in the summaries, and the user's estimates. The interestingness of the summaries is defined as the distance between the user's estimates and the observed probability distributions. During the mining process, the user specifies his/her estimates at a certain conceptual level in a GenSpace, and the system propagates them to other conceptual levels. The interesting summaries, i.e., the summaries far from the user's estimates, are then selected for presentation to the user. With the interesting summaries as new evidence, the user can revise his/her estimates and input them into the system to start the next round of the mining process. The GSSM process is iterative and it can be interactive. GenSpace summary mining consists of two parts, GenSpace estimate propagation (GSEP) and GenSpace summary selection (GSSS). The GSEP process is a probability based belief revision process. We argue that GSEP should preserve the consistency of the estimates in the GenSpace graph, be efficient, and guarantee the minimum change to the old estimates. Based on these principles, we formalize the GSEP problem as an optimization problem and propose a linear GSEP method as a heuristic approach to solving this problem. We then propose two pruning and path selection strategies to improve the propagation efficiency in GenSpace subgraphs. We also introduce virtual bottom nodes to further reduce the propagation and storage costs during the GSEP process. The experiments indicate that these techniques can greatly improve propagation efficiency. For the GSSS process, we study nine interestingness measures for summaries and their properties. These properties can be used as pruning strategies during the summary selection process to improve system efficiency. We demonstrate the effectiveness of the GSSM method on three real data sets, the Saskatchewan weather data set, the University of Regina student data set, and a customer data set. Experiments in all three data sets show that when the user accepts the distribution of the most interesting summary, its closely related summaries become less interesting in the following mining round and the user's estimates of all summaries approach the observed distributions.
Signal modeling with dynamic fuzzy sets
Authors: B. R. Kosanovic
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

Signals originating from a class of time-varying systems are modeled as dynamic fuzzy sets, i.e. fuzzy sets with membership functions that change in time. A signal trajectory in feature space is mapped into a dynamic fuzzy set which quantifies and characterizes the most significant aspects of the system's dynamics. A dynamic fuzzy set is visualized as a trajectory within a corresponding fuzzy information space. An example involving modeling of electroencephalographic signals during sleep is presented to illustrate the applicability of the method.
Synchrony vs Asynchrony in Communication Primitives
Authors: Daniele Gorla
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

We study, from the expressiveness point of view, the impact of synchrony in the communication primitives that arise when combining together some common and useful programming features like arity of data, communication medium and possibility of pattern matching. For some primitives, we show how their synchronous version can be encoded in their asynchronous counterpart via a fully abstract encoding, thus proving that the two versions have the same expressive power. For the remaining primitives, we prove that no 'reasonable' encoding can exist, thus proving that synchrony adds expressiveness to the language.
A direct method to computational acoustics
Authors: R. Rabenstein
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

The exact knowledge of the sound field within an enclosure is essential for a number of applications in electro-acoustics. Conventional methods for the assessment of room acoustics model the sound propagation in analogy to the propagation of light. More advanced computational methods rely on the numerical solution of the wave equation. A recently presented method is based on multidimensional wave digital principles. It allows a physically exact numerical modelling of the relevant acoustical effects and yields robust algorithms. This contribution presents a new foundation of the multidimensional wave digital principle as applied to room acoustics. It starts from the first principles of physics. From there, the derivation of the algorithm only involves basic knowledge of numerical mathematics, linear algebra, and multidimensional system theory. An example for the simulation of dynamic three-dimensional sound propagation demonstrates the capability of the method.
Architecting Fault Tolerant Systems
Authors: H. Muccini, P. Pelliccione, A. Romanovsky
Venue: Proceedings of the Sixth Working IEEE/IFIP Conference on Software Architecture (2007)

Fault tolerance, being one of the four means for guaranteeing dependability, is intended to ensure the delivery of the correct services in the presence of active faults. It is implemented by error detection and subsequent system recovery. Error detection finds an erroneous system state. Following system recovery transforms the system state that contains one or more errors and (possibly) faults into a state without detected errors and faults (fault handling). Exceptions and exception handling provide a general framework for structuring the fault tolerance activities in a system, by focusing on the concept of exceptional/abnormal behaviour (as opposed to normal behaviour), exception handling enables specifying actions to be undertaken in the presence of abnormal events.
Proceedings of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches
Venue: High Performance Distributed Computing (2007)

