ppxscal/embedding_network huggingface dataset:
Characterizing Example Embedding as a software activity
Authors: Ohad Barzilay, Orit Hazzan, Amiram Yehudai
Venue: Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation (2009)

We use an empirical qualitative software engineering research to characterize Example Embedding (EE) as a software activity - a collection of fine grained techniques which together assemble an abstract key notion in software development. This perspective lays the foundations for building an activity catalogue, forming new software practices, affecting the development process and motivating the development of new software tools.
An Information Theoretic Perspective of the Sparse Coding
Authors: Hideitsu Hino, Noboru Murata
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

The sparse coding method is formulated as an information theoretic optimization problem. The rate distortion theory leads to an objective functional which can be interpreted as an information theoretic formulation of the sparse coding. Viewing as an entropy minimization problem, the rate distortion theory and consequently the sparse coding are extended to discriminative variants. As a concrete example of this information theoretic sparse coding, a discriminative non-linear sparse coding algorithm with neural networks is proposed. Experimental results of gender classification by face images show that the discriminative sparse coding is more robust to noise, compared to the conventional method which directly uses images as inputs to a linear support vector machine.
Pareto-efficient and goal-driven power control in wireless networks: a game-theoretic approach with a novel pricing scheme
Authors: Mehdi Rasti, Ahmad R. Sharafat, Babak Seyfe
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

A Pareto-efficient, goal-driven, and distributed power control scheme for wireless networks is presented. We use a non-cooperative game-theoretic approach to propose a novel pricing scheme that is linearly proportional to the signal-to-interference ratio (SIR) and analytically show that with a proper choice of prices (proportionality constants), the outcome of the noncooperative power control game is a unique and Pareto-efficient Nash equilibrium (NE). This can be utilized for constrained-power control to satisfy specific goals (such as fairness, aggregate throughput optimization, or trading off between these two goals). For each one of the above goals, the dynamic price for each user is also analytically obtained. In a centralized (base station) price setting, users should inform the base station of their path gains and their maximum transmit-powers. In a distributed price setting, for each goal, an algorithm for users to update their transmit-powers is also presented that converges to a unique fixed-point in which the corresponding goal is satisfied. Simulation results confirm our analytical developments.
Knowledge Acquisition for Generative Model Construction
Authors: Wojciech Skarka
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Generative Model of a product constructed in CAD system integrates knowledge which is necessary for designing process and product modeling. Such a model in CAD system environment can be treated as KBE application. There is a lack of methodological guidelines for creation of such models, including the whole process of creation from data collection and acquisition to modeling in CAD environment. The paper presents briefly methodology of creation of such a system. The solution for the process of knowledge acquisition for this model has been suggested, including the aspects of the very product, designing process and the usage of a given CAD tool.
Hierarchical Design Rewriting with Maude
Authors: Roberto Bruni, Alberto Lluch Lafuente, Ugo Montanari
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Architectural Design Rewriting (ADR) is a rule-based approach for the design of dynamic software architectures. The key features that make ADR a suitable and expressive framework are the algebraic presentation and the use of conditional rewrite rules. These features enable, e.g. hierarchical (top-down, bottom-up or composition-based) design and inductively-defined reconfigurations. The contribution of this paper is twofold: we define Hierarchical Design Rewriting (HDR) and present our prototypical tool support. HDR is a flavour of ADR that exploits the concept of hierarchical graph to deal with system specifications combining both symbolic and interpreted parts. Our prototypical implementation is based on Maude and its presentation serves several purposes. First, we show that HDR is not only a well-founded formal approach but also a tool-supported framework for the design and analysis of software architectures. Second, our illustration tailored to a particular algebra of designs and a particular scenario traces a general methodology for the reuse and exploitation of ADR concepts in other scenarios.
Code decompression unit design for VLIW embedded processors
Authors: Yuan Xie, Wayne Wolf, Hafts Lekatsas
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

