ppxscal/embedding_network huggingface dataset:
Collective intelligence for demand-responsive transportation systems: a self organization model
Authors: Besma Zeddini, Adnan Yassine, Moncef Temani, Khaled Ghédira
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

Today's public transportation systems are subject to many requirements that are difficult to reconcile. They are deterministic and based on frequencies and routes that are set in advance. In this paper, we propose a self-organization model in order to carry out a global adaptability that is able to maintain a good dispatching of the fleet of vehicles in a purely dynamic Demand-Responsive Transportation Systems. Our proposal consists on a decentralized approach and a multi-agent system to model the environment. The behaviour of the proposed system is derived from a collective arrangement of the various individual activities, enabling vehicles agents, with respect to a given demand, to calculate the overcosts via an offer protocol and following an insertion heuristic.
Resolution Enhancement of PMD Range Maps
Authors: A. N. Rajagopalan, Arnav Bhavsar, Frank Wallhoff, Gerhard Rigoll
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

Photonic mixer device (PMD) range cameras are becoming popular as an alternative to algorithmic 3D reconstruction but their main drawbacks are low-resolution (LR) and noise. Recently, some interesting works have stressed on resolution enhancement of PMD range data. These works use high-resolution (HR) CCD images or stereo pairs. But such a system requires complex setup and camera calibration. In contrast, we propose a super-resolution method through induced camera motion to create a HR range image from multiple LR range images. We follow a Bayesian framework by modeling the original HR range as a Markov random field (MRF). To handle discontinuities, we propose the use of an edge-adaptive MRF prior. Since such a prior renders the energy function non-convex, we minimize it by graduated non-convexity.
The Combinatorics of Differentiation
Authors: Anna S. Bertiger, Robert J. Mceliece, Sarah Sweatlock
Venue: Proceedings of the 5th international conference on Sequences and Their Applications (2008)

Let S 1, S 2, ... be a sequence of finite sets, and suppose we are asked to find the sequence of cardinalities s[1], s[2], .... We are usually satisfied to find a closed-form expression for the a-generating function $F_S(z) = \sum_{n \geq 0} s[n]a[n] { z^n}$, where a[n] is a fixed positive causal sequence. But extracting s[n] from F S (z) is often itself a challenging problem, because of the unnavoidable link to calculus $s[n] ={a[n] \over n!} D^n[F(z)]_{z=0}$. In this paper we will consider the case a[n] = 1/n!, (exponential generating functions), and find many links between combinatorics and calculus.
The CrocodileAgent: A Software Agent for SCM Procurement Gaming
Authors: Tvrtko Milicic, Vedran Podobnik, Ana Petric, Gordan Jezic
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

The Trading Agent Competition (TAC) is an international forum which promotes high-quality research regarding the trading agent problem. One of the TAC competitive scenarios is Supply Chain Management Procurement Challenge (SCM-PC) where three agents compete by buying components, assembling PCs from these components and selling the manufactured PCs to customers. The idea of SCM-PC is the development of agent-based systems that implement efficient business strategies, with special emphasis on the procurement processes. In this paper, we analyze the SCM-PC environment and describe the main features of the CrocodileAgent, our entry in the SCM-PC Competition.
A reactive behavioural model for context-aware semantic devices
Authors: Jose Luis Roman
Venue:  (2007)

Our environment is being populated by an increasing number of digital devices. Even traditional objects are being substituted by their electronic versions, demanding more skills from users.The amount of intelligence in these devices does not match the pace at which they are being disseminated through our lives. This situation leads to interaction problems with the environment, since the user is the sole responsible for contextualising the information and solving cooperation problems between devices; that is, the user is the intelligence provider. One of the major consequences of this situation is that people are continuously disturbed and required to configure, operate and interact with these devices.We deem that digital objects shall be more intelligent, autonomous, and able to share, interpret and reason upon exchanged information to release users from part of these activities.In this thesis, we propose a model for knowledge sharing between devices and for representing their behaviour in a way that promotes autonomous context-aware reactivity. In our approach, we bring Semantic Web technologies to the Ubiquitous Computing world in order to provide the means for collaboratively transforming data into knowledge and enabling intelligent reasoning mechanisms.The model leads to a decentralised architecture where devices spontaneously discover each other, share context information, perform reasoning and adapt their behaviour dynamically in order to create a feel for Ambient Intelligence in the environment. In order to validate our approach we have identified some evaluation criteria and developed a number of prototypes that were deployed in experimental scenarios. The results of our research may contribute to pave the way for a new wave of social digital objects that we denominate semantic devices.
Feature Extraction from Sensor Data Streams for Real-Time Human Behaviour Recognition
Authors: Julia Hunter, Martin Colley
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

