ppxscal/embedding_network huggingface dataset:
Using Selectional Restrictions to Query an OWL Ontology
Authors: Leila Kosseim, Reda Siblini, Christopher J. O. Baker, Sabine Bergler
Venue: Proceeding of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006) (2006)

This paper discusses the linguistic module of an Ontology Natural Language Interaction System that is based on semantic restrictions. The system, called ONLI, takes as input questions in unrestricted natural language, translates them into nRQL, an extension to the RACER ontology query language, then generates answers as returned by the RACER ontology reasoning server. Translation into nRQL is done through a syntactic analysis (with Minipar), followed by the use of semantic restrictions imposed by the roles stored in the ontology to map terms in the question to concepts and roles in the ontology. The system was evaluated on the FungalWeb ontology using the mean reciprocal rank (MRR) measure used in question-answering. With a test set of 36 questions, the systems achieved an MRR of 0.72.
Ontology-Based Service Discovery Front-End Interface for GloServ
Authors: Knarig Arabshian, Christian Dickmann, Henning Schulzrinne
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

This paper describes an ontology-based service discovery front-end interface for GloServ. GloServ is a service discovery engine, which is an ontology-based distributed service discovery system that allows sophisticated querying of services. The working implementation of the front-end interface demonstrates how GloServ can be used for different types of web service discovery. The front-end generates a search form from the service class ontology. It also allows multiple services to be queried for in a single search by generating cascaded forms for combined service queries. It then converts the input to a GloServ query and displays the results to the user in a coherent manner. The use cases that are demonstrated with this implementation are service discovery for location-based services, tagged services and collaborative search with other users.
Annotated Semantics for Nonmonotonic Reasonings in Artificial Intelligence II
Authors: Kazumi Nakamatsu, Atsuyuki Suzuki
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

In this paper, we introduce the annotated semantics for Reiter's default theory. We propose a syntactical translation from the Reiter's default theory into ALPSN(Annotated Logic Program with Strong Negation), and show that the translation preserves their provability and satisfiability, that is to say, if a formula in the default theory is provable then the translated a-clause is also provable in the corresponding ALPSN. We clarify this relation by showing that there is a one-to-one correspondence between the default extension classes of the original default theory and the stable classes of the translated ALPSN.
3D Shape Recovery of Smooth Surfaces: Dropping the Fixed-Viewpoint Assumption
Authors: Yael Moses, Ilan Shimshoni
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

We present a new method for recovering the 3D shape of a featureless smooth surface from three or more calibrated images illuminated by different light sources (three of them are independent). This method is unique in its ability to handle images taken from unconstrained perspective viewpoints and unconstrained illumination directions. The correspondence between such images is hard to compute and no other known method can handle this problem locally from a small number of images. Our method combines geometric and photometric information in order to recover dense correspondence between the images and accurately computes the 3D shape. Only a single pass starting at one point and local computation are used. This is in contrast to methods that use the occluding contours recovered from many images to initialize and constrain an optimization process. The output of our method can be used to initialize such processes. In the special case of fixed viewpoint, the proposed method becomes a new perspective photometric stereo algorithm. Nevertheless, the introduction of the multiview setup, self-occlusions, and regions close to the occluding boundaries are better handled, and the method is more robust to noise than photometric stereo. Experimental results are presented for simulated and real images.
Unified framework for developing testing effort dependent software reliability growth models
Authors: P. K. Kapur, Omar Shatnawi, Anu G. Aggarwal, Ravi Kumar
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

Several software reliability growth models (SRGMs) have been presented in the literature in the last three decades. These SRGMs take into account different testing environment depending on size and efficiency of testing team, type of components and faults, design of test cases, software architecture etc. The plethora of models makes the model selection an uphill task. Recently, some authors have tried to develop a unifying approach so as to capture different growth curves, thus easing the model selection process. The work in this area done so far relates the fault removal process to the testing/execution time and does not consider the consumption pattern of testing resources such as CPU time, manpower and number of executed test cases. More realistic modeling techniques can result if the reliability growth process is studied with respect to the amount of expended testing efforts. In this paper, we propose a unified framework for testing effort dependent software reliability growth models incorporating imperfect debugging and error generation. The proposed framework represents the realistic case of time delays between the different stages of fault removal process i.e Failure Observation/Fault Detection and Fault Removal/Correction processes. The Convolution of probability distribution functions have been used to characterize time differentiation between these two processes. Several existing and new effort dependent models have been derived by using different types of distribution functions. We have also provided data analysis based on the actual software failure data sets for some of the models discussed and proposed in the paper.
Cascading dynamics on complex networks
Authors: Byungnam Kahng
Venue: Proceedings of the 4th International Conference on Future Internet Technologies (2009)