Code size "bloating" in embedded very long instruction word (VLIW) processors is a major concern for embedded systems since memory is one of the most restricted resources. In this paper, we describe a code compression algorithm based on arithmetic coding, discuss how to design decompression architecture, and illustrate the tradeoffs between compression ratio and decompression overhead, by using different probability models. Experimental results for a VLIW embedded processor TMS320C6x show that compression ratios between 67% and 80% can be achieved, depending on the probability models used. A precache decompression unit design is implemented in TSMC 0.25µm and a test chip is fabricated.
An upgraded Petri net model of systolic architecture for solving differential equations based on Taylor's method
Authors: Perica Strbac, Milan Tuba, Dana Simian
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

This paper presents an UPN (Upgraded Petri Net) model of a systolic array for solving of differential equations using Taylor's method. The iterative sequence of modelling - simulation - analysis of the model is shown. By evaluating results of the simulation relevant characteristics of the systolic array are observed: synchronism, regularity, time locality and pipeline. Two UPN models are developed. The first one refers to the high level systolic array modeling. This model shows processing elements that calculate or pass their input to the output. Thus, the next processing element use results of the previous one. The second model is more detailed and refers to single processing element. This model is capable to generate solution of differential equation through UPN execution based on Taylor's method. This execution is based on parralel firing of a group of transitions. The suitability of UPN for modelling of the systems at different levels of abstraction is examined and established. Original software for modelling and simulations of Upgraded Petri Nets, PeM (Petri Net Manager), is developed and used for all models described in this paper.
Restoration of clouded pixels in multispectral remotely sensed imagery with cokriging
Authors: Chuanrong Zhang, Weidong Li, David J. Travis
Venue: International Journal of Remote Sensing (2009)

The presence of clouds and their shadows in remotely sensed images limits their potential uses for extracting information. The commonly used methods for replacing clouded pixels by land cover reflection estimates usually yield poor results if the images being combined exhibit radical differences in target radiance due, for example, to large date separation and high temporal variability. This study focuses on introducing geostatistical techniques for interpolating the DN values of clouded pixels in multispectral remotely sensed images using traditional ordinary cokriging and standardized ordinary cokriging. Two case studies were conducted in this study. The first case study shows that the methods work well for the small clouds in a heterogeneous landscape even when the images being combined show high temporal variability. Although the basic spatial structure in large size clouds can be captured, image interpolation-related artefacts such as smoothing effects are visually apparent in a heterogeneous landscape. The second case study indicates that the cokriging methods work better in homogenous regions such as the dominantly agricultural areas in United States Midwest. Various statistics including both global statistics and local statistics are employed to confirm the reliability of the methods.
Enhanced bioinformatics data modeling concepts and their use in querying and integration
Authors: Ramez Elmasri
Venue:  (2008)

In bioinformatics research, scientists usually face the problems of modeling complex data types and integrating diverse resources. Traditional data models such as EER lack the expressing power to capture many characteristics that are common in bioinformatics data. We first propose extensions to the ER model that allow accurate representation of many of these characteristics. We then utilize these concepts in an integrative system to provide an easy-to-use interface for biologists to construct queries. Our research utilizes the enhanced conceptual modeling concepts to create a prototype mediator for querying multiple data sources. The various relationships between different biological entities are all semantically represented as domain ontologies stored in the mediator for experts to analyze and correlate the integrated query results. The following research has been conducted: (1) We first propose new EER schema notation to represent the common occurring biological concepts: the ordering properties of the DNA sequences, the 3D structure of proteins and the functional processes of metabolic pathways. (2) Then, we utilize these new relationships in the development of the mediated domain ontology, which helps the interface design and query processor implementation of our mediator system. Our mediated schema features are based on a hybrid of taxonomy ontologies (core concepts and external classification/annotation concepts) for interpretation of raw data sets (protein and gene sequences) in the context of molecular interactions, biochemical pathways and biological processes. We adopt the RDF data model to implement the mediation data. Our mediator mainly takes a browsing-based approach to integrate different data sources. Extra data can be dynamically retrieved through the web service. By browsing the ontology tree in the query interface, users can select concepts of interest and associated attributes to formulate queries based on their domain knowledge. The query result is a set of various database entry accessions with associated attribute values. Users can click each link of the accessions to see the detailed reports, or cross-compare attributes of these data instances. Query usability and performance experiments are tested for real data sets from UniProt [30], ENZYME [8], CATH [23], and GO [29].
EAFoC: enterprise architecture framework based on commonality
Authors: Jin-Woo Kim, Ju-Hum Kwon, Young-Gab Kim, Chee-Yang Song, Hyun-Seok Kim, Doo-Kwon Baik
Venue: Journal of Computer Science and Technology (2006)