In this paper we illustrate the potential of motion behaviour analysis in assessing the wellbeing of unsupervised, vulnerable individuals. By learning the routine motion behaviour of the subject (i.e. places visited, routes taken between places) we show it is possible to detect unusual behaviours while they are happening. This requires the processing of continuous sensor data streams, and real-time recognition of the subject's behaviour. To address privacy concerns, analysis will be performed locally to the subject on a small computing device. Current data mining techniques were not developed for restricted computing environments, nor for the demands of real-time behaviour recognition. In this paper we present a novel, online technique for discretizing a sensor data stream that supports both unsupervised learning of human motion behaviours and real-time recognition. We performed experiments using GPS data and compared the results of Dynamic Time Warping.
Meta-assemblers
Authors: E. Skordalakis
Venue: IEEE Micro (1983)

Meta-assemblers automate the construction of assemblers. The availability of microcomputers spurred the development of meta-assemblers, and many now exist. They are described and classified here. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
The Pleasure Principle
Authors: Robert R. Hoffman, Patrick J. Hayes
Venue: IEEE Intelligent Systems (2004)

Unfortunately, computers do not always provide an unmixed increase in pleasure. Recent evidence suggests, contrary to what one might hope or suppose, that the computerization of the modern workplace has actually led to declines in productivity. Negative impacts are likely due, at least in part, to systems' user-unfriendliness and outright user hostility: Rapid change in software, incompatibility of various hardware and software systems, poor software and interface design, weak documentation and help support, and so on. Many computer systems require the devotion of effort to create work-arounds and kludges. All such features make both individual workers and teams of workers feel less effective, and perceived self-efficacy is a critical facto in job satisfaction, motivation, and morale. Human-centered systems must leverage the intrinsic motivation of domain practitioners, especially that intrinsic motivation that is definitive of expertise. The authors discuss several examples, including the Next-Generation Weather Radar system.
Realizing an MDA and SOA Marriage for the Development of Mobile Services
Authors: Mariano Belaunde, Paolo Falcarin
Venue: Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications (2008)

The paper presents an approach for developing composite tele-communication services running on mobile phones which takes advantage of the use of model driven techniques as well as the loose coupling paradigm in SOA. A domain-specific UML dialect named SPATEL has been developed which serves as the basis for generating applications that can be deployed in distinct terminals and servers technologies. The composite services typically combines telecommunication enablers - like SMS sending and GSM locali-sation - with traditional IT components accessible over the internet, such as a Yellow Page facility. This work has been conducted in the context of the IST SPICE European collaborative project.
An Improved Fusion Design of Audio-Gesture for Multi-modal HCI Based on Web and WPS
Authors: Jung-Hyun Kim, Kwang-Seok Hong
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

This paper introduces improved fission rule depending on SNNR (Signal Plus Noise to Noise Ratio) and fuzzy value for simultaneous multi-modality, and suggests the Fusion User Interface (hereinafter, FUI) including a synchronization between audio-gesture modalities, based on the embedded KSSL (Korean Standard Sign Language) recognizer using the WPS (Wearable Personal Station for the next generation PC) and Voice-XML. Our approach fuses and recognizes 62 sentential and 152 word language models that are represented by speech and KSSL, then translates recognition results that is fissioned according to a weight decision rule into synthetic speech and visual illustration (graphical display by HMD-Head Mounted Display) in real-time. The experimental results, average recognition rates of the FUI for 62 sentential and 152 word language models were 94.33% and 96.85% in clean environments (e.g. office space), and 92.29% and 92.91% were shown in noisy environments.
Dependency by Concentration of Pheromone Trail for Multiple Robots
Authors: Ryusuke Fujisawa, Shigeto Dobata, Daisuke Kubota, Hikaru Imamura, Fumitoshi Matsuno
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

In this paper, we discuss the concentration dependency of pheromone communication in swarm robotics. Instead of a pheromone trail and the insect antenna, we used ethanol and an alcohol sensor. This experimental system has a trade-off problem; high concentrations of the pheromone yield high signal strength but the signal duration is short, while low pheromone concentrations yield low signal strength but a long signal duration. We examined the optimal pheromone concentration for a swarm of robots. For this purpose, we developed a swarm behaviour algorithm and swarm robots that communicate using a pheromone trail. In addition, we discuss the effects of the pheromone concentration.
Mapping Properties of Heterogeneous Ontologies
Authors: Chiara Ghidini, Luciano Serafini
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