Frequently, complex systems in nature as well as in human society suffer massive catastrophes triggered from only a small fraction of their constituents. Unexpected epidemic spread of diseases, the power outage, and the congestion of packet transport in the Internet are prototypical examples of such avalanche phenomena. Such a cascading dynamics is not always harmful to us. The information cascades making popular hits of books, movies, and albums are good to writers, actors, and singers, respectively. Thus, it is interesting to understand and predict how those cascades propagate in complex systems. Recently, the network approach, by which a system is viewed as a network consisting of nodes representing its constituents and links interactions between them, simplifies complicated details of complex systems. In my talk, I present how cascading dynamics in complex systems can be modeled on complex networks. In many cases, cascading dynamics spreads along the path that is a tree. When the network is scale-free in the degree distribution, the tree can be a critical branching tree. In this case, the avalanche dynamics can be understood the multiplicative branching process. Using this method, we can set up the self-consistent equation for the avalanche size distribution, which behaves in a power law fashion. This method can be modified to study the fad propagation problem. it is important to choose a triggering node. Such theoretical results are confirmed by numerical simulations. I will introduce a recent model to prevent such a cascading dynamics on the complex network. For the problem of packet congestions, we study the transition between the free-flow to congested state as the number of packets increases. At the transition point, there exists a synchronized phase, in which the traffic flow changes in jammed or relaxed state, alternatively. In this case, the congested nodes (routers) can spread out over the entire systems, and recover to the normal state, alternatively. The congested area can fluctuate over time. As a result, the power spectrum of the traffic amount on the network exhibits 1/f-type behavior.
Exact rotamer optimization for computational protein design
Authors: Tomas Lozano-Perez
Venue:  (2008)

The search for the global minimum energy conformation (GMEC) of protein side chains is an important computational challenge in protein structure prediction and design. Using rotamer models, the problem is formulated as a NP-hard optimization problem. Dead-end elimination (DEE) methods combined with systematic A* search (DEE/A*) have proven useful, but may not be strong enough as we attempt to solve protein design problems where a large number of similar rotamers is eligible and the network of interactions between residues is dense. In this thesis, we present an exact solution method, named BroMAP (branch-and-bound rotamer optimization using MAP estimation), for such protein design problems. The design goal of BroMAP is to be able to expand smaller search trees than conventional branch-and-bound methods while performing only a moderate amount of computation in each node, thereby reducing the total running time. To achieve that, BroMAP attempts reduction of the problem size within each node through DEE and elimination by energy lower bounds from approximate maximum-a-posteriori (MAP) estimation. The lower bounds are also exploited in branching and subproblem selection for fast discovery of strong upper bounds. Our computational results show that BroMAP tends to be faster than DEE/A* for large protein design cases. BroMAP also solved cases that were not solvable by DEE/A* within the maximum allowed time, and did not incur significant disadvantage for cases where DEE/A* performed well. In the second part of the thesis, we explore several ways of improving the energy lower bounds by using Lagrangian relaxation. Through computational experiments, solving the dual problem derived from cyclic subgraphs, such as triplets, is shown to produce stronger lower bounds than using the tree-reweighted max-product algorithm. In the second approach, the Lagrangian relaxation is tightened through addition of violated valid inequalities. Finally, we suggest a way of computing individual lower bounds using the dual method. The preliminary results from evaluating BroMAP employing the dual bounds suggest that the use of the strengthened bounds does not in general improve the running time of BroMAP due to the longer running time of the dual method. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Law as a seamless web?: comparison of various network representations of the United States Supreme Court corpus (1791-2005)
Authors: Michael J. Bommarito,  II, Daniel Katz, Jon Zelner
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

In this paper, we compare several network representations of the corpus of United States Supreme Court decisions (1791--2005). This corpus is not only of seminal importance, but also represents a highly structured and largely self-contained body of case law. As constructed herein, nodes represent whole cases or individual "opinion units" within cases. Edges represent either citations or semantic connections. As our broader goal is to better understand American common law development, we are particularly interested in the union, intersect and compliment of these various citation networks as they offer potential insight into the time developing structure of the "web of the law."
Legal safeguards for privacy and data protection in ambient intelligence
Authors: Paul Hert, Serge Gutwirth, Anna Moscibroda, David Wright, Gloria González Fuster
Venue: Personal and Ubiquitous Computing (2009)