The recent rapid development in information systems (ISs) has resulted in a critical need for integration and interoperability between heterogeneous ISs in various domains, using specific commonalities. However, stovepipe systems have been caused due to inconsistencies in planning IS architecture among stakeholders. So far, there has been no research on an enterprise architecture framework (EAF) that can satisfy with the coefficient factors of system architecture (SA) and enterprise architecture (EA). This paper proposes a new EAF that can resolve the problems inherent in existing legacy EAFs and their features. EAFoC (Enterprise Architecture Framework based on Commonality) is based on commonality that can be satisfied as the coefficient factors in both SA and EA within a common information technology (IT) domain. Thus, it should be possible to integrate an established heterogeneous framework for each stakeholder's view. Consequently, the most important contribution of this paper is to establish the appropriate EAFoC for the development of consistent IS architecture, smooth communication among stakeholders, systematic integration management of diversified and complicated new IT technologies, interoperability among heterogeneous ISs, and reusability based on commonality with other platforms.
On some open problems in monotonic and conservative learning
Authors: Sanjay Jain
Venue: Information Processing Letters (2009)

In this paper we solve some open problems in monotonic and conservative learning.
Combination of CFD and DOE to analyse solid particle erosion in elbows
Authors: Patrick Frawley, Julie Corish, Andy Niven, Marco Geron
Venue: International Journal of Computational Fluid Dynamics (2009)

Solid particle erosion is a major concern in the engineering industry, particularly where transport of slurry flow is involved. Such flow regimes are characteristic of those in alumina refinement plants. The entrainment of particulate matter, for example sand, in the Bayer liquor can cause severe erosion in pipe fittings, especially in those which redirect the flow. The considerable costs involved in the maintenance and replacement of these eroded components led to an interest in research into erosion prediction by numerical methods at Rusal Aughinish alumina refinery, Limerick, Ireland, and the University of Limerick. The first stage of this study focused on the use of computational fluid dynamics (CFD) to simulate solid particle erosion in elbows. Subsequently an analysis of the factors that affect erosion of elbows was performed using design of experiments (DOE) techniques. Combining CFD with DOE harnesses the computational power of CFD in the most efficient manner for prediction of elbow erosion. An analysis of the factors that affect the erosion of elbows was undertaken with the intention of producing an erosion prediction model.
Large-scale collaborative prediction using a nonparametric random effects model
Authors: Kai Yu, John Lafferty, Shenghuo Zhu, Yihong Gong
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

A nonparametric model is introduced that allows multiple related regression tasks to take inputs from a common data space. Traditional transfer learning models can be inappropriate if the dependence among the outputs cannot be fully resolved by known input-specific and task-specific predictors. The proposed model treats such output responses as conditionally independent, given known predictors and appropriate unobserved random effects. The model is nonparametric in the sense that the dimensionality of random effects is not specified a priori but is instead determined from data. An approach to estimating the model is presented uses an EM algorithm that is efficient on a very large scale collaborative prediction problem. The obtained prediction accuracy is competitive with state-of-the-art results.
Studies on gesture expressivity for a virtual agent
Authors: Catherine Pelachaud
Venue: Speech Communication (2009)

Our aim is to create an affective embodied conversational agent (ECA); that is an ECA able to display communicative and emotional signals. Nonverbal communication is done through certain facial expressions, gesture shapes, gaze direction, etc. But it can also carry a qualitative aspect through behavior expressivity: how a facial expression, a gesture is executed. In this paper we describe some of the work we have conducted on behavior expressivity, more particularly on gesture expressivity. We have developed a model of behavior expressivity using a set of six parameters that act as modulation of behavior animation. Expressivity may act at different levels of the behavior: on a particular phase of the behavior, on the whole behavior and on a sequence of behaviors. When applied at these different levels, expressivity may convey different functions.
Preface: Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (II)
Authors: Yingxu Wang, Du Zhang, Shusaku Tsumoto
Venue: Fundamenta Informaticae (2009)