In recent papers, we have proposed an extension of the formalism of Distributed Description Logic (DDL) to represent a wide set of homogeneous and heterogeneous mappings involving relations and concepts. Here we investigate in depth how to provide an effective reasoning algorithm for reasoning within this logic in the case of homogeneous mappings.
Protein Structure Prediction with Large Neighborhood Constraint Programming Search
Authors: Ivan Dotu, Manuel Cebrián, Pascal Hentenryck, Peter Clote
Venue: Proceedings of the 14th international conference on Principles and Practice of Constraint Programming (2008)

Protein structure predictions is regarded as a highly challenging problem both for the biology and for the computational communities. Many approaches have been developed in the recent years, moving to increasingly complex lattice models or even off-lattice models. This paper presents a Large Neighborhood Search (LNS) to find the native state for the Hydrophobic-Polar (HP) model on the Face Centered Cubic (FCC) lattice or, in other words, a self- avoiding walk on the FCC lattice having a maximum number of H-H contacts. The algorithm starts with a tabu-search algorithm, whose solution is then improved by a combination of constraint programming and LNS. This hybrid algorithm improves earlier approaches in the literature over several well-known instances and demonstrates the potential of constraint-programming approaches for ab initio methods.
On determinism versus nondeterminism for restarting automata
Authors: Hartmut Messerschmidt, Friedrich Otto
Venue: Information and Computation (2008)

A restarting automaton processes a given word by executing a sequence of local simplifications until a simple word is obtained that the automaton then accepts. Such a computation is expressed as a sequence of cycles. A nondeterministic restarting automaton M is called correctness preserving, if, for each cycle u@?"M^cv, the string v belongs to the characteristic language L"C(M) of M, if the string u does. Our first result states that for each type of restarting automaton X@?{R,RW,RWW,RL,RLW,RLWW}, if M is a nondeterministic X-automaton that is correctness preserving, then there exists a deterministic X-automaton M"1 such that the characteristic languages L"C(M"1) and L"C(M) coincide. When a restarting automaton M executes a cycle that transforms a string from the language L"C(M) into a string not belonging to L"C(M), then this can be interpreted as an error of M. By counting the number of cycles it may take M to detect this error, we obtain a measure for the influence that errors have on computations. Accordingly, this measure is called error detection distance. It turns out, however, that an X-automaton with bounded error detection distance is equivalent to a correctness preserving X-automaton, and therewith to a deterministic X-automaton. This means that nondeterminism increases the expressive power of X-automata only in combination with an unbounded error detection distance.
Harmonic-Wavelet and Approximate-Entropy Extracted Weak Noise
Authors: Wanqing Song, Yan Yue
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The objective of this paper is to introduce Newland Harmonic wavelets and Pincus (1991) approximate entropy are applied to extract weak cycle jumps. Because some weak vibration signals contained strong noises are very important for fault forecast. Based on harmonic wavelet mesh plot of the vibration signals, we can induce contours of the mesh map with log space, then, we offer the time-frequency profile plot from the mesh map. This time-frequency profile plot is corresponding to decompose level on harmonic wavelets. Final, by computing approximately entropy in each level time-frequency profile plot, the weak cycle signal can be easily extracted from strong noise.
Discriminative Structure Learning of Markov Logic Networks
Authors: Marenglen Biba, Stefano Ferilli, Floriana Esposito
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

Markov Logic Networks (MLNs) combine Markov networks and first-order logic by attaching weights to first-order formulas and viewing these as templates for features of Markov networks. Learning the structure of MLNs is performed by state-of-the-art methods by maximizing the likelihood of a relational database. This can lead to suboptimal results given prediction tasks. On the other hand better results in prediction problems have been achieved by discriminative learning of MLNs weights given a certain structure. In this paper we propose an algorithm for learning the structure of MLNs discriminatively by maximimizing the conditional likelihood of the query predicates instead of the joint likelihood of all predicates. The algorithm chooses the structures by maximizing conditional likelihood and sets the parameters by maximum likelihood. Experiments in two real-world domains show that the proposed algorithm improves over the state-of-the-art discriminative weight learning algorithm for MLNs in terms of conditional likelihood. We also compare the proposed algorithm with the state-of-the-art generative structure learning algorithm for MLNs and confirm the results in [22] showing that for small datasets the generative algorithm is competitive, while for larger datasets the discriminative algorithm outperfoms the generative one.
Theoretical Study on the Capacity of Associative Memory with Multiple Reference Points
Authors: Enrique Mérida-Casermeiro, Domingo López-Rodríguez, Gloria Galán-Marín, Juan M. Ortiz-De-Lazcano-Lobato
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