To get the maximum benefit from ambient intelligence (AmI), we need to anticipate and react to possible drawbacks and threats emerging from the new technologies in order to devise appropriate safeguards. The SWAMI project took a precautionary approach in its exploration of the privacy risks in AmI and sought ways to reduce them. It constructed four "dark scenarios" showing possible negative implications of AmI, notably for privacy protection. Legal analysis of the depicted futures showed the shortcomings of the current legal framework in being able to provide adequate privacy protection in the AmI environment. In this paper, the authors, building upon their involvement in SWAMI research as well as the further advancement of EU privacy analysis, identify various outstanding issues regarding the legal framework that still need to be resolved in order to deal with AmI in an equitable and efficacious way. This article points out some of the lacunae in the legal framework and postulates several privacy-specific safeguards aimed at overcoming them.
Hydroxyapatite powder used for rapid prototyping in medical engineering
Authors: Alexander Ott, Franz Irlinger
Venue: International Journal of Computer Applications in Technology (2009)

A key requirement in the field of bone tissue engineering is the development of scaffold structures on which cells adhere. This can be done by fabricating scaffolds by direct procedures like Three-Dimensional (3D) printing or by indirect procedures like casting. With the 3D-printing process, different structures were built up using HydroxyApatite (HA) powder and a special binder material. Afterwards the printed 3D structures were sintered. For the casting process, moulds have been made of different resins by stereolithography and other processes using polymers and waxes. These structures were filled by a suspension of HA. The casting process yielded a better resolution than 3D printing, but exhibited restrictions with respect to the degree of porosity.
VARIAC: an Autogenous Cognitive Architecture
Authors: J. Storrs Hall
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

Learning theory and programs to date are inductively bounded: they can be described as “wind-up toys” which can only learn the kinds of things that their designers envisioned. We conjecture [1] that general intelligence involves an unbounded learning ability. VARIAC is an experimental cognitive architecture designed to learn by modifying and extending itself, including its ability to learn, so that it can learn to become a better learner.
QuOnt: an ontology for the reuse of quality criteria
Authors: Remco C. de Boer, Hans van Vliet
Venue: Proceedings of the 2009 ICSE Workshop on Sharing and Reusing Architectural Knowledge (2009)

Software product audits are knowledge-intensive tasks in which architectural knowledge plays a pivotal role. In the input stage of a software product audit, quality criteria are selected to which the software product should conform. These quality criteria resemble architectural tactics and can be viewed as a definition of the Soll-architecture of the product. Like tactics, the same quality criteria can be applied to different software products. However, there are currently no models that support the codification of quality criteria as reusable assets. In this work, we present an ontology that supports the reuse of quality criteria in the input stage of software product audits.
Channel assignment with partially overlapping channels in wireless mesh networks
Authors: Yong Ding, Yi Huang, Guokai Zeng, Li Xiao
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Many efforts have been devoted to maximizing the network throughput with limited channel resources in multi-radio multi-channel wireless mesh networks. It has been believed that the limited spectrum resource can be fully exploited by utilizing partially overlapping channels in addition to non-overlapping channels in 802.11b/g networks. However, there are only few studies of channel assignment algorithms for partially overlapping channels. In this paper, an extension to the traditional conflict graph model, weighted conflict graph, is proposed to model the interference between wireless links more accurately. Based on this model, we first present a greedy algorithm for partially overlapping channel assignment, and then propose a novel genetic algorithm, which has the potential to obtain better solutions. Through evaluation, we demonstrate that the network performance can be dramatically improved by properly utilizing the partially overlapping channels. In addition, the genetic algorithm outperforms the greedy algorithm in mitigating the interference within the network and therefore leads to higher network throughput.
SOM-based data analysis of speculative attacks' real effects
Authors: Ismael E. Arciniegas Rueda, Fabio A. Arciniegas
Venue: Intelligent Data Analysis (2009)

In some cases, currency crises are followed by strong recessions (e.g., recent Asian and Argentinean crises), but in other cases they are not. This paper uses Self-Organizing Maps (SOM) to search for meaningful associations between speculative attacks' real effects and 28 variables that characterize the economic, financial, legal, and socio-political structure of the country at the onset of the attack. SOM is a neural network-based generalization of Principal Component Analysis (PCA) that provides an efficient non-linear projection of the multidimensional data space on a curved surface. This paper finds a strong association of speculative attacks` real effects with fundamentals and the banking sector structure.
Kode ViciousKode reviews 101
Authors: George V. Neville-Neil
Venue: Communications of the ACM (2009)