Cognitive Informatics is a cutting-edge and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, computing, software engineering, AI, cybernetics, cognitive science, neuropsychology, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences. This editorial introduces the emerging field of cognitive informatics and its applications in cognitive computing, abstract intelligence, computational mathematics, and computational intelligence. The themes and structure of this special issue on cognitive informatics are described, and then, focuses of the selected papers in Part II of this special issue are highlighted.
Strongest postcondition of unstructured programs
Authors: Radu Grigore, Julien Charles, Fintan Fairmichael, Joseph Kiniry
Venue: Proceedings of the 11th International Workshop on Formal Techniques for Java-like Programs (2009)

To avoid exponential explosion, program verifiers turn the program into a passive form before generating verification conditions. A little known fact is that the passive form makes it easy to use a strongest postcondition calculus to derive the verification condition. In the first part of this paper, the passivation phase is defined precisely enough to allow a study of its algorithmic properties. In the second part, the weakest precondition and strongest postcondition methods are presented in a unified way and then compared empirically.
Optimizing complex extraction programs over evolving text data
Authors: Fei Chen, Byron J. Gao, AnHai Doan, Jun Yang, Raghu Ramakrishnan
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Most information extraction (IE) approaches have considered only static text corpora, over which we apply IE only once. Many real-world text corpora however are dynamic. They evolve over time, and so to keep extracted information up to date we often must apply IE repeatedly, to consecutive corpus snapshots. Applying IE from scratch to each snapshot can take a lot of time. To avoid doing this, we have recently developed Cyclex, a system that recycles previous IE results to speed up IE over subsequent corpus snapshots. Cyclex clearly demonstrated the promise of the recycling idea. The work itself however is limited in that it considers only IE programs that contain a single IE ``blackbox.'' In practice, many IE programs are far more complex, containing multiple IE blackboxes connected in a compositional ``workflow.'' In this paper, we present Delex, a system that removes the above limitation. First we identify many difficult challenges raised by Delex, including modeling complex IE programs for recycling purposes, implementing the recycling process efficiently, and searching for an optimal execution plan in a vast plan space with different recycling alternatives. Next we describe our solutions to these challenges. Finally, we describe extensive experiments with both rule-based and learning-based IE programs over two real-world data sets, which demonstrate the utility of our approach.
QuestSemantics-Intelligent Search and Retrieval of Business Knowledge
Authors: Ian Blacoe, Ignazio Palmisano, Valentina Tamma, Luigi Iannone
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Keyword-based search engines, though hugely popular, show limitations when trying to answer very specific queries. The processing of search results is performed by users, rather than by software. Ontologies provide a means to create formal, machineprocessable descriptions of the knowledge in a certain domain [14], and, by using elements of these descriptions to annotate suitable information sources, they can be analysed and manipulated in an intelligent manner. The QuestSemantics platform provides automated ontology-based metadata creation and resource annotation, with subsequent ontology-based querying of the annotated resources. The platform has been deployed in two commercial scenarios, providing useful feedback on both the feasibility and effectiveness of applying Semantic Web technologies to specific business problems.
Value-Based Multiple Software Projects Scheduling with Genetic Algorithm
Authors: Junchao Xiao, Qing Wang, Mingshu Li, Qiusong Yang, Lizi Xie, Dapeng Liu
Venue: Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes (2009)

Scheduling human resources to multiple projects under various resource requirements, constraints and value objectives is a key problem that many software organizations struggle with. This paper gives a value-based human resource scheduling method among multiple software projects by using a genetic algorithm. The method synthesizes the constraints such as those of schedule and cost as well as the value objectives among different projects, and also the construction of comprehensive value function for evaluating the results of human resource scheduling. Under the guidance of value function, capable human resources can be scheduled for project activities by using the genetic algorithm and make the near-maximum value for organizations. Case study and the simulation results show that the method can perform the scheduling and reflect the value objectives of different projects effectively, and the results provide a concrete decision support for project managers.