ppxscal/embedding_network huggingface dataset:
Computing inversion pair cardinality through partition-based sorting
Authors: K. Subramani
Venue: Computing (2008)

In this paper, we introduce a new randomized, partition-based algorithm for the problem of computing the number of inversion pairs in an unsorted array of n numbers. The algorithm runs in expected time O(n &#x00b7; log n) and uses O(n) extra space. The expected time analysis of the new algorithm is different from the analyses existing in the literature, in that it explicitly uses inversion pairs. The problem of determining the inversion pair cardinality of an array finds applications in a number of design domains, including but not limited to real-time scheduling and operations research. At the heart of our algorithm is a new inversion pair conserving partition procedure that is different from existing partition procedures such as Hoare-partition and Lomuto-partition. Although the algorithm is not fully adaptive, we believe that it is the first step towards the design of an adaptive, partition-based sorting algorithm whose running time is proportional to the number of inversion pairs in the input.
Brief paper: Optimal cycle production of a manufacturing system subject to deterioration
Authors: Francesco Martinelli, Fabio Piedimonte
Venue: Automatica (Journal of IFAC) (2008)

A single part type, single machine, fluid model manufacturing system is considered. The machine is subject to a deterministic deterioration process, which depends on the operation rate. The objective is to minimize a long term average cost index which penalizes inventory surplus and backlog. The optimal policy determined presents some similarities with the policy conjectured optimal in the past for a similar Markovian formulation. The considered problem can be applied to several real contexts, and not just from the manufacturing domain, as briefly discussed in the paper.
Spatially Distributed Normative Objects
Authors: Fabio Y. Okuyama, Rafael H. Bordini, Antônio Carlos Rocha Costa
Venue: Coordination, Organizations, Institutions, and Norms in Agent Systems II: AAMAS 2006 and ECAI 2006 International Workshops, COIN 2006 Hakodate, Japan, May 9, 2006 Riva del Garda, Italy, August 28, 2006. Revised Selected Papers (2007)

Organisational structures for multi-agent systems are usually defined independently of any spatial or temporal structure. Therefore, when the multi-agent system is situated in a spatial environment, there is usually a conceptual gap between the definition of the system's organisational structures and the definition of the environment. In this paper, we focus on a mechanism for the spatial distribution of an organization's normative information. Spatially distributing the normative information over the environment is a natural way to simplify the definition of organisational structures and the development of large-scale multi-agent systems. By distributing the normative information in different spatial locations, we allow agents to directly access the relevant information needed in each environmental context. We extend our previous work on a language for modelling multi-agent environments in order to allow for the definition of spatially distributed norms in the form of normative objects.
On a Generalization of the Master Cyclic Group Polyhedron
Authors: Sanjeeb Dash, Ricardo Fukasawa, Oktay Günlük
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

We study the Master Equality Polyhedron (MEP) which generalizes the Master Cyclic Group Polyhedron and the Master Knapsack Polyhedron.We present an explicit characterization of the nontrivial facet-defining inequalities for MEP. This result generalizes similar results for the Master Cyclic Group Polyhedron by Gomory [9] and for the Master Knapsack Polyhedron by Araoz [1]. Furthermore, this characterization also gives a polynomial time algorithm for separating an arbitrary point from the MEP.We describe how facet defining inequalities for the Master Cyclic Group Polyhedron can be lifted to obtain facet defining inequalities for the MEP, and also present facet defining inequalities for the MEP that cannot be obtained in such a way. Finally, we study the mixed-integer extension of the MEP and present an interpolation theorem that produces valid inequalities for general Mixed Integer Programming Problems using facets of the MEP.
FindSUMO: A PSSM-Based Method for Sumoylation Site Prediction
Authors: Christopher J. Friedline, Xueping Zhang, Zendra E. Zehner, Zhongming Zhao
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Post-translation modification by sumoylation is an important step in the regulation of many cellular processes. Existing programs predict sumoylation sites based on a consensus motif ( φ-K-X-E/D. However, ~23% of real SUMO sites do not match this motif, which makes prediction of sumoylation sites complicated. Here, we present a new method, FindSUMO, which predicts sumoylation sites using a position-specific scoring matrix. The comparison of FindSUMO with other two programs (SUMOsp and SUMOplot) indicates that FindSUMO accurately predicts sumoylation sites out of fewer total candidates and, in many cases, real sites with the highest scores. Overall, FindSUMO has at least the same performance as the other methods. While many improvements are expected, FindSUMO can also be applied to predict sumoylation sites that do not follow the consensus motif.
How to Define 3D Geoprocessing Operations for the OGC Web Processing Service (WPS)? Towards a Classification of 3D Operations
Authors: Rüdiger Göbel, Alexander Zipf
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