A review of code review do's and don'ts.
Visualising and Interpreting Group Behavior through Social Networks
Authors: Kwang Deok Kim, Liaquat Hossain
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

In this study, we visualise and interpret the relationships between different types of social network (SN) structures (i.e., degree centrality, cut-points) and group behavior using political contribution dataset. We seek to identify whether investment behavior is network dependent using the political contribution dataset. By applying social networks analysis as a visualisation and interpretation technique, we find patterns of social network structures from the dataset, which explains the political contribution behavior (i.e., investment behavior) of political action committee (PAC). The following questions guide this study: Is there a correlation between SN structure and group behavior? Do we see patterns of different network structures for different types and categories of political contribution (i.e., support or oppose; level of contribution)? Is there a structural difference of networks between different types of support and oppose behavior? Do the group networks for support and oppose differ structurally on the basis of different types of political contribution patterns?
Intelligent Safety Verification for Pipeline Based on EVALPSN
Authors: Kazumi Nakamatsu, Kenji Kawasumi, Atsuyuki Suzuki
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

We have developed an annotated logic program called an Extended Vector Annotated Logic Program with Strong Negation(abbr. EVALPSN), which can deal with defeasible deontic reasoning and contradiction. We have already applied EVALPSN to safety verification and control such as railway interlocking safety verification. In this paper, we show pipeline valve safety verification to avoid liquid mixture accidents with a simple example for brewery pipeline control.
The heuristic methods of obtaining the effective measurement in diagnostic systems
Authors: V. N. Vagin, P. V. Oskin
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

The problem of finding the best current measurement point in model-based device diagnostics with assumption-based truth maintenance systems is viewed. The new heuristic approaches of current measurement point choosing on the basis of supporting and inconsistent environments are presented.
An Extension of the Internal Rate of Return to Stochastic Cash Flows
Authors: Gordon Hazen
Venue: Management Science (2009)

The internal rate of return (IRR) is a venerable technique for evaluating deterministic cash flow streams. Part of the difficulty in extending this measure to stochastic cash flows is the lack of coherent methods for accounting for multiple or nonexistent internal rates of return in deterministic streams. Recently such a coherent theory has been developed, and we examine its implications for stochastic cash flows. We devise an extension of the deterministic IRR, which we call the stochastic rate of return on mean investment. It has significant computational and conceptual advantages over the stochastic internal rate. For instance, in the deterministic case, the standard result is that under proper conditions a cash flow stream is acceptable (in the sense of positive present value) if its internal rate exceeds the interest rate. We show that a stochastic cash flow stream is acceptable (in the sense of positive certainty equivalent expected value) if the rate of return on mean investment has a suitably defined certainty equivalent exceeding the risk-free interest rate.
Elasticity with Mathematica: An Introduction to Continuum Mechanics and Linear Elasticity, 1st edition
Authors: Andrei Constantinescu, Alexander Korsunsky
Venue:  (2007)

This book is intended for researchers, engineers and students in solid mechanics, materials science and physics who are interested in using the power of modern computing to solve a wide variety of problems of both practical and fundamental significance in elasticity. Extensive use of Mathematica in the book makes available to the reader a range of recipes that can be readily adjusted to match particular tastes or requirements, to visualize solutions, and to carry out symbolic and numerical analysis and optimization.
Ranking distributed probabilistic data
Authors: Feifei Li, Ke Yi, Jeffrey Jestes
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where uncertainty and fuzzy information arise, data are collected from multiple sources in distributed, networked locations, e.g., distributed sensor fields with imprecise measurements, multiple scientific institutes with inconsistency in their scientific data. Due to the network delay and the economic cost associated with communicating large amounts of data over a network, a fundamental problem in these scenarios is to retrieve the global top-k tuples from all distributed sites with minimum communication cost. Using the well founded notion of the expected rank of each tuple across all possible worlds as the basis of ranking, this work designs both communication- and computation-efficient algorithms for retrieving the top-k tuples with the smallest ranks from distributed sites. Extensive experiments using both synthetic and real data sets confirm the efficiency and superiority of our algorithms over the straightforward approach of forwarding all data to the server.