An extension to Hopfield's model of associative memory is studied in the present work. In particular, this paper is focused in giving solutions to the two main problems present in the model: the apparition of spurious patterns in the learning phase (implying the well-known and undesirable effect of storing the opposite pattern) and the problem of its reduced capacity (the probability of error in the retrieving phase increases as the number of stored patterns grows). In this work, a method to avoid spurious patterns is presented and studied, and an explanation to the previously mentioned effect is given. Another novel technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network is provided. This formula shows the linear dependence of the capacity of the new model on the number of reference points, implying the increase of the capacity in this model.
A Framework for Model Checking Institutions
Authors: Francesco Viganò
Venue: Model Checking and Artificial Intelligence: 4th Workshop, MoChArt IV, Riva del Garda, Italy, August 29, 2006, Revised Selected and Invited Papers (2007)

To increase positive expectations in the outcome of open multiagent systems, institutions have been put forward to regulate agents' behaviour. To model and to verify such institutions, we propose to adopt the notion of status function, which provides for a unified approach to ontological and deontic aspects regulated by an institution. Also, to enhance the development of functional and rational institutions, we propose a language amenable to model checking to describe them and their properties. Finally, we present our tool and an evaluation of our approach.
Ranking Automata and Games for Prioritized Requirements
Authors: Rajeev Alur, Aditya Kanade, Gera Weiss
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

Requirements of reactive systems are usually specified by classifying system executions as desirable and undesirable. To specify prioritized requirements, we propose to associate a rank with each execution. This leads to optimization analogs of verification and synthesis problems in which we compute the "best" requirement that can be satisfied or enforced from a given state. The classical definitions of acceptance criteria for automata can be generalized to ranking conditions. In particular, given a mapping of states to colors, the Büchi ranking condition maps an execution to the highest color visited infinitely often by the execution, and the cyclic ranking condition with cycle k maps an execution to the modulo-k value of the highest color repeating infinitely often. The well-studied parity acceptance condition is a special case of cyclic ranking with cycle 2, and we show that the cyclic ranking condition can specify all ¿-regular ranking functions. We show that the classical characterizations of acceptance conditions by fixpoints over sets generalize to characterizations of ranking conditions by fixpoints over an appropriately chosen lattice of coloring functions. This immediately leads to symbolic algorithms for solving verification and synthesis problems. Furthermore, the precise complexity of a decision problem for ranking conditions is no more than the corresponding acceptance version, and in particular, we show how to solve Büchi ranking games in quadratic time.
S-SimRank: Combining Content and Link Information to Cluster Papers Effectively and Efficiently
Authors: Yuanzhe Cai, Pei Li, Hongyan Liu, Jun He, Xiaoyong Du
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Both Content analysis and link analysis have its advantages in measuring relationships among documents. In this paper, we propose a new method to combine these two methods to compute the similarity of research papers so that we can do clustering of these papers more accurately. In order to improve the efficiency of similarity calculation, we develop a strategy to deal with the relationship graph separately without affecting the accuracy. We also design an approach to assign different weights to different links to the papers, which can enhance the accuracy of similarity calculation. The experimental results conducted on ACM Data Set show that our new algorithm, S-SimRank, outperforms other algorithms.
Enabling high resolution collaborative visualization in display rich virtual organizations
Authors: Luc Renambot, Byungil Jeong, Hyejung Hur, Andrew Johnson, Jason Leigh
Venue: Future Generation Computer Systems (2009)

We predict that high-resolution displays will penetrate scientific laboratories first, and will become pervasive at the office, in the cubicle, and meeting room, and ultimately at home. In this paper, we present a novel approach to distribute high-resolution images to multiple tiled displays in real-time using a high-performance PC cluster. This approach allows users to share their visualization applications and videos on multiple tiled displays, repositioning and resizing each application window independently. These operations require high-resolution image multicasting from a rendering cluster to multiple display clusters. A high-performance bridging system called SAGE Bridge performs the image multicasting on a high-performance PC cluster. We show in several experiments that this system enables sharing of high-resolution scientific animations and high-definition videos (with audio) between multiples international sites, hence creating virtual research laboratories (i.e. virtual organizations), as observed in a figure given in this article.