ppxscal/embedding_network huggingface dataset:
Call admission control in computer communication networks
Authors: Daniel C. Lee
Venue:  (2007)

Our research results are in the field of call or connection admission control (CAC) for computer communication networks. They are mainly related to connection-oriented packet switching networks, and address switch-level CAC, and what we call best-effort-friendly CAC and routing of connections with quality-of-service (QoS) requirements. Best-effort-friendly CAC and routing of QoS connections refers to a methodology for protecting low-priority best-effort traffic in a network domain that provides both virtual-circuit routing with bandwidth reservation &ndash; e.g., by Internet multiprotocol label switching (MPLS) &ndash; for QoS traffic and datagram routing for best-effort traffic. We formulate a QoS-virtual-circuit admission control and routing policy that sustains a minimum level of best-effort performance. In response to a QoS connection request, the policy executes a two-stage optimization. The first stage seeks a minimum-net-effective-bandwidth reservation path that satisfies a best-effort protecting constraint; the second stage is a tie-breaking rule, selecting from tied paths one that least disturbs best-effort traffic. Our novel policy implementation efficiently executes both optimization stages simultaneously by a single run of Dijkstra's algorithm. Within a practical operating range, the consideration that our policy gives to best-effort service does not increase the blocking probability for QoS connection requests. Switch-level CAC refers to the CAC that is performed for each link of a candidate path for supporting a QoS connection request. Associated with a link is its finite bandwidth capacity and, typically, an output buffer on the link's upstream switch. Packets are lost when the buffer overflows. We minimize the QoS connection requests' call blocking probability, as subject to a packet loss QoS constraint. For a single class of calls, we use our novel linear programming (LP) formulation, along with a convexity-like property and the complementary slackness condition from LP theory, to analytically prove optimality of a &lsquo;soft-threshold&rsquo; CAC policy. This policy is a threshold policy in terms of the number of calls in progress using the link, with the qualification that the admission decision may be random at the threshold. We present the soft-threshold policy as an explicit algebraic expression of the problem parameters, and show its optimality for general conditions, including general call holding time distributions.
D-eigenvalues of diffusion kurtosis tensors
Authors: Liqun Qi, Yiju Wang, Ed X. Wu
Venue: Journal of Computational and Applied Mathematics (2008)

Diffusion kurtosis imaging (DKI) is a new model in medical engineering, where a diffusion kurtosis (DK) tensor is involved. A DK tensor is a fourth-order three-dimensional fully symmetric tensor. In this paper, we introduce D-eigenvalues for a DK tensor. The largest, the smallest and the average D-eigenvalues of a DK tensor correspond with the largest, the smallest and the average apparent kurtosis coefficients (AKC) of a water molecule in the space, respectively. We present their computational methods and discuss related anisotropy value of AKC.
Neural Model for the Visual Recognition of Goal-Directed Movements
Authors: Falk Fleischer, Antonino Casile, Martin A. Giese
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Mirror neurons in monkey premotor cortex of are active during the motor planning and the visual observation of actions. These neurons have recently received a vast amount of interest in cognitive neuroscience and have been discussed as potential basis of imitation learning and the understanding of actions. We present a model that explains visual properties of mirror neurons without a reconstruction of the three-dimensional structure of action and object. The proposed model is based on a small number of physiologically well-established principles. In addition, it postulates novel neural mechanisms for the integration of information about object and effector movement, which can be tested in electrophysiological experiments.
A Study of SAT-Based Branching Heuristics for the CSP
Authors: Yannis Argyropoulos, Kostas Stergiou
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