In the literature a number of taxonomies are present which categorize the functions of GIS. While such taxonomies used to be more of scientific interest they are now getting more practical relevance due to the adoption of the OGC Web Processing Service (WPS) specification. While this standard currently allows specifying arbitrary geoprocessing functionalities, for ensuring interoperability we argue that more detailed definition of possible functions with their parameters is needed. This would facilitate the development of specific application profiles of the WPS if needed. Further classifications of geoprocessing services would help to identify appropriate functions to be grouped together at a higher level (this could be handled in extended web service registries). The goal of this paper is to start a discussion about appropriate concepts of 2.5D (2D with one additional z-value per x-, y-coordinate) and 3D geoprocessing functions and the different ways to group them --- in particular we need to distinguish generic and domain-specific functions. This can lead to the definition of relevant WPS profiles. We propose a general classification for 2.5D and 3D functions which contains groups of general purpose functions. This classification leads to sub-classifications that contain several basic functions for each group of the general classification. In addition to these generic functions we further propose domain specific classifications that contain the most important 2.5D and 3D functions for a specific application area, especially functions that are used only within this field. These domain specific classifications will give access to many important functions of a domain. Therefore this paper gives an overview of the state of art, i.e. existing taxonomies of GIS-functions and discusses a new classification for 2.5D and 3D geoprocessing functions as well as domain specific classifications.
Design of Quadruped Robot Based Neural Network
Authors: Lei Sun, Max Q. Meng, Wanming Chen, Huawei Liang, Tao Mei
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The paper proposed a method for a quadruped robot control system based Central Pattern Generator (CPG) and fuzzy neural networks (FNN). The common approach for the control of a quadruped robot includes two methods mainly. One is the CPG that is based the bionics, the other is the dynamic control that is based the model of quadruped robot. The control result of CPG is decided by the gait data of the quadruped and the parameters of the CPG are choosing manually. Modeling a quadruped robot is difficult because it is a high nonlinear system. This paper presents a much simpler method for the control of a quadruped robot. A simple CPG is adopted for a timing oscillator; it generates the motion periodic pattern of legs. The FNN is used to control the joint motion in order to get a desired stable trajectory motion.
A Novel Global Hybrid Algorithm for Feedforward Neural Networks
Authors: Hongru Li, Hailong Li, Yina Du
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A novel global optimization hybrid algorithm was presented for training neural networks in this paper. During the course of neural networks training, when the weights are being adjusted with Quasi-Newton(QN) method, the error function may be stuck in a local minimum. In order to solve this problem, a original Filled-Function was created and proved. It was combined with QN method to become a global optimization hybrid algorithm. When the net is trained with our new hybrid algorithm, if error function was tripped in a local minimal point, the new hybrid algorithm was able to help networks out of the local minimal point. After that, the weights could being adjusted until the global minimal point for weights vector was found. One illustrative example is used to demonstrate the effectiveness of the presented scheme.
A Fully Automatic Approach to Facial Feature Tracking Based on Image Registration
Authors: Xuetao Feng, Yangsheng Wang, Bin Ding, Xiaoyan Wang
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

This paper presents a real time, fully automatic facial feature detection and tracking approach. The head pose and facial action is tracked by a modified Candide 3D wireframe model based on an improved image registration technique. An effective model shape and position initialization method is also proposed. Experimental results demonstrate that our system is accurate, robust and fast enough for common applications, even when there are great pose and expression variations.
RST-Based RBF Neural Network Modeling for Nonlinear System
Authors: Tengfei Zhang, Jianmei Xiao, Xihuai Wang, Fumin Ma
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Due to its structural simplicity and good properties, radial basis function (RBF) neural network has increasingly been used in many areas for the solution of difficult real-world problems, especially the nonlinear system dynamic modeling. However, the major problem toward using RBF network is the appropriate selection of radial basis function parameters. The basis function parameters are in general the centers and the widths. Our attention in this paper is focused on the configuring the optimal set of parameters to make the networks small and efficient based on rough set theory (RST), which is a valid mathematical tool to perform data reduction. RST is first applied to extract the underlying rules from data. The condition components of the rules are then mapped into network centers. For improve performance, the width parameter of each hidden neuron is initialized individual. The valid of this algorithm is illustrated by an example on the modeling of a ship synchronous generator.
How are we doing?
Authors: Moshe Y. Vardi
Venue: Communications of the ACM (2009)

A rabbinical story tells about an angry reader who stormed into a newspaper office waving the day's paper, asking to see the editor of the obituary column.
Automatic Decidability and Combinability Revisited
Authors: Christopher Lynch, Duc-Khanh Tran
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

We present an inference system for clauses with ordering constraints, called Schematic Paramodulation. Then we show how to use Schematic Paramodulation to reason about decidability and stable infiniteness of finitely presented theories. We establish a close connection between the two properties: if Schematic Paramodulation for a theory halts then the theory is decidable; and if, in addition, Schematic Paramodulation does not derive the trivial equality X = Y then the theory is stably infinite. Decidability and stable infiniteness of component theories are conditions required for the Nelson-Oppen combination method. Schematic Paramodulation is loosely based on Lynch-Morawska's meta-saturation but it differs in several ways. First, it uses ordering constraints instead of constant constraints. Second, inferences into constrained variables are possible in Schematic Paramodulation. Finally, Schematic Paramodulation uses a special deletion rule to deal with theories for which Lynch-Morawska's meta-saturation does not halt.
Visibly Pushdown Languages and Term Rewriting
Authors: Jacques Chabin, Pierre Réty
Venue: Proceedings of the 6th international symposium on Frontiers of Combining Systems (2007)

To combine tree languages with term rewriting, we introduce a new class of tree languages, that both extends regular languages and restricts context-free languages, and that is closed under intersection (unlike context-free languages). To do it, we combine the concept of visibly pushdown language, with top-down pushdown tree automata, and we get the visibly pushdown tree automata. Then, we use them to express the sets of descendants for a sub-class of growing term rewrite systems, and thanks to closure under intersection, we get that joinability and (restricted) unifiability are decidable.
Using DEA and Grey Markovian Model to Measure the Goal Cost of Petroleum Enterprise
Authors: Jin-Lan Liu, Meng-Dong Wang, Yin Bai
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

With the longstanding development of Chinese petroleum enterprises, the control of discovery and exploitation goal cost is becoming a essential problem. Data Envelopment Analysis (DEA) is a linear programming method for measuring the relative efficiency of decision making units where the presence of multiple inputs and outputs makes comparisons difficult. Grey Markovian model has the merits of both grey model and Markov transition probability matrix model. In this paper, DEA and Grey Markovian model are combined to measure the discovery and exploitation goal cost of petroleum enterprise. This method is applied to the cost analysis of Huabei Oil Company of PetroChina, which gives strong support to the feasibility and availability of the study in this paper.
Distributed Production Scheduling Using Federated Agent Architecture
Authors: Jayeola Femi Opadiji, Toshiya Kaihara
Venue: Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2007)

Making a production system readily reconfigurable in a bid to adapt to very fluid demand profile is pertinent to cost reduction and facility utilization objectives of the system. We consider a production scheduling methodology based on federated agent architecture designed for a flexible job shop with dynamic demand. The interaction protocol within the social network is based on a facilitated auction mechanism. This model employs competition at job centers to maximize financial returns and uses cooperation among facilitator agents to minimize weighted tardiness.
Monotone DNF Formula That Has a Minimal or Maximal Number of Satisfying Assignments
Authors: Takayuki Sato, Kazuyuki Amano, Eiji Takimoto, Akira Maruoka
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

We consider the following extremal problem: Given three natural numbers n, m and l, what is the monotone DNF formula that has a minimal or maximal number of satisfying assignments over all monotone DNF formulas on n variables with m terms each of length l? We first show that the solution to the minimization problem can be obtained by the Kruskal-Katona theorem developed in extremal set theory. We also give a simple procedure that outputs an optimal formula for the more general problem that allows the lengths of terms to be mixed. We then show that the solution to the maximization problem can be obtained using the result of Bollobás on the number of complete subgraphs when l = 2 and the pair (n,m) satisfies a certain condition. Moreover, we give the complete solution to the problem for the case l = 2 and m ≤ n, which cannot be solved by direct application of Bollobás's result. For example, when n = m, an optimal formula is represented by a graph consisting of $\lfloor{n/3}\rfloor-1$ copies of C 3 and one $C_{3+(n \mbox{\scriptsize \ mod\ } 3)}$, where C k denotes a cycle of length k.
Towards practical intrusion tolerant systems: a blueprint
Authors: Wenbing Zhao
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