It is our great pleasure to welcome you to the Workshop on Service-Oriented Computing Performance: Aspects, Issues, and Approaches -- SOCP'07. The mission of the workshop is to share innovative approaches and ideas to addressing issues in the performance of service-oriented computing. We had 18 submissions from all over the world, including Europe and Asia. From this, we accepted 10 papers covering a variety of topics, including alternate serialization formats, Bayesian approaches to modeling, and multicore approache.
Linearly independent split systems
Authors: David Bryant, Andreas Dress
Venue: European Journal of Combinatorics (2007)

An important procedure in the mathematics of phylogenetic analysis is to associate, to any collection of weighted splits, the metric given by the corresponding linear combination of split metrics. In this note, we study necessary and sufficient conditions for a collection of splits of a given finite set X to give rise to a linearly independent collection of split metrics. In addition, we study collections of splits called affine split systems induced by a configurations of lines and points in the plane. These systems not only satisfy the linear-independence condition, but also provide a Z-basis of the Z-lattice D"e"v"e"n(X|Z) consisting of all integer-valued symmetric maps D:XxX->Z defined on X that vanish on the diagonal and for which, in addition, D(x,y)+D(y,z)+D(z,x)=0mod2 holds for all x,y,z@?X. This Z-lattice is generated by all split metrics considered as vectors in the real vectorspace D(X|R) consisting of all real-valued symmetric maps defined on X that vanish on the diagonal - and, hence, is also an R-basis of that vectorspace.
Real-time rewriting semantics of orc
Authors: Musab AlTurki, José Meseguer
Venue: Proceedings of the 9th ACM SIGPLAN international conference on Principles and practice of declarative programming (2007)

Orc is a language proposed by Jayadev Misra [19] for orchestration of distributed services. Orc is very simple and elegant, based on a few basic constructs, and allows succinct and understandable programming of sophisticated applications. However, because of its real-time nature and the different priorities given to internal and external events in an Orc program, giving a formal operational semantics that captures the real-time behavior of Orc programs is nontrivial and poses some interesting challenges. In this paper we propose such a real-time operational Orc semantics, that captures the informal operational semantics given in [19]. This operational semantics is given as a rewrite theory in which the elapse of time is explicitly modeled. The priorities between internal and external events are also modeled in two alternative ways: (i) by a rewrite strategy; and (ii) by adding extra conditions to the semantic rules. Since rewriting logic has efficient implementations such as Maude, we also get, directly out of the semantic definitions, both an Orc interpreter and an LTL model checker for Orc programs.
TSM. Topic Selection Method of Web Documents
Authors: Myunggwon Huang, Hyunjang Kong, Sunkyoung Baek, Pankoo Kim
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

In this paper, we propose a topic selection method about web documents. The idea of our approach is to utilize an ontology structure and TF (Term Frequency) values of each term. For improving the performance of documents clustering, our research is strongly demanded. We process web documents for keywords acquisition using TF values and relevancy values between terms using relations defined in WordNet. And then, we proposed the topic selection formula as we consider three kinds of cases during the topic selection. In conclusion, we demonstrate that our approach is very useful for the topic selection of documents.
A Service Architecture for Countering Distributed Denial of Service Attacks
Authors: Fareed Zaffar, Gershon Kedem
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 01 (2007)

We present AMP, a novel service architecture for countering distributed denial of service (dDos) attacks. AMP uses dynamically configured network components to perform traffic monitoring, filtering and detection of commonly known attacks. It does not require universal deployment and is complementary to other schemes for countering dDoS attacks, however with the use of collaborative policing techniques, the performance of the scheme can be improved greatly. In addition, it is economically viable, it can be offered as a service to the customers by service providers. We give a detailed design of our system which we implemented on our simulation test-bed. Performance evaluation of our system shows that using our scheme we were able to recover 83% of throughput lost during an attack.