Constraint Satisfaction Problems (CSPs) and Propositional Satisfiability (SAT) are two closely related frameworks used for solving hard combinatorial problems. Despite their similarities regarding the problem formulation and the basic backtracking search algorithms they use, several advanced techniques have been developed and standardized in one framework but have been rather ignored in the other. One class of such techniques includes branching heuristics for variable and value ordering. Typically, SAT heuristics are highly sophisticated while CSP ones tend to be simplistic. In this paper we study some well known SAT heuristics with the aim of transferring them to the CSP framework. Through this attempt, new CSP branching techniques are developed; exploiting information not used by most of the standard CSP heuristics. For instance such information can be the arity of the constraints and the supports of values on the constraints. Preliminary empirical results on random problems show that this unexploited information can be used to design new efficient CSP heuristics or to enhance the performance of existing ones, like dom/wdeg.
Detection of Clusters of Microcalcifications in Mammograms: A Multi Classifier Approach
Authors: Ciro D'Elia, Claudio Marrocco, Mario Molinara, Francesco Tortorella
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Mammography is a not invasive diagnostic technique widely used for early cancer detection in women breast. A particularly significant clue of such disease is the presence of clusters of microcalcifications. The automatic detection and classification of such clusters is a very difficult task because of the small size of the microcalcifications and of the poor quality of the digital mammograms. In literature, all the proposed methods for the automatic detection focus on the single microcalcification. In this paper, an approach that moves the final decision on the regions identified by the segmentation in the phase of clustering is proposed. To this aim, the output of a classifier on the single microcalcifications is used as input data in a clustering algorithms which produce the detected clusters. As final output the system highlights the suspicious clusters, leaving to the specialist the diagnosis responsibility. The approach has been successfully tested on a standard database of 40 mammographic images, publicly available.
Rules and Ontologies for the Semantic Web
Authors: Thomas Eiter, Giovambattista Ianni, Thomas Krennwallner, Axel Polleres
Venue: Reasoning Web: 4th International Summer School 2008, Venice, Italy, September 7-11, 2008, Tutorial Lectures (2008)

Rules and ontologies play a key role in the layered architecture of the Semantic Web, as they are used to ascribe meaning to, and to reason about, data on the Web. While the Ontology Layer of the Semantic Web is quite developed, and the Web Ontology Language (OWL) is a W3C recommendation since a couple of years already, the rules layer is far less developed and an active area of research; a number of initiatives and proposals have been made so far, but no standard as been released yet. Many implementations of rule engines are around which deal with Semantic Web data in one or another way. This article gives a comprehensive, although not exhaustive, overview of such systems, describes their supported languages, and sets them in relation with theoretical approaches for combining rules and ontologies as foreseen in the Semantic Web architecture. In the course of this, we identify desired properties and common features of rule languages and evaluate existing systems against their support. Furthermore, we review technical problems underlying the integration of rules and ontologies, and classify representative proposals for theoretical integration approaches into different categories.
On the Performance of Transparent MPI Piggyback Messages
Authors: Martin Schulz, Greg Bronevetsky, Bronis R. Supinski
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

Many tools, including performance analysis tools, tracing libraries and application level checkpointers, add piggyback data to messages. However, transparently implementing this functionality on top of MPI is not trivial and can severely reduce application performance. We study three transparent piggyback implementations on multiple production platforms and demonstrate that all are inefficient for some application scenarios. Overall, our results show that efficient piggyback support requires mechanisms within the MPI implementation and, thus, the interface should be extended to support them.
Decidable Properties of 2D Cellular Automata
Authors: Alberto Dennunzio, Enrico Formenti
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

In this paper we study some decidable properties of two-dimensional cellular automata (2D CA). The notion of closingness is generalized to the 2D case and it is linked to permutivity and openness. The major contributions of this work are two deep constructions which have been fundamental in order to prove our new results and we strongly believe it will be a valuable tool for proving other new ones in the near future.
WiSARD and NSP for Robot Global Localization
Authors: Paolo Coraggio, Massimo Gregorio
Venue: Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II (2007)

In this paper a hybrid approach for solving a robot global localization problem in an office-like environment is presented. The global localization problem deals with the estimation of the robot position when its initial pose is unknown. The core of this system is formed by a virtual sensor, capable of detecting and classifying the corners in the room in which the robot acts, and an NSP (Neuro Symbolic Processor) control that infers and computes the possible robot locations. In this way, the whole global self localization problem is tackled with a hybrid approach: a classic neurosymbolic hybrid system, composed of a weightless neural network and a BDI agent (it processes the map and build the landmark connections), a neural virtual sensor (for detecting landmarks) and a unified neurosymbolic hybrid system (NSP) devoted to the computation of the robot location on the given map.
Specifying Strategies for Exercises
Authors: Bastiaan Heeren, Johan Jeuring, Arthur Leeuwen, Alex Gerdes
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

The feedback given by e-learning tools that support incrementally solving problems in mathematics, logic, physics, etc. is limited, or laborious to specify. In this paper we introduce a language for specifying strategies for solving exercises. This language makes it easier to automatically calculate feedback when users make erroneous steps in a calculation. Although we need the power of a full programming language to specify strategies, we carefully distinguish between context-free and non-context-free sublanguages of our strategy language. This separation is the key to automatically calculating all kinds of desirable feedback.
Processing top-k queries from samples
Authors: Edith Cohen, Nadav Grossaug, Haim Kaplan
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

Top-k queries are desired aggregation operations on datasets. Examples of queries on network data include finding the top 100 source Autonomous Systems (AS), top 100 ports, or top domain names over IP packets or over IP flow records. Since the complete dataset is often not available or not feasible to examine, we are interested in processing top-k queries from samples. If all records can be processed, the top-k items can be obtained by counting the frequency of each item. Even when the full dataset is observed, however, resources are often insufficient for such counting so techniques were developed to overcome this issue. When we can observe only a random sample of the records, an orthogonal complication arises: The top frequencies in the sample are biased estimates of the actual top-k frequencies. This bias depends on the distribution and must be accounted for when seeking the actual value. We address this by designing and evaluating several schemes that derive rigorous confidence bounds for top-k estimates. Simulations on various datasets that include IP flows data, show that schemes exploiting more of the structure of the sample distribution produce much tighter confidence intervals with an order of magnitude fewer samples than simpler schemes that utilize only the sampled top-k frequencies. The simpler schemes, however, are more efficient in terms of computation.
Note: The Independence Number for De Bruijn networks and Kautz networks
Authors: Zhi-Guo Deng, Bao-Gen Xu
Venue: Discrete Applied Mathematics (2008)

Let D be a directed graph; the (l,@w)-Independence Number of graph D, denoted by @a"l","@w(D), is an important performance parameter for interconnection networks. De Bruijn networks and Kautz networks, denoted by B(d,n) and K(d,n) respectively, are versatile and efficient topological structures of interconnection networks. For l=1,2,...,n, this paper shows that @a"l","d"-"1(B(d,n))=d^n,@a"l","d"-"1(K(d,n))=@a"l","d(K(d,n))=d^n+d^n^-^1 if d>=3 and n@?d-2. In particular, the paper shows the exact value of the Independence Number for B(d,1) and B(d,2) for any d. For the generalized situation, the paper obtains a lower bound @a"l","d"-"1(B(d,n))>=d^2 if n>=3 and d>=5.
Total recall: a debugging framework for GPUs
Authors: Ahmad Sharif, Hsien-Hsin S. Lee
Venue: Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware (2008)

GPUs have transformed from simple fixed-function processors to powerful, programmable stream processors and are continuing to evolve. Programming these massively parallel GPUs, however, is very different from programming a sequential CPU. Lack of native support for debugging coupled with the parallelism in the GPU makes program development for the GPU a non-trivial task. As GPU programs grow in complexity because of scaling in maximum allowed program size and increased demand in terms of realism, debugging GPU code is becoming a major timesink for content developers. In addition to more complex shaders, applications are using multi-pass effects in order to create more convincing reality. In this paper, we present a debugging framework that can be employed to debug complex code running on the GPU in an efficient manner. By observing the API calls of the application that are made to the 3D runtime, the framework can keep track of the program's state in memory. Upon the programmer's request, it is able to capture and deterministically replay the stream of instructions that caused the final write to a pixel of interest. This execution stream includes writes to intermediate render targets and spans across shader boundaries. The stream of instructions can then be replayed on the CPU via emulation and the programmer can debug the straight-line code with ease. We also present a hardware-friendly scheme that can be used to accelerate the debugging process for long-chain multi-pass effects.
Internet-based firms entering offline channels: empirical models & analysis
Authors: Dipak C. Jain
Venue:  (2008)

This dissertation consists of three empirical essays on issues related to Internet-based firms entering the offline channel. Issues arising from offline entry include the potential spillovers in online revenue, online customer acquisition, and online customer activity. Over the past decade, there has been considerable research examining brick mortar companies entering the online channel. The maturation of the Internet industry has led to several established online-based firms that have opened physical stores. The first essay of the dissertation investigates the impact of an online e-commerce marketplace provider opening physical stores. The focus is on the spillover effects with respect to online seller revenue, online seller acquisition, and online seller activity. The analysis finds store entry leads to a positive revenue spillover, however store entry cannibalizes new online sellers as well as online seller listings. The positive online revenue spillover may be due to the relative rise in the average selling price of products sold online in regions with store entry. The focus of the second essay is on the role of offline store entry on online consumer purchase behavior; in particular, the spillover effects with respect to online buyer revenue, online buyer acquisition, and online bidding activity. The analysis finds store entry engenders positive online buyer sales and positive online buyer acquisition spillover. The analysis also finds a positive spillover for the average price of products purchased online in regions with store entry. The increase in average sales price for products purchased may be explained by both a change in the assortment of products being purchased and an increase in the price expectation for products sold through the firm. The third essay extends the study of the relationship between the study of product quality and market size to an Internet setting. Additionally, the empirical essay examines the link between firm specialization and market size, as well as product quality, in an Internet setting. The results indicate that similar to other settings, there is a positive relationship between market size and market concentration. However, unlike previous studies, there is an overall negative link between market size and product quality. The analysis also finds that the level of firm specialization diminishes with increases in market size, but there is a positive link between the level of firm specialization and the product quality of firms. The product quality findings of the study may be explained by the partially hidden nature of quality in this setting.
Dynamic data assigning assessment clustering of streaming data
Authors: O. Georgieva, F. Klawonn
Venue: Applied Soft Computing (2008)

Discovering interesting patterns or substructures in data streams is an important challenge in data mining. Clustering algorithms are very often applied to identify single substructures although they are designed to partition a data set. Another problem of clustering algorithms is that most of them are not designed for data streams. This paper discusses a recently introduced procedure that deals with both problems. The procedure explores ideas from cluster analysis, but was designed to identify single clusters without the necessity to partition the whole data set into clusters. The new extended version of the algorithm is an incremental clustering approach applicable to stream data. It identifies new clusters formed by the incoming data and updates the data space partition. Clustering of artificial and real data sets illustrates the abilities of the proposed method.
CACS: A Novel Classification Algorithm Based on Concept Similarity
Authors: Jing Peng, Dong-Qing Yang, Chang-Jie Tang, Jing Zhang, Jian-Jun Hu
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

This paper proposes a novel algorithm of classification based on the similarities among data attributes. This method assumes data attributes of dataset as basic vectors of m dimensions, and each tuple of dataset as a sum vector of all the attribute-vectors. Based on transcendental concept similarity information among attributes, this paper suggests a novel distance algorithm to compute the similarity distance of each pairs of attribute-vectors. In the method, the computing of correlation is turned to attribute-vectors and formulas of their projections on each other, and the correlation among any two tuples of dataset can be worked out by computing these vectors and formulas. Based on the correlation computing method, this paper proposes a novel classification algorithm. Extensive experiments prove the efficiency of the algorithm.
θ-Subsumption Based on Object Context
Authors: Olga Skvortsova
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

We propose a novel method for efficient &theta;-subsumption. Our solution is based on the idea of object context which embody the contextual information in a clause and is given by occurrences of identical objects or chains of such occurrences. Efficient &theta;-subsumption is crucial for AI planning approaches that rely on lifted first-order reasoning. We incorporate our object context-based method for &theta;-subsumption within one approach for lifted first-order planning under uncertainty, referred to as LIFT-UP, and compare it with several related techniques.
Robust Window Detection from 3D Laser Scanner Data
Authors: Haider Ali, Basheer Ahmed, Gerhard Paar
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

In this paper we propose a robust system for window detection using popular descriptive statistics and image based methods, making use of 3D information from a laser scanner. The scanner generates 3D point clouds containing intensity and distance information in a spherical coordinate system, with optional additional RGB texture information. The applied descriptive statistical method exploits basic local features such as mean, variance and standard deviation of the distance measurement data. The laser distance information shows high variability in windows region, due to specular reflections on window screens on one hand, and screen penetration on the other hand. Therefore we determine an adaptive threshold on the basis of local absolute differences of adjacent laser-measured distances in the image formed by the angular coordinate system of the scanner. For window segmentation the image is binarized using the derived threshold, and morphological operations such as closing using adaptive (i.e. distance - dependent) structural elements are performed. After contour analysis the resulting bounding rectangles are used to retrieve the positions and global shapes of windows in the image. The system provides a sufficient windows detection rate for direct application in a deformation measurement system.
Contextual service loading by dependency graph colouring
Authors: Amira Ben Hamida, Frédéric Le Mouël, Stéphane Frénot, Mohamed Ben Ahmed
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

While installing applications on mobiles devices, we may face issues due to the limit of the device resources. In this paper, we propose AxSeL: A conteXtual Service Loader that considers services-oriented applications and loads them from a distant repository. Services dependencies are represented in a graph that is coloured considering the devices and services constraints. The graph colouring aims to take services loading decisions.