In this paper, we present the blueprint of a novel middleware infrastructure that can be used to build mission-critical systems with increased resiliency against intrusion attacks. The infrastructure is designed to be practical and it imposes a well-defined structure on the application by adhering the principle of the separation of concerns: (1) the processing of each application request is carried out at a single execution node, and if the execution node becomes faulty, another node can take over immediately; (2) the state of the server is replicated transparently across a pool of state replicas, and a novel append-only strategy is used so that not only the state is protected against hardware failures, it is resilient to attacks aimed to cause state corruption and destruction; (3) the fault monitoring, execution and state integrity checking, and system configuration management are carried out by distinct components which by themselves are replicated.
Distance Measures for Gabor Jets-Based Face Authentication: A Comparative Evaluation
Authors: Daniel González-Jiménez, Manuele Bicego, J. W. Tangelder, B. A. Schouten, Onkar Ambekar, José Luis Alba-Castro, Enrico Grosso, Massimo Tistarelli
Venue: Proceedings of the international conference on Advances in Biometrics (2007)

Local Gabor features (jets) have been widely used in face recognition systems. Once the sets of jets have been extracted from the two faces to be compared, a proper measure of similarity (or distance) between corresponding features should be chosen. For instance, in the well known Elastic Bunch Graph Matching (EBGM) approach and other Gabor-based face recognition systems, the cosine distance was used as a measure. In this paper, we provide an empirical evaluation of seven distance measures for comparison, using a recently introduced face recognition system, based on Shape Driven Gabor Jets (SDGJ). Moreover we evaluate different normalization factors that are used to pre-process the jets. Experimental results on the BANCA database suggest that the concrete type of normalization applied to jets is a critical factor, and that some combinations of normalization + distance achieve better performance than the classical cosine measure for jet comparison.
A Learning Automata Approach to Multi-agent Policy Gradient Learning
Authors: Maarten Peeters, Ville Könönen, Katja Verbeeck, Ann Nowé
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

The policy gradient method is a popular technique for implementing reinforcement learning in an agent system. One of the reasons is that a policy gradient learner has a simple design and strong theoretical properties in single-agent domains. Previously, Williams showed that the REINFORCE algorithm is a special case of policy gradient learning. He also showed that a learning automaton could be seen as a special case of the REINFORCE algorithm. Learning automata theory guarantees that a group of automata will converge to a stable equilibrium in team games. In this paper we will show a theoretical connection between learning automata and policy gradient methods to transfer this theoretical result to multi-agent policy gradient learning. An appropriate exploration technique is crucial for the convergence of a multi-agent system. Since learning automata are guaranteed to converge, they posses such an exploration. We identify the identical mapping of a learning automaton onto the Boltzmann exploration strategy with an suitable temperature setting. The novel idea is that the temperature of the Boltzmann function is not dependent on time but on the action probabilities of the agents.
Flexible Feature Processing Mechanism of Radar Target Signal
Authors: Jing Zhang, Wenxian Yu, Jicai Wei
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

Extracting effective and reliable features is fundamental and critical for constructing target recognition systems. Flexible Feature Processing Mechanism emphasizes the integration of feature extraction arithmetic and the self-adaptation of feature selection. On one hand, it would try to dig up the valuable information on as many as possible aspects, so as to construct the feature extraction method sets. On the other hand, it emphasizes to select the distinct features and eliminate the redundant features. The series of feature processing methods have been applied in multiple radar recognition projects successfully. According to the observation and analysis on a large number of real-life data, and taking the thinking process and the description methods of radar operators for reference, a set of feature extraction and selection methods basing on visual effects for dynamic radar target echo series have been introduced. The effectiveness, robustness and extendibility have been proved by large amount of tests and applications.
Options in Readylog Reloaded --- Generating Decision-Theoretic Plan Libraries in Golog
Authors: Lutz Böhnstedt, Alexander Ferrein, Gerhard Lakemeyer
Venue: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence (2007)

Readylog is a logic-based agent programming language and combines many important features from other Golog dialects. One of the features of Readylog is to make use of decision-theoretic planning for specifying the behavior of an agent or robot. In this paper we show a method to reduce the planning time for decision-theoretic planning in the Readylog framework. Instead of planning policies on the fly over and over again, we calculate an abstract policy once and store it in a plan library. This policy can later be re-instantiated. With this plan library the on-line planning time can be significantly reduced. We compare computing policies on the fly with those stored in our plan library with examples from the robotic soccer domain. In the 2D soccer simulation league we show the significant speed-up when using our plan library approach. Moreover, the use of the plan library together with a suitable state space abstraction for the soccer domain makes it possible to apply macro-actions in an otherwise continuous